bluuebunny/crossref_metadata_2025 huggingface dataset:
Closed-Form Solution and Experimental Verification for the Axisymmetric Deformation Problem of Blistering Circular Thin Polymer Films under Uniformly Distributed Gas Pressure
Authors: Yang Zhi-Xin , He Xiao-Ting , Wen Si-Rui
Published: May 2020

The existing studies indicate that the measurement formulas used in blister test techniques, which are used to measure the mechanical properties of thin-film/substrate systems, are usually given based on an approximation—that is, the applied direction of the uniformly distributed transverse load is always vertical, while the applied direction of the uniformly distributed gas pressure is always perpendicular to the surface of the thin film. This approximation will lead to a large measurement error. In this study, we obtained the analytical solution to the problem of axisymmetric deformation of blistering circular thin polymer films under the action of uniformly distributed gas pressure via the power series method. An example is given to illustrate the error caused by the approximation mentioned above, and the validity of the solution presented here is verified. The result shows that the chance of error caused by the approximation increases with the increase in the applied load, and it far exceeds the allowable error of measurement when the applied load is relatively large. In addition, the related experiments of the blistering circular thin polymer film under uniformly distributed gas pressure are carried out, and the experimental results are compared with the theoretical results. The comparison results show that the analytical solution given in this paper is correct. The solution presented here is of great significance to improve the measurement accuracy of the blister test technique.
Numerical Simulation for the Combustion Chamber of a Reference Calorimeter
Authors: González-Durán José Eli Eduardo , Zamora-Antuñano Marco Antonio , Lira-Cortés Leonel , Rodríguez-Reséndiz Juvenal , Olivares-Ramírez Juan Manuel , Lozano Néstor Efrén Méndez
Published: May 2020

This paper focuses on the numerical modeling of the effect of the height of a combustion chamber on the development of a reference calorimeter whose objective is to measure the calorific value of natural gas. The impacts of temperature, velocity, and mass fraction on the exhaust gases were evaluated by varying the height of the combustion chamber. The eddy dissipation concept (EDC) approach was used to model combustion with two different chemical kinetic mechanisms: one with three steps, called the three-step mechanism defined by default in the software used, and second skeletal model, which consists of 41 steps, through the ChemKin-import file with 16 species. The main result of this study is the selection of a combustion chamber height for the reference calorimeter that produces the best performance in the combustion process, which is 70 mm, as well as the main differences in using a three-step mechanism and a skeletal model to simulate an oxy-fuel combustion reaction.
Assessment of Supply Chain Agility to Foster Sustainability: Fuzzy-DSS for a Saudi Manufacturing Organization
Authors: Rehman Ateekh Ur , Al-Zabidi Ayoub , AlKahtani Mohammed , Umer Usama , Usmani Yusuf Siraj
Published: May 2020

Supply chain agility and sustainability is an essential element for the long-term survival and success of a manufacturing organization. Agility is an organization’s ability to respond rapidly to customers’ dynamic demands and volatile market changes. In a dynamic business environment, manufacturing firms demand agility to be evaluated to support any alarming decision. Sustainability is an aspect to sustain collaboration, value creation, and survival of firms under a dynamic competitive business scenario. Agility is a capability that drives competitiveness to foster sustainability aspects. The purpose of this article is to consider and evaluate the supply chain behavior within the context of Saudi enterprises. The efficacy and relevance of this model were explored through a case study conducted in a Saudi dairy manufacturing corporation. Owing to the complexity and a large number of calculations that are required for evaluating the agility of the supply chain, a decision support system was proposed as a tool to assess the supply chain and identifying barriers to a strategic sustainable solution for a specific organizational target. The decision support system is extensive as it contains six separate agility enablers and ninety-three agility attributes for the supply chain. The assessment was carried out using a fuzzy multi-criteria method. It combines the performance rating and importance weight of each agile supply chain-enabler-attribute. To achieve and sustain local and global success, the case organization strove to become a major local and global manufacturer to satisfy its customers, reduce its time to market, lower its total ownership costs, and boost its overall competitiveness through improving its agility across supply chain activities to foster sustainability for a manufacturing organization located in Saudi Arabia.
Identification and Analysis of Microscale Hydrologic Flood Impacts Using Unmanned Aerial Systems
Authors: Dyer Jamie L. , Moorhead Robert J. , Hathcock Lee
Published: May 2020

The need for accurate and spatially detailed hydrologic information is critical due to the microscale influences on the severity and distribution of flooding, and new and/or updated approaches in observations of river systems are required that are in line with the current push towards microscale numerical simulations. In response, the aim of this project is to define and illustrate the hydrologic response of river flooding relative to microscale surface properties by using an unmanned aerial system (UAS) with dedicated imaging, sensor, and communication packages for data collection. As part of a larger project focused on increasing situational awareness during flood events, a fixed-wing UAS was used to overfly areas near Greenwood, MS before and during a flood event in February 2019 to provide high-resolution visible and infrared imagery for analysis of hydrologic features. The imagery obtained from these missions provide direct examples of fine-scale surface features that can alter water level and discharge, such as built structures (i.e., levees and bridges), natural storage features (low-lying agricultural fields), and areas of natural resistance (inundated forests). This type of information is critical in defining where and how to incorporate high-resolution information into hydrologic models and also provides an invaluable dataset for eventual verification of hydrologic simulations through inundation mapping.
SemImput: Bridging Semantic Imputation with Deep Learning for Complex Human Activity Recognition
Authors: Razzaq Muhammad Asif , Cleland Ian , Nugent Chris , Lee Sungyoung
Published: May 2020

The recognition of activities of daily living (ADL) in smart environments is a well-known and an important research area, which presents the real-time state of humans in pervasive computing. The process of recognizing human activities generally involves deploying a set of obtrusive and unobtrusive sensors, pre-processing the raw data, and building classification models using machine learning (ML) algorithms. Integrating data from multiple sensors is a challenging task due to dynamic nature of data sources. This is further complicated due to semantic and syntactic differences in these data sources. These differences become even more complex if the data generated is imperfect, which ultimately has a direct impact on its usefulness in yielding an accurate classifier. In this study, we propose a semantic imputation framework to improve the quality of sensor data using ontology-based semantic similarity learning. This is achieved by identifying semantic correlations among sensor events through SPARQL queries, and by performing a time-series longitudinal imputation. Furthermore, we applied deep learning (DL) based artificial neural network (ANN) on public datasets to demonstrate the applicability and validity of the proposed approach. The results showed a higher accuracy with semantically imputed datasets using ANN. We also presented a detailed comparative analysis, comparing the results with the state-of-the-art from the literature. We found that our semantic imputed datasets improved the classification accuracy with 95.78% as a higher one thus proving the effectiveness and robustness of learned models.
Validity of a Fully-Immersive VR-Based Version of the Box and Blocks Test for Upper Limb Function Assessment in Parkinson’s Disease
Authors: Oña Edwin Daniel , Jardón Alberto , Cuesta-Gómez Alicia , Sánchez-Herrera-Baeza Patricia , Cano-de-la-Cuerda Roberto , Balaguer Carlos
Published: May 2020

In recent decades, gaming technology has been accepted as a feasible method for complementing traditional clinical practice, especially in neurorehabilitation; however, the viability of using 3D Virtual Reality (VR) for the assessment of upper limb motor function has not been fully explored. For that purpose, we developed a VR-based version of the Box and Blocks Test (BBT), a clinical test for the assessment of manual dexterity, as an automated alternative to the classical procedure. Our VR-based BBT (VR-BBT) integrates the traditional BBT mechanics into gameplay using the Leap Motion Controller (LMC) to capture the user’s hand motion and the Oculus Rift headset to provide a fully immersive experience. This paper focuses on evaluating the validity of our VR-BBT to reliably measure the manual dexterity in a sample of patients with Parkinson’s Disease (PD). For this study, a group of twenty individuals in a mild to moderate stage of PD were recruited. Participants were asked to perform the physical BBT (once) and our proposed VR-BBT (twice) system, separately. Correlation analysis of collected data was carried out. Statistical analysis proved that the performance data collected by the VR-BBT significantly correlated with the conventional assessment of the BBT. The VR-BBT scores have shown a significant association with PD severity measured by the Hoehn and Yahr scale. This fact suggests that the VR-BBT could be used as a reliable indicator for health improvements in patients with PD. Finally, the VR-BBT system presented high usability and acceptability rated by clinicians and patients.
Indoor Localization Based on VIO System and Three-Dimensional Map Matching
Authors: Zhang Jitong , Ren Mingrong , Wang Pu , Meng Juan , Mu Yuman
Published: May 2020

High-precision indoor localization plays a vital role in various places. In recent years, visual inertial odometry (VIO) system has achieved outstanding progress in the field of indoor localization. However, it is easily affected by poor lighting and featureless environments. For this problem, we propose an indoor localization algorithm based on VIO system and three-dimensional (3D) map matching. The 3D map matching is to add height matching on the basis of previous two-dimensional (2D) matching so that the algorithm has more universal applicability. Firstly, the conditional random field model is established. Secondly, an indoor three-dimensional digital map is used as a priori information. Thirdly, the pose and position information output by the VIO system are used as the observation information of the conditional random field (CRF). Finally, the optimal states sequence is obtained and employed as the feedback information to correct the trajectory of VIO system. Experimental results show that our algorithm can effectively improve the positioning accuracy of VIO system in the indoor area of poor lighting and featureless.
A Sustainable Quantitative Stock Selection Strategy Based on Dynamic Factor Adjustment
Authors: Fu Yi , Cao Shuai , Pang Tao
Published: May 2020

In this paper, we consider a sustainable quantitative stock selection strategy using some machine learning techniques. In particular, we use a random forest model to dynamically select factors for the training set in each period to ensure that the factors that can be selected in each period are the optimal factors in the current period. At the same time, the classification probability prediction (CPP) of stock returns is performed. Historical back-testing using Chinese stock market data shows that the proposed CPP quantitative stock selection strategy performs better than the traditional machine learning stock selection methods, and it can outperform the market index over the same period in most back-testing periods. Moreover, this strategy is sustainable in all market conditions, such as a bull market, a bear market, or a volatile market.
Projection of Wind Energy Potential over Northern China Using a Regional Climate Model
Authors: Chen Zhuo , Li Wei , Guo Junhong , Bao Zhe , Pan Zhangrong , Hou Baodeng
Published: May 2020

With the purpose of achieving carbon emission reduction targets, the wind power industry has developed rapidly in recent years. Wind power is greatly affected by climate change, and the increase or decrease of wind speed directly affects wind energy production. Based on the numerical simulation results from a high-resolution (~ 25 km) regional climate model PRECIS, we analyze the changes of future wind speed and wind power potential in the "Three North" (TN) region in China. Firstly, we verify whether the PRECIS can capture the current spatiotemporal patterns in simulating the wind speed compared with observation (CN05.1). The results show PRECIS has a good ability in reproducing the spatiotemporal patterns of wind speed in the eastern part of the TN region, but still has great uncertainty in the northwest. In the future, the projected wind power density in the TN region will increase by about 0.7% in the middle of the 21st century, but will drop significantly in the end of the century (about −3.32%). Furthermore, Wind power density will increase significantly in winter. However, the wind speed in spring and summer will generally decrease. It is predicted that most of the Northwest (NW) and North (N) will have strong inter-annual variability in the middle of this century, and will be more stable at the end of this century. It should be noted that the potential of wind energy in Northeast (NE) will grow steadily in this century, which will have certain guiding significance for future wind power planning in this region.
Urban Niche Assessment: An Approach Integrating Social Media Analysis, Spatial Urban Indicators and Geo-Statistical Techniques
Authors: Bernetti Iacopo , Alampi Sottini Veronica , Bambi Lorenzo , Barbierato Elena , Borghini Tommaso , Capecchi Irene , Saragosa Claudio
Published: May 2020

Cities are human ecosystems. Understanding human ecology is important for designing and planning the built environment. The ability to respond to changes and adapt actions in a positive way helps determine the health of cities. Recently, many studies have highlighted the great potential of photographic data shared on the Flickr platform for the analysis of environmental perceptions in landscape and urban planning. Other research works used panoramic images from the Google Street View (GSV) web service to extract urban quality data. Although other researches have used social media to characterize human habitat from an emotional point of view, there is still a lack of knowledge of the correlation between environmental and physical variables of the city and visual perception, especially at a scale suitable for urban planning and design. In ecology, the environmental suitability of a territory for a given biological community is studied through species distribution models (SDM). In this work we have adopted the state of the art of SDM (the ensemble approach) to develop a methodology transferable to cities with different sizes and characteristics that uses data deriving from many sources available on a global scale: social media platform, Google internet services, shared geographical information, remote sensing and geomorphological data. The result of our application in the city of Livorno offers important information on the most significant variables for the conservation, planning and design of urban public spaces at the project scale. However, further research developments will be needed to test the model in cities of different sizes and geographic locations, integrate the model with other social media, other databases and with traditional surveys and improve the quality of indicators that can be derived from information shared on the Internet.
Modified Activated Carbon Fiber Felt for the Electrosorption of Norfloxacin in Aqueous Solution
Authors: Li Xianzhen , Hu Yue , She Diao , Shen Wei-Bo
Published: May 2020

As an antibiotic, Norfloxacin (NOR) is widely found in the water environment and presents considerable harm to human beings. At present, the preparation of removal materials is complicated, and the removal efficiency is not high. The adsorption effect of modified activated carbon fiber felt (MACFF) electrosorption and its influencing factors on NOR were studied. Activated carbon fiber felt (ACFF) was modified with 20% nitric acid, and the ACFFs were characterized by SEM, TEM, and FTIR both before and after modification. The optimal working conditions for electrosorption with an MACFF electrode were as follows: the voltage was 1.0 V, the pH was 6, and the plate spacing was 10 mm. The maximum adsorption capacity of the MACFF for NOR was 128.55 mg/g. Model fitting showed that pseudo-second-order kinetic model and Langmuir model were more suitable for explaining this adsorption process. In addition, this study found that, with 20% nitric acid as the regeneration liquid and under the reverse charging method, the regeneration rate of the MACFF electrode was maintained at approximately 96% and the regeneration was good, therefore, this technology can not only save operation costs but also has good development prospects in sewage treatment.
Migrants Workers and Processes of Social Inclusion in Italy: The Possibilities Offered by Social Farming
Authors: Giarè Francesca , Ricciardi Gabriella , Borsotto Patrizia
Published: May 2020

The agricultural sector, even though it has been greatly reduced and is in constant transformation, continues to be of strategic importance. Although it does not represent a quantitatively relevant employment sector, the dynamics are interesting because they reflect the structural, economic, and social transformations that are affecting the sector in recent years; there is a growing need for external labor that corresponds to a massive recourse of foreigners to work. Innovative approaches are required to explore the capacity of social farming to create a sustainable and inclusive workplace for migrants. The overall methodological approach of the paper seeks to synthesize fieldwork research and qualitative interviewing to validate the Italian inclusive model. To do this, we have selected four experiences of Italian social agriculture in which migrants are included.
A Bibliometric Analysis on No-Show Research: Status, Hotspots, Trends and Outlook
Authors: Wang Cheng , Wu Runhua , Deng Lili , Chen Yong , Li Yingde , Wan Yuehua
Published: May 2020

No-show is a thorny issue within the social scope. It not only affects the sustainability of service system operation but also causes heavy irretrievable losses. To maintain and develop the sustainability of service, this paper adopts bibliometric technology to reflect the current status and future prospects about no-show research. And we strive to explore and summarize appointment scheduling methods for no-show problems. The bibliometric analysis was carried out from various aspects including research areas, countries/regions, institutions, journals, authors and author keywords based on papers harvested from Web of Science Core Collection database. The total 1197 papers show that the United States is in a leading position in this field, followed by England and Canada. University of London is the most productive institution with the highest total citations and H-Index. BMC Health Services Research ranks first as the most productive journal, followed by European Journal of Operational Research and Production and Operations Management. Through the analysis of hot articles, we can conclude that how to reduce the impact of no-shows on the sustainability of service systems has become the main research direction. In addition to appointment scheduling, other effective methods are also mentioned. Further study on these methods will be a major research direction in the future.
Promoting Employability in Higher Education: A Case Study on Boosting Entrepreneurship Skills
Authors: Pardo-Garcia Cristina , Barac Maja
Published: May 2020

How can higher education increase the employability of university students? We present a case study on an innovative training itinerary aimed to promote the participation of teaching staff to stimulate the creativity of students and enhance their employability skills. Students acquire the entrepreneurship competences by applying the problem-solving methodology to their innovative projects based on sustainable development. The participation in the contest shows a growing importance, with topics ranging from the more technical ones, such as nutrition innovation, science innovation, or sustainability, to the social projects, related to social services, inclusion, or services against gender violence, harassment, and bullying. The percentage of multidisciplinary teams increased from 38% in 2015 to 76% in 2019 and even more in finalist teams, a positive trend in improving soft skills. According to some testimonies, the acquisition of these entrepreneurship competences partially compensates for students’ lack of professional experience by enriching their curriculum vitae (CV) and, for some students, lays the groundwork for establishing a real business after their participation in the contest.
Blockchain of Carbon Trading for UN Sustainable Development Goals
Authors: Kim Seong-Kyu , Huh Jun-Ho
Published: May 2020

Carbon credits should reduce the environmental pollution and carbon emission of the Earth in the future. The market for carbon credits will become a critical issue from 2021, and carbon credits will be applied to systems where individuals can trade. In order for these carbon credits to be traded between individuals, however, a corresponding exchange of carbon credits is needed. Policies, strategies, and technologies are also necessary to measure the trading of carbon credits. This paper aims at making transactions more reliable by applying blockchain technology to measure carbon emission rights. It uses blockchain to verify carbon emissions rights among the UN-SDGs’ (United Nations Sustainable Development Goals’) 17 tasks. In addition, it introduces the necessary dApp. In fact, we can protect against carbon emissions anomalies by using big data and artificial intelligence in mobile cloud environments. Thus, this paper proposes a blockchain-based carbon emission rights verification system to learn proven data further by using the governance system analysis and blockchain mainnet engine to solve these problems.
Multivariate Gamma Regression: Parameter Estimation, Hypothesis Testing, and Its Application
Authors: Rahayu Anita , Purhadi  , Sutikno  , Prastyo Dedy Dwi
Published: May 2020

Gamma distribution is a general type of statistical distribution that can be applied in various fields, mainly when the distribution of data is not symmetrical. When predictor variables also affect positive outcome, then gamma regression plays a role. In many cases, the predictor variables give effect to several responses simultaneously. In this article, we develop a multivariate gamma regression (MGR), which is one type of non-linear regression with response variables that follow a multivariate gamma (MG) distribution. This work also provides the parameter estimation procedure, test statistics, and hypothesis testing for the significance of the parameter, partially and simultaneously. The parameter estimators are obtained using the maximum likelihood estimation (MLE) that is optimized by numerical iteration using the Berndt–Hall–Hall–Hausman (BHHH) algorithm. The simultaneous test for the model’s significance is derived using the maximum likelihood ratio test (MLRT), whereas the partial test uses the Wald test. The proposed MGR model is applied to model the three dimensions of the human development index (HDI) with five predictor variables. The unit of observation is regency/municipality in Java, Indonesia, in 2018. The empirical results show that modeling using multiple predictors makes more sense compared to the model when it only employs a single predictor.
Gate Sizing Methodology with a Novel Accurate Metric to Improve Circuit Timing Performance under Process Variations
Authors: Perez-Rivera Zahira , Tlelo-Cuautle Esteban , Champac Victor
Published: May 2020

The impact of process variations on circuit performance has become more critical with the technological scaling, and the increasing level of integration of integrated circuits. The degradation of the performance of the circuit means economic losses. In this paper, we propose an efficient statistical gate-sizing methodology for improving circuit speed in the presence of independent intra-die process variations. A path selection method, a heuristic, two coarse selection metrics, and one fine selection metric are part of the new proposed methodology. The fine metric includes essential concepts like the derivative of the standard deviation of delay, a path segment analysis, the criticality, the slack-time, and area. The proposed new methodology is applied to ISCAS Benchmark circuits. The average percentage of optimization in the delay is 12%, the average percentage of optimization in the delay standard deviation is 27.8%, the average percentage in the area increase is less than 5%, and computing time is up to ten times less than using analytical methods like Lagrange Multipliers.
Psychosocial Implications of Large-Scale Implementations of Solar Power in Malaysia
Authors: Teoh Ai Ni , Go Yun Ii , Yap Tze Chuen
Published: May 2020

The present study aimed to investigate the psychosocial impacts of large-scale solar (LSS) power projects. There were 225 participants (n = 109 women, n = 3 did not indicate gender) participated in our study by completing a series of questionnaires. We found that participants who lived farther from the LSS power project location and those who viewed the project as being impactful were optimistic about the benefits LSS power projects could bring. Our participants also demonstrated support for renewable energy development in Malaysia. These findings may provide important implications for the implementation and execution of LSS power projects and policies.
Global Transmission, Spatial Segregation, and Recombination Determine the Long-Term Evolution and Epidemiology of Bovine Coronaviruses
Authors: Salem Elias , Dhanasekaran Vijaykrishna , Cassard Herve , Hause Ben , Maman Sarah , Meyer Gilles , Ducatez Mariette
Published: May 2020

Bovine coronavirus (BCoV) is widespread in cattle and wild ruminant populations throughout the world. The virus causes neonatal calf diarrhea and winter dysentery in adult cattle, as well as upper and lower respiratory tract infection in young cattle. We isolated and deep sequenced whole genomes of BCoV from calves with respiratory distress in the south–west of France and conducted a comparative genome analysis using globally collected BCoV sequences to provide insights into the genomic characteristics, evolutionary origins, and global diversity of BCoV. Molecular clock analyses allowed us to estimate that the BCoV ancestor emerged in the 1940s, and that two geographically distinct lineages diverged from the 1960s–1970s. A recombination event in the spike gene (breakpoint at nt 1100) may be at the origin of the genetic divergence sixty years ago. Little evidence of genetic mixing between the spatially segregated lineages was found, suggesting that BCoV genetic diversity is a result of a global transmission pathway that occurred during the last century. However, we found variation in evolution rates between the European and non-European lineages indicating differences in virus ecology.
Infectious Bronchitis Virus Regulates Cellular Stress Granule Signaling
Authors: Brownsword Matthew J. , Doyle Nicole , Brocard Michèle , Locker Nicolas , Maier Helena J.
Published: May 2020

Viruses must hijack cellular translation machinery to express viral genes. In many cases, this is impeded by cellular stress responses. These stress responses result in the global inhibition of translation and the storage of stalled mRNAs, into RNA-protein aggregates called stress granules. This results in the translational silencing of the majority of mRNAs excluding those beneficial for the cell to resolve the specific stress. For example, the expression of antiviral factors is maintained during viral infection. Here we investigated stress granule regulation by Gammacoronavirus infectious bronchitis virus (IBV), which causes the economically important poultry disease, infectious bronchitis. Interestingly, we found that IBV is able to inhibit multiple cellular stress granule signaling pathways, whilst at the same time, IBV replication also results in the induction of seemingly canonical stress granules in a proportion of infected cells. Moreover, IBV infection uncouples translational repression and stress granule formation and both processes are independent of eIF2α phosphorylation. These results provide novel insights into how IBV modulates cellular translation and antiviral stress signaling.
The Phylogeography of MERS-CoV in Hospital Outbreak-Associated Cases Compared to Sporadic Cases in Saudi Arabia
Authors: Chen Xin , Adam Dillon Charles , Chughtai Abrar Ahmad , Stelzer-Braid Sacha , Scotch Matthew , MacIntyre Chandini Raina
Published: May 2020

This study compared the phylogeography of MERS-CoV between hospital outbreak-associated cases and sporadic cases in Saudi Arabia. We collected complete genome sequences from human samples in Saudi Arabia and data on the multiple risk factors of human MERS-CoV in Saudi Arabia reported from 2012 to 2018. By matching each sequence to human cases, we identified isolates as hospital outbreak-associated cases or sporadic cases. We used Bayesian phylogenetic methods including temporal, discrete trait analysis and phylogeography to uncover transmission routes of MERS-CoV isolates between hospital outbreaks and sporadic cases. Of the 120 sequences collected between 19 June 2012 and 23 January 2017, there were 64 isolates from hospital outbreak-associated cases and 56 from sporadic cases. Overall, MERS-CoV is fast evolving at 7.43 × 10−4 substitutions per site per year. Isolates from hospital outbreaks showed unusually fast evolutionary speed in a shorter time-frame than sporadic cases. Multiple introductions of different MERS-CoV strains occurred in three separate hospital outbreaks. MERS-CoV appears to be mutating in humans. The impact of mutations on viruses transmissibility in humans is unknown.
Adaptation of H9N2 Influenza Viruses to Mammalian Hosts: A Review of Molecular Markers
Authors: Sun Xiangjie , Belser Jessica A. , Maines Taronna R.
Published: May 2020

As the number of human infections with avian and swine influenza viruses continues to rise, the pandemic risk posed by zoonotic influenza viruses cannot be underestimated. Implementation of global pandemic preparedness efforts has largely focused on H5 and H7 avian influenza viruses; however, the pandemic threat posed by other subtypes of avian influenza viruses, especially the H9 subtype, should not be overlooked. In this review, we summarize the literature pertaining to the emergence, prevalence and risk assessment of H9N2 viruses, and add new molecular analyses of key mammalian adaptation markers in the hemagglutinin and polymerase proteins. Available evidence has demonstrated that H9N2 viruses within the Eurasian lineage continue to evolve, leading to the emergence of viruses with an enhanced receptor binding preference for human-like receptors and heightened polymerase activity in mammalian cells. Furthermore, the increased prevalence of certain mammalian adaptation markers and the enhanced transmissibility of selected viruses in mammalian animal models add to the pandemic risk posed by this virus subtype. Continued surveillance of zoonotic H9N2 influenza viruses, inclusive of close genetic monitoring and phenotypic characterization in animal models, should be included in our pandemic preparedness efforts.
Acellular Pertussis Vaccine Components: Today and Tomorrow
Authors: Dewan Kalyan K. , Linz Bodo , DeRocco Susan E. , Harvill Eric T.
Published: May 2020

Pertussis is a highly communicable acute respiratory infection caused by Bordetella pertussis. Immunity is not lifelong after natural infection or vaccination. Pertussis outbreaks occur cyclically worldwide and effective vaccination strategies are needed to control disease. Whole-cell pertussis (wP) vaccines became available in the 1940s but have been replaced in many countries with acellular pertussis (aP) vaccines. This review summarizes disease epidemiology before and after the introduction of wP and aP vaccines, discusses the rationale and clinical implications for antigen inclusion in aP vaccines, and provides an overview of novel vaccine strategies aimed at better combating pertussis in the future.
A Novel Synonymous Mutation of SARS-CoV-2: Is This Possible to Affect Their Antigenicity and Immunogenicity?
Authors: Kim Sung-Jae , Nguyen Van-Giap , Park Yong-Ho , Park Bong-Kyun , Chung Hee-Chun
Published: May 2020

The S glycoprotein of coronaviruses is important for viral entry and pathogenesis with most variable sequences. Therefore, we analyzed the S gene sequences of SARS-CoV-2 to better understand the antigenicity and immunogenicity of this virus in this study. In phylogenetic analysis, two subtypes (SARS-CoV-2a and -b) were confirmed within SARS-CoV-2 strains. These two subtypes were divided by a novel synonymous mutation of D614G. This may play a crucial role in the evolution of SARS-CoV-2 to evade the host immune system. The region containing this mutation point was confirmed as a B-cell epitope located in the S1 domain, and SARS-CoV-2b strains exhibited severe reduced antigenic indexes compared to SARS-CoV-2a in this area. This may allow these two subtypes to have different antigenicity. If the two subtypes have different serological characteristics, a vaccine for both subtypes will be more effective to prevent COVID-19. Thus, further study is urgently required to confirm the antigenicity of these two subtypes.
Prevalence, Genotype Distribution, and Predictors against HPV Infections Targeted by 2-, 4-, 9-Valent HPV Vaccines among Japanese Males
Authors: Matsuzawa Yukimasa , Kitamura Tadaichi , Suzuki Motofumi , Koyama Yasuhiro , Shigehara Kazuyoshi
Published: May 2020

Objectives: Epidemiological reports of sexual life and human papilloma virus (HPV) infection among Japanese men are scarce, and the necessity of HPV vaccines for males is regarded as a controversial topic in Japan. The objective of this study is to determine the prevalence, genotype distribution, and risk factors against HPV infections targeted by bivalent (2v), quadrivalent (4v), and 9-valent (9v) HPV vaccines among Japanese male patients who visited our urological clinics. Material and Methods: The study population consisted of 798 males aged 20 to 95 years (mean ± standard deviation, 55.4 ± 19.5 years). We collected scraping samples from the glans penis using cotton swabs from all patients for genotyping of HPVs. We compared patients’ characteristics and detected HPV genotypes in order to determine the risk factors against HPV infections. Results: Of 798 participants, 198 participants (198/798; 24.8%) had at least one genotype of any HPV infection. The total number of detected HPV genotypes was 328. Of 328 genotypes, 30% (n = 99; 99/328) were 9v HPV genotypes. Most frequently detected types of high-risk HPV infection were type 52 (n = 40; 40/328; 12.2%). Number of lifetime sex partners (≥21) and present or history of sexually transmitted infections were found to be predictors of any HPV infection with adjusted odds ratios of 3.106 (95% confidence interval (CI), 1.593–6.509) and 1.894 (95% CI, 1.185–3.026), respectively. Age of sex initiation was a predictor of 2v and 4v HPV infections with adjusted odds ratios of 100 (95% CI, 1.013–25.673) and 2.676 (95% CI, 1.037–6.905), respectively. Number of lifetime sex partners (≥21) was a predictor of 9v HPVs with adjusted odds ratios of 2.397 (95% CI, 1.060–5.424). Conclusions: Approximately, a quarter of Japanese male patients who visited urological clinics were exposed to HPV. Moreover, from the perspective of our multivariate logistic regression analysis, some kinds of sexual behavior aggravate the risk of typical HPV genotypes infections.
Contamination of Surface Water and River Sediments by Antibiotic and Antiretroviral Drug Cocktails in Low and Middle-Income Countries: Occurrence, Risk and Mitigation Strategies
Authors: Kairigo Pius , Ngumba Elijah , Sundberg Lotta-Riina , Gachanja Anthony , Tuhkanen Tuula
Published: May 2020

Presence of antimicrobial cocktails in the hydrological cycles is of interest because of their potential to mediate antimicrobial resistance within the natural environment. In this study, we determined the concentrations of selected antibiotics and antiretroviral drugs (ARVDs) in wastewater treatment plant (WWTP) effluent, effluent suspended particulate matter (SPM), surface waters and river sediments in Kenya in order to determine the extent of pollution within the sampled environment. Target analysis for the most common antibiotics and ARVDs was done. Sulfamethoxazole (SMX), ciprofloxacin (CIP), trimethoprim (TMP), norfloxacin (NOR), zidovidine (ZDV), lamivudine (3TC) and nevirapine (NVP) were analyzed using LC-ESI-MS/MS. Effluent aqueous phase had concentrations ranging between 1.2 µg L−1 to 956.4 µg L−1 while the effluent SPM showed higher concentrations, ranging between 2.19 mg Kg−1 and 82.26 mg Kg−1. This study shows emission of active pharmaceutical ingredients (APIs) from WWTP to the environment mainly occurs via the SPM phase, which is usually overlooked in environmental analyses. Concentrations in surface waters and river sediments ranged between 1.1 µg L−1 to 228 µg L−1 and 11 µg Kg−1 to 4125 µg Kg−1 respectively. ARVDs occurred at consistently higher concentrations than antibiotics in both the aqueous and solid samples. The wastewater treatment plants and lagoons where sludge degradation should occur, are sources of active pharmaceutical ingredients (APIs) including transformational products, nutrients and organic matter that are released back to the aqueous phase.
Removal of Phosphate Ions from Aqueous Solutions by Adsorption onto Leftover Coal
Authors: Mekonnen Dereje Tadesse , Alemayehu Esayas , Lennartz Bernd
Published: May 2020

High loadings of wastewater with phosphors (P) require purification measures, which can be challenging to realize in regions where the technical and financial frame does not allow sophisticated applications. Simple percolation devices employing various kinds of adsorbents might be an alternative. Here, we investigated the application of leftover coal, which was collected from Ethiopian coal mining areas, as an adsorbent for the removal of phosphate from aqueous solutions in a classical slurry batch set-up. The combined effects of operational parameters such as contact time, initial concentration, and solution pH on P retention efficiency was studied employing the Response Surface Methodology (RSM). The maximum phosphate adsorption (79% removal and 198 mg kg−1 leftover coal) was obtained at a contact time of 200 min, an initial phosphate concentration of 5 mg/L, and a solution pH of 2.3. The Freundlich isotherm was fitted to the experimental data. The pseudo second-order equation describes the experimental data well, with a correlation value of R2 = 0.99. The effect of temperature on the adsorption reveals that the process is exothermic. The results demonstrate that leftover coal material could potentially be applied for the removal of phosphate from aqueous media, but additional testing in a flow-through set-up using real wastewater is required to draw definite conclusions.
Uncertainty Assessment of Urban Hydrological Modelling from a Multiple Objective Perspective
Authors: Pang Bo , Shi Shulan , Zhao Gang , Shi Rong , Peng Dingzhi , Zhu Zhongfan
Published: May 2020

The uncertainty assessment of urban hydrological models is important for understanding the reliability of the simulated results. To satisfy the demand for urban flood management, we assessed the uncertainty of urban hydrological models from a multiple-objective perspective. A multiple-criteria decision analysis method, namely, the Generalized Likelihood Uncertainty Estimation-Technique for Order Preference by Similarity to Ideal Solution (GLUE-TOPSIS) was proposed, wherein TOPSIS was adopted to measure the likelihood within the GLUE framework. Four criteria describing different urban stormwater characteristics were combined to test the acceptability of the parameter sets. The TOPSIS was used to calculate the aggregate employed in the calculation of the aggregate likelihood value. The proposed method was implemented in the Storm Water Management Model (SWMM), which was applied to the Dahongmen catchment in Beijing, China. The SWMM model was calibrated and validated based on the three and two flood events respectively downstream of the Dahongmen catchment. The results showed that the GLUE-TOPSIS provided a more precise uncertainty boundary compared with the single-objective GLUE method. The band widths were reduced by 7.30 m3/s in the calibration period, and by 7.56 m3/s in the validation period. The coverages increased by 20.3% in the calibration period, and by 3.2% in the validation period. The median estimates improved, with an increase of the Nash–Sutcliffe efficiency coefficients by 1.6% in the calibration period, and by 10.0% in the validation period. We conclude that the proposed GLUE-TOPSIS is a valid approach to assess the uncertainty of urban hydrological model from a multiple objective perspective, thereby improving the reliability of model results in urban catchment.
Scientifically and practically significant development of a major and relevant economic and managerial topic (about the book by Yu.B. Vinslav «Management of integrated structures: theoretical and methodical aspects»)
Authors: Dementiev V.E.
Published: May 2020

The article is a review of the book named in the title. According to the reviewer, the author of the monograph is highly qualified: 1) considers a complex set of issues of management modernization in domestic integrated companies; 2) develops a historical overview of the formation of large corporate business in post-Soviet Russia, systematizes its current problems; 3) describes the conceptual features of management of integrated corporate structures (ICS); 4) substantiates. practical recommendations for improving the management of ICS and public management of the development of the sector of these structures. The reviewer's reflections on the book are summarized in the thesis about its high value for business circles and the scientific and educational community of the country, for state and local government bodies.
Beyond Panel-Based Testing: Exome Analysis Increases Sensitivity for Diagnosis of Genetic Kidney Disease
Authors: Wilson Parker C. , Love-Gregory Latisha , Corliss Meagan , McNulty Samantha , Heusel Jonathan W. , Gaut Joseph P.
Published: May 2020

Background

Next-generation sequencing (NGS) is a useful tool for evaluating patients with suspected genetic kidney disease. Clinical practice relies on the use of targeted gene panels that are ordered based on patient presentation. We compare the diagnostic yield of clinical panel-based testing to exome analysis.

Methods

In total, 324 consecutive patients underwent physician-ordered, panel-based NGS testing between December 2014 and October 2018. Gene panels were available for four clinical phenotypes, including atypical hemolytic uremic syndrome (n=224), nephrotic syndrome (n=56), cystic kidney disease (n=26), and Alport syndrome (n=13). Variants were analyzed and clinical reports were signed out by a pathologist or clinical geneticist at the time of testing. Subsequently, all patients underwent retrospective exome analysis to detect additional clinically significant variants in kidney disease genes that were not analyzed as part of the initial clinical gene panel. Resulting variants were classified according to the American College of Medical Genetics and Genomics 2015 guidelines.

Results

In the initial physician-ordered gene panels, we identified clinically significant pathogenic or likely pathogenic variants in 13% of patients (n=42/324). CFHR3-CFHR1 homozygous deletion was detected in an additional 13 patients with aHUS without a pathogenic or likely pathogenic variant. Diagnostic yield of the initial physician-ordered gene panel was 20% and varied between groups. Retrospective exome analysis identified 18 patients with a previously unknown pathogenic or likely pathogenic variant in a kidney disease gene and eight patients with a high-risk APOL1 genotype. Overall, retrospective exome analysis increased the diagnostic yield of panel-based testing from 20% to 30%.

Conclusions

These results highlight the importance of a broad and collaborative approach between the clinical laboratory and their physician clients that employs additional analysis when a targeted panel of kidney disease–causing genes does not return a clinically meaningful result.
SAĞLIK SEKTÖRÜNDE HİZMET KALİTESİ ÖLÇÜMÜ: SİSTEMATİK BİR DERLEME ÇALIŞMASI
Authors: ŞAHİNLİ Serhan , TARIM Mehveş
Published: May 2020

Bu çalışmanın amacı, yerli ve yabancı literatürde
sağlık sektöründe Servqual ölçeği kullanılarak yapılan hizmet kalitesi
ölçümleri ile ilgili seçilmiş araştırmaları sistematik bir şekilde
değerlendirmektir. Araştırma verilerini, 2000-2018 yılları arasında sağlık
sektöründe yapılmış rastgele seçilmiş 23 çalışma oluşturmaktadır. Araştırmanın
kaynağını oluşturan çalışmalar, Kasım-Aralık 2018 tarihleri arasında Google
Akademik, TR Dizin Tarama, Dergi Park, ResearchGate ve Academia’dan
seçilmiştir. Araştırmada yerli ve yabancı literatürde sağlık sektöründen hizmet
alan hastaların kalite algıları ile ilgili yapılmış çalışmalar amaç, hastane
türü, boyut, hastaların hizmet alma şekli ve bulgular açısından
değerlendirilmiştir. Araştırmada, yerli ve yabancı literatür incelendiğinde
hastaların en az önem verdiği hizmet kalitesi boyutunun fiziksel özellikler
olduğu tespit edilmiştir. Araştırmada, hastalar tarafından 2000-2007 yılları
arasında sağlık kurumlarında en fazla önem verilen boyutlardan birisi empati
iken, 2007 yılından itibaren hastaların empatiye verdiği önem azalmıştır.
Hizmet kalitesi ölçümü ile ilgili yapılan çalışmalarda özellikle 2000’li
yılların başında ağırlıklı olarak fiziksel özellikler, güvenilirlik, güven,
empati ve heveslilik boyutları değerlendirilirken, son yıllarda bu beş boyuta
personel, denetim, temizlik, ücret, bilgilendirme, eşit hizmet, sistem ve
bekleme süreside eklenmiştir. Hizmet kalitesi ölçümleri daha çok özel sektörde,
yatarak tedavi gören hastalar üzerinde yapılmıştır. Sağlık işletmelerinde
algılanan hizmet kalitesinin hem kamu hem de özel kurumlarda, çeşitli
boyutlarda kontrol edilmesi ve tespit edilmesi, sınırlı sayıdaki hastane girdilerinin
aktif bir biçimde değerlendirilmesi ve bu sayede giderlerin azaltılması, rakiplerine
üstünlük sağlama ve hasta ihtiyaçlarının giderilmesi bakımından önemli avantajlar
sağlayacaktır.