Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data

Abstract. This paper integrates decision tree–based data mining (DM) and object-based image analysis (OBIA) to provide a transferable model for the detailed characterization of urban land-cover classes using WorldView-2 (WV-2) satellite images. Many articles have been published on OBIA in recent years based on DM for different applications. However, less attention has been paid to the generation of a transferable model for characterizing detailed urban land cover features. Three subsets of WV-2 images were used in this paper to generate transferable OBIA rule-sets. Many features were explored by using a DM algorithm, which created the classification rules as a decision tree (DT) structure from the first study area. The developed DT algorithm was applied to object-based classifications in the first study area. After this process, we validated the capability and transferability of the classification rules into second and third subsets. Detailed ground truth samples were collected to assess the classification results. The first, second, and third study areas achieved 88%, 85%, and 85% overall accuracies, respectively. Results from the investigation indicate that DM was an efficient method to provide the optimal and transferable classification rules for OBIA, which accelerates the rule-sets creation stage in the OBIA classification domain.
A New Method to Prepare Stable Polyaniline Dispersions for Highly Loaded Cathodes of All-Polymer Li-Ion Batteries

A new method for the preparation of polyaniline (PANI) films that have a 2D structure and can record high active mass loading (up to 30 mg cm−2) via acid-assisted polymerization in the presence of concentrated formic acid was developed. This new approach represents a simple reaction pathway that proceeds quickly at room temperature in quantitative isolated yield with the absence of any byproducts and leads to the formation of a stable suspension that can be stored for a prolonged time without sedimentation. The observed stability was explained by two factors: (a) the small size of the obtained rod-like particles (50 nm) and (b) the change of the surface of colloidal PANI particles to a positively charged form by protonation with concentrated formic acid. The films cast from the concentrated suspension were composed of amorphous PANI chains assembled into 2D structures with nanofibrillar morphology. Such PANI films demonstrated fast and efficient diffusion of the ions in liquid electrolyte and showed a pair of revisable oxidation and reduction peaks in cyclic voltammetry. Furthermore, owing to the high mass loading, specific morphology, and porosity, the synthesized polyaniline film was impregnated by a single-ion conducting polyelectrolyte-poly(LiMn-r-PEGMm) and characterized as a novel lightweight all-polymeric cathode material for solid-state Li batteries by cyclic voltammetry and electrochemical impedance spectroscopy techniques.
Ubiquitous Earthquake Dynamic Triggering in Southern California

Earthquakes can be dynamically triggered by the passing waves of other distant events. The frequent occurrence of dynamic triggering offers tangible hope in revealing earthquake nucleation processes. However, the physical mechanisms behind earthquake dynamic triggering have remained unclear, and contributions of competing hypotheses are challenging to isolate with individual case studies. To gain a systematic understanding of the spatiotemporal patterns of dynamic triggering, we investigate the phenomenon in southern California from 2008 to 2017. We use the Quake Template Matching catalog and an approach that does not assume an earthquake occurrence distribution. We develop a new set of statistics to examine the significance of seismicity‐rate changes as well as moment‐release changes. Our results show that up to 70% of 1,388 global M ≥ 6 events may have triggered earthquakes in southern California. The triggered seismicity often occurred several hours after the passing seismic waves. The Salton Sea Geothermal Field, San Jacinto fault, and Coso Geothermal Field are particularly prone to triggering. Although adjacent fault segments can be triggered by the same earthquakes, the majority of triggered earthquakes seem to be uncorrelated, suggesting that the process is primarily governed by local conditions. Further, the occurrence of dynamic triggering does not seem to correlate with ground motion (e.g., peak ground velocity) at the triggered sites. These observations indicate that nonlinear processes may have primarily regulated the dynamic triggering cases.
PUBLIC POLICY APPROACH TO DISASTER RISK ANTICIPATION STRATEGIES IN CIVIL ENGINEERING STUDIES IN INDONESIA

This study described a public policy approach to anticipate the impact of natural disasters in Indonesia's civil engineering context. Many studies have reported how public policy approaches anticipate and manage disaster risk strategies. However, few relate to the role of civil engineering, especially the younger generation involved in designing policies and playing their role in natural disaster management. This study has reviewed 50 disaster papers that we analyzed with a phenomenological approach to understanding the role and approach of public policy in dealing with disaster hazards and risks. Our Monalisa system involves data coding, in-depth evaluation, and impotence of data to get the most answers. After a series of studies and discussions, we can conclude that the disaster management policy was originally a policy designed by the state and then directed to the National Disaster Management Agency following presidential regulations so that the law was made an effort to cope with disasters and be responsible to the state. The relationship between civil engineering is that they participate in policy and impact analysis studies closely related to public and private development. We hope that these findings will become an essential friend for further studies.
UPO Biobank: The Challenge of Integrating Biobanking into the Academic Environment to Support Translational Research

Biobanks are driving motors of precision and personalized medicine by providing high-quality biological material/data through the standardization and harmonization of their collection, preservation, and distribution. UPO Biobank was established in 2020 as an institutional, disease, and population biobank within the University of Piemonte Orientale (UPO) for the promotion and support of high-quality, multidisciplinary studies. UPO Biobank collaborates with UPO researchers, sustaining academic translational research, and supports the Novara Cohort Study, a longitudinal cohort study involving the population in the Novara area that will collect data and biological specimens that will be available for epidemiological, public health, and biological studies on aging. UPO Biobank has been developed by implementing the quality standards for the field and the ethical and legal issues and normative about privacy protection, data collection, and sharing. As a member of the “Biobanking and Biomolecular Resources Research Infrastructure” (BBMRI) network, UPO Biobank aims to expand its activity worldwide and launch cooperation with new national and international partners and researchers. The objective of this manuscript is to report an institutional and operational experience through the description of the technical and procedural solutions and ethical and scientific implications associated with the establishment of this university research biobank.
Markov Moment Problem and Related Approximation

The present review article contains recently published results on Markov moment problem and related approximation. The main idea is to apply theorems concerning solutions of the abstract moment problem and approximation theory to the classical moment problem on unbounded subsets of R n . We approximate some nonnegative functions of several variables by sums of tensor products of positive polynomials in each separate variables, which for the analytic expression in terms of sums of squares is known. Thus, one obtains characterizations of the solutions of multidimensional moment problem in terms of quadratic forms, similarly to the one-dimensional case. On the other hand, the case of multiplicative operator-solution is discussed in the end.
THE EFFECT OF TRANSFER PRICING, INTANGIBLE ASSETS AND CAPITAL INTENSITY ON TAX AGGRESIVENESS WITH FOREIGN OWNERSHIP AS A MODERATING VARIABLE

For the government, taxes are a source of state revenue. However, for companies, taxes are considered a burden that can reduce their profits. This difference can potentially cause non-compliance by taxpayers and has implications for corporate efforts to carry out tax aggressiveness. This study determines the effect of transfer pricing, intangible assets, and capital intensity on tax aggressiveness with foreign ownership as a moderating variable. This study uses data from manufacturing companies listed on the Indonesia Stock Exchange (IDX) in a sample of 36 companies with 108 observations during the 2018-2020 period. The results show that both transfer price and intangible assets positively affect tax aggressiveness, while capital intensity does not affect tax aggressiveness. Foreign ownership was found to strengthen the effect of transfer prices and intangible assets on tax aggressiveness. Furthermore, foreign ownership does not strengthen the effect of capital intensity on tax aggressiveness. Keywords: transfer price, intangible assets, capital intensity, foreign ownership, tax aggressiveness
Pest Detection and Classification in Peanut Crops Using CNN, MFO, and EViTA Algorithms

The growth of vision transformer (ViT) methods have been quite enormous since its features provide efficient outcome in image classification, and identification. Inspired of this beneficial, this paper propose an Enhanced vision transformer architecture (EViTA) model for pest identification, segmentation, and classification. The as of late found that, compare to machine learning, Convolutional neural network algorithms the ViT has providing trusted results on image classification. Motivated by this, in this paper, we concentrate on the best way to learn dual barch segment representations in ViT models for image arrangement. Based upon its features, here propose a double layer transformer encoder to integrate pest image segments of various sizes of pest images to create more grounded image highlights. The current study uses, three pest datasets that affects peanut crops such as Aphids (IP102 Dataset), Wireworm (IP102 Dataset), and Gram Caterpillar collected from public available repository. Our methodology processes small segment and huge segment of tokens with two separate parts of various computational intricacy also, these tokens are then combined simply by consideration numerous times to complete one another. The taken datasets’ are preprocessed utilizing the characteristic by using moth flame optimization (MFO), and flatten the images by using linear projector methodology to enhance the missing quality in pest images, and afterward normalization methods are executed to switch it over completely in to mathematical arrangement. This processed information is standardized further utilizing the self attention in StandardScaler procedures are carried out for choosing the ideal highlights in the dataset accordingly having huge effect towards affecting pest image predictions. These ideal highlights are at last taken care of into the EViTA model and the outcomes created are considered in contrast to the cutting edge models which at last legitimize the predominance of the proposed EViTA+PCA+MFO model in pest image prediction with high accuracy rate. Broad trials show that our methodology performs better compared to or on standard with a few simultaneous deals with vision transformer, notwithstanding productive CNN models.
The Growing Importance of the Practical Application of Corporate Social Responsibility in the Management of Companies in the Czech Republic

The paper is aimed at researching the issue of Corporate Social Responsibility (hereinafter “CSR”) in the Czech Republic (hereinafter “CR”). Social responsibility is now an integral part of integrated business management. It has a long tradition in the Czech Republic, because one of the most prominent businessmen of the 20th century – a Czech entrepreneur, Tomas Bata began to apply CSR in his plants around the world in the first half of the last century. Currently, the issue of CSR becomes increasingly important. There is an integration of positive attitudes, practices or programs into company’s business strategy at the top management level. We follow a shift in management focus from the level of “profit only” to a wider view in the context of the three P’s people planet profit. This involves the functioning of the organization with regard to the so called triple bottom line, when the company focuses not only on economic growth, but also on environmental and social aspects of its activities. The main objective of the paper is to analyze the current state of CSR in the Czech Republic on the basis of quantitative research (approx. 100 organizations were approached) and compare it with an analysis from 2004. The conclusion summarizes the approaches of managers to the issue of CSR in the CR, including some trends.
Notes on the oberst beam test technique

The definition of the mechanical properties of viscoelastic materials, i.e. the elastic modulus and the loss factor, is carried out, according to many national and international standards, with many different techniques, both of the resonant and non-resonant type. In this paper we focus our attention on the pros and cons of the resonant technique based on the classical Oberst beam method. When the damping material to be tested is not self-supporting, its properties are determined taking start from the measured modal frequencies and loss factors of a laminated beam, constituted by one or two metallic strips, ideally undamped, and one or two viscoelastic layers. The formulae specified on the standards hold valid under the assumptions of the theory developed by Kerwin, Ungar and Ross and we try in this paper to quantify witch deviation of the results should be expected when moving away from their ideal hypotheses.
Improving the English Speaking Ability of Sixth Grade Thai Students Using the Role-play Technique

Speaking is one of the fundamental abilities that students should develop. In fact, the students are struggling in speaking English due to several factors such as fear of making grammatical errors, lack of confidence or limited vocabulary knowledge which led to low motivation to practice their speaking skills. The aims of this study were to investigate how the role-play technique improves the students’ speaking abilities and to explore students’ opinions towards the use of role-play techniques. This study employed pre-experimental research with a target group using a pre-test, post-test, and a questionnaire. The participants in the study were selected by employing a purposive random sampling method, which consisted of 24 sixth grade students from Ban Namon school, Kalasin province during the first semester of the academic year 2022. The findings of the study were analyzed using SPSS to calculate the t-test score, mean and standard deviation. The research results revealed a great improvement from the pre-test to post-test from 9.38 to 14.79. It showed that role-plays can help students gain more confidence as well as being able to speak more fluently in public. It was found that they were motivated by the fun atmosphere in the classroom. Moreover, role-plays can be an alternative technique for teaching speaking because students gain a direct experience of using the expressions they have learned in different situations.
The Geometry of Iterated Loop Spaces

i Preface This it the first of a series of papers devoted to the study of iterated loop spaces. Our goal is to develop a simple coherent theory which encompasses most of the known results about such spaces. We begin with some history and a description of the desiderata of such a theory. First of all, we require a recognition principle for n-fold loop spaces. That is, we wish to specify appropriate internal structure such that a space X possesses such structure if and only if X is of the (weak) homotopy type of an n-fold loop space. For the case n = 1, Stasheff's notion [28] of an A ∞ space is such a recognition principle. Beck [5] has given an elegant proof of a recognition principle, but, in practice, his recognition principle appears to be unverifiable for a space that is not given a priori as an n-fold loop space. In the case n = ∞, a very convenient recognition principle is given by Boardman and Vogt's notion [8] of a homotopy everything space, and, in [7], Boardman has stated a similar recognition principle for n < ∞. We shall prove a recognition principle for n < ∞ in section 13 (it will first be stated in section 1) and for n = ∞ in section 14; the latter result agrees (up to language) with that of Boardman and Vogt, but our proof is completely different. By generalizing the methods of Beck, we are able to obtain immediate non-iterative constructions of classifying spaces of all orders. Our proof also yields very precise consistency and naturality statements. In particular, a connected space X which satisfies our recognition principle (say for n = ∞) is not only weakly homotopy equivalent to an infinite loop space B 0 X, where spaces B i X with B i X = ΩB i+1 X are explicitly constructed, but also the given internal structure on X agrees under this equivalence with the internal structure on B 0 X derived from the existence of the spaces B i X. We shall have various other consistency statements and our subsequent papers will show that these statements help to make the recognition principle not merely a statement as to the existence of certain cohomology theories, but, far more important, an extremely effective tool for the calculation of the homology of the representing spaces. An alternative recognition principle …
Record of Crambionella annandalei Rao, 1931 from Bangladesh, with a review of the geographic distribution of the genus Crambionella (Cnidaria: Scyphozoa)

ABSTRACT Geographic ranges of some members of the genus Crambionella are not clarified so far. In the context of C. annandalei Rao, 1931, which has been reported only from India and Myanmar, herein we document the first record of this species from the coastal waters of Bangladesh, Bay of Bengal, providing a detailed account of characters, morphometric measurements and illustrations. A comparison of morphological features of C. annandalei from different geographic locations and its congeners is presented, including notes on its fishery value. A cautious review on the occurrence of Crambionella species within the Indian Ocean suggests that geographic distributions of each species are constrained within certain areas around their type localities. Thus, C. annandalei, C. helmbiru, C. orsini and C. stuhlmanni occur in the north-east, south-east, north-west and south-west regions of the Indian Ocean, respectively, without or with a minimum overlapping of each other. All four species occur during both summer and winter seasons of the Indian Ocean.
New attribute reduction algorithm of incomplete decision table of information quantity

At present,there is few researchers have investigated attribute reduction based on incomplete decision table.Incomplete decision table of attribute reduction based on information quantity is a new issue.In this kind of attribute reduction,computation of tolerance relation of the incomplete decision table is the main computation.At the same time,it is more difficult than computing equivalent relation of complete decision table.The time complexity of the existed algorithms of attribute reduction based on information quantity is almost O(|C|3 |U|2). To lower the time complexity,this paper first analyzes the shortcoming of those algorithms.And also provids an efficient algorithm for computing the tolerance class.Then using the above algorithm,this paper designs an efficient algorithm of attribute reduction based on information quantity.Its time complexity is O(|C|2|U|2).
THE INFLUENCE OF PROFITABILITY, CAPITAL STRUCTURE, INVESTMENT DECISION, AND FIRM SIZE ON FIRM VALUE (A Study in the Pharmaceutical Sector Listed on the Indonesian Stock Exchange)

This study examines the influence of profitability, capital structure, investment decisions, and firm size on firm value in pharmaceutical sub-sector companies on the Indonesia Stock Exchange. This study uses secondary data from the financial statements of each pharmaceutical sub-sector company. The sample in this study consists of 9 pharmaceutical sub-sector companies listed on the Indonesia Stock Exchange during 2018-2021. The data analysis method used is a multiple linear regression test with the help of Eviews 12. The results partially show that return on assets, return on equity, and capital structure has a positive and significant effect on firm value. Meanwhile, investment decisions and firm size partially do not significantly affect firm value in pharmaceutical sub-sector companies listed on the Indonesia Stock Exchange for the 2018-2021 period.
A Modified Bond-Associated Non-Ordinary State-Based Peridynamic Model for Impact Problems of Quasi-Brittle Materials

In this work, we have developed a novel bond-associated non-ordinary state-based peridynamic (BA-NOSB PD) model for the numerical modeling and prediction of the impact response and fracture damage of quasi-brittle materials. First, the improved Johnson-Holmquist (JH2) constitutive relationship is implemented in the framework of BA-NOSB PD theory to describe the nonlinear material response, which also helps to eliminate the zero-energy mode. Afterwards, the volumetric strain in the equation of state is redefined by the introduction of the bond-associated deformation gradient, which can effectively improve the stability and accuracy of the material model. Then, a new general bond-breaking criterion is proposed in the BA-NOSB PD model, which is capable of covering various failure modes of quasi-brittle materials, including the tensile-shear failure that is not commonly considered in the literature. Subsequently, a practical bond-breaking strategy and its computational implementation are presented and discussed by means of energy convergence. Finally, the proposed model is verified by two benchmark numerical examples and demonstrated by the numerical simulation of edge-on impact and normal impact experiments on ceramics. The comparison between our results and references shows good capability and stability for impact problems of quasi-brittle materials. Numerical oscillations and unphysical deformation modes are effectively eliminated, showing strong robustness and bright prospects for relevant applications.