bluuebunny/crossref_metadata_2025 huggingface dataset:
Preparations of Poly(lactic acid) Dispersions in Water for Coating Applications
Authors: Belletti Giada , Buoso Sara , Ricci Lucia , Guillem-Ortiz Alejandro , Aragón-Gutiérrez Alejandro , Bortolini Olga , Bertoldo Monica
Published: August 2021

A green, effective methodology for the preparation of water-based dispersions of poly(lactic acid) (PLA) for coating purposes is herein presented. The procedure consists of two steps: in the first one, an oil-in-water emulsion is obtained by mixing a solution of PLA in ethyl acetate with a water phase containing surfactant and stabilizer. Different homogenization methods as well as oil/water phase ratio, surfactant and stabilizer combinations were screened. In the second step, the quantitative evaporation of the organic provides water dispersions of PLA that are stable, at least, over several weeks at room temperature or at 4 °C. Particle size was in the 200–500 nm range, depending on the preparation conditions, as confirmed by scanning electron microscope (SEM) analysis. PLA was found not to suffer significant molecular weight degradation by gel permeation chromatography (GPC) analysis. Furthermore, two selected formulations with glass transition temperature (Tg) of 51 °C and 34 °C were tested for the preparation of PLA films by drying in PTFE capsules. In both cases, continuous films that are homogeneous by Fourier-transform infrared spectroscopy (FT-IR) and SEM observation were obtained only when drying was performed above 60 °C. The formulation with lower Tg results in films which are more flexible and transparent.
Sonication, a Potential Technique for Extraction of Phytoconstituents: A Systematic Review
Authors: Ranjha Muhammad Modassar A. N. , Irfan Shafeeqa , Lorenzo José M. , Shafique Bakhtawar , Kanwal Rabia , Pateiro Mirian , Arshad Rai Naveed , Wang Lufeng , Nayik Gulzar Ahmad , Roobab Ume , Aadil Rana Muhammad
Published: August 2021

Traditional extraction techniques have lost their optimum performance because of rising consumer demand and novel technologies. In this regard, several techniques were developed by humans for the extraction of plant materials from various indigenous sources, which are no longer in use. Many of the techniques are not efficient enough to extract maximum plant material. By this time, evolution in extraction has led to development of various techniques including microfiltration, pulsed electric fields, high pressure, microwave assistance, enzyme assistance, supercritical fluid, subcritical fluid and ultrasonication. These innovations in food processing/extraction are known as “Green Food Processing”. These technologies were basically developed by focusing on three universal parameters: simplicity, energy efficiency and economy. These green technologies are practical in a number of different food sectors, mostly for preservation, inhibition of microorganisms, inactivation of enzymes and extraction of plant material. Like the others, ultrasonication could also be used for the said purposes. The primary objective of this review is to confine the potential use of ultrasonication for extraction of oils, pectin and phytochemicals by reviewing the literature systematically.
The Openseminary Methodology: Practical Theology as Personal, Local and Transformative
Authors: Macallan Brian
Published: August 2021

Theological education continues to be subject to rapid social and technological change, which is further exacerbated by the recent global pandemic. Practical theology as a discipline continues to grow, being well placed methodologically to engage with diverse contexts and these global realities. The task for theological education is whether it can meet these challenges and be part of the transformation required. Openseminary as a methodology and program was developed in the early 2000s by Wynand De Kock to enable students to both learn practical theology as a methodology, as well as reflect theologically in their own context. Over the last two decades, it has run in South Africa, at Tabor College in Australia, as well as Palmer Seminary in the United States. In what follows, the methodology and program are explored in terms of their genesis, history, and current articulation. It is argued that it is a practical theological methodology well suited to the personal, local, and transformative goals of theological education today.
Earnings Management, Related Party Transactions and Corporate Performance: The Moderating Role of Internal Control
Authors: Zimon Grzegorz , Appolloni Andrea , Tarighi Hossein , Shahmohammadi Seyedmohammadali , Daneshpou Ebrahim
Published: August 2021

The primary purpose of this study is to investigate the impacts of earnings management (EM) and related party transactions (RPTs) on corporate financial performance in an emerging market, Iran. This paper also aims to examine the moderating role of internal control weakness (ICW) in the relationship between them. The study sample includes 108 Iranian manufacturing companies listed on the Tehran Stock Exchange (TSE) between 2013 and 2018, and panel data with random effects are used to test the hypotheses. When an accounting-based measure called ROA is defined as a proxy for corporate performance, the results show that there is a negative association between real earnings management (REM) and corporate financial situation, while accrual-based earnings management (AEM) and firm value are correlated positively. However, when Tobin’s Q index is defined as a proxy for corporate performance, we do not find any significant association between them. Consistent with the tunneling hypothesis or agency theory, our findings confirm RPTs damage corporate value (ROA and Tobin’s Q) because managers probably consider it a mechanism to exploit enterprise resources owing to existing conflictual interests. Moreover, purchase-related party transactions lead to lower ROA, whereas sale-related party transactions and Tobin’s Q are correlated negatively. Moreover, weak internal control has a positive moderating influence on the linkage between AEM and Tobin’s Q index. Finally, we provide robust evidence that there is a positive association between sale growth and institutional owners with ROA and Tobin’s Q, although financial leverage and mergers and acquisitions (M&A) have a destructive effect on corporate value.
Review of Wide-Baseline Stereo Image Matching Based on Deep Learning
Authors: Yao Guobiao , Yilmaz Alper , Meng Fei , Zhang Li
Published: August 2021

Strong geometric and radiometric distortions often exist in optical wide-baseline stereo images, and some local regions can include surface discontinuities and occlusions. Digital photogrammetry and computer vision researchers have focused on automatic matching for such images. Deep convolutional neural networks, which can express high-level features and their correlation, have received increasing attention for the task of wide-baseline image matching, and learning-based methods have the potential to surpass methods based on handcrafted features. Therefore, we focus on the dynamic study of wide-baseline image matching and review the main approaches of learning-based feature detection, description, and end-to-end image matching. Moreover, we summarize the current representative research using stepwise inspection and dissection. We present the results of comprehensive experiments on actual wide-baseline stereo images, which we use to contrast and discuss the advantages and disadvantages of several state-of-the-art deep-learning algorithms. Finally, we conclude with a description of the state-of-the-art methods and forecast developing trends with unresolved challenges, providing a guide for future work.
Improved Streamflow Forecast in a Small-Medium Sized River Basin with Coupled WRF and WRF-Hydro: Effects of Radar Data Assimilation
Authors: Gu Tianwei , Chen Yaodeng , Gao Yufang , Qin Luyao , Wu Yuqing , Wu Yazhen
Published: August 2021

Accurate and long leading time flood forecasting is very important for flood disaster mitigation. It is an effective method to couple the Quantitative Precipitation Forecast (QPF) products provided by Numerical Weather Prediction (NWP) models to a distributed hydrological model with the goal of extending the leading time for flood forecasting. However, the QPF products contain a certain degree of uncertainty and would affect the accuracy of flood forecasting, especially in the mountainous regions. Radar data assimilation plays an important role in improving the quality of QPF and further improves flood forecasting. In this paper, radar data assimilation was applied in order to construct a high-resolution atmospheric-hydrological coupling model based on the WRF and WRF-Hydro models. Four experiments with conventional observational and radar data assimilation were conducted to evaluate the flood forecasting capability of this coupled model in a small-medium sized basin based on eight typical flood events. The results show that the flood forecast skills are highly QPF-dependent. The QPF from the WRF model is improved by assimilating radar data and further increasing the accuracy of flood forecasting, although both precipitation and flood are slightly over-forecasted. However, the improvements by assimilating conventional observational data are not obvious. In general, radar data assimilation can improve flood forecasting effectively in a small-medium sized basin based on the atmospheric-hydrological coupling model.
Wide Bandwidth Vibration Energy Harvester with Embedded Transverse Movable Mass
Authors: Jackson Nathan , Rodriguez Luis A. , Adhikari Rahul
Published: August 2021

One of the biggest challenges associated with vibration energy harvesters is their limited bandwidth, which reduces their effectiveness when utilized for Internet of Things applications. This paper presents a novel method of increasing the bandwidth of a cantilever beam by using an embedded transverse out-of-plane movable mass, which continuously changes the resonant frequency due to mass change and non-linear dynamic impact forces. The concept was investigated through experimentation of a movable mass, in the form of a solid sphere, that was embedded within a stationary proof mass with hollow cylindrical chambers. As the cantilever oscillated, it caused the movable mass to move out-of-plane, thus effectively altering the overall effective mass of the system during operation. This concept combined high bandwidth non-linear dynamics from the movable mass with the high power linear dynamics from the stationary proof mass. This paper experimentally investigated the frequency and power effects of acceleration, the amount of movable mass, the density of the mass, and the size of the movable mass. The results demonstrated that the bandwidth can be significantly increased from 1.5 Hz to >40 Hz with a transverse movable mass, while maintaining high power output. Dense movable masses are better for high acceleration, low frequency applications, whereas lower density masses are better for low acceleration applications.
An On-Demand Charging for Connected Target Coverage in WRSNs Using Fuzzy Logic and Q-Learning
Authors: Nguyen Phi Le , La Van Quan , Nguyen Anh Duy , Nguyen Thanh Hung , Nguyen Kien
Published: August 2021

In wireless rechargeable sensor networks (WRSNs), a mobile charger (MC) moves around to compensate for sensor nodes’ energy via a wireless medium. In such a context, designing a charging strategy that optimally prolongs the network lifetime is challenging. This work aims to solve the challenges by introducing a novel, on-demand charging algorithm for MC that attempts to maximize the network lifetime, where the term “network lifetime” is defined by the interval from when the network starts till the first target is not monitored by any sensor. The algorithm, named Fuzzy Q-charging, optimizes both the time and location in which the MC performs its charging tasks. Fuzzy Q-charging uses Fuzzy logic to determine the optimal charging-energy amounts for sensors. From that, we propose a method to find the optimal charging time at each charging location. Fuzzy Q-charging leverages Q-learning to determine the next charging location for maximizing the network lifetime. To this end, Q-charging prioritizes the sensor nodes following their roles and selects a suitable charging location where MC provides sufficient power for the prioritized sensors. We have extensively evaluated the effectiveness of Fuzzy Q-charging in comparison to the related works. The evaluation results show that Fuzzy Q-charging outperforms the others. First, Fuzzy Q-charging can guarantee an infinite lifetime in the WSRNs, which have a sufficient large sensor number or a commensurate target number. Second, in other cases, Fuzzy Q-charging can extend the time until the first target is not monitored by 6.8 times on average and 33.9 times in the best case, compared to existing algorithms.
Examination of Potential of Thermopile-Based Contactless Respiratory Gating
Authors: Zhan Qi , Wang Wenjin , Ding Xiaorong
Published: August 2021

To control the spread of coronavirus disease 2019 (COVID-19), it is effective to perform a fast screening of the respiratory rate of the subject at the gate before entering a space to assess the potential risks. In this paper, we examine the potential of a novel yet cost-effective solution, called thermopile-based respiratory gating, to contactlessly screen a subject by measuring their respiratory rate in the scenario with an entrance gate. Based on a customized thermopile array system, we investigate different image and signal processing methods that measure respiratory rate from low-resolution thermal videos, where an automatic region-of-interest selection-based approach obtains a mean absolute error (MAE) of 0.8 breaths per minute. We show the feasibility of thermopile-based respiratory gating and quantify its limitations and boundary conditions in a benchmark (e.g., appearance of face mask, measurement distance and screening time). The technical validation provided by this study is helpful for designing and implementing a respiratory gating solution toward the prevention of the spread of COVID-19 during the pandemic.
A Proof-of-Concept Study Using Numerical Simulations of an Acoustic Spheroid-on-a-Chip Platform for Improving 3D Cell Culture
Authors: Yahyazadeh Shourabi Arash , Salajeghe Roozbeh , Barisam Maryam , Kashaninejad Navid
Published: August 2021

Microfluidic lab-on-chip devices are widely being developed for chemical and biological studies. One of the most commonly used types of these chips is perfusion microwells for culturing multicellular spheroids. The main challenge in such systems is the formation of substantial necrotic and quiescent zones within the cultured spheroids. Herein, we propose a novel acoustofluidic integrated platform to tackle this bottleneck problem. It will be shown numerically that such an approach is a potential candidate to be implemented to enhance cell viability and shrinks necrotic and quiescent zones without the need to increase the flow rate, leading to a significant reduction in costly reagents’ consumption in conventional spheroid-on-a-chip platforms. Proof-of-concept, designing procedures and numerical simulation are discussed in detail. Additionally, the effects of acoustic and hydrodynamic parameters on the cultured cells are investigated. The results show that by increasing acoustic boundary displacement amplitude (d0), the spheroid’s proliferating zone enlarges greatly. Moreover, it is shown that by implementing d0  = 0.5 nm, the required flow rate to maintain the necrotic zone below 13% will be decreased 12 times compared to non-acoustic chips.
Electrical Properties and Strain Sensing Mechanisms in Hybrid Graphene Nanoplatelet/Carbon Nanotube Nanocomposites
Authors: Sánchez-Romate Xoan F. , Jiménez-Suárez Alberto , Campo Mónica , Ureña Alejandro , Prolongo Silvia G.
Published: August 2021

Electrical and electromechanical properties of hybrid graphene nanoplatelet (GNP)/carbon nanotube (CNT)-reinforced composites were analyzed under two different sonication conditions. The electrical conductivity increases with increasing nanofiller content, while the optimum sonication time decreases in a low viscosity media. Therefore, for samples with a higher concentration of GNPs, an increase of sonication time of the hybrid GNP/CNT mixture generally leads to an enhancement of the electrical conductivity, up to values of 3 S/m. This means that the optimum sonication process to achieve the best performances is reached in the longest times. Strain sensing tests show a higher prevalence of GNPs at samples with a high GNP/CNT ratio, reaching gauge factors of around 10, with an exponential behavior of electrical resistance with applied strain, whereas samples with lower GNP/CNT ratio have a more linear response owing to a higher prevalence of CNT tunneling transport mechanisms, with gauge factors of around 3–4.
A Novel Anti-Noise Fault Diagnosis Approach for Rolling Bearings Based on Convolutional Neural Network Fusing Frequency Domain Feature Matching Algorithm
Authors: Zhou Xiangyu , Mao Shanjun , Li Mei
Published: August 2021

The development of deep learning provides a new research method for fault diagnosis. However, in the industrial field, the labeled samples are insufficient and the noise interference is strong so that raw data obtained by the sensor are occupied with noise signal. It is difficult to recognize time-domain fault signals under the severe noise environment. In order to solve these problems, the convolutional neural network (CNN) fusing frequency domain feature matching algorithm (FDFM), called CNN-FDFM, is proposed in this paper. FDFM extracts key frequency features from signals in the frequency domain, which can maintain high accuracy in the case of strong noise and limited samples. CNN automatically extracts features from time-domain signals, and by using dropout to simulate noise input and increasing the size of the first-layer convolutional kernel, the anti-noise ability of the network is improved. Softmax with temperature parameter T and D-S evidence theory are used to fuse the two models. As FDFM and CNN can provide different diagnostic information in frequency domain, and time domain, respectively, the fused model CNN-FDFM achieves higher accuracy under severe noise environment. In the experiment, when a signal-to-noise ratio (SNR) drops to -10 dB, the diagnosis accuracy of CNN-FDFM still reaches 93.33%, higher than CNN’s accuracy of 45.43%. Besides, when SNR is greater than -6 dB, the accuracy of CNN-FDFM is higher than 99%.
Encryption Based Image Watermarking Algorithm in 2DWT-DCT Domains
Authors: Hasan Nayeem , Islam Md Saiful , Chen Wenyu , Kabir Muhammad Ashad , Al-Ahmadi Saad
Published: August 2021

This paper proposes an encryption-based image watermarking scheme using a combination of second-level discrete wavelet transform (2DWT) and discrete cosine transform (DCT) with an auto extraction feature. The 2DWT has been selected based on the analysis of the trade-off between imperceptibility of the watermark and embedding capacity at various levels of decomposition. DCT operation is applied to the selected area to gather the image coefficients into a single vector using a zig-zig operation. We have utilized the same random bit sequence as the watermark and seed for the embedding zone coefficient. The quality of the reconstructed image was measured according to bit correction rate, peak signal-to-noise ratio (PSNR), and similarity index. Experimental results demonstrated that the proposed scheme is highly robust under different types of image-processing attacks. Several image attacks, e.g., JPEG compression, filtering, noise addition, cropping, sharpening, and bit-plane removal, were examined on watermarked images, and the results of our proposed method outstripped existing methods, especially in terms of the bit correction ratio (100%), which is a measure of bit restoration. The results were also highly satisfactory in terms of the quality of the reconstructed image, which demonstrated high imperceptibility in terms of peak signal-to-noise ratio (PSNR ≥ 40 dB) and structural similarity (SSIM ≥ 0.9) under different image attacks.
Mission Unaccomplished: Impediments to Affordable Housing Drive in Addressing Homelessness in Sub-Saharan Africa
Authors: Obioha Emeka Emmanuel
Published: August 2021

Affordable housing is a people-centered strategy in dealing with homelessness. However, the increasing number of people in need of homes in sub-Saharan Africa suggests that this strategy has not afforded homes to the homeless. Theoretically, affordable housing exists to provide cheap and decent homes, but in contrast, these social houses are practically unaffordable, which raises the question of why this is the case. This paper articulates the impediments that account for unrealized affordable social housing in sub-Saharan Africa. It argues that tackling these impediments through the recommended ways will booster realization of this dream. In conclusion, while provision of affordable housing to all who are in need of homes in various countries in sub-Saharan Africa is a desirable goal, all indications point to the reality that this mission is far from an accomplished status.
Strengthening the Collaborative Environment in Port-Hinterland Corridor Management Initiatives: A Value System Approach
Authors: Sdoukopoulos Eleftherios , Boile Maria
Published: August 2021

With port competition now increasingly taking place on the landside, port actors have a genuine interest in enhancing their role and introducing improvements in the hinterland transport and logistics system. Among the different opportunities that are available, less attention has been placed on those that port–hinterland corridor management initiatives have to offer. These will be discussed herein, and a proposal is put forward for strengthening the collaborative environment in those initiatives, further reinforcing existing opportunities or creating new ones. More specifically, a value system approach is outlined and the steps for its development are sketched, putting forward value-oriented perspectives over the current performance-related ones. The proposed approach adds another useful dimension to the business thinking and decision-making of corridor members, enabling them to more holistically understand their respective roles and positioning and, in turn, further enhance collaboration among them, not just for improving performance but also, more importantly, for adding further value to the corridor. In the long term, this can result in greater benefits being realized for the corridor community as a whole.
Wastewater Based Microbial Biorefinery for Bioenergy Production
Authors: Bhatia Shashi Kant
Published: August 2021

A continuous increase in global population is demanding more development and industrialization, which leads to the production of various waste such as municipal wastewater, agricultural waste, industrial waste, medical waste, electronic wastes, etc [...]
Profiling Spanish Prospective Buyers of Electric Vehicles Based on Demographics
Authors: Esteves Jose , Alonso-Martínez Daniel , de Haro Guillermo
Published: August 2021

As traffic congestion and air pollution rise at alarming rates in many cities worldwide, new smart technologies are emerging to meet the urban mobility challenge. In addition, automotive firms have transformed their business models to make them more sustainable and to adjust to demand response. Electric vehicles (EVs) represent a viable option to reduce ecological damage and improve public health. However, in the previous literature, no consensus has been reached on the profile of prospective buyers of EVs. Based on a large-scale sample of Spanish citizens and using cluster analysis, our study provides a better understanding of the demographics of such prospective buyers. We identified four types of EV prospective buyers. Our results show that although men have a strong preference for EVs, low-income older women prove to be the most EV-aware group; their automotive driving experience and concern for sustainability could be among the underlying causes of this particular interest. Another valuable insight is the greater partiality of older people for EVs. These findings have many implications for managers, especially in the automotive industry, policymakers, and sustainability strategists. They show that EV prospective buyers should not be approached as a homogeneous group but as a heterogeneous group with different socio-demographic characteristics that might help decision-makers make better business decisions.
Understanding Public Intentions to Pay for the Conservation of Urban Trees Using the Extended Theory of Planned Behavior
Authors: Chiou Chyi-Rong , Chan Wei-Hsun , Lin Jiunn-Cheng , Wu Meng-Shan
Published: August 2021

Urban trees could provide a variety of ecosystem services. However, they require conservation to sustain a healthy and consistent provision of services. This study applies an extended theory of planned behavior (ETPB) to understand residents’ pay intention for conserving urban trees. In order to explore the impact of the public perception of urban trees, two constructs such as perceived usefulness and perceived tree benefits have been added to the TPB model. This study conducted a questionnaire survey on Taipei city residents and received 364 valid responses. The partial least squares structural equation modeling (PLS-SEM) was used for the analysis of the model. The results show that residents’ perceived usefulness and perceived tree benefits of urban trees have a significantly positive impact on public attitude toward protecting urban trees. Individuals’ intention to pay towards conservation of urban trees is, on the other hand, affected by subjective norm, attitude, perceived behavioral control, and perceived usefulness. Thus, with education and promotion of tree usefulness and benefits of ecosystem services, it is helpful to improve residents’ attitudes regarding the protection of urban trees and increase their intention to pay for urban tree conservation.
How the Extended Theory of Planned Behavior Can Be Applied in the Research of the Influencing Factors of Food Waste in Restaurants: Learning from Serbian Urban Centers
Authors: Blešić Ivana , Petrović Marko D. , Gajić Tamara , Tretiakova Tatiana N. , Syromiatnikova Julia A. , Radovanović Milan , Popov-Raljić Jovanka , Yakovenko Natalia V.
Published: August 2021

This study is based on the general notion that restaurants should find more responsible solutions to dispose of the large amount of food that is not consumed. Moreover, the food wasted has great environmental, social and financial impacts, and yet this issue is still insufficiently presented in contemporary studies on food waste management. This paper applied the extended theory of planned behavior as a theoretical framework to elicit consumers’ behavior concerning food waste. A standard paper and pen survey recorded quantitative data provided by 221 respondents. The findings reported the following: (1) personal attitudes toward food waste positively affect an individual’s intention not to waste food; (2) perceived behavioral control positively affects an individual’s intention not to waste food; (3) the intention not to waste food negatively affects self-reported food waste behavior; (4) negative environmental attitudes negatively affect intention not to waste food; (5) hygiene-based food waste negatively affects perceived behavioral control. This study contributes to understanding consumers’ food waste behavior in restaurants and might have practical implications in the hospitality sector.
Does Capital Account Liberalization Spur Entrepreneurship: The Role of Financial Development
Authors: Jiang Chun , Feng Amei , Xiao Chunhuan
Published: August 2021

Entrepreneurship is regarded as the cornerstone of the sustainable development of a society. In this study, we empirically investigate the possible economic impacts of capital account liberalization on entrepreneurship. Using a panel dataset of 103 countries and regions and the system generalized method of moments (GMM), this paper demonstrates a positive relationship between capital account liberalization and entrepreneurship in developed economies whereas a negative relationship in developing economies. Furthermore, domestic financial development plays an important moderating role in the relationship between capital account openness and entrepreneurship. Specifically, the negative impact of capital account liberalization in developing economies is mitigated by a high degree of domestic credit and equity market development, the continuous deepening of finance and better financial inclusion. Our findings imply that domestic financial development is an essential prerequisite for the opening of a country’s capital account, especially for developing countries.
Nutritional Profile and Potential Health Benefits of Super Foods: A Review
Authors: Jagdale Yash D. , Mahale Saurabh V. , Zohra Beenish , Nayik Gulzar Ahmad , Dar Aamir Hussain , Khan Khalid Ali , Abdi Gholamreza , Karabagias Ioannis K.
Published: August 2021

The advancement within the food and nutrition sector has resulted in the development of a special category of food, particularly referred to as “superfoods”. Superfoods are special kind of foods capable of exhibiting different positive effects involving prevention of different ailments, provide impetus to the immune system, and essential macro- and micro-nutrients in ample quantities. Nowadays, these are gaining considerable attention due to the increased health consciousness of consumers. In contrast to their exceptional health or even medicinal benefits, which are based on their long history of use, the concept of superfoods is still little understood. The category of superfoods mainly comprises different types of fruits, vegetables, grains, etc. This review sheds light on the nutritional composition as well as the possible intervention in the prevention of various chronic ailments of some significant superfoods. This manuscript could help consumers to use superfoods as part of their diet more often and very effectively.
iPVP-MCV: A Multi-Classifier Voting Model for the Accurate Identification of Phage Virion Proteins
Authors: Han Haitao , Zhu Wenhong , Ding Chenchen , Liu Taigang
Published: August 2021

The classic structure of a bacteriophage is commonly characterized by complex symmetry. The head of the structure features icosahedral symmetry, whereas the tail features helical symmetry. The phage virion protein (PVP), a type of bacteriophage structural protein, is an essential material of the infectious viral particles and is responsible for multiple biological functions. Accurate identification of PVPs is of great significance for comprehending the interaction between phages and host bacteria and developing new antimicrobial drugs or antibiotics. However, traditional experimental approaches for identifying PVPs are often time-consuming and laborious. Therefore, the development of computational methods that can efficiently and accurately identify PVPs is desired. In this study, we proposed a multi-classifier voting model called iPVP-MCV to enhance the predictive performance of PVPs based on their amino acid sequences. First, three types of evolutionary features were extracted from the position-specific scoring matrix (PSSM) profiles to represent PVPs and non-PVPs. Then, a set of baseline models were trained based on the support vector machine (SVM) algorithm combined with each type of feature descriptors. Finally, the outputs of these baseline models were integrated to construct the proposed method iPVP-MCV by using the majority voting strategy. Our results demonstrated that the proposed iPVP-MCV model was superior to existing methods when performing the rigorous independent dataset test.
Acyl(imidoyl)ketenes: Reactive Bidentate Oxa/Aza-Dienes for Organic Synthesis
Authors: Lystsova Ekaterina A. , Khramtsova Ekaterina E. , Maslivets Andrey N.
Published: August 2021

Polyfunctional building blocks are essential for the implementation of diversity-oriented synthetic strategies, highly demanded in small molecule libraries’ design for modern drug discovery. Acyl(imidoyl)ketenes are highly reactive organic compounds, bearing both oxa- and aza-diene moieties, conjugated symmetrically to the ketene fragment, enabling synthesis of various skeletally diverse heterocycles on their basis. The highlights of reactions utilizing acyl(imidoyl)ketenes are high yields, short reaction time (about several minutes), high selectivity, atom economy, and simple purification procedures, which benefits the drug discovery. The present review focuses on the approaches to thermal generation of acyl(imidoyl)ketenes, patterns of their immediate transformations via intra- and intermolecular reactions, including the reactions of cyclodimerization, in which either symmetric or dissymmetric heterocycles can be formed. Recent advances in investigations on mechanisms, identifications of intermediates, and chemo- and regioselectivity of reactions with participation of acyl(imidoyl)ketenes are also covered.
Force Analysis of Self-Anchored Suspension Bridges after Cable Clamp Slippage
Authors: Li Hongfeng , Liu Yancheng , Li Chunwei , Hu Hao , Sun Quansheng
Published: August 2021

The slippage of cable clamps during the long-term operation of suspension bridges is a common and detrimental phenomenon. From an experimental point of view, the cable clamp slippage of a suspension bridge was investigated to reveal the effect of this sliding on the force acting on the full bridge. The forces acting on the bridge before and after the slippage were analyzed using a finite element model. The calculation results showed that the cable clamp slippage directly affects the cable forces of the hangers. The hanger cable force decreased by 19.2% when the slippage reached 10.2 cm, while the maximum increase in the cable force of adjacent hangers was 147.7 kN, an increase of 7.25%. The variation of forces in the hanger cable disrupted the force balance of the main girder, thereby producing a torque effect at the corresponding position in the girder, i.e., increased torque. Meanwhile, the slippage affected the axial tension in the main cable and the main girder. The impact of the tower internal force was less than 1%. Hence, the study concluded that the effect of cable clamp slippage is better understood, ensuring the safety of the suspension bridge.
The Cellular Prion Protein Increases the Uptake and Toxicity of TDP-43 Fibrils
Authors: Scialò Carlo , Celauro Luigi , Zattoni Marco , Tran Thanh Hoa , Bistaffa Edoardo , Moda Fabio , Kammerer Robert , Buratti Emanuele , Legname Giuseppe
Published: August 2021

Cytoplasmic aggregation of the primarily nuclear TAR DNA-binding protein 43 (TDP-43) affects neurons in most amyotrophic lateral sclerosis (ALS) and approximately half of frontotemporal lobar degeneration (FTLD) cases. The cellular prion protein, PrPC, has been recognized as a common receptor and downstream effector of circulating neurotoxic species of several proteins involved in neurodegeneration. Here, capitalizing on our recently adapted TDP-43 real time quaking induced reaction, we set reproducible protocols to obtain standardized preparations of recombinant TDP-43 fibrils. We then exploited two different cellular systems (human SH-SY5Y and mouse N2a neuroblastoma cells) engineered to express low or high PrPC levels to investigate the link between PrPC expression on the cell surface and the internalization of TDP-43 fibrils. Fibril uptake was increased in cells overexpressing either human or mouse prion protein. Increased internalization was associated with detrimental consequences in all PrP-overexpressing cell lines but was milder in cells expressing the human form of the prion protein. As described for other amyloids, treatment with TDP-43 fibrils induced a reduction in the accumulation of the misfolded form of PrPC, PrPSc, in cells chronically infected with prions. Our results expand the list of misfolded proteins whose uptake and detrimental effects are mediated by PrPC, which encompass almost all pathological amyloids involved in neurodegeneration.
HTS-Based Diagnostics of Sugarcane Viruses: Seasonal Variation and Its Implications for Accurate Detection
Authors: Malapi-Wight Martha , Adhikari Bishwo , Zhou Jing , Hendrickson Leticia , Maroon-Lango Clarissa J. , McFarland Clint , Foster Joseph A. , Hurtado-Gonzales Oscar P.
Published: August 2021

Rapid global germplasm trade has increased concern about the spread of plant pathogens and pests across borders that could become established, affecting agriculture and environment systems. Viral pathogens are of particular concern due to their difficulty to control once established. A comprehensive diagnostic platform that accurately detects both known and unknown virus species, as well as unreported variants, is playing a pivotal role across plant germplasm quarantine programs. Here we propose the addition of high-throughput sequencing (HTS) from total RNA to the routine quarantine diagnostic workflow of sugarcane viruses. We evaluated the impact of sequencing depth needed for the HTS-based identification of seven regulated sugarcane RNA/DNA viruses across two different growing seasons (spring and fall). Our HTS analysis revealed that viral normalized read counts (RPKM) was up to 23-times higher in spring than in the fall season for six out of the seven viruses. Random read subsampling analyses suggested that the minimum number of reads required for reliable detection of RNA viruses was 0.5 million, with a viral genome coverage of at least 92%. Using an HTS-based total RNA metagenomics approach, we identified all targeted viruses independent of the time of the year, highlighting that higher sequencing depth is needed for the identification of DNA viruses.
Adaptive Immune Response to Vaccinia Virus LIVP Infection of BALB/c Mice and Protection against Lethal Reinfection with Cowpox Virus
Authors: Shchelkunov Sergei N. , Sergeev Alexander A. , Yakubitskiy Stanislav N. , Titova Ksenia A. , Pyankov Stepan A. , Kolosova Irina V. , Starostina Ekaterina V. , Borgoyakova Mariya B. , Zadorozhny Alexey M. , Kisakov Denis N. , Shulgina Irina S. , Karpenko Larisa I.
Published: August 2021

Mass vaccination has played a critical role in the global eradication of smallpox. Various vaccinia virus (VACV) strains, whose origin has not been clearly documented in most cases, have been used as live vaccines in different countries. These VACV strains differed in pathogenicity towards various laboratory animals and in reactogenicity exhibited upon vaccination of humans. In this work, we studied the development of humoral and cellular immune responses in BALB/c mice inoculated intranasally (i.n.) or intradermally (i.d.) with the VACV LIVP strain at a dose of 105 PFU/mouse, which was used in Russia as the first generation smallpox vaccine. Active synthesis of VACV-specific IgM in the mice occurred on day 7 after inoculation, reached a maximum on day 14, and decreased by day 29. Synthesis of virus-specific IgG was detected only from day 14, and the level increased significantly by day 29 after infection of the mice. Immunization (i.n.) resulted in significantly higher production of VACV-specific antibodies compared to that upon i.d. inoculation of LIVP. There were no significant differences in the levels of the T cell response in mice after i.n. or i.d. VACV administration at any time point. The maximum level of VACV-specific T-cells was detected on day 14. By day 29 of the experiment, the level of VACV-specific T-lymphocytes in the spleen of mice significantly decreased for both immunization procedures. On day 30 after immunization with LIVP, mice were infected with the cowpox virus at a dose of 46 LD50. The i.n. immunized mice were resistant to this infection, while 33% of i.d. immunized mice died. Our findings indicate that the level of the humoral immune response to vaccination may play a decisive role in protection of animals from orthopoxvirus reinfection.
Effect of SARS-CoV-2 Mutations on the Efficacy of Antibody Therapy and Response to Vaccines
Authors: Yaqinuddin Ahmed , Shafqat Areez , Kashir Junaid , Alkattan Khaled
Published: August 2021

SARS-CoV-2 causes severe acute respiratory syndrome, which has led to significant morbidity and mortality around the world. Since its emergence, extensive prophylactic and therapeutic countermeasures have been employed to successfully prevent the spread of COVID-19. Extensive work has been undertaken on using monoclonal antibody therapies, mass vaccination programs, and antiviral drugs to prevent and treat COVID-19. However, since antiviral drugs could take years to become widely available, immunotherapy and vaccines currently appear to be the most feasible option. In December 2020, the first vaccine against SARS-CoV-2 was approved by the World Health Organization (WHO) and, subsequently, many other vaccines were approved for use by different international regulators in different countries. Most monoclonal antibodies (mAbs) and vaccines target the SARS-CoV-2 surface spike (S) protein. Recently, mutant (or variant) SARS-CoV-2 strains with increased infectivity and virulence that evade protective host antibodies present either due to infection, antibody therapy, or vaccine administration have emerged. In this manuscript, we discuss the different monoclonal antibody and vaccine therapies available against COVID-19 and how the efficacy of these therapies is affected by the emergence of variants of SARS-CoV-2. We also discuss strategies that might help society cope with variants that could neutralize the effects of immunotherapy and escape the protective immunity conferred by vaccines.
The Promise and Challenges of Cyclic Dinucleotides as Molecular Adjuvants for Vaccine Development
Authors: Yan Hongbin , Chen Wangxue
Published: August 2021

Cyclic dinucleotides (CDNs), originally discovered as bacterial second messengers, play critical roles in bacterial signal transduction, cellular processes, biofilm formation, and virulence. The finding that CDNs can trigger the innate immune response in eukaryotic cells through the stimulator of interferon genes (STING) signalling pathway has prompted the extensive research and development of CDNs as potential immunostimulators and novel molecular adjuvants for induction of systemic and mucosal innate and adaptive immune responses. In this review, we summarize the chemical structure, biosynthesis regulation, and the role of CDNs in enhancing the crosstalk between host innate and adaptive immune responses. We also discuss the strategies to improve the efficient delivery of CDNs and the recent advance and future challenges in the development of CDNs as potential adjuvants in prophylactic vaccines against infectious diseases and in therapeutic vaccines against cancers.
Groundwater Arsenic-Attributable Cardiovascular Disease (CVD) Mortality Risks in India
Authors: Wu Ruohan , Xu Lingqian , Polya David A.
Published: August 2021

Cardiovascular diseases (CVDs) have been recognized as the most serious non-carcinogenic detrimental health outcome arising from chronic exposure to arsenic. Drinking arsenic contaminated groundwaters is a critical and common exposure pathway for arsenic, notably in India and other countries in the circum-Himalayan region. Notwithstanding this, there has hitherto been a dearth of data on the likely impacts of this exposure on CVD in India. In this study, CVD mortality risks arising from drinking groundwater with high arsenic (>10 μg/L) in India and its constituent states, territories, and districts were quantified using the population-attributable fraction (PAF) approach. Using a novel pseudo-contouring approach, we estimate that between 58 and 64 million people are exposed to arsenic exceeding 10 μg/L in groundwater-derived drinking water in India. On an all-India basis, we estimate that 0.3–0.6% of CVD mortality is attributable to exposure to high arsenic groundwaters, corresponding to annual avoidable premature CVD-related deaths attributable to chronic exposure to groundwater arsenic in India of between around 6500 and 13,000. Based on the reported reduction in life of 12 to 28 years per death due to heart disease, we calculate value of statistical life (VSL) based annual costs to India of arsenic-attributable CVD mortality of between USD 750 million and USD 3400 million.
Climate and Land Use Change Effects on Sediment Production in a Dry Tropical Forest Catchment
Authors: García Montoya Juan Pablo , Giraldez Cervera Juan Vicente , Vanwalleghem Tom
Published: August 2021

Understanding the natural and anthropogenic drivers that influence erosion and sediment transport is a key prerequisite for adequate management of river basins, where, especially in tropical catchments, there are few direct measurements or modeling studies. Therefore, this study analyzed the effect of human-induced land-use changes and natural ENSO (El Niño-Southern Oscillation) related changes in rainfall patterns on soil erosion and catchment-scale sediment dynamics with the SEDD (Sediment Delivery Distributed) model. In the 393 km2 Tonusco river basin, representative of tropical, mountainous conditions, daily rainfall data were used to quantify changes in rainfall erosivity and satellite images for the evaluation of cover factor changes between 1977 and 2015. The final model combined soil loss, calculated by RUSLE, with a sediment routing-based delivery ratio, that was calibrated and validated with data from the sediment load recorded at the basin outlet. The results detected a great reduction of the vegetation cover in the catchment during the last decade of from 79.5 to 29.5%, and the influence of important runoff and erosion events linked to La Niña episodes. Soil erosion rates were locally very high, of over 120 Mg ha−1yr−1, and sediment yields were estimated at the range of 6.17–8.23 Mg ha−1yr−1.
Optimal Number of Pressure Sensors for Real-Time Monitoring of Distribution Networks by Using the Hypervolume Indicator
Authors: Ferreira Bruno , Carriço Nelson , Covas Dídia
Published: August 2021

This article proposes a novel methodology to determine the optimal number of pressure sensors for the real-time monitoring of water distribution networks based on a quality hypervolume indicator. The proposed methodology solves the optimization problem for different numbers of pressure sensors, assesses the gain of installing each set of sensors by means of the hypervolume indicator and determines the optimal number of sensors by the variation of the hypervolume indicator. The methodology was applied to a real case study. Several robustness analyses were carried out. The results demonstrate that the methodology is hardly influenced by the method parameters and that a reasonable estimation of the optimal number of sensors can be easily achieved.
Automated Detection of Instability-Inducing Channel Geometry Transitions in Saint-Venant Simulation of Large-Scale River Networks
Authors: Yu Cheng-Wei , Hodges Ben R. , Liu Frank
Published: August 2021

A new sweep-search algorithm (SSA) is developed and tested to identify the channel geometry transitions responsible for numerical convergence failure in a Saint-Venant equation (SVE) simulation of a large-scale open-channel network. Numerical instabilities are known to occur at “sharp” transitions in discrete geometry, but the identification of problem locations has been a matter of modeler’s art and a roadblock to implementing large-scale SVE simulations. The new method implements techniques from graph theory applied to a steady-state 1D shallow-water equation solver to recursively examine the numerical stability of each flowpath through the channel network. The SSA is validated with a short river reach and tested by the simulation of ten complete river systems of the Texas–Gulf Coast region by using the extreme hydrological conditions recorded during hurricane Harvey. The SSA successfully identified the problematic channel sections in all tested river systems. Subsequent modification of the problem sections allowed stable solution by an unsteady SVE numerical solver. The new SSA approach permits automated and consistent identification of problem channel geometry in large open-channel network data sets, which is necessary to effectively apply the fully dynamic Saint-Venant equations to large-scale river networks or for city-wide stormwater networks.