bluuebunny/crossref_metadata_2025 huggingface dataset:
Are Machine Learning Methods the Future for Smoking Cessation Apps?
Authors: Abo-Tabik Maryam , Benn Yael , Costen Nicholas
Published: June 2021

Smoking cessation apps provide efficient, low-cost and accessible support to smokers who are trying to quit smoking. This article focuses on how up-to-date machine learning algorithms, combined with the improvement of mobile phone technology, can enhance our understanding of smoking behaviour and support the development of advanced smoking cessation apps. In particular, we focus on the pros and cons of existing approaches that have been used in the design of smoking cessation apps to date, highlighting the need to improve the performance of these apps by minimizing reliance on self-reporting of environmental conditions (e.g., location), craving status and/or smoking events as a method of data collection. Lastly, we propose that making use of more advanced machine learning methods while enabling the processing of information about the user’s circumstances in real time is likely to result in dramatic improvement in our understanding of smoking behaviour, while also increasing the effectiveness and ease-of-use of smoking cessation apps, by enabling the provision of timely, targeted and personalised intervention.
Evaluating Pedometer Algorithms on Semi-Regular and Unstructured Gaits
Authors: Mattfeld Ryan , Jesch Elliot , Hoover Adam
Published: June 2021

Pedometers are popular for counting steps as a daily measure of physical activity, however, errors as high as 96% have been reported in previous work. Many reasons for pedometer error have been studied, including walking speed, sensor position on the body and pedometer algorithm, demonstrating some differences in error. However, we hypothesize that the largest source of error may be due to differences in the regularity of gait during different activities. During some activities, gait tends to be regular and the repetitiveness of individual steps makes them easy to identify in an accelerometer signal. During other activities of everyday life, gait is frequently semi-regular or unstructured, which we hypothesize makes it difficult to identify and count individual steps. In this work, we test this hypothesis by evaluating the three most common types of pedometer algorithm on a new data set that varies the regularity of gait. A total of 30 participants were video recorded performing three different activities: walking a path (regular gait), conducting a within-building activity (semi-regular gait), and conducting a within-room activity (unstructured gait). Participants were instrumented with accelerometers on the wrist, hip and ankle. Collectively, 60,805 steps were manually annotated for ground truth using synchronized video. The main contribution of this paper is to evaluate pedometer algorithms when the consistency of gait changes to simulate everyday life activities other than exercise. In our study, we found that semi-regular and unstructured gaits resulted in 5–466% error. This demonstrates the need to evaluate pedometer algorithms on activities that vary the regularity of gait. Our dataset is publicly available with links provided in the introduction and Data Availability Statement.
Deep Learning-Based Stroke Disease Prediction System Using Real-Time Bio Signals
Authors: Choi Yoon-A , Park Se-Jin , Jun Jong-Arm , Pyo Cheol-Sig , Cho Kang-Hee , Lee Han-Sung , Yu Jae-Hak
Published: June 2021

The emergence of an aging society is inevitable due to the continued increases in life expectancy and decreases in birth rate. These social changes require new smart healthcare services for use in daily life, and COVID-19 has also led to a contactless trend necessitating more non-face-to-face health services. Due to the improvements that have been achieved in healthcare technologies, an increasing number of studies have attempted to predict and analyze certain diseases in advance. Research on stroke diseases is actively underway, particularly with the aging population. Stroke, which is fatal to the elderly, is a disease that requires continuous medical observation and monitoring, as its recurrence rate and mortality rate are very high. Most studies examining stroke disease to date have used MRI or CT images for simple classification. This clinical approach (imaging) is expensive and time-consuming while requiring bulky equipment. Recently, there has been increasing interest in using non-invasive measurable EEGs to compensate for these shortcomings. However, the prediction algorithms and processing procedures are both time-consuming because the raw data needs to be separated before the specific attributes can be obtained. Therefore, in this paper, we propose a new methodology that allows for the immediate application of deep learning models on raw EEG data without using the frequency properties of EEG. This proposed deep learning-based stroke disease prediction model was developed and trained with data collected from real-time EEG sensors. We implemented and compared different deep-learning models (LSTM, Bidirectional LSTM, CNN-LSTM, and CNN-Bidirectional LSTM) that are specialized in time series data classification and prediction. The experimental results confirmed that the raw EEG data, when wielded by the CNN-bidirectional LSTM model, can predict stroke with 94.0% accuracy with low FPR (6.0%) and FNR (5.7%), thus showing high confidence in our system. These experimental results demonstrate the feasibility of non-invasive methods that can easily measure brain waves alone to predict and monitor stroke diseases in real time during daily life. These findings are expected to lead to significant improvements for early stroke detection with reduced cost and discomfort compared to other measuring techniques.
An Improved Voltage Clamp Circuit Suitable for Accurate Measurement of the Conduction Loss of Power Electronic Devices
Authors: Yu Qiuping , Zhao Zhibin , Sun Peng , Zhao Bin , Cai Yumeng
Published: June 2021

Power electronic devices are essential components of high-capacity industrial converters. Accurate assessment of their power loss, including switching loss and conduction loss, is essential to improving electrothermal stability. To accurately calculate the conduction loss, a drain–source voltage clamp circuit is required to measure the on-state voltage. In this paper, the conventional drain–source voltage clamp circuit based on a transistor is comprehensively investigated by theoretical analysis, simulations, and experiments. It is demonstrated that the anti-parallel diodes and the gate-shunt capacitance of the conventional drain–source voltage clamp circuit have adverse impacts on the accuracy and security of the conduction loss measurement. Based on the above analysis, an improved drain–source voltage clamp circuit, derived from the conventional drain–source voltage clamp circuit, is proposed to solve the above problems. The operational advantages, physical structure, and design guidelines of the improved circuit are fully presented. In addition, to evaluate the influence of component parameters on circuit performance, this article comprehensively extracts three electrical quantities as judgment indicators. Based on the working mechanism of the improved circuit and the indicators mentioned above, general mathematical analysis and derivation are carried out to give guidelines for component selection. Finally, extensive experiments and detailed analyses are presented to validate the effectiveness of the proposed drain–source voltage clamp circuit. Compared with the conventional drain–source voltage clamp circuit, the improved drain–source voltage clamp circuit has higher measurement accuracy and working security when measuring conduction loss, and the proposed component selection method is verified to be reasonable and effective for better utilizing the clamp circuit.
V2X Wireless Technology Identification Using Time–Frequency Analysis and Random Forest Classifier
Authors: Skiribou Camelia , Elbahhar Fouzia
Published: June 2021

Signal identification is of great interest for various applications such as spectrum sharing and interference management. A typical signal identification system can be divided into two steps. A feature vector is first extracted from the received signal, then a decision is made by a classification algorithm according to its observed values. Some existing techniques show good performance but they are either sensitive to noise level or have high computational complexity. In this paper, a machine learning algorithm is proposed for the identification of vehicular communication signals. The feature vector is made up of Instantaneous Frequency (IF) resulting from time–frequency (TF) analysis. Its dimension is then reduced using the Singular Value Decomposition (SVD) technique, before being fed into a Random Forest classifier. Simulation results show the relevance and the low complexity of IF features compared to existing cyclostationarity-based ones. Furthermore, we found that the same accuracy can be maintained regardless of the noise level. The proposed framework thus provides a more accurate, robust and less complex V2X signal identification system.
Single Photon Avalanche Diode Arrays for Time-Resolved Raman Spectroscopy
Authors: Madonini Francesca , Villa Federica
Published: June 2021

The detection of peaks shifts in Raman spectroscopy enables a fingerprint reconstruction to discriminate among molecules with neither labelling nor sample preparation. Time-resolved Raman spectroscopy is an effective technique to reject the strong fluorescence background that profits from the time scale difference in the two responses: Raman photons are scattered almost instantaneously while fluorescence shows a nanoseconds time constant decay. The combination of short laser pulses with time-gated detectors enables the collection of only those photons synchronous with the pulse, thus rejecting fluorescent ones. This review addresses time-gating issues from the sensor standpoint and identifies single photon avalanche diode (SPAD) arrays as the most suitable single-photon detectors to be rapidly and precisely time-gated without bulky, complex, or expensive setups. At first, we discuss the requirements for ideal Raman SPAD arrays, particularly focusing on the design guidelines for optimized on-chip processing electronics. Then we present some existing SPAD-based architectures, featuring specific operation modes which can be usefully exploited for Raman spectroscopy. Finally, we highlight key aspects for future ultrafast Raman platforms and highly integrated sensors capable of undistorted identification of Raman peaks across many pixels.
Efficient Cell Segmentation from Electroluminescent Images of Single-Crystalline Silicon Photovoltaic Modules and Cell-Based Defect Identification Using Deep Learning with Pseudo-Colorization
Authors: Lin Horng-Horng , Dandage Harshad Kumar , Lin Keh-Moh , Lin You-Teh , Chen Yeou-Jiunn
Published: June 2021

Solar cells may possess defects during the manufacturing process in photovoltaic (PV) industries. To precisely evaluate the effectiveness of solar PV modules, manufacturing defects are required to be identified. Conventional defect inspection in industries mainly depends on manual defect inspection by highly skilled inspectors, which may still give inconsistent, subjective identification results. In order to automatize the visual defect inspection process, an automatic cell segmentation technique and a convolutional neural network (CNN)-based defect detection system with pseudo-colorization of defects is designed in this paper. High-resolution Electroluminescence (EL) images of single-crystalline silicon (sc-Si) solar PV modules are used in our study for the detection of defects and their quality inspection. Firstly, an automatic cell segmentation methodology is developed to extract cells from an EL image. Secondly, defect detection can be actualized by CNN-based defect detector and can be visualized with pseudo-colors. We used contour tracing to accurately localize the panel region and a probabilistic Hough transform to identify gridlines and busbars on the extracted panel region for cell segmentation. A cell-based defect identification system was developed using state-of-the-art deep learning in CNNs. The detected defects are imposed with pseudo-colors for enhancing defect visualization using K-means clustering. Our automatic cell segmentation methodology can segment cells from an EL image in about 2.71 s. The average segmentation errors along the x-direction and y-direction are only 1.6 pixels and 1.4 pixels, respectively. The defect detection approach on segmented cells achieves 99.8% accuracy. Along with defect detection, the defect regions on a cell are furnished with pseudo-colors to enhance the visualization.
Characterization of Moravian Wines by Selected Chemical Parameters
Authors: Javorský Jan , Král Martin , Šnirc Marek , Árvay Július , Tremlová Bohuslava , Dordević Dani
Published: June 2021

Knowledge of analytical values in wines is essential to ensure product safety and compliance with legislation, and it is also essential to understand the various technologies in wine production. The aim of this work was to evaluate the analytical parameters of bottled Moravian wines from the Znojmo sub-region, from harvests 2015 and 2016. Basic oenological parameters and biologically active substances were evaluated. Moreover, we evaluated conditions during bottle aging in wines from harvest 2016. The results of the basic analytical values such as total phenolic acid (TPA), total sulfur dioxide (SO2), pH, actual alcohol content (EtOH), and titratable acidity (TA) were in accordance with generally known values in wines and met the legislative requirements within oenological practices. Biologically active substances, such as gallic acid, trans-caffeic acid (TCA), trans-p-coumaric acid (TPCA), rutin, ferulic acid (FA), myricetin, resveratrol, and quercetin were identified. Comparing the analytical values of individual types of wine leads to a better understanding of winemaking technology and the development of wine as such. The subject of the study was also the monitoring of produced grape pomace incurred during wine production harvest 2015 with the indication of possibilities of its further use.
Language Ideologies, Practices, and Kindergarteners’ Narrative Macrostructure Development: Crucial Factors for Sustainable Development of Early Language Education
Authors: Yin Jing , Ding Yan , Fan Lin
Published: June 2021

This paper explored crucial factors to achieve sustainable development of early language education by examining the relationship between two dimensions of family language policy—language ideologies and language practices—as well as the relationship between family language policy and the development of children’s narrative macrostructure. Data were collected via a language performance test and a questionnaire survey of 131 kindergartners from 10 kindergartens in a Chinese city. Structural equation modeling corroborated the relationship between family language ideologies and family language practices proposed by family language policy theorists. Results showed that family language policy significantly predicted kindergarteners’ development of narrative macrostructure. In addition, age was shown to be a significant predictor of narrative macrostructure development, whereas gender was not. Implications for early intervention of children’s narrative macrostructure development were discussed.
Framing Corporate Social Responsibility to Achieve Sustainability in Urban Industrialization: Case of Bangladesh Ready-Made Garments (RMG)
Authors: Saha Polin Kumar , Akhter Shahida , Hassan Azizul
Published: June 2021

According to both scholars and society, Corporate Social Responsibility (CSR) plays a controversial role in terms of corporate management towards sustainability. The business has presently become an integrated with the society and takes in a complex form of global demand for sustainability management. Due to the globalization of business, it is difficult to form a common sustainability model for CSR while its approach could be an opportunity for achieving sustainability. Evidently, a strong connection is found between the CSR approach and achieving urban sustainability since a smart urbanization requires a well-planned industrialization process that could be accelerated by the proper application of CSR. However, the CSR concept has already been initiated and developed in Western developed countries. Nowadays, it is being widely practiced by the developing countries as well. The developing country Bangladesh takes CSR issues seriously. Therefore, the study seeks the sustainability prospects of CSR by considering sustainability challenges in the rapid development of the “Ready-made Garments (RMG)” industry and corporate sector in Bangladesh. Finally, this paper explores some strategic paths to initiate sustainable development by framing the conditions and challenges of CSR.
Assessment of Visual Values as a Tool Supporting the Design Decisions of the Cultural Park Protection Plan. The Case of Kazimierz and Stradom in Kraków
Authors: Forczek-Brataniec Urszula
Published: June 2021

Krakow is a city of high landscape values, which has found confirmation in the entry onto the UNESCO heritage list. Its cultural landscape requires protection and clarification within the context of intensive tourist use and a rapid pace of urban spatial development. For preservation protection and restoration of landscape values, the city authorities undertook work on the creation of a Cultural Park in the Stradom and Kazimierz districts, providing a comprehensive, sustainable, and multidisciplinary approach to natural, cultural and visual values of the urban structure. The article presents the application of the method of research on visual values in order to protect individual scenic resources of the historical urban structure. It is one of the analytical studies of a comprehensive protection plan project. This project defines the scope, framework and methods of development and management of a Cultural Park. The task of the visual analysis was to identify, characterize and evaluate the visual resources. It created a visual framework for further development of the historical district while preserving its local spatial identity. The studies resulted in a division into zones according to their nature and intensity of activities as well as outlining protection zones and intervention zones adjusted to individual characteristics of those places. An original method combining achievements of the method of landscape and visual assessment (LVIA) as well as achievements of the Krakow School of Landscape Architecture (KSLA) in terms of cultural landscape assessment was used for the research. The applied method provided guidelines to support sustainable project decisions regarding further development of the district for the preservation of local spatial identity. Its universal character creates possibilities for its application into the plans of other Krakow districts and is intended to be applicable to both urban and rural structures.
Macadamia Husk Compost Improved Physical and Chemical Properties of a Sandy Loam Soil
Authors: Maselesele Dembe , Ogola John B.O. , Murovhi Romeo N.
Published: June 2021

Poor soil fertility caused mainly by low and declining soil organic carbon is one of the major constraints limiting crop productivity in tropical and subtropical regions of South Africa. We evaluated the effect of macadamia husk compost (MHC) on selected chemical and physical properties of a sandy loam soil in NE South Africa in two successive seasons. The treatments, laid out in randomised, complete block design and replicated four times, were: (i) zero control, (ii) inorganic fertilizer (100:60:60 NPK Kg ha−1), (iii) MHC at 15 t ha−1, and (iv) MHC at 30 t ha−1. Soil bulk density; water holding capacity; soil pH; electrical conductivity (EC); organic carbon; total N; and available P, K, Ca, Mg, Al, Zn, and Cu were determined at 0–15 cm soil depth. Macadamia husk compost application decreased bulk density and increased water holding capacity. MHC and inorganic fertilizer increased soil pH, organic carbon, total N, C:N ratio, available P, exchangeable cations, and micronutrients but the effect was more pronounced under MHC treatments in both seasons. The positive effect of MHC on soil physicochemical properties was associated with an increase in soil organic carbon due to MHC application; hence, MHC may offer a sustainable option of increasing soil productivity, particularly in areas characterised by low SOC.
Optimized High-Performance Liquid Chromatography Method for Determining Nine Cytokinins, Indole-3-acetic Acid and Abscisic Acid
Authors: Qi Beibei , Wu Chao , Liang Huiling , Cui Kehui , Fahad Shah , Wang Manlian , Liu Baoyu , Nie Lixiao , Huang Jianliang , Tang Hui
Published: June 2021

Liquid-liquid extraction and solid phase extraction followed by high-performance liquid chromatography (HPLC) connected with ultraviolet (UV) detection were used for the determination of phytohormones. The parameters influencing the performance of the HPLC-UV method, including composition of the mobile phase for gradient elution, column temperature, flow rate, and detection wavelength, were optimized. This method can simultaneously determine 11 phytohormones, including nine cytokinins, indole-3-acetic acid, and abscisic acid. The limit of detection of this method is 0.22 to 1.1 µg L−1, and the coefficient factors of linear regression are >0.998. The recoveries of the target phytohormones ranged between 62.1~109.4%, and the relative standard deviations were <10%. This method is suitable for determining phytohormones, especially cytokinins, in young panicles, roots, and xylem sap of rice plants.
The 9-SRA Scale: A Simplified 9-Items Version of the SRA Scale to Assess Altruism
Authors: Manzur Enrique , Olavarrieta Sergio
Published: June 2021

In a classic study, Rushton and colleagues presented a 20-item scale to assess the altruistic behavior of people: the Self-Report Altruism (SRA) scale. This article focuses on the development of a simplified 9-item scale—the 9-SRA scale—describing the entire refinement and validation procedure using exploratory and confirmatory factor analysis. The 9-SRA shows adequate reliability and validity and represents a more parsimonious instrument to assess altruism and for use in empirical studies focused on human and prosocial behavior. The article discusses the advantages and potential applications of the new scale.
Port Greening: Discrete Choice Analysis Investigation on Environmental Parameters Affecting Container Shipping Companies’ Behaviors
Authors: Franchi Lorenzo , Vanelslander Thierry
Published: June 2021

For centuries, ports have functioned as an economic engine, facilitating maritime transport, offering prosperity and social development to the host communities. Ports are gateways for international trade playing a vital role in the world economy, but it is not excluded that port operations can also have adverse effects on the environment. Air and water emissions, marine sediments, noise, waste generation, loss and degradation of terrestrial habitats and changes to marine ecosystems are just some of the leading environmental challenges with port’s operations. Environmental management within port operations has been a rapidly growing trend, with many ports around the world adopting different types of approaches and initiatives to improve ecological performance. Despite that many ports around the world have implemented greening strategies for growth and sustainable development, there are still many other ports that work less than they should do on environmental aspects and on the generation of ‘green ports’. These latter have fallen behind in the development of the theme. Therefore, the work reported here aims at analyzing what the best way to act should be, even starting from the beginning for a port that is not very innovative, in order to pursue the practical and theoretical levels of ‘green port’.
Gamified Wearable Fitness Tracker for Physical Activity: A Comprehensive Literature Review
Authors: Cho Inje , Kaplanidou Kyriaki , Sato Shintaro
Published: June 2021

Recently, gamified wearable fitness trackers have received greater attention and usage among sport consumers. Although a moderate amount of aerobic physical activity can significantly reduce the risk of many serious illnesses, physical inactivity issues are still prominent. Although wearable fitness trackers have the potential to contribute to physical activity engagement and sustainable health outcomes, there are dwindling engagement and discontinuance issues. Thus, examining its gamification elements and role in physical activity becomes critical. This study examined the gamification elements in wearable fitness trackers and their role in physical activity and sports engagement. A comprehensive literature review yielded 26 articles that empirically measured a variety of gamification features and the effect of the device on physical activity and sports engagement. The study suggests three key gamification themes: goal-based, social-based, and rewards-based gamification that can be a point of interest for future scholars and practitioners. Based on the review, we propose a conceptual framework that embraces motivational affordances and engagement in physical activity and sports.
Creating Shared Value to Enhance Customer Loyalty: A Case of a Sporting Goods Company in Korean Athletic Shoe Market
Authors: Kim Sang-soo , Baek Woo-yeul , Byon Kevin K. , Ju Sung-bum
Published: June 2021

Despite the efforts of academia on exploring the merits of creating shared value, prior relevant literature seems to have a limitation that overlooks the environmental contribution suggested as a crucial component of creating shared value program by Porter and Kramer. More importantly, since most of the existing creating shared value-related studies have focused on firms in the general marketing field, there is a lack of research on the efficacy of creating shared value programs that are implemented by sporting goods companies. Thus, the objective of the present study was to examine the influence of consumers’ perceived creating shared value activities of sporting goods firm on brand image and customer loyalty in the context of the Korean sporting goods market. A total of 187 Korean sport consumers participated in the present study. Results indicated that sporting goods consumers’ perceived economic, social, and environmental values had significant impacts on brand image and, in turn, brand image positively affected customer loyalty. Consequently, the current study’s findings provide sporting goods firms with practical implications for launching creating shared value programs.
Urban Design and Rivers: A Critical Review of Theories Devising Planning and Design Concepts to Define Riverside Urbanity
Authors: Pattacini Laurence
Published: June 2021

In a post-industrial world one of the foci of urbanism has been on the regeneration of former industrial sites along urban rivers. This is a contemporary urban design issue that needs further attention, especially in relation to urban forms and design interventions. This paper sets out to contribute to research in design by reviewing past theories and practices in order to inform the formation of conceptual ideas. These are of importance to inform practice and ensure responsive and responsible processes in planning and design. Such a review has hitherto been lacking, but with a renewed interest in urban densification, research in the design of cities is required. Thus, this paper provides a critical assessment of theories, which are identified and categorised in relation to urban riverside regeneration. For this study, urban design is considered as a craft requiring ‘savoir faire’ to ensure the functionality and quality of urban spaces. Transferable principles and ideas are identified in relation to the specific characteristics of riverside locations contributing to the definition of a ‘riverside urbanity’. It provides a theoretical framework identifying types of riverside landscapes, including the relationship between urban forms and river corridors.
Spatial Pattern Analysis of the Ecosystem Services in the Guangdong-Hong Kong-Macao Greater Bay Area Using Sentinel-1 and Sentinel-2 Imagery Based on Deep Learning Method
Authors: Wen Dawei , Ma Song , Zhang Anlu , Ke Xinli
Published: June 2021

Assessment of ecosystem services supply, demand, and budgets can help to achieve sustainable urban development. The Guangdong-Hong Kong-Macao Greater Bay Area, as one of the most developed megacities in China, sets up a goal of high-quality development while fostering ecosystem services. Therefore, assessing the ecosystem services in this study area is very important to guide further development. However, the spatial pattern of ecosystem services, especially at local scales, is not well understood. Using the available 2017 land cover product, Sentinel-1 SAR and Sentinel-2 optical images, a deep learning land cover mapping framework integrating deep change vector analysis and the ResUnet model was proposed. Based on the produced 10 m land cover map for the year 2020, recent spatial patterns of the ecosystem services at different scales (i.e., the GBA, 11 cities, urban–rural gradient, and pixel) were analyzed. The results showed that: (1) Forest was the primary land cover in Guangzhou, Huizhou, Shenzhen, Zhuhai, Jiangmen, Zhaoqing, and Hong Kong, and an impervious surface was the main land cover in the other four cities. (2) Although ecosystem services in the GBA were sufficient to meet their demand, there was undersupply for all the three general services in Macao and for the provision services in Zhongshan, Dongguan, Shenzhen, and Foshan. (3) Along the urban–rural gradient in the GBA, supply and demand capacity showed an increasing and decreasing trend, respectively. As for the city-level analysis, Huizhou and Zhuhai showed a fluctuation pattern while Jiangmen, Zhaoqing, and Hong Kong presented a decreasing pattern along the gradient. (4) Inclusion of neighborhood landscape led to increased demand scores in a small proportion of impervious areas and oversupply for a very large percent of bare land.
Static Behavior of a Retractable Suspen-Dome Structure
Authors: Shen Xuhong , Zhang Qian , Lee Daniel Sang-Hoon , Cai Jianguo , Feng Jian
Published: June 2021

A new design of a radially retractable roof structure based on the concept of the suspen-dome is proposed in this paper. The radially foldable bar structure is strengthened by the lower cable-strut system to obtain a higher structural stiffness. Then the comparison of the static behavior between the retractable suspen-domes and their corresponding foldable bar shell with quadrangular mesh is discussed. Moreover, the effects of different structural and geometric parameters, such as the rise-to-span ratio, the cross-section area of beams, cables and struts, and the pre-stress level of the lower cable-strut system, on the nodal displacements and member forces are investigated systematically. The results show that higher structural stiffness is anticipated with the introduction of cable-strut systems into the hybrid structure. When the rise-to-span ratio is equal to 0.2, the maximal nodal displacement of the suspen-dome reaches the minimal value. The increase of the cross-section area of steel beams contributes an enormous amount to the structural stiffness. Increasing cable and strut sections has little impact on the mechanical behavior of suspen-domes. Moreover, the prestress level of cable-strut systems has a slight influence on the nodal displacements and member forces. Parametric analysis can be regarded as an essential basis for the optimization of the design of a retractable suspen-dome structure.
Research on Hydroelastic Response of an FMRC Hexagon Enclosed Platform
Authors: Liu Wei-Qin , Xiong Luo-Nan , Zhang Guo-Wei , Yang Meng , Wu Wei-Guo , Song Xue-Min
Published: June 2021

The numerical hydroelastic method is used to study the structural response of a hexagon enclosed platform (HEP) of flexible module rigid connector (FMRC) structure that can provide life accommodation, ship berthing and marine supply for ships sailing in the deep ocean. Six trapezoidal floating structures constitute the HEP structure so that it is a symmetrical very large floating structure (VLFS). The HEP has the characteristics of large area and small depth, so its hydroelastic response is significant. Therefore, this paper studies the structural responses of a hexagon enclosed platform of FMRC structure in waves by means of a 3D potential-flow hydroelastic method based on modal superposition. Numerical models, including the hydrodynamic model, wet surface model and finite element method (FEM) model, are established, a rigid connection is simulated by many-point-contraction (MPC) and the number of wave cases is determined. The load and structural response of HEP are obtained and analyzed in all wave cases, and frequency-domain hydroelastic calculation and time-domain hydroelastic calculation are carried out. After obtaining a number of response amplitude operators (RAOs) for stress and time-domain stress histories, the mechanism of the HEP structure is compared and analyzed. This study is used to guide engineering design for enclosed-type ocean platforms.
The Effect of Herpes Simplex Virus-Type-1 (HSV-1) Oncolytic Immunotherapy on the Tumor Microenvironment
Authors: Uche Ifeanyi Kingsley , Kousoulas Konstantin G. , Rider Paul J. F.
Published: June 2021

The development of cancer causes disruption of anti-tumor immunity required for surveillance and elimination of tumor cells. Immunotherapeutic strategies aim for the restoration or establishment of these anti-tumor immune responses. Cancer immunotherapies include immune checkpoint inhibitors (ICIs), adoptive cellular therapy (ACT), cancer vaccines, and oncolytic virotherapy (OVT). The clinical success of some of these immunotherapeutic modalities, including herpes simplex virus type-1 derived OVT, resulted in Food and Drug Administration (FDA) approval for use in treatment of human cancers. However, a significant proportion of patients do not respond or benefit equally from these immunotherapies. The creation of an immunosuppressive tumor microenvironment (TME) represents an important barrier preventing success of many immunotherapeutic approaches. Mechanisms of immunosuppression in the TME are a major area of current research. In this review, we discuss how oncolytic HSV affects the tumor microenvironment to promote anti-tumor immune responses. Where possible we focus on oncolytic HSV strains for which clinical data is available, and discuss how these viruses alter the vasculature, extracellular matrix and immune responses in the tumor microenvironment.
Early Onset of SARS-COV-2 Antibodies after First Dose of BNT162b2: Correlation with Age, Gender and BMI
Authors: Pellini Raul , Venuti Aldo , Pimpinelli Fulvia , Abril Elva , Blandino Giovanni , Campo Flaminia , Conti Laura , De Virgilio Armando , De Marco Federico , Di Domenico Enea Gino , Di Bella Ornella , Di Martino Simona , Ensoli Fabrizio , Giannarelli Diana , Mandoj Chiara , Manciocco Valentina , Marchesi Paolo , Mazzola Francesco , Moretto Silvia , Petruzzi Gerardo , Petrone Fabrizio , Pichi Barbara , Pontone Martina , Zocchi Jacopo , Vidiri Antonello , Vujovic Branka , Piaggio Giulia , Morrone Aldo , Ciliberto Gennaro
Published: June 2021

Background: The first goal of the study was to analyse the antibody titre 21 days after the first dose of the BNT162b2 vaccine in a group of 252 healthcare workers (HCW). The second goal was to analyse how the antibody titre changes in correlation with age, gender and body mass index (BMI). Methods: Participants had a nasopharyngeal swab for SARS-CoV-2 and were assessed for the presence of SARS-CoV-2 antibodies at baseline and 21 days after the BNT162b2 priming dose. Results: First dose of BNT162b2 activated immune responses in 98% of the participants. Five HWC had no increase in antibody titre 21 days after the first dose. Antibody titre was greater in young (<38 years) vs. older participants (<38 vs. 47–56 p = 0.002; <38 vs. >56 p = 0.001). Higher antibody levels were detected in underweight vs. pre-obesity group (p = 0.026) and in normal-weight vs. pre-obesity group (p = 0.007). This association was confirmed after adjusting for age (p = 0.0001) and gender (p = 0.00001). Conclusions: Our study demonstrates that a single dose of BNT162b2 activates the immune response, and being young and normal-weight correlate positively with this response. Larger specifically designed clinical trials are needed to validate these results.
A Possible Role for HSV-1-Specific Humoral Response and PILRA rs1859788 Polymorphism in the Pathogenesis of Parkinson’s Disease
Authors: Agostini Simone , Mancuso Roberta , Costa Andrea S. , Citterio Lorenzo A. , Guerini Franca R. , Meloni Mario , Navarro Jorge , Clerici Mario
Published: June 2021

The etiology of Parkinson’s disease (PD), a progressive nervous system disorder that affects movement, is still unknown; both genetic and environmental factor are believed to be involved in onset of the disease and its development. Herpes simplex virus type 1 (HSV-1), in particular, is suspected to have a role in PD. Paired Immunoglobulin-like type 2 receptor alpha (PILRA) is an inhibitory receptor that down-regulates inflammation and is expressed on innate immune cells. The PILRA rs1859788 polymorphism is protective against Alzheimer’s disease, even in relation with HSV-1 antibody titers, but no data are available in PD. We analyzed HSV-1 antibody titers and PILRA rs1859788 in PD (n = 51) and age-and sex-matched healthy controls (HC; n = 73). Results showed that HSV-1, but not cytomegalovirus (CMV) or human herpes virus type 6 (HHV-6) antibody titers were significantly higher in PD compared to HC (p = 0.045). The rs1859788 polymorphism was not differentially distributed between PD and HC, but the minor allele A was more frequently carried by PD (68%) compared to HC (50%) (p = 0.06). Notably, the rs1859788 minor allele A was statically more frequent in male PD (65%) compared to male HC (37%) (p = 0.036). Finally, no relation was found between HSV-1 antibody titers and PILRA genotype. Results herein suggest an involvement of HSV-1 in PD and indicate a possible interaction between PILRA gene polymorphisms and this neuropathology.
A Systematic Review of Interventions to Improve HPV Vaccination Coverage
Authors: Mavundza Edison J. , Iwu-Jaja Chinwe J. , Wiyeh Alison B. , Gausi Blessings , Abdullahi Leila H. , Halle-Ekane Gregory , Wiysonge Charles S.
Published: June 2021

Human papillomavirus (HPV) infection is the most common sexually transmitted infection worldwide. Although most HPV infections are transient and asymptomatic, persistent infection with high-risk HPV types may results in diseases. Although there are currently three effective and safe prophylactic HPV vaccines that are used across the world, HPV vaccination coverage remains low. This review evaluates the effects of the interventions to improve HPV vaccination coverage. We searched the Cochrane Central Register of Controlled Trials, PubMed, Web of Science, Scopus, and the World Health Organization International Clinical Trials Registry Platform and checked the reference lists of relevant articles for eligible studies. Thirty-five studies met inclusion criteria. Our review found that various evaluated interventions have improved HPV vaccination coverage, including narrative education, outreach plus reminders, reminders, financial incentives plus reminders, brief motivational behavioral interventions, provider prompts, training, training plus assessment and feedback, consultation, funding, and multicomponent interventions. However, the evaluation of these intervention was conducted in high-income countries, mainly the United States of America. There is, therefore, a need for studies to evaluate the effect of these interventions in low-and middle-income countries, where there is a high burden of HPV and limited HPV vaccination programs.
Effect of Vegetation Restoration on Soil Hydrology in Karst Area of Southwest China: Inspiration from Barrel Planting Experiments
Authors: Liu Ziqi , She Rong , Xiong Kangning , Li Yuan , Cai Lulu
Published: June 2021

The purpose of this study was to explore the effects of different vegetation restoration types on soil hydrology characteristics in the Karst Plateau Gorge and to clarify the soil moisture (θ) use characteristics. A barrel experiment was conducted to monitor θ and the water potential (Ψ) of three vegetation types (Zanthoxylum bungeanum (ZB), Zea mays L. (ZM), and Sophora tonkinensis (ST), Abandoned land (AL)) was used as a control to explore θ use conditions of each vegetation type. A larger surface permeability led to lower moisture storage. The soil moisture storage showed the law of ZM > ST > AL > ZB. The soil moisture storage also had obvious characteristics in dry-wet seasons. As a typical drought-tolerant crop, ZB responded more obviously to rainfall and had the highest effective replenishment amount and efficiency. Two processes were clearly involved in decreasing soil moisture, which could be divided into three stages of changes: a consumption period (CP), a moisture supplying period (SP), and a relatively stable period (RSP). CP occurred primarily in November to April, when θ was prone to water stress and required proper artificial replenishment. SP was characterized by limited rainfall replenishment in January and May, which significantly increased θ. During the rainy season, corresponding with RSP, θ fluctuated within a relatively stable range. At the end of the CP, the water shortage was more severe. In actual agricultural production, attention should be given to reasonable artificial recharge. This research aims to provide a theoretical basis for karst θ management.
Seasonal and Long-Term Connections between Trophic Status, Sestonic Chlorophyll, Nutrients, Organic Matter, and Monsoon Rainfall in a Multipurpose Reservoir
Authors: Jargal Namsrai , Atique Usman , Mamun Md , An Kwang-Guk
Published: June 2021

Due to rapid eutrophication, sustainable water quality management and supply are essential in drinking water sources and aquatic biota in large reservoirs. We evaluated the potentially crucial factors influencing the algal chlorophyll (CHL-a), nutrients, and the links between the rainfall and other vital elements in a large multipurpose reservoir (Yongdam Reservoir) during 2013–2019. We developed the empirical models on algal CHL-a, total phosphorus (TP), total nitrogen (TN), and TN:TP’s ambient ratios considering the maneuvering influence of Asian monsoons. The intensive rainfall during the monsoon months strongly impacted the nutrient regime and other vital factors. The seasonal patterns of algal CHL-a varied in response to the nutrient contents (TN, TP), suspended solids, and ambient N:P ratios along the longitudinal gradient. The conditional plot analysis, empirical modeling, and observations supported an overall P-limitation scenario, as was evident from the magnitude of N:P ratios (R2 = 0.36, F = 24.9, p < 0.001). Furthermore, the reservoir’s trophic status alluded to the larger particles and blue-green algae during the monsoon and postmonsoon months. The correlation analysis, Mann–Kendall trend test, and principal component analysis illustrated compelling links between CHL-a, TP, and rainfall regime. The outcomes suggested the reservoir was primarily controlled by phosphorus limitation, with an increasing CHL-a tendency along with nitrogen dilution. However, a slight decline in phosphorus was also detected. The Yongdam Reservoir is under the threat of recurrent eutrophication events that could jeopardize this vital drinking water facility due to increasing agricultural and anthropic activities.
Urban Flood Management through Urban Land Use Optimization Using LID Techniques, City of Addis Ababa, Ethiopia
Authors: Jemberie Mengistu A. , Melesse Assefa M.
Published: June 2021

In recent years, many urban areas in Ethiopia have experienced frequent flood events as a result of climate change and urban sprawl. Unplanned and unsustainable poor urban storm water management strategies will aggravate the impact and frequency of flood occurrence. In this study, impacts of urbanization and climate change on generated flood magnitude are analyzed using the urban hydrological model of Storm Water Management Model (SWMM) and Low Impact Development (LID) sustainable land use optimization techniques. Three rainfall distribution patterns (TS1, TS2 and TS3) in combination with rainfall duration periods of 10, 30 and 60 min and a pessimistic climate change scenario of RCP 4.5 compared to RCP 8.5 are used for the analysis purpose for selected infiltration and storage LID techniques (Bio-Retention Cell, Infiltration Trench and Rain Barrel). The study results showed that combined LID techniques have a significant impact on urban flood reduction of up to 75%. This significant amount of flood reduction is greater than the amount of excess flood magnitude which occurred as a result of climate change using the most pessimistic climate change scenario. The study results also confirmed that rainfall patterns have a significant impact on peak discharge for shorter rainfall durations. This study highly recommends using cost effective, easy and environmental adaptive and sustainable LID techniques for urban flood management in addition to existing drainage structures.
Assimilating X- and S-Band Radar Data for a Heavy Precipitation Event in Italy
Authors: Capecchi Valerio , Antonini Andrea , Benedetti Riccardo , Fibbi Luca , Melani Samantha , Rovai Luca , Ricchi Antonio , Cerrai Diego
Published: June 2021

During the night between 9 and 10 September 2017, multiple flash floods associated with a heavy-precipitation event affected the town of Livorno, located in Tuscany, Italy. Accumulated precipitation exceeding 200 mm in two hours was recorded. This rainfall intensity is associated with a return period of higher than 200 years. As a consequence, all the largest streams of the Livorno municipality flooded several areas of the town. We used the limited-area weather research and forecasting (WRF) model, in a convection-permitting setup, to reconstruct the extreme event leading to the flash floods. We evaluated possible forecasting improvements emerging from the assimilation of local ground stations and X- and S-band radar data into the WRF, using the configuration operational at the meteorological center of Tuscany region (LaMMA) at the time of the event. Simulations were verified against weather station observations, through an innovative method aimed at disentangling the positioning and intensity errors of precipitation forecasts. A more accurate description of the low-level flows and a better assessment of the atmospheric water vapor field showed how the assimilation of radar data can improve quantitative precipitation forecasts.
Prevalence of Antibiotic Resistance Genes in Pharmaceutical Wastewaters
Authors: Obayiuwana Amarachukwu , Ogunjobi Adeniyi , Ibekwe Abasiofiok
Published: June 2021

Pharmaceutical wastewaters are recognized as reservoirs of antibiotic resistance genes (ARGs) and antibiotic resistant bacteria (ARB), and also as hotspots for their horizontal gene transfer (HGT) using mobile genetic elements. Our study employed the use of PCR analysis of metagenomic DNA samples obtained from four pharmaceutical wastewaters using known primers to study the prevalence of thirty-six ARGs and four MGEs active against the commonly used antibiotics in Nigeria. The ARGs most frequently detected from the metagenomic DNA samples in each of the antibiotic classes under study include tetracycline [tet(G)], aminoglycoside [aadA, strA and strB], chloramphenicol [catA1], sulphonamides [sulI and sulII], and β-lactams and penicillins [blaOXA]. The ARGs showed a 100% prevalence in their various environmental sources. The pharmaceutical facility PFIV showed the highest concentration of ARGs in this study. The highest concentration for MGEs was shown by pharmaceutical facility PFIII, positive for intl1, intl2, and IFS genes. This study highlights the wide distribution of ARGs to the antibiotics tested in the wastewater, making pharmaceutical wastewater reservoirs of ARGs which could potentially be transferred from commensal microorganisms to human pathogens.