Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of the Media Environment on the Advertising Market in Russia

The development of the media environment and the advertising market is closely interrelated. The current research demonstrates that this relationship is more significant than previously thought. Addressing Russia’s advertising market’s case study, we analyze the major trends and establish the media environment’s effect. To do so, we put forward several hypotheses designed to elucidate the ongoing changes. Statistical and structural-dynamic analysis of development indicators of the media sphere and advertising in 2010–2019 and analysis of macroeconomic data led to the conclusion that Russia’s advertising market has considerable unfulfilled potential for growth. The research results indicate a structural shift towards a growing share of Internet advertising (3.97 times), while all other media market segments are shrinking amid deepening industry diversification. The study confirms the hypothesis that the advertising market is dramatically affected by the level of internet penetration, investments in the media and content sector, and the size of the profit and loss balance of organizations (potential advertisers). The hypothesis that there is a correlation between the growth of the advertising market and the growth in the number of organizations operating in the economy was not confirmed. Based on the regression models, we produce a scenario forecast for developing Russia’s advertising market for 2020–2024. Depending on the action factor, its growth potential ranges from + 5% to + 27% during the indicated period. One of the avenues for further studies is searching for useful tools to stimulate market development based on the patterns identified.
Uma arquitetura para a Gerência de Migração de Máquinas Virtuais

The cloud infrastructure is provided by Cloud Providers (CP) enabling Cloud Services (CS) being supplied by Cloud Service Providers (CSP). In order to guarantee elasticity to CSs, Virtual Machine migrations have been adopted within the dynamic resource management. However, the workloads dynamism becomes a drawback to Cloud Management Platforms (CMP). Solutions in that scenario are challenging, concerning the diversity of service integration strategies performed by CMPs. As a consequence, migrations tend to be poorly planned, increasing the risks of failures and delays. This work proposes an architecture that allows integrating different sources of information, aiding in the automation and management of VM migrations. The proposal was compared with a solution that does not employ migration management features, in a scenario involving inter-DC communication. The evaluations show the effectiveness of the proposal, diminishing unnecessary migrations as well as the frequency of overload situations. Resumo. Provedores de Infraestrutura (Cloud Provider CP) fornecem recursos físicos para a provisão de Serviços Baseados em Nuvem (Cloud Service CS) que são coordenados por um Provedor de CSs (Cloud Service Provider CSP). Para garantir a elasticidade de CSs, a migração de VMs tem sido adotada no gerenciamento dinâmico de recursos. Contudo, o dinamismo que as cargas de trabalho (workload) impõe às VMs tem sido um obstáculo para as Plataformas de Gerência de Nuvens (Cloud Management Platforms CMP). Propor soluções nesse cenário é desafiador, considerando a diversidade de abordagens de integração de serviços dos CMPs. Neste cenário, migrações tendem a ser mal planejadas, aumentando o risco de falhas e atrasos. Este trabalho propõe uma arquitetura que possibilita a integração das diferentes fontes de informação, contribuindo para a automatização e o gerenciamento das migrações de VMs. A proposta foi comparada com uma solução que não emprega recursos de gerenciamento, em um cenário de migrações entre Datacenters (DCs). A avaliação mostra a efetividade da abordagem proposta, diminuindo a quantidade de migrações desnecessárias e a frequência de sobrecargas pontuais.
Lentinan for Integrative Cancer Treatment: An Umbrella Review

The aim of this review is to understand whether lentinan can be a useful integrative remedy for cancer patients. PubMed, EMBASE, Web of Science, Cochrane Library and Google Scholar were screened for relevant meta-analyses from inception to 29th September 2020. After database search, 8 meta-analyses met inclusion criteria. Retrieved evidence reported that lentinan may be useful to improve response rate, 1-year survival, performance status, quality of life and radio/chemotherapy toxicity when administered in adjunct to standard therapy, especially for some lung and gastrointestinal cancers. Further studies are advised due to limitations of existing evidence.
Contributing factors in academic performance and troubles associated with teaching in areas of physics in engineering students

Learning processes are affected by a series of factors, both individual students and the institutional environment in which they develop. The present work is developed under the context of learning processes in areas of physics in engineering students, belonging to the academic program of technology in industrial processes, considering the socio-demographic and academic variables that affect students and that in turn affect student dropout. Data collection instruments were applied to a population group of 90 students, allowing to propose strategic scenarios that would contribute to improve the quality of academic processes and students’ skills in the study of mechanical and electromagnetic physics. It was determined that the role played by teachers and the methodology in which they teach their students, the physical conditions and teaching methods directly affect the effectiveness of learning and academic performance. It was also demonstrated that the lack of prior knowledge in the fundamentals of logic-mathematics and basic physics are determining aspects in the failure and repetition of the subjects.
Influencers’ recommendations on the Internet: effects of codes of conduct

Recommendations of goods and/or services on social networks are an increasingly widespread advertising tactic. Brands are aware of the power of persuasion that influencers in the digital world have on their followers. In this article, we analyze the particularities of this phenomenon and then focus on its regulation. Specifically, we refer to the suggestive role that self-regulation plays in this area. By virtue of the latter, codes of conduct in the influencer market are possible.
Exploring popular topic models

Information from micro-blogging site such as Twitter is a huge repository of data. A lot of research is happening on sentiments, discovering patterns and prediction. One challenging task is dividing this humongous unstructured data into clusters. Several topic modeling methods are proposed by researchers. This paper presents a brief summary of topic modeling methods LDA, LSI and NMF and their applications. Experiments are conducted on the Twitter based datasets created using tweets on keywords Cauvery river, Lokpal bill and Rahul Gandhi. Paper covers a brief discussion on evaluating the accuracy of topics formed using perplexity, log-likelihood and topic coherence measures. Best topics formed are then fed to the Logistic regression model. The model created is showing better accuracy with LDA.
3D PRINTING OF PHARMACEUTICALS – LEADING TREND IN PHARMACEUTICAL INDUSTRY AND FUTURE PERSPECTIVES

3D printing technology is a rapid prototyping process based on computer-aided design software that is proficient to construct solid objects with various geometrics by depositing numerous layers in a sequence. The major advantages of three-dimensional printing (3DP) technology over the traditional manufacturing of pharmaceuticals include the customization of medications with individually adjusted doses, on-demand tailored manufacturing, unprecedented flexibility in the design, manufacturing of complex and sophisticated solid dosage forms, and economic benefits. Recently, many researchers have been invested their efforts in applying 3DP technology to the pharmaceutical development of drug products and different drug delivery systems. Selective laser sintering, fused deposition modeling, semi-solid extrusion, stereolithography, etc., are the multiple 3DP technologies that can be established in several customized and programmable medicines. Sublingual, orodispersible, and fast-dissolving drug delivery formulations by 3DP technology have been already manufactured. Controlled-release formulations with different characteristics, doughnut-shaped multi-layered tablets with linear release kinetics, and drug-loaded tablets with modified-release characteristics are recently fabricated using 3DP. However, few 3DP methods produce uneven shapes of dosage forms and comparatively porous structures. Cost of transition, adaptation to the existing facility, achieving regulatory approval, etc., are the present challenges that can restrict the extensive application of 3DP technology to pharmaceutical products. Intense research work for modifying the 3DP methods is simultaneously sustained for by-passing the flaws and current limitations of this technology. 3DP technology can act as a convenient and potential tool for the pharmaceutical industry which will set a revolutionary manufacturing style in the near future to facilitate patient-centered health care.
The Role of FDI on Exports Performance: Evidence from the Mexican States

This article examines manufacturing export determinants across Mexican states and regions from 2007 to 2015. Paying particular attention to the role of FDI, the analysis considers internal and external determinants of manufacturing exports under static and dynamic panel data methods. Several interesting results were obtained. First, the ratio of manufacturing to total GDP is the most consistent determinant of exports performance, regardless of the estimation method or specification employed. Second, static panel data estimations under GMM techniques suggest different sensitivity to FDI across regions, with the Mexico-U.S. border region observing the most substantial short-term effect of FDI on manufacturing exports. Finally, using dynamic panel data methods, we found significant persistence and similar long-term effects of FDI across most of the regions.
Improving Training Instance Quality in Aerial Image Object Detection With a Sampling-Balance-Based Multistage Network

Object detection, aiming to recognize and locate objects of interest in aerial images, has historically played a significant role in the remote sensing community. Following remarkable improvements in Earth observation technologies, high-resolution remote sensing (HRRS) images with a bird’s eye view perspective have revealed many categories of objects with sufficient variations in appearance and on complex backgrounds that make HRRS object detection an active but challenging task. The selection of positive samples and negative training instances is an essential factor in influencing detectors’ performance. Related studies have found that many low-quality negative samples in the detectors’ training process have caused training instability and low detection accuracy. In this work, a novel sampling-balance-based multistage network (SB-MSN) is presented to adaptively mine high-quality positive and negative instances for training an accurate detector. It has a series of components to ensure the selection and generation of high-quality examples for training an accurate detector, including a multiscale information retention module, an intersection over union balance sampling strategy, a balance L1 loss, and a multistage network. The proposed detector has been evaluated on three representative HRRS data sets. The extensive experimental results show that our detector can solve the problem of low-quality samples and significantly improve the detection performance of the mAP by 1.4% with the NWPU VHR-10 data set, 3.5% with the high-resolution remote sensing detection (HRRSD) data set, and 4.2% with the detection in the optical remote (DIOR) data set.1
UM DESENHO METODOLÓGICO PARA ENGAJAR E MOTIVAR OS ALUNOS NAS AULAS REMOTAS NA PANDEMIA DO COVID-19

Este artigo apresenta um desenho metodológico para ser aplicado em aulas remotas, tomando como base boas práticas pedagógicas oriundas da Educação a Distância, Aprendizado Colaborativo e Metodologias Ativas. A proposta é aplicada em quatro turmas de Interação Humano-Computador (IHC), de dois cursos da área de tecnologia da informação em uma universidade do Nordeste do Brasil. Para avaliar a experiência dos alunos com as práticas pedagógicas aplicadas durante as aulas, foi utilizada uma técnica proveniente da área de Experiência do Usuários (User eXperience – UX). O legado do estudo pode contribuir para que professores de diferentes áreas possam melhorar a experiência dos alunos em aulas remotas durante e pós pandemia do Covid-19.
Pilot Application of Biofeedback Training Program for Racket Sports Players

Background. A biofeedback program receives attention as an intervention program for athletes to regulate their psychological state. Objectives. The purpose was to apply for a heart rate variability (HRV) biofeedback training program and validate its effectiveness for racket sports players. Objectives. The purpose was to apply a heart rate variability (HRV) biofeedback training program and validate its effectiveness for racket sports players. Methods. he participants were eight elite sport athletes (three men and five women): five squash players and three tennis players. The HRV biofeedback training program consisted of ten sessions in which the participants performed paced breathing for 10 minutes (e.g., 5-second inspiration and 5-second expiration). The means and standard deviations of the collected data were calculated, and the Wilcoxon signed-rank test was performed using SPSS windows 18.0. Results. Changes in HRV by the biofeedback training were significant. Standard Deviation of Normal to Normal (SDNN; Z = -2.38, p = 0.017) in time domain and Low Frequency (LF, Z = -2.52, p = 0.12) and the ratio of LF to High Frequency (HF; Z = -2.52, p = 0.12) in frequency domain were increased. Conclusion. The present study provides empirical results needed to expand HRV biofeedback training research for the performance enhancement program of athletes.
Evolution of Consumption Expenditures of Population of the Republic of Moldova

Consumption expenditures is one of the key indicators that reflects the purchasing power of the population. Purchasing power in turn shows the level of social welfare. The population with a stable evolution of consumer spending is at least able to maintain its level of consumption with inflation. In addition, if consumer spending rises in proportion to the level of inflation, there is an increase in welfare and living standards. High level of consumption has positive influence on business. greater aggregate demand will generate more profits, boost company development, and foster job creation. In this study, the affirmation was verified that the consumer price index is one of the factors that influence the standard of living, but not primarily. The following scientific methods were used to approve or reject the statement: scientific abstraction, analysis and synthesis, graphical and tabular method, comparative analysis method, correlation and regression analysis. In this study there was made comparison of consumption evolution and its structure in the Republic of Moldova and in the European Union to identify the difference in welfare. The linear regression model between the consumer price index and growth rate of household expenditures was elaborated.
Productive traits, blood biochemical parameters and meat quality of rainbow trout (Oncorhynchus mykiss W.) fed with supplement of nutmeg extract (Myristica fragrans)

The aim of the present study was to evaluate the effect of the dietary nutmeg extract (Myristica fragrans) supplement on the survival rate, weight gain, feed conversion ratio (FCR), economic efficiency (ECR), blood biochemical parameters, chemical composition and fatty acid profile of rainbow trout (Oncorhynchus mykiss W.), cultivated in a recirculation system. One hundred and sixty rainbow trouts were distributed in two experimental variants, each with two replications with 80 fish in one group. The average initial live weight of trouts from control (C) and experimental (E) groups was 13.43±0.33 g and 13.46±0.29 g, respectively. Fish were reared in concrete tanks with effective volume of 0.8 m3, part of a recirculation system. Trouts were fed „Aqua garant UNI“ extruded feed produced by Garant-Tiernahrung Gesellschaft m.b. H. Austria, with pellet size of 2 mm. The feed of fish from the experimental group was supplemented with 1% powdered nutmeg extract (P.I.C.Co LTD), by lubricating the pellets with 5 ml sunflower oil/100 g feed. Control rainbow trouts received feed lubricated with the same amount of sunflower oil. Fish from both groups were fed 3 times daily and their ration was 3% of body weight. The experimental period lasted 60 days. The dietary supplementation of rainbow trouts with nutmeg extract had a negative impact on growth performance and economic efficiency of farming of the species. Final live weight and average individual weight gain were lower, and FCR and ECR values were inferior vs controls. The nutmeg extract had also an adverse effect on water content and dry matter of meat from supplemented fish. A positive effect was demonstrated only on meat fat content, which was substantially lower compared to that of control fish. Despite the higher SFA as well as lower UFA, MUFA, PUFA, n-6 and n-3 fatty acid content of trout meat that received nutmeg extract with feed, the PUFA/SFA and n-6/n-3 ratios remained within the favourable range for human nutrition, e.g. >0.4 and <5, respectively.
Precision study of mineralization features of enamel apatite in the development of fluorosis by means of optical spectroscopy

We have investigated the molecular composition of the tooth enamel microregions in the normal and initial stages of the development of fluorosis by means of the IR and Raman spectroscopy. It has been shown that in the pathology of fluorosis, tooth mineralization takes place with the formation of calcium fluoroapaptite. It was found that an increased fluorine content causes a change in the characteristic profile of the bands and a redistribution of the intensity of the components of the υ1 PO4 and υ3 CO3 groups of the infrared and υ4 PO4 Raman spectra. The resulting IR and Raman spectra can be utilized as standards in the development of a new diagnostic approach of the early forms of the disease.
Effects of process variables and their interactions on melt pelletization in a high shear mixer

Cette etude porte sur la possibilite d'utilisation d'un nouveau melangeur a cisaillement revetu interieurement de polytetrafluorethylene pour la pelletisation avec produit fondu. Les effets de la vitesse du rotor, du temps de melange, de la concentration en liant et de la charge du melangeur ont ete etudies sur du lactose monohydrate et du polyoxyethylene glycol 3000. Les interactions entre les variables controlees ont ete suivies par la methode des surfaces de reponses. Un plan orthogonal a ete utilise pour l'optimisation du procede de pelletisation avec un produit fondu. Il a ete montre que les principaux mecanismes de grossissement des grains sont la coalescence, l'ecrasement et le depot de couches. Avec une forte teneur en liant, la coalescence est augmentee grâce a la facilite accrue d'obtention de surfaces plastiques et deformables. Les forces de cisaillement elevees obtenues pour de grandes vitesses du rotor accelerent la consolidation et le grossissement des agglomerats. Le melangeur a cisaillement permet de preparer, a l'aide d'un produit fondu, des pellets de la granulometrie desiree avec une distribution etroite, lorsque le mode operatoire et les variables de formulation sont bien maitrises. La charge du melangeur interagit avec la vitesse du rotor et le temps de melange et doit etre soigneusement ajustee afin de fournir l'energie correcte au systeme. Une forte charge du melangeur et une faible teneur en liant conduisent a un processus de formation des pellets plus facile a maitriser.
Neural networks and their application in forecasting problems

The report describes popular machine learning methods and applications of neural networks. It reveals methods of training neural networks and offers a method of forecasting based on neural networks for modelling financial time series. Neural networks have recently gained in popularity among scholars. In particular, neural networks are widely used in the field of visualization and image recognition. But the practical significance of neural networks does not end there, they also find usage in such areas as forecasting, classification, clustering and modelling. This success can mainly be attributed to the remarkable property of models based on neural networks – they can «see» non-linear connections in contrast to many models, which for the most part have linear connections only. Currently, the use of neural networks is developing in the following directions: Stock market and macroeconomic forecasting (Neuro XL, OptimuStock, StocksNeural); Speech recognition and man-machine dialogue (Siri, Alexa, Cortana, Alice); Imitation of intellectual activity (weak AI in Siri, Alexa, Cortana, Alice); Improving low-quality and noisy information (DeepImagePrior). The advantages of using neural networks include: versatility. simplicity. Neural networks are able to model dependencies also in cases when there is a large number of variables.
The Impact of Flooding on Urban Transit and Accessibility: A Case Study of Kinshasa

Transportation networks underpin socioeconomic development by enabling the movement of goods and people. However, little is known about how flooding disrupts transportation systems in urban areas in developing country cities, despite these natural disasters occurring frequently. This study documents the channels through which regular flooding in Kinshasa, the Democratic Republic of Congo, impacts transport services, commuters' ability to reach their jobs, and the associated economic opportunity costs from travel delays. This assessment is based on transit feed specification data sets collected specifically for this analysis under normal and flooded conditions. These data sets were combined with travel survey data containing travelers' socioeconomic attributes and trip parameters, as well as a high-resolution flood maps. The results show that (1) flood disruptions cause increases in public transit headways and transit re-routing, decreases in travel speeds, and thus travel time delays, which translate into substantial economic costs to local commuters; (2) accessibility to jobs decreases under flooded conditions, hindering the establishment of an integrated citywide labor market; (3) there are spatial clusters where some of the poorest commuters experience among the highest travel delays, highlighting socio-spatial equity aspects of floods; (4) certain road segments are critical for the transport network and should be prioritized for resilience measures; and (5) the estimated daily cost of flood disruption to commutersâ€™ trips in Kinshasa is $1,166,000. The findings of this assessment provide disaster mitigation guidance to the Office des Voiries et Drainage under the Ministry of Infrastructure, as well as strategic investment recommendations to the Ministry of Housing and Planning.