bluuebunny/crossref_metadata_2025 huggingface dataset:
Deviating from the Beaten Track: New Twists in Brassinosteroid Receptor Function
Authors: Wolf Sebastian
Published: February 2020

A key feature of plants is their plastic development tailored to the environmental conditions. To integrate environmental signals with genetic growth regulatory programs, plants rely on a number of hormonal pathways, which are intimately connected at multiple levels. Brassinosteroids (BRs), a class of plant sterol hormones, are perceived by cell surface receptors and trigger responses instrumental in tailoring developmental programs to environmental cues. Arguably, BR signalling is one of the best-characterized plant signalling pathways, and the molecular composition of the core signal transduction cascade seems clear. However, BR research continues to reveal new twists to re-shape our view on this key signalling circuit. Here, exciting novel findings pointing to the plasma membrane as a key site for BR signalling modulation and integration with other pathways are reviewed and new inputs into the BR signalling pathway and emerging “non-canonical” functions of the BR receptor complex are highlighted. Together, this new evidence underscores the complexity of plant signalling integration and serves as a reminder that highly-interconnected signalling pathways frequently comprise non-linear aspects which are difficult to convey in classical conceptual models.
Ticagrelor Increases SIRT1 and HES1 mRNA Levels in Peripheral Blood Cells from Patients with Stable Coronary Artery Disease and Chronic Obstructive Pulmonary Disease
Authors: Aquila Giorgio , Vieceli Dalla Sega Francesco , Marracino Luisa , Pavasini Rita , Cardelli Laura Sofia , Piredda Anna , Scoccia Alessandra , Martino Valeria , Fortini Francesca , Bononi Ilaria , Martini Fernanda , Manfrini Marco , Pannuti Antonio , Ferrari Roberto , Rizzo Paola , Campo Gianluca
Published: February 2020

Ticagrelor is a powerful P2Y12 inhibitor with pleiotropic effects in the cardiovascular system. Consistently, we have reported that in patients with stable coronary artery disease (CAD) and concomitant chronic obstructive pulmonary disease (COPD) who underwent percutaneous coronary intervention (PCI), 1-month treatment with ticagrelor was superior in improving biological markers of endothelial function, compared with clopidogrel. The objective of this study was to investigate the mechanisms underlying these beneficial effects of ticagrelor by conducting molecular analyses of RNA isolated from peripheral blood cells of these patients. We determined mRNAs levels of markers of inflammation and oxidative stress, such as RORγt (T helper 17 cells marker), FoxP3 (regulatory T cells marker), NLRP3, ICAM1, SIRT1, Notch ligands JAG1 and DLL4, and HES1, a Notch target gene. We found that 1-month treatment with ticagrelor, but not clopidogrel, led to increased levels of SIRT1 and HES1 mRNAs. In patients treated with ticagrelor or clopidogrel, we observed a negative correlation among changes in both SIRT1 and HES1 mRNA and serum levels of Epidermal Growth Factor (EGF), a marker of endothelial dysfunction found to be reduced by ticagrelor treatment in our previous study. In conclusion, we report that in stable CAD/COPD patients ticagrelor positively regulates HES1 and SIRT1, two genes playing a protective role in the context of inflammation and oxidative stress. Our observations confirm and expand previous studies showing that the beneficial effects of ticagrelor in stable CAD/COPD patients may be, at least in part, mediated by its capacity to reduce systemic inflammation and oxidative stress.
Shedding Light on the Effect of Uncertainties in the Seismic Fragility Analysis of Existing Concrete Dams
Authors: Sevieri Giacomo , De Falco Anna , Marmo Giovanni
Published: February 2020

The seismic risk assessment of existing concrete gravity dams is of primary importance for our society because of the fundamental role of these infrastructures in the sustainability of a country. The seismic risk assessment of dams is a challenging task due to the lack of case histories, such as gravity dams’ seismic collapses, which hinders the definition of limit states, thus making the application of any conventional safety assessment approach difficult. Numerical models are then fundamental to predict the seismic behaviour of the complex dam-soil-reservoir interacting system, even though uncertainties strongly affect the results. These uncertainties, mainly related to mechanical parameters and variability of the seismic motion, are among the reasons that, so far, prevented the performance-based earthquake engineering approach from being applied to concrete dams. This paper discusses the main issues behind the application of the performance-based earthquake engineering to existing concrete dams, with particular emphasis on the fragility analysis. After a critical review of the most relevant studies on this topic, the analysis of an Italian concrete gravity dam is presented to show the effect of epistemic uncertainties on the calculation of seismic fragility curves. Finally, practical conclusions are derived to guide professionals to the reduction of epistemic uncertainties, and to the definition of reliable numerical models.
Effects of Seedling Age on Colonization Patterns of Citrus limon Plants by Endophytic Beauveria bassiana and Metarhizium anisopliae and Their Influence on Seedlings Growth
Authors: Bamisile Bamisope Steve , Senyo Akutse Komivi , Dash Chandra Kanta , Qasim Muhammad , Ramos Aguila Luis Carlos , Ashraf Hafiza Javaria , Huang Wei , Hussain Mubasher , Chen Shiman , Wang Liande
Published: February 2020

The inoculation methods, the fungal strains, and several other factors are known to influent the success of fungal entomopathogens colonization in plants. The physiological status of the plant could also be another determinant. In the present study, the ability of three strains of Beauveria bassiana and one strain of Metarhizium anisopliae to successfully colonize Citrus limon plants and the influence of seedling age on endophytic colonization success was examined. Three, 4, and 6 months old seedlings were inoculated with 10 mL of 1 × 108 conidial·mL−1 suspensions of each of the four fungal strains via foliar spraying. All fungal strains successfully colonized citrus seedlings and were sustained up to 2 months in colonized plants irrespective of the seedling age, with differences in the mean percentage colonization recorded at various post-inoculation periods among the fungal strains. The highest percent endophytic fungi recovery rate was recorded in the 3 months old seedlings, where fungal mycelia of inoculated fungi were successfully re-isolated from 65.6% of the untreated newly developed leaf and stem tissues. One strain of B. bassiana, BB Fafu-12, significantly improved seedling height and leaf number. The study demonstrates the influence of seedling age on B. bassiana and M. anisopliae successful colonization in the citrus plant.
Finite Element Analysis of the Stability of a Sinusoidal Web in Steel and Composite Steel-Concrete Girders
Authors: Śledziewski Krzysztof , Górecki Marcin
Published: February 2020

This paper presents the results of numerical investigations into the behavior of a sinusoidal web loaded in shear due to buckling in the period from the onset of buckling until failure, as well as the impact of a reinforced concrete slab on the stability of the web. The analysis concerned steel girders and composite girders with the top flange bonded to a reinforced concrete slab. Nonlinear analyses were performed using the finite element method. The results of the investigations support the conclusion that the appearance and propagation of shear stresses in the sinusoidal web of the composite steel–concrete beam are the same as those in an identical non-composite steel beam, but the bracing of the top flanges improves the shear strength and, at the same time, affects the location of initial stresses. In addition, it was found that, despite the three types of buckling, the predominant failure of the sinusoidal webs, regardless of the presence of the concrete slab, is global buckling. It occurs diagonally through several folds at the same time, including deformation of the web over its entire height.
Land-Cover Changes to Surface-Water Buffers in the Midwestern USA: 25 Years of Landsat Data Analyses (1993–2017)
Authors: Berhane Tedros , Lane Charles , Mengistu Samson , Christensen Jay , Golden Heather , Qiu Shi , Zhu Zhe , Wu Qiusheng
Published: February 2020

To understand the timing, extent, and magnitude of land use/land cover (LULC) change in buffer areas surrounding Midwestern US waters, we analyzed the full imagery archive (1982–2017) of three Landsat footprints covering ~100,000 km2. The study area included urbanizing Chicago, Illinois and St. Louis, Missouri regions and agriculturally dominated landscapes (i.e., Peoria, Illinois). The Continuous Change Detection and Classification algorithm identified 1993–2017 LULC change across three Landsat footprints and in 90 m buffers for ~110,000 surface waters; waters were also size-binned into five groups for buffer LULC change analyses. Importantly, buffer-area LULC change magnitude was frequently much greater than footprint-level change. Surface-water extent in buffers increased by 14–35x the footprint rate and forest decreased by 2–9x. Development in buffering areas increased by 2–4x the footprint-rate in Chicago and Peoria area footprints but was similar to the change rate in the St. Louis area footprint. The LULC buffer-area change varied in waterbody size, with the greatest change typically occurring in the smallest waters (e.g., <0.1 ha). These novel analyses suggest that surface-water buffer LULC change is occurring more rapidly than footprint-level change, likely modifying the hydrology, water quality, and biotic integrity of existing water resources, as well as potentially affecting down-gradient, watershed-scale storages and flows of water, solutes, and particulate matter.
New Insights in Regional Climate Change: Coupled Land Albedo Change Estimation in Greenland from 1981 to 2017
Authors: Peng Fei , Zhou Haoran , Chen Gong , Li Qi , Wu Yongxing , Liang Heming
Published: February 2020

Land albedo is an essential variable in land surface energy balance and climate change. Within regional land, albedo has been altered in Greenland as ice melts and runoff increases in response to global warming against the period of the pre-industrial revolution. The assessment of spatiotemporal variation in albedo is a prerequisite for accurate prediction of ice sheet loss and future climate change, as well as crucial prior knowledge for improving current climate models. In our study, we employed the satellite data product from the global land surface satellite (GLASS) project to obtain the spatiotemporal variation of albedo from 1981 to 2017 using the non-parameter-based M-K (Mann-Kendall) method. It was found that the albedo generally showed a decreasing trend in the past 37 years (−0.013 ± 0.001 decade−1, p < 0.01); in particular, the albedo showed a significant increasing trend in the middle part of the study area but a decreasing trend in the coastal area. The interannual and seasonal variations of albedo showed strong spatial-temporal heterogeneity. Additionally, based on natural and anthropogenic factors, in order to further reveal the potential effects of spatiotemporal variation of albedo on the regional climate, we coupled climate model data with observed data documented by satellite and adopted a conceptual experiment for detections and attributions analysis. Our results showed that both the greenhouse gas forcing and aerosol forcing induced by anthropogenic activities in the past 37 decades were likely to be the main contributors (46.1%) to the decrease of albedo in Greenland. Here, we indicated that overall, Greenland might exhibit a local warming effect based on our study. Albedo–ice melting feedback is strongly associated with local temperature changes in Greenland. Therefore, this study provides a potential pathway to understanding climate change on a regional scale based on the coupled dataset.
Analysis of the Transport of Aerosols over the North Tropical Atlantic Ocean Using Time Series of POLDER/PARASOL Satellite Data
Authors: Fréville Hélène , Chami Malik , Mallet Marc
Published: February 2020

The time series of total, fine and coarse POLAC/PARASOL aerosol optical depth (AOD) satellite products (2005–2013) processed by the POLAC algorithm are examined to investigate the transport of aerosols over the North Tropical Atlantic Ocean, a region that is characterized by significant dust aerosols events. First, the comparison of satellite observations with ground-based measurements acquired by AERONET ground-based measurements shows a satisfactory consistency for both total AOD and coarse mode AOD (i.e., correlation coefficients of 0.75 and bias ranging from −0.03 to 0.03), thus confirming the robustness and performance of POLAC/PARASOL data to investigate the spatio-temporal variability of the aerosols over the study area. Regarding fine mode aerosol, POLAC/PARASOL data present a lower performance with correlation coefficient ranging from 0.37 to 0.73. Second, the analysis of POLAC/PARASOL aerosol climatology reveals a high contribution of the coarse mode of aerosols ( AOD c between 0.1 and 0.4) at long distance from the African sources, confirming previous studies related to dust transport. The POLAC/PARASOL data were also compared with aerosol data obtained over the North Tropical Atlantic Ocean from MACC and MERRA-2 reanalyses. It is observed that the total AOD is underestimated in both reanalysis with a negative bias reaching −0.2. In summary, our results thus suggest that satellite POLAC/PARASOL observations of fine and coarse modes of aerosols could provide additional constraints useful to improve the quantification of the dust direct radiative forcing on a regional scale but also the biogeochemical processes such as nutrient supply to the surface waters.
Determining the Fracture Process Zone Length and Mode I Stress Intensity Factor in Concrete Structures via Mechanoluminescent Technology
Authors: Kim Seong-Kyum , Shin Ho Geun , Timilsina Suman , Kim Ji Sik
Published: February 2020

The mechanoluminescent (ML) technology that is being developed as a new and substitutive technology for structural health monitoring systems (SHMS) comprises stress/strain sensing micro-/nanoparticles embedded in a suitable binder, digital imaging system, and digital image processing techniques. The potential of ML technology to reveal the fracture process zone (FPZ) that is commonly found in structural materials like concrete and to calculate the stress intensity factor (SIF) of concrete, which are crucial for SHMS, has never been done before. Therefore, the potential of ML technology to measure the length of the FPZ and to calculate the SIF has been demonstrated in this work by considering a single-edge notched bend (SENB) test of the concrete structures. The image segmentation approach based on the histogram of an ML image as well the skeletonization of an ML image have been introduced in this work to facilitate the measurement of the length of ML pattern, crack, and FPZ. The results show ML technology has the potential to determine fracture toughness, to visualize FPZ and cracks, and to measure their lengths in structural material like concrete, which makes it applicable to structural health monitoring systems (SHMS) to characterize the structural integrity of structures.
Motives, Barriers, and Expected Benefits of ISO 14001 in the Agri-Food Sector
Authors: Carrillo-Labella Rocio , Fort Fatiha , Parras-Rosa Manuel
Published: February 2020

Over time, sustainability has gained a greater presence in companies and with consumers around the world, although it can be said that there is still some confusion in its conceptualization and in the identification of the driving factors. A part of the literature considers that environmental management systems (EMS) such as ISO 14001 are facilitating factors that allow organizational remodeling towards more sustainable production. For a better understanding, this paper presents a qualitative study with semi-structured interviews to analyze the perceptions that managers, employees, and quality managers have about the concept of sustainability and, given that environmental management systems are considered as motivational factors, it also analyzes the perceptions they have about the motivations, barriers, and expected benefits of their adoption in the olive food industry in southern Spain. It is possible to point out the existence of some confusion about the concept of sustainability, and that both regulatory and market factors such as image and reputation improvement, differentiation, and sales increases, especially in exports, are considered to be motivational for their implementation. This work contributes to the literature on sustainability and environmental management systems in sectors of activity with high environmental involvement, such as the agri-food industry.
A Stochastic Dominance Approach to Evaluating Pro-Poor Growth—An Application to the Spanish Case
Authors: Ahamdanech Ismael , García-Pérez Carmelo , Prieto-Alaiz Mercedes
Published: February 2020

In this paper, we analyze, in a novel way, the nature of economic growth in Spain after the Great Recession, in relation to its effect on poverty reduction. We use a statistical test to analyze the pro-poorness nature of economic growth using a stochastic dominance approach, not used in this context so far. We decompose changes in the difference in generalized Lorenz ordinates into a growth effect and an inequality effect and apply this to formal Spanish income data statistical tests based on dominance methods. We found that growth was pro-poor in Spain as a whole between 2013 and 2017. As regards regional growth effects, we conclude that growth was weakly pro-poor in seven of Spain’s 17 regions, it was neither pro-poor nor anti-poor in nine regions, and only weakly anti-poor in one region.
A Symmetry-Based Approach for First-Passage-Times of Gauss-Markov Processes through Daniels-Type Boundaries
Authors: Pirozzi Enrica
Published: February 2020

Symmetry properties of the Brownian motion and of some diffusion processes are useful to specify the probability density functions and the first passage time density through specific boundaries. Here, we consider the class of Gauss-Markov processes and their symmetry properties. In particular, we study probability densities of such processes in presence of a couple of Daniels-type boundaries, for which closed form results exit. The main results of this paper are the alternative proofs to characterize the transition probability density between the two boundaries and the first passage time density exploiting exclusively symmetry properties. Explicit expressions are provided for Wiener and Ornstein-Uhlenbeck processes.
Correction: Çakmak, A. New Type Direction Curves in 3-Dimensional Compact Lie Group Symmetry 2019, 11, 387
Authors: Çakmak Ali
Published: February 2020

The authors wish to make the following corrections to their paper [...]
Primeness of Relative Annihilators in BCK-Algebra
Authors: Bordbar Hashem , Muhiuddin G. , Alanazi Abdulaziz M.
Published: February 2020

Conditions that are necessary for the relative annihilator in lower B C K -semilattices to be a prime ideal are discussed. Given the minimal prime decomposition of an ideal A, a condition for any prime ideal to be one of the minimal prime factors of A is provided. Homomorphic image and pre-image of the minimal prime decomposition of an ideal are considered. Using a semi-prime closure operation “ c l ”, we show that every minimal prime factor of a c l -closed ideal A is also c l -closed.
Building a Speech and Text Corpus of Turkish: Large Corpus Collection with Initial Speech Recognition Results
Authors: Polat Huseyin , Oyucu Saadin
Published: February 2020

To build automatic speech recognition (ASR) systems with a low word error rate (WER), a large speech and text corpus is needed. Corpus preparation is the first step required for developing an ASR system for a language with few argument speech documents available. Turkish is a language with limited resources for ASR. Therefore, development of a symmetric Turkish transcribed speech corpus according to the high resources languages corpora is crucial for improving and promoting Turkish speech recognition activities. In this study, we constructed a viable alternative to classical transcribed corpus preparation techniques for collecting Turkish speech data. In the presented approach, three different methods were used. In the first step, subtitles, which are mainly supplied for people with hearing difficulties, were used as transcriptions for the speech utterances obtained from movies. In the second step, data were collected via a mobile application. In the third step, a transfer learning approach to the Grand National Assembly of Turkey session records (videotext) was used. We also provide the initial speech recognition results of artificial neural network and Gaussian mixture-model-based acoustic models for Turkish. For training models, the newly collected corpus and other existing corpora published by the Linguistic Data Consortium were used. In light of the test results of the other existing corpora, the current study showed the relative contribution of corpus variability in a symmetric speech recognition task. The decrease in WER after including the new corpus was more evident with increased verified data size, compensating for the status of Turkish as a low resource language. For further studies, the importance of the corpus and language model in the success of the Turkish ASR system is shown.
Predicting Daily Air Pollution Index Based on Fuzzy Time Series Markov Chain Model
Authors: Alyousifi Yousif , Othman Mahmod , Sokkalingam Rajalingam , Faye Ibrahima , Silva Petronio C. L.
Published: February 2020

Air pollution is a worldwide problem faced by most countries across the world. Prediction of air pollution is crucial in air quality research since it is related to public health effects. The symmetry concept of fuzzy data transformation from a single point (crisp) to a fuzzy number is essential for the forecasting model. Fuzzy time series (FTS) is applied for predicting air pollution; however, it has a limitation caused by utilizing an arbitrary number of intervals. This study involves predicting the daily air pollution index using the FTS Markov chain (FTSMC) model based on a grid method with an optimal number of partitions, which can greatly develop the model accuracy for air pollution. The air pollution index (API) data, which was collected from Klang, Malaysia, is considered in the analysis. The model has been validated using three statistical criteria, which are the root mean (RMSE), the mean absolute percentage error (MAPE), and the Thiels’ U statistic. Also, the model’s validation has been investigated by comparison with some of the famous statistical models. The results of the proposed model demonstrated outperformed the other models. Thus, the proposed model could be a better option in air pollution forecasting that can be useful for managing air quality.
Antiautomorphisms and Biantiautomorphisms of Some Finite Abelian Groups
Authors: López-Aguayo Daniel , López Aguayo Servando
Published: February 2020

We extend the concepts of antimorphism and antiautomorphism of the additive group of integers modulo n, given by Gaitanas Konstantinos, to abelian groups. We give a lower bound for the number of antiautomorphisms of cyclic groups of odd order and give an exact formula for the number of linear antiautomorphisms of cyclic groups of odd order. Finally, we give a partial classification of the finite abelian groups which admit antiautomorphisms and state some open questions.
Analysis of the Spanish IBEX-35 Companies’ Returns Using Extensions of the Fama and French Factor Models
Authors: Jareño Francisco , González María de la O , Munera Laura
Published: February 2020

This paper studies in depth the sensitivity of Spanish companies’ returns to changes in several risk factors between January 2000 and December 2018 using the quantile regression approach. Concretely, this research applies extensions of the Fama and French three- and five-factor models (1993 and 2015), according to González and Jareño (2019), adding relevant explanatory factors, such as nominal interest rates, the Carhart (1997) risk factor for momentum and for momentum reversal and the Pastor and Stambaugh (2003) traded liquidity factor. Additionally, for robustness, this paper splits the entire sample period into three sub-sample periods (pre-crisis, crisis and post-crisis) to analyse the results according to the economic cycle. The main conclusions of this paper are fourfold: First, these two models have the greatest explanatory power in the extreme quantiles of the return distribution (0.1 and 0.9) and more specifically in the lowest quantile 0.1. Second, the second model, based on the Fama and French five-factor model, shows the highest explanatory power not only in the full period but also in the three sub-periods. Third, the bank BBVA is the company that shows the highest sensitivity to changes in the explanatory factors in most periods because its adjusted R2 is the highest. Fourth, the stage of the economy with the highest explanatory power is the crisis subperiod. Thus, the final conclusion of this paper is that the second model explains best variations in Spanish companies’ returns in crisis stages and low quantiles.
Facial Expression Recognition by Regional Weighting with Approximated Q-Learning
Authors: Oh Seong-Gi , Kim TaeYong
Published: February 2020

Several facial expression recognition methods cluster facial elements according to similarity and weight them considering the importance of each element in classification. However, these methods are limited by the pre-definitions of units restricting modification of the structure during optimization. This study proposes a modified support vector machine classifier called Grid Map, which is combined with reinforcement learning to improve the classification accuracy. To optimize training, the input image size is normalized according to the cascade rules of a pre-processing detector, and the regional weights are assigned by an adaptive cell size that divides each region of the image using bounding grids. Reducing the size of the bounding grid reduces the area used for feature extraction, allowing more detailed weighted features to be extracted. Error-correcting output codes with a histogram of gradient is selected as the classification method via an experiment to determine the optimal feature and classifier selection. The proposed method is formulated into a decision process and solved via Q-learning. To classify seven emotions, the proposed method exhibits accuracies of 96.36% and 98.47% for four databases and Extended Cohn-–Kanade Dataset (CK+), respectively. Compared to the basic method exhibiting a similar accuracy, the proposed method requires 68.81% fewer features and only 66.33% of the processing time.
The Pauli Exclusion Principle and the Problems of Its Experimental Verification
Authors: Kaplan Ilya G.
Published: February 2020

The modern state of the Pauli exclusion principle is shortly discussed. We describe the discovery by Pauli, his principle for electrons, and how it was generalized for all elementary particles in the framework of quantum mechanics. The motivations and theoretical conceptions that induced the experiments for verification of the Pauli exclusion principle are analyzed. The results and methodology of two different types of experiments are discussed: (1) the search of unusual atoms and nuclei in the stable non-Pauli states, and (2) the experiments in which the emitted radiation of non-Pauli transitions is measured. In conclusion, the comments on the discussed experiments that follow from the general quantum mechanical conceptions and group theory are formulated.
Optimal Location and Sizing of PV Sources in DC Networks for Minimizing Greenhouse Emissions in Diesel Generators
Authors: Montoya Oscar Danilo , Grisales-Noreña Luis Fernando , Gil-González Walter , Alcalá Gerardo , Hernandez-Escobedo Quetzalcoatl
Published: February 2020

This paper addresses the problem of the optimal location and sizing of photovoltaic (PV) sources in direct current (DC) electrical networks considering time-varying load and renewable generation curves. To represent this problem, a mixed-integer nonlinear programming (MINLP) model is developed. The main idea of including PV sources in the DC grid is minimizing the total greenhouse emissions produced by diesel generators in isolated areas. An artificial neural network is employed for short-term forecasting to deal with uncertainties in the PV power generation. The general algebraic modeling system (GAMS) package is employed to solve the MINLP model by using the CONOPT solver that works with mixed and integer variables. Numerical results demonstrate important reductions of harmful gas emissions to the atmosphere when PV sources are optimally integrated (size and location) to the DC grid.
LiDAR and Camera Fusion Approach for Object Distance Estimation in Self-Driving Vehicles
Authors: Kumar G Ajay , Lee Jin Hee , Hwang Jongrak , Park Jaehyeong , Youn Sung Hoon , Kwon Soon
Published: February 2020

The fusion of light detection and ranging (LiDAR) and camera data in real-time is known to be a crucial process in many applications, such as in autonomous driving, industrial automation, and robotics. Especially in the case of autonomous vehicles, the efficient fusion of data from these two types of sensors is important to enabling the depth of objects as well as the detection of objects at short and long distances. As both the sensors are capable of capturing the different attributes of the environment simultaneously, the integration of those attributes with an efficient fusion approach greatly benefits the reliable and consistent perception of the environment. This paper presents a method to estimate the distance (depth) between a self-driving car and other vehicles, objects, and signboards on its path using the accurate fusion approach. Based on the geometrical transformation and projection, low-level sensor fusion was performed between a camera and LiDAR using a 3D marker. Further, the fusion information is utilized to estimate the distance of objects detected by the RefineDet detector. Finally, the accuracy and performance of the sensor fusion and distance estimation approach were evaluated in terms of quantitative and qualitative analysis by considering real road and simulation environment scenarios. Thus the proposed low-level sensor fusion, based on the computational geometric transformation and projection for object distance estimation proves to be a promising solution for enabling reliable and consistent environment perception ability for autonomous vehicles.
Hybrid Computational Intelligence Methods for Landslide Susceptibility Mapping
Authors: Wang Guirong , Lei Xinxiang , Chen Wei , Shahabi Himan , Shirzadi Ataollah
Published: February 2020

In this study, hybrid integration of MultiBoosting based on two artificial intelligence methods (the radial basis function network (RBFN) and credal decision tree (CDT) models) and geographic information systems (GIS) were used to establish landslide susceptibility maps, which were used to evaluate landslide susceptibility in Nanchuan County, China. First, the landslide inventory map was generated based on previous research results combined with GIS and aerial photos. Then, 298 landslides were identified, and the established dataset was divided into a training dataset (70%, 209 landslides) and a validation dataset (30%, 89 landslides) with ensured randomness, fairness, and symmetry of data segmentation. Sixteen landslide conditioning factors (altitude, profile curvature, plan curvature, slope aspect, slope angle, stream power index (SPI), topographical wetness index (TWI), sediment transport index (STI), distance to rivers, distance to roads, distance to faults, rainfall, NDVI, soil, land use, and lithology) were identified in the study area. Subsequently, the CDT, RBFN, and their ensembles with MultiBoosting (MCDT and MRBFN) were used in ArcGIS to generate the landslide susceptibility maps. The performances of the four landslide susceptibility maps were compared and verified based on the area under the curve (AUC). Finally, the verification results of the AUC evaluation show that the landslide susceptibility mapping generated by the MCDT model had the best performance.
Estimation for the Discretely Observed Cox–Ingersoll–Ross Model Driven by Small Symmetrical Stable Noises
Authors: Wei Chao
Published: February 2020

This paper is concerned with the least squares estimation of drift parameters for the Cox–Ingersoll–Ross (CIR) model driven by small symmetrical α-stable noises from discrete observations. The contrast function is introduced to obtain the explicit formula of the estimators and the error of estimation is given. The consistency and the rate of convergence of the estimators are proved. The asymptotic distribution of the estimators is studied as well. Finally, some numerical calculus examples and simulations are given.
Efficient and Simultaneous Chitosan-Mediated Removal of 11 Mycotoxins from Palm Kernel Cake
Authors: Abbasi Pirouz Atena , Selamat Jinap , Zafar Iqbal Shahzad , Iskandar Putra Samsudin Nik
Published: February 2020

Mycotoxins are an important class of pollutants that are toxic and hazardous to animal and human health. Consequently, various methods have been explored to abate their effects, among which adsorbent has found prominent application. Liquid chromatography tandem mass spectrometry (LC–MS/MS) has recently been applied for the concurrent evaluation of multiple mycotoxins. This study investigated the optimization of the simultaneous removal of mycotoxins in palm kernel cake (PKC) using chitosan. The removal of 11 mycotoxins such as aflatoxins (AFB1, AFB2, AFG1 and AFG2), ochratoxin A (OTA), zearalenone (ZEA), fumonisins (FB1 and FB2) and trichothecenes (deoxynivalenol (DON), HT-2 and T-2 toxin) from palm kernel cake (PKC) was studied. The effects of operating parameters such as pH (3–6), temperature (30–50 °C) and time (4–8 h) on the removal of the mycotoxins were investigated using response surface methodology (RSM). Response surface models obtained with R2 values ranging from 0.89–0.98 fitted well with the experimental data, except for the trichothecenes. The optimum point was obtained at pH 4, 8 h and 35 °C. The maximum removal achieved with chitosan for AFB1, AFB2, AFG1, AFG2, OTA, ZEA, FB1 and FB2 under the optimized conditions were 94.35, 45.90, 82.11, 84.29, 90.03, 51.30, 90.53 and 90.18%, respectively.
2-Phenylethyl Isothiocyanate Exerts Antifungal Activity against Alternaria alternata by Affecting Membrane Integrity and Mycotoxin Production
Authors: Zhang Miao , Li Yongcai , Bi Yang , Wang Tiaolan , Dong Yupeng , Yang Qian , Zhang Tingting
Published: February 2020

Black spot caused by Alternaria alternata is one of the important diseases of pear fruit during storage. Isothiocyanates are known as being strong antifungal compounds in vitro against different fungi. The aim of this study was to assess the antifungal effects of the volatile compound 2-phenylethyl isothiocyanate (2-PEITC) against A. alternata in vitro and in pear fruit, and to explore the underlying inhibitory mechanisms. The in vitro results showed that 2-PEITC significantly inhibited spore germination and mycelial growth of A. alternata—the inhibitory effects showed a dose-dependent pattern and the minimum inhibitory concentration (MIC) was 1.22 mM. The development of black spot rot on the pear fruit inoculated with A. alternata was also significantly decreased by 2-PEITC fumigation. At 1.22 mM concentration, the lesion diameter was only 39% of that in the control fruit at 7 days after inoculation. Further results of the leakage of electrolyte, increase of intracellular OD260, and propidium iodide (PI) staining proved that 2-PEITC broke cell membrane permeability of A. alternata. Moreover, 2-PEITC treatment significantly decreased alternariol (AOH), alternariolmonomethyl ether (AME), altenuene (ALT), and tentoxin (TEN) contents of A. alternata. Taken together, these data suggest that the mechanisms underlying the antifungal effect of 2-PEITC against A. alternata might be via reduction in toxin content and breakdown of cell membrane integrity.
Phytotoxic Metabolites Isolated from Neufusicoccum batangarum, the Causal Agent of the Scabby Canker of Cactus Pear (Opuntia ficus-indica L.)
Authors: Masi Marco , Aloi Francesco , Nocera Paola , Cacciola Santa Olga , Surico Giuseppe , Evidente Antonio
Published: February 2020

Six phytotoxins were obtained from the culture filtrates of the ascomycete Neofusicoccum batangarum, the causal agent of the scabby canker of cactus pear (Opuntia ficus-indica L.) in minor Sicily islands. The phytotoxins were identified as (−)-(R)-mellein (1); (±)-botryoisocoumarin A (2); (−)-(3R,4R)- and (−)-(3R,4S)-4-hydroxymellein (3 and 4); (−)-terpestacin (5); and (+)-3,4-dihydro-4,5,8-trihydroxy-3-methylisocoumarin, which we named (+)-neoisocoumarin (6). This identification was done by comparing their spectral and optical data with those already reported in literature. The absolute configuration (3R,4S) to (+)-neoisocoumarin (6) was determined using the advanced Mosher method. All six metabolites were shown to have phytotoxicity on the host (cactus pear) and non-host (tomato) plants, and the most active compounds were (±)-botryoisocoumarin A (2), (−)-terpestacin (5), and (+)-neoisocoumarin (6).
Efficacy and Safety of OnabotulinumtoxinA 400 Units in Patients with Post-Stroke Upper Limb Spasticity: Final Report of a Randomized, Double-Blind, Placebo-Controlled Trial with an Open-Label Extension Phase
Authors: Abo Masahiro , Shigematsu Takashi , Hara Hiroyoshi , Matsuda Yasuko , Nimura Akinori , Yamashita Yoshiyuki , Takahashi Kaoru
Published: February 2020

In many countries, 400 units (U) is the maximum dose of onabotulinumtoxinA available to treat upper limb spasticity, but few studies have demonstrated the optimal use of this dose. In the double-blind phase of this randomized, controlled trial, we compared the efficacy and safety of 400 vs. 240 U onabotulinumtoxinA in patients with post-stroke upper limb spasticity. Both groups received 240 U onabotulinumtoxinA injected in the forearm. An additional 160 U onabotulinumtoxinA (400 U group) or placebo (240 U group) was injected in the elbow flexors. Both groups showed similar muscle tone reduction in the wrist, fingers, and thumb; muscle tone reduction in the elbow flexors was greater in the group treated with onabotulinumtoxinA (400 U group) compared to placebo (240 U group). Functional disabilities improved in both groups. No substantial difference was found in safety profiles. In the subsequent open-label phase, all participants received repeat injections of 400 U onabotulinumtoxinA (target muscles and doses per muscle determined by the physician). Similar efficacy and safety outcomes, as with the 400 U group in the double-blind phase, were confirmed. This final report demonstrates that injection of onabotulinumtoxinA 400 U relieves muscle tone in a wide range of areas and improves functional disabilities; generally, it was well-tolerated, and no new safety concerns were identified. The dosing data in the open-label phase will inform optimal use of onabotulinumtoxinA in clinical practice (ClinicalTrials.gov: NCT03261167).
Interactions of Destruxin A with Silkworms’ Arginine tRNA Synthetase and Lamin-C Proteins
Authors: Wang Jingjing , Weng Qunfang , Yin Fei , Hu Qiongbo
Published: February 2020

Destruxin A (DA), a cyclodepsipeptidic mycotoxin produced by entomopathogenic fungus Metarhizium anisopliae, has good insecticidal activity and potential to be a new pesticide. However, the mechanism of action is still obscure. Our previous experiments showed that DA was involved in regulation of transcription and protein synthesis and suggested that silkworms’ arginine tRNA synthetase (BmArgRS), Lamin-C Proteins (BmLamin-C) and ATP-dependent RNA helicase PRP1 (BmPRP1) were candidates of DA-binding proteins. In this study, we employed bio-layer interferometry (BLI), circular dichroism (CD), cellular thermal shift assay (CETSA), and other technologies to verify the interaction of DA with above three proteins in vitro and in vivo. The results of BLI indicated that BmArgRS and BmLamin-C were binding-protein of DA with KD value 5.53 × 10−5 and 8.64 × 10−5 M, but not BmPRP1. These interactions were also verified by CD and CETSA tests. In addition, docking model and mutants assay in vitro showed that BmArgRS interacts with DA at the pocket including Lys228, His231, Asp434 and Gln437 in its enzyme active catalysis region, while BmLamin-C binds to DA at His524 and Lys528 in the tail domain. This study might provide new insight and evidence in illustrating molecular mechanism of DA in breaking insect.
Effect of Ozone and Electron Beam Irradiation on Degradation of Zearalenone and Ochratoxin A
Authors: Yang Kai , Li Ke , Pan Lihong , Luo Xiaohu , Xing Jiali , Wang Jing , Wang Li , Wang Ren , Zhai Yuheng , Chen Zhengxing
Published: February 2020

Zearalenone (ZEN) and ochratoxin A (OTA) are key concerns of the food industry because of their toxicity and pollution scope. This study investigated the effects of ozone and electron beam irradiation (EBI) on the degradation of ZEN and OTA. Results demonstrated that 2 mL of 50 μg/mL ZEN was completely degraded after 10 s of treatment by 2.0 mg/L ozone. The degradation rate of 1 μg/mL ZEN by 16 kGy EBI was 92.76%. Methanol was superior to acetonitrile in terms of degrading ZEN when the irradiation dose was higher than 6 kGy. The degradation rate of 2 mL of 5 μg/mL OTA by 50 mg/L ozone at 180 s was 34%, and that of 1 μg/mL OTA by 16 kGy EBI exceeded 90%. Moreover, OTA degraded more rapidly in acetonitrile. Ozone performed better in the degradation of ZEN, whereas EBI was better for OTA. The conclusions provide theoretical and practical bases for the degradation of different fungal toxins.
Should We Consider the Cardiovascular System While Evaluating CKD-MBD?
Authors: Rroji Merita , Figurek Andreja , Spasovski Goce
Published: February 2020

Cardiovascular (CV) disease is highly prevalent in the population with chronic kidney disease (CKD), where the risk of CV death in early stages far exceeds the risk of progression to dialysis. The presence of chronic kidney disease-mineral and bone disorder (CKD-MBD) has shown a strong correlation with CV events and mortality. As a non-atheromatous process, it could be partially explained why standard CV disease-modifying drugs do not provide such an impact on CV mortality in CKD as observed in the general population. We summarize the potential association of CV comorbidities with the older (parathyroid hormone, phosphate) and newer (FGF23, Klotho, sclerostin) CKD-MBD biomarkers.
Human Tibroviruses: Commensals or Lethal Pathogens?
Authors: Kuhn Jens H. , Pān Hào , Chiu Charles Y. , Stremlau Matthew
Published: February 2020

Rhabdoviruses are a large and ecologically diverse family of negative-sense RNA viruses (Mononegavirales: Rhabdoviridae). These viruses are capable of infecting an unexpectedly wide variety of plants, vertebrates, and invertebrates distributed over all human-inhabited continents. However, only a few rhabdoviruses are known to infect humans: a ledantevirus (Le Dantec virus), several lyssaviruses (in particular, rabies virus), and several vesiculoviruses (e.g., Chandipura virus, vesicular stomatitis Indiana virus). Recently, several novel rhabdoviruses have been discovered in the blood of both healthy and severely ill individuals living in Central and Western Africa. These viruses—Bas-Congo virus, Ekpoma virus 1, and Ekpoma virus 2—are members of the little-understood rhabdoviral genus Tibrovirus. Other than the basic genomic architecture, tibroviruses bear little resemblance to well-studied rhabdoviruses such as rabies virus and vesicular stomatitis Indiana virus. These three human tibroviruses are quite divergent from each other, and each of them clusters closely with tibroviruses currently known only from biting midges or healthy cattle. Seroprevalence studies suggest that human tibrovirus infections may be common but are almost entirely unrecognized. The pathogenic potential of this diverse group of viruses remains unknown. Although certain tibroviruses may be benign and well-adapted to humans, others could be newly emerging and produce serious disease. Here, we review the current knowledge of tibroviruses and argue that assessing their impact on human health should be an urgent priority.
Evaluation of Hydromulches as an Erosion Control Measure Using Laboratory-Scale Experiments
Authors: Ricks Matthew D. , Wilson Wesley T. , Zech Wesley C. , Fang Xing , Donald Wesley N.
Published: February 2020

Discharge of sediment-laden stormwater from active construction sites, such as highway construction projects, continues to be a growing concern in the construction industry. Therefore, there has been an increased interest in research efforts to test many different erosion and sediment control practices. The purpose of this research effort was to test the laboratory-scale performance of four hydromulches and two methods of mulching (crimped and tackified), normalized to a bare soil control condition using 0.6 m (2 ft) wide by 1.2 m (4 ft) long test plots. The treatments consisted of a (1) bare soil control, (2) conventional straw, crimped, (3) conventional straw, tackified, (4) wood fiber hydromulch, (5) straw and cotton hydromulch, (6) cotton fiber reinforced matrix hydromulch, and (7) bonded wheat fiber matrix hydromulch. Each treatment was subject to simulated rainfall, divided into four 15 min rainfall events with 15 min breaks in between, producing a total cumulative rainfall of 11.2 cm (4.4 in.). To determine the overall performance of each treatment, turbidity and soil loss measurements were continuously collected from plot runoff. The products tested provided a reduction in turbidity of 80%, 98%, 85%, 92%, 95%, and 99%; and a soil loss reduction of 96%, 98%, 94%, 97%, 99%, and 100%, respectively. Overall, the results showed that the four tested hydromulch practices and conventional straw applications were successful in controlling and reducing erosion under laboratory-scale simulated rainfall conditions.
Effect of Seasonality on the Quantiles Estimation of Maximum Floodwater Levels in a Reservoir and Maximum Outflows
Authors: Aranda José , García-Bartual R.
Published: February 2020

Certain relevant variables for dam safety and downstream safety assessments are analyzed using a stochastic approach. In particular, a method to estimate quantiles of maximum outflow in a dam spillway and maximum water level reached in the reservoir during a flood event is presented. The hydrological system analyzed herein is a small mountain catchment in north Spain, whose main river is a tributary of Ebro river. The ancient Foradada dam is located in this catchment. This dam has no gates, so that flood routing operation results from simple consideration of fixed crest spillway hydraulics. In such case, both mentioned variables (maximum outflow and maximum reservoir water level) are basically derived variables that depend on flood hydrograph characteristics and the reservoir’s initial water level. A Monte Carlo approach is performed to generate very large samples of synthetic hydrographs and previous reservoir levels. The use of extreme value copulas allows the ensembles to preserve statistical properties of historical samples and the observed empirical correlations. Apart from the classical approach based on annual periods, the modelling strategy is also applied differentiating two subperiods or seasons (i.e., summer and winter). This allows to quantify the return period distortion introduced when seasonality is ignored in the statistical analysis of the two relevant variables selected for hydrological risk assessment. Results indicate significant deviations for return periods over 125 years. For the analyzed case study, ignoring seasonal statistics and trends, yields to maximum outflows underestimation of 18% for T = 500 years and 29% for T = 1000 years were obtained.