bluuebunny/crossref_metadata_2025 huggingface dataset:
Data-Driven Reinforcement-Learning-Based Automatic Bucket-Filling for Wheel Loaders
Authors: Huang Jianfei , Kong Dewen , Gao Guangzong , Cheng Xinchun , Chen Jinshi
Published: October 2021

Automation of bucket-filling is of crucial significance to the fully automated systems for wheel loaders. Most previous works are based on a physical model, which cannot adapt to the changeable and complicated working environment. Thus, in this paper, a data-driven reinforcement-learning (RL)-based approach is proposed to achieve automatic bucket-filling. An automatic bucket-filling algorithm based on Q-learning is developed to enhance the adaptability of the autonomous scooping system. A nonlinear, non-parametric statistical model is also built to approximate the real working environment using the actual data obtained from tests. The statistical model is used for predicting the state of wheel loaders in the bucket-filling process. Then, the proposed algorithm is trained on the prediction model. Finally, the results of the training confirm that the proposed algorithm has good performance in adaptability, convergence, and fuel consumption in the absence of a physical model. The results also demonstrate the transfer learning capability of the proposed approach. The proposed method can be applied to different machine-pile environments.
Scheduling of Single-Arm Cluster Tools with Residency Time Constraints and Chamber Cleaning Operations
Authors: Li Jie , Qiao Yan , Zhang Siwei , Li Zhiwu , Wu Naiqi , Song Tairan
Published: October 2021

To ensure wafer quality, engineers have to impose wafer residency time constraints and chamber cleaning operations on cluster tools; this has been widely used in semiconductor manufacturing. Wafer residency time constraints and chamber cleaning operations make the scheduling problem of cluster tools more challenging. This work aims to solve such a scheduling problem for single-arm cluster tools and presents a novel method based on the use of virtual wafers. Under a one-cyclic schedule obtained for single-arm cluster tools without chamber cleaning requirements, virtual wafers are loaded into the tool such that when a process module (PM) processes virtual wafers, a chamber cleaning operation is performed in practice. The key to solve this scheduling problem is to find a wafer loading sequence with the highest performance in terms of cycle time. With this idea, this work constructs a genetic algorithm to search for such a solution. Since the obtained solution is a periodical wafer loading sequence based on a one-wafer cyclic schedule, it can be easily implemented. Therefore, this work has high practical value to numerous semiconductor manufacturers. Experiments were performed to show the efficiency and effectiveness of the proposed method.
A Photo Identification Framework to Prevent Copyright Infringement with Manipulations
Authors: Kim Doyoung , Heo Suwoong , Kang Jiwoo , Kang Hogab , Lee Sanghoon
Published: October 2021

In recent years, copyright infringement has been one of the most serious problems that hamper the development of the culture and arts industry. Due to the limitations of existing image search services, these infringements have not been properly identified and the number of infringements has been increasing continuously. To uncover these infringements and handle big data extracted from copyright photos, we propose a photo copyright identification framework to accurately handle manipulations of stolen photos. From a collage of cropped photos, regions of interest (RoIs) are detected to reduce the influence of cropping and identify each photo by Image RoI Detection. Binary descriptors for quick database search are generated from the RoIs by Image Hashing robustly to geometric and color manipulations. The matching results of Image Hashing are verified by measuring their similarity using the proposed Image Verification to reduce false positives. Experimental results demonstrate that the proposed framework outperforms other image retrieval methods in identification accuracy and significantly reduces the false positive rate by 2.8%. This framework is expected to identify copyright infringements in practical situations and have a positive effect on the copyright market.
Geometrical Parametric Study on Steel Beams Exposed to Solar Radiation
Authors: Abid Sallal R. , Al-Gasham Thaar S. , Xue Junqing , Liu Yongjian , Liu Jiang , Briseghella Bruno
Published: October 2021

A finite element thermal analysis was conducted in this study with the aim of evaluating the influence of the geometrical parameters of steel sections on their thermal response under solar radiation. Four W12 and W24 standard steel beams were investigated under the solar irradiation conditions of a sunny summer day. The finite element analysis was carried out using COMSOL Multiphysics considering the Sun’s movement from sunrise to sunset, reflected radiation from the ground, surface convection of air and long wave radiation as the main boundary thermal loads. The temperature-time variation at different locations in the sections, vertical temperature distributions, temperature gradient distributions and thermal stress distributions were investigated. The results showed that the daily maximum temperatures, temperature variation, temperature and temperature gradient distributions and thermal stresses are influenced by the geometry of the steel section. The flange width and flange thickness were found to be the controlling parameters during the noon hours, while these parameters in addition to web depth control the shading effect during the afternoon. On the other hand, web thickness affects the temperature of webs at sunrise and sunset times. Geometrical ratios like Wf/H, Wf/tf2 and 2Wf/Htf were the most influential parameters on temperatures, temperature gradients and thermal stresses of steel beams subjected to solar radiation. The investigated section with the maximum Wf/tf2 value of 0.96 (W12 × 58) recorded the highest top-surface noon temperature, while section W24 × 84 with the lowest Wf/tf2 value of 0.60 exhibited the lowest temperature.
Visual-Saliency-Based Abnormality Detection for MRI Brain Images—Alzheimer’s Disease Analysis
Authors: Andrushia A. , Sagayam K. , Dang Hien , Pomplun Marc , Quach Lien
Published: October 2021

In recent years, medical image analysis has played a vital role in detecting diseases in their early stages. Medical images are rapidly becoming available for various applications to solve human problems. Therefore, complex medical features are needed to develop a diagnostic system for physicians to provide better treatment. Traditional methods of abnormality detection suffer from misidentification of abnormal regions in the given data. Visual-saliency detection methods are used to locate abnormalities to improve the accuracy of the proposed work. This study explores the role of a visual saliency map in the classification of Alzheimer’s disease (AD). Bottom-up saliency corresponds to image features, whereas top-down saliency uses domain knowledge in magnetic resonance imaging (MRI) brain images. The novelty of the proposed method lies in the use of an elliptical local binary pattern descriptor for low-level MRI characterization. Ellipse-like topologies help to obtain feature information from different orientations. Extensively directional features at different orientations cover the micro patterns. The brain regions of the Alzheimer’s disease stages were classified from the saliency maps. Multiple-kernel learning (MKL) and simple and efficient MKL (SEMKL) were used to classify Alzheimer’s disease from normal controls. The proposed method used the OASIS dataset and experimental results were compared with eight state-of-the-art methods. The proposed visual saliency-based abnormality detection produces reliable results in terms of accuracy, sensitivity, specificity, and f-measure.
The Effect of Arachidic Acid Mixtures on the Cooling Performance of a Heat Sink
Authors: Hammoud Mohammad , Mjallal Ibrahim , Farhat Hussien , Abdallah Nour , Habchi Charbel , Lemenand Thierry
Published: October 2021

The temperature of an electronic device is one of the most important parameters to deal with. Any increase above the temperature limits results in a failure in the device. Thus, to ensure good operation, an electronic device should be cooled. One promising technique is the use of Phase Change Materials (PCMs) for their well-known ability to absorb the heat dissipated by the device, thanks to their high latent heat of fusion. Arachidic acid is a fatty acid that, when mixed with sodium decanoate and potassium oleate salts, can be used as a promising PCM due to its high latent heat. This paper aims to shed light on the use such mixtures of Arachidic acid for cooling in a heat sink. An experimental setup was built for this purpose. The results show that the Arachidic acid mixtures are suitable for applications requiring intermediate heat dissipation.
Investigation of Nonthermal Plasma Jet Excitation Mode and Optical Assessment of Its Electron Concentration
Authors: Ivankov Anton S. , Kozhevnikova Anastasia M. , Schitz Dmitry V. , Alekseenko Igor V.
Published: October 2021

The results of a study of a plasma jet of atmospheric-pressure helium driven by a capacitive discharge using sine and pulsed modes of excitation are presented. The homogeneous discharge of a multi-channel plasma jet at gas temperature of 34 °C and helium flow rate of 0.5 L/min was achieved with short pulse excitation. A digital holography method is proposed to estimate a basic plasma parameter, i.e., its electron concentration. An automated digital holographic interferometry set-up for the observation and study of a nonthermal plasma jet in a pulse mode is developed and described. The synchronization features of recording devices with the generation of plasma pulses are considered. The electron concentration of the plasma jet is also estimated. The disadvantages of the proposed technique and its further application are discussed.
A Multifeatured Data-Driven Homogenization for Heterogeneous Elastic Solids
Authors: Haghighi Ehsan Motevali , Na Seonhong
Published: October 2021

A computational homogenization of heterogeneous solids is presented based on the data-driven approach for both linear and nonlinear elastic responses. Within the Double-Scale Finite Element Method (FE2) framework, a data-driven model is proposed to substitute the micro-level Finite Element (FE) simulations to reduce computational costs in multiscale simulations. The heterogeneity of porous solids at the micro-level is considered in various material properties and geometrical attributes. For material properties, elastic constants, which are Lame’s coefficients, are subjected to be heterogeneous in the linear elastic responses. For geometrical features, different numbers, sizes, and locations of voids are considered to reflect the heterogeneity of porous solids. A database for homogenized microstructural responses is constructed from a series of micro-level FE simulations, and machine learning is used to train and test our proposed model. In particular, four geometrical descriptors are designed, based on N-probability and lineal-path functions, to clearly reflect the geometrical heterogeneity of various microstructures. This study indicates that a simple deep neural networks model can capture diverse microstructural heterogeneous responses well when given proper input sources, including the geometrical descriptors, are considered to establish a computational data-driven homogenization scheme.
Perioperative Chemotherapy with FLOT Scheme in Resectable Gastric Adenocarcinoma: A Preliminary Correlation between TRG and Radiomics
Authors: Garbarino Giovanni Maria , Zerunian Marta , Berardi Eva , Mainardi Federico , Pilozzi Emanuela , Polici Michela , Guido Gisella , Rucci Carlotta , Polidori Tiziano , Tarallo Mariarita , Laracca Giovanni Guglielmo , Iannicelli Elsa , Mercantini Paolo , Annibale Bruno , Laghi Andrea , Caruso Damiano
Published: October 2021

Perioperative chemotherapy (p-ChT) with a fluorouracil plus leucovorin, oxaliplatin, and docetaxel (FLOT) scheme is the gold standard of care for locally advanced gastric cancer. We aimed to test CT radiomics performance in early response prediction for p-ChT. Patients with advanced gastric cancer who underwent contrast enhanced CT prior to and post p-ChT were retrospectively enrolled. Histologic evaluation of resected specimens was used as the reference standard, and patients were divided into responders (TRG 1a-1b) and non-responders (TRG 2-3) according to their Becker tumor regression grade (TRG). A volumetric region of interest including the whole tumor tissue was drawn from a CT portal-venous phase before and after p-ChT; 120 radiomic features, both first and second order, were extracted. CT radiomics performances were derived from baseline CT radiomics alone and ΔRadiomics to predict response to p-ChT according to the TRG and tested using a receiver operating characteristic (ROC) curve. The final population comprised 15 patients, 6 (40%) responders and 9 (60%) non-responders. Among pre-treatment CT radiomics parameters, Shape, GLCM, First order, and NGTDM features showed a significant ability to discriminate between responders and non-responders (p < 0.011), with Cluster Shade and Autocorrelation (GLCM features) having AUC = 0.907. ΔRadiomics showed significant differences for Shape, GLRLM, GLSZM, and NGTDM features (p < 0.007). MeshVolume (Shape feature) and LongRunEmphasis (GLRLM feature) had AUC = 0.889. In conclusion, CT radiomics may represent an important supportive approach for the radiologic evaluation of advanced gastric cancer patients.
Harmony Search Algorithm for Minimizing Assembly Variation in Non-linear Assembly
Authors: Mahalingam Siva Kumar , Nagarajan Lenin , Salunkhe Sachin , Nasr Emad Abouel , Davim Jõao Paulo , Hussein Hussein M. A.
Published: October 2021

The proposed work aims to acquire the maximum number of non-linear assemblies with closer assembly tolerance specifications by mating the different bins’ components. Before that, the components are classified based on the range of tolerance values and grouped into different bins. Further, the manufacturing process of the components is selected from the given and known alternative processes. It is incredibly tedious to obtain the best combinations of bins and the best process together. Hence, a novel approach using the combination of the univariate search method and the harmony search algorithm is proposed in this work. Overrunning clutch assembly is taken as an example. The components of overrunning clutch assembly are manufactured with a wide tolerance value using the best process selected from the given alternatives by the univariate search method. Further, the manufactured components are grouped into three to nine bins. A combination of the best bins is obtained for the various assembly specifications by implementing the harmony search algorithm. The efficacy of the proposed method is demonstrated by showing 24.9% of cost-savings while making overrunning clutch assembly compared with the existing method. The efficacy of the proposed method is demonstrated by showing 24.9% of cost-savings while making overrunning clutch assembly compared with the existing method. The results show that the contribution of the proposed novel methodology is legitimate in solving selective assembly problems.
Microgrid for a Cluster of Grid Independent Buildings Powered by Solar and Wind Energy
Authors: Sandoval Aguilar Raquel , Michaelides Efstathios E.
Published: October 2021

The reduction of CO2 emissions and the avoidance of Global Climate Change necessitate the conversion of the electricity generation industry to rely on non-carbon sources. Additionally, the mitigation of the duck-curve effects in microgrids requires the development of grid-independent buildings. Computations were performed for a cluster of one thousand grid-independent buildings in the North Texas area, where air-conditioning demand is high in the summer months. The electricity demand is balanced with energy supply generated from wind turbines, photovoltaic cells, or stored energy in hydrogen tanks. The results indicate that with one wind turbine operating, each building must be fitted with 10.2 kW rating photovoltaics capacity and a tank with 5.2 m3 of hydrogen storage capacity to satisfy the hourly demand of the buildings’ community. The addition of more wind turbines significantly reduces the needed PV rating but increases the required storage. Investing in energy conservation measures in the buildings significantly reduces both the needed storage capacity and the PV cell ratings.
A New Foot Trajectory Planning Method for Legged Robots and Its Application in Hexapod Robots
Authors: Xia Haichuang , Zhang Xiaoping , Zhang Hong
Published: October 2021

Compared with wheeled and tracked robots, legged robots have better movement ability and are more suitable for the exploration of unknown environments. In order to further improve the adaptability of legged robots to complex terrains such as slopes, obstacle environments, and so on, this paper makes a new design of the legged robot’s foot sensing structure that can successfully provide accurate feedback of the landing information. Based on this information, a new foot trajectory planning method named three-element trajectory determination method is proposed. For each leg in one movement period, the three elements are the start point in the support phase, the end point in the support phase, and the joint angle changes in the transfer phase where the first two elements are used to control the height, distance, and direction of the movement, and the third element is used make decisions during the lifting process of the leg. For the support phase, the trajectory is described in Cartesian space, and a spline of linear function with parabolic blends is used. For the transfer phase, the trajectory is described in joint-space, and the joint angle function is designed as the superposition of the joint angle reverse-chronological function and the interpolation function which is obtained based on joint angle changes. As an important legged robot, a hexapod robot that we designed by ourselves with triangle gait is chosen to test the proposed foot trajectory planning method. Experiments show that, while the foot’s landing information can be read and based on the three-element trajectory planning method, the hexapod robot can achieve stable movement even in very complex scenes. Although the experiments are performed on a hexapod robot, our method is applicable to all forms of legged robots.
Spatial—Temporal Traffic Flow Data Restoration and Prediction Method Based on the Tensor Decomposition
Authors: Yan Jiahe , Li Honghui , Bai Yanhui , Lin Yingli
Published: October 2021

As an important part of urban big data, traffic flow data play a critical role in traffic management and emergency response. Traffic flow data contain multi-mode characteristics, which need to be deeply mined. To make full use of multi-mode characteristics, we use a 3-order tensor to represent the traffic flow data, considering “temporal-spatial-periodic” characteristics. To recover the missing data of traffic flow, we propose the Missing Data Completion Algorithm Based on Residual Value Tensor Decomposition (MDCA-RVTD), which combines linear regression, univariate spline, and CP decomposition. Then, we predict the future traffic flow data by using the proposed Traffic Flow Prediction Algorithm Based on Data Completion Strategy (TFPA-DCS). The experimental results show that recovering the missing data is helpful in improving the prediction accuracy. Additionally, the prediction accuracy of the proposed Algorithm is better than gray model and traditional tensor CP decomposition method.
Stability Reinforcement of Slopes Using Vegetation Considering the Existence of Soft Rock
Authors: Liu Chungang , Bi Huanjun , Wang Dong , Li Xiaoning
Published: October 2021

This study investigates the effectiveness of vegetation reinforcement on the stability of a slope with red-bed soft rock in a slope along the Xining-Chengdu railway, China. Four kinds of vegetation were considered to reinforce the soil and the slope. The rooted soil parameters were determined based on the laboratory tests. A numerical model was developed based on the actual geometry and soil layer distributions. The soils were modeled as elastic perfectly plastic materials and the vegetation reinforcement was represented as addition cohesion of a series of subsoil layers within a given depth. The effectiveness of vegetation on slope reinforcement under both dry and rainfall conditions was investigated regarding this case. The potential failure surface and corresponding factor of safety of the red-bed soft rock slope for those different conditions were analyzed and compared. It has been found that the addition of vegetation increased the safety of slope stability whether the slope is under a dry condition or a rainfall condition, while the increasing proportion of factor of safety due to vegetation reinforcement for this case is very limited. The results and findings in this study are still significant for the practitioner to evaluate the reasonability of vegetation reinforcement.
Development of an Intelligent Voltage Control System for Bulk Power Systems
Authors: Lee Heungjae , Yu Wonkun , Oh Junghyun , Kim Hyungsuk , Kim Jinyoung
Published: October 2021

As modern power systems become large and complicated, an automated voltage and reactive power control system is required in most developed countries due to the remarkable recent progress in computer networks and information technology. To date, voltage control has depended on human operators in the Korean power system. Accordingly, this paper proposes a universal intelligent voltage control system for bulk power systems based on sensitivity analysis and a main expert system. A detailed state space modeling technique is discussed, and an effective performance index is proposed to accelerate the searching performance of the expert system. As the searching strategy is an important factor for the speed of the expert system, the least-first search algorithm is applied using this performance index. The proposed system has been applied to the Korean power system, showing promising results.
Planar Array Failed Element(s) Radiation Pattern Correction: A Comparison
Authors: Boopalan Navaamsini , Ramasamy Agileswari K. , Nagi Farrukh , Alkahtani Ammar Ahmed
Published: October 2021

Phased arrays are widely used in different fields, such as broadcasting, radar, optics, and space communications. The principle of phased arrays is to generate a directed signal from a large number of antennas to be steered at any desired angle. This, however, increases the probability of defective elements in an array. Faulty elements in an array cause asymmetry and result in increased sidelobe levels which rigorously distort the radiation pattern. Increased sidelobe radiation wastes energy and can cause interference by radiating and receiving signals in unintended directions. Therefore, it is necessary to find a method that can provide accuracy in the radiation pattern transmitted or received in the presence of failed element(s) in an array. This paper compares the few available optimization methods, namely, simulated annealing (SA), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Pattern Search (PS) methods. For each method, various types of failures were examined, and the most suitable techniques to recover the far-field radiation are recommended. The optimization is then carried out by selecting the optimal weights of the remaining working elements in the planar array. The optimized radiation pattern’s efficiency was evaluated by comparing the Signal to Noise Ratio (SNR) value of the optimized radiation with reference and failed radiation patterns. The PSO method showed a better performance compared to all the other methods in reducing the failed radiation pattern’s SNR value. In various types of failure tests, this method reduced the failed radiation pattern’s SNR from 1 to 10 dB. This method also successfully produced a radiation pattern that closely matches the reference pattern before any failed element(s) are presented in the array. The life cycle of a planar array system with faulty elements can be increased by optimizing the remaining active elements in the array with the PSO method. It also reduces the cost of restoring and replacing the failed elements in an array regularly. This approach also prevents near-field measurement that requires complicated processes using costly equipment.
Optimization and Mapping of the Deep Drawing Force Considering Friction Combination
Authors: Zein Hussein , Irfan Osama M.
Published: October 2021

Deep drawing is characterized by extremely complex deformation that is influenced by process characteristics such as die and punch shapes, blank shape, blank holding force, material properties, and lubrication. The optimization of the deep drawing process is a challenging issue due to the complicated functions that define and relate the process parameters. However, the optimization is essential to enhance the productivity and the product cost in the deep drawing process. In this paper, a MATLAB toolbox (Pattern Search) was employed to minimize the maximum deep drawing force (Fd-min) at different values of the operating and the geometrical parameters. As a result, a minimum deep drawing force chart (carpet plot) was generated to show the best combination of friction coefficients at the blank contact interfaces. The extracted friction coefficients guided the selection of proper lubricants while minimizing the deep drawing force. A finite element analysis (FEA) was applied through 3D model to simulate the deep drawing process. The material modeling was implemented utilizing the ABAQUS/EXPLICIT program with plastic anisotropy. The optimization results showed that the deep drawing force and the wrinkling decrease when compared with experimental and numerical results from the literature.
An Approach to Exploring Non-Governmental Development Organizations Interest Groups on Facebook
Authors: Galiano-Coronil Araceli , Mier-Terán Franco Juan José , Serrano Domínguez César , Tobar Pesánte Luis Bayardo
Published: October 2021

This paper presents an approach for analyzing the stakeholders from various organizations based on their Facebook activity. On a practical level, the proposed approach has been applied in two of the Non-Governmental Development Organizations (NGDOs) with the largest number of delegations in the province of Cadiz: Red Cross Cadiz, and Caritas Asidonia Jerez. The purposes of the research are to describe the management of marketing activities on Facebook; to identify the network stakeholders, their roles in the communication, and the community generating factors; and to position organizations according to their leadership, activity, and popularity in the network. This study used a mixed-methods research design, combining personal interviews and Social Network Analysis (SNA). The SNA provided insights into the various ways the analyzed NGDOs are active on Facebook, the roles they play in communication, and how communities are generated. Moreover, the SNA made it possible to visualize the interactions between organizations and their stakeholders within the Facebook environment using the Gephi software package. Two factors that generate communities were detected in the results: the organization’s nature and its geographical location. Moreover, two solutions were proposed to determine the organizations’ positioning according to their roles in communication. Consequently, two maps were created, a two-dimensional map with the activity and popularity of the parameters, which shows that just because an NGDO is active does not mean it is popular (in terms of receiving “likes”), and a second three-dimensional graph to which a leadership parameter was added. In this last map, four groups of important actors can be seen, with one group formed by the organizations with the best ratings on the three dimensions, and the other three with a low level of leadership in common but who were different in terms of the popularity and activity dimensions.
Preliminary Evaluation of an Adaptive Robotic Training Program of the Wrist for Persons with Multiple Sclerosis
Authors: Mannella Kailynn , Albanese Giulia A. , Ditor David , Zenzeri Jacopo , Holmes Michael W. R.
Published: October 2021

Robotics can be used to describe wrist kinematics and assess sensorimotor impairments, while the implementation of training algorithms can be aimed at improving neuromuscular control. The purpose of this study was to use a robotic device to develop an adaptive and individualized training program of the distal upper extremity for individuals with multiple sclerosis (MS). This approach included an online assessment of performance aimed at changing the level of assistance/resistance provided during the task. Participants (N = 7) completed a robotic training program that occurred 3 times weekly for 4 weeks. The training protocol consisted of tracking a target moving along a figure by grasping the end-effector of the robotic device and moving it along the trajectory. Outcome measures were assessed pre- and post-intervention. Improvements in performance were quantified by average tracking (p = 0.028) and figural error (p = 0.028), which was significantly reduced by 26% and 43%, respectively. Isometric wrist strength significantly improved post-intervention (flexion: p = 0.043, radial and ulnar deviation: p = 0.028). The results of this work demonstrate that 4-weeks of adaptive robotic training is a feasible rehabilitative program that has the potential to improve distal upper extremity motor accuracy and muscular strength in a MS population.
Application of Air-Coupled Ultrasonic Nondestructive Testing in the Measurement of Elastic Modulus of Materials
Authors: Chen Jie , Wang Xiaoyu , Yang Xu , Zhang Li , Wu Hong
Published: October 2021

It is difficult to measure elastic modulus simply and accurately in the testing of mechanical properties of materials. Combined with static tensile method, this paper presents a method for measuring elastic modulus of materials based on air-coupled ultrasonic nondestructive testing. Firstly, the 1–3 piezoelectric composite material and the matching material of low acoustic impedance are self-made, and 400 kHz air-coupled ultrasonic transducer is fabricated. Then, the performance of the transducer is tested, and the insertion loss and bandwidth of −6 dB are −33.5 dB and 23.4%, respectively. Compared with the traditional instrument for measuring elastic modulus, the measurement of elastic modulus of carbon steel rod material is realized in this paper, and the measured results are in agreement with the accepted value. In addition, from the angle of relative uncertainty, how to reduce the measurement error by improving the device is analyzed. It can be shown that the method has high linearity, high symmetry, and good stability and repeatability. This paper provides a new way for the selection and design of measuring instrument components.
Fermented Cranberry Fortified Buckwheat Product—Phenolic Composition, Antioxidant and Microbiological Properties
Authors: Mikulajová Anna , Matejčeková Zuzana , Mošovská Silvia , Kohajdová Zlatica , Valík Ľubomír , Hybenová Eva
Published: October 2021

This study determined the effect of fermentation by Fresco DVS 1010 starter culture with added probiotic strain Lactobacillus rhamnosus GG and potentially probiotic isolate Lactobacillus plantarum HM1, at fermentation times (0, 8 h) and cold storage period (24 h, 4th day, 7th day, 14th day), on microbial parameters, pH changes, total phenolic content, phenolic compounds profile, and antioxidant activity of buckwheat water- and milk-based mashes, flavored with cranberries and unflavored. The tested starter Fresco culture effectively fermented the buckwheat products and the viable cell counts of potentially probiotic bacteria were sufficient to demonstrate the health-promoting properties of final products. Lactic acid bacteria had a positive impact on total phenolic compound content, total flavonoid content, and antioxidant activity of buckwheat mashes, whereby final values (14 days) were higher by about 16.9–130.8%, 13.4–37.7%, and 14.5–145.9%, respectively, in comparison to initial values (0 h). Seven phenolic acids (gallic, protocatechuic, vanillic, syringic, caffeic, p-coumaric, and ferulic) and two flavonoids (rutin and quercetin) in buckwheat mashes were measured during the experimental period. The content of quercetin, gallic, and protocatechuic acids increased and, conversely, p-coumaric acid decreased, in all products. Prepared buckwheat fermented products have the potential to meet the criteria for potentially functional foods.
Rapid Update with EnVar Direct Radar Reflectivity Data Assimilation for the NOAA Regional Convection-Allowing NMMB Model over the CONUS: System Description and Initial Experiment Results
Authors: Wang Yongming , Wang Xuguang
Published: October 2021

This study first describes the extended Grid-Point Statistical Interpolation analysis system (GSI)-based ensemble-variational data assimilation (DA) system within the North American Mesoscale Rapid Refresh (NAMRR) system for the Nonhydrostatic Multiscale Model on the B grid (NMMB). Experiments were conducted to examine three critical aspects of data assimilation configuration in this system. Ten retrospective high-impact convective cases during the warm season of 2015–2016 were adopted for testing. A 10-member, 18 h ensemble forecast was launched for each experiment. Specifically, the experiment using horizontal (vertical) localization radii (Lr) of 300 km (0.55-scaled height measured in the nature log of pressure) overall had more skills than that of 500 km (1.1-scaled height) for conventional in-situ observation assimilation. Diagnostics suggest that the higher forecast skills could be attributed to applying smaller Lr in the boundary with large temperature and moisture gradients. For radar DA, the experiment was more skillful with horizontal (vertical) Lr of 15 km (1.1-scaled height) than that of 12 km (0.55-scaled height). Diagnostics suggest that the improved forecasts were achieved by using wider Lr to spread radar observations into unobserved areas more effectively. Slight forecast skill differences between the relaxation inflation factors of 95% and 65% are presented. The impact of varying inflation magnitudes primarily occurred in the upper-level spread.
Investigation of Biofuel as a Potential Renewable Energy Source
Authors: Khan M. Anwar H. , Bonifacio Sophia , Clowes Joanna , Foulds Amy , Holland Rayne , Matthews James C. , Percival Carl J. , Shallcross Dudley E.
Published: October 2021

An accelerating global energy demand, paired with the harmful environmental effects of fossil fuels, has triggered the search for alternative, renewable energy sources. Biofuels are arguably a potential renewable energy source in the transportation industry as they can be used within current infrastructures and require less technological advances than other renewable alternatives, such as electric vehicles and nuclear power. The literature suggests biofuels can negatively impact food security and production; however, this is dependent on the type of feedstock used in biofuel production. Advanced biofuels, derived from inedible biomass, are heavily favoured but require further research and development to reach their full commercial potential. Replacing fossil fuels by biofuels can substantially reduce particulate matter (PM), carbon monoxide (CO) emissions, but simultaneously increase emissions of nitrogen oxides (NOx), acetaldehyde (CH3CHO) and peroxyacetyl nitrate (PAN), resulting in debates concerning the way biofuels should be implemented. The potential biofuel blends (FT-SPK, HEFA-SPK, ATJ-SPK and HFS-SIP) and their use as an alternative to kerosene-type fuels in the aviation industry have also been assessed. Although these fuels are currently more costly than conventional aviation fuels, possible reduction in production costs has been reported as a potential solution. A preliminary study shows that i-butanol emissions (1.8 Tg/year) as a biofuel can increase ozone levels by up to 6% in the upper troposphere, highlighting a potential climate impact. However, a larger number of studies will be needed to assess the practicalities and associated cost of using the biofuel in existing vehicles, particularly in terms of identifying any modifications to existing engine infrastructure, the impact of biofuel emissions, and their chemistry on the climate and human health, to fully determine their suitability as a potential renewable energy source.
Climate Change, Obesity, and COVID-19—Global Crises with Catastrophic Consequences. Is This the Future?
Authors: Cuschieri Sarah , Grech Elizabeth , Cuschieri Andrea
Published: October 2021

Climate change and obesity were considered threats to our planet long before the onset of COVID-19. The recent pandemic has enhanced the global burden of both pre-existing crises. The aim of this narrative review is to explore the interaction between the three concurrent crises and the future of our planet should they not be dealt with accordingly. A PubMed and Google Scholar literature search was performed using different combinations of search strategies and using the keywords “obesity”, “climate/temperature change”, “cold/hot temperatures”, and “COVID-19”. High global greenhouse gas (GHG) emissions link obesity and climate change as a result of the interplay between biological and behavioural factors. COVID-19 mitigation measures have indirectly impacted obesity and GHG emissions through the shift in dietary habits, restricted mobility, the impact on healthcare services, and enhanced psychological stress. Furthermore, COVID-19 has a more detrimental effect if acquired by an obese individual, with a higher chance of hospitalization and mechanical ventilation. This leads to higher GHG emissions and negative repercussions on the climate. A tri-directional relationship exists between obesity, climate change, and COVID-19. Various factors contribute to this relationship, but unless urgent global integrated action plans are implemented that target all three calamities, and not just COVID-19, a devastating and unsustainable future may ensue.
Photoionization and Electron-Ion Recombination of n = 1 to Very High n-Values of Hydrogenic Ions
Authors: Nahar Sultana
Published: October 2021

Single electron hydrogen or hydrogenic ions have analytical forms to evaluate the atomic parameters for the inverse processes of photoionization and electron-ion recombination (H I + hν↔ H II + e) where H is hydrogen. Studies of these processes have continued until the present day (i) as the computations are restricted to lower principle quantum number n and (ii) to improve the accuracy. The analytical expressions have many terms and there are numerical instabilities arising from cancellations of terms. Strategies for fast convergence of contributions were developed but precise computations are still limited to lower n. This report gives a brief review of the earlier precise methodologies for hydrogen, and presents numerical tables of photoionization cross sections (σPI), and electron-ion recombination rate coefficients (αRC) obtained from recombination cross sections (σRC) for all n values going to a very high value of 800. σPI was obtained using the precise formalism of Burgess and Seaton, and Burgess. αRC was obtained through a finite integration that converge recombination exactly as implemented in the unified method of recombination of Nahar and Pradhan. Since the total electron-ion recombination includes all levels for n = 1–∞, the total asymptotic contribution of n = 801–∞, called the top-up, is obtained through a n−3 formula. A FORTRAN program “hpxrrc.f” is provided to compute photoionization cross sections, recombination cross sections and rate coefficients for any nl. The results on hydrogen atom can be used to obtain those for any hydrogenic ion of charge z through z-scaling relations provided in the theory section. The present results are of high precision and complete for astrophysical modelings.
De novo Assembly and Analysis of Tissue-Specific Transcriptomes of the Edible Red Sea Urchin Loxechinus albus Using RNA-Seq
Authors: Antiqueo Paulette , Zuloaga Rodrigo , Bastias-Molina Macarena , Meneses Claudio , Estrada Juan Manuel , Molina Alfredo , Valdés Juan Antonio
Published: October 2021

Edible red sea urchin (Loxechinus albus) is an endemic echinoderm species of the Chilean coasts. The worldwide demand for high-quality gonads of this species has addressed the depletion of its natural populations. Studies on this sea urchin are limited, and genomic information is almost nonexistent. Hence, generate a transcriptome is crucial information that will considerably enrich molecular data and promote future findings for the L. albus aquaculture. Here, we obtained transcriptomic data of the edible red sea urchin by Illumina platform. Total RNA was extracted from gonads, intestines, and coelomocytes of juvenile urchins, and samples were sequenced using MiSeq Illumina technology. A total of 91,119,300 paired-end reads were de novo assembled, 185,239 transcripts produced, and a reference transcriptome created with 38.8% GC content and an N50 of 1769 bp. Gene ontology analysis revealed notable differences in the expression profiles between gonads, intestines, and coelomocytes, allowing the detection of transcripts associated with specific biological processes and KEGG pathways. These data were validated using 12 candidate transcripts by real-time qPCR. This dataset will provide a valuable molecular resource for L. albus and other species of sea urchins.
Depside and Depsidone Synthesis in Lichenized Fungi Comes into Focus through a Genome-Wide Comparison of the Olivetoric Acid and Physodic Acid Chemotypes of Pseudevernia furfuracea
Authors: Singh Garima , Armaleo Daniele , Dal Grande Francesco , Schmitt Imke
Published: October 2021

Primary biosynthetic enzymes involved in the synthesis of lichen polyphenolic compounds depsides and depsidones are non-reducing polyketide synthases (NR-PKSs), and cytochrome P450s. However, for most depsides and depsidones the corresponding PKSs are unknown. Additionally, in non-lichenized fungi specific fatty acid synthases (FASs) provide starters to the PKSs. Yet, the presence of such FASs in lichenized fungi remains to be investigated. Here we implement comparative genomics and metatranscriptomics to identify the most likely PKS and FASs for olivetoric acid and physodic acid biosynthesis, the primary depside and depsidone defining the two chemotypes of the lichen Pseudevernia furfuracea. We propose that the gene cluster PF33-1_006185, found in both chemotypes, is the most likely candidate for the olivetoric acid and physodic acid biosynthesis. This is the first study to identify the gene cluster and the FAS likely responsible for olivetoric acid and physodic acid biosynthesis in a lichenized fungus. Our findings suggest that gene regulation and other epigenetic factors determine whether the mycobiont produces the depside or the depsidone, providing the first direct indication that chemotype diversity in lichens can arise through regulatory and not only through genetic diversity. Combining these results and existing literature, we propose a detailed scheme for depside/depsidone synthesis.
The Histamine H4 Receptor Participates in the Anti-Neuropathic Effect of the Adenosine A3 Receptor Agonist IB-MECA: Role of CD4+ T Cells
Authors: Micheli Laura , Durante Mariaconcetta , Lucarini Elena , Sgambellone Silvia , Lucarini Laura , Di Cesare Mannelli Lorenzo , Ghelardini Carla , Masini Emanuela
Published: October 2021

A3 adenosine receptor (A3AR) agonists have emerged as potent relievers of neuropathic pain by a T cell-mediated production of IL-10. The H4 histamine receptor (H4R), also implicated in pain modulation, is expressed on T cells playing a preeminent role in its activation and release of IL-10. To improve the therapeutic opportunities, this study aimed to verify the hypothesis of a possible cross-talk between A3AR and H4R in the resolution of neuropathic pain. In the mouse model of Chronic Constriction Injury (CCI), the acute intraperitoneal co-administration of the A3AR agonist IB-MECA (0.5 mg/kg) and the H4R agonist VUF 8430 (10 mg/kg), were additive in counteracting mechano-allodynia increasing IL-10 plasma levels. In H4R−/− mice, IB-MECA activity was reduced, lower pain relief and lower modulation of plasma IL-1β, TNF-α, IL-6 and IL-10 were shown. The complete anti-allodynia effect of IB-MECA in H4R−/− mice was restored after intravenous administration of CD4+ T cells obtained from naïve wild type mice. In conclusion, a role of the histaminergic system in the mechanism of A3AR-mediated neuropathic pain relief was suggested highlighting the driving force evoked by CD4+ T cells throughout IL-10 up-regulation.
Topical Administration of Melatonin-Loaded Extracellular Vesicle-Mimetic Nanovesicles Improves 2,4-Dinitrofluorobenzene-Induced Atopic Dermatitis
Authors: Kim Yoon Seon , Go Gyeongyun , Yun Chul-Won , Yea Ji-Hye , Yoon Sungtae , Han Su-Yeon , Lee Gaeun , Lee Mi-Young , Lee Sang Hun
Published: October 2021

Atopic dermatitis (AD) is caused by multiple factors that trigger chronic skin inflammation, including a defective skin barrier, immune cell activation, and microbial exposure. Although melatonin has an excellent biosafety profile and a potential to treat AD, there is limited clinical evidence from controlled trials that support the use of melatonin as an AD treatment. The delivery of melatonin via the transdermal delivery system is also a challenge in designing melatonin-based AD treatments. In this study, we generated melatonin-loaded extracellular vesicle-mimetic nanoparticles (MelaNVs) to improve the transdermal delivery of melatonin and to evaluate their therapeutic potential in AD. The MelaNVs were spherical nanoparticles with an average size of 100 nm, which is the optimal size for the transdermal delivery of drugs. MelaNVs showed anti-inflammatory effects by suppressing the release of TNF-α and β-hexosaminidase in LPS-treated RAW264.7 cells and compound 48/80-treated RBL-2H3 cells, respectively. MelaNVs showed a superior suppressive effect compared to an equivalent concentration of free melatonin. Treating a 2,4-dinitrofluorobenzene (DNCB)-induced AD-like mouse model with MelaNVs improved AD by suppressing local inflammation, mast cell infiltration, and fibrosis. In addition, MelaNVs effectively suppressed serum IgE levels and regulated serum IFN-γ and IL-4 levels. Taken together, these results suggest that MelaNVs are novel and efficient transdermal delivery systems of melatonin and that MelaNVs can be used as a treatment to improve AD.
Interactions of HMGB Proteins with the Genome and the Impact on Disease
Authors: Voong Calvin K. , Goodrich James A. , Kugel Jennifer F.
Published: October 2021

High Mobility Group Box (HMGB) proteins are small architectural DNA binding proteins that regulate multiple genomic processes such as DNA damage repair, nucleosome sliding, telomere homeostasis, and transcription. In doing so they control both normal cellular functions and impact a myriad of disease states, including cancers and autoimmune diseases. HMGB proteins bind to DNA and nucleosomes to modulate the local chromatin environment, which facilitates the binding of regulatory protein factors to the genome and modulates higher order chromosomal organization. Numerous studies over the years have characterized the structure and function of interactions between HMGB proteins and DNA, both biochemically and inside cells, providing valuable mechanistic insight as well as evidence these interactions influence pathological processes. This review highlights recent studies supporting the roles of HMGB1 and HMGB2 in global organization of the genome, as well as roles in transcriptional regulation and telomere maintenance via interactions with G-quadruplex structures. Moreover, emerging models for how HMGB proteins function as RNA binding proteins are presented. Nuclear HMGB proteins have broad regulatory potential to impact numerous aspects of cellular metabolism in normal and disease states.