bluuebunny/crossref_metadata_2025 huggingface dataset:
The Arabidopsis Protein Disulfide Isomerase Subfamily M Isoform, PDI9, Localizes to the Endoplasmic Reticulum and Influences Pollen Viability and Proper Formation of the Pollen Exine During Heat Stress
Authors: Feldeverd Elizabeth , Porter Brad W. , Yuen Christen Y. L. , Iwai Kaela , Carrillo Rina , Smith Tyler , Barela Cheyenne , Wong Katherine , Wang Pengfei , Kang Byung-Ho , Matsumoto Kristie , Christopher David A.
Published: December 2020

Plants adapt to heatviathermotolerance pathways in which the activation of protein folding chaperones is essential. In eukaryotes, protein disulfide isomerases (PDIs) facilitate the folding of nascent and misfolded proteins in the secretory pathway by catalyzing the formation and isomerization of disulfide bonds and serving as molecular chaperones. In Arabidopsis, several members of the PDI family are upregulated in response to chemical inducers of the unfolded protein response (UPR), including both members of the non-classical PDI-M subfamily, PDI9 and PDI10. Unlike classical PDIs, which have two catalytic thioredoxin (TRX) domains separated by two non-catalytic TRX-fold domains, PDI-M isoforms are orthologs of mammalian P5/PDIA6 and possess two tandem catalytic domains. Here, PDI9 accumulation was found to be upregulated in pollen in response to heat stress. Histochemical staining of plants harboring thePDI9andPDI10promoters fused to thegusAgene indicated they were actively expressed in the anthers of flowers, specifically in the pollen and tapetum. Immunoelectron microscopy revealed that PDI9 localized to the endoplasmic reticulum in root and pollen cells. transfer DNA (T-DNA) insertional mutations in thePDI9gene disrupted pollen viability and development in plants exposed to heat stress. In particular, the pollen grains ofpdi9mutants exhibited disruptions in the reticulated pattern of the exine and an increased adhesion of pollen grains. Pollen in thepdi10single mutant did not display similar heat-associated defects, butpdi9 pdi10double mutants (DMs) completely lost exine reticulation. Interestingly, overexpression ofPDI9partially led to heat-associated defects in the exine. We conclude that PDI9 plays an important role in pollen thermotolerance and exine biogenesis. Its role fits the mechanistic theory of proteostasis in which an ideal balance of PDI isoforms is required in the endoplasmic reticulum (ER) for normal exine formation in plants subjected to heat stress.
Benevolent Creativity Buffers Anxiety Aroused by Mortality Salience: Terror Management in COVID-19 Pandemic
Authors: Cui Yu-Xin , Zhou Xiang , Zu Chong , Zhai Hong-Kun , Bai Bo-Ren , Xu Yu-Mei , Li Duo
Published: December 2020

With the outbreak of the COVID-19 crisis, the public keeps getting epidemic-related information on the media. News reports on the increasing number of fatalities have exposed individuals to death, which causes negative emotional experiences such as tension, anxiety, and fear. This study aimed to investigate whether creativity could serve as an anxiety-buffer when mortality is salient. Based on previous findings, the present study utilized type of creative task and personal search for meaning as moderators. In Study 1, a 2 (mortality salience: absent, present) × 2 (type of creative task: benevolent, malevolent) between-subject design was utilized, and 168 subjects were randomly assigned to four experimental conditions. In Study 2, 221 subjects were recruited. The experimental procedure was similar to Study 1, except that the priming paradigm of mortality was changed and search for meaning was included as an additional moderating variable. State anxiety was measured as the dependent variable in both studies. Results of Study 1 showed that, while the benevolent creative task could buffer anxiety in the mortality salience condition, the malevolent creative task did not have the same effect. Furthermore, there was a significant interaction between mortality salience, type of creative task, and search for meaning in life on anxiety. In Study 2, the buffering function of benevolent creativity was more intense for participants with a higher level of search for meaning. Together, these findings reveal the influence of different types of creative tasks on individual anxiety levels under death priming conditions and the moderating effect of search for meaning in this relationship. Further, they suggest the need to focus on the role of creativity in terror management.
Field Performance and Genetic Stability of Micropropagated Gooseberry Plants (Ribes grossularia L.)
Authors: Wójcik Danuta , Trzewik Aleksandra , Kucharska Danuta
Published: December 2020

Gooseberry (Ribes grossularia L.) is a small fruit crop producing valuable fruits, which is constantly gaining importance. In vitro propagation of this species can significantly support the production of virus-free planting material and accelerate the introduction of new cultivars to the market. The aim of presented study was to assess field performance and genetic stability of micropropagated plants (MPs) of four gooseberry cultivars, “Captivator”, “Hinnonmaki Rot”, “Invicta”, and “Resika”. The growth vigor and yield of MPs and plants propagated by standard methods from softwood cuttings (ST) were evaluated in a field experiment. Microscopic observations of the number and length of the stomata of MP and ST plants were carried out. Two DNA-based techniques, amplified fragment length polymorphism (AFLP) and inter simple sequence repeat (ISSR), were used to assess genetic stability of MP plants. For analysis of genetic stability of ST plants, the ISSR technique was applied. For three cultivars, Captivator, Hinnonmaki Rot, and Invicta, the plants’ growth vigor and fruit yield were greater in MP plants than in ST plants. In the case of Resika, most of these parameters were higher in ST plants. Microscopic observations of the stomata indicated a lack of differences in the length between MP and ST plants, while the stomata frequency on leaves of MP plants was higher than that of ST plants. The genetic variability of MP plants, assessed by AFLP, ranged from 0.35% for Hinnonmaki Rot to 2.12% for Resika. The results of ISSR analysis of MP plants showed variability from 0% in the case of Hinnonmaki Rot and Resika to 4% and 8.69% for Captivator and Invicta, respectively. No polymorphism was detected among ST plants of all analyzed gooseberry cultivars.
Fertilizer Application Levels in Potato Crops and the Diagnosis and Recommendation Integrated System (DRIS)
Authors: Oliveira Roberta Camargos , da Silva João Ricardo Rodrigues , Lana Regina Maria Quintão , de Azevedo Pereira Alexandre Igor , Castoldi Renata , de Camargo Reginaldo , Luz José Magno Queiroz
Published: December 2020

The rates of nitrogen, phosphorus, and potassium fertilizers used in the cultivation of potatoes are often considered excessive, as they can cause imbalance among the essential elements present in the soil. Using leaf nutrient analysis, this study aimed to evaluate the productivity of potato tubers subjected to different rates of nitrogen (N), phosphorus (P), and potassium (K) to establish the diagnosis and recommendation integrated system indices. Three experiments were conducted, one for each nutrient (N, P, and K), with Agata and Atlantic cultivars in Unaí (Minas Gerais state) and the Agata cultivar in Mucugê (Bahia state). The nutrient rates were 0, 30, 70, 120, and 280 kg ha−1 of N; 0, 150, 300, 600, and 900 kg ha−1 of P2O5; and 0, 70, 110, 220, and 450 kg ha−1 of K2O. Agata and Atlantic had adequate nutritional balance under K application. Agata had a more adequate nutritional balance under P application in Mucugê, whereas K fertilization was more decisive for the nutritional balance in Unaí. The differences in the results can be explained by the different soil textures and nutrients in the soil between the regions. The results show the need to consider the soil conditions and the nutrient uptake/translocation capacity of cultivars before establishing rates to increase production revenue and avoid the waste of fertilizers.
N-Use Efficiency and Yield of Cotton (G. hirsutumn L.) Are Improved through the Combination of N-Fertilizer Reduction and N-Efficient Cultivar
Authors: Niu Jing , Gui Huiping , Iqbal Asif , Zhang Hengheng , Dong Qiang , Pang Nianchang , Wang Sujie , Wang Zhun , Wang Xiangru , Yang Guozheng , Song Meizhen
Published: December 2020

Nitrogen (N) fertilizer plays a vital role in increasing cotton yield, but its excessive application leads to lower yield, lower nitrogen use efficiency (NUE), and environmental pollution. The main objective of this study was to find an effective method to enhance the NUE in cotton production. A two-year field experiment was conducted by using a split plot design with N rates (N0, 0 kg N ha−1; N1, 112.5 kg N ha−1; N2, 225 kg N ha−1, N3, 337.5 kg N ha−1), and cotton cultivars (CRI 69; ZZM 1017; ZZM GD89 and XLZ 30) to evaluate both their individual effect and their interactions on cotton yield and NUE. The results showed that the biomass and N accumulation of four cultivars increased with an increase in N rate, whereas the NUE decreased. Cotton yield increased first and then decreased for CRI 69 and ZZM 1017, while kept increasing from N0 to N3 for ZZM GD89 and XLZ 30. Compared with ZZM GD89 and XLZ 30, CRI 69, and ZZM 1017 showed higher yield, resulted from higher biomass, bolls per plant, and boll weight, especially under low N level. In addition, the CRI 69 and ZZM 1017 had stronger N absorption and transformation capabilities, and showed higher NUE than those of ZZM GD89 and XLZ 30 under the same N rate. The results indicated that CRI 69 and ZZM 1017 show advantages over ZZM GD89 and XLZ 30 in yield, and NUE, especially under low N rate.
Introgression of Resistance to Leafminer (Liriomyza cicerina Rondani) from Cicer reticulatum Ladiz. to C. arietinum L. and Relationships between Potential Biochemical Selection Criteria
Authors: Chrigui Nesrine , Sari Duygu , Sari Hatice , Eker Tuba , Cengiz Mehmet Fatih , Ikten Cengiz , Toker Cengiz
Published: December 2020

The chickpea leafminer, Liriomyza cicerina (Rondani), is one of the most destructive insect pests of cultivated chickpea (Cicer arietinum L.) in the Mediterranean region under field conditions. For sustainable and environmentally friendly chickpea production, efforts have been devoted to managing the leafminer via decreasing the use of insecticides. Breeding of new resistant varieties is not only an efficient and practical approach, but also cost-effective and environmentally sensitive. To improve resistant varieties, breeders need reliable biochemical selection criteria that can be used in breeding programs. The first objective was to investigate the possible introgression of resistance to the leafminer from C. reticulatum Ladiz. (resistant) to C. arietinum (susceptible), then, to estimate inheritance of resistance to the leafminer for efficient breeding strategies, and finally, to study organic acid contents as selection criteria. Recombinant inbred lines (RILs) and their parents were evaluated using a visual scale of 1–9 (1 = free from leafminer damage and 9 = mines in more than 91% of the leaflets and defoliation greater than 31%) in the field under natural infestation conditions after the susceptible parent and check had scores of >7 on the visual scale. Superior RILs were found for resistance to the leafminer, and agro-morphological traits indicating that introgression of resistance to leaf miner from C. reticulatum to C. arietinum could be possible using interspecific crosses. The inheritance pattern of resistance to the leafminer in RILs was shown to be quantitative. Organic acids, including oxalic, malic, quinic, tartaric, citric and succinic acids in RILs grown in the field under insect epidemic conditions and in the greenhouse under non-infested conditions were detected by using high performance liquid chromatography (HPLC). In general, organic acids were found to be higher in resistant RILs than susceptible RILs. Path and correlation coefficients showed that succinic acid exhibited the highest direct effects on resistance to the leafminer. Multivariate analyses, including path, correlation and factor analyses suggested that a high level of succinic acid could be used as a potential biochemical selection criterion for resistance to leafminer in chickpea. Resistant RILs with a high seed yield resembling kabuli chickpea can be grown directly in the target environments under leaf miner infestation conditions.
Phenylalanine and Tyrosine as Feed Additives for Reducing Stress and Enhancing Welfare in Gilthead Seabream and Meagre
Authors: Salamanca Natalia , Giráldez Inmaculada , Morales Emilio , de La Rosa Ignacio , Herrera Marcelino
Published: December 2020

Increased aquaculture production is associated with a growing interest in improving fish welfare. For this reason, the search for strategies to mitigate stress has intensified, one of these strategies being food supplementation with amino acids. The objective of this study was to evaluate the effects of dietary phenylalanine (Phe) and Tyrosine (Tyr) on the stress response and metabolism of juvenile gilthead seabreams (Sparus aurata) and meagres (Argyrosomus regius). Fish batches were fed a control diet and two diets supplemented with 5% Phe or Tyr for seven days. At the end of the experiment fish were stressed by air exposure for 3 min and then sacrificed for the extraction of blood and brain. Classical plasma stress markers were analyzed (glucose, lactate, proteins, cortisol), as well as hormones derived from those amino acids (adrenaline, noradrenaline and dopamine). Despite interspecific differences, fish fed the diets supplemented with Phe or Tyr showed a reduction on several stress markers. However, interspecific differences were detected for many indicators. Concretely, hormonal stress markers were significantly attenuated in meagres fed the enriched diets. Moreover, the stress condition favored a mobilization of amino acids towards the brain, especially in supplemented diets, hence this amino acid excess could be used as an energy substrate to cope with stress.
Omics Insights into Animal Resilience and Stress Factors
Authors: Basile Federica , Capaccia Camilla , Zampini Danilo , Biagetti Tommaso , Diverio Silvana , Guelfi Gabriella
Published: December 2020

Resilience is conceived as a dynamic developmental process involving the achievement of positive adaptation within the context of significant adversity. Resilience is not a unique ability but rather a set of capacities of a system put in place to absorb a disturbance and to reorganize while trying to retain the same function, structure, and identity. This review describes the characteristics and the molecular mechanisms of resilience to understand the core elements of resilience and its indicators. The objectives of this review are: (1) to define some of the leading environmental stressors and clarify the mechanism of vulnerability or resilience outcomes; (2) to clarify some of the prominent epigenetic modulations mediating resilience or vulnerability as a stress response; (3) to highlight the neural mechanisms related to stress resilience since the central nervous system is a highly dynamic structure characterized by an everlasting plasticity feature, which therefore has the opportunity to modify resilience. The review aims to introduce the reader to the concept of resilience seen as an ability acquired in life and not only inherited from birth.
Determination of Body Parts in Holstein Friesian Cows Comparing Neural Networks and k Nearest Neighbour Classification
Authors: Salau Jennifer , Haas Jan Henning , Junge Wolfgang , Thaller Georg
Published: December 2020

Machine learning methods have become increasingly important in animal science, and the success of an automated application using machine learning often depends on the right choice of method for the respective problem and data set. The recognition of objects in 3D data is still a widely studied topic and especially challenging when it comes to the partition of objects into predefined segments. In this study, two machine learning approaches were utilized for the recognition of body parts of dairy cows from 3D point clouds, i.e., sets of data points in space. The low cost off-the-shelf depth sensor Microsoft Kinect V1 has been used in various studies related to dairy cows. The 3D data were gathered from a multi-Kinect recording unit which was designed to record Holstein Friesian cows from both sides in free walking from three different camera positions. For the determination of the body parts head, rump, back, legs and udder, five properties of the pixels in the depth maps (row index, column index, depth value, variance, mean curvature) were used as features in the training data set. For each camera positions, a k nearest neighbour classifier and a neural network were trained and compared afterwards. Both methods showed small Hamming losses (between 0.007 and 0.027 for k nearest neighbour (kNN) classification and between 0.045 and 0.079 for neural networks) and could be considered successful regarding the classification of pixel to body parts. However, the kNN classifier was superior, reaching overall accuracies 0.888 to 0.976 varying with the camera position. Precision and recall values associated with individual body parts ranged from 0.84 to 1 and from 0.83 to 1, respectively. Once trained, kNN classification is at runtime prone to higher costs in terms of computational time and memory compared to the neural networks. The cost vs. accuracy ratio for each methodology needs to be taken into account in the decision of which method should be implemented in the application.
Crosstalk between Long-Term Sublethal Oxidative Stress and Detrimental Inflammation as Potential Drivers for Age-Related Retinal Degeneration
Authors: Macchioni Lara , Chiasserini Davide , Mezzasoma Letizia , Davidescu Magdalena , Orvietani Pier Luigi , Fettucciari Katia , Salviati Leonardo , Cellini Barbara , Bellezza Ilaria
Published: December 2020

Age-related retinal degenerations, including age-related macular degeneration (AMD), are caused by the loss of retinal pigmented epithelial (RPE) cells and photoreceptors. The pathogenesis of AMD, deeply linked to the aging process, also involves oxidative stress and inflammatory responses. However, the molecular mechanisms contributing to the shift from healthy aging to AMD are still poorly understood. Since RPE cells in the retina are chronically exposed to a pro-oxidant microenvironment throughout life, we simulated in vivo conditions by growing ARPE-19 cells in the presence of 10 μM H2O2 for several passages. This long-term oxidative insult induced senescence in ARPE-19 cells without affecting cell proliferation. Global proteomic analysis revealed a dysregulated expression in proteins involved in antioxidant response, mitochondrial homeostasis, and extracellular matrix organization. The analyses of mitochondrial functionality showed increased mitochondrial biogenesis and ATP generation and improved response to oxidative stress. The latter, however, was linked to nuclear factor-κB (NF-κB) rather than nuclear factor erythroid 2–related factor 2 (Nrf2) activation. NF-κB hyperactivation also resulted in increased pro-inflammatory cytokines expression and inflammasome activation. Moreover, in response to additional pro-inflammatory insults, senescent ARPE-19 cells underwent an exaggerated inflammatory reaction. Our results indicate senescence as an important link between chronic oxidative insult and detrimental chronic inflammation, with possible future repercussions for therapeutic interventions.
A Directly Modulated Laterally Coupled Distributed Feedback Laser Array Based on SiO2 Planarization Process
Authors: Wang Qichao , Wang Jian , Sun Changzheng , Xiong Bing , Luo Yi , Hao Zhibiao , Han Yanjun , Wang Lai , Li Hongtao , Yu Jiadong
Published: December 2020

Low-cost and high-speed single-mode semiconductor lasers are increasingly required as wide-band access fiber communication expands in recent years. Here, a high-speed laterally coupled distributed feedback (LC-DFB) laser array is achieved based on a SiO2 planarization process. The device exhibits low threshold currents of about 12 mA and high slope efficiencies over 0.26 W/A. Stable single mode operation and high-speed performance are realized with side mode suppression ratios (SMSR) over 45 dB, and 3-dBe bandwidths exceed 14 GHz for all four channels. Such a high-speed and process simple LC-DFB laser array shows great potential to the low-cost fiber communication networks.
Numerical Investigations on the Shape Optimization of Stainless-Steel Ring Joint with Machine Learning
Authors: Kim Minsoo , Yi Sarang , Hong Seokmoo
Published: December 2020

Since pipes used for water pipes are thin and difficult to fasten using welding or screws, they are fastened by a crimping joint method using a metal ring and a rubber ring. In the conventional crimping joint method, the metal ring and the rubber ring are arranged side by side. However, if water leaks from the rubber ring, there is a problem that the adjacent metal ring is rapidly corroded. In this study, to delay and minimize the corrosion of connected water pipes, we propose a spaced crimping joint method in which metal rings and rubber rings are separated at appropriate intervals. This not only improves the contact performance between the connected water pipes but also minimizes the load applied to the crimping jig during crimping to prevent damage to the jig. For this, finite element analyses were performed for the crimp tool and process analysis, and the design parameters were set as the curling length at the top of the joint, the distance between the metal rings and rubber rings, and the crimp jig radius. Through FEA of 100 cases, data to be trained in machine learning were acquired. After that, training data were trained on a machine learning model and compared with a regression model to verify the model’s performance. If the number of training data is small, the two methods are similar. However, the greater the number of training data, the higher the accuracy predicted by the machine learning model. Finally, the spaced crimping joint to which the derived optimal shape was applied was manufactured, and the maximum pressure and pressure distribution applied during compression were obtained using a pressure film. This is almost similar to the value obtained by finite element analysis under the same conditions, and through this, the validity of the approach proposed in this study was verified.
6D Pose Estimation of Objects: Recent Technologies and Challenges
Authors: He Zaixing , Feng Wuxi , Zhao Xinyue , Lv Yongfeng
Published: December 2020

6D pose estimation is a common and important task in industry. Obtaining the 6D pose of objects is the basis for many other functions such as bin picking, autopilot, etc. Therefore, many corresponding studies have been made in order to improve the accuracy and enlarge the range of application of various approaches. After several years of development, the methods of 6D pose estimation have been enriched and improved. Although some predecessors have analyzed the methods and summarized them in detailed, there have been many new breakthroughs in recent years. To understand 6D pose estimation better, this paper will make a new and more detailed review of 6D pose estimation. We divided these methods into two approaches: Learning-based approaches and non-learning-based approaches, including 2D-information-based approach and 3D-information-based approach. Additionally, we introduce the challenges that exist in 6D pose estimation. Finally, we compare the performance of different methods qualitatively and discuss the future development trends of the 6D pose estimation.
Preventive Control Policy Construction in Active Distribution Network of Cyber-Physical System with Reinforcement Learning
Authors: Sun Pengpeng , Dong Yunwei , Yuan Sen , Wang Chong
Published: December 2020

Once an active distribution network of a cyber-physical system is in alert state, it is vulnerable to cross-domain cascading failures. It is necessary to transit the state of an active distribution network of cyber-physical system from an alert state to a normal state using a preventive control policy against cross-domain cascading failures. In fact, it is difficult to construct and analyze a preventive control policy via theoretical analysis methods or physical experimental methods. The theoretical analysis methods may not be accurate due to approximated models, and the physical experimental methods are expensive and time consuming for building prototypes. This paper presents a preventive control policy construction method based on a deep deterministic policy gradient idea (shorted as PCMD) to generate and optimize a preventive control policy with Artificial Intelligence (AI) technologies. It adopts the reinforcement learning technique to make full use of the available historical data to overcome the problems of high cost and low accuracy. Firstly, a preventive control model is designed based on the finite automaton theory, which can guide the data collection and learning policy selection. The control model considers the voltage stability, frequency stability, current overload prevention, and the control cost reduction as a feedback variable, without the specific power flow equations and differential equations. Then, after enough training, a local optimal preventive control policy can be constructed under the comparability condition among a fitted action-value function and a fitted policy function. The constructed preventive control policy contains some control actions to achieve a low cost and in accord with the principle of shortening a cross-domain cascading failures propagation sequence as far as possible. The PCMD is more flexible and closer to reality than the theoretical analysis methods and has a lower cost than the physical experimental methods. To evaluate the performance of the proposed method, an experimental case study, China Electric Power Research-Cyber-Physical System (shorted as CEPR-CPS), which comes from China Electric Power Research Institute, is carried out. The result shows that the effectiveness of preventive control policy construction with the PCMD is better than most current methods, such as the multi-agent method in terms of reducing the number of failure nodes and avoiding the state space explosion.
Modification of Olive Leaves’ Surface by Ultrasound Cavitation. Correlation with Polyphenol Extraction Enhancement
Authors: Rombaut Natacha , Chave Tony , Nikitenko Sergey I. , Maâtaoui Mohamed El , Fabiano-Tixier Anne Sylvie , Chemat Farid
Published: December 2020

We investigated the impact of ultrasound at 20 kHz on olive leaves to understand how acoustic cavitation could increase polyphenol extraction. Application of ultrasound to whole leaf from 5 to 60 min enabled us to increase extraction from 6.96 to 48.75 µg eq. oleuropein/mL of extract. These results were correlated with Environmental Scanning Electron Microscopy, allowing for leaf surface observation and optical microscopy of treated leaf cross sections to understand histochemical modifications. Our observations suggest that the effectiveness of ultrasound applied to extraction is highly dependent on plant structure and on how this material will react when subjected to acoustic cavitation. Ultrasound seems to impact the leaves by two mechanisms: cuticle erosion, and fragmentation of olive leaf surface protrusions (hairs), which are both polyphenol-rich structures.
Study and Verification of a New Method to Test the Bonding Ability between Basalt Fiber and Asphalt Mortar
Authors: Wu Xing , Wu Zhengguang , Kang Aihong , Xiao Peng , Wu Bangwei
Published: December 2020

The bonding ability between basalt fiber bundle and asphalt mortar has a great influence on the properties of basalt fiber reinforced asphalt mixtures, yet the studies about the bonding between them is very limited. In this paper, a new test instrument called fiber-asphalt pulling machine and a new index called the nominal bonding stress (NBS) were designed and adopted to test and reveal the bonding between basalt fiber bundle and asphalt mortar. The procedures and rationality analysis of this new experiment was specified in this paper. In order to verify the reliability of the NBS index, the NBS values derived from this new test method and the rheological property indexes values of asphalt mortar under different powder–cement ratios were adopted to analyze the correlation between them. Two kinds of basalt fibers produced by two different manufacturers were adopted to conduct the parallel experiment. The results show that the nominal bonding stress between basalt fiber and asphalt mortar derived from this new test has a great correlation with the rheological properties of asphalt mortar, which also proves the credibility of this new test method and the NBS index.
Smooth Design of 3D Self-Supporting Topologies Using Additive Manufacturing Filter and SEMDOT
Authors: Fu Yun-Fei , Ghabraie Kazem , Rolfe Bernard , Wang Yanan , Chiu Louis N. S.
Published: December 2020

The smooth design of self-supporting topologies has attracted great attention in the design for additive manufacturing (DfAM) field as it cannot only enhance the manufacturability of optimized designs but can obtain light-weight designs that satisfy specific performance requirements. This paper integrates Langelaar’s AM filter into the Smooth-Edged Material Distribution for Optimizing Topology (SEMDOT) algorithm—a new element-based topology optimization method capable of forming smooth boundaries—to obtain print-ready designs without introducing post-processing methods for smoothing boundaries before fabrication and adding extra support structures during fabrication. The effects of different build orientations and critical overhang angles on self-supporting topologies are demonstrated by solving several compliance minimization (stiffness maximization) problems. In addition, a typical compliant mechanism design problem—the force inverter design—is solved to further demonstrate the effectiveness of the combination between SEMDOT and Langelaar’s AM filter.
Validation of EMT Digital Twin Models for Dynamic Voltage Performance Assessment of 66 kV Offshore Transmission Network
Authors: Ganesh Saran , Perilla Arcadio , Torres Jose Rueda , Palensky Peter , van der Meijden Mart
Published: December 2020

The increase in Power Electronic (PE) converters due to the increase in offshore wind energy deployment have given rise to technical challenges (e.g., due to unprecedented fast dynamic phenomena) related to voltage and frequency stability in the power system. In the Offshore Wind Farms (OWFs), the currently available current injection-based voltage control for PE converters are not suitable for voltage control in PE dominated systems due to the absence of continuous voltage control and ineffectiveness during islanding. Moreover, in such power systems, the conventional controllers are not suitable for frequency control due to the absence of dynamic frequency control. The paper presents the Direct Voltage Control (DVC) strategy in a real-time environment to mitigate challenges related to voltage and frequency stability during islanding of OWFs. The control strategy is implemented in the average Electro-magnetic Transient (EMT) model of Type-4 Wind Generator (WG) in RSCAD® Version 5.011.1. It is compared with the benchmark model of the control strategy in DIgSILENT PowerFactoryTM 2019 SP2 (×64) in EMT platform. The comparison based on short-term voltage stability and reactive current injection reveals that both the models provide similar results, confirming the validation of the RSCAD model. Moreover, the detailed representation of the converters in the RSCAD model provides a better depiction of the real-world operation.
Renewable Energy Tracking and Optimization in a Hybrid Electric Vehicle Charging Station
Authors: Petrusic Andrija , Janjic Aleksandar
Published: December 2020

The increasing electric vehicle fleet requires an upgrade and expansion of the available charging infrastructure. The uncontrolled charging cycles greatly affect the electric grid, and for this reason, renewable energy sources and battery storage are getting incorporated into a hybrid charging station solution. Adding a renewable source and a battery to the charging station can help to “buffer” the power required from the grid, thus avoiding peaks and related grid constraints. To date, the origin of the energy coming from the battery has not been traced. In this paper, a solution of the hybrid electric vehicle charging station coupled with the small-scale photovoltaic system and battery energy storage is proposed to eliminate the adverse effects of uncontrolled electric vehicle charging, with the exact calculation of renewable energy share coming from energy stored in the battery. The methodology for the multicriteria optimization of the charging/discharging schedule of a battery and electric vehicle charging level is based on multi-attribute utility theory. The optimization criteria include the minimization of charging costs, maximization of renewable energy (from both the solar plant and the battery), and the minimization of battery degradation. The problem is solved using a genetic algorithm optimization procedure adapted to the multicriteria optimization function. The methodology is tested on an illustrative example, and it is proven that the decision-maker’s preferences greatly affects the choice of the optimal strategy and the optimal battery capacity.
Insight into Tar Formation Mechanism during Catalytic Pyrolysis of Biomass over Waste Aluminum Dross
Authors: Liu Peng , Liu Li , Zhou Zhengzhong , Yuan Haoran , Zheng Tao , Wu Qigang , Taoli Huhe
Published: December 2020

Tar is one of major products from biomass pyrolysis. Its formation mechanism in a catalytic pyrolysis system comprising pine sawdust and waste aluminum dross (AD) is investigated with the aid of analytical methods including thermogravimetric analysis (TG), Nuclear Magnetic Resonance (NMR), electron paramagnetic resonance (EPR), and gas chromatography coupling with mass spectrometry (GC-MS). The results show that AD plays a vital role in cleavage of C-O bonds to enhance selective formation of furans, ketones, and phenols. The catalytic pyrolysis is initiated by active C-O-M intermediate formation that accelerates C-O bond cleavage and generates great amounts of free radicals to 1020 spins/g at 300–500 °C. Compared with pure pine pyrolysis, the percentage of glucosidic bonds from cellulose decreases from 14.00% to 9.66% at 500 °C; the etherified guaiacyl is more actively ruptured and disappears at 700 °C. Furans and ketones increase from 17.45% to 22.23% and 6.71% to 10.80% at 500 °C, respectively. Phenols increase from 66.75% to 71.57%. The preferential production of higher value-added products via catalytic pyrolysis between biomass and industrial wastes may bring new insight to the simultaneous valorization of agricultural, municipal, and industrial waste.
DASH Live Broadcast Traffic Model: A Time-Bound Delay Model for IP-Based Digital Terrestrial Broadcasting Systems
Authors: Seo Hyungyoon , Kim Goo
Published: December 2020

This paper proposes a live broadcast traffic model for an internet protocol (IP)-based terrestrial digital broadcasting system to transmit dynamic adaptive streaming over hypertext transfer protocol (DASH) media. The IP-based terrestrial digital broadcasting systems such as Advanced Television Systems Committee (ATSC) 3.0 transmit media content (e.g., full high definition and ultra-high definition) in units of DASH segment files. Although the DASH segment file has the same quality and playback time, the size of each DASH segment file can vary according to the media composition. The transmission resource of the terrestrial broadcasting system has increased the transmission capacity of broadcasting with new technologies. However, the transmission capacity is still limited and fixed compared to wired broadcasting networks. Therefore, a problem occurs with the efficiency of broadcasting resources and transmission delay when transmitting a variable segment file to a terrestrial digital broadcasting network. In this paper, the resource efficiency and transmission delay results that occur when transmitting the actual DASH segment file are simulated through the live broadcast traffic model, and the maximum delay time that a viewer accessing the terrestrial broadcast can experience is presented.
Development of Jasmine Rice Flour Properties as a Safe and Efficient Ingredient for Compact Powder
Authors: Jarupinthusophon Suekanya , Anurukvorakun Oraphan
Published: December 2020

Natural flour is usually not used directly in compact powder since there are some drawbacks, such as roughness and poor skin adhesion. The purpose of this research was to investigate the extraction and modification of jasmine rice flour using polyethylene glycol (PEG)-50 shea butter. The physical properties in terms of flowability and water resistance of the modified rice flour were investigated and compared with talcum. The modified rice flour was used as the ingredient to develop the compact powder by replacing talcum, which is the main ingredient in compact powder that provides the slipperiness and spread properties, but it is quite harmful. The results of this research revealed that the physical properties of the modified powder changed in terms of flowability and water-resistance by PEG-50 shea butter. The modified rice flour provided better physical properties compared to non-modified rice powder. The modified rice powder, a safe ingredient, could replace 100% talcum in the developed compact powder. Furthermore, the developed compact powder provided Sun Protection Factor (SPF) greater than 15, or 93%, UVB protection, good coverage with a natural appearance, smoothness, diffusion, softness of the skin, and a higher satisfaction level compared with the commercial product.
Study of the Mechanical Behavior of Subcellular Organelles Using a 3D Finite Element Model of the Tensegrity Structure
Authors: Khunsaraki Gholamreza Mohammadi , Oscuii Hanieh Niroomand , Voloshin Arkady
Published: December 2020

A tensegrity model can be used to describe the mechanical behavior of living cells. A finite element model (FEM) was used to assess the mechanical contribution of subcellular organelles. Continuum parts like the cytoplasm and membrane were modeled as continuous elements, while the tensegrity was chosen to model the cytoskeleton and nucleoskeleton. An atomic force microscope load was implemented to simulate the external load. The cell components were loaded separately to evaluate their mechanical contributions. The analysis started with a single cytoplasm and each of the cell components was added in consecutive steps. The results showed that the cytoskeleton carried the largest part of the reaction force. The cytoplasm was the second important component of the cell’s mechanical response. It was shown that the nucleoskeleton has a stiffer structure than the membrane and cytoplasm. The cytoskeleton supported approximately 90% of the reaction force, while the cytoplasm carried 9% and the shell parts and nucleoskeleton were responsible for about 1%.
Influence of Crack Geometry on Dynamic Damage of Cracked Rock: Crack Number and Filling Material
Authors: Wang Feili , Wang Shuhong , Xiu Zhanguo
Published: December 2020

The dynamic damage of cracked rock threatens the stability of rock structures in rock engineering applications such as underground excavation, mineral exploration and rock slopes. In this study, the dynamic damage of cracked rock with different spatial geometry was investigated in an experimental method. Approximately 54 sandstone specimens with different numbers of joints and different filling materials were tested using the split Hopkinson pressure bar (SHPB) apparatus. The energy absorption in this process was analyzed, and the damage variable was obtained. The experimental results revealed that the dynamic damage of cracked rock is obviously influenced by the number of cracks; the larger the number, the higher the energy absorption and the bigger the dynamic damage variable. Moreover, it was observed from the dynamic compressive experiments that the energy absorption and the dynamic variable decreased with the strength and cohesion of the filling material, indicating that the filling material of crack has considerate influence on the dynamic damage of cracked rock.
Ontological Approach for Automatic Inference of Concrete Crack Cause
Authors: Jung Seoyoung , Lee Seulki , Yu Jungho
Published: December 2020

The cause of cracks in concrete is traditionally estimated by analyzing information such as patterns and locations of the cracks and whether other defects are present, followed by aggregating the findings to estimate the cause. This method is highly dependent on the expert’s knowledge and experience in the process of identifying the cause of the cracks by compiling information related to the occurrence of the cracks, and it is likely that each expert will make a different diagnosis or an expert with insufficient knowledge and experience will make an inaccurate diagnosis. Therefore, we propose automated technology using the ontology to improve the consistency and accuracy of crack diagnosis results in this research. The proposed approach uses information on the crack patterns, locations, and penetration status, as well as the occurrence of other defects, to automatically infer the causes of cracks. We developed ontology that can infer the cause of cracks using the information on their appearance and applied actual cases of cracks to verify the ontological operation. In addition, the consistency and accuracy of the ontology were validated using eight actual cases of crack. The approach of this study can support expert decision-making in the crack diagnosis process, thereby reducing the possibility of various errors caused by the intervention of inaccurate judgments in the crack diagnosis process and improving the efficiency of the crack diagnosis tasks.
A Remark for the Hyers–Ulam Stabilities on n-Banach Spaces
Authors: Choy Jaeyoo , Chu Hahng-Yun , Kim Ahyoung
Published: December 2020

In this article, we deal with stabilities of several functional equations in n-Banach spaces. For a surjective mapping f into a n-Banach space, we prove the generalized Hyers–Ulam stabilities of the cubic functional equation and the quartic functional equation for f in n-Banach spaces.
A Review of Local Outlier Factor Algorithms for Outlier Detection in Big Data Streams
Authors: Alghushairy Omar , Alsini Raed , Soule Terence , Ma Xiaogang
Published: December 2020

Outlier detection is a statistical procedure that aims to find suspicious events or items that are different from the normal form of a dataset. It has drawn considerable interest in the field of data mining and machine learning. Outlier detection is important in many applications, including fraud detection in credit card transactions and network intrusion detection. There are two general types of outlier detection: global and local. Global outliers fall outside the normal range for an entire dataset, whereas local outliers may fall within the normal range for the entire dataset, but outside the normal range for the surrounding data points. This paper addresses local outlier detection. The best-known technique for local outlier detection is the Local Outlier Factor (LOF), a density-based technique. There are many LOF algorithms for a static data environment; however, these algorithms cannot be applied directly to data streams, which are an important type of big data. In general, local outlier detection algorithms for data streams are still deficient and better algorithms need to be developed that can effectively analyze the high velocity of data streams to detect local outliers. This paper presents a literature review of local outlier detection algorithms in static and stream environments, with an emphasis on LOF algorithms. It collects and categorizes existing local outlier detection algorithms and analyzes their characteristics. Furthermore, the paper discusses the advantages and limitations of those algorithms and proposes several promising directions for developing improved local outlier detection methods for data streams.
Molecular Dynamics of Chloroplast Membranes Isolated from Wild-Type Barley and a Brassinosteroid-Deficient Mutant Acclimated to Low and High Temperatures
Authors: Sadura Iwona , Latowski Dariusz , Oklestkova Jana , Gruszka Damian , Chyc Marek , Janeczko Anna
Published: December 2020

Plants have developed various acclimation strategies in order to counteract the negative effects of abiotic stresses (including temperature stress), and biological membranes are important elements in these strategies. Brassinosteroids (BR) are plant steroid hormones that regulate plant growth and development and modulate their reaction against many environmental stresses including temperature stress, but their role in modifying the properties of the biological membrane is poorly known. In this paper, we characterise the molecular dynamics of chloroplast membranes that had been isolated from wild-type and a BR-deficient barley mutant that had been acclimated to low and high temperatures in order to enrich the knowledge about the role of BR as regulators of the dynamics of the photosynthetic membranes. The molecular dynamics of the membranes was investigated using electron paramagnetic resonance (EPR) spectroscopy in both a hydrophilic and hydrophobic area of the membranes. The content of BR was determined, and other important membrane components that affect their molecular dynamics such as chlorophylls, carotenoids and fatty acids in these membranes were also determined. The chloroplast membranes of the BR-mutant had a higher degree of rigidification than the membranes of the wild type. In the hydrophilic area, the most visible differences were observed in plants that had been grown at 20 °C, whereas in the hydrophobic core, they were visible at both 20 and 5 °C. There were no differences in the molecular dynamics of the studied membranes in the chloroplast membranes that had been isolated from plants that had been grown at 27 °C. The role of BR in regulating the molecular dynamics of the photosynthetic membranes will be discussed against the background of an analysis of the photosynthetic pigments and fatty acid composition in the chloroplasts.
Effects of Ketamine on Learning and Memory in the Hippocampus of Rats through ERK, CREB, and Arc
Authors: Shi Mingxian , Ding Jiafeng , Li Lin , Bai Hui , Li Xinran , Lan Ling , Fan Honggang , Gao Li
Published: December 2020

Ketamine has become a popular recreational drug due to its neuronal anesthesia effect and low price. The process of learning and memory is part of the distinctive high-level neural activities in animals. We investigated the effects of subanesthetic and anesthetic doses of ketamine on the learning and memory-related signal transduction mechanisms. We used the Morris water maze test to execute rats’ learning and memory ability and detected changes of Arc mRNA and Arc, cAMP-response element-binding protein (CREB), phospho-CREB (p-CREB), extracellular signal-regulated kinase (ERK), and phospho-ERK (p-ERK) protein expression in the hippocampus 10 min and 24 h after administration. Ten min after ketamine injection, the Arc gene and the protein expression levels increased in all groups; p-ERK only increased in the chronic subanesthetic dose group. After 24 h, the Arc gene and the protein expression levels of the subanesthetic dose group increased, but those of the chronic subanesthetic dose group and anesthetic dose group decreased. However, p-ERK increased in all groups. A chronic subanesthetic dose of ketamine could increase learning and memory ability through ERK, CREB, and Arc in a short time, and the high body temperature after the subanesthetic dose of ketamine injection was the main factor leading to changes in Arc. The subanesthetic dose of ketamine regulated learning and memory through ERK, CREB, and ARC 24 h after injection.