Miracle-dz/UniFAR-FTUs huggingface dataset:
The relationship between strategic management and public relations and their implications for financial operations

In this paper, the co-authors have addressed the relationship between strategic management and public relations, and their implications for financial operations. In addition to growth and development, financial results of an organization are the focus of a business plan implemented by the director general (strategic manager), and as a rule, they represent the hierarchical link between the public relations service and other services affecting financial operations. The lack of appropriate internal communication and coordination of this "triangle," which is a common occurrence in practice, adversely affects financial results. In this paper, explanations of their mutual relations in the above "triangle" with certain recommendations shed some light on multidimensional frameworks of modern business, in which heterogeneous, renaissance knowledge and experiences are required, on the application of which the outcomes of overall, and especially financial business depend. For the aforementioned reasons, in addition to aligning the organization with the environment, strategic managers also have in their portfolio of activities the internal alignment of individual teams, whose synergy contributes to the achievement of the vision, mission, and strategic goals.
Protestzwitschern. Wie Twitter-Netzwerke zur Eskalation der G20-Proteste in Hamburg 2017 beitrugen

Der Beitrag fragt, inwiefern das soziale Medium Twitter zur gewaltsamen Eskalation der G20-Proteste in Hamburg 2017 beigetragen hat. Die These dazu lautet, dass sich parallel zur Eskalation des Protestgeschehens auf den Straßen Hamburgs eine antagonistische Diskursdynamik in Twitter ereignet, die eine sich selbst verstärkende Spirale aus Solidarisierung und Feindbildkonstruktion begünstigt. Die vorliegende Analyse untermauert somit die inzwischen sowohl in der Protestund Bewegungsforschung als auch in der Gewaltsoziologie gängige Annahme, dass eskalierende Konfliktverläufe notwendig mit Transformationen kognitiver Wahrnehmungsund Deutungsmuster einhergehen, die durch ihren polarisierenden Effekt zu einem zentralen Bestandteil der Verursachungsstruktur gewaltsamer Konflikte werden. Schlüsselwörter: Gewalt, Protest, Eskalation, Soziale Medien, Twitter, Netzwerkanalyse
Broadband and High Sensitivity FBG Accelerometer Based on Double Diaphragms and h-Shaped Hinges

A novel broadband and high sensitivity fiber Bragg grating (FBG) accelerometer is designed and analyzed. The accelerometer is based on a compact structure consisting of double diaphragms and h-shaped hinges. The h-shaped hinge structure is used to break through the restriction between sensitivity and resonance frequency. The FBG accelerometer is demodulated by an interferometric method and test results show that the acceleration sensitivity is 32 dB re pm/g between 1 Hz and 1 kHz, with a fluctuation less than ±3 dB, and the resonant frequency is above 1.6 kHz. The cross-sensitivity is less than −26 dB in the flat frequency range. The sensor shows a high acceleration resolution of $15\mu \text{g} / \surd $ Hz in a wide frequency range, making it promising for cross-well seismic, micro-seismic monitoring and electromechanical equipment vibration monitoring, etc.
The role of DNA methylation in the disorders of bone metabolism

Osteoporosis is one of multifactorial diseases, it develops from interactions between the genetic component and the environment. However, the universal epigenetic markers of osteoporosis are not yet defined. Finding the risk factors will predict the risk of osteoporosis at the preclinical stage, help define the course and severity of the disease, and develop preventive measures based on them to reduce the risk of fractures. Expanding knowledge in the field of bone biology, especially in the genetics of osteoporosis and osteoimmunology, showed that osteoporosis is a disease that occurs not only due to hormonal or mechanical disorders, but also as a clinically and genetically heterogeneous disease, and there are still unknown pathogenetic links in its structure. Decreases in bone mass and matrix mineralization as well as changes in bone microarchitecture can have different pathogenetic patterns of development and, moreover, there are unknown links of the pathogenesis of osteoporosis. It is possible that DNA methylation is one of these links and a mechanism for epigenetic regulation of gene expression. Evidence exists that this mechanism alongside regulatory miRNAs and post-translational modifications makes a significant contribution to the central processes of bone remodeling; however, the results of various studies vary greatly, and, therefore, there is a need to understand the significance of the accumulated data and to make them consistent. The purpose of this review is to compile and systematize data on the role of DNA methylation in bone metabolism in normal and pathological conditions, in the formation of osteoporosis, and to assess achievements and trends in this field of research and technologies for studying DNA methylation.
Compassion-Cultivating Pedagogy

Abstract Previous studies suggest that narrative fiction promotes social justice by increasing empathy, but critics have argued that the partiality of empathy severely limits its effectiveness as an engine of social justice, and that what needs to be developed is universal compassion rather than empathy. We created Compassion-Cultivating Pedagogy (CCP) to target the development of two social-cognition capabilities that entail compassion: (1) recognition of self-other overlap and (2) cognizance of the situational, uncontrollable causes of bad character, bad behavior, and bad life-outcomes. Employing a pre/post within- and between-subjects design, we found that students in the CCP classes, but not students in conventionally taught classes, improved in these two areas of social cognition and also exhibited increased preference for compassionate social policies for stigmatized groups. This finding suggests that pedagogy can play a significant role in literature’s contribution to social justice, and that further efforts to develop and test pedagogies for improving social cognition are warranted.
Innovations in Management Forecast: Time Development of Stock Prices with Neural Networks

Accurate prediction of stock market values is a challenging task for over decades. Prediction of stock prices is associated with numerous benefits including but not limited to helping investors make wise decisions to accumulate profits. The development of the share price is a dynamic and nonlinear process affected by several factors. What is interesting is the unpredictability of share prices due to the global financial crisis. However, classical methods are no longer sufficient for the application of share price development prediction.However, over-relying on prediction data can lead to losses in the case of software malfunction. This paper aims to innovate the prediction management when predicting the share price development over time by the use of neural networks. For the contribution, the data on the prices of CEZ, a.s. shares obtained from the Prague Stock Exchange database. The stock price data are available for the period 2012-2017. In the case of Statistica software, the multilayer perceptron networks (MLP) and the radial basis function networks (RBF) are generated. In the case of Matlab software, the Support Vector Regression (SVR) and the Back-Propagation Neural Network (BPNN) are generated. The networks with the best characteristics are retained and based on the statistical interpretation of the results, and all are applicable in practice. In all data sets, MLP networks show stable performance better than in the case of SVR and BPNN networks. As for the final assessment, the deviation of 2.26% occurs in the most significant differential of the maximal and the minimal prediction. It is not necessarily significant regarding the price of one stock. However, in the case of purchasing or selling a large number of stocks, the difference may seem significant. Therefore, in practice, the application of two networks is recommended: MLP 1-2-1 and MLP 1-5-1. The first network always represents a pessimistic, minimal prediction. The second one of the recommended networks is an optimistic, maximal prediction. The actual situation should correspond to the interval of the difference between the optimistic and pessimistic prediction. Keywords: Statistica software, Matlab software, stock price development, neural networks, prediction.
Fast Mesh Denoising With Data Driven Normal Filtering Using Deep Variational Autoencoders

Recent advances in 3-D scanning technology have enabled the deployment of 3-D models in various industrial applications such as digital twins, remote inspection, and reverse engineering. Despite their evolving performance, 3-D scanners still introduce noise and artifacts in the acquired dense models. In this article, we propose a fast and robust denoising method for the dense 3-D scanned industrial models. The proposed approach employs conditional variational autoencoders to effectively filter face normals. Training and inference are performed in a sliding patch setup reducing the size of the required training data and execution times. We conducted extensive evaluation studies using 3-D scanned and CAD models. The results verify plausible denoising outcomes, demonstrating similar or higher reconstruction accuracy, compared to other state-of-the-art approaches. Specifically, for 3-D models with more than $1\text{e}4$ faces, the presented pipeline is twice as fast as methods with equivalent reconstruction error.
Dual Circularly Polarized Array Antenna Based on Corporate Feeding Network in Square Waveguide Technology

In this communication, the design and fabrication of a Ku-band antenna array is presented for dual circular polarization, using a corporate feeding network (CFN) with orthogonal dual-mode operation. A four-way CFN in square waveguide technology is implemented to uniformly illuminate the antenna array. Each of the two propagating modes in the square waveguide excites orthogonal polarizations in the antenna. A dual circularly polarized radiating element is used for the dual-polarized array. Consequently, the link capacity can be doubled by using orthogonal polarizations in a compact and low-loss antenna system. Prototypes have been fabricated by conventional machining and they have been experimentally tested. A 90% total efficiency and matching coefficient better than −10 dB have been obtained in the frequency band between 16.5 and 17.5 GHz for the dual circularly polarized antenna. Further simulations have proven the validity of this topology for larger dual-polarized planar arrays.
Assessment of Aglycones Isoflavone Profiling of Staple Indian Grain Flours and Soybean Sprout-Flour

In the present study, investigation of fourteen traditional and most commonly used Indian staple grain flour types (viz. wheat, white rice, processed little millet, maize, all-purpose/refined wheat flour, chickpea flour, toasted gram flour, little millet, quinoa, soybean, white millet, pearl millet, semolina/cream of wheat and finger millet) was undertaken for the assessment of 3 major bioactive aglycone forms of isoflavone (IF): daidzein (DI), glycitein (GY) and genistein (GN), with a special interest on the effect of sprouting on total and individual IF components. The obtained results showed that the content and composition of total IF were negligible among all the investigated flours except for soybean, wherein detectable total (227 mg kg-1) and individual IF (45, 129 and 53 mg kg-1 for DI, GY and GN respectively) components were observed. From soybean mature seeds to sprouts formation with ~80% germination rate at a pilot-scale, a 31% increase in total IF (298 mg kg-1), characterised by an individual and respective increment of 30% (58 mg kg-1), 25% (161 mg kg-1) and 48% (78 mg kg-1) in corresponding DI, GY and GN components, was observed. The current results demonstrated that for the Indian scenario, contribution of aforementioned grains, other than soybean in daily dietary intake of IF is negligible and sprouting represents an effective way to enhance the endogenous IF content.
Catheter-Related Infection (CRI) Treatment with Taurolidine - Citrate Lock Solution in Patients Undergoing Total Parenteral Nutrition

The use of central venous catheter (CVC) is associated with risk of catheter-related infection (CRI). They have a huge impact on healthcare costs. One of the prevention strategies of CRI is the administration of non-antibiotic lock solutions such as taurolidine. Taurolidine has been proposed as a lock therapy in CVC because of its antimicrobial effect against a broad range of microrganisms. Some authors suggest a beneficial role of taurolidine lock solution application not only for prevention of CRI but for CRI therapy too. In this paper we report six cases of patient undergoing TPN with CRI treated with taurolidine 1.35 % citrate 4% (TC), implanted in Department of Pain Therapy Vascular Access Device Ambulatory, (Monaldi Hospital, Naples Italy). Patients were in Total Parenteral Nutrition (TPN) and received central (CBC) and peripheral blood culture (PBC), clinical evalutation, white blood cell (WBC) count. Patients with positive blood culture received TC every 48 hours throughout vascular access. Parenteral nutrition was suspended only during the day of TC infusion. The drug was administered until the patients didn’t show no fever. In our experience, TC eradicated CRI in all six patients in a six-days therapy, interrupting the TPN only for three days. No side effects occurred. The efficacy of TC in this series of case reports has made possible to resolve all CRI with simple outpatient treatments and therefore could be a further task in the management of infective TPN complication.
Synergizing Mathematical Learning for Future Ready Curriculum using Adventure-Based Learning

The adventure learning consists of highly structured physical activity with debrief session that helps promote personal and social development. It is an approach with the future ready curriculum framework that highlights three elements; curriculum structure, learning and teaching delivery and assessment that are constructively aligned to prepare graduates in meeting the challenges of the 21st century. Previous researches showed that future adventure learning projects are recommended to focus on higher education, small and diverse which can yield significant knowledge into adventure learning. Thus, this study aims to develop an adventurebased learning module for learning statistical inference course at diploma level. This article will highlight two activities of adventure learning in the developed module. The experiential learning theory, the inquiry-based learning and the concept of outdoor learning point of views will be explained to shed additional light on the way the activities in adventure learning endeavors are formed and enacted. This study contributes valuable opportunities for higher education, where connecting learners with real-life and relevant explorations may be the links missing to make higher education experiential, authentic, and engaging.
Evaluating the effect of yeast cell wall supplementation on ideal threonine to lysine ratios in broilers as measured by performance, intestinal mucin secretion, morphology, and goblet cell number

SUMMARY The objective of this study was to investigate whether or not a prebiotic yeast cell wall (YCW), previously shown to improve performance in challenge studies, affects threonine requirements of broilers. Gain, F/G, intestinal morphology, mucin secretion, and goblet cell (GC) number per villi were measured. A total of 240 1‐d‐old Ross 308 broiler chickens were distributed in 2 Petersime battery brooder units (48 pens; 5 birds per pen). Birds were fed for a 21‐d trial with different threonine to lysine ratios (0.65, 0.70, and 0.75) with and without YCW at 250 ppm. A basal diet with 22% protein and 2,980 Kcal/kg ME was used for the dietary treatments. The calculated lysine concentration was 1.35%, while threonine was 0.88%, 0.95%, and 1.02%, respectively. Birds and feed were weighed by pen, and the weights recorded at days 0, 7, 14, and 21 of the experiment for general performance data. At day 21, samples from excreta and small intestine (jejunum and ileum) were collected. YCW did not show any significant effect with respect to the variables evaluated in this non‐challenge study. There was no significant effect for threonine to lysine ratios for all performance variables that had been measured throughout the study. With respect to intestinal morphology, there were significant increases in main effects for the threonine to lysine ratio 0.75 compared with 0.65 in mucin secretion, GC, and jejunum VW, while the jejunum VH significantly increased compared with threonine to lysine ratio 0.70.
Identification of brains tissue hyperelastic parameters

The goal of the paper is to correlate real brain deflection with its numerical model as the 3D model of a fragment of the brain and suction pipe. The model is analyzed with the Finite Element Method with use of Ansys software. The brain tissue can undergo large strains, which is why it is described by a hyperelastic material. The Mooney-Rivlin material model is used for numerical analyzes. The inverse problem is solved with use of optimization Non-Linear Programming by Quadratic Lagrangian (NLPQL). MSC 2010: 92C10, 74S05
Disturbance-Encoding-Based Neural Hammerstein–Wiener Model for Industrial Process Predictive Control

The control reliability of model predictive control is largely determined by the accuracy of the process model. The Hammerstein–Wiener (HW) model is an important nonlinear process modeling technique that has obtained great success in some process industries. Disturbances result in model mismatch and steady-state deviation, but little effort has been devoted to the coupling effects and inertial information in measured disturbances. In addition, few studies try to construct a disturbance observer (DO) to alleviate unmeasured disturbances. The present work proposes prompt disturbance rejection. First, a spatial–temporal long short-term memory-based measurable disturbance encoder is devised to analyze time-series information from measured disturbances and their coupling effects. The encoder can further clarify the status of inertial interference components and the disturbance intensity. Second, a DO is designed to estimate and attenuate unmeasured disturbances. Third, to create the new HW network, which is improved by integrating the disturbance encoder and observer differential, neural networks are used as nonlinear parts. Finally, a model predictive controller based on this improved model is constructed for real-time industrial process control. Simulation comparison experiments have demonstrated the superiority of the proposed methods. Real industry application in the country’s largest lead-zinc froth flotation plant in China validated the proposed model’s effectiveness in controlling chemical reagents.
Climate adaptation and job prospects for young people in agriculture

According to the United Nations, the world’s population will grow by 2 billion people over the coming decades to reach 9.7 billion by 2050 (UNDESA-DP 2019a). The dignity and life prospects of those additional 2 billion people will depend on their ability to meet basic needs, such as food, clothing, and shelter, and their access to adequate employment. The most pressing need for jobs will be felt in those regions and countries that have not yet gone through the demographic transition,1 and where the cohort of young people is growing rapidly. The challenge will be compounded by an increasingly crowded, more competitive world with fewer natural resources per capita, and by the threat of climate change, which is projected to affect every sector of the economy (Arent 2014).
Sampled-Data Asynchronous Fuzzy Output Feedback Control for Active Suspension Systems in Restricted Frequency Domain

This paper proposes a novel sampled-data asynchronous fuzzy output feedback control approach for active suspension systems in restricted frequency domain. In order to better investigate uncertain suspension dynamics, the sampled-data Takagi-Sugeno (T-S) fuzzy half-car active suspension (HCAS) system is considered, which is further modelled as a continuous system with an input delay. Firstly, considering that the fuzzy system and the fuzzy controller cannot share the identical premises due to the existence of input delay, a reconstructed method is employed to synchronize the time scales of membership functions between the fuzzy controller and the fuzzy system. Secondly, since external disturbances often belong to a restricted frequency range, a finite frequency control criterion is presented for control synthesis to reduce conservatism. Thirdly, given a full information of state variables is hardly available in practical suspension systems, a two-stage method is proposed to calculate the static output feedback control gains. Moreover, an iterative algorithm is proposed to compute the optimum solution. Finally, numerical simulations verify the effectiveness of the proposed controllers.
Du bon usage d'ingrédients linguistiques spéciaux pour classer des recettes exceptionnelles

Nous presentons un modele d’apprentissage automatique qui combine modeles neuronaux et linguistiques pour traiter les tâches de classification dans lesquelles la distribution des etiquettes des instances est desequilibree. Les performances de ce modele sont mesurees a l’aide d’experiences menees sur les tâches de classification de recettes de cuisine de la campagne DEFT 2013 (Grouin et al., 2013). Nous montrons que les plongements lexicaux (word embeddings) associes a des methodes d’apprentissage profond obtiennent de meilleures performances que tous les algorithmes deployes lors de la campagne DEFT. Nous montrons aussi que ces memes classifieurs avec plongements lexicaux peuvent gagner en performance lorsqu’un modele linguistique est ajoute au modele neuronal. Nous observons que l’ajout d’un modele linguistique au modele neuronal ameliore les performances de classification sur les classes rares.
Gerenciamento de evasão dos discentes em uma instituição de ensino superior do vale do paraíba

RESUMO Este artigo é um estudo de caso em uma Instituição de Ensino Superior (IES), aqui tratada como uma empresa de gestão educacional, que busca a excelência na aplicação do ensino. O objetivo do trabalho é identificar quais as causas que estão influenciando os índices de evasão dos discentes, e através desta identificação executar uma gestão de implantação de ações para os discentes que apresentam tais dificuldades. São utilizadas ferramentas de gestão encontradas no ambiente das empresas para análise dos dados e verificação do processo de produção educacional, identificando as e propondo melhorias para a instituição e discentes. O processo de produção educacional em estudo apresenta a análise de dois cursos superiores de tecnologias: Eletrônica Automotiva e Análise de Desenvolvimento de Sistemas. As vantagens iniciais desses cursos é que atualmente estão com alta demanda no vestibular, dentro da cidade de Taubaté.