bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Glow Discharge Mass Spectrometry for the Monitoring of Dopant Distribution in Optical Crystals Grown by TSSG Method
Authors: Gubal Anna , Chuchina Victoria , Trefilov Ivan , Glumov Oleg , Yakobson Viktor , Titov Alexander , Solovyev Nikolay , Ganeev Alexander
Published: June 2020

Direct analysis of matrix and admixture elements in non-conducting crystals is a relevant analytical task in terms of quality assurance of optical materials. The current study aimed to develop a method capable to assess the inhomogeneity of optical crystals with sufficient sensitivity. K1−xRbxTiOPO4 (x = 0.002 and 0.05) and KGd1−yNdy(WO4)2 (y = 0.05) were grown using the top-seeded solution growth method (TSSG). The samples were analyzed by microsecond direct current pulsed glow discharge time-of-flight mass spectrometry (µs-PDC TOF GDMS). The data were compared with the results obtained by scanning electron microscope-energy dispersive X-ray spectroscopy (SEM EDX) and spectrophotometry and validated by the analysis of certified reference material. Sample glow discharge sputtering and analysis were optimized and implemented in real samples. Sample coating with a silver layer and sample pressing in the metallic matrix were proposed to ensure effective sputtering for K1−xRbxTiOPO4 and KGd1−yNdy(WO4)2, respectively. Using the designed method, the inhomogeneity of the dopant’s distribution was demonstrated along the growth axis and in the case of K1−xRbxTiOPO4, also in the growth sectors of different faces. The designed method is applicable for the direct analysis of optical crystal and may be implemented in quality assurance in the manufacturing of optical materials.
Hydrogen Bonds with BF4− Anion as a Proton Acceptor
Authors: Grabowski Sławomir J.
Published: June 2020

The BF4− anion is characterised by weak Lewis base properties; it is usually classified as a “non-coordinating anion”. The searches through the Cambridge Structural Database (CSD) were performed and it was found that the BF4− anion often occurs in crystal structures and it is involved in numerous intermolecular interactions; hydrogen bonds are the majority of them. The hydrogen bonds involving the BF4− anion as a proton acceptor are closer to linearity with the increase of the strength of interaction that is in line with the tendency known for other hydrogen bonds. However, even for short contacts between the proton and the Lewis base centre, slight deviations from linearity occur. The MP2/aug-cc-pVTZ calculations on the BF4−…HCN complex and on the BF4−…(HCN)4 cluster were also carried out to characterise corresponding C-H…F hydrogen bonds; such interactions often occur in crystal structures.
Morphometric Response of Galaxias maculatus (Jenyns) to Lake Colonization in Chile
Authors: Mercer Margaret , Searle Peter C. , Cifuentes Roberto , Habit Evelyn , Belk Mark C.
Published: June 2020

Body and head shape in fish responds to environmental factors such as water flow rate, food sources, and niche availability. However, the way in which fish respond to these environmental factors varies. In Central Chile, multiple river and lake systems along the coast provide an ideal study site to investigate these types of shape changes. We use geometric morphometrics to characterize shape differences in Galaxias maculatus (Jenyns) between river and lake populations. Lake fish converge on a shape with a more fusiform body, narrower head, and larger eyes, while river fish have a more robust body, rounder head, and smaller eyes. These shape changes are consistent with a shift to zooplanktivorous foraging in lakes, as evidenced in other systems. Unlike some fish species that develop polymorphisms in body shape after colonization (e.g., benthic and limnetic forms), G. maculatus in lakes exhibit a monomorphic limnetic form.
Analyzing 24-Hour Blood Pressure Measurements with a Novel Cuffless Pulse Transit Time Device in Clinical Practice—Does the Software for Heartbeat Detection Matter?
Authors: Kilian Leo , Krisai Philipp , Socrates Thenral , Arranto Christian , Pfister Otmar , Meienberg Andrea , Mayr Michael , Vischer Annina S. , Burkard Thilo
Published: June 2020

Background: The Somnotouch-Non-Invasive-Blood-Pressure (NIBP) device delivers raw data consisting of electrocardiography and photoplethysmography for estimating blood pressure (BP) over 24 h using pulse-transit-time. The study’s aim was to analyze the impact on 24-hour BP results when processing raw data by two different software solutions delivered with the device. Methods: We used data from 234 participants. The Somnotouch-NIBP measurements were analyzed using the Domino-light and Schiller software and compared. BP values differing >5 mmHg were regarded as relevant and explored for their impact on BP classification (normotension vs. hypertension). Results: Mean (±standard deviation) absolute systolic/diastolic differences for 24-hour mean BP were 1.5 (±1.7)/1.1 (±1.3) mm Hg. Besides awake systolic BP (p = 0.022), there were no statistically significant differences in systolic/diastolic 24-hour mean, awake, and asleep BP. Twenty four-hour mean BP agreement (number (%)) between the software solutions within 5, 10, and 15 mmHg were 222 (94.8%), 231 (98.7%), 234 (100%) for systolic and 228 (97.4%), 232 (99.1%), 233 (99.5%) for diastolic measurements, respectively. A BP difference of >5 mmHg was present in 24 (10.3%) participants leading to discordant classification in 4–17%. Conclusion: By comparing the two software solutions, differences in BP are negligible at the population level. However, at the individual level there are, in a minority of cases, differences that lead to different BP classifications, which can influence the therapeutic decision.
Sovereign Risk Indices and Bayesian Theory Averaging
Authors: Lenkoski Alex , Aanes Fredrik L.
Published: June 2020

In economic applications, model averaging has found principal use in examining the validity of various theories related to observed heterogeneity in outcomes such as growth, development, and trade. Though often easy to articulate, these theories are imperfectly captured quantitatively. A number of different proxies are often collected for a given theory and the uneven nature of this collection requires care when employing model averaging. Furthermore, if valid, these theories ought to be relevant outside of any single narrowly focused outcome equation. We propose a methodology which treats theories as represented by latent indices, these latent processes controlled by model averaging on the proxy level. To achieve generalizability of the theory index our framework assumes a collection of outcome equations. We accommodate a flexible set of generalized additive models, enabling non-Gaussian outcomes to be included. Furthermore, selection of relevant theories also occurs on the outcome level, allowing for theories to be differentially valid. Our focus is on creating a set of theory-based indices directed at understanding a country’s potential risk of macroeconomic collapse. These Sovereign Risk Indices are calibrated across a set of different “collapse” criteria, including default on sovereign debt, heightened potential for high unemployment or inflation and dramatic swings in foreign exchange values. The goal of this exercise is to render a portable set of country/year theory indices which can find more general use in the research community.
Energy-Aware Sensing on Battery-Less LoRaWAN Devices with Energy Harvesting
Authors: Sabovic Adnan , Delgado Carmen , Subotic Dragan , Jooris Bart , De Poorter Eli , Famaey Jeroen
Published: June 2020

Billions of Internet of Things (IoT) devices rely on batteries as the main power source. These batteries are short-lived, bulky and harmful to the environment. Battery-less devices provide a promising alternative for a sustainable IoT, where energy harvested from the environment is stored in small capacitors. This constrained energy storage and the unpredictable energy harvested result in intermittent on–off behavior of the device. Measuring and understanding the current consumption and execution time of different tasks of IoT applications is crucial to properly operate these battery-less devices. In this paper, we study how to properly schedule sensing and transmission tasks on a battery-less LoRaWAN device. We analyze the trade-off between sleeping and allowing the device to turn off between the execution of application tasks. This study allows us to properly define the device configuration (i.e., capacitor size) based on the application tasks (i.e., sensing and sending) and environmental conditions (i.e., harvesting rate). We define an optimization problem that determines the optimal capacitor voltage at which the device should start performing its tasks. Our results show that a device using LoRaWAN Class A can measure the temperature and transmit its data at least once every 5 s if it can harvest at least 10 mA of current and uses a relatively small capacitor of 10 mF or less. At harvesting rates below 3 mA, it is necessary to turn off the device between application cycles and use a larger supercapacitor of at least 140 mF. In this case, the device can transmit a temperature measurement once every 60–100 s.
Fast Hole Filling for View Synthesis in Free Viewpoint Video
Authors: Huang Hui-Yu , Huang Shao-Yu
Published: June 2020

The recent emergence of three-dimensional (3D) movies and 3D television (TV) indicates an increasing interest in 3D content. Stereoscopic displays have enabled visual experiences to be enhanced, allowing the world to be viewed in 3D. Virtual view synthesis is the key technology to present 3D content, and depth image-based rendering (DIBR) is a classic virtual view synthesis method. With a texture image and its corresponding depth map, a virtual view can be generated using the DIBR technique. The depth and camera parameters are used to project the entire pixel in the image to the 3D world coordinate system. The results in the world coordinates are then reprojected into the virtual view, based on 3D warping. However, these projections will result in cracks (holes). Hence, we herein propose a new method of DIBR for free viewpoint videos to solve the hole problem due to these projection processes. First, the depth map is preprocessed to reduce the number of holes, which does not produce large-scale geometric distortions; subsequently, improved 3D warping projection is performed collectively to create the virtual view. A median filter is used to filter the hole regions in the virtual view, followed by 3D inverse warping blending to remove the holes. Next, brightness adjustment and adaptive image blending are performed. Finally, the synthesized virtual view is obtained using the inpainting method. Experimental results verify that our proposed method can produce a pleasant visibility of the synthetized virtual view, maintain a high peak signal-to-noise ratio (PSNR) value, and efficiently decrease execution time compared with state-of-the-art methods.
Channel and Spatial Attention Regression Network for Cup-to-Disc Ratio Estimation
Authors: Li Shuo , Ge Chiru , Sui Xiaodan , Zheng Yuanjie , Jia Weikuan
Published: June 2020

Cup-to-disc ratio (CDR) is of great importance during assessing structural changes at the optic nerve head (ONH) and diagnosis of glaucoma. While most efforts have been put on acquiring the CDR number through CNN-based segmentation algorithms followed by the calculation of CDR, these methods usually only focus on the features in the convolution kernel, which is, after all, the operation of the local region, ignoring the contribution of rich global features (such as distant pixels) to the current features. In this paper, a new end-to-end channel and spatial attention regression deep learning network is proposed to deduces CDR number from the regression perspective and combine the self-attention mechanism with the regression network. Our network consists of four modules: the feature extraction module to extract deep features expressing the complicated pattern of optic disc (OD) and optic cup (OC), the attention module including the channel attention block (CAB) and the spatial attention block (SAB) to improve feature representation by aggregating long-range contextual information, the regression module to deduce CDR number directly, and the segmentation-auxiliary module to focus the model’s attention on the relevant features instead of the background region. Especially, the CAB selects relatively important feature maps in channel dimension, shifting the emphasis on the OD and OC region; meanwhile, the SAB learns the discriminative ability of feature representation at pixel level by capturing the relationship of intra-feature map. The experimental results of ORIGA dataset show that our method obtains absolute CDR error of 0.067 and the Pearson’s correlation coefficient of 0.694 in estimating CDR and our method has a great potential in predicting the CDR number.
AC-DC Converters for Electrolyzer Applications: State of the Art and Future Challenges
Authors: Yodwong Burin , Guilbert Damien , Phattanasak Matheepot , Kaewmanee Wattana , Hinaje Melika , Vitale Gianpaolo
Published: June 2020

The main objective of the article is to provide a thorough review of currently used AC-DC converters for alkaline and proton exchange membrane (PEM) electrolyzers in power grid or wind energy conversion systems. Based on the current literature, this article aims at emphasizing the advantages and drawbacks of AC-DC converters mainly based on thyristor rectifier bridges and chopper-rectifiers. The analysis is mainly focused on the current issues for these converters in terms of specific energy consumption, current ripple, reliability, efficiency, and power quality. From this analysis, it is shown that thyristors-based rectifiers are particularly fit for high-power applications but require the use of active and passive filters to enhance the power quality. By comparison, the association combination of the chopper-rectifier can avoid the use of bulky active and passive filters since it can improve power quality. However, the use of a basic chopper (i.e., buck converter) presents several disadvantages from the reliability, energy efficiency, voltage ratio, and current ripple point of view. For this reason, new emerging DC-DC converters must be employed to meet these important issues according to the availability of new power switching devices. Finally, based on the authors’ experience in power conversion for PEM electrolyzers, a discussion is provided regarding the future challenges that must face power electronics for green hydrogen production based on renewable energy sources.
Delta Multi-Stage Interconnection Networks for Scalable Wireless On-Chip Communication
Authors: Mnejja Sirine , Aydi Yassine , Abid Mohamed , Monteleone Salvatore , Catania Vincenzo , Palesi Maurizio , Patti Davide
Published: June 2020

The Network-on-Chip (NoC) paradigm emerged as a viable solution to provide an efficient and scalable communication backbone for next-generation Multiprocessor Systems-on-Chip. As the number of integrated cores keeps growing, alternatives to the traditional multi-hop wired NoCs, such as wireless Networks-on-Chip (WiNoCs), have been proposed to provide long-range communications in a single hop. In this work, we propose and analyze the integration of the Delta Multistage Interconnection Network (MINs) as a backbone for wireless-enabled NoCs. After extending the well-known Noxim platform to implement a cycle-accurate model of a wireless Delta MIN, we perform a comprehensive set of SystemC simulations to analyze how wireless-augmented Delta MINs can potentially lead to an improvement in both average delay and saturation. Further, we compare the results obtained with traditional mesh-based topologies, reporting energy profiles that show an overall energy cost reduced on both wired/wireless scenarios.
Blended Multi-Modal Deep ConvNet Features for Diabetic Retinopathy Severity Prediction
Authors: Bodapati Jyostna Devi , Naralasetti Veeranjaneyulu , Shareef Shaik Nagur , Hakak Saqib , Bilal Muhammad , Maddikunta Praveen Kumar Reddy , Jo Ohyun
Published: June 2020

Diabetic Retinopathy (DR) is one of the major causes of visual impairment and blindness across the world. It is usually found in patients who suffer from diabetes for a long period. The major focus of this work is to derive optimal representation of retinal images that further helps to improve the performance of DR recognition models. To extract optimal representation, features extracted from multiple pre-trained ConvNet models are blended using proposed multi-modal fusion module. These final representations are used to train a Deep Neural Network (DNN) used for DR identification and severity level prediction. As each ConvNet extracts different features, fusing them using 1D pooling and cross pooling leads to better representation than using features extracted from a single ConvNet. Experimental studies on benchmark Kaggle APTOS 2019 contest dataset reveals that the model trained on proposed blended feature representations is superior to the existing methods. In addition, we notice that cross average pooling based fusion of features from Xception and VGG16 is the most appropriate for DR recognition. With the proposed model, we achieve an accuracy of 97.41%, and a kappa statistic of 94.82 for DR identification and an accuracy of 81.7% and a kappa statistic of 71.1% for severity level prediction. Another interesting observation is that DNN with dropout at input layer converges more quickly when trained using blended features, compared to the same model trained using uni-modal deep features.
Adaptive Quantization Parameter Estimation for HEVC Based Surveillance Scalable Video Coding
Authors: HoangVan Xiem
Published: June 2020

Visual surveillance systems have been playing a vital role in human modern life with a large number of applications, ranging from remote home management, public security to traffic monitoring. The recent High Efficiency Video Coding (HEVC) scalable extension, namely SHVC, provides not only the compression efficiency but also the adaptive streaming capability. However, SHVC is originally designed for videos captured from generic scenes rather than from visual surveillance systems. In this paper, we propose a novel HEVC based surveillance scalable video coding (SSVC) framework. First, to achieve high quality inter prediction, we propose a long-term reference coding method, which adaptively exploits the temporal correlation among frames in surveillance video. Second, to optimize the SSVC compression performance, we design a quantization parameter adaptation mechanism in which the relationship between SSVC rate-distortion (RD) performance and the quantization parameter is statistically modeled by a fourth-order polynomial function. Afterwards, an appropriate quantization parameter is derived for frames at long-term reference position. Experiments conducted for a common set of surveillance videos have shown that the proposed SSVC significantly outperforms the relevant SHVC standard, notably by around 6.9% and 12.6% bitrate saving for the low delay (LD) and random access (RA) coding configurations, respectively while still providing a similar perceptual decoded frame quality.
Ground Deformation and Seismic Fault Model of the M6.4 Durres (Albania) Nov. 26, 2019 Earthquake, Based on GNSS/INSAR Observations
Authors: Ganas Athanassios , Elias Panagiotis , Briole Pierre , Cannavo Flavio , Valkaniotis Sotirios , Tsironi Varvara , Partheniou Eleni I.
Published: June 2020

We identify the source of the Mw = 6.4 earthquake that rocked north-central Albania on November 26, 2019 02:54 UTC. We use synthetic aperture radar interferograms tied to the time series of coordinates of two permanent Global Navigation Satellite System (GNSS) stations (DUR2 and TIR2). We model the source by inverting the displacement data. Assuming in our model a half-space elastic medium and uniform slip along a rectangular fault surface, we invert the 104 picked measurements on a couple of ascending and descending interferograms to calculate the parameters of the fault. All inversions made with different input parameters converge towards a stable and robust solution with root mean square (r.m.s.) residual of 5.4 mm, thus ~1/5 of a fringe. They reveal that the earthquake occurred deep in the crust on a low-angle fault (23°) dipping towards east with a centroid at 16.5 km depth. The best-fitting length and width of the fault are 22 and 13 km, and the reverse slip, 0.55 m. The seismic moment deduced from our model agrees with those of the published seismic moment tensors. This geometry is compatible with a blind thrust fault that may root on the main basal thrust, i.e., along the thrust front that separates Adria–Apulia from Eurasia. It is notable that there is a 123 ns yr−1 active shortening of the crust between the GNSS stations DUR2-TIR2 (equivalent to a shortening rate of 3.6 mm yr−1), and roughly in the east–west direction. Given this amount of strain the recurrence time of M6+ earthquakes along this fault should be of the order of 150 years.
Analysis of Outbreak and Global Impacts of the COVID-19
Authors: Priyadarshini Ishaani , Mohanty Pinaki , Kumar Raghvendra , Son Le Hoang , Chau Hoang Thi Minh , Nhu Viet-Ha , Thi Ngo Phuong Thao , Tien Bui Dieu
Published: June 2020

Corona viruses are a large family of viruses that are not only restricted to causing illness in humans but also affect animals such as camels, cattle, cats, and bats, thus affecting a large group of living species. The outbreak of Corona virus in late December 2019 (also known as COVID-19) raised major concerns when the outbreak started getting tremendous. While the first case was discovered in Wuhan, China, it did not take long for the disease to travel across the globe and infect every continent (except Antarctica), killing thousands of people. Since it has become a global concern, different countries have been working toward the treatment and generation of vaccine, leading to different speculations. While some argue that the vaccine may only be a few weeks away, others believe that it may take some time to create the vaccine. Given the increasing number of deaths, the COVID-19 has caused havoc worldwide and is a matter of serious concern. Thus, there is a need to study how the disease has been propagating across continents by numbers as well as by regions. This study incorporates a detailed description of how the COVID-19 outbreak started in China and managed to spread across the globe rapidly. We take into account the COVID-19 outbreak cases (confirmed, recovered, death) in order to make some observations regarding the pandemic. Given the detailed description of the outbreak, this study would be beneficial to certain industries that may be affected by the outbreak in order to take timely precautionary measures in the future. Further, the study lists some industries that have witnessed the impact of the COVID-19 outbreak on a global scale.
The Urban-Rural Disparity in the Status and Risk Factors of Health Literacy: A Cross-Sectional Survey in Central China
Authors: Wang Wenna , Zhang Yulin , Lin Beilei , Mei Yongxia , Ping Zhiguang , Zhang Zhenxiang
Published: June 2020

Health literacy is the ability of individuals to access, process, and understand health information to make decisions regarding treatment and their health on the whole; it is critical to maintain and improve public health. However, the health literacy of urban and rural populations in China has been little known. Thus, this study aims to assess the status of health literacy and explore the differences of its possible determinants (e.g., socio-economic factors) among urban and rural populations in Henan, China. A cross-sectional study, 78,646 participants were recruited from a populous province in central China with a multi-stage random sampling design. The Chinese Resident Health Literacy Scale was adopted to measure the health literacy of the respondents. In the participants, the level of health literacy (10.21%) in central China was significantly lower than the national average, and a big gap was identified between urban and rural populations (16.92% vs. 8.09%). A noticeable difference was reported in different aspects and health issues of health literacy between urban and rural populations. The health literacy level was lower in those with lower levels of education, and a significant difference was identified in the level of health literacy among people of different ages and occupations in both urban and rural areas. Note that in rural areas, as long as residents educated, they all had higher odds to exhibit basic health literacy than those uneducated; in rural areas, compared with those aged 15 to 24 years, residents aged 45 to 54 years (OR = 0.846,95% CI (0.730, 0.981)), 55 to 64 years (OR = 0.716,95% CI (0.614, 0.836)) and above 65 years (OR = 0.679, 95% CI (0.567, 0.812)) were 84.6%, 71.6%, and 67.9%, respectively, less likely to exhibit basic health literacy. Considering the lower health literacy among rural residents compared with their urban counterparts, a reorientation of the health policy-making for Chinese rural areas is recommended. This study suggests that urban–rural disparity about health literacy risk factors should be considered when implementing health literacy promotion intervention.
Nontuberculous Mycobacterial Disease and Molybdenum in Colorado Watersheds
Authors: Lipner Ettie M. , French Joshua , Bern Carleton R. , Walton-Day Katherine , Knox David , Strong Michael , Prevots D. Rebecca , Crooks James L.
Published: June 2020

Nontuberculous mycobacteria (NTM) are environmental bacteria that may cause chronic lung disease. Environmental factors that favor NTM growth likely increase the risk of NTM exposure within specific environments. We aimed to identify water-quality constituents (Al, As, Cd, Ca, Cu, Fe, Pb, Mg, Mn, Mo, Ni, K, Se, Na, Zn, and pH) associated with NTM disease across Colorado watersheds. We conducted a geospatial, ecological study, associating data from patients with NTM disease treated at National Jewish Health and water-quality data from the Water Quality Portal. Water-quality constituents associated with disease risk were identified using generalized linear models with Poisson-distributed discrete responses. We observed a highly robust association between molybdenum (Mo) in the source water and disease risk. For every 1- unit increase in the log concentration of molybdenum in the source water, disease risk increased by 17.0%. We also observed a statistically significant association between calcium (Ca) in the source water and disease risk. The risk of NTM varied by watershed and was associated with watershed-specific water-quality constituents. These findings may inform mitigation strategies to decrease the overall risk of exposure.
Coping with COVID-19: Exposure to COVID-19 and Negative Impact on Livelihood Predict Elevated Mental Health Problems in Chinese Adults
Authors: Guo Jing , Feng Xing Lin , Wang Xiao Hua , van IJzendoorn Marinus H.
Published: June 2020

The COVID-19 pandemic might lead to more mental health problems. However, few studies have examined sleep problems, depression, and posttraumatic symptoms among the general adult population during the COVID-19 outbreak, and little is known about coping behaviors. This survey was conducted online in China from February 1st to February 10th, 2020. Quota sampling was used to recruit 2993 Chinese citizens aged ≥18 years old. Mental health problems were assessed with the Post-Traumatic Stress Disorders (PTSD) Checklist for the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), the Center for Epidemiological Studies Depression inventory, and the Pittsburgh Sleep Quality Index. Exposure to COVID-19 was measured with questions about residence at outbreak, personal exposure, media exposure, and impact on livelihood. General coping style was measured by the brief Coping Style Questionnaire (SCSQ). Respondents were also asked 12 additional questions about COVID-19 specific coping behaviors. Direct exposure to COVID-19 instead of the specific location of (temporary) residence within or outside the epicenter (Wuhan) of the pandemic seems important (standardized beta: 0.05, 95% confidence interval (CI): 0.02–0.09). Less mental health problems were also associated with less intense exposure through the media (standardized beta: −0.07, 95% CI: −0.10–−0.03). Perceived negative impact of the pandemic on livelihood showed a large effect size in predicting mental health problems (standardized beta: 0.15, 95% CI: 0.10–0.19). More use of cognitive and prosocial coping behaviors were associated with less mental health problems (standardized beta: −0.30, 95% CI: −0.34–−0.27). Our study suggests that the mental health consequences of the lockdown impact on livelihood should not be underestimated. Building on cognitive coping behaviors reappraisal or cognitive behavioral treatments may be most promising.
Are Services Inclusive? A Review of the Experiences of Older GSD Women in Accessing Health, Social and Aged Care Services
Authors: Dune Tinashe , Ullman Jacqueline , Ferfolja Tania , Thepsourinthone Jack , Garga Shirali , Mengesha Zelalem
Published: June 2020

The review aimed to examine the views and experiences of ageing gender and sexually diverse (GSD) women—a triple minority in relation to their age, gender and sexual orientation—in accessing health, social and aged care services. Eighteen peer reviewed articles identified from seven electronic databases in health and social sciences were evaluated according to predefined criteria and a thematic review methodology drawing upon socio-ecological theory was used to analyse and interpret the findings. Four major themes were identified from the analysis: “The Dilemma of Disclosure”, “Belonging/Connection”, “Inclusiveness of Aged Care” and “Other Barriers to Access Care”. In the dilemma of disclosure, older GSD women consider factors such as previous experiences, relationship with the provider and anticipated duration of stay with the provider before disclosing their sexual identifies. The review also revealed that aged care services lack inclusiveness in their policies, advertising materials, aged care spaces and provider knowledge and attitude to provide sensitive and appropriate care to GSD women. Overall, older GSD women experience multiple and multilevel challenges when accessing health, aged and social services and interventions are needed at all levels of the socio-ecological arena to improve their access and quality of care.
The Use of Geographic Databases for Analyzing Changes in Land Cover—A Case Study of the Region of Warmia and Mazury in Poland
Authors: Cieślak Iwona , Biłozor Andrzej , Źróbek-Sokolnik Anna , Zagroba Marek
Published: June 2020

This article analyzes the applicability of spatial data for evaluating and monitoring changes in land use and their impact on the local landscape. The Coordination of Information on the Environment (CORINE) Land Cover database was used to develop a procedure and an indicator for analyzing changes in land cover, and the continuity of different land use types. Changes in land use types were evaluated based on land cover data. The results were analyzed over time to track changes in the evaluated region. The studied area was the Region of Warmia and Mazury in Poland. The preservation of homogeneous land cover plays a particularly important role in areas characterized by high natural value and an abundance of forests and water bodies. The study revealed considerable changes in land cover and landscape fragmentation in the analyzed region.
Economic Growth Patterns: Spatial Econometric Analysis for Russian Regions
Authors: Balash Vladimir , Balash Olga , Faizliev Alexey , Chistopolskaya Elena
Published: June 2020

In this article, we analyze the σ - and β -convergence, using the data of the socio-economic development of Russian areas, and discover the role of spatial autocorrelation in regional economic development. We are considering 80 areas of the Russian Federation for the period of 2010–2017. Moran coefficients were used to estimate spatial autocorrelation. We compare the Moran scatterplots for GDP per capita and GDP growth rates per capita in 2017 and in 2014. We study the impact on raising investment in leading capital and the costs of technological innovation. We evaluate a wide range of specifications of spatial econometric models for all kinds of weight matrices. We combine standard geographical proximity with specialization proximity to assess whether they are substitutes or additions to converging economic growth rates. The weight matrix of the neighborhood and specialization similarities are used. The weight matrix of specialization similarities of the regional economies is based on data on the structure of tax payments in 82 industries. The specialization structure of the region’s economy is related to its location. Clusters obtained by matrices of specialization proximity are well separable from each other in space. The connectivity within clusters and the boundaries between them become more apparent over time. It is shown that according to the results of estimation of conditional β -convergence models, the models of 2010–2014 and 2014–2017 differ significantly. There is a statistically significant β -convergence for the period 2010–2014. There is also the presence of spatial autocorrelation. Based on the results of valuation models constructed from data after 2014, it can be concluded that the coefficient estimates for the explanatory variables are not significantly different from zero, and accordingly there is no tendency towards regional convergence in terms of economic development. The results obtained in the work are stable for the proposed models and spatial weight matrices. Territorial proximity is a more important factor than the similarity of specialization for explanation the economic growth rates of Russian regions.
Smart Ligands for Efficient 3d-, 4d- and 5d-Metal Single-Molecule Magnets and Single-Ion Magnets
Authors: Perlepe Panagiota S. , Maniaki Diamantoula , Pilichos Evangelos , Katsoulakou Eugenia , Perlepes Spyros P.
Published: June 2020

There has been a renaissance in the interdisciplinary field of Molecular Magnetism since ~2000, due to the discovery of the impressive properties and potential applications of d- and f-metal Single-Molecule Magnets (SMMs) and Single-Ion Magnets (SIMs) or Monometallic Single-Molecule Magnets. One of the consequences of this discovery has been an explosive growth in synthetic molecular inorganic and organometallic chemistry. In SMM and SIM chemistry, inorganic and organic ligands play a decisive role, sometimes equally important to that of the magnetic metal ion(s). In SMM chemistry, bridging ligands that propagate strong ferromagnetic exchange interactions between the metal ions resulting in large spin ground states, well isolated from excited states, are preferable; however, antiferromagnetic coupling can also lead to SMM behavior. In SIM chemistry, ligands that create a strong axial crystal field are highly desirable for metal ions with oblate electron density, e.g., TbIII and DyIII, whereas equatorial crystal fields lead to SMM behavior in complexes based on metal ions with prolate electron density, e.g., ErIII. In this review, we have attempted to highlight the use of few, efficient ligands in the chemistry of transition-metal SMMs and SIMs, through selected examples. The content of the review is purely chemical and it is assumed that the reader has a good knowledge of synthetic, structural and physical inorganic chemistry, as well as of the properties of SIMs and SMMs and the techniques of their study. The ligands that will be discussed are the azide ion, the cyanido group, the tris(trimethylsilyl)methanide, the cyclopentanienido group, soft (based on the Hard-Soft Acid-Base model) ligands, metallacrowns combined with click chemistry, deprotonated aliphatic diols, and the family of 2-pyridyl ketoximes, including some of its elaborate derivatives. The rationale behind the selection of the ligands will be emphasized.
Enzymology, Histological and Ultrastructural Effects of Ar-Turmerone on Culex pipiens pallens Larvae
Authors: Liu Jia , Fernandez Diana , Gao Yanjin , Silvie Pierre , Gao Yongdong , Dai Guanghui
Published: June 2020

Our previous article demonstrated that ar-turmerone ((6S)-2-methyl-6-(4-methylphenyl)-2-hepten-4-one) extracted from Curcuma longa L. has a significant larvicidal activity against the fourth instar larvae of Culex pipiens pallens. To reveal the effects of ar-turmerone on C. pipiens pallens larvae, light microscopy and transmission electron microscopy were used to observe the histological and ultrastructure changes in muscle and digestive tissues of fourth instar larvae. It was also revealed by detecting the activity of the acetylcholinesterase (AChE) enzyme and three detoxifying enzymes, including carboxylesterase (CarE), glutathione-S-transferase (GST) and Cytochrome P450 monooxidases (P450). The observation under the light microscope showed that the larvae displayed a disruption of myofibril in ventral muscle cells, the disappearance of nucleolus in the malpighian tubule cells, and the exfoliation of the brush border in midgut epithelial cells, 24 h after treatment. The observation under the transmission electron microscope displayed disorganized Z-lines in the ventral muscle cells, and dissolved membrane of mitochondria, nuclear and endoplasmic reticulum in abdominal cells. The enzymatic activity results showed that ar-turmerone significantly increased the level of detoxifying enzymes, while the activity of AChE was not obviously affected. All the results suggest that the larvicidal mechanism of ar-turmerone is estimated to be stomach poison and the active sites might be the muscle and digestive tissues, and the mode of action of ar-turmerone may be unrelated to AChE.
Simulation of Subcritical Vibrations of a Large Flexible Rotor with Varying Spherical Roller Bearing Clearance and Roundness Profiles
Authors: Kurvinen Emil , Viitala Raine , Choudhury Tuhin , Heikkinen Janne , Sopanen Jussi
Published: June 2020

In large rotor-bearing systems, the rolling element bearings act as a considerable source of subcritical vibration excitation. Simulation of such rotor bearing systems contains major sources of uncertainty contributing to the excitation, namely the roundness profile of the bearing inner ring and the clearance of the bearing. In the present study, a simulation approach was prepared to investigate carefully the effect of varying roundness profile and clearance on the subcritical vibration excitation. The FEM-based rotor-bearing system simulation model included a detailed description of the bearings and asymmetricity of the rotor. The simulation results were compared to measured responses for validation. The results suggest that the simulation model was able to capture the response of the rotor within a reasonable accuracy compared to the measured responses. The bearing clearance was observed to have a major effect on the subcritical resonance response amplitudes. In addition, the simulation model confirmed that the resonances of the 3rd and 4th harmonic vibration components in addition to the well-known 2nd harmonic resonance (half-critical resonance) can be significantly high and should thus be taken into account already in the design phase of large subcritical rotors.
Generalized Sasakian Space Forms Which Are Realized as Real Hypersurfaces in Complex Space Forms
Authors: Carriazo Alfonso , Cho Jong Taek , Martín-Molina Verónica
Published: June 2020

We prove a classification theorem of the generalized Sasakian space forms which are realized as real hypersurfaces in complex space forms.
Research on Fatigue Crack Propagation of 304 Austenitic Stainless Steel Based on XFEM and CZM
Authors: Hu Xiaodong , Xu Jie , Du Xiangmei , Zhang Yong , Zhou Fan
Published: June 2020

The fatigue crack propagation of 304 austenitic stainless steel was studied both by experiments and numerical simulations. Two methods were applied to simulate the crack propagation: the extended finite element method (XFEM) and the cohesive zone model (CZM). Based on the XFEM, the direct cyclic solver was used to simulate the fatigue crack propagation. Based on the CZM, the VUMAT subroutine was used to describe the crack tip constitutive equation during fatigue crack propagation, and the mechanical properties of the crack tip were simulated. The effects of different frequency, f, and stress ratio, R, on the fatigue crack growth life were studied by XFEM and CZM separately and compared with the experimental results. Results show that the crack propagation path simulated by the XFEM agrees well with the experimental result, but the deviation of the fatigue life between the simulated results and the experimental results is large. The CZM model can predict the crack propagation life very well in comparison with the experimental data, but it has certain limitations because the crack propagation path is preset.
Modeling Pharmacokinetic Profiles for Assessment of Anti-Cancer Drug on a Microfluidic System
Authors: Guo Yaqiong , Deng Pengwei , Chen Wenwen , Li Zhongyu
Published: June 2020

The pharmacokinetic (PK) properties of drug, which include drug absorption and excretion, play an important role in determining the in vivo pharmaceutical activity. However, current in vitro systems that model PK profiles are often limited by the in vivo-like concentration profile of a drug. Herein, we present a perfused and multi-layered microfluidic chip system to model the PK profile of anti-cancer drug 5-FU in vitro. The chip device contains two layers of culture channels sandwiched by a porous membrane, which allows for drug exposure and diffusion between the two channels. The integration of upper intestine cells (Caco-2) and bottom targeted cells within the device enables the generation of loading and clearance portions of a PK curve under peristaltic flow. Fluorescein as a test molecule was initially used to generate a concentration-time curve, investigating the effects of parameters of flow rate, administration time, and initial concentration on dynamic drug concentration profiles. Furthermore, anti-cancer drug 5-FU was performed to assess its pharmaceutical activity on target cells (human lung adenocarcinoma cells or human pulmonary alveolar epithelial cells) using different drug administration regimens. A dynamic, in vivo-like 5-FU exposure refers to PK profile regimen, led to generate a lower drug concentration (dynamically fluctuate from 0 to 1 μg/mL affected by absorption) compared to the constant exposure. Moreover, the PK profile regimen alleviates the drug-induced cytotoxicity on target cells. These results demonstrate the feasibility of determining the PK profiles using this microfluidic system with in vivo-like drug administration regimens. This established system may provide a powerful platform for the prediction of drug safety and effectiveness in the pharmaceutical research.
Differentiation of Leishmania (L.) infantum, Leishmania (L.) amazonensis and Leishmania (L.) mexicana Using Sequential qPCR Assays and High-Resolution Melt Analysis
Authors: Ceccarelli Marcello , Diotallevi Aurora , Buffi Gloria , De Santi Mauro , Fernández-Figueroa Edith A. , Rangel-Escareño Claudia , Muñoz-Montero Said A. , Becker Ingeborg , Magnani Mauro , Galluzzi Luca
Published: June 2020

Leishmania protozoa are the etiological agents of visceral, cutaneous and mucocutaneous leishmaniasis. In specific geographical regions, such as Latin America, several Leishmania species are endemic and simultaneously present; therefore, a diagnostic method for species discrimination is warranted. In this attempt, many qPCR-based assays have been developed. Recently, we have shown that L. (L.) infantum and L. (L.) amazonensis can be distinguished through the comparison of the Cq values from two qPCR assays (qPCR-ML and qPCR-ama), designed to amplify kDNA minicircle subclasses more represented in L. (L.) infantum and L. (L.) amazonensis, respectively. This paper describes the application of this approach to L. (L.) mexicana and introduces a new qPCR-ITS1 assay followed by high-resolution melt (HRM) analysis to differentiate this species from L. (L.) amazonensis. We show that L. (L.) mexicana can be distinguished from L. (L.) infantum using the same approach we had previously validated for L. (L.) amazonensis. Moreover, it was also possible to reliably discriminate L. (L.) mexicana from L. (L.) amazonensis by using qPCR-ITS1 followed by an HRM analysis. Therefore, a diagnostic algorithm based on sequential qPCR assays coupled with HRM analysis was established to identify/differentiate L. (L.) infantum, L. (L.) amazonensis, L. (L.) mexicana and Viannia subgenus. These findings update and extend previous data published by our research group, providing an additional diagnostic tool in endemic areas with co-existing species.
Lanthanide-Dependent Methanol and Formaldehyde Oxidation in Methylobacterium aquaticum Strain 22A
Authors: Yanpirat Patcha , Nakatsuji Yukari , Hiraga Shota , Fujitani Yoshiko , Izumi Terumi , Masuda Sachiko , Mitsui Ryoji , Nakagawa Tomoyuki , Tani Akio
Published: June 2020

Lanthanides (Ln) are an essential cofactor for XoxF-type methanol dehydrogenases (MDHs) in Gram-negative methylotrophs. The Ln3+ dependency of XoxF has expanded knowledge and raised new questions in methylotrophy, including the differences in characteristics of XoxF-type MDHs, their regulation, and the methylotrophic metabolism including formaldehyde oxidation. In this study, we genetically identified one set of Ln3+- and Ca2+-dependent MDHs (XoxF1 and MxaFI), that are involved in methylotrophy, and an ExaF-type Ln3+-dependent ethanol dehydrogenase, among six MDH-like genes in Methylobacterium aquaticum strain 22A. We also identified the causative mutations in MxbD, a sensor kinase necessary for mxaF expression and xoxF1 repression, for suppressive phenotypes in xoxF1 mutants defective in methanol growth even in the absence of Ln3+. Furthermore, we examined the phenotypes of a series of formaldehyde oxidation-pathway mutants (fae1, fae2, mch in the tetrahydromethanopterin (H4MPT) pathway and hgd in the glutathione-dependent formaldehyde dehydrogenase (GSH) pathway). We found that MxaF produces formaldehyde to a toxic level in the absence of the formaldehyde oxidation pathways and that either XoxF1 or ExaF can oxidize formaldehyde to alleviate formaldehyde toxicity in vivo. Furthermore, the GSH pathway has a supportive role for the net formaldehyde oxidation in addition to the H4MPT pathway that has primary importance. Studies on methylotrophy in Methylobacterium species have a long history, and this study provides further insights into genetic and physiological diversity and the differences in methylotrophy within the plant-colonizing methylotrophs.
Overexpression of lpxT Gene in Escherichia coli Inhibits Cell Division and Causes Envelope Defects without Changing the Overall Phosphorylation Level of Lipid A
Authors: Falchi Federica A. , Di Lorenzo Flaviana , Pizzoccheri Roberto , Casino Gianluca , Paroni Moira , Forti Francesca , Molinaro Antonio , Briani Federica
Published: June 2020

LpxT is an inner membrane protein that transfers a phosphate group from the essential lipid undecaprenyl pyrophosphate (C-55PP) to the lipid A moiety of lipopolysaccharide, generating a lipid A tris-phosphorylated species. The protein is encoded by the non-essential lpxT gene, which is conserved in distantly related Gram-negative bacteria. In this work, we investigated the phenotypic effect of lpxT ectopic expression from a plasmid in Escherichia coli. We found that lpxT induction inhibited cell division and led to the formation of elongated cells, mostly with absent or altered septa. Moreover, the cells became sensitive to detergents and to hypo-osmotic shock, indicating that they had cell envelope defects. These effects were not due to lipid A hyperphosphorylation or C-55PP sequestering, but most likely to defective lipopolysaccharide transport. Indeed, lpxT overexpression in mutants lacking the L,D-transpeptidase LdtD and LdtE, which protect cells with outer membrane defects from osmotic lysis, caused cell envelope defects. Moreover, we found that pyrophosphorylated lipid A was also produced in a lpxT deletion mutant, indicating that LpxT is not the only protein able to perform such lipid A modification in E. coli.