bluuebunny/crossref_metadata_2025 huggingface dataset:
Shaping the transmission trajectory of vortex beam by controlling its radial phase
Authors: Zhu Long , Zhu Yue , Deng Mingliang , Lu Bing , Guo Xiaojin , Wang Andong
Published: November 2022

Vortex beam carrying orbital angular momentum (OAM), which features a helical phase front, has shown its potential applications in diverse areas, especially in free-space optical (FSO) communications. However, when generating vortex beams, the radial phase distribution is usually disregarded in previous reports. In this paper, by controlling the radial phase distribution, we propose a method for the generation of vortex beams with arbitrary convex trajectories. By using this method, we successfully generate vortex beams with different predesigned trajectories with high accuracy. Moreover, we also demonstrate the transmission of the radial phase-controlled vortex beams in FSO links for different scenarios in simulation. Firstly, we generate vortex beams with different OAM states (l=+1, + 3, and +6), which have the same ring diameter at the receiver side. Secondly, we generate three vortex beams (l=+3) with the same ring diameter at different transmission distances (z = 100 m, 200 m, and 300 m). Finally, by carefully controlling the radial phase of the vortex beam, we generate vortex beams that can almost keep the same ring diameter for a long distance. The proposed method for shaping the transmission trajectory of vortex beams may pave the way for more applications in OAM-based FSO communications.
Tunable plasmonics on epsilon-near-zero materials: the case for a quantum carrier model
Authors: Shabaninezhad Masoud , Ramunno Lora , Berini Pierre
Published: November 2022

The carrier density profile in metal-oxide-semiconductor (MOS) capacitors is computed under gating using two classical models - conventional drift-diffusion (CDD) and density-gradient (DG) - and a self-consistent Schrödinger-Poisson (SP) quantum model. Once calibrated the DG model approximates well the SP model while being computationally more efficient. The carrier profiles are used in optical mode computations to determine the gated optical response of surface plasmons supported by waveguides incorporating MOS structures. Indium tin oxide (ITO) is used as the semiconductor in the MOS structures, as the real part of its optical permittivity can be driven through zero to become negative under accumulation, enabling epsilon-near-zero (ENZ) effects. Under accumulation the predictions made by the CDD and SP models differ considerably, in that the former predicts one ENZ point but the latter predicts two. Consequently, the CDD model significantly underestimates perturbations in

n

e
f
f

of surface plasmons (by ∼4×) and yields incorrect details in surface plasmon fields near ENZ points. The discrepancy is large enough to invalidate the CDD model in MOS structures on ENZ materials under accumulation, strongly motivating a quantum carrier model in this regime.
No sonographer, no radiologist: Assessing accuracy of artificial intelligence on breast ultrasound volume sweep imaging scans
Authors: Marini Thomas J. , Castaneda Benjamin , Parker Kevin , Baran Timothy M. , Romero Stefano , Iyer Radha , Zhao Yu T. , Hah Zaegyoo , Park Moon Ho , Brennan Galen , Kan Jonah , Meng Steven , Dozier Ann , O’Connell Avice
Published: November 2022

Breast ultrasound provides a first-line evaluation for breast masses, but the majority of the world lacks access to any form of diagnostic imaging. In this pilot study, we assessed the combination of artificial intelligence (Samsung S-Detect for Breast) with volume sweep imaging (VSI) ultrasound scans to evaluate the possibility of inexpensive, fully automated breast ultrasound acquisition and preliminary interpretation without an experienced sonographer or radiologist. This study was conducted using examinations from a curated data set from a previously published clinical study of breast VSI. Examinations in this data set were obtained by medical students without prior ultrasound experience who performed VSI using a portable Butterfly iQ ultrasound probe. Standard of care ultrasound exams were performed concurrently by an experienced sonographer using a high-end ultrasound machine. Expert-selected VSI images and standard of care images were input into S-Detect which output mass features and classification as “possibly benign” and “possibly malignant.” Subsequent comparison of the S-Detect VSI report was made between 1) the standard of care ultrasound report by an expert radiologist, 2) the standard of care ultrasound S-Detect report, 3) the VSI report by an expert radiologist, and 4) the pathological diagnosis. There were 115 masses analyzed by S-Detect from the curated data set. There was substantial agreement of the S-Detect interpretation of VSI among cancers, cysts, fibroadenomas, and lipomas to the expert standard of care ultrasound report (Cohen’s κ = 0.73 (0.57–0.9 95% CI), p<0.0001), the standard of care ultrasound S-Detect interpretation (Cohen’s κ = 0.79 (0.65–0.94 95% CI), p<0.0001), the expert VSI ultrasound report (Cohen’s κ = 0.73 (0.57–0.9 95% CI), p<0.0001), and the pathological diagnosis (Cohen’s κ = 0.80 (0.64–0.95 95% CI), p<0.0001). All pathologically proven cancers (n = 20) were designated as “possibly malignant” by S-Detect with a sensitivity of 100% and specificity of 86%. Integration of artificial intelligence and VSI could allow both acquisition and interpretation of ultrasound images without a sonographer and radiologist. This approach holds potential for increasing access to ultrasound imaging and therefore improving outcomes related to breast cancer in low- and middle- income countries.
Histone acetyltransferase inhibition reverses opacity in rat galactose-induced cataract
Authors: Nagaya Masaya , Yamaoka Risa , Kanada Fumito , Sawa Tamotsu , Takashima Masaru , Takamura Yoshihiro , Inatani Masaru , Oki Masaya
Published: November 2022

Cataract, a disease that causes opacity of the lens, is the leading cause of blindness worldwide. Cataracts secondary to diabetes are common, even in young patients, so they are of significant clinical importance. Here, we used an ex vivo model of galactose-induced cataracts in the rat lens to investigate the therapeutic effects of histone acetyltransferase (HAT) inhibitors. Among the tested HAT inhibitors, TH1834 was the only one that could reverse most of the opacity once it had formed in the lens. Combination treatment with C646/CPTH2 and CBP30/CPTH2 also had therapeutic effects. In lens cross-sections, vacuoles were present in the tissue of the cortical equatorial region of untreated cataract samples. In treated cataract samples, lens tissue regenerated to fill the vacuoles. To identify the genes regulated by HAT inhibitors, qRT-PCR was performed on treated and untreated cataract samples to determine candidate genes. Expression of Acta1 and Stmn4, both of which are involved in the cytoskeleton, were altered significantly in C646+CPTH2 samples. Expression of Emd, a nuclear membrane protein, and Prtfdc1, which is involved in cancer cell proliferation, were altered significantly in CBP30+CPTH2 samples. Acta1, Acta2, Arrdc3, Hebp2, Hist2h2ab, Pmf1, Ppdpf, Rbm3, RGD1561694, Slc16a6, Slfn13, Tagln, Tgfb1i1, and Tuba1c in TH1834 samples were significantly altered. These genes were primarily related to regulation of cell proliferation, the cytoskeleton, and cell differentiation. Expression levels increased with the onset of cataracts and was suppressed in samples treated with HAT inhibitors.
Three new species of Homatula (Teleostei: Nemacheilidae) from Yunnan, China, with comments on habitat conservation
Authors: Li Xu , Yang Bo , Guo Yi , Zhou Wei
Published: November 2022

Based on the morphological comparisons and molecular results, three new species of Homatula, i.e., H. geminusclathratus sp. nov., H. microcephala sp. nov., and H. longibarbatus sp. nov., have been described and named from the Lancang-jiang (the upper Mekong River) and the Chuan-he (the upper Black River, a tributary of the Red River) basins. The loaches of Homatula from the Lancang-jiang and the Chuan-he can be distinguished via morphology, genetics, and geographic distribution. All of the 10 recorded species distributed in the Nu-jiang (the upper Salween River), the Lancang-jiang, and the upper Black River share the following combination of character states: whole body, except head, densely scaled; lateral line complete; and a short adipose crest along the dorsal midline of the caudal peduncle, anteriorly not reaching vertically through the anal-fin origin. Species with these characters are called the densely-scaled group of Homatula. The three newly described species belong to the densely-scaled group of Homatula. Based on molecular phylogenetics, these Homatula species form a monophyletic group that can be divided into two clades, the densely-scaled group and the non-densely-scaled group. The densely-scaled group of Homatula includes 13 species occurring between the Nu-jiang and the upper Black River. The non-densely-scaled group is non-monophyletic and includes 14 species that are distributed in the Red, Pearl, Yangtze, and Yellow River basins. Species of the non-densely-scaled group are clustered into four sub-clades that are constrained to the four river basins. Homatula exclusively inhabits mountain streams with rapid or gentle currents, vauclusian springs, underground rivers connected to streams, and ditches near villages and farmland. No specimens of Homatula were collected from the main streams of Lixian-jiang, Lancang-jiang, and Nu-jiang as well as their large tributaries. Small environmental changes in the habitat of Homatula, such as water pollution or extensive human use, can lead to species/population extinction. Effective conservation of rare and endemic fishes, like loaches of Homatula, entails systematic observations and more targeted protection.
Large-scale assessment of German dairy farmers´ personality and resulting ideas for improving veterinary consultancy
Authors: Adler Friedemann , Campe Amely
Published: November 2022

The here presented investigation was part of a cross-sectional study on dairy cattle health aiming to identify risk factors for animal health and welfare. Within this setting, we chose a social-science related approach to explore German dairy farmers’ personality composition in a variable-centered and person-centered approach. We have assessed German dairy farmers’ personalities based on the HEXACO model of personality in three representative regional samples. In total, 765 farm visits were conducted within two and half years (north n = 253; east n = 252; south n = 260). The proportions of returned questionnaires eligible for analysis (i.e., answered completely) were 71.54% (n = 181), 68.25% (n = 172) and 86.92% (n = 226) for the northern, eastern and southern samples, respectively. Variable-centered personality analyses revealed the farmers’ structure of personality to be similar within all samples. Overall, we found the farmers to be averagely emotional and agreeable, whereas the results indicate tendencies for a pronounced display of extraversion, conscientiousness and openness to experience. Compared to the German general population, dairy farmers appear to be more extraverted and open to experience. We could not deduce a subcategorization of farmers in different latent personality profiles in person-centered analysis. Our findings provide a basis for further evaluation of the farmers´ personality as an influencing factor for farm outcomes (e.g., productivity, animal health and welfare). Furthermore, we provide a glance and encourage interdisciplinary research to link personality information with communication theory aiming to enhance effectiveness of veterinary consultancy.
Prevalence and determinants of wasting of under-5 children in Bangladesh: Quantile regression approach
Authors: Hossain Md. Moyazzem , Abdulla Faruq , Rahman Azizur
Published: November 2022

Background

Wasting is perhaps one of the signs of malnutrition that has been linked to the deaths of children suffering from malnutrition. As a result, understanding its correlations and drivers is critical. Using quantile regression analysis, this research aims to contribute to the discussion on under-5 malnutrition by analyzing the predictors of wasting in Bangladesh.

Methods and materials

The dataset was extracted from the 2017–18 Bangladesh demographic and health survey (BDHS) data. The weight-for-height (WHZ) z-score based anthropometric indicator was used in the study as the target variable. The weighted sample constitutes 8,334 children of under-5 years. However, after cleaning the missing values, the analysis is based on 8,321 children. Sequential quantile regression was used for finding the contributing factors.

Results

The findings of this study depict that the prevalence of wasting in children is about 8 percent and only approximately one percent of children are severely wasted in Bangladesh. Age, mother’s BMI, and parental educational qualification, are all major factors of the WHZ score of a child. The coefficient of the female child increased from 0.1 to 0.2 quantiles before dropping to 0.75 quantile. For a child aged up to three years, the coefficients have a declining tendency up to the 0.5 quantile, then an increasing trend. Children who come from the richest households had 16.3%, 3.6%, and 15.7% higher WHZ scores respectively than children come from the poorest households suggesting that the risk of severe wasting in children under the age of five was lower in children from the wealthiest families than in children from the poorest families. The long-term malnutrition indicator (wasting) will be influenced by the presence of various childhood infections and vaccinations. Furthermore, a family’s economic position is a key determinant in influencing a child’s WHZ score.

Conclusions

It is concluded that socioeconomic characteristics are correlated with the wasting status of a child. Maternal characteristics also played an important role to reduce the burden of malnutrition. Thus, maternal nutritional awareness might reduce the risk of malnutrition in children. Moreover, the findings disclose that to enrich the nutritional status of children along with achieving Sustainable Development Goal (SDG)-3 by 2030, a collaborative approach should necessarily be taken by the government of Bangladesh, and non-governmental organizations (NGOs) at the community level in Bangladesh.
A Google Earth-GIS based approach to examine the potential of the current rainwater harvesting practices to meet water demands in Mityana district, Uganda
Authors: Nanteza Jamiat , Thomas Brian , Kisembe Jesse , Nakabugo Rhoda , Mukwaya Paul Isolo , Rodell Mathew
Published: November 2022

Rainwater harvesting (RWH) has become an integral part of global efforts to improve water access. Despite the increasing adoption of RWH in Uganda, there remains a significant knowledge gap in the assessment of RWH systems to meet water demands. In this study, a simplified methodology to estimate rainwater harvesting potential (RWHP) as a function of mean seasonal rainfall and rooftop area, generated using Google Earth and GIS tools is applied. Desired tank storage (DTS) capacities based on user population, demand and dry period lengths, were compared with RWHP to assess whether rooftop areas and tank storage can sustainably supply water for use during the March—May (MAM) and September-November (SON) 90-day dry periods, for three demand levels (i.e. for drinking and cooking (15 litres per capita per day (l/c/d)); for drinking, cooking and hand washing (20 l/c/d); and for drinking, cooking, hand washing, bathing and laundry (50 l/c/d)). Our findings document minimum catchment areas of 60m2to have rainwater harvesting potential that can sustain households for 90-day dry periods for all three demand levels. However, considering their storage capacities, 25%, 48% and 97% of the existing RWHTs (with storage capacities below 8,000, 10,000 and 20,000 litres respectively) are unable to meet the demand of 15 l/c/d, 20 l/c/d and 50 l/c/d respectively for a 90-day dry period. The results document that the existing storage systems are under-sized for estimated water use under 50 l/c/d demand scenarios. Costs of between 2,000,000–4,500,000 Ugandan shillings (~ 600–1, 250 USD) would be needed to increase existing tank capacities to meet the 50 l/c/d demands for a 90-day dry period. These findings document onerous financial costs to achieve rainwater harvesting potential, meaning that households in Mityana district may have to resort to other sources of water during times of shortage.
The effectiveness of augmented reality in marketing communications on Generation Z consumer behaviour
Authors: Boonchutima Smith , Sahakitpijarn Kanokrat
Published: November 2022

Multiple brands, especially in the beauty industry, have considered and employed marketing strategies involving augmented reality (AR) in the past few years. However, the efficiency of augmented reality marketing (ARM) remains understudied. There are few experimental studies, and most are based on samples from western cultures and feature a narrow range of products. This study aims to fill this gap by conducting an experimental study using a sample of Generation Z women in Thailand to examine the effect of AR on lipstick purchase behaviour. This study primarily compares the efficiency of traditional and ARM in improving brand attitudes, reducing the perceived risk related to making a purchase and increasing purchase intentions. The results demonstrate that traditional marketing and ARM lead to significantly different results regarding the three constructs. Nonetheless, both approaches are effective in achieving all three desired outcomes. ARM is slightly more effective in reducing perceived risk, thereby providing valuable insights into its potential for successfully marketing cosmetics.
COMPARATIVE ASSESSMENT OF THE DEVELOPMENT OF BORDER REGIONS OF A NUMBER OF FOREIGN CONTRIES AND RUSSIA
Authors: Badarchy K. B. , Sevek V. K. , Sereezhikpei A. A.
Published: November 2022

The article is devoted to the issue of assessing the level of socio-economic development of border regions in foreign countries in the context of similar domestic experience. The analysis is based on a comparison of the countries of the world in terms of the level of interregional differentiation in terms of gross regional product per capita and a correlation analysis of the GRP per capita with the share of the titular ethnic group in the structure of the population of border regions, as a significant subjective influencing factor. The analysis shows that the deepest lag of border territories is characteristic of multi-ethnic states with administrative division along ethnic lines. A typical representative of countries with a cultural and civilizational type of border area is China, for which the correlation between the indicators of gross regional product per capita and the relative share of the titular ethnic group in the composition of the population in the border areas as of 2010 was 0.55. At the same time, by the 1920s, China should reduce the gap in the backlog of ethnic border areas to the level of the absence of a connection between the GRP indicator and the share of the titular ethnic group in the population of the provinces. The analysis shows that the cultural and civilizational type of the borderlands, characterized by a relatively low share of the titular ethnic group in the structure of the population, requires that this factor be taken into account as one of the key factors in the implementation of investment projects and integrated projects for the development of such territories. Unlike those for border areas with a relatively homogeneous population structure (spatial-economic type of border areas) with a predominance of the titular ethnic group, it is possible to limit oneself to standard approaches to stimulating economic activity and economic growth. From this point of view, the experience of developing the Tibetan and Xinjiang Uygur Autonomous Regions of China may be relevant for solving the problems of the development of Russia's ethnic borderlands.
THE MARKET OF SPA SERVICES: PROBLEMS AND PROSPECTS OF DEVELOPMENT
Authors: Balashova S. P.
Published: November 2022

The sanatorium complex is a promising and significant component of the social and economic spheres of the state. The activities of its organizations are directly related both to participation in the process of preserving the health of the population, and the formation of the gross domestic product, ansuring effective employment, and increasing incomes at all levels.

The quality and variety of health resort services provided must correspond to the first-class level that is necessary to meet the needs of citizens. The expansion of the complex of sanatorium-resort organizations and the improvement of the quality of the services they provide will promote natural competition between them, which will have a positive impact on the market in this area in the future.

In the article analyzes the state of the health resort complex in Russia and its further development. Problems and specific features of the market of sanatorium and resort services are revealed, the structure of their regional market is characterized. The main tendencies of the market of sanatorium-and-spa services are determined.
HARMONIZATION OF THE GOALS OF SUSTAINABLE DEVELOPMENT OF THE DAIRY INDUSTRY
Authors: Borisova O. V. , Butakova M. M. , Goryaninskaya O. А.
Published: November 2022

The article is devoted to a problem that is relevant for many countries of the world — ensuring food security. In the Russian Federation, ensuring food security must be carried out simultaneously with the development of exports of agricultural products. The purpose of the author's research is to assess the possibilities and identify the problems of the dairy industry's participation in solving the tasks of ensuring food security and export development. The article reflects the results of a study of the dairy industry in the Siberian Federal District. Based on the indicators of domestic databases, the authors investigated the dynamics, product and territorial structure of production, export and import of dairy products for 2014-2020. The established trends, regional peculiarities of dairy products consumption are revealed, the opportunities, risks and prospects of Siberian exports are assessed from the perspective of sustainable development of the dairy industry. Based on the materials of the analysis and review of the scientific discussion on the problems of implementing the Food Security Doctrine of the Russian Federation, the authors identify the main directions of innovative development of the industry and its state support. The scientific novelty lies in the justification of the need for strategic planning of sustainable development of the dairy industry on the basis of harmonization of the goals of food supply of the population and export-oriented and import-substituting development strategies. The results of the research reflected may be of interest to representatives of government bodies, heads of the dairy industry, representatives of the scientific community, students and postgraduates dealing with similar issues.
THE USE OF INFORMATION AND COMMUNICATION TECHNOLOGIES IN ORGANIZATIONS TAKING INTO ACCOUNT THEIR REGIONAL DEPLOYMENT
Authors: Pinkovetskaia I. S.
Published: November 2022

In the twenty-first century, there was an explosive development of information and communication technologies that affected all spheres of people's lives and especially organizations. The purpose of our study was to evaluate the indicators characterizing the use of four types of information and communication technologies, namely big data analysis, data mining, cloud computing and the Internet of Things by organizations located in Russian regions. The official information of the Federal State Statistics Service of Russia for 2020 was used as empirical data. Empirical data modeling was based on the density functions of the normal distribution. The main attention in the study paid to the regional peculiarities of the use of the technologies in question by organizations. The results of the work showed that these types of technologies have received significant development in Russia. Big data analysis and cloud computing have become the most widespread among the four technologies under consideration. In the process of comparative analysis, lists of regions were compiled in which organizations were located, differing in the maximum and minimum values of indicators.
TAX HARMONIZATION AND ITS IMPACT ON ECONOMIC GROWTH IN THE EURASIAN ECONOMIC UNION COUNTRIES
Authors: Fedotov D.Yu.
Published: November 2022

A study of the level of tax harmonization in the countries of the Eurasian Economic Union has been carried out. The points of view of various authors on the problems of tax harmonization and tax competition are considered. The objectives of the study are to assess the degree of tax harmonization of the EAEU countries, as well as to analyze the impact of tax harmonization on economic growth. The study used econometric methods of macroeconomic analysis. It has been established that despite the rather long time that has elapsed since the creation of a single economic union, tax harmonization has not taken place in the EAEU countries. The size of the main tax rates in the EAEU countries differs significantly. The highest level of tax burden is in Armenia. The least time is needed to prepare and pay taxes in Russia. The smallest share of income tax in the total profit of companies is paid by Kyrgyz taxpayers. In turn, the lack of tax harmonization in the EAEU creates preconditions for tax competition between countries, associated with the creation of attractive conditions for taxpayers who will be ready to transfer their business to the country with a more favorable tax regime. As a result of the study, it was found that in conditions of tax competition, Russia and Kazakhstan are in the most advantageous position. The study revealed the negative impact on economic growth of a high tax burden and a significant length of time required for the calculation and payment of taxes. A close correlation has been established between total tax revenues and the growth of the economies of the EAEU countries.
HERITAGE ASSETS: RECONHECIMENTO, MENSURAÇÃO E EVIDENCIAÇÃO EM MUSEUS
Authors: Pires Charline , Niyama Jorge Katsumi , Beuren Ilse Maria , Ott Ernani
Published: November 2022

Objetivos: O estudo objetiva investigar a forma como os heritage assets são reconhecidos, mensurados e evidenciados pelos museus.

Método: Uma pesquisa documental foi realizada com abordagem quantitativa. Analisaram-se as demonstrações contábeis de 42 museus australianos, 25 neozelandeses e 171 ingleses, totalizando uma amostra de 238 entidades. Os dados foram analisados considerando-se as dimensões definidas conforme os itens apresentados das normas AASB 116, PBE IPSAS 17 e FRS 102.

Resultados: Os resultados da análise documental revelaram a adoção de diferentes práticas, seja quando observados os museus de um mesmo país, ou quando da comparação entre os países. Na Austrália predominaram museus que capitalizam seus heritage assets de forma plena, enquanto que no Reino Unido a maioria dos museus adotou a abordagem mista ou não reconheceram esses ativos. A Nova Zelândia, por sua vez, apresenta um cenário intermediário, com entidades divididas entre essas duas possibilidades.

Contribuições: O estudo contribui para a compreensão dos limites de aplicação dos padrões vigentes, levando a reflexões sobre os tratamentos mais adequados no contexto das organizações investigadas.

Palavras-chave: Heritage assets. Reconhecimento. Mensuração. Evidenciação.
(IN)COMPREENSIBILIDADE DAS DEMONSTRAÇÕES FINANCEIRAS DOS MUNICÍPIOS BRASILEIROS PELOS USUÁRIOS EXTERNOS
Authors: Camacho Eliane Utrabo , Weffort Elionor Farah Jreige , Garcia Alexandre Sanches , Gonçalves Andreá de Oliveira
Published: November 2022

Objetivo: O estudo analisa as variáveis associadas à compreensibilidade das demonstrações financeiras do setor público a partir da percepção dos usuários externos das informações. 

Método: Foram selecionadas variáveis associadas à compreensibilidade e desenvolvido um questionário eletrônico que permitisse observá-las.  Foram obtidas 415 respostas válidas em uma amostra de cidadãos brasileiros. A análise foi realizada de forma qualitativa e quantitativa por meio de teste de relações entre as variáveis, em especial, análise confirmatória.

Resultados: Apontaram relações estatisticamente significativas entre a compreensibilidade das demonstrações e as variáveis: grau de escolaridade, formação acadêmica, ocupação e autoavaliação em conhecimento sobre a contabilidade do setor público. Foi encontrada ainda relação entre a legibilidade, medida pelo teste de Flesch, o grau de escolaridade do respondente e a compreensibilidade das informações, corroborando com a literatura sobre este tema, ainda que majoritariamente voltada aos relatórios de entidade do setor privado.

Contribuições: O estudo preenche uma lacuna na literatura nacional e internacional sobre compreensibilidade das informações contábeis, precipuamente na esfera pública e apresenta como principais contribuições: (i)  para pesquisas futuras oferece um instrumento para coleta de dados (questionário) inédito, calcado em sólido arcabouço teórico e validado por uma ampla amostra; (ii) achados inéditos sobre variáveis relacionadas à compreensibilidade não abrangidos ainda em outras pesquisas para o setor público; (iii) evidências que provocam uma reflexão junto ao poder público e à comunidade sobre a necessidade de melhoria na forma de divulgação e comunicação das informações do setor público, bem como, identifica caminhos para tal.
DOES TAX AVOIDANCE DIFFER BETWEEN ECONOMIES AND SECTORS? DETERMINANTS OF TAX AVOIDANCE IN DEVELOPED AND EMERGING ECONOMIES
Authors: Cabello Otavio Gomes , Watrin Christoph , Moraes Marcelo Botelho da Costa
Published: November 2022

Purpose
This study aims to examine whether tax avoidance determinants result in different levels of avoidance depending on the country and sector. Prior literature finds that firms in developed countries avoid taxes (Dyreng et al. 2008, 2017). However, the level of tax avoidance differs across developed economies (Lee and Swenon, 2012; Thomsen and Watrin, 2018). In emerging economies, there are few studies that investigate tax planning and the results are not always in line with developed economies.
Design/methodology/approach
We expect that the extent of tax avoidance also differs between developed and emerging economies. We use a sample of firms from major economies (IMF, 2018), the G7 countries, and firms from major emerging economies, called BRICS (Brazil, Russia, India, China, and South Africa). We use a panel data multilevel analysis.
Findings
We find that the country and sector can influence tax avoidance practices to some extent and must be considered in the decision-making process regarding companies’ new international investments. It is also possible to observe that some determinants of tax avoidance do not yield different tax avoidance levels across countries and sectors.
Originality
This study fills a gap in the tax avoidance literature, showing that tax avoidance determinants may not accurately predict tax avoidance behaviour, depending on the country, industry, and level of regulatory enforcement.
Fabrication and Characterization of an Active Nanocomposite Film based on Polystyrene/ Thyme/Nano ZnO for Food Packaging
Authors: Thirugnanasambandan Theivasanthi , Kumar Thiagamani Senthil Muthu , Natarajan Hariram , Siengchin Suchart , Rangappa Sanjay Mavinkere
Published: November 2022

The main objective of this research is to develop an active antifungal packaging material utilizing polystyrene as the matrix material with active agents. The uniqueness of this study lies in the use of thyme extract as a reducing agent in the green synthesis of zinc oxide nanoparticles. The nanocomposite film was fabricated by impregnating zinc oxide nanoparticles in polystyrene. The nanocomposite films were characterized using XRD, FTIR, SEM and antifungal testing. The crystallite size of the synthesized ZnO NPs was observed to be in the 20–30 nm range. The FTIR spectra revealed the presence of ZnO NPs at the peak of 1000 cm–1. The morphological analysis showed the nanoparticles having a spherical shape. The results indicated that nanocomposite films exhibited excellent resistance against the fungus viz., Pencillum sp, Nigrospora oryzae and Chaetomium oryzae. The development of such active packaging materials with nanoparticles to preserve food grains will pave the way for a new technological path in food packaging applications.
ENTREPRENEURIAL RESOURCES AND ENGAGEMENT OF AFRICAN ACADEMICS: EVIDENCE FROM NIGERIA
Authors:   University of Lagos, Odetunde Oladimeji J.
Published: November 2022

The objective of this study is to empirically examine African academics' entrepreneurial resources and engagement using a leading Nigerian university in order to evaluate the speculation that African academics lack entrepreneurial capabilities to engage in knowledge discovery and commercialisation, as well as to develop an understanding of the entrepreneurship gap in African universities. A cross-sectional survey and validated scales were used to collect data from 298 randomly selected academics from the university's 79 departments and 12 faculties. Descriptive and inferential analyses using mean scores and standard deviations of academics on the study variables, as well as regression analysis, were conducted to test the hypotheses. Contrary to expectations, academics have the necessary entrepreneurial resources to engage in entrepreneurial activities, but as speculated, the level of their entrepreneurial engagement is low. The study adds to the body of knowledge on academic entrepreneurship and makes recommendations to improve African academic entrepreneurial engagement. The limitations of the study and future research directions were discussed.
Textile Fabric Defect Detection Based on Improved Faster R-CNN
Authors: He Dongfang , Wen Jiajun , Lai Zhihui
Published: November 2022

To identify and locate industrial textile defects accurately, this study proposes a textile detection model based on a convolution neural network (CNN) known as Faster R-CNN. First, a textile defect feature map was extracted by ResNet-101 deep convolution network. Faster R-CNN only extracts features from the last layer of the feature map, which leads to a loss of low-level location information. The proposed method adds the feature pyramid network (FPN) to the network architecture to make an independent prediction for each level in the feature extraction stage. The extracted feature map is input into the regional proposal network, among which the overlapping regional proposals are suppressed. The proposed improved Faster R-CNN model with Region Proposal Network (RPN), Soft Non-Maximum Suppression (NMS), and Region of Interest (ROI) Align can achieve a detection accuracy of 98% and an mean of Average Precision (mAP) of 85%, which is more competitive than the state-of-the-art deep learning-based object detection algorithms.
Differences in Calves’ Shape and Circumference Profiles between Chinese Males and Females
Authors: Xi Wang , Xia Guo , Xiaoming Tao , Qiao Li
Published: November 2022

Functional garments are required to be closely and properly fitted on diverse human limbs. However, most manufacturers classify their products based on a number of anthropometric statistical parameters of Caucasian body sizes. This work focuses on the diversities in the real curved shapes, and their detailed anatomy characteristics, for Chinese people. Differences in the 3D-scanned human calves’ shapes and circumference profiles between Chinese male and female subjects were identified through primary component analysis, extracted, and compared. Results show that calves of males were longer in length, straighter, and had a larger circumference within the belly of gastrocnemius, while females were found to have shorter overall length, more bent, and had a smaller gastrocnemius. Females had a larger averaged circumference. The focus of this study was on the size design of compression stockings.
How to Transfer Strided Data into Accelerator
Authors: Gan Xinbiao , Wang Zhiying
Published: November 2022

Data transfer from a host central processing unit (CPU) into an accelerator is a performance bottleneck for applications accelerated by accelerators (such as general purpose digital signal processing (GPDSP), many integrated core (MIC), and general purpose graphics processing unit (GPGPU)). It is complicated and inefficient to transfer non-contiguous data with special respect to strided data. In this work, we present three approaches to transfer strided data for different scenarios: Redundant copy (RC), selective copy (SC), and transfer after transformed (TaT). We propose a space and time efficient method named TaT, in which strided data are transformed on the CPU first and then transferred into the accelerator. We simulated regions-of-interest (ROI) coding and validate proposed techniques. TaT was superior to RC on space efficiency and close to SC on saving space, but better than SC on time waste respectively.
Feature Norm-Based Deep Network for Multi-Domain Fashion Image Retrieval
Authors: Zou Xingxing , Wong Wai Keung , Qian Jianjun
Published: November 2022

Current fashion image searching technology based on fine-grained fashion recognition on fashion images has recently achieved great success in online shopping. However, this technique is limited to a single domain—real product images—and thus is inflexible. Recognition and search performance are degraded to a large extent when the distribution of the target data is different from the source training data. To improve the flexibility of fashion image retrieval, we propose multi-domain fashion image recognition in this work. We firstly established Fashion-DA, a large-scale fashion dataset comprising 14 fashion categories and a total of 13,435 images originating from three domains. Then, we propose an unsupervised domain adaption approach based on adaptive feature norm to handle data with different feature distributions. The experiment evaluated the effectiveness of the proposed method.
A New Method Based on Deep Convolutional Neural Networks for Object Detection and Classification
Authors: Liu Yan , Zhuxngjie Zhu , Zhang Qiuhui , Ding Xiaotian , Wang Ruonan , Han Senyao , Li Chi
Published: November 2022

Accurate object detection and classification has a broad application in industrial tasks, such as fabric defect and invoice detection. Previous state-of-the-art methods such as SSD and Faster-RCNN usually need to carefully adjust anchor box related hyper parameters and have poor performance in special fields with large object size/ratio variations and complex background texture. In this study, we proposed a new accurate, robust, and anchor-free method to handle automatic object detection and classification problems. First, we used the feature pyramid network (FPN), to merge the feature maps of different scales of features extracted from a convolutional neural network (CNN), which allowed easy and robust multi-scale feature fusion. Second, we built two subnets to generate candidate region proposals from the FPN outputs. followed by another CNN that determined the categories of the proposed regions from the two subnets.
Symmetrical Robust Canonical Correlation Analysis for Image Classification
Authors: Wang Wenjing , Lu Yuwu , Lai Zhihui
Published: November 2022

Canonical correlation analysis (CCA) is a useful technique for multivariate data analysis, which can find correlations between two sets of multidimensional data. CCA projects two sets of data into a low-dimensional space in which the correlations between them are maximized. However, CCA is sensitive to noise or outliers in the collected data of real-world applications, which will degrade its performance. To overcome this disadvantage, we propose symmetrical robust canonical correlation analysis (SRCCA) for image classification. By using low-rank learning, the noise is removed, and CCA is used to encode correlations between images and their symmetry samples. To verify effectiveness, four public image databases were tested. The result was that SRCCA was more robust than CCA and had good performance for image classification.
Method of Metal Button Defect Detection Based on Extreme Learning Machine and Sparse Representation
Authors: Li Xiang , Xu Leilei , Liu Xunhua , Sun Shaoyuan
Published: November 2022

We studied the algorithms of button defect detection, while metal button defect detection is seldom explored in the literature. In this paper, we propose to effectively improve the detecting speed, accuracy, and robustness of the model. We propose a new method of cascading Extreme Learning Machine (ELM) and Sparse Representation Classification (SRC). This method transforms the defect detection problem into a pattern classification problem. First, we preprocess the input button images via eliminating reflection, edges extraction, and dimensionality reduction. ELM has a faster learning speed and better detecting accuracy than the single layer perceptron and support layer machine. ELM was utilized to estimate the probability of the defective buttons, with parameters obtained from the five-fold cross-validation method. SRC was used to reclassify those button images with high noise. Our method improved the detection accuracy, as well as guaranteed the detecting speed. We showed state-of-the-art performance in comparison to other approaches.
Finite Element-Based Machine Learning Method to Predict Breast Displacement during Running
Authors: Liang Ruixin , Yip Joanne , Yu Winnie , Chen Lihua , Lau Newman
Published: November 2022

This paper presents an effective method to simulate the dynamic deformation of the breasts when a sports bra is worn during physical activity. A subject-specific finite element (FE) model of a female subject is established, and the accuracy of the material coefficients of the model is analyzed. An FE model of the sports bra is also built based on a commercially-available compression sports bra with a vest style. Then, an FE contact model between the body and bra is developed and validated, and the results applied to train a neural network model for predicting breast displacement based on bra straps with different tensile moduli. In this study, a four-layer neural network with a backpropagation algorithm (a Levenberg-Marquardt learning algorithm) is used. A comparison of the FE and machine learning results shows that machine learning can well predict the dynamic displacement of the breasts in a more time-efficient and convenient manner.
ASPEK PERLINDUNGAN MASYARAKAT SEBAGAI SARANA KEEFEKTIFAN SANKSI PIDANA BAGI PELAKU USAHA DI BIDANG METROLOGI LEGAL
Authors: Megawati Wenny , Rochmani Rochmani , Khasanah Dian Ratu Ayu Uswatun
Published: November 2022

Undang-Undang Nomor 2 Tahun 1981 tentang Metrologi Legal dimana pelakunya adalah pelaku usaha yang dengan sengaja melakukan perbuatan curang dalam alat ukur/takar/timbang dan perlengkapannya. Metode yang digunakan adalah penelitian hukum yuridis empiris. Hasil penelitian mekanisme pengaduannya melalui balai metrologi dinas perindustrian dan perdagangan yang kemudian akan ditindaklanjuti menggunakan pengawasan dan pembinaan oleh PPNS. Dari hasil tersebut didapat hasil adanya temuan kecurangan atau tidak. Keefektifan suatu peraturan perundang-undangan terjadi apabila undang-undang tersebut melihat dari segi aspek kepentingan masyarakat, sehingga suatu pidana dibidang metrologi legal bisa efektif jika pidana tersebut sebanyak mungkin dapat mencegah atau mengurangi para pelaku usaha melakukan kejahatan perbuatan curang. Sehingga kriteria keefektifan suatu undang-undang dilihat dari seberapa jauh frekuensi kejahatan itu dapat ditekan, baik secara kuantitatif maupun secara kualitatif.
Delayed Spontaneous Pneumothorax in a Previously Healthy Nonventilated COVID-19 Patient
Authors: Zahornacký Ondrej , Porubčin Štefan , Rovňáková Alena , Jarčuška Pavol
Published: November 2022

Spontaneous pneumothorax is a serious and life-threatening complication of SARS-CoV-2 pneumonia. It most commonly occurs during the acute phase of the disease in patients with pre-existing lung disease (e.g. emphysema, bronchiectasis, cystic fibrosis, etc.) and in patients who require oxygen supplementation in any form (low-flow oxygen therapy, high-flow non-invasive or mechanical invasive or mechanical invasion). A rare case of a 52-year-old patient with a spontaneous pneumothorax who developed four weeks after PCR SARS-CoV-2 positivity was described. Interestingly, the patient did not have any factors that the literature considered risky for the development of this complication. During the acute phase of the disease, his condition did not require hospitalization. Imaging examinations could not clarify the cause of pneumothorax. With this case report, we want to point out the fact that spontaneous pneumothorax, as a rare and life-threatening complication of COVID-19 infection, may develop during recovery, and it is necessary to think about this complication in the differential diagnosis of dyspnoea.
Editorial
Authors: Šír Jan , Filipová Lucie , Vykoukal Jiří
Published: November 2022

Editorial
‘It’s not so scary anymore. It’s actually exhilarating’: A proof-of-concept study using virtual reality technology for music performance training under pressure
Authors: Osborne Margaret , Glasser Solange , Loveridge Ben
Published: November 2022

Extended lockdowns associated with the COVID-19 pandemic severely ruptured the capacity of performing artists to connect with peers and colleagues in professional and educational contexts. In this study we test a protocol for the use of immersive performance technologies in tertiary institutions to provide developing and early career musicians to connect with pedagogues and access safe, realistic spaces within which to practice performing under varying degrees of pressure. We investigated the affordances of a VR environment to trigger performance anxiety, and the effectiveness of a synchronous digitally mediated environment for tertiary educators to train a key performance psychology skill. Heart rate, self-reported anxiety and confidence measurements were taken over four levels of situational stress and performance demands. Results revealed that the technology enabled a pre-performance routine to be effectively taught online by an instructor to a musician wearing a VR headset. Notably, this was achieved by both participants being in separate locations without detriment to the teacher-student relationship. This study provides encouraging insight into the capacity for immersive technologies to help students effectively manage the stresses of live performance in both virtual and real worlds.
Turn-it-out? Reframing the Academic Integrity Conversation in Online Legal Education
Authors: Bailey Kim , Kalache Lachlan , Acheson Rebecca
Published: November 2022

The challenge of academic integrity in online study is not a new phenomenon. For undergraduate law students, a finding of academic misconduct is especially serious, having ramifications for student eligibility to be admitted to legal practice. To date, higher education strategies to address plagiarism, contract cheating, and collusion have predominantly focused on detection methodology / technology via assessment. Reconceptualising the challenge of academic integrity in online learning requires an iterative understanding of the motivations of online learners, informed by the unique engagement challenges associated with adult online learning.  Arguably, the ‘battle’ for integrity can never be won via increased detection and punitive measures; rather a focus on fostering student desire to act with integrity, by helping learners to connect academic integrity with their emerging professional identity is key. This connection must be supported by profession-facing teaching and assessment design, with facilitated learning relationships that build skills and confidence.