Miracle-dz/UniFAR-FTUs huggingface dataset:
Indicators of Sustainable Entrepreneurial Ecosystems

The purpose of this paper is to develop a system of indicators for assessing the effectiveness of entrepreneurial ecosystems based on platform solutions. These indicators can further be used as a mechanism for tracking the ongoing transformations in business environment. Scientific publications, normative legal acts, and analytical materials of Russian, foreign and international organizations served as a methodological basis of the research. The proposed principles of forming a system of indicators take into account the possibility of achieving the objectives of the entrepreneurial ecosystem and increasing the value created within the ecosystem.
Controlador Difuso Para Gestión De La Energía En Un Proceso De Transición De Central De Generación Térmica A Renovables

El presente artículo considera un escenario de transición a fuentes energía renovable no convencional (ERNC) de tecnología mixta, compuesta por generación solar fotovoltaica y micro generación eólica, tomando en cuenta un evento paulatino de descarbonización. Como caso de estudio se va considerar la central termoeléctrica Dayuma (2MW), ubicada en la provincia de Orellana, Ecuador. Inicialmente para su desarrollo se evaluó los recursos naturales energéticos de la zona, tales como, temperatura, irradiancia, velocidad de viento en sus puntos máximos, mínimos y promedio, en un intervalo de tiempo de cinco años. Posteriormente para la óptima gestión de la producción energética se utilizó controladores basados en lógica difusa, para el seguimiento del punto de máxima potencia (MPPT), y se ha comparado este controlador con un P&O convencional. Finalmente se llevó a cabo los cálculos correspondientes para determinar la cantidad de paneles de alta eficiencia necesarios y se comparó con otros de baja, de igual forma se estableció el número de micro-generadores eólicos y el área física necesaria para la implementación de la central propuesta en cada uno de los casos, obteniendo resultados importantes para la posibilidad de la sustitución de la central termoeléctrica existente. Con esta investigación se busca estimar la máxima generación posible mediante la obtención del punto de máxima transferencia de potencia basado en un control lógico difuso y con esto definir la posibilidad de suplantar la central térmica ya mencionada.
Application of Type-1 Fuzzy Terminal and Fast Terminal Sliding Mode Controllers for tracking the Stewart Manipulator

In this paper, Finite-time control design of the Stewart mechanism is performed using the Type-1 Fuzzy terminal and Type-1 Fuzzy fast terminal sliding mode controllers. Manipulator has six hydraulic jacks or linear actuators and top plate has six degrees of freedom. Fuzzy boundary layer and fuzzy sliding surface are defined for the controllers to decrease the chattering and oscillation of the actuators. The dynamic equations are derived using the Lagrange method by applying the uncertainties and the super-twisting observer is developed to estimate the velocity of the hydraulic jacks. For eliminating undesirable chattering phenomena using the fuzzy logic, a set of type-1 fuzzy rules is used in such a way that approximates the boundary layer of the sliding surface. Moreover for better performance tracking of the controllers, the parameters of the terminal and fast terminal sliding mode controllers are optimized using the genetic algorithm. Integral of absolute error was defined as objective function. Simulations present the good performance of the fuzzy controllers in tracking the desired path of the top plate, high robustness in the presence uncertainty and reduction of noisy sensors.
Preparation and Applications of Nanocomposite Membranes for Water/Wastewater Treatment

Because of scarcity of clean water all over the globe, it is leads to serious challenges to the survival of all living species. Advanced treatment of water/wastewater techniques such as filtration separation and ion exchange separation are necessary for degradable or non-biodegradable detrimental and hazardous wastes removal from water. Membrane technology is of critical importance to solve this vital problem. In membrane technology, nanocomposite membranes (NCMs) are the most preferred in terms of their convenience. These membranes and their constituent materials are eco-friendly, low-cost, and energy-efficient materials. Also they have operational flexibility and feasibility. The current study presents an overview of the progress in NCMs to treat water/wastewater. To prepare NCMs, various used methods are discussed. Also, to improve the mechanical, antibacterial, and adsorption, properties of NCMs have been investigated. The objective of this work was to summarize the removal of toxic wastes from water/wastewater using various NCMs and to emphasize the shortfalls, and future prospective of NCMs technology are highlighted.
THEORETICAL FUNDAMENTALS OF THE CONCEPT IN COGNITIVE LINGUISTICS

Cognitive linguistics is the study of the essence of a particular concept in the linguistic description of the world and its relation to world realities. Concept is one of the main categories of cognitive linguistics and is an element that establishes the connection between culture and man. Cognitive linguistics is a cluster of closely related approaches to the study of language as a mental phenomenon. Cognitive linguistics emerged as a school of linguistics in the 1970s. Cognitive linguistics is the study of knowledge, the study of language, which represents the crucial role of secular information structures in our interactions with the world. This paper discusses the theoretical foundations of conceptualization in cognitive linguistics.
Pix2Pix Network to Estimate Agricultural Near Infrared Images from RGB Data

Abstract Remote sensing has been applied to agriculture, making it possible to acquire a large amount of data far away from crops, providing information for decision making by producers that can impact production costs and crops quality. One way of getting the production information is through vegetation indices, arithmetic operations that use spectral bands, especially the Near Infrared (NIR). However, sensors that capture this spectral information are very expensive for small producers to afford it. In a previous article, a pixel-to-pixel image synthesis model to estimate NIR images from RGB data using hyperspectral endmembers (pure hyperspectral signatures) was described. In this work, an image-to-image synthesis model, known as Pix2Pix, is used for estimating NIR images from low-cost RGB camera images. Pix2Pix is a kind of Generative Adversarial Networks (GANs), composed by two neural networks, a generator (G) and a discriminator (D), that compete. G learns to create images from a random noise inputs and D learns to verify if these images are real or fake. The results showed that the presented method generated NIR images quite similar to real ones, reaching a value of 0.912 on M3SIM similarity metric, outperforming results obtained with the previous endmembers method (0.775 on M3SIM).
Deliberate practice in music: Development and psychometric validation of a standardized measurement instrument

Practice is the process through which musicians improve their performance abilities and increase their level of expertise. Deliberate Practice (DP) is a theory of expertise based on the concept that interindividual differences in the level of proficiency in a specific domain can be mostly explained by interindividual differences in the amount of deliberate practice; despite its popularity, subsequent studies have demonstrated several critical issues in Ericsson’s DP concept, due to its vagueness in definitions, arbitrary measurements of expertise, and inability to account for the possible role of genes. The present project aimed at creating a new questionnaire, capable of measuring practice quality in terms of deliberate practice for the music domain, regardless of the instrument and musical genre played, at any level of expertise. Based on data from a sample of 1,558 musicians, ranging from amateurs to world-renowned soloists, the Deliberate Practice in Music Inventory (DPMI) was created, a self-report questionnaire and measurement instrument for practice quality consisting of a main DP scale and four subscales: Process improvement, Practice competences, Mindless practice (inverted scale), and Task decomposition. Results indicated that musicians who implement effective practice habits are focused on solving problems related to music playing and often refine their practice routines to increase their effectiveness. In addition, musicians who usually exhibit high amounts of DP behavior often decompose long and complex tasks into shorter and simpler elements, aiming to master them more easily and in shorter time. The DPMI instrument shows good convergent validity with measures related to expertise in music as well as good predictive validity for performance improvement. The DPMI generates new perspectives for the field of musical expertise research.
Diagnosis of Depressive Disorder Model on Facial Expression Based on Fast R-CNN

This study examines related literature to propose a model based on artificial intelligence (AI), that can assist in the diagnosis of depressive disorder. Depressive disorder can be diagnosed through a self-report questionnaire, but it is necessary to check the mood and confirm the consistency of subjective and objective descriptions. Smartphone-based assistance in diagnosing depressive disorders can quickly lead to their identification and provide data for intervention provision. Through fast region-based convolutional neural networks (R-CNN), a deep learning method that recognizes vector-based information, a model to assist in the diagnosis of depressive disorder can be devised by checking the position change of the eyes and lips, and guessing emotions based on accumulated photos of the participants who will repeatedly participate in the diagnosis of depressive disorder.
Great Minds Think Alike, and Fools Seldom Differ: A Theory on the Moments of Firms' Performance Distributions.

The association between mean and variance of firm performance is widely believed to be generated by decision makers that deliberately and accurately choose preferred levels of risk. Nevertheless, there is growing dissatisfaction with this explanation, due to the unrealistic assumption about human cognition, on which it is based, and in this paper we challenge that perspective by introducing a new. We model price negotiation between firms that utilize information similarly, share dispositions to invest more heavily upon discovery of greater perceived margins, but have diverse judgment abilities within environments they find uncertain. We explicitly generate, and do not merely assume, the performance distributions of firms, and demonstrate associations between the mean, variance, skewness, and kurtosis of these distributions, which all resemble empirical observations. Our study disputes the validity of prospect theory and behavioral theory in explaining observed aggregate performance patterns within industries, while arguing the importance of explaining not only the first two moments of performance distributions, but higher moments too.
Environmental drivers influencing the abundance of round sardinella (Sardinella aurita) and European sprat (Sprattus sprattus) in different areas of the Mediterranean Sea

Data on Sardinella aurita (round sardinella) and Sprattus sprattus (European sprat) in the Mediterranean Sea are limited due to their scarce commercial interest, at least in European countries. Yet, these two small pelagic fish, sitting at opposite ends of the thermal range, could be interesting sentinel species to monitor the effects of climate change in the basin. Using the Mediterranean International Acoustic Surveys (MEDIAS) – the most extensive source of information on these species – we analyzed their biomass in several geographical subareas of the central and western Mediterranean Sea in relation to satellite-derived environmental parameters. Our findings highlight that the S. aurita biomass responded to temperature, salinity, chlorophyll concentration and sea level anomaly, depending on the GSA examined, whereas the S. sprattus biomass correlated significantly with salinity in GSA 6, with salinity and chlorophyll concentration in GSA 7, and with sea level anomaly in GSA 17. These data widen our knowledge of the factors that contribute to the ecology of these species. Further studies of their spatial distribution and of their interactions with other small pelagic species, predators and prey are needed to depict a more comprehensive scenario.
Penerapan Metode SVM Untuk Deteksi Manusia Secara Realtime

Deteksi manusia pada sebuah video atau gambar adalah tugas yang menantang karena ada beberapa berbagai macam pose dan gerak yang dilakukan dalam video. Ekstraksi fitur yang kuat dapat memungkinkan untuk mendeteksi manusia dengan baik, bahkan dalam latar belakang yang acak dan di bawah penerangan yang sulit. Masalah ekstraksi fitur untuk deteksi manusia, menunjukkan bahwa deskriptor Histogram of Oriented Gradient (HOG) memberikan kinerja yang sangat baik. Selain deskriptor fitur, metode klasifikasi juga memiliki pengaruh besar pada performa deteksi manusia. Support Vector Machine (SVM) merupakan salah satu dari metode klasifikasi yang banyak digunakan karena efisiensinya yang baik . Sehingga dalam penelitian ini akan dilakukan deteksi manusia secara realtime menggunakan metode Histogram Of Oriented Gradient dan klasifikasi Support Vector Machine. Selanjutnya output yang dihasilkan notifikasi berupa audio suara. Pada penelitian ini, dari hasil pengujian didapatkan nilai kecepatan FPS sekitar 22 – 25 fps dengan kecepatan deteksi 328,5 – 510,3 (ms) dan nilai akurasi deteksi manusia dengan 4 skenario memiliki rata rata akurasi sebesar 74,2%
The Electoral Consequences of Affective Polarization? Negative Voting in the 2020 US Presidential Election

About one third of American voters cast a vote more “against” than “for” a candidate in the 2020 Presidential election. This pattern, designated by negative voting, has been initially understood by rational choice scholarship as a product of cognitive dissonance and/or retrospective evaluations. This article revisits this concept through the affective polarization framework in the light of the rise of political sectarianism in American society. Based on an original CAWI survey fielded after the 2020 election, our regression analysis demonstrates that the predicted probability of casting a negative vote significantly increases among individuals for whom out-candidate hate outweighs in-candidate love. Negative voting is less prevalent among partisans as their higher levels of in-group affection can offset out-group contempt. By asserting the enduring relevance of negative voting in American presidential elections, we aim at stimulating further research and discussion of its implications for democratic representation.
Designation of the Quality of EGNOS+SDCM Satellite Positioning in the Approach to Landing Procedure

The main aim of this paper is to present the results of research on the application of a modified mathematical model to determine the quality parameters of SBAS (Satellite Based Augmentation System) satellite positioning in aviation. The authors developed a new calculation strategy to determine the resultant values of the parameters of accuracy, continuity, availability and integrity of SBAS positioning. To achieve it, a weighted mean model was used for the purposes of developing a mathematical algorithm to determine the resultant values of SBAS positioning. The created algorithm was implemented for two SBAS supporting systems, i.e., EGNOS (European Geostationary Navigation Overlay Service) and SDCM (System of Differential Correction and Monitoring). The algorithm was tested in a flight test conducted with a Diamond DA 20-C airplane in north-eastern Poland in 2020. The conducted research revealed that the resultant error of the position in 3D space determined with use of the proposed weighted mean model improved by, respectively, 1–7% in comparison to the standard arithmetic mean model and by 1–37% in comparison to a single SBAS/EGNOS solution. Moreover, the application of the Multi-SBAS positioning algorithm results in an increase in the nominal results of continuity and availability by 50% in comparison to the arithmetic mean model. Apart from that, the values of the integrity parameters determined with use of the proposed weighted mean model improved by 62–63% in comparison to the standard arithmetic mean model.
Design of H-Shape Chamber in Thermal Bubble Printer

The utilization rate of ink liquid in the chamber is critical for the thermal bubble inkjet head. The difficult problem faced by the thermal bubble inkjet printing is how to maximize the use of ink in the chamber and increase the printing frequency. In this paper, by adding a flow restrictor and two narrow channels into the chamber, the H-shape flow-limiting structure is formed. At 1.8 μs, the speed of bubble expansion reaches the maximum, and after passing through the narrow channel, the maximum reverse flow rate of ink decreased by 25%. When the vapor bubble disappeared, the ink fills the nozzle slowly. At 20 μs, after passing through the narrow channel, the maximum flow rate of the ink increases by 39%. The inkjet printing frequency is 40 kHz, and the volume of the ink droplet is about 13.1 pL. The structure improves the frequency of thermal bubble inkjet printing and can maximize the use of liquid in the chamber, providing a reference for cell printing, 3D printing, bioprinting, and other fields.
Study on the preparation and antibacterial properties of CTAB-coated AuNPs

In this paper, spherical gold nanoparticles (AuNPs), rod-shape AuNPs and triangular AuNPs were synthesized using CTAB as the coating reagent, and their bactericidal properties against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) were studied. By the plate count method and turbidity method, the minimum bactericidal concentrations (MBC) and the minimum bacteriostasis concentrations (MIC) to the two kinds of bacteria were determined. The MIC of rod-shape AuNPs, triangular AuNPs and spherical AuNPs to E. coli were 0.65 μg/mL, 3.71 μg/mL, 21.21 μg/mL, and MBC were 1.30 μg/mL, 11.09 μg/mL, 21.21 μg/mL, respectively. The MIC to S. aureus were 0.26 μg/mL, 0.56 μg/mL, 2.65 μg/mL, while MBC were 0.52 μg/mL, 1.11 μg/mL, 2.65 μg/mL, respectively. The results showed that the bactericidal effect of rod-shape AuNPs on E. coli and S. aureus was higher than that of the other two forms, and the bactericidal effect of three different forms of AuNPs on S. aureus was better than that on E. coli.
Novel Artificial Biofilm Equivalent for Denture Surfaces: A Pilot Study

The microbial population of the dental biofilm is embedded in an extracellular matrix that contains organic polymers such as polysaccharides. The extracellular matrix promotes biofilm adhesion on surfaces of dental prostheses and acts as a protective barrier. Thus, a breakdown of the extracellular matrix is crucial for an effective mechanical biofilm removal by brushing. The purpose of this study was to develop an artificial biofilm equivalent (ABE) that is able to mimic the mechanical properties of a natural biofilm concerning abrasion resistance. It contains the two polysaccharides chitosan (ChS) and methylcellulose (MC). Polymethylmethacrylate (PMMA) cylinders ( n = 80 ) were manufactured and coated with the ABE with varying concentration ratios of ChS and MC. Eight test series ( n = 8 each) with different mixing ratios of ChS/MC were tested for their abrasion resistance to brushing in a toothbrush simulator. For the ABE, a total of 2.0 g of polysaccharides were added to 100 ml of 2% acetic acid: 0.3–1.0 g ChS and 1.0–1.7 MC, respectively. Furthermore, two control series ( n = 8 each) with 2.0 g of ChS only or 2.0 g of MC only were performed. Coated specimens were subjected to an increasing number of brushing strokes from 5 to 45 via abrasion test. The specimens were photographed, and a computerized planimetric method (CPM) was used to calculate the percentage of remaining ABE on the brushed areas of the PMMA cylinders. The abrasion resistance of the ABE to brushing decreased with an increasing ratio of MC in the mixture. The abrasion resistance of the ABE can be adjusted by changing the ratio of ChS and MC.
A modal self-excitation method of tensegrity robots

A tensegrity robot is a type of soft-rigid system, whose high compliance is prone to induce structural vibrations which traditionally should be avoided. However, a stable limit cycle oscillation at a natural frequency can be exploited to improve motion efficiency of tensegrity robots. By constructing a modal self-excitation system, we can produce limit cycle oscillation for tensegrity robots. Therefore, in this paper, we propose a method to realize modal self-excitation of under-actuated tensegrity robots. A task-space second-order structural model of a tensegrity robot is developed and a mapping between forces of cable-space and that of task-space is derived. Meanwhile, we propose a cable sensitivity vector from modal shape to guide the selection of active cables in the tensegrity robot. A modal self-excitation system is designed by combining a bandpass filter with a describing function into the control system. In this way, a limit cycle oscillation at a frequency can be formed close to the desired natural frequency. The stability of this limit cycle oscillation is analyzed by perturbation method. Modal switching excitation is also achieved by switching between different modal excitation loops online. The effectiveness of the proposed modal self-excitation method for tensegrity robots is verified by several numerical simulations and tests.