bluuebunny/crossref_metadata_2025 huggingface dataset:
An Influence Maximization Algorithm for Dynamic Social Networks Based on Effective Links
Authors: Fu Baojun , Zhang Jianpei , Bai Hongna , Yang Yuting , He Yu
Published: July 2022

The connection between users in social networks can be maintained for a certain period of time, and the static network structure formed provides the basic conditions for various kinds of research, especially for discovering customer groups that can generate great influence, which is important for product promotion, epidemic prevention and control, and public opinion supervision, etc. However, the computational process of influence maximization ignores the timeliness of interaction behaviors among users, the screened target users cannot diffuse information well, and the time complexity of relying on greedy rules to handle the influence maximization problem is high. Therefore, this paper analyzes the influence of the interaction between nodes in dynamic social networks on information dissemination, extends the classical independent cascade model to a dynamic social network dissemination model based on effective links, and proposes a two-stage influence maximization solution algorithm (Outdegree Effective Link—OEL) based on node degree and effective links to enhance the efficiency of problem solving. In order to verify the effectiveness of the algorithm, five typical influence maximization methods are compared and analyzed on four real data sets. The results show that the OEL algorithm has good performance in propagation range and running time.
PGraphD*: Methods for Drift Detection and Localisation Using Deep Learning Modelling of Business Processes
Authors: Hanga Khadijah Muzzammil , Kovalchuk Yevgeniya , Gaber Mohamed Medhat
Published: July 2022

This paper presents a set of methods, jointly called PGraphD*, which includes two new methods (PGraphDD-QM and PGraphDD-SS) for drift detection and one new method (PGraphDL) for drift localisation in business processes. The methods are based on deep learning and graphs, with PGraphDD-QM and PGraphDD-SS employing a quality metric and a similarity score for detecting drifts, respectively. According to experimental results, PGraphDD-SS outperforms PGraphDD-QM in drift detection, achieving an accuracy score of 100% over the majority of synthetic logs and an accuracy score of 80% over a complex real-life log. Furthermore, PGraphDD-SS detects drifts with delays that are 59% shorter on average compared to the best performing state-of-the-art method.
A Mixed Finite Element Method for Stationary Magneto-Heat Coupling System with Variable Coefficients
Authors: Ding Qianqian , Long Xiaonian , Mao Shipeng
Published: July 2022

In this article, a mixed finite element method for thermally coupled, stationary incompressible MHD problems with physical parameters dependent on temperature in the Lipschitz domain is considered. Due to the variable coefficients of the MHD model, the nonlinearity of the system is increased. A stationary discrete scheme based on the coefficients dependent temperature is proposed, in which the magnetic equation is approximated by Nédélec edge elements, and the thermal and Navier–Stokes equations are approximated by the mixed finite elements. We rigorously establish the optimal error estimates for velocity, pressure, temperature, magnetic induction and Lagrange multiplier with the hypothesis of a low regularity for the exact solution. Finally, a numerical experiment is provided to illustrate the performance and convergence rates of our numerical scheme.
Autopoiesis, Thermodynamics, and the Natural Drift of Living Beings: Another Way to the New Evolutionary Synthesis
Authors: Villalobos Mario , Frick Ramiro , Vicencio-Jimenez Sergio
Published: July 2022

The New Evolutionary Synthesis (NES) groups a series of theories that, departing from the gene-centric approach of Modern Synthesis evolutionary theory (MS), place the organism as the central agent of evolution. Two versions of NES, each one with advantages and disadvantages, can be distinguished in this regard; the restrictive NES and the comprehensive NES. Comparatively, the comprehensive NES is a more robust theoretical construction than the restrictive one because it comes grounded on a general, thermodynamically informed theory of living beings (something that the restrictive NES lacks). However, due to its strong teleological commitments, the comprehensive NES has serious problems fitting with modern science’s methodological framework; a problem that the restrictive version, with no explicit commitment to teleology, does not face. In this paper, we propose the autopoietic approach to evolution as a way of integrating these two versions of NES, combining the theoretical robustness of the comprehensive view with the methodological appropriateness of the restrictive one. The autopoietic approach, we show, offers a non-teleological, organism-centered theory of evolution, namely the natural drift theory (NDT), and a grounding on a thermodynamic theory of living beings, namely the embodied autopoietic theory (EAT). We conclude that, from the programmatic point of view, an autopoietic (NDT plus EAT) approach to evolution offers a promising way to develop the NES project.
MCMCINLA Estimation of Missing Data and Its Application to Public Health Development in China in the Post-Epidemic Era
Authors: Teng Jiaqi , Ding Shuzhen , Shi Xiaoping , Zhang Huiguo , Hu Xijian
Published: July 2022

Medical data are often missing during epidemiological surveys and clinical trials. In this paper, we propose the MCMCINLA estimation method to account for missing data. We introduce a new latent class into the spatial lag model (SLM) and use a conditional autoregressive specification (CAR) spatial model-based approach to impute missing values, making the model fit into the integrated nested Laplace approximation (INLA) framework. Combining the advantages of both the Markov chain Monte Carlo (MCMC) and INLA frameworks, the MCMCINLA algorithm is used to implement imputation of the missing data and fit the model to derive estimates of the parameters from the posterior margins. Finally, the economic data and the hemorrhagic fever with renal syndrome (HFRS) disease data of mainland China from 2016–2018 are used as examples to explore the development of public health in China in the post-epidemic era. The results show that compared with expectation maximization (EM) and full information maximum likelihood estimation (FIML), the predicted values of the missing data obtained using our method are closer to the true values, and the spatial distribution of HFRS in China can be inferred from the imputation results with a southern-heavy and northern-light distribution. It can provide some references for the development of public health in China in the post-epidemic era.
Fine-Grained Classification of Announcement News Events in the Chinese Stock Market
Authors: Miu Feng , Wang Ping , Xiong Yuning , Jia Huading , Liu Wei
Published: July 2022

Determining the event type is one of the main tasks of event extraction (EE). The announcement news released by listed companies contains a wide range of information, and it is a challenge to determine the event types. Some fine-grained event type frameworks have been built from financial news or stock announcement news by domain experts manually or by clustering, ontology or other methods. However, we think there are still some improvements to be made based on the existing results. For example, a legal category has been created in previous studies, which considers violations of company rules and violations of the law the same thing. However, the penalties they face and the expectations they bring to investors are different, so it is more reasonable to consider them different types. In order to more finely classify the event type of stock announcement news, this paper proposes a two-step method. First, the candidate event trigger words and co-occurrence words satisfying the support value are extracted, and they are arranged in the order of common expressions through the algorithm. Then, the final event types are determined using three proposed criteria. Based on the real data of the Chinese stock market, this paper constructs 54 event types (p = 0.927, f = 0.946), and some reasonable and valuable types have not been discussed in previous studies. Finally, based on the unilateral trading policy of the Chinese stock market, we screened out some event types that may not be valuable to investors.
A Semantic Classification Approach for Indoor Robot Navigation
Authors: Alenzi Ziyad , Alenzi Emad , Alqasir Mohammad , Alruwaili Majed , Alhmiedat Tareq , Alia Osama Moh’d
Published: July 2022

Autonomous robot navigation has become a crucial concept in industrial development for minimizing manual tasks. Most of the existing robot navigation systems are based on the perceived geometrical features of the environment, with the employment of sensory devices including laser scanners, video cameras, and microwave radars to build the environment structure. However, scene understanding is a significant issue in the development of robots that can be controlled autonomously. The semantic model of the indoor environment offers the robot a representation closer to the human perception, and this enhances navigation tasks and human–robot interaction. In this paper, we propose a low-cost and low-memory framework that offers an improved representation of the environment using semantic information based on LiDAR sensory data. The output of the proposed work is a reliable classification system for indoor environments with an efficient classification accuracy of 97.21% using the collected dataset.
Relative Prices of Ethanol-Gasoline in the Major Brazilian Capitals: An Analysis to Support Public Policies
Authors: Quintino Derick David , Burnquist Heloisa Lee , Ferreira Paulo
Published: July 2022

The use of biomass as an energy source has advanced in recent decades, given the scientific evidence that it is a solution to the environmental problems faced globally. In this context, biofuels derived from biomass have a prominent role. Among the countries where this alternative is the most promising, Brazil stands out, just behind the USA. It is, therefore, necessary to assess whether such a replacement is economically viable. For such an assessment, the behavior of the relative price of bioethanol/gasoline is crucial. In the present work, the degree of temporal persistence of relative prices, considering the existence of shocks to which they are exposed, is evaluated, considering 15 important Brazilian capitals, via the detrended fluctuation analysis (DFA). The degree of correlation is also evaluated through the detrended cross-correlation analysis (DCCA) between fuel prices in São Paulo, the capital of the most populous state and main producer of bioethanol, with the capitals of the 14 states selected for the analysis. The period of analysis takes place between 2004 and 2020. The use of DCCA with sliding windows was recently proposed and we also evaluate DFA dynamically in this way, and this, together with an extended sample in the context of Brazilian fuel prices, represents the main innovations of the present work. We found that the degree of persistence varies significantly depending on the capitals analyzed, which means that price variations are localized and demand regional stimulus policies. Furthermore, it was found that the correlation with São Paulo is less intense in the most geographically distant capitals. Such evidence is important and complementary to infer how integrated the national bioethanol market is, in order to support public policies aimed at its consolidation.
Study of the Appropriate Well Types and Parameters for the Safe and Efficient Production of Marine Gas Hydrates in Unconsolidated Reservoirs
Authors: Chen Yuan , Wu Shiguo , Sun Ting , Jia Shu
Published: July 2022

The majority of marine hydrates are buried in unconsolidated or poorly consolidated marine sediments with limited cementation and strength. As a result, hydrate decomposition during production may cause significant subsidence of the formation, necessitating a halt in production. The numerical model of unconsolidated hydrate formation, based on geomechanics, was established in order to elucidate the depressurization production process. The sensitive factors of unconsolidated hydrate production were determined by analyzing the influence of formation parameters and production parameters on gas production. Then, a safety formation subsidence was proposed in this paper, and the appropriate well type and parameters for the safe and efficient production of hydrates in unconsolidated formations of various saturations were determined. The sensitivity of gas production to the formation parameters was in the order of formation porosity, hydrate saturation, and buried depth, while the effects of the production parameters were BHP (bottom hole pressure), horizontal length, and heat injection, in descending order. For hydrate reservoirs in the South China Sea, when hydrate saturation is 20%, a horizontal well is necessary and the appropriate horizontal length should be less than 80 m. However, when hydrate saturation is more than 30%, a vertical well should be selected, and the appropriate bottom hole pressure should be no less than 3800 kPa and 4800 kPa for 30% and 40% saturation, respectively. Based on the simulation results, hydrate saturation was the key factor by which to select an appropriate production technique in advance and adjust the production parameters. The study has elucidated the depressurization production of marine unconsolidated hydrate formations at depth, which has numerous implications for field production.
Investigation of the Heat Transfer Performance of Multi-Borehole Double-Pipe Heat Exchangers in Medium-Shallow Strata
Authors: Li Wenjing , Zhang Wenke , Li Zhenxing , Yao Haiqing , Cui Ping , Zhang Fangfang
Published: July 2022

Just as the double-pipe heat exchanger is being utilized in an increasing number of applications, its research content is also deepening. For this paper, based on the air-conditioning cold and heat source project of a building in Handan, Hebei Province, a 300-meter medium-shallow well double-pipe heat exchanger was used for heating and cooling, and a corresponding heat transfer model was established. The changes of parameters such as the inlet and outlet temperature, heat exchange (with and without a temperature gradient), and borehole wall temperature distribution between a single borehole, double boreholes, and four boreholes over one year in medium-shallow wells were simulated and analyzed. By comparing the obtained experimental data and the simulation data, the accuracy of the heat transfer model was verified. This provides a theoretical basis for the further advancement of the project and lays the foundation for an in-depth study of multi-borehole double-pipe heat exchangers.
Dynamic Modeling of a PEM Fuel Cell Power Plant for Flexibility Optimization and Grid Support
Authors: Crespi Elena , Guandalini Giulio , Nieto Cantero German , Campanari Stefano
Published: July 2022

The transition toward high shares of non-programmable renewable energy sources in the power grid requires an increase in the grid flexibility to guarantee grid reliability and stability. This work, developed within the EU project Grasshopper, identifies hydrogen Fuel Cell (FC) power plants, based on low temperature PEM cells, as a source of flexibility for the power grid. A dynamic numerical model of the flexible FC system is developed and tested against experimental data from a 100-kW pilot plant, built within the Grasshopper project. The model is then applied to assess the flexible performance of a 1 MW system in order to optimize the scale-up of the pilot plant to the MW-size. Simulations of load-following operation show the flexibility of the plant, which can ramp up and down with a ramp rate depending only on an externally imposed limit. Warm-up simulations allow proposing solutions to limit the warm-up time. Of main importance are the minimization of the water inventory in the system and the construction of a compact system, which minimizes the distance between the components.
New Cell Balancing Technique Using SIMO Two-Switch Flyback Converter with Multi Cells
Authors: Kim Ui-Jin , Park Sung-Jun
Published: July 2022

Recently, as the perception of eco-friendliness has changed, the demand for energy storage devices has been rapidly increasing due to the growth of the electric vehicle industry and smart grid facilities, which are emerging as an alternative to next-generation electricity supply and demand. Therefore, the importance of battery management technology is growing, and various voltage balancing techniques between battery cells are being studied in order to maintain high efficiency and continuous performance of batteries. This paper proposes a voltage balancing topology using a single input-multiple output (SIMO) two-switch flyback converter in a series battery configuration to resolve voltage imbalance between batteries. The characteristic of the proposed topology is that each cell on the secondary side of the two-switch flyback converter is connected to one high-frequency transformer to share the magnetic flux, and voltage balancing is performed according to the switch operation of the converter. At this time, the accumulated excess energy of the converter is refluxed to the power supply side through the freewheeling diode and converted into reactive power. The verification of the usefulness of the theoretical analysis in this paper was based on the analysis of the dynamic characteristics and steady state of the circuit through PSIM and experiments, and was conducted for one module composed of four cells.
The Impact of Renewable Energy Supply on Economic Growth and Productivity
Authors: Makieła Kamil , Mazur Błażej , Głowacki Jakub
Published: July 2022

The threat of the negative consequences of global warming makes the discussion about the relationship between economic growth, productivity, and increasing renewable energy involvement an important topic. Hence, the aim of this study is to analyze the impact of renewable energy and energy supply on economic growth and productivity at the national level using stochastic frontier analysis and the aggregate production function framework. In doing so, we analyzed a panel of annual data from 133 countries from 2008 to 2014. We apply a generalized stochastic frontier model, which allows us to differentiate between persistent and transient inefficiency, as well as individual effects. Our results indicate a threshold level in terms of a country’s development that needs to be obtained to benefit from increasing renewable energy involvement over time. However, if this threshold level is obtained, productivity gains are evident. We also found that the role of the energy supply in aggregate production is nontrivial. That is, its inclusion changes the relationship between key input factors (capital and labor) by decreasing their overall elasticities and increasing the observed economies of scale.
Characteristics of Source Rocks and Formation of Reservoir Bitumen in Yinchuan Graben, Ordos Basin, China
Authors: Fu Qingmeng , Liu Xianfeng , Yao Jingli , Wang Yongbo , Wu Nan , Xu Qinghai , Wang Jian , Liang Yilin
Published: July 2022

The Yinchuan Graben is an important potential exploration area that is located on the western margin of the Ordos Basin. Over 8000 m of Cenozoic strata have been formed since the Cretaceous. With an integrated approach of cores observation, logging analysis, and geochemical analysis, we analyzed the characteristics of the Cenozoic source rocks in the Yinchuan Graben and determined the formation and destruction of the fossil oil reservoirs. With type III kerogen, the TOC of the dark mudstone in the Qingshuiying Formation is up to 7.5%, and the Ro is 0.95–1.04%, indicating the source rocks have entered the mature stage but the hydrocarbon generation potential is insufficient. A quantity of reservoir bitumen and oil-bearing fluid inclusions (GOI = 1.67–4%) were found in the Qingshuiying Formation sandstone in Well YQ-1, which indicates a fossil oil reservoir had existed. The fossil oil reservoir and reservoir bitumen were generated by the unexplored pre-Cenozoic strata in the Yinchuan Graben. The reservoir bitumen has high maturity and is associated with many fluid inclusions with a high homogenization temperature or CO2. This indicates that the bitumen was formed by the pyrolysis of the oil which was caused by the hot fluid migrating along with the deep fault belts.
Multi-Objective Optimization Design of a Stator Coreless Multidisc Axial Flux Permanent Magnet Motor
Authors: Huang Changchuang , Kou Baoquan , Zhao Xiaokun , Niu Xu , Zhang Lu
Published: July 2022

The stator coreless axial flux permanent magnet (AFPM) motor with a compact structure, low torque ripple, and high efficiency is particularly suitable as a motor for electric propulsion systems. However, it still requires great effort to design an AFPM motor with higher torque density and lower torque ripple. In this paper, a stator coreless multidisc AFPM (SCM-AFPM) motor with a three-rotor and two-stator topology is proposed. To reduce rotor mass and increase torque density, the proposed SCM-AFPM motor adopts the hybrid permanent magnets (PMs) array with Halbach PMs in the two-terminal rotor and the conventional PMs array in the middle rotor. In addition, a multi-objective optimization model combining response surface method (RSM) and genetic algorithm (GA) is proposed and applied to the proposed SCM-AFPM motor. With the help of the three-dimensional finite-element analysis (3-D FEA), it is found that the torque ripple of the optimized SCM-AFPM motor is 4.73%, while it is 6.21% for the initial motor. Its torque ripple is reduced by 23.8%. Therefore, the proposed multi-objective optimization design method can quickly and reliably obtain the optimal design of the SCM-AFPM motor.
Properties and Simulating Research of Epoxy Resin/Micron-SiC/Nano-SiO2 Composite
Authors: Guo Ning , Meng Ruixiao , Gao Junguo , He Mingpeng , Zhang Yue , He Lizhi , Hu Haitao
Published: July 2022

The dielectric behavior of insulations is a key factor affecting the development of anti-corona materials for generators. Epoxy resin (EP), as the matrix, is blended with inorganic fillers of micron SiC and nano SiO2 to investigate the effect of micro and nano doping on the conductivity and breakdown mechanism of the composites. Using experimental and simulation analysis, it is found that the effect of nano-SiO2 doping concentration on the conductivity is related to the dispersion of SiC particles. The lower concentration of SiO2 could decrease the conductivity of the composites. The conductivity increases with raising the nano-SiO2 doping concentration to a critical value. Meanwhile, the breakdown field strength of the composites decreases with the rising content of SiC in constant SiO2 and increases with more SiO2 when mixed with invariable SiC. When an equivalent electric field is applied to the samples, the electric field at the interface of micron particles is much stronger than the average field of the dielectric, close to the critical electric field of the tunneling effect. The density of the homopolar space charge bound to the surface of the stator bar elevates as the concentration of filled nanoparticles increases, by which a more effective Coulomb potential shield can be built to inhibit the further injection of carriers from the electrode to the interior of the anti-corona layer, thus reducing the space charge accumulation in the anti-corona layer as well as increasing the breakdown field strength of the dielectric.
Kisspeptin Modulation of Reproductive Function
Authors: Szeliga Anna , Meczekalski Blazej
Published: July 2022

Kisspeptin is a peptide expressed mainly in the infundibular nucleus of the hypothalamus. Kisspeptin plays a crucial role in the regulation of reproductive functions. It is regarded as the most important factor responsible for the control of the hypothalamic–pituitary–gonadal axis, the onset of puberty, and the regulation of menstruation and fertility. Kisspeptin activity influences numerous processes such as steroidogenesis, follicular maturation, ovulation, and ovarian senescence. The identification of kisspeptin receptor mutations that cause hypogonadotropic hypogonadism has initiated studies on the role of kisspeptin in puberty. Pathologies affecting the neurons secreting kisspeptin play a major role in the development of PCOS, functional hypothalamic amenorrhea, and perimenopausal vasomotor symptoms. Kisspeptin analogs (both agonists and antagonists), therefore, may be beneficial as therapy in those afflicted with such pathologies. The aim of this review is to summarize the influence of kisspeptin in the physiology and pathology of the reproductive system in humans, as well as its potential use in therapy.
Potential of Measure App in Estimating Log Biometrics: A Comparison with Conventional Log Measurement
Authors: Borz Stelian Alexandru , Morocho Toaza Jenny Magaly , Forkuo Gabriel Osei , Marcu Marina Viorela
Published: July 2022

Wood measurement is an important process in the wood supply chain, which requires advanced solutions to cope with the current challenges. Several general-utility measurement options have become available by the developments in LiDAR or similar-capability sensors and Augmented Reality. This study tests the accuracy of the Measure App developed by Apple, running by integration into Augmented Reality and LiDAR technologies, in estimating the main biometrics of the logs. In a first experiment (E1), an iPhone 12 Pro Max running the Measure App was used to measure the diameter at one end and the length of 267 spruce logs by a free-eye measurement approach, then reference data was obtained by taking conventional measurements on the same logs. In a second experiment (E2), an iPhone 13 Pro Max equipped with the same features was used to measure the diameter at one end and the length of 200 spruce logs by a marking-guided approach, and the reference data was obtained similar to E1. The data were compared by a Bland and Altman analysis which was complemented by the estimation of the mean absolute error (MAE), root mean squared error (RMSE) and normalized root mean square error (NRMSE). In E1, nearly 86% of phone-based log diameter measurements were within ±1 cm compared to the reference data, of which 37% represented a perfect match. Of the phone-based log length measurements, 94% were within ±5 cm compared to the reference data, of which approximately 22% represented a perfect match. MAE, RMSE, and NRMSE of the log diameter and length were of 0.68, 0.96, and 0.02 cm, and of 1.81, 2.55, and 0.10 cm, respectively. Results from E2 were better, with 95% of the phone-based log diameter agreeing within ±1 cm, of which 44% represented a perfect match. As well, 99% of the phone-based length measurements were within ±5 cm, of which approximately 27% were a perfect match. MAE, RMSE, and NRMSE of the log diameter and length were of 0.65, 0.92, and 0.03 cm, and 1.46, 1.93, and 0.04 cm, respectively. The results indicated a high potential of replacing the conventional measurements for non-piled logs of ca. 3 m in length, but the applicability of phone-based measurement could be readily extended to log-end diameter measurement of the piled wood. Further studies could check if the accuracy of measurements would be enhanced by larger samples and if the approach has good replicability. Finding a balance between capability and measurement accuracy by extending the study to longer log lengths, different species and operating conditions would be important to characterize the technical limitations of the tested method.
Tropical Cyclone Disturbances Induce Contrasting Impacts on Forest Structure, Plant Composition, and Soil Properties in Temperate Broadleaf and Coniferous Forests
Authors: Černý Tomáš , Doležal Jiří , Petřík Petr , Šrůtek Miroslav , Song Jong-Suk , Altman Jan
Published: July 2022

Knowledge of forest recovery processes after severe disturbances, such as tropical cyclones, is essential for understanding the mechanisms maintaining forest diversity and ecosystem functioning. However, studies examining the impact of tropical cyclones on forest dynamics are still rare, especially in Northeast Asia. Here, we explore the complex responses of vegetation and soil chemistry to severe tropical cyclone disturbances in Hallasan National Park in South Korea. Vegetation and soil were examined five years before and five years after passages of tropical cyclones in 2012 in natural broadleaf and coniferous forests along an elevation gradient from 950 to 1770 m a.s.l., including the largest population of endemic Abies koreana. Tropical cyclones caused abundant tree mortality, resulting in a 46% decrease in stem basal area. Tropical cyclone disturbances triggered the spread of pioneer trees and shrubs and intense clonal propagation of graminoids, including dwarf bamboo, resulting in less diverse understory vegetation, especially in coniferous forests. In contrast, broadleaf forests at lower elevations experienced only minor disturbance. Opening of canopies after tropical cyclone disturbance led to the decrease in soil cations and doubling of available soil phosphorus stock, which likely contributed to the increased coverage of clonal graminoids, especially in coniferous forests (from 36 to 66%). Hence, increased competition of graminoids and reduction in seed fall and seedling recruitment prevented A. koreana regeneration. The subalpine forest dominated by A. koreana is forecasted to gradual loss due to the fact of temperature increases, intensified tropical cyclones and, particularly, due to the altered competition between dwarf bamboo and fir seedlings.
Altering Methane Emission, Fatty Acid Composition, and Microbial Profile during In Vitro Ruminant Fermentation by Manipulating Dietary Fatty Acid Ratios
Authors: Sun Xiaoge , Wang Qianqian , Yang Zhantao , Xie Tian , Wang Zhonghan , Li Shengli , Wang Wei
Published: July 2022

This study evaluated the effects of different dietary n-6/n-3 polyunsaturated fatty acid (PUFA) ratios on in vitro ruminant fermentation. Methane production, fatty acid composition, and microbial profiles were compared after the in vitro fermentation of rumen fluid collected from cows that had been fed isoenergetic and isoproteic experimental diets at three different n-6/n-3 ratios: 3.04 (HN6, high n-6 source), 2.03 (MN6, medium n-6 source), and 0.8 (LN6, low n-6 source). The fermented rumen fluid pH and total volatile fatty acid (VFA) levels were significantly decreased (p < 0.05) in the HN6 group as compared with those in the MN6 and LN6 groups. Additionally, the HN6 group produced a significantly lower (p < 0.05) proportion of methane than the MN6 group during in vitro fermentation. The MN6 and LN6 groups had significantly increased (p < 0.05) levels of C18:2n6 and C18:3n3 in the fermented rumen fluid, respectively, as compared with the HN6 group. The Chao 1 diversity index value was lower (p < 0.05) in the HN6 group than in the MN6 and LN6 groups. The observed species richness was significantly lower (p < 0.05) in the HN6 group than in the MN6 group. The reduced relative abundances of Lachnospiraceae UCG-006 and Selenomonas in the HN6 group resulted in lower pH and VFA levels (i.e., acetate, propionate, butyrate, and total VFA) during in vitro fermentation. Furthermore, n-6 and n-3 PUFAs were toxic to Butyrivibrio_2 growth, resulting in high levels of incomplete biohydrogenation. Taken together, the study findings suggest that supplementation of high-forage diets with high levels of n-6 PUFAs could reduce methane emissions, whereas both VFA concentration and pH are reduced.
Influence of the Dry Yeast Preparation Method on Final Sparkling Wine Characteristics
Authors: Berbegal Carmen , Polo Lucía , García-Esparza M. José , Álvarez Inmaculada , Zamora Fernando , Ferrer Sergi , Pardo Isabel
Published: July 2022

The effect of preparing the commercial yeast prise de mousse S. cerevisiae IOC 18-2007 on the second fermentation kinetics of a Macabeo white base wine was evaluated. The influence of yeast preparation on the final “Cava” sparkling wines was determined. The medium glucose, peptone, yeast extract (GPY medium), and the characteristic classic pied de cuve procedure were used to prepare the inoculum, which was placed besides a tirage liqueur inside bottles in which a second fermentation took place by the “traditional method”. The fermentation kinetics were similar for the first 60 days regardless of the employed yeast inoculum preparation. In both cases, glucose was exhausted and a few grams of fructose remained on day 30. The ethanol concentration after 60 days was the same in all of the wines. The sparkling wines inoculated with the GPY-grown yeasts showed higher titratable acidity, lower total polysaccharide and protein contents, and greater foamability (HM) and foam stability (HS). Regarding volatile compounds, these wines contained higher esters, fatty acids, higher alcohols, and γ-butyrolactone. Differences in the wine’s visual and flavor attributes were not significant no matter what inoculum was used. However, the aroma score was significantly higher in the wines inoculated with the pied de cuve-prepared yeasts.
Towards Strengthening the Resilience of IoV Networks—A Trust Management Perspective
Authors: Wang Yingxun , Zen Hushairi , Sabri Mohamad Faizrizwan Mohd , Wang Xiang , Kho Lee Chin
Published: July 2022

Over the past decade or so, considerable and rapid advancements in the state of the art within the promising paradigms of the Internet of Things (IoT) and Artificial Intelligence (AI) have accelerated the development of conventional Vehicular Ad Hoc Networks (VANETS) into the Internet of Vehicles (IoV), thereby bringing both connected and autonomous driving much closer to realization. IoV is a new concept in the Intelligent Traffic System (ITS) and an extended application of IoV in intelligent transportation. It enhances the existing capabilities of mobile ad hoc networks by integrating them with IoT so as to build an integrated and unified vehicle-to-vehicle network. It is worth mentioning that academic and industrial researchers are paying increasing attention to the concept of trust. Reliable trust models and accurate trust assessments are anticipated to improve the security of the IoV. This paper, therefore, focuses on the existing trustworthiness management models along with their corresponding trust parameters, as well as the corresponding trust evaluation parameters and simulation, which provide the basis for intelligent and efficient model suggestions and optimal parameter integration. In addition, this paper also puts forward some open research directions that need to be seriously solved before trust can play its due role in enhancing IoV network elasticity.
Correlation between Human Emotion and Temporal·Spatial Contexts by Analyzing Environmental Factors
Authors: Park Minwoo , Lee Euichul
Published: July 2022

In this paper, we propose a method for extracting emotional factors through audiovisual quantitative feature analysis from images of the surrounding environment. Nine features were extracted such as time complexity, spatial complexity (horizontal and vertical), color components (hue and saturation), intensity, contrast, sound amplitude, and sound frequency. These nine features were used to infer “pleasant-unpleasant” and “arousal-relaxation” scores through two support vector regressions. First, the inference accuracy for each of the nine features was calculated as a hit ratio to check the distinguishing power of the features. Next, the difference between the position in the two-dimensional emotional plane inferred through SVR and the ground truth determined subjectively by the subject was examined. As a result of the experiment, it was confirmed that the time-complexity feature had the best classification performance, and it was confirmed that the emotion inferred through SVR can be valid when the two-dimensional emotional plane is divided into 3 × 3.
Securing the Smart City Airspace: Drone Cyber Attack Detection through Machine Learning
Authors: Baig Zubair , Syed Naeem , Mohammad Nazeeruddin
Published: July 2022

Drones are increasingly adopted to serve a smart city through their ability to render quick and adaptive services. They are also known as unmanned aerial vehicles (UAVs) and are deployed to conduct area surveillance, monitor road networks for traffic, deliver goods and observe environmental phenomena. Cyber threats posed through compromised drones contribute to sabotage in a smart city’s airspace, can prove to be catastrophic to its operations, and can also cause fatalities. In this contribution, we propose a machine learning-based approach for detecting hijacking, GPS signal jamming and denial of service (DoS) attacks that can be carried out against a drone. A detailed machine learning-based classification of drone datasets for the DJI Phantom 4 model, compromising both normal and malicious signatures, is conducted, and results obtained yield advisory to foster futuristic opportunities to safeguard a drone system against such cyber threats.
Integrating Ecological Forecasting into Undergraduate Ecology Curricula with an R Shiny Application-Based Teaching Module
Authors: Moore Tadhg N. , Thomas R. Quinn , Woelmer Whitney M. , Carey Cayelan C.
Published: July 2022

Ecological forecasting is an emerging approach to estimate the future state of an ecological system with uncertainty, allowing society to better manage ecosystem services. Ecological forecasting is a core mission of the U.S. National Ecological Observatory Network (NEON) and several federal agencies, yet, to date, forecasting training has focused on graduate students, representing a gap in undergraduate ecology curricula. In response, we developed a teaching module for the Macrosystems EDDIE (Environmental Data-Driven Inquiry and Exploration; MacrosystemsEDDIE.org) educational program to introduce ecological forecasting to undergraduate students through an interactive online tool built with R Shiny. To date, we have assessed this module, “Introduction to Ecological Forecasting,” at ten universities and two conference workshops with both undergraduate and graduate students (N = 136 total) and found that the module significantly increased undergraduate students’ ability to correctly define ecological forecasting terms and identify steps in the ecological forecasting cycle. Undergraduate and graduate students who completed the module showed increased familiarity with ecological forecasts and forecast uncertainty. These results suggest that integrating ecological forecasting into undergraduate ecology curricula will enhance students’ abilities to engage and understand complex ecological concepts.
Editorial on Special Issue “New Era in the Volume Phase Transition of Gels”
Authors: Tokita Masayuki , Annaka Masahiko , Manning Gerald S.
Published: July 2022

The Special Issue of gels titled “Advancements in Gel Science” has been published from MDPI in 2019 [...]
Genotype-Phenotype Correlation and Functional Insights for Two Monoallelic TREX1 Missense Variants Affecting the Catalytic Core
Authors: Amico Giulia , Hemphill Wayne O. , Severino Mariasavina , Moratti Claudio , Pascarella Rosario , Bertamino Marta , Napoli Flavia , Volpi Stefano , Rosamilia Francesca , Signa Sara , Perrino Fred , Zedde Marialuisa , Ceccherini Isabella ,   on behalf of the Gaslini Stroke Study Group
Published: July 2022

The TREX1 exonuclease degrades DNA to prevent aberrant nucleic-acid sensing through the cGAS-STING pathway, and dominant Aicardi–Goutières Syndrome type 1 (AGS1) represents one of numerous TREX1-related autoimmune diseases. Monoallelic TREX1 mutations were identified in patients showing early-onset cerebrovascular disease, ascribable to small vessel disease, and CADASIL-like neuroimaging. We report the clinical-neuroradiological features of two patients with AGS-like (Patient A) and CADASIL-like (Patient B) phenotypes carrying the heterozygous p.A136V and p.R174G TREX1 variants, respectively. Genetic findings, obtained by a customized panel including 183 genes associated with monogenic stroke, were combined with interferon signature testing and biochemical assays to determine the mutations’ effects in vitro. Our results for the p.A136V variant are inconsistent with prior biochemistry-pathology correlates for dominant AGS-causing TREX1 mutants. The p.R174G variant modestly altered exonuclease activity in a manner consistent with perturbation of substrate interaction rather than catalysis, which represents the first robust enzymological data for a TREX1 variant identified in a CADASIL-like patient. In conclusion, functional analysis allowed us to interpret the impact of TREX1 variants on patients’ phenotypes. While the p.A136V variant is unlikely to be causative for AGS in Patient A, Patient B’s phenotype is potentially related to the p.R174G variant. Therefore, further functional investigations of TREX1 variants found in CADASIL-like patients are warranted to determine any causal link and interrogate the molecular disease mechanism(s).
Current Understanding of the Genetics and Molecular Mechanisms Regulating Wood Formation in Plants
Authors: Kim Min-Ha , Bae Eun-Kyung , Lee Hyoshin , Ko Jae-Heung
Published: July 2022

Unlike herbaceous plants, woody plants undergo volumetric growth (a.k.a. secondary growth) through wood formation, during which the secondary xylem (i.e., wood) differentiates from the vascular cambium. Wood is the most abundant biomass on Earth and, by absorbing atmospheric carbon dioxide, functions as one of the largest carbon sinks. As a sustainable and eco-friendly energy source, lignocellulosic biomass can help address environmental pollution and the global climate crisis. Studies of Arabidopsis and poplar as model plants using various emerging research tools show that the formation and proliferation of the vascular cambium and the differentiation of xylem cells require the modulation of multiple signals, including plant hormones, transcription factors, and signaling peptides. In this review, we summarize the latest knowledge on the molecular mechanism of wood formation, one of the most important biological processes on Earth.
A Systematic Review of the Impact of Mitochondrial Variations on Male Infertility
Authors: Amor Houda , Hammadeh Mohamad Eid
Published: July 2022

According to current estimates, infertility affects one in four couples trying to conceive. Primary or secondary infertility can be due either to both partners or only to the man or the woman. Up to 15% of infertility cases in men can be attributed to genetic factors that can lead to irreversible partial or complete spermatogenic arrest. The increased use of assisted reproductive technology (ART) has provided not only insights into the causes of male infertility but also afforded a diagnostic tool to detect and manage this condition among couples. Genes control a variety of physiological attributes, such as the hypothalamic–pituitary–gonadal axis, development, and germ cell differentiation. In the era of ART, it is important to understand the genetic basis of infertility so as to provide the most tailored therapy and counseling to couples. Genetic factors involved in male infertility can be chromosome abnormalities or single-gene disorders, mitochondrial DNA (mtDNA) mutations, Y-chromosome deletions, multifactorial disorders, imprinting disorders, or endocrine disorders of genetic origin. In this review, we discuss the role of mitochondria and the mitochondrial genome as an indicator of sperm quality and fertility.
Studying the Utilization of a Map-Based Visualization with Vitality Datasets by Domain Experts
Authors: Wada Kenji , Wallner Günter , Vos Steven
Published: July 2022

With the rapid growth of information technology and geographic information science, many map-based visualization applications for decision-making have been proposed. These applications are used in various contexts. Our study provides empirical evidence of how domain experts utilize map-based data visualization for generating insights into vitality with respect to health-related concepts. We conducted a study to understand domain experts’ knowledge, approach, and experience. Nine domain experts participated in the study, with three experts each from the fields of government, business, and research. The study followed a mixed-methods approach involving an online survey, open-ended tasks, and semi-structured interviews. For this purpose, a map-based data visualization application containing various vitality-related datasets was developed for the open-ended tasks. Our study confirms the importance of maps in this domain but also shows that vitality is strongly geographical. Furthermore, we found that map-based visualizations require multiple data sources and dimensions to enhance the utilization of them in the context of vitality. Therefore, our study suggests the necessity of a combination of multiple datasets as ‘vitality themes’ to efficiently communicate this particular subject to experts. As such, our results provide guidelines for designing map-based data visualizations that support the decision-making process across various domain experts in the field of vitality.
A Lignin-Rich Extract of Giant Reed (Arundo donax L.) as a Possible Tool to Manage Soilborne Pathogens in Horticulture: A Preliminary Study on a Model Pathosystem
Authors: Galletti Stefania , Cianchetta Stefano , Righini Hillary , Roberti Roberta
Published: July 2022

Finding new sustainable tools for crop protection in horticulture has become mandatory. Giant reed (Arundo donax L.) is a tall, perennial, widely diffuse lignocellulosic grass, mainly proposed for bioenergy production due to the fact of its high biomass yield and low agronomic requirements. Some studies have already highlighted antimicrobial and antifungal properties of giant reed-derived compounds. This study aimed at investigating the potential of a lignin-rich giant reed extract for crop protection. The extract, obtained by dry biomass treatment with potassium hydroxide at 120 °C, followed by neutralization, was chemically characterized. A preliminary in vitro screening among several pathogenic strains of fungi and oomycetes showed a high sensitivity by most of the soilborne pathogens to the extract; thus, an experiment was performed with the model pathosystem, Pythium ultimum–zucchini in a growth substrate composed of peat or sand. The adsorption by peat and sand of most of the lignin-derived compounds contained in the extract was also observed. The extract proved to be effective in restoring the number of healthy zucchini plantlets in the substrate infected with P. ultimum compared to the untreated control. This study highlights the potential of the lignin-rich giant reed extract to sustain crop health in horticulture.