bluuebunny/crossref_metadata_2025 huggingface dataset:
Respiratory and Photosynthetic Responses of Antarctic Vascular Plants Are Differentially Affected by CO2 Enrichment and Nocturnal Warming
Authors: Sanhueza Carolina , Cortes Daniela , Way Danielle A. , Fuentes Francisca , Bascunan-Godoy Luisa , Fernandez Del-Saz Nestor , Sáez Patricia L. , Bravo León A. , Cavieres Lohengrin A.
Published: June 2022

Projected rises in atmospheric CO2 concentration and minimum night-time temperatures may have important effects on plant carbon metabolism altering the carbon balance of the only two vascular plant species in the Antarctic Peninsula. We assessed the effect of nocturnal warming (8/5 °C vs. 8/8 °C day/night) and CO2 concentrations (400 ppm and 750 ppm) on gas exchange, non-structural carbohydrates, two respiratory-related enzymes, and mitochondrial size and number in two species of vascular plants. In Colobanthus quitensis, light-saturated photosynthesis measured at 400 ppm was reduced when plants were grown in the elevated CO2 or in the nocturnal warming treatments. Growth in elevated CO2 reduced stomatal conductance but nocturnal warming did not. The short-term sensitivity of respiration, relative protein abundance, and mitochondrial traits were not responsive to either treatment in this species. Moreover, some acclimation to nocturnal warming at ambient CO2 was observed. Altogether, these responses in C. quitensis led to an increase in the respiration-assimilation ratio in plants grown in elevated CO2. The response of Deschampsia antarctica to the experimental treatments was quite distinct. Photosynthesis was not affected by either treatment; however, respiration acclimated to temperature in the elevated CO2 treatment. The observed short-term changes in thermal sensitivity indicate type I acclimation of respiration. Growth in elevated CO2 and nocturnal warming resulted in a reduction in mitochondrial numbers and an increase in mitochondrial size in D. antarctica. Overall, our results suggest that with climate change D. antarctica could be more successful than C. quitensis, due to its ability to make metabolic adjustments to maintain its carbon balance.
Preconditioning to Water Deficit Helps Aloe vera to Overcome Long-Term Drought during the Driest Season of Atacama Desert
Authors: Delatorre-Castillo José P. , Delatorre-Herrera José , Lay Kung Sang , Arenas-Charlín Jorge , Sepúlveda-Soto Isabel , Cardemil Liliana , Ostria-Gallardo Enrique
Published: June 2022

Throughout evolution, plants have developed different strategies of responses and adaptations that allow them to survive in different conditions of abiotic stress. Aloe vera (L.) Burm.f. is a succulent CAM plant that can grow in warm, semi-arid, and arid regions. Here, we tested the effects of preconditioning treatments of water availability (100, 50, and 25% of soil field capacity, FC) on the response of A. vera to prolonged drought growing in the hyper-arid core of the Atacama Desert. We studied leaf biomass, biochemical traits, and photosynthetic traits to assess, at different intervals of time, the effects of the preconditioning treatments on the response of A. vera to seven months of water deprivation. As expected, prolonged drought has deleterious effects on plant growth (a decrease of 55–65% in leaf thickness) and photosynthesis (a decrease of 54–62% in Emax). There were differences in the morphophysiological responses to drought depending on the preconditioning treatment, the 50% FC pretreatment being the threshold to better withstand prolonged drought. A diurnal increase in the concentration of malic acid (20–30 mg mg−1) in the points where the dark respiration increased was observed, from which it can be inferred that A. vera switches its C3-CAM metabolism to a CAM idling mode. Strikingly, all A. vera plants stayed alive after seven months without irrigation. Possible mechanisms under an environmental context are discussed. Overall, because of a combination of morphophysiological traits, A. vera has the remarkable capacity to survive under severe and long-term drought, and further holistic research on this plant may serve to produce biotechnological solutions for crop production under the current scenario of climatic emergency.
Forecasting Oil Production Flowrate Based on an Improved Backpropagation High-Order Neural Network with Empirical Mode Decomposition
Authors: Prasetyo Joko Nugroho , Setiawan Noor Akhmad , Adji Teguh Bharata
Published: June 2022

Developing a forecasting model for oilfield well production plays a significant role in managing mature oilfields as it can help to identify production loss earlier. It is very common that mature fields need more frequent production measurements to detect declining production. This study proposes a machine learning system based on a hybrid empirical mode decomposition backpropagation higher-order neural network (EMD-BP-HONN) for oilfields with less frequent measurement. With the individual well characteristic of stationary and non-stationary data, it creates a unique challenge. By utilizing historical well production measurement as a time series feature and then decomposing it using empirical mode decomposition, it generates a simpler pattern to be learned by the model. In this paper, various algorithms were deployed as a benchmark, and the proposed method was eventually completed to forecast well production. With proper feature engineering, it shows that the proposed method can be a potentially effective method to improve forecasting obtained by the traditional method.
Calculation Model of the Effect of Periodic Change of Normal Force on Sliding Friction Characteristics between the Planes
Authors: Liu Yongwang , Liu Yanan , Guan Zhichuan , Niu Yixiang
Published: June 2022

How to reduce the friction resistance between two planes is a difficult problem that has been studied in the field of tribology. Aiming at this problem, the concept of reducing the friction resistance by exciting the periodic change of normal force between the planes is proposed. A calculation model of the displacement amplitude distribution of the plate is established based on the principle of reciprocity of work, and the influence of the periodic change of normal force on sliding friction between the planes is studied. Additionally, an experimental device for analysis of friction between the planes under the periodic change of normal force is established. The calculation model of the plate’s displacement amplitude distribution considering the change frequency of normal force is verified and modified by experiments. The research results mainly show two aspects. On the one hand, the calculation model of the displacement amplitude distribution of the plate is in good agreement with the experimental results, which can effectively help to study the effect of periodic change of normal force on sliding friction between the planes. On the other hand, the change of amplitude and frequency of the normal force have an influence on the sliding friction between the planes. That is, the latter decreases with the increase of the former. The above conclusions have great reference significance for the study of vibration drag reduction in engineering production.
A Machine Learning Approach for Predicting the Maximum Spreading Factor of Droplets upon Impact on Surfaces with Various Wettabilities
Authors: Tembely Moussa , Vadillo Damien C. , Dolatabadi Ali , Soucemarianadin Arthur
Published: June 2022

Drop impact on a dry substrate is ubiquitous in nature and industrial processes, including aircraft de-icing, ink-jet printing, microfluidics, and additive manufacturing. While the maximum spreading factor is crucial for controlling the efficiency of the majority of these processes, there is currently no comprehensive approach for predicting its value. In contrast to the traditional approach based on scaling laws and/or analytical models, this paper proposes a data-driven approach for estimating the maximum spreading factor using supervised machine learning (ML) algorithms such as linear regression, decision tree, random forest, and gradient boosting. For this purpose, a dataset of hundreds of experimental results from the literature and our own—spanning the last thirty years—is collected and analyzed. The dataset was divided into training and testing sets, each representing 70% and 30% of the input data, respectively. Subsequently, machine learning techniques were applied to relate the maximum spreading factor to relevant features such as flow controlling dimensionless numbers and substrate wettability. In the current study, the gradient boosting regression model, capable of handling structured high-dimensional data, is found to be the best-performing model, with an R2-score of more than 95%. Finally, the ML predictions agree well with the experimental data and are valid across a wide range of impact conditions. This work could pave the way for the development of a universal model for controlling droplet impact, enabling the optimization of a wide variety of industrial applications.
Mystical Theology and Its Relevance for Today’s Theology: Some Historical Observations
Authors: Faesen Rob
Published: June 2022

Although a convergence between theology and mystical literature can be observed in recent years, it is not always very clear what the relationship between the two is. That there has been a gap between the two, for several centuries, is obvious. A passage in Teresa of Avila’s work is a sign of this, as are the difficulties the Jesuit Balthasar Alvarez encountered during his lifetime. However, there are older models—such as those by the twelfth-century Carthusian Guigo—in which there is an organic connection between the two. The cause of the problem may lie in a misunderstanding of the status of both, namely that the rational, investigative activity of theology on the one hand and the receptive surrender to God of mystical contemplation on the other are regarded as mutually exclusive. However, if one assumes, as John of Ruusbroec does, that the contemplative can be situated on the level of being, namely of the direct contact between God as Creator and the human person as creature, and not on the same “level” as the faculty of reason or intellect, then this misunderstanding disappears, and activity (including intellectual activity of theology) and contemplation can go together well. In particular, the model of the personal encounter between God and the human person can be helpful in this regard.
Hidden Person Makes Dialogue Present: The Place of It in the System of Dialogue According to Cohen, Buber and Rosenzweig
Authors: Dvorkin Ilya
Published: June 2022

The philosophy of dialogue is often presented as an attitude towards the world within the framework of the relationship “I and Thou”. Martin Buber represented this approach in his works. Meanwhile, for other philosophers, especially Cohen and Rosenzweig, dialogue is unthinkable outside of a more complete system of person relations, which also includes He, She, They, We. A particularly sharp controversy unfolded between Rosenzweig and Buber around the place of It in the dialogical process. Rosenzweig not only criticized Buber’s belittling of It and ignoring the deep connection of the I–Thou and I–It relations, but also built his own philosophy of the third person, which is an important element of his philosophical system as a whole. In particular, Rosenzweig showed the extraordinary role of the It in the construction of language. Rosenzweig’s concept of It not only challenges Buber’s It, but also echoes Freud’s Id. Rosenzweig’s philosophy can be seen in many respects as an attempt to harmonize the relationship between I and It, i.e., between the selfhood of a separated person and the closeness of the world completed in itself.
Healing by Spiritual Possession in Medieval Japan, with a Translation of the Genja sahō
Authors: Iyanaga Nobumi
Published: June 2022

From the mid-10th century onward, in cases of illness, the Japanese aristocracy relied on new Buddhist healing methods based on spiritual possession techniques. This essay examines the features and procedures according to which monks and mediums operated the healing. This method, of Indian origin, was imported in Japan through Esoteric Buddhism, and was adapted in order to fit healing purposes. The author focuses his analysis on the role played by an invisible “spirit” who acted to catch the ill-causing demon within the patient’s body and expelled this malign entity from it. The article ends with a translation of a unique ritual text entitled Genja sahō 驗者作法, which describes these rituals in detail.
Estimation of Downwelling Surface Longwave Radiation with the Combination of Parameterization and Artificial Neural Network from Remotely Sensed Data for Cloudy Sky Conditions
Authors: Jiang Yun , Tang Bo-Hui , Zhao Yanhong
Published: June 2022

This work proposes a new method for estimating downwelling surface longwave radiation (DSLR) under cloudy-sky conditions based on a parameterization method and a genetic algorithm–artificial neural network (GA-ANN) algorithm. The new method establishes a GA-ANN model based on simulated data, and then combines MODIS satellite data and ERA5 reanalysis data to estimate the DSLR. According to the validation results of the field sites, the bias and RMSE are –9.18 and 34.88 W/m2, respectively. Compared with the existing research, the new method can achieve reasonable accuracy. Parameter analysis using independently simulated data shows that the near-surface air temperature (Ta) and cloud base height (CBH) have an important influence on DSLR estimation under cloudy-sky conditions. With an increase in CBH, DSLR gradually decreases; however, with an increase in Ta, DSLR shows a trend of gradual increase. When estimating DSLR under cloudy-sky conditions, under the influence of clouds, except for cirrus, the change in DSLRs with CBH and Ta is greater than 20 W/m2.
Editorial for the Special Issue: “Human-Environment Interactions Research Using Remote Sensing”
Authors: Lam Nina S.-N. , Cai Heng , Zou Lei
Published: June 2022

In the wake of increasingly frequent extreme weather events and population growth in hazard-prone areas worldwide, human communities are faced with growing threats from natural hazards [...]
A Novel Detection and Multi-Classification Approach for IoT-Malware Using Random Forest Voting of Fine-Tuning Convolutional Neural Networks
Authors: Ben Atitallah Safa , Driss Maha , Almomani Iman
Published: June 2022

The Internet of Things (IoT) is prone to malware assaults due to its simple installation and autonomous operating qualities. IoT devices have become the most tempting targets of malware due to well-known vulnerabilities such as weak, guessable, or hard-coded passwords, a lack of secure update procedures, and unsecured network connections. Traditional static IoT malware detection and analysis methods have been shown to be unsatisfactory solutions to understanding IoT malware behavior for mitigation and prevention. Deep learning models have made huge strides in the realm of cybersecurity in recent years, thanks to their tremendous data mining, learning, and expression capabilities, thus easing the burden on malware analysts. In this context, a novel detection and multi-classification vision-based approach for IoT-malware is proposed. This approach makes use of the benefits of deep transfer learning methodology and incorporates the fine-tuning method and various ensembling strategies to increase detection and classification performance without having to develop the training models from scratch. It adopts the fusion of 3 CNNs, ResNet18, MobileNetV2, and DenseNet161, by using the random forest voting strategy. Experiments are carried out using a publicly available dataset, MaleVis, to assess and validate the suggested approach. MaleVis contains 14,226 RGB converted images representing 25 malware classes and one benign class. The obtained findings show that our suggested approach outperforms the existing state-of-the-art solutions in terms of detection and classification performance; it achieves a precision of 98.74%, recall of 98.67%, a specificity of 98.79%, F1-score of 98.70%, MCC of 98.65%, an accuracy of 98.68%, and an average processing time per malware classification of 672 ms.
A Combined Sensing System for Intrusion Detection Using Anti-Jamming Random Code Signals
Authors: Xu Hang , Li Yingxin , Ma Cheng , Liu Li , Wang Bingjie , Li Jingxia
Published: June 2022

In order to prevent illegal intrusion, theft, and destruction, important places require stable and reliable human intrusion detection technology to maintain security. In this paper, a combined sensing system using anti-jamming random code signals is proposed and demonstrated experimentally to detect the human intruder in the protected area. This sensing system combines the leaky coaxial cable (LCX) sensor and the single-transmitter-double-receivers (STDR) radar sensor. They transmit the orthogonal physical random code signals generated by Boolean chaos as the detection signals. The LCX sensor realizes the early intrusion alarm at the protected area boundary by comparing the correlation traces before and after intrusion. Meanwhile, the STDR radar sensor is used to track the intruder’s moving path inside the protected area by correlation ranging and ellipse positioning, as well as recognizing intruder’s activities by time-frequency analysis, feature extraction, and support vector machine. The experimental results demonstrate that this combined sensing system not only realizes the early alarm and path tracking for the intruder with the 13 cm positioning accuracy, but also recognizes the intruder’s eight activities including squatting, picking up, jumping, waving, walking forward, running forward, walking backward, and running backward with 98.75% average accuracy. Benefiting from the natural randomness and auto-correlation of random code signal, the proposed sensing system is also proved to have a large anti-jamming tolerance of 27.6 dB, which can be used in the complex electromagnetic environment.
Potential of Connected Fully Autonomous Vehicles in Reducing Congestion and Associated Carbon Emissions
Authors: Neufville Roxanne , Abdalla Hassan , Abbas Ali
Published: June 2022

Congestion is an ongoing problem for many urban centres worldwide (such as London), leading to excessive delays, noise and air pollution, frustrated drivers, and high energy consumption. The carbon footprint of conventional transport systems can be high as a result and transport is among the highest contributors of greenhouse gas emissions. Therefore, with the growing interest in developing connected fully autonomous vehicles (ConFAVs), there is a pressing need to consider their effects within the congested urban setting. To address this, the current research study was designed to investigate the potential for ConFAVs in providing a sustainable transport solution. During this research, a simulation model was developed, calibrated, and validated using field data collected from several sites in East London, using the graphical user interface (GUI) simulation software PTV VISSIM to simulate the proposed driving and car following behaviour, which included the platooning of these ConFAVs, to assess how they could improve the level of service of the roads. Using the new model, this research addresses the shortcomings of two other adaptations of the Wiedemann 99 car-following models by changing the ConFAV’s behaviour to be more cautious when travelling behind a human driven vehicle, and less cautious when behind another ConFAV. As little is known about the transitional period from zero autonomy to full autonomy on the already congested road network, due to the fact that these vehicles are typically tested in small numbers (often one at a time in a controlled environment), the present research study introduced ConFAVs to the simulated network gradually and in large numbers at 20% intervals (namely 0% where there are no ConFAVs, 20%, 40%, 60%, 80%, and finally 100% where all vehicles within the network were ConFAVs). The average delays and subsequent level of service for the roads within the networks were then assessed against each ConFAV penetration level. This helped understand how the network’s efficiency changes when the number of ConFAVs increases, and the potential benefits for these self-driving vehicles on congestion and the ensuing greenhouse gas emissions. The model showed that a reduction in delay of up to 100% can be achieved by introducing ConFAVs, which translates to a significant reduction in greenhouse gas emissions. This, coupled with the fact that ConFAVs are predominantly electric, points to a future sustainable road transport system. The primary purpose of this research would be to investigate the potential of ConFAVs in reducing traffic congestion and, as a result, greenhouse gas emissions.
Chemical Recycling of a Textile Blend from Polyester and Viscose, Part II: Mechanism and Reactivity during Alkaline Hydrolysis of Textile Polyester
Authors: Bengtsson Jenny , Peterson Anna , Idström Alexander , de la Motte Hanna , Jedvert Kerstin
Published: June 2022

Chemical recycling of textiles holds the potential to yield materials of equal quality and value as products from virgin feedstock. Selective depolymerization of textile polyester (PET) from regenerated cellulose/PET blends, by means of alkaline hydrolysis, renders the monomers of PET while cellulose remains in fiber form. Here, we present the mechanism and reactivity of textile PET during alkaline hydrolysis. Part I of this article series focuses on the cellulose part and a possible industrialization of such a process. The kinetics and reaction mechanism for alkaline hydrolysis of polyester packaging materials or virgin bulk polyester are well described in the scientific literature; however, information on depolymerization of PET from textiles is sparse. We find that the reaction rate of hydrolysis is not affected by disintegrating the fabric to increase its surface area. We ascribe this to the yarn structure, where texturing and a low density assures a high accessibility even without disintegration. The reaction, similar to bulk polyester, is shown to be surface specific and proceeds via endwise peeling. Finally, we show that the reaction product terephthalic acid is pure and obtained in high yields.
Agricultural Insurance in the DOCG Area of Conegliano—Valdobbiadene: An Assessment of Policy Measures
Authors: De Pin Antonio , Miglietta Pier Paolo , Coluccia Benedetta , Capitanio Fabian
Published: June 2022

Agricultural insurance stands prominant in the protection of crop products. In Italy, the increasing occurrence of extreme weather events has had an important impact on the crop insurance market’s dynamics by lowering insurance companies propensity to take on climate risks. In this context, the main aim of the study is to focus on an economic assessment of the demand for insurance in the Controlled and Guaranteed Designation of Origin (DOCG) area of Conegliano-Valdobbiadene, exploiting the economic effects of public contributions for the three main subjects involved in the market: winegrowers, public stakeholders, and insurance companies. The results showed that the more favorable conditions laid down in the Omnibus Regulation in favor of producers do not appear justified in the area investigated. As regards the goodness of public intervention, the overall positivity of the Indicator Efficiency Subsidies (IES) underlines the relative efficiency of the subsidized contribution. As for the insurance companies, the financial equilibrium appears precarious, closed between falling tariffs and increasing quotas in consideration of the feared climate change.
Effect of Short-Term and UV Irradiation Aging on the Behaviour of SBS-Modified Bitumen
Authors: Celauro Clara , Teresi Rosalia , Dintcheva Nadka Tz.
Published: June 2022

To obtain road bitumen with improved temperature and fatigue resistance, polymers and/or rubbers could be added to it. A particularly suitable polymer for bitumen modification is styrene-butadiene-styrene (SBS) copolymer but limited information is available about the ageing behaviour of modified binders. In this work, two neat bitumens, with different penetration grades, and two SBS-modified bitumens, containing different SBS amounts, were selected, and their short-term and UVB ageing behaviour were investigated considering dynamic shear rheometry and Attenuated Total Reflectance-Fourier Transformation InfraRed spectroscopy (ATR-FTIR). Short-time ageing behaviour was investigated performing the rolling thin film oven test (RTFOT), while artificial UV ageing was examined/investigated using UVB lamps. The structural changes in bitumen were monitored at different UV exposure times. All the results suggest that the bitumen having higher penetration grade is more stable than the one with a lower penetration grade in the RTFOT ageing condition, and SBS addition exerts a beneficial effect on thermal stability during processing. Further, SBS addition also has a beneficial effect on the UV ageing resistance of bitumen, reducing its oxidation tendency.
Social Cost-Benefit Analysis of Bottom-Up Spatial Planning in Shrinking Cities: A Case Study in The Netherlands
Authors: Louali Samira , Ročak Maja , Stoffers Jol
Published: June 2022

In current research, the social return to citizens initiatives is important but often under-evaluated. Within this work, we collected the information that has emerged from measuring the social value of regenerative projects in shrinking cities. We used a case study of the regenerative project Gebrookerbos, a socio-spatial regeneration project in the shrinking city of Heerlen, the Netherlands. To assess the project’s monetary and immaterial aspects, a social cost–benefit analysis (SCBA) was used to understand the complexities of the costs and benefits associated with citizens in regeneration projects in a shrinking area. Drawing from the literature on urban shrinkage, citizen involvement, and social cost–benefit analyses, a theoretical framework was proposed. The case study included primary (i.e., interviews) and secondary (i.e., document analysis) data to identify the social value of the Gebrookerbos project, with results suggesting that the project has been meaningful to diverse stakeholders. Based on experiences with the SCBA of Gebrookerbos, one finding was the complexity of measuring citizens’ initiatives in terms of social return due to their process, organisation, and goals, in combination with the dynamics of shrinking cities. We discuss why research on social return to citizens’ initiatives is important and with this study we draw attention to the tendencies, opportunities, and future potential of citizens’ initiatives, which contribute to vacant open spaces and quality of life in shrinking cities.
Reactive Power Management Based Hybrid GAEO
Authors: Hemeida Mahmoud , Senjyu Tomonobu , Alkhalaf Salem , Fawzy Asmaa , Ahmed Mahrous , Osheba Dina
Published: June 2022

Electrical power networks are expanded regularly to meet growing energy requirements. Reactive power dispatch (RPD) optimization is a powerful tool to enhance a system’s efficiency, reliability, and security. RPD optimization is classified as a non-linear and non-convex problem. In this paper, the RPD optimization problem is solved based on novel hybrid genetic algorithms—equilibrium optimizer (GAEO) optimization algorithms. The control variables are determined in such a way that optimizes RPD and minimizes power losses. The efficiency of the proposed optimization algorithms is compared to other techniques that have been used recently to solve the RPD problem. The proposed algorithm has been tested for optimization RPD for three test systems, IEEE14-bus, IEEE-30bus, and IEEE57-bus. The obtained results show the superiority of GAEO over other techniques for small test systems, IEEE14-bus and IEEE-30bus. GAEO shows good results for large system, IEEE 57-bus.
Nanogenerator-Based Wireless Intelligent Motion Correction System for Storing Mechanical Energy of Human Motion
Authors: Mao Yupeng , Sun Fengxin , Zhu Yongsheng , Jia Changjun , Zhao Tianming , Huang Chaorui , Li Caixia , Ba Ning , Che Tongtong , Chen Song
Published: June 2022

As it is urgently needed to address the energy consumption and health care problems caused by population growth, the field of sustainable energy collection and storage equipment as well as intelligent health care for monitoring human motion behavior has received wide attention and achieved rapid development. However, the portable intelligent systems that integrate them have not been widely discussed. In this work, we propose a design of a nanogenerator-based wireless intelligent motion correction system, combining triboelectric nanogenerator technology with wireless intelligent host computer signal processing and visualization systems. Under the condition of no external power supply, a noninvasive triboelectric nanogenerator (FL-TENG) sensor integrated system stores the mechanical energy due to human movement behavior and drives wireless micro-electronic devices to realize the human–computer interaction application of the intelligent system. In the conducted test, the reported instantaneous output of an ordinary clap action was around 241V. For a variety of physical exercise types being monitored, it can accurately determine human movement behavior and perform error correction and scoring for movement techniques. Additionally, using hydrogel as an electrode improves the service life and stability of the device. Therefore, this flexible and convenient design concept is beneficial to the development and utilization of sustainable energy and sports activities. In addition, it extends the application prospects of FL-TENG in self-powered sensing systems.
On Prešić–Ćirić-Type α-ψ Contractions with an Application
Authors: Sk Faruk , Tom Mohammed Ahmed Osman , Khan Qamrul Haq , Khan Faizan Ahmad
Published: June 2022

In this paper, we extend the idea of α-ψ contraction mapping to the product spaces by introducing Prešić–Ćirić-type α-ψ contractions and utilize them to prove some coincidence and common fixed-point theorems in the context of ordered metric spaces using α-admissibility of the mapping. Our newly established results generalize a number of well-known fixed-point theorems from the literature. Moreover, we give some examples that attest to the credibility of our results. Further, we give an application to the nonlinear integral equations, which can be employed to study the existence and uniqueness of solutions to the integral equations.
A Pareto–Pontryagin Maximum Principle for Optimal Control
Authors: Lovison Alberto , Cardin Franco
Published: June 2022

In this paper, an attempt to unify two important lines of thought in applied optimization is proposed. We wish to integrate the well-known (dynamic) theory of Pontryagin optimal control with the Pareto optimization (of the static type), involving the maximization/minimization of a non-trivial number of functions or functionals, Pontryagin optimal control offers the definitive theoretical device for the dynamic realization of the objectives to be optimized. The Pareto theory is undoubtedly less known in mathematical literature, even if it was studied in topological and variational details (Morse theory) by Stephen Smale. This reunification, obviously partial, presents new conceptual problems; therefore, a basic review is necessary and desirable. After this review, we define and unify the two theories. Finally, we propose a Pontryagin extension of a recent multiobjective optimization application to the evolution of trees and the related anatomy of the xylems. This work is intended as the first contribution to a series to be developed by the authors on this subject.
Patterns Simulations Using Gibbs/MRF Auto-Poisson Models
Authors: Zimeras Stelios
Published: June 2022

Pattern analysis is the process where characteristics of big data can be recognized using specific methods. Recognition of the data, especially images, can be achieved by applying spatial models, explaining the neighborhood structure of the patterns. These models can be introduced by Markov random field (MRF) models where conditional distribution of the pixels may be defined by a specific distribution. Various spatial models could be introduced, explaining the real patterns of the data; one class of these models is based on the Poisson distribution, called auto-Poisson models. The main advantage of these models is the consideration of the local characteristics of the image. Based on the local analysis, various patterns can be introduced and models that better explain the real data can be estimated, using advanced statistical techniques like Monte Carlo Markov Chains methods. These methods are based on simulations where the proposed distribution must converge to the original (final) one. In this work, an analysis of a MRF model under Poisson distribution would be defined and simulations would be illustrated based on Monte Carlo Markov Chains (MCMC) process like Gibbs sampler. Results would be illustrated using simulated and real patterns data.
Exacerbation of Fatality Rates Induced by Poor Air Quality Due to Open-Air Mass Funeral Pyre Cremation during the Second Wave of COVID-19
Authors: Manoj M. G. , Satheesh Kumar M. K. , Valsaraj K. T. , Vijayan Soumya K. , Nishanth T.
Published: June 2022

This study investigates the air pollution-induced mortality rate during the second wave of COVID-19, which claimed several thousand lives in the capital city of India, New Delhi, even during a lockdown period. Delhi is a hotspot of unhealthy air quality. During the second wave of COVID-19 in 2021, surface ozone levels were observed to be higher, which had a direct impact on lung function, thereby making people more susceptible to COVID-19. The correlation coefficient between surface ozone concentration and mortality has been observed to be 0.74 at a 95% confidence level. This work focuses on the plausible impact and feedback of poor air quality induced by the burning of open-air funeral pyres due to the increased COVID-19 mortality rate in New Delhi, estimated by using an epidemiological model (AirQ+) of the World Health Organization. The mortality rate estimated quantitatively with the aid of AirQ+ is 1.27 excess deaths per 100,000 population due to surface ozone from pyre burning. The findings suggest transformational system goals before the resurgence of a subsequent wave.
Pore-Forming Cardiotoxin VVA2 (Volvatoxin A2) Variant I82E/L86K Is an Atypical Duplex-Specific Nuclease
Authors: Lu Jia-Qi , Shou Jia-Wen , Lo Ka-Ching , Tang Yun-Sang , Shi Wei-Wei , Shaw Pang-Chui
Published: June 2022

VVA2 (volvatoxin A chain 2) is a cardiotoxic protein purified from Volvariella volvacea. Its biological activities include hemolysis, writhing reaction, neurotoxicity, and ventricular systolic arresting activity. The cytotoxicity of VVA2 was mainly considered due to its pore-forming activity. Here we report a novel biological activity of its variants VVA2 I82E/K86K as a duplex-specific nuclease. Recombinant VVA2 variant I82E/L86K (Re-VVA2 I82E/L86K), deprived of the oligomerization property, shows increased nuclease activity compared to VVA2. Re-VVA2 I82E/L86K converts supercoiled DNA (Replicative form I, RF I) into nicked form (RF II) and linear form (RF III) in the presence of Mg2+ or Mn2+. Besides plasmid DNA, it also exhibits nuclease activity on E. coli genomic DNA rather than ssDNA or RNA. Re-VVA2 I82E/L86K preferentially cleaves dG-dC-rich dsDNA regions and shows the best performance at pH 6–9 and 55 °C. Our structure–function study has revealed amino acid E111 may take an active part in nuclease activity through interacting with metal ions. Based on the sequences of its cleavage sites, a “double-hit” mechanism was thereby proposed. Given that Re-VVA2 I82E/L86K did not exhibit the conserved nuclease structure and sequence, it is considered an atypical duplex-specific nuclease.
Understanding COVID-19 Vaccines Today: Are T-cells Key Players?
Authors: Shafqat Areez , Arabi Tarek Z. , Sabbah Belal N. , Abdulkader Humzah S. , Shafqat Shameel , Razak Adhil , Kashir Junaid , Alkattan Khaled , Yaqinuddin Ahmed
Published: June 2022

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has heavily mutated since the beginning of the coronavirus-2019 (COVID-19) pandemic. In this regard, the so-called variants of concern (VOCs) feature mutations that confer increased transmissibility and evasion of antibody responses. The VOCs have caused significant spikes in COVID-19 cases, raising significant concerns about whether COVID-19 vaccines will protect against current and future variants. In this context, whereas the protection COVID-19 vaccines offer against the acquisition of infection appears compromised, the protection against severe COVID-19 is maintained. From an immunologic standpoint, this is likely underpinned by the maintenance of T-cell responses against VOCs. Therefore, the role of T-cells is essential to understanding the broader adaptive immune response to COVID-19, which has the potential to shape public policies on vaccine protocols and inform future vaccine design. In this review, we survey the literature on the immunology of T-cell responses upon SARS-CoV-2 vaccination with the current FDA-approved and Emergency Use Authorized COVID-19 vaccines.
COVID-19 Vaccination Strategies and Their Adaptation to the Emergence of SARS-CoV-2 Variants
Authors: Stefanelli Paola , Rezza Giovanni
Published: June 2022

About one year after the identification of the first cases of pneumonia due to a novel coronavirus in Wuhan, several vaccines against SARS-CoV-2/COVID-19 started to be approved for emergency use or authorized for early or limited use. The rapid development of effective vaccines based on different technological platforms represents an unprecedented success for vaccinology, providing a unique opportunity for a successful public health intervention. However, it is widely known that only a limited number of vaccine doses are usually available at the beginning of vaccination campaigns against an emerging virus; in this phase, protecting health care workers and reducing mortality rates is the priority. When a larger number of vaccines become available, the identification of the drivers of virus circulation coupled with the use of transmission blocking vaccines are key to achieve epidemic control through population immunity. However, as we learned during the vaccination campaigns against the pandemic coronavirus, several factors may hamper this process. Thus, flexible plans are required to obtain the best sustainable result with available tools, modulating vaccination strategies in accordance with improved scientific knowledge, and taking into account the duration of protective immune response, virus evolution, and changing epidemic dynamics.
Evaluation of the Potency of the Pertussis Vaccine in Experimental Infection Model with Bordetella pertussis: Study of the Case of the Pertussis Vaccine Used in the Expanded Vaccination Program in Algeria
Authors: Tahar djebbar Khedidja , Allouache Mounia , Kezzal Salim , Benguerguoura Fouzia , TouilBoukoffa Chafia , Zidi Ines , Raache Rachida , Ouzari Hadda-Imene
Published: June 2022

In Algeria, vaccination against pertussis is carried out using the whole-cell pertussis vaccine combined with the diphtheria and tetanus toxoids (DTwp). The quality control of vaccines locally produced or imported is carried out before the batch release. The aim of our work was to evaluate the potency of pertussis vaccines. In the present study, five consecutive trials of potency were conducted on samples of the same batch of (DTwp) using the mouse protection test (MPT) against experimental infection of Bordetella pertussis strain 18323, based on the Kendrick test. The virulence of B. pertussis strain 18–323 was verified by the mortality of mice, with an average LD50 of 338.92, as well as the dose of the lethal test containing a mean number of LD50 of 324.43. The (MPT) test recorded a relative potency of 8.02 IU/human dose, with 95% CL of (3.56–18.05) IU/human dose. The development of the (MPT) at the laboratory of quality control of vaccines and sera at the Pasteur Institute of Algeria was effective in evaluating the potency of whole-cell pertussis vaccines. Interestingly, our study indicates that this potency is necessary for the vaccine quality assurance. Further validation is needed to strengthen the application and routine use of the test.
MADE: A Computational Tool for Predicting Vaccine Effectiveness for the Influenza A(H3N2) Virus Adapted to Embryonated Eggs
Authors: Chen Hui , Wang Junqiu , Liu Yunsong , Ling Ivy Quek Ee , Shih Chih Chuan , Wu Dafei , Fu Zhiyan , Lee Raphael Tze Chuen , Xu Miao , Chow Vincent T. , Maurer-Stroh Sebastian , Zhou Da , Liu Jianjun , Zhai Weiwei
Published: June 2022

Seasonal Influenza H3N2 virus poses a great threat to public health, but its vaccine efficacy remains suboptimal. One critical step in influenza vaccine production is the viral passage in embryonated eggs. Recently, the strength of egg passage adaptation was found to be rapidly increasing with time driven by convergent evolution at a set of functionally important codons in the hemagglutinin (HA1). In this study, we aim to take advantage of the negative correlation between egg passage adaptation and vaccine effectiveness (VE) and develop a computational tool for selecting the best candidate vaccine virus (CVV) for vaccine production. Using a probabilistic approach known as mutational mapping, we characterized the pattern of sequence evolution driven by egg passage adaptation and developed a new metric known as the adaptive distance (AD) which measures the overall strength of egg passage adaptation. We found that AD is negatively correlated with the influenza H3N2 vaccine effectiveness (VE) and ~75% of the variability in VE can be explained by AD. Based on these findings, we developed a computational package that can Measure the Adaptive Distance and predict vaccine Effectiveness (MADE). MADE provides a powerful tool for the community to calibrate the effect of egg passage adaptation and select more reliable strains with minimum egg-passaged changes as the seasonal A/H3N2 influenza vaccine.
Multidetector-Row CT Findings in Dogs with Different Primary Parathyroid Gland Diseases
Authors: Cordella Alessia , Bertaccini Jessica , Rondena Marco , Zoia Andrea , Bertolini Giovanna
Published: June 2022

Primary hyperparathyroidism in dogs is a possibly life-threatening condition, characterized by the excess of parathyroid hormone (PTH) secretion, which leads to an increase in serum ionized calcium level. The utility of computed tomography (CT) in the detection and characterization of parathyroid diseases in dogs has not been assessed to date. Therefore, the aim of this study was to describe the use of multidetector-row CT (MDCT) for the diagnosis of parathyroid disease in dogs. For this descriptive, single-center study, the database of the San Marco Veterinary Clinic was searched for dogs having a suspicion of parathyroid disease who underwent contrast-enhanced MDCT in the period from 2005 to 2021. Dogs with histopathology of the affected parathyroid gland were subsequently considered for inclusion. A total of 22 parathyroid glands were included: 12 adenomas, 8 adenocarcinomas, and two glands with hyperplasia. Several CT features were evaluated, including parathyroid gland affected, lateralization, shape, size, attenuation, and contrast-enhancement. Although the overlap between the appearance of different diseases exists, contrast-enhanced CT was a useful method for the diagnosis of parathyroid disease in dogs.
Single-Nucleotide Polymorphism on Spermatogenesis Associated 16 Gene-Coding Region Affecting Bovine Leukemia Virus Proviral Load
Authors: Mekata Hirohisa , Yamamoto Mari
Published: June 2022

Bovine leukemia virus (BLV) is an etiological agent of malignant lymphoma in cattle and is endemic in many cattle-breeding countries. Thus, the development of cattle genetically resistant to BLV is desirable. The purpose of this study was to identify novel single-nucleotide polymorphisms (SNPs) related to resistance to BLV. A total of 146 DNA samples from cattle with high BLV proviral loads (PVLs) and 142 samples from cattle with low PVLs were used for a genome-wide association study (GWAS). For the verification of the GWAS results, an additional 1342 and 456 DNA samples from BLV-infected Japanese Black and Holstein cattle, respectively, were used for an SNP genotyping PCR to compare the genotypes for the identified SNPs and PVLs. An SNP located on the spermatogenesis associated 16 (SPATA16)-coding region on bovine chromosome 1 was found to exceed the moderate threshold (p < 1.0 × 10−5) in the Additive and Dominant models of the GWAS. The SNP genotyping PCR revealed that the median values of the PVL were 1278 copies/50 ng of genomic DNA for the major homozygous, 843 for the heterozygous, and 621 for the minor homozygous genotypes in the Japanese Black cattle (p < 0.0001). A similar tendency was also observed in the Holstein cattle. We found that cattle with the minor allele for this SNP showed 20–25% lower PVLs. Although the mechanisms through which this SNP impacts the PVL remain unknown, we found a novel SNP related to BLV resistance located on the SPATA16 gene-coding region on bovine chromosome 1.
Determination of Glufosinate-P-Ammonium in Soil Using Precolumn Derivation and Reversed-Phase High-Performance Liquid Chromatography
Authors: Chen Lin , Kong Shun , Wang Guodong , Yan Xiaoju , Zhang Xuemei , Kong Xiangji , Bu Yuanqing
Published: June 2022

This study developed an analytical method to quantify glufosinate-P-ammonium (GLUF-P) in farmland soil using a reversed-phase high-performance liquid chromatography (HPLC) system with a fluorescence detector after derivatization. GLUF-P in farmland soil was extracted with a mixed alkaline solution and was further derivatized with 9-fluorenyl methyl chloroformate (FMOC) at 25 °C for 1 h. The derivatives were separated with an ACE-C18 column, gradient eluted with a mobile phase A of acetonitrile and a mobile phase B of 0.2% phosphoric acid solution, and finally determined by high-performance liquid chromatography (HPLC) with fluorescence detection at an excitation wavelength of 254 nm and an emission wavelength of 279.8 nm. The limits of detection (LODs) in the four types of soil ranged from 0.004 to 0.015 mg/kg, and the limits of quantification (LOQs) ranged from 0.0125 to 0.05 mg/kg. The mean recoveries of GLUF-P ranged from 94% to 119.8%, and the relative standard deviations (RSDs) varied between 2.8% and 9.0% when the spiked concentrations of GLUF-P were 0.1 mg/kg and 1.0 mg/kg, respectively. The coefficients of regression for the linearity equation were more than 0.99. The proposed method had high sensitivity and could be used for the determination of GLUF-P residues in farmland soil.