bluuebunny/crossref_metadata_2025 huggingface dataset:
Overview of Helicobacter pylori Infection: Clinical Features, Treatment, and Nutritional Aspects
Authors: Öztekin Merve , Yılmaz Birsen , Ağagündüz Duygu , Capasso Raffaele
Published: September 2021

Helicobacter pylori (H. pylori) is a 0.5–1 µm wide, 2–4 µm long, short helical, S-shaped Gram-negative microorganism. It is mostly found in the pyloric region of the stomach and causes chronic gastric infection. It is estimated that these bacteria infect more than half of the world’s population. The mode of transmission and infection of H. pylori is still not known exactly, but the faecal–oral and oral–oral routes via water or food consumption are thought to be a very common cause. In the last three decades, research interest has increased regarding the pathogenicity, microbial activity, genetic predisposition, and clinical treatments to understand the severity of gastric atrophy and gastric cancer caused by H. pylori. Studies have suggested a relationship between H. pylori infection and malabsorption of essential micronutrients, and noted that H. pylori infection may affect the prevalence of malnutrition in some risk groups. On the other hand, dietary factors may play a considerably important role in H. pylori infection, and it has been reported that an adequate and balanced diet, especially high fruit and vegetable consumption and low processed salty food consumption, has a protective effect against the outcomes of H. pylori infection. The present review provides an overview of all aspects of H. pylori infection, such as clinical features, treatment, and nutrition.
Classification of Photogrammetric and Airborne LiDAR Point Clouds Using Machine Learning Algorithms
Authors: Duran Zaide , Ozcan Kubra , Atik Muhammed Enes
Published: September 2021

With the development of photogrammetry technologies, point clouds have found a wide range of use in academic and commercial areas. This situation has made it essential to extract information from point clouds. In particular, artificial intelligence applications have been used to extract information from point clouds to complex structures. Point cloud classification is also one of the leading areas where these applications are used. In this study, the classification of point clouds obtained by aerial photogrammetry and Light Detection and Ranging (LiDAR) technology belonging to the same region is performed by using machine learning. For this purpose, nine popular machine learning methods have been used. Geometric features obtained from point clouds were used for the feature spaces created for classification. Color information is also added to these in the photogrammetric point cloud. According to the LiDAR point cloud results, the highest overall accuracies were obtained as 0.96 with the Multilayer Perceptron (MLP) method. The lowest overall accuracies were obtained as 0.50 with the AdaBoost method. The method with the highest overall accuracy was achieved with the MLP (0.90) method. The lowest overall accuracy method is the GNB method with 0.25 overall accuracy.
Inference on COVID-19 Epidemiological Parameters Using Bayesian Survival Analysis
Authors: Bardelli Chiara
Published: September 2021

The need to provide accurate predictions in the evolution of the COVID-19 epidemic has motivated the development of different epidemiological models. These models require a careful calibration of their parameters to capture the dynamics of the phenomena and the uncertainty in the data. This work analyzes different parameters related to the personal evolution of COVID-19 (i.e., time of recovery, length of stay in hospital and delay in hospitalization). A Bayesian Survival Analysis is performed considering the age factor and period of the epidemic as fixed predictors to understand how these features influence the evolution of the epidemic. These results can be easily included in the epidemiological SIR model to make prediction results more stable.
Predicting the Economic Impact of the COVID-19 Pandemic in the United Kingdom Using Time-Series Mining
Authors: Rakha Ahmed , Hettiarachchi Hansi , Rady Dina , Gaber Mohamed Medhat , Rakha Emad , Abdelsamea Mohammed M.
Published: September 2021

The COVID-19 pandemic has brought economic activity to a near standstill as many countries imposed very strict restrictions on movement to halt the spread of the virus. This study aims at assessing the economic impacts of COVID-19 in the United Kingdom (UK) using artificial intelligence (AI) and data from previous economic crises to predict future economic impacts. The macroeconomic indicators, gross domestic products (GDP) and GDP growth, and data on the performance of three primary industries in the UK (the construction, production and service industries) were analysed using a comparison with the pattern of previous economic crises. In this research, we experimented with the effectiveness of both continuous and categorical time-series forecasting on predicting future values to generate more accurate and useful results in the economic domain. Continuous value predictions indicate that GDP growth in 2021 will remain steady, but at around −8.5% contraction, compared to the baseline figures before the pandemic. Further, the categorical predictions indicate that there will be no quarterly drop in GDP following the first quarter of 2021. This study provided evidence-based data on the economic effects of COVID-19 that can be used to plan necessary recovery procedures and to take appropriate actions to support the economy.
The Designing and Re-Designing of a Blended University Course Based on the Trialogical Learning Approach
Authors: Sansone Nadia , Cesareni Donatella , Bortolotti Ilaria , McLay Katherine Frances
Published: September 2021

To have a positive impact on students’ development of crucial skills, blended university courses need careful planning to fruitfully integrate learning settings as well as methodologies. The authors adopted Design-Based Research to design a blended university course based on the Trialogical Learning Approach, and then to redesign it according to the learning outputs and the overall learner’s experience. The first iteration of the course (a.y. 2015) was followed by an observational study that aimed to identify student perceptions of (1) the impact of the course on the acquisition of the targeted knowledge–work skills and (2) strengths and areas for improvement to be considered when re-designing the subsequent edition. A total of 109 students participated in the two editions of the course under scrutiny in this research. The data corpus included students’ self-report questionnaires investigating the development of specific knowledge–work skills and focus group interviews that explored students’ perceptions. The data showed this blended course had a generally positive impact on students’ perception of acquisition of skills and knowledge, which increased between one edition and the next. This positive impact seemed to correspond with course refinements made by the teacher and with the activities that received greater attention in the second edition of the course.
Regulation of Digital Behavior Models for Knowledge Transfer: Organizational Concerns of Remote Learning
Authors: Pokrovskaia Nadezhda N. , Leontyeva Veronika L. , Ababkova Marianna Yu. , D’Ascenzo Fabrizio
Published: September 2021

Research on behavior regulation was carried out after several months of social isolation, provoked by the pandemic, between the months of February and March 2020. In spring 2020, many higher education institutions began to introduce digital tools of education, remote learning, and distance teaching. The reaction during the first weeks and months was negative, but the experience of this remote regime of work and learning continued into the autumn semester due to COVID-19. This experience included the perceptions of new organizational approaches that were needed to regulate digital behavior as a specific type of strategy and choices made in the virtual space. This need was expressed in an understanding of the improvements to be implemented in the organization of educational processes at traditional institutions to efficiently apply the remote learning regime. Between December 2020 and March 2021, six focus groups were conducted to investigate if the regulation of behavior for remote work and learning (work for university administrative staff and academic teachers; studying for students) differed, with informal interviews also conducted to check the validity of the opinions formulated. The hypotheses of the lack of responsibility, and of iterative accomplishment of shorter and simpler tasks, were supported with the data obtained. The hypothesis on an imbalanced vision of mutual interests, and of the assessments of gains and costs of the remote activity, was confirmed. The hypothesis of the externalization of motivation was neither confirmed nor rejected, contradictory opinions were obtained, and, thus, further quantitative study is required. The conclusions based on the obtained results included support for improving the regulation mechanisms required to organize knowledge transfer when digital tools are applied at traditional educational institutions. To enhance the remote regime of learning, redesign and reorganization is necessary when considering the assistance needed by teachers and learners. Specific organizational efforts need to be implemented to restructure the teaching to shorter sequences, to stimulate the creativity of both teachers and learners (due to the readiness to experiment and the lack of critics, and constant access to online bases), and to identify the borders of the “sandbox” to clearly define and articulate the common rules of behavior.
Describing I2V Communication in Scenarios for Simulation-Based Safety Assessment of Truck Platooning
Authors: Sluis Jacco van de , Op den Camp Olaf , Broos Jeroen , Yalcinkaya Ihsan , de Gelder Erwin
Published: September 2021

V2X communication plays an important role in the transition towards connected, cooperative, automated driving. Wireless communication enables instant information exchange between vehicles (V2V) to support, e.g., platooning, and between the infrastructure and vehicles (I2V) to inform vehicles on, e.g., the local speed limit information or the approach of an accident location. In the Horizon 2020 HEADSTART project, we have shown how to test V2V communication in a scenario-based safety assessment framework. Safety assessment aims to determine the impact on safety in the case of potentially critical scenarios, e.g., due to, or in parallel to deterioration of communication. In this study, we extend this methodology with the incorporation of I2V communication. The developed method allows us to treat V2V and I2V communication independently. We demonstrate the method in the use case of an Intelligent Speed Adaptation I2V-functionality for platooning trucks. The practical implementation of test descriptions that consider the potential deterioration of communication signals in the standardized OpenSCENARIO format is shown. The study illustrates how tests are performed in a hardware-in-the-loop setup specifically developed for testing platooning functions. The availability of a test method that is capable of dealing with V2X communication is an important step towards the implementation of type approval methods for Cooperative, Connected and Automated Mobility (CCAM) systems.
Control of a Variable-Impedance Fault Current Limiter to Assist Low-Voltage Ride-Through of Doubly Fed Induction Generators
Authors: Huang Jiejie , Sang Shun , Zhang Lei , Xue Xiaocen , Sun Tingting
Published: September 2021

A fault current limiter (FCL) may be applied to assist the low-voltage ride-through (LVRT) of a doubly fed induction generator (DFIG). FCLs with fixed impedance, lack the flexibility to adjust their impedance to adapt to different LVRT scenarios. The direct switch-in and -out of the fixed-impedance FCL yields transient electromagnetic oscillations in the DFIG, which need to be addressed. In this paper, a variable-impedance FCL is implemented at the stator side of the DFIG to assist its LVRT, and a novel methodology is proposed to control the impedance of the FCL, with which the stator current oscillation is effectively constrained and the smooth switch-out of the FCL is realized to avoid continued active power consumption of the FCL and to restore the DFIG to its pre-fault working condition. Analysis of the LVRT transient is carried out, which lays the foundation for the control methodology to determine the impedance of the FCL based on calculation of the optimization goal. The feasibility and effectiveness of the control to the variable-impedance FCL are verified by the numerical analysis results, which compare the LVRT simulation results with the application of the fixed-impedance and the variable-impedance FCLs.
A Survey on Layer-Wise Security Attacks in IoT: Attacks, Countermeasures, and Open-Issues
Authors: Sharma Gaurav , Vidalis Stilianos , Anand Niharika , Menon Catherine , Kumar Somesh
Published: September 2021

Security is a mandatory issue in any network, where sensitive data are transferred safely in the required direction. Wireless sensor networks (WSNs) are the networks formed in hostile areas for different applications. Whatever the application, the WSNs must gather a large amount of sensitive data and send them to an authorized body, generally a sink. WSN has integrated with Internet-of-Things (IoT) via internet access in sensor nodes along with internet-connected devices. The data gathered with IoT are enormous, which are eventually collected by WSN over the Internet. Due to several resource constraints, it is challenging to design a secure sensor network, and for a secure IoT it is essential to have a secure WSN. Most of the traditional security techniques do not work well for WSN. The merger of IoT and WSN has opened new challenges in designing a secure network. In this paper, we have discussed the challenges of creating a secure WSN. This research reviews the layer-wise security protocols for WSN and IoT in the literature. There are several issues and challenges for a secure WSN and IoT, which we have addressed in this research. This research pinpoints the new research opportunities in the security issues of both WSN and IoT. This survey climaxes in abstruse psychoanalysis of the network layer attacks. Finally, various attacks on the network using Cooja, a simulator of ContikiOS, are simulated.
Homogenization Method to Calculate the Stiffness Matrix of Laminated Composites
Authors: Kaddaha Mohamad Abbas , Younes Rafic , Lafon Pascal
Published: September 2021

New analytical models have been developed for predicting equivalent Young’s and shear moduli of laminate composites. Sets of procedures and calculations are presented in order to obtain equivalent properties in all levels, lamina and laminate. An ultimate path to predict the mechanical properties of laminated composites on the perspective of the material, orientation, and thickness has been developed. By calculating the mechanical properties using Chamis model then an Objectif function with five norms, these norms allow the mechanical properties to be examined and the ultimate answer to be predicted. Another model discusses an alternative concept of equivalent lamina elements (ELEs) by first using Chamis model for hybrid composites. Next, the ELEs are laminated in the direction and integrated into the compliance matrix for each ply. In addition, four new Generalization models for equivalence in thickness and in angle are presented in this paper. The analytical results are validated against other developed models in published articles as well as experimental results. Numerical case studies were conducted to assess the precision of results from the suggested models. The results demonstrated the capability and efficiency of the presented models for predicting the mechanical properties of multi-layer/multi-material laminate composites under different orientation conditions.
Dothistroma septosporum Not Detected in Pinus sylvestris Seed Trees from Investigated Stands in Southern Poland
Authors: Wartalska Pola , Oszako Tomasz , Bakier Sławomir , Belbahri Lassaâd , Malewski Tadeusz , Hsiang Tom , Popowska-Nowak Elżbieta , Nowakowska Justyna
Published: September 2021

In recent years, the decline of pine stands in Europe, including Poland, has been caused by the emerging needle pathogen Dothistroma septosporum. Although this fungus appears to preferentially infect Pinus pini, P. pinaster or P. radiata in Southern Europe, it has been reported in stands of P. nigra, P. mugo and P. sylvestris from Southern Poland. Our preliminary tests of symptomatic needles of diseased pines, including black pine (P. nigra), showed the presence of both D. septosporum and D. pini—the latter as the first report in Poland. No other endophytic pathogen, i.e., Lecanosticta acicola or Cenangium ferruginosum, were found. More extensive molecular surveying based on β-tub2 amplification of DNA in needle samples from 72 seed trees of P. sylvestris in nine different Forest Districts of Southern Poland did not find the presence of D. septosporum. Our study revealed that the seed trees from which we collected propagation material were free from the pathogen, and its endophytic behavior was not confirmed in our testing. Consequently, these investigated trees of P. sylvestris should be suitable for seed collection and propagation, following the requirements of “good” phytosanitary quality as “pathogen-free” pine seeds used for reforestation.
The Impact of Heterogeneous Management Interests in Reducing Social Losses from Wildfire Externalities
Authors: Al Abri Ibtisam , Grogan Kelly
Published: September 2021

The United States has experienced an even longer and more intense wildfire season than normal in recent years, largely resulting from drought conditions and a buildup of flammable vegetation. The derived stochastic dynamic model in this study was utilized to evaluate the interaction of wildfire risk mitigation policies for two adjacent landowners under various scenarios of forest benefits while accounting for full awareness of fire externalities. This study also evaluated the effectiveness of cost-share programs and fuel stock regulation and investigated under which scenarios of forest management interests the implementation of these policies encourages risk mitigation behaviors and yields larger reductions in social costs. The findings revealed that social costs significantly reduced after the implementation of cost-share programs and fuel stock regulation. Market-oriented adjacent landowners were more responsive to policy instruments compared to other types of neighboring landowners, and their responsiveness was greater for fuel stock regulation policies than for cost-share programs. Policymakers may introduce extra financial incentives or more rigorous fuel stock regulations to induce nonmarket-oriented landowners to undertake increased fuel management activities.
Multi-Objective Sustainability Optimization of Biomass Residues to Ethanol via Gasification and Syngas Fermentation: Trade-Offs between Profitability, Energy Efficiency, and Carbon Emissions
Authors: de Medeiros Elisa M. , Noorman Henk , Maciel Filho Rubens , Posada John A.
Published: September 2021

This work presents a strategy for optimizing the production process of ethanol via integrated gasification and syngas fermentation, a conversion platform of growing interest for its contribution to carbon recycling. The objective functions (minimum ethanol selling price (MESP), energy efficiency, and carbon footprint) were evaluated for the combinations of different input variables in models of biomass gasification, energy production from syngas, fermentation, and ethanol distillation, and a multi-objective genetic algorithm was employed for the optimization of the integrated process. Two types of waste feedstocks were considered, wood residues and sugarcane bagasse, with the former leading to lower MESP and a carbon footprint of 0.93 USD/L and 3 g CO2eq/MJ compared to 1.00 USD/L and 10 g CO2eq/MJ for sugarcane bagasse. The energy efficiency was found to be 32% in both cases. An uncertainty analysis was conducted to determine critical decision variables, which were found to be the gasification zone temperature, the split fraction of the unreformed syngas sent to the combustion chamber, the dilution rate, and the gas residence time in the bioreactor. Apart from the abovementioned objectives, other aspects such as water footprint, ethanol yield, and energy self-sufficiency were also discussed.
Recovering Apple Agro-Industrial Waste for Bioethanol and Vinasse Joint Production: Screening the Potential of Chile
Authors: Hernández Diógenes , Rebolledo-Leiva Ricardo , Fernández-Puratich Harald , Quinteros-Lama Héctor , Cataldo Fernando , Muñoz Edmundo , Tenreiro Claudio
Published: September 2021

Bioethanol production has increased in demand as a replacement for conventional fuels. This work studies the use of apple pomace, which corresponds to 45% (w/w) of dehydrated apple production, as a reliable and inexpensive source for bioethanol production. Additionally, the vinasse obtained from the process as a byproduct is analyzed. Apple pomace has important properties for energy purposes, with high soluble sugar (6%–8%), organic compounds and low protein content. The carbohydrates were consumed in 99.3% in 144 h at a temperature of 30 °C and in a yeast Saccharomyces cerevisiae (YSC) concentration of 0.10 g/L. The bioethanol purity produced, 99.5% (v/v), was quantified by gas chromatography and calorific value (23.21 MJ/kg). This high purity, which fulfills the EN 15376, ASTM D 4806 Standard, allows its use as a fuel and oil additive. Moreover, it can be stated that vinasse obtained from alcohol distillation is a compound that has physicochemical values like other vinasses. Finally, Chile, as the most important exporting country of dehydrated apples in the world, has great potential to take advantage of the use of this raw material for bioethanol and vinasse production.
Linear Stability of a Steady Convective Flow between Permeable Cylinders
Authors: Zigunovs Maksims , Kolyshkin Andrei , Iltins Ilmars
Published: September 2021

Linear stability analysis of a steady convective flow in a tall vertical annulus caused by nonlinear heat sources is conducted in the paper. Heat sources are generated as a result of a chemical reaction. The effect of radial cross-flow through permeable porous walls of the annulus is analyzed. The problem is relevant to biomass thermal conversion. The base flow solution is obtained by solving nonlinear boundary value problem. Linear stability analysis is performed, using collocation method. The calculations show that radial inward or outward flow has a stabilizing effect on the flow, while the increase in the Frank–Kamenetskii parameter (proportional to the intensity of the chemical reaction) destabilizes the flow. The increase in the Reynolds number based on the radial velocity leads to the appearance of the second minimum on the marginal stability curves. The rate of increase in the critical Grashof number with respect to the Reynolds number is different for inward and outward radial flows.
A Statistical Approach to Describe the Ripening Evolution of Sangiovese Grapes Coming from Different Chianti Classico Sub-Areas
Authors: Bianchi Alessandro , Taglieri Isabella , Rimbotti Antinori Verdiana , Palla Fabrizio , Macaluso Monica , Ferroni Giuseppe , Sanmartin Chiara , Venturi Francesca , Zinnai Angela
Published: September 2021

In Italy, Chianti Classico identifies a territory located in the heart of Tuscany that was once known as Chianti. From the pedological point of view, the entire DOCG (Denomination of controlled and guaranteed origin) has some common features but also shows many specific features related to certain small areas that give rise to the presence of many “terroirs”. Due to the intertwining created by the alternation of valleys and hills and the different characteristics of the territory, factors such as altitude and exposure play a very important role in the vegetative and productive expression of grapes. Some production areas were identified within the appellation where it is argued that the terroir and the grapes are quite distinct from those of other surrounding areas, albeit within the Chianti Classico appellation. On the basis of this information and considering that no data are available in the literature, the present study proposed an innovative multidisciplinary approach (analytical and statistical) that was capable of carrying out an objective evaluation of the various sub-areas investigated, using Sangiovese grapes as the variety in question. This research took into account the climatic results and the different pedological characteristics, evaluating the evolutionary phenomena that were linked to the ripening of the grapes in each phase of its formation.
Kinetics of Colour Development during Frying of Potato Pre-Treated with Pulsed Electric Fields and Blanching: Effect of Cultivar
Authors: Abduh Setya Budi Muhammad , Leong Sze Ying , Zhao Chun , Baldwin Samantha , Burritt David J. , Agyei Dominic , Oey Indrawati
Published: September 2021

The current research aimed to investigate the effect of pulsed electric fields (1 kV/cm; 50 and 150 kJ/kg) followed by blanching (3 min., 100 °C) on the colour development of potato slices during frying on a kinetic basis. Four potato cultivars ‘Crop77’, ‘Moonlight’, ‘Nadine’, and ‘Russet Burbank’ with different content of glucose and amino acids were used. Lightness (L* values from colorimeter measurement) was used as a parameter to assess the colour development during frying. The implementation of PEF and blanching as sequential pre-treatment prior to frying for all potato cultivars was found effective in improving their lightness in the fried products. PEF pre-treatment did not change the kinetics of L* reduction during frying (between 150 and 190 °C) which followed first-order reaction kinetics. The estimated reaction rate constant (k) and activation energy (Ea based on Arrhenius equation) for non-PEF and PEF-treated samples were cultivar dependent. The estimated Ea values during the frying of PEF-treated ‘Russet Burbank’ and ‘Crop77’ were significantly (p < 0.05) lower (up to 30%) than their non-PEF counterparts, indicating that the change in k value of L* became less temperature dependence during frying. This kinetic study is valuable to aid the optimisation of frying condition in deep-fried potato industries when PEF technology is implemented.
Battery Sizing for Different Loads and RES Production Scenarios through Unsupervised Clustering Methods
Authors: Nespoli Alfredo , Matteri Andrea , Pretto Silvia , De Ciechi Luca , Ogliari Emanuele
Published: September 2021

The increasing penetration of Renewable Energy Sources (RESs) in the energy mix is determining an energy scenario characterized by decentralized power production. Between RESs power generation technologies, solar PhotoVoltaic (PV) systems constitute a very promising option, but their production is not programmable due to the intermittent nature of solar energy. The coupling between a PV facility and a Battery Energy Storage System (BESS) allows to achieve a greater flexibility in power generation. However, the design phase of a PV+BESS hybrid plant is challenging due to the large number of possible configurations. The present paper proposes a preliminary procedure aimed at predicting a family of batteries which is suitable to be coupled with a given PV plant configuration. The proposed procedure is applied to new hypothetical plants built to fulfill the energy requirements of a commercial and an industrial load. The energy produced by the PV system is estimated on the basis of a performance analysis carried out on similar real plants. The battery operations are established through two decision-tree-like structures regulating charge and discharge respectively. Finally, an unsupervised clustering is applied to all the possible PV+BESS configurations in order to identify the family of feasible solutions.
Solvability Issues of a Pseudo-Parabolic Fractional Order Equation with a Nonlinear Boundary Condition
Authors: Aitzhanov Serik E. , Berdyshev Abdumauvlen S. , Bekenayeva Kymbat S.
Published: September 2021

This paper is devoted to the fundamental problem of investigating the solvability of initial-boundary value problems for a quasi-linear pseudo-parabolic equation of fractional order with a sufficiently smooth boundary. The difference between the studied problems is that the boundary conditions are set in the form of a nonlinear boundary condition with a fractional differentiation operator. The main result of this work is establishing the local or global solvability of stated problems, depending on the parameters of the equation. The Galerkin method is used to prove the existence of a quasi-linear pseudo-parabolic equation’s weak solution in a bounded domain. Using Sobolev embedding theorems, a priori estimates of the solution are obtained. A priori estimates and the Rellich–Kondrashov theorem are used to prove the existence of the desired solutions to the considered boundary value problems. The uniqueness of the weak generalized solutions of the initial boundary value problems is proved on the basis of the obtained a priori estimates and the application of the generalized Gronwall lemma. The need to consider and study such initial boundary value problems for a quasi-linear pseudo-parabolic equation follows from practical requirements, such as solving fractional differential equations that simulate physical processes that occur during the study of liquid filtration processes, etc.
The Systematic Risk at the Crisis—A Multifractal Non-Uniform Wavelet Systematic Risk Estimation
Authors: Sarraj Mounir , Ben Mabrouk Anouar
Published: September 2021

In the last decade, many factors, such as socio-political and econo-environmental ones, have led to a perturbation in the timeline of the worldwide development, and especially in countries and regions having political changes. This led us to introduce a new idea of risk estimation taking into account the non-uniform changes in markets by introducing a non-uniform wavelet analysis. We aim to explain the econo-political situation of Arab spring countries and the effect of the revolutions on the market beta. The main novelty is first the construction of a dynamic backward-forward model for missing data, and next the application of random non-uniform wavelets. The proposed procedure will be acted empirically on a sample corresponding to TUNINDEX stock as a representative index of the Tunisian market actively traded over the period from 14 January 2016 to 13 January 2021. The chosen 5-year period is important as it constitutes the first five years after the revolution and depends strongly on the socio-econo-political stability in the revolutionary countries. The results showed the efficiency of non-uniform wavelets in explaining the dynamics of the market well. They therefore may be good tools to explore important phenomena in the market such as the non-stationary aspect of financial series, non-constancy, and time-varying parameters. These facts in turn will have positive implications for investors as well as politicians in front of the evolution of the market. Besides, recommendations to extend the present method for other types of wavelets and markets will be of interest.
Certain Coefficient Estimate Problems for Three-Leaf-Type Starlike Functions
Authors: Shi Lei , Khan Muhammad Ghaffar , Ahmad Bakhtiar , Mashwani Wali Khan , Agarwal Praveen , Momani Shaher
Published: September 2021

In our present investigation, some coefficient functionals for a subclass relating to starlike functions connected with three-leaf mappings were considered. Sharp coefficient estimates for the first four initial coefficients of the functions of this class are addressed. Furthermore, we obtain the Fekete–Szegö inequality, sharp upper bounds for second and third Hankel determinants, bounds for logarithmic coefficients, and third-order Hankel determinants for two-fold and three-fold symmetric functions.
Demand Response Optimal Dispatch and Control of TCL and PEV Agents with Renewable Energies
Authors: Hu Jianqiang , Cao Jinde
Published: September 2021

Demand response (DR) flexible loads can provide fast regulation and ancillary services as reserve capacity in power systems. This paper proposes a demand response optimization dispatch control strategy for flexible thermostatically controlled loads (TCLs) and plug-in electric vehicles (PEVs) with stochastic renewable power injection. Firstly, a chance constraint look-ahead programming model is proposed to maximize the social welfare of both units and load agents, through which the optimal power scheduling for TCL/PEV agents can be obtained. Secondly, two demand response control algorithms for TCLs and PEVs are proposed, respectively, based on the aggregate control models of the load agents. The TCLs are controlled by its temperature setpoints and PEVs are controlled by its charging power such that the DR control objective can be fulfilled. It has been shown that the proposed dispatch and control strategy can coordinate the flexible load agents and the renewable power injection. Finally, the simulation results on a modified IEEE 39 bus system demonstrate the effectiveness of the proposed demand response strategy.
Experimental Studies on Wood Pellets Combustion in a Fixed Bed Combustor Using Taguchi Method
Authors: Castro Carlos , Fraga Lelis , Ferreira Eduardo , Martins Jorge , Ribeiro Pedro , Teixeira José C.
Published: September 2021

The combustion of wood pellets in a fixed bed combustor of a 20 kW capacity domestic pellet boiler was tested according to several factors including Power, Excess Air (EA), Primary/Secondary air Split Ratio (SR) and Grate Area (GA). The Taguchi method was applied to program the experimental design. Several parameters were measured, including gas emissions (CO), fuel bed temperature (measured at 4 different heights), and efficiency. The experimental results show that the lower CO emission and the higher efficiency were obtained at medium thermal loads and the highest temperature on the fuel bed was obtained at about ¼ of its height (15 mm). The results obtained from the analysis of variance (ANOVA) show that the SR and the Power are the most important factors contributing to the CO reduction and also increase the fuel bed temperature.
The Space-Based Car-Following Model: Development and Application for Managed Motorway System Safety Evaluation
Authors: Bevrani Kaveh , Chung Edward , Teo Pauline
Published: September 2021

Traffic safety studies need more than what the current micro-simulation models can provide, as they presume that all drivers exhibit safe behaviors. Therefore, existing micro-simulation models are inadequate to evaluate the safety impacts of managed motorway systems such as Variable Speed Limits. All microscopic traffic simulation packages include a core car-following model. This paper highlights the limitations of the existing car-following models to emulate driver behaviour for safety study purposes. It also compares the capabilities of the mainstream car-following models, modelling driver behaviour with precise parameters such as headways and time-to-collisions. The comparison evaluates the robustness of each car-following model for safety metric reproductions. A new car-following model, based on the personal space concept and fish school model is proposed to simulate more accurate traffic metrics. This new model is capable of reflecting changes in the headway distribution after imposing the speed limit from variable speed limit (VSL) systems. This model can also emulate different traffic states and can be easily calibrated. These research findings facilitate assessing and predicting intelligent transportation systems effects on motorways, using microscopic simulation.
Development of a Polysaccharide-Based Hydrogel Drug Delivery System (DDS): An Update
Authors: Pushpamalar Janarthanan , Meganathan Puviarasi , Tan Hui Li , Dahlan Nuraina Anisa , Ooi Li-Ting , Neerooa Bibi Noorheen Haleema Mooneerah , Essa Raahilah Zahir , Shameli Kamyar , Teow Sin-Yeang
Published: September 2021

Delivering a drug to the target site with minimal-to-no off-target cytotoxicity is the major determinant for the success of disease therapy. While the therapeutic efficacy and cytotoxicity of the drug play the main roles, the use of a suitable drug delivery system (DDS) is important to protect the drug along the administration route and release it at the desired target site. Polysaccharides have been extensively studied as a biomaterial for DDS development due to their high biocompatibility. More usefully, polysaccharides can be crosslinked with various molecules such as micro/nanoparticles and hydrogels to form a modified DDS. According to IUPAC, hydrogel is defined as the structure and processing of sols, gels, networks and inorganic–organic hybrids. This 3D network which often consists of a hydrophilic polymer can drastically improve the physical and chemical properties of DDS to increase the biodegradability and bioavailability of the carrier drugs. The advancement of nanotechnology also allows the construction of hydrogel DDS with enhanced functionalities such as stimuli-responsiveness, target specificity, sustained drug release, and therapeutic efficacy. This review provides a current update on the use of hydrogel DDS derived from polysaccharide-based materials in delivering various therapeutic molecules and drugs. We also highlighted the factors that affect the efficacy of these DDS and the current challenges of developing them for clinical use.
Genetic Knockouts Indicate That the ABCC2 Protein in the Bollworm Helicoverpa zea Is Not a Major Receptor for the Cry1Ac Insecticidal Protein
Authors: Perera Omaththage P. , Little Nathan S. , Abdelgaffar Heba , Jurat-Fuentes Juan Luis , Reddy Gadi V. P.
Published: September 2021

Members of the insect ATP binding cassette transporter subfamily C2 (ABCC2) in several moth species are known as receptors for the Cry1Ac insecticidal protein from Bacillus thuringiensis (Bt). Mutations that abolish the functional domains of ABCC2 are known to cause resistance to Cry1Ac, although the reported levels of resistance vary widely depending on insect species. In this study, the function of the ABCC2 gene as a putative Cry1Ac receptor in Helicoverpa zea, a major pest of over 300 crops, was evaluated using CRISPR/Cas9 to progressively eliminate different functional ABCC2 domains. Results from bioassays with edited insect lines support that mutations in ABCC2 were associated with Cry1Ac resistance ratios (RR) ranging from 7.3- to 39.8-fold. No significant differences in susceptibility to Cry1Ac were detected between H. zea with partial or complete ABCC2 knockout, although the highest levels of tolerance were observed when knocking out half of ABCC2. Based on >500–1000-fold RRs reported in similar studies for closely related moth species, the low RRs observed in H. zea knockouts support that ABCC2 is not a major Cry1Ac receptor in this insect.
Antibacterial Peptides Resistance in Staphylococcus aureus: Various Mechanisms and the Association with Pathogenicity
Authors: Kawada-Matsuo Miki , Le Mi Nguyen-Tra , Komatsuzawa Hitoshi
Published: September 2021

Staphylococcus aureus is a bacterium that mainly colonizes the nasal cavity and skin. To colonize the host, it is necessary for S. aureus to resist many antibacterial factors derived from human and commensal bacteria. Among them are the bacteria-derived antimicrobial peptides (AMPs) called bacteriocins. It was reported that some two-component systems (TCSs), which are signal transduction systems specific to bacteria, are involved in the resistance to several bacteriocins in S. aureus. However, the TCS-mediated resistance is limited to relatively low concentrations of bacteriocins, while high concentrations of bacteriocins still exhibit antibacterial activity against S. aureus. To determine whether we could obtain highly bacteriocin-resistant mutants, we tried to isolate highly nisin A-resistant mutants by exposing the cells to sub-minimum inhibitory concentrations (MICs) of nisin A. Nisin A is one of the bacteriocins produced by Lactococcus lactis and is utilized as a food preservative worldwide. Finally, we obtained highly nisin A-resistant mutants with mutations in one TCS, BraRS, and in PmtR, which is involved in the expression of pmtABCD. Notably, some highly resistant strains also showed increased pathogenicity. Based on our findings, this review provides up-to-date information on the role of TCSs in the susceptibility to antibacterial peptides. Additionally, the mechanism for high antimicrobial peptides resistance and its association with pathogenicity in S. aureus is elucidated.
Context Fear Conditioning in Down Syndrome Mouse Models: Effects of Trisomic Gene Content, Age, Sex and Genetic Background
Authors: Ahmed Md. Mahiuddin , Block Aaron , Busquet Nicolas , Gardiner Katheleen J.
Published: September 2021

Down syndrome (DS), trisomy of the long arm of human chromosome 21 (Hsa21), is the most common genetic cause of intellectual disability (ID). Currently, there are no effective pharmacotherapies. The success of clinical trials to improve cognition depends in part on the design of preclinical evaluations in mouse models. To broaden understanding of the common limitations of experiments in learning and memory, we report performance in context fear conditioning (CFC) in three mouse models of DS, the Dp(16)1Yey, Dp(17)1Yey and Dp(10)1Yey (abbreviated Dp16, Dp17 and Dp10), separately trisomic for the human Hsa21 orthologs mapping to mouse chromosomes 16, 17 and 10, respectively. We examined female and male mice of the three lines on the standard C57BL/6J background at 3 months of age and Dp17 and Dp10 at 18 months of age. We also examined female and male mice of Dp17 and Dp10 at 3 months of age as F1 hybrids obtained from a cross with the DBA/2J background. Results indicate that genotype, sex, age and genetic background affect CFC performance. These data support the need to use both female and male mice, trisomy of sets of all Hsa21 orthologs, and additional ages and genetic backgrounds to improve the reliability of preclinical evaluations of drugs for ID in DS.
Risk Allele Frequency Analysis of Single-Nucleotide Polymorphisms for Vitamin D Concentrations in Different Ethnic Group
Authors: Yoon Byung-Woo , Shin Hyun-Tae , Seo Jehyun
Published: September 2021

The prevalence of vitamin D deficiency varies from 20.8% to 61.6% among populations of different ethnicities, suggesting the existence of a genetic component. The purpose of this study was to provide insights into the genetic causes of vitamin D concentration differences among individuals of diverse ancestry. We collected 320 single-nucleotide polymorphisms (SNPs) associated with vitamin D concentrations from a genome-wide association studies catalog. Their population-level allele frequencies were derived based on the 1000 Genomes Project and Korean Reference Genome Database. We used Fisher’s exact tests to assess the significance of the enrichment or depletion of the effect allele at a given SNP in the database. In addition, we calculated the SNP-based genetic risk score (GRS) and performed correlation analysis with vitamin D concentration that included latitude. European, American, and South Asian populations showed similar heatmap patterns, whereas African, East Asian, and Korean populations had distinct ones. The GRS calculated from allele frequencies of vitamin D concentration was highest among Europeans, followed by East Asians and Africans. In addition, the difference in vitamin D concentration was highly correlated with genetic factors rather than latitude effects.
Robert Wise’s The Day the Earth Stood Still (1951) and Interplanetary Emissary Klaatu Are Not Anti-Atomic: A Reassessment of the Filmic Evidence
Authors: Kozlovic Anton Karl
Published: September 2021

Inspired by a 1940s short story by Harry Bates, scripted by Edmund H. North, and directed by Robert Wise, The Day the Earth Stood Still (1951) is a science fiction cult classic. Of all its diverse interpretations, a commonly adopted reading influenced by the dawning of the Atomic Age parades it as an anti-nuclear exemplar starring alien emissary Klaatu visiting Earth with his robot companion Gort to (supposedly) suppress humanity’s atomic progress. However, upon a close forensic inspection of the film and commentator comments, this anti-atomic claim is resoundingly rejected. Utilizing humanist film criticism as the guiding analytical lens (i.e., looking inside not outside the frame), plus a selective review of the critical literature, it was demonstrated that: (a) there is a dearth of atomic iconography and dialogue, (b) there is no mention of banning atomic energy or weapons, (c) Earth’s atomics are nascent and not serious threats to the Federation, and (d) Klaatu is not anti-atomic but proudly pro-atomic. Overall, this SF film is strongly pro-nuclear in intention, word, and deed, which was frequently misinterpreted due to faulty film criticism, invented facts, and jumping to conclusions, and thus in need of academic correction. Further research into alien first-contact scenarios, robotic artificial intelligence, and the moral make-up of the SF universe is warranted and long overdue.
Feelings, Behavioral Actions and Depressive Symptoms Related to COVID-19 among Undergraduates in Hail, Saudi Arabia
Authors: Aldhmadi Badr K. , Itumalla Ramaiah , Kumar Rakesh , Perera Bilesha
Published: September 2021

The severe acute respiratory syndrome coronavirus 2 (COVID-19) outbreak has had a profound psychological impact on university undergraduates. Feelings, behavioral actions, and depressive symptoms related to COVID-19 in undergraduates in Hail, Saudi Arabia, were assessed using an online survey. Eighteen feelings and six behavioral acts were assessed. The Center for Epidemiological Studies Depression Scale was used to measure depressive symptomatology. Descriptive statistics and logistic regression techniques were used. The mean age of the participants (n = 418) was 20.2 years (standard deviation (SD) = 1.8 years), and 52.9% (n = 221) were males. Elevated levels of depressive symptoms were reported by 47.1% of male and 51.3% of female participants. Social isolation, loss of interest, obsessive monitoring of symptoms, concentration difficulties, recurrent negative thoughts, and worries about health services emerged as vital negative feelings related to COVID-19 that were expressed by the participants. Younger age (odds ratio (OR) = 0.636, 95% confidence interval (95% CI) = 0.428–0.946) and coming from the middle-income category (OR = 0.388, 95% CI = 0.151–0.994) were found to be protective factors against developing depressive symptoms. Frequent cleaning of hands, wearing masks when going out, and adherence to social distancing rules were practiced by 71.5% (95% CI = 67.2–75.8%), 78.7% (95% CI = (74.4–82.5%) and 66.0% (95% CI = (61.3–70.5%) of the participants, respectively. These behavioral acts were not associated with the development of depressive symptoms. Although the practice of COVID-19 precautionary measures by the participants was satisfactory, nearly half of the participants reported depressive symptoms. Innovative educational strategies are needed to curb concentration difficulties and social isolation experienced by undergraduates during outbreaks such as COVID-19.