bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of VaMyb40 and VaMyb60 Overexpression on Stilbene Biosynthesis in Cell Cultures of Grapevine Vitis amurensis Rupr.
Authors: Ananev Alexey A. , Suprun Andrey R. , Aleynova Olga A. , Nityagovsky Nikolay N. , Ogneva Zlata V. , Dubrovina Alexandra S. , Kiselev Konstantin V.
Published: July 2022

Stilbenes are plant defense compounds known to rapidly accumulate in grapevine and some other plant species in response to microbial infection and several abiotic stresses. Stilbenes have attracted considerable attention due to valuable biological effects with multi-spectrum therapeutic application. However, there is a lack of information on natural signaling pathways and transcription factors regulating stilbene biosynthesis. It has been previously shown that MYB R2R3 transcription factor genes VaMyb40 and VaMyb60 were up-regulated in cell cultures of wild-growing grapevine Vitis amurensis Rupr. in response to UV irradiation. In this study, the effects of VaMyb40 or VaMyb60 overexpression in cell cultures of V. amurensis on their capability to produce stilbenes were investigated. Overexpression of the VaMyb60 gene led to a considerable increase in the content of stilbenes in three independently transformed transgenic lines in 5.9–13.9 times, while overexpression of the VaMyb40 gene also increased the content of stilbenes, although to a lesser extent (in 3.4–4.0 times) in comparison with stilbene levels in the empty vector-transformed calli. Stilbene content and stilbene production in the VaMyb60-transgenic calli reached 18.8 mg/g of dry weight (DW) and 150.8 mg/L, respectively. Using HPLC analysis, we detected eight individual stilbenes: t-resveratrol diglucoside, t-piceid, t-resveratrol, ε-viniferin, δ-viniferin, cis-resveratrol, cis-piceid, t-piceatannol. T-resveratrol prevailed over other stilbenoid compounds (53.1–89.5% of all stilbenes) in the VaMyb-overexpressing cell cultures. Moreover, the VaMyb40- and VaMyb60-transformed calli were capable of producing anthocyanins up to 0.035 mg/g DW, while the control calli did not produce anthocyanins. These findings show that the VaMyb40 and VaMyb60 genes positively regulate the stilbene biosynthesis as strong positive transcription regulators and can be used in biotechnological applications for stilbene production or high-quality viticulture and winemaking.
Natural Products in Cardiovascular Diseases: The Potential of Plants from the Allioideae Subfamily (Ex-Alliaceae Family) and Their Sulphur-Containing Compounds
Authors: Alves-Silva Jorge M. , Zuzarte Mónica , Girão Henrique , Salgueiro Lígia
Published: July 2022

Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide and, together with associated risk factors such as diabetes, hypertension, and dyslipidaemia, greatly impact patients’ quality of life and health care systems. This burden can be alleviated by fomenting lifestyle modifications and/or resorting to pharmacological approaches. However, due to several side effects, current therapies show low patient compliance, thus compromising their efficacy and enforcing the need to develop more amenable preventive/therapeutic strategies. In this scenario, medicinal and aromatic plants are a potential source of new effective agents. Specifically, plants from the Allioideae subfamily (formerly Alliaceae family), particularly those from the genus Allium and Tulbaghia, have been extensively used in traditional medicine for the management of several CVDs and associated risk factors, mainly due to the presence of sulphur-containing compounds. Bearing in mind this potential, the present review aims to gather information on traditional uses ascribed to these genera and provide an updated compilation of in vitro and in vivo studies validating these claims as well as clinical trials carried out in the context of CVDs. Furthermore, the effect of isolated sulphur-containing compounds is presented, and whenever possible, the relation between composition and activity and the mechanisms underlying the beneficial effects are pointed out.
Preparation and Performance Characterization of a Composite Film Based on Corn Starch, κ-Carrageenan, and Ethanol Extract of Onion Skin
Authors: Wang Cuntang , Lu Yueyi , Li Ziyu , An Xuanzhe , Gao Zengming , Tian Shengxin
Published: July 2022

Using corn starch (CS) and κ-carrageenan(κC) as the raw material and active composite, respectively, films containing different concentrations of ethanol extract of onion skin were prepared. The effects of different concentrations of ethanol extract of onion skin (EEOS) on the physicochemical properties, as well as the antioxidant and antibacterial properties, of CS/κC films were also discussed. The addition of ethanol extract of onion skin inhibited the recrystallization of starch molecules in the composite films. It affected the microstructure of the composite films. The color of the composite films was deepened, the brightness was reduced, and the opacity was increased. Water vapor permeability increased, tensile strength decreased, and elongation at the break increased. The glass-transition temperature decreased. The clearance of DPPH radicals and ABTS cation radicals increased. Moreover, when the concentration of EEOS was 3%, the antioxidant effect of the films on oil was greatly improved and could effectively inhibit Staphylococcus aureus and Escherichia coli. The above results showed that adding ethanol extract of onion skin improved the physicochemical properties and biological activities of the CS/κC composite films, so CS/κC/EEOS composite films can be used as an active packaging material to extend food shelf-life. These results can provide a theoretical basis for the production and application of corn starch/κ-carrageenan/ethanol extract of onion skin composite films.
Hemicellulose Films from Curaua Fibers (Ananas erectifolius): Extraction and Thermal and Mechanical Characterization
Authors: Roldi-Oliveira Mariana , Diniz Layse M. , Elias Anastasia L. , Luz Sandra M.
Published: July 2022

With growing environmental concerns over synthetic polymers, natural polymeric materials, such as hemicellulose, are considered a good sustainable alternative. Curaua fibers could be an excellent source of biopolymer as they have a relatively high hemicellulose content (15 wt%) and only a small amount of lignin (7 wt%). In this work, hemicellulose was extracted by an alkaline medium using KOH and the influence of the alkali concentration, temperature, and time was studied. A hemicellulose film was produced by water casting and its mechanical, thermal, and morphological properties were characterized. The results show that the best method, which resulted in the highest hemicellulose yield and lowest contamination from lignin, was using 10% (w/v) KOH concentration, 25 °C, and time of 3 h. The hemicellulose film exhibited better thermal stability and elongation at break than other polymeric films. It also exhibited lower rigidity and higher flexibility than other biodegradable polymers, including polylactic acid (PLA) and polyhydroxybutyrate (PHB).
Optimization of Sour Water Stripping Unit Using Artificial Neural Network–Particle Swarm Optimization Algorithm
Authors: Zhang Ye , Fan Zheng , Jing Genhui , Saif Mohammed Maged Ahemd
Published: July 2022

Sour water stripping can treat the sour water produced by crude oil processing, which has the effect of environmental protection, energy saving and emission reduction. This paper aims to reduce energy consumption of the unit by strengthening process parameter optimization. Firstly, the basic model is established by utilizing Aspen Plus, and the optimal model is determined by comparative analysis of back propagation neural network (BPNN), radial basis function neural network (RBFNN) and generalized regression neural network (GRNN) models. Then, the sensitivity analysis of Sobol is used to select the operating variables that have a significant influence on the energy consumption of the sour water stripping system. Finally, the particle swarm optimization (PSO) algorithm is used to optimize the operating conditions of the sour water stripping unit. The results show that the RBFNN model is more accurate than other models. Its network structure is 5-66-1, and the expected value has an approximately linear relationship with the output value. Through sensitivity analysis, it is found that each operating parameter has an impact on the sour water stripping process, which needs to be optimized by the PSO algorithm. After 210 iterations of the PSO algorithm, the optimal system energy consumption is obtained. In addition, the cold/hot feed ratio, sideline production position, tower bottom pressure, hot feed temperature, and cold feed temperature are 0.117, 18, 436 kPa, 146 °C, and 35 °C, respectively; the system energy consumption is 5.918 MW. Compared with value of 7.128 MW before optimization, the energy consumption of the system is greatly reduced by 16.97%, which shows that the energy-saving effect is very significant.
Effect of Plant Growth Regulators on Different Explants of Artemisia ludoviciana under Photoperiod and Darkness Conditions and Their Influence on Achillin Production
Authors: Sánchez-Ramos Mariana , Berman-Bahena Samantha , Alvarez Laura , Sánchez-Carranza Jessica Nayelli , Bernabé-Antonio Antonio , Román-Guerrero Angélica , Marquina-Bahena Silvia , Cruz-Sosa Francisco
Published: July 2022

Species of the genus Artemisia mainly biosynthesize sesquiterpene lactones. Achillin is a guaianolide-type sesquiterpene lactone isolated from Artemisia ludoviciana; it has shown antibacterial and anti-inflammatory activities. In addition, achillin exhibits a significant chemosensitizing effect on hepatocellular carcinoma cells resistant to paclitaxel (PTX). The objective of this study was to establish a callus culture from different explants under conditions of light and total darkness to produce achillin. To obtain in vitro cultures, explants of leaves, nodes, internodes, and roots were used, and they were cultured in MS medium with 0.1 mg/L of kinetin (KIN) or benzyl amino purine (BAP) and/or naphthaleneacetic acid (NAA), 2,4-dichlorophenoxyacetic acid (2,4-D), indole-3-acetic acid (IAA) and 4-amino-3,5,6-trichloro-2-pyridine carboxylic acid (PIC) at 0.1 and 1.0 mg/L. Of all treatments, internodes with BAP (0.1 mg/L) and PIC (1.0 mg/L) grown under photoperiod showed the best friable callus induction, however, GC-MS analysis showed higher achillin content (1703.05 µg/mL) in leaf calluses with PIC (1.0) and KIN (0.1) under photoperiod, and in node plantlets (1880.01 µg/mL) with PIC (0.1) and BAP (0.1). From 12.34 g of dry leaves of Artemisia ludoviciana, 257 mg of achillin were isolated and purified, which was used as a reference in the quantification of achillin in the in vitro culture.
Parameter Identification of Five-Phase Squirrel Cage Induction Motor Based on Extended Kalman Filter
Authors: Luo Xiangyu , Zhao Jinghong , Xiong Yiyong , Xu Hao , Chen Hansi , Zhang Shuheng
Published: July 2022

The use of multiphase electric drives in industrial applications has increased in the last few years. These machines’ advantages over the three-phase system make them appropriate for harsh working situations. To increase their inherent reliability, some authors have been working in sensorless control schemes, where the absence of an encoder ensures proper system performance. Nevertheless, these sensorless control systems present some problems due to the uncertainties of the parameters. In this regard, using extended Kalman filters overcomes this situation, since Kalman filters consider the system error and measurement error in the estimation process. However, when the three-phase Kalman filters are extended to the five-phase case of study, the complexity of the problem increases substantially. In this work, the authors propose an extended Kalman filter, which discomposes the original state equation, reducing the complexity of the estimation stage. In addition, the system suppresses the third-harmonic injection, which enhances the overall phase-current quality.
Evaluation of the Toxicity of Cafeteria Wastewater Treated by a Coupled System (ARFB-SD)
Authors: Hernández-Aguilar Hannia , García-Lara Carlos M. , Nájera-Aguilar Hugo A. , Gutiérrez-Hernández Rubén F. , Martínez-Salinas Rebeca I. , Aguilar Juan A. Araiza
Published: July 2022

In developing countries, achieving greater coverage in the treatment and safe reuse of graywater is a pending task. Therefore, this article presents the results obtained from cafeteria wastewater treatability tests and effluent toxicity tests. For the treatment, a serial system was applied: an aged refuse filled bioreactor (ARFB) and a solar distiller (SD). In the first stage (ARFB), two hydraulic loads (HLs) were tested (200 and 400 L/m3·day), the latter being the best of them, with an average decrease of 95.7% in chemical oxygen demand (COD). In the second stage (SD), the decrease was 62.8%, resulting in a final effluent with 67.7 mg/L COD, which corresponded to a global COD decrease of 97.4%. For the toxicity tests, radish seeds were used in the serial system effluent, obtaining a relative seed germination (RSG) rate of 93.3% compared to 80% obtained in the ARFB effluent. For the percentage germination index (PGI), it was determined that both effluents (ARFB and ARFB-SD) presented a toxicity considered low, especially the ARFB-SD effluent whose PGI value was close to zero (−0.0667). The results obtained showed not only that the ARFB-SD system is efficient in removing the high organic load that can go along with cafeteria wastewater, but also that it can provide an effluent with a very low toxicity level based on the PGI close to zero.
A Feedback Control Strategy for a Fed-Batch Monoclonal Antibody Production Process Utilising Infrequent and Irregular Sampled Measurements
Authors: Joynes Lydia , Zhang Jie
Published: July 2022

The ability to take non-invasive Raman measurements presents a unique opportunity to use one Raman probe across multiple vessels in parallel, reducing costs but making measurements infrequent. Under these conditions, infrequent and irregular feedback signals can result in poor closed-loop control performance. This study addressed the issue of infrequent and irregular Raman measurements using a linear dynamic model developed from interpolated data to predict more frequent measurements of the controlled variable. The simulated monoclonal antibody production was sampled hourly with white noise added to the simulated glucose concentration to replicate real Raman measurements. The hourly samples were interpolated into 15 min intervals and a linear dynamic model was developed to predict the glucose concentration at 15 min intervals. These predicted values were then used in a feedback control loop by using model predictive control or a conventional proportional and integral controller to control the glucose concentration at 15 min sampling intervals. For setpoint tracking, the model predictive control reduced the integral of absolute errors to 14,600 from 15,900 (with a 1 h sampling time) or 8.2% reduction. With adaptive model predictive control, the integral of absolute errors was reduced from 14,500 (1 h sampling time) to 14,200 for setpoint tracking and from 13,500 (1 h sampling time) to 13,300 for disturbance rejection. A final comparison demonstrated that the proposed method can also cope with random variations in the sampling time.
Swarm Crawler Robots Using Lévy Flight for Targets Exploration in Large Environments
Authors: Katada Yoshiaki , Hasegawa Sho , Yamashita Kaito , Okazaki Naoki , Ohkura Kazuhiro
Published: July 2022

This study tackles the task of swarm robotics, where robots explore the environment to detect targets. When a robot detects a target, the robot must be connected with a base station via intermediate relay robots for wireless communication. Our previous results confirmed that Lévy flight outperformed the usual random walk for exploration strategy in an indoor environment. This paper investigated the search performance of swarm crawler robots with Lévy flight on target detection problems in large environments through a series of real robots’ experiments. The results suggest that the swarm crawler robots with Lévy flight succeeded in the target’s discovery in the indoor environment with a 100% success rate, and were able to find several targets in a given time in the outdoor environment. Thus, we confirmed that target exploration in a large environment would be possible by crawler robots with Lévy flight and significant variances in the detection rate among the positions to detect the outdoor environment’s target.
The Spatiotemporal Response of Vegetation Changes to Precipitation and Soil Moisture in Drylands in the North Temperate Mid-Latitudes
Authors: Yu Zongxu , Wang Tianye , Wang Ping , Yu Jingjie
Published: July 2022

Vegetation growth in drylands is highly constrained by water availability. How dryland vegetation responds to changes in precipitation and soil moisture in the context of a warming climate is not well understood. In this study, warm drylands in the temperate zone between 30 and 50° N, including North America (NA), the Mediterranean region (MD), Central Asia (CA), and East Asia (EA), were selected as the study area. After verifying the trends and anomalies of three kinds of leaf area index (LAI) datasets (GLASS LAI, GLEAM LAI, and GLOBAMAP LAI) in the study area, we mainly used the climate (GPCC precipitation and ERA5 temperature), GLEAM soil moisture, and GLASS LAI datasets from 1981 to 2018 to analyze the response of vegetation growth to changes in precipitation and soil moisture. The results of the three mutually validated LAI datasets show an overall greening of dryland vegetation with the same increasing trend of 0.002 per year in LAI over the past 38 years. LAI and precipitation exhibited a strong correlation in the eastern part of the NA drylands and the northeastern part of the EA drylands. LAI and soil moisture exhibited a strong correlation in the eastern part of the NA drylands, the eastern part of the MD drylands, the southern part of the CA drylands, and the northeastern part of the EA drylands. The results of this study will contribute to the understanding of vegetation dynamics and their response to changing water conditions in the Northern Hemisphere midlatitude drylands.
A Quadrifocal Tensor SFM Photogrammetry Positioning and Calibration Technique for HOFS Aerial Sensors
Authors: Wang Tao , Zhang Yan , Zhang Yongsheng , Yu Ying , Li Lei , Liu Shaocong , Zhao Xiang , Zhang Zhenchao , Wang Longhui
Published: July 2022

Nowadays, the integration between photogrammetry and structure from motion (SFM) has become much closer, and many attempts have been made to combine the two approaches to realize the positioning, calibration, and 3D reconstruction of a large number of images. For the positioning and calibration of high oblique frame sweep (HOFS) aerial cameras, a quadrifocal tensor SFM photogrammetry technique is proposed to resolve the positioning and calibration task of such cameras. It adopts the quadrifocal tensor idea into the OpenMVG SFM pipeline to solve the complexity problem caused by the small single-viewing imaging area and the high image overlapping ratio. It also integrates the photogrammetry iteration idea into the OpenMVG SFM pipeline to enhance the positioning and calibration accuracy, which includes a coarse to fine three-stage Bundle Adjustment (BA) processing approach. In this paper, the overall workflow of the proposed technique was first introduced in detail, from feature extraction and image matching, relative rotation and translation estimation, global rotation and translation estimation, and the quadrifocal tensor model construction to the three-stage BA process and calibration. Then, experiments were carried out in the Zhengzhou area, implementing four types of adjustment methods. The results suggest that the proposed quadrifocal tensor SFM photogrammetry is suitable for large tilt frame sweep camera positioning and calibration without prior information on detailed camera intrinsic parameters and structure. The modifications made to the OpenMVG SFM pipeline enhanced the precision of image positioning and calibration and provided the precision level of professional photogrammetry software.
The Influence of Image Properties on High-Detail SfM Photogrammetric Surveys of Complex Geometric Landforms: The Application of a Consumer-Grade UAV Camera in a Rock Glacier Survey
Authors: Martínez-Fernández Adrián , Serrano Enrique , Pisabarro Alfonso , Sánchez-Fernández Manuel , de Sanjosé José Juan , Gómez-Lende Manuel , Rangel-de Lázaro Gizéh , Benito-Calvo Alfonso
Published: July 2022

The detailed description of processing workflows in Structure from Motion (SfM) surveys using unmanned aerial vehicles (UAVs) is not common in geomorphological research. One of the aspects frequently overlooked in photogrammetric reconstruction is image characteristics. In this context, the present study aims to determine whether the format or properties (e.g., exposure, sharpening, lens corrections) of the images used in the SfM process can affect high-detail surveys of complex geometric landforms such as rock glaciers. For this purpose, images generated (DNG and JPEG) and derived (TIFF) from low-cost UAV systems widely used by the scientific community are applied. The case study is carried out through a comprehensive flight plan with ground control and differences among surveys are assessed visually and geometrically. Thus, geometric evaluation is based on 2.5D and 3D perspectives and a ground-based LiDAR benchmark. The results show that the lens profiles applied by some low-cost UAV cameras to the images can significantly alter the geometry among photo-reconstructions, to the extent that they can influence monitoring activities with variations of around ±5 cm in areas with close control and over ±20 cm (10 times the ground sample distance) on surfaces outside the ground control surroundings. The terrestrial position of the laser scanner measurements and the scene changing topography results in uneven surface sampling, which makes it challenging to determine which set of images best fit the LiDAR benchmark. Other effects of the image properties are found in minor variations scattered throughout the survey or modifications to the RGB values of the point clouds or orthomosaics, with no critical impact on geomorphological studies.
Spectral Analysis to Improve Inputs to Random Forest and Other Boosted Ensemble Tree-Based Algorithms for Detecting NYF Pegmatites in Tysfjord, Norway
Authors: Santos Douglas , Cardoso-Fernandes Joana , Lima Alexandre , Müller Axel , Brönner Marco , Teodoro Ana Cláudia
Published: July 2022

As an important source of lithium and rare earth elements (REE) and other critical elements, pegmatites are of great strategic economic interest for present and future technological development. Identifying new pegmatite deposits is a strategy adopted by the European Union (EU) to decrease its import dependence on non-European countries for these raw materials. It is in this context that the GREENPEG project was established, an EU project whose main objective is to identify new deposits of pegmatites in Europe in an environmentally friendly way. Remote sensing is a non-contact exploration tool that allows for identifying areas of interest for exploration at the early stage of exploration campaigns. Several RS methods have been developed to identify Li-Cs-Ta (LCT) pegmatites, but in this study, a new methodology was developed to detect Nb-Y-F (NYF) pegmatites in the Tysfjord area in Norway. This methodology is based on spectral analysis to select bands of the Sentinel 2 satellite and adapt RS methods, such as Band Ratios and Principal Component Analysis (PCA), to be used as input in the Random Forest (RF) and other tree-based ensemble algorithms to improve the classification accuracy. The results obtained are encouraging, and the algorithm was able to successfully identify the pegmatite areas already known and new locations of interest for exploration were also defined.
Estimating the Optimal Threshold for Accuracy Assessment of the Global Ecosystem Dynamics Investigation (GEDI) Data in a Gentle Relief Urban Area
Authors: Barbosa Felipe Lima Ramos , Guimarães Renato Fontes , de Carvalho Júnior Osmar Abílio , Gomes Roberto Arnaldo Trancoso , de Carvalho Osmar Luiz Ferreira , de Lima Thyego Pery Monteiro
Published: July 2022

LiDAR is an excellent source of elevation data used in many surveys. The spaceborne handle system, Global Ecosystem Dynamics Investigation (GEDI), provides ground elevation information with high accuracy except for areas with steep slopes. GEDI data have a lot of noise from atmospheric conditions, and therefore filtering procedures are mandatory to select the best dataset. The dataset presents uncertainties of different magnitudes, with values reaching more than 100 m of difference between the reference data and the GEDI data. The challenge is to find a criterion to determine a threshold to filter accurate GEDI samples. This research aims to identify the threshold based on the difference values between the reference data and the GEDI data to select the maximum number of samples with low RMSE values. Therefore, we used the Kolmogorov–Smirnov (KS) non-parametric test to define the best threshold based on a normal distribution. Our results demonstrated a lower RMSE value with a high number of samples when compared with the quality flag parameter threshold, even using sensitivity parameter thresholds. This method is useful for achieving the best possible accuracy from GEDI data worldwide.
Performance Analysis of BDS-3 SAIM and Enhancement Research on Autonomous Satellite Ephemeris Monitoring
Authors: Chen Lei , Dai Yongshan , Gao Weiguang , Cao Yueling , Hu Zhigang , Ren Qianyi , Nie Xin , Zheng Jiaju , Shao Ruiqiang , Pei Ling , Wang Lu
Published: July 2022

Integrity is one of the key indicators used to characterize the performance of the global navigation satellite systems (GNSSs) and is closely related to user safety. In order to realize real-time global integrity monitoring, the BeiDou Global Navigation Satellite System (BDS-3) has realized the “satellite autonomous integrity monitoring” (SAIM) function in its satellites for the first time. BDS-3 SAIM has the monitoring functions of signal power, pseudo-range, satellite clock frequency and phase, but not the monitoring function of broadcast ephemeris. In this study, the long-term stability and distribution characteristics of BDS-3 SAIM monitoring data were analyzed by using the actual telemetry data for the first time. The results show that the SAIM monitoring data have good long-term stability and basically follow a normal distribution, which meets the design expectations. Meanwhile, in view of the fact that BDS-3 SAIM does not have the ability to independently monitor broadcast ephemerides, which may lead to the over-tolerance of BDS-3 to the probability risk of risks of integrity in the active space environment, a SAIM enhancement design for ephemeris monitoring is proposed, which integrates three relatively independent methods, with the ephemeris extrapolated from the previous cycle, and the ephemeris generated by autonomous orbit determination, inter-satellite link distance measurement data as reference data, respectively. The three methods are analyzed and verified. The results show that each of the three methods has advantages and disadvantages in terms of monitoring accuracy and resource dependence. The integration of the three methods can combine their complementary advantages and can also provide valuable as an important reference for engineering applications.
Remote-Sensing-Based Assessment of the Ecological Restoration Degree and Restoration Potential of Ecosystems in the Upper Yellow River over the Past 20 Years
Authors: Liu Shuchao , Shao Quanqin , Ning Jia , Niu Linan , Zhang Xiongyi , Liu Guobo , Huang Haibo
Published: July 2022

The Upper Yellow River is the most important area for water retention and flow production in the Yellow River basin, and the statuses of the ecosystems in this region are related to the ecological stability of the whole Yellow River basin. In this paper, the fractional vegetation cover (FVC), net primary productivity (NPP) of vegetation and water retention, soil retention, and windbreak and sand fixation services of the Upper Yellow River ecosystems were analysed from 2000 to 2019 with the trend analysis method. Ecological restoration degree evaluation indices were constructed to comprehensively assess the ecological restoration situation and restoration potential of the ecosystems in the Upper Yellow River region over the past 20 years and to quantitatively determine the contribution rates of climate factors and human activities to these ecosystem changes. The results showed that the settlement ecosystem area exhibited the greatest increase, while the grassland ecosystem area decreased significantly over the study period. In the Upper Yellow River region, the ecosystem quality and ecosystem services generally remained stable or improved. Areas with moderately, strongly and extremely improved ecological restoration degrees accounted for 32.9%, 21.0% and 2.8% of the entire Upper Yellow River region, respectively. Areas with strongly improved and extremely improved ecological restoration degrees were mainly distributed in the Loess Plateau gully areas and on the eastern Hetao Plain. The contribution rates of climatic factors and human activities to the NPP changes measured in the Upper Yellow River were 81.6% and 18.4%, respectively, while the contribution rates of these processes to soil erosion modulus changes were 77.6% and 22.4%, respectively. The restoration potential index of the FVC in the Upper Yellow River was 22.7%; that of the forest vegetation coverage was 14.4%; and that of the grassland vegetation coverage was 23.0%. Over the past 20 years, the ecosystems in the Upper Yellow River region have improved and recovered significantly. This study can provide scientific support for the next stage of ecological projects in the Upper Yellow River region.
A Hybrid-Order Spectral-Spatial Feature Network for Hyperspectral Image Classification
Authors: Liu Dongxu , Han Guangliang , Liu Peixun , Wang Yirui , Yang Hang , Chen Dianbing , Li Qingqing , Wu Jiajia
Published: July 2022

Convolutional neural networks are widely applied in hyperspectral image (HSI) classification and show excellent performance. However, there are two challenges: the first is that fine features are generally lost in the process of depth transfer; the second is that most existing studies usually restore to first-order features, whereas they rarely consider second-order representations. To tackle the above two problems, this article proposes a hybrid-order spectral-spatial feature network (HS2FNet) for hyperspectral image classification. This framework consists of a precedent feature extraction module (PFEM) and a feature rethinking module (FRM). The former is constructed to capture multiscale spectral-spatial features and focus on adaptively recalibrate channel-wise and spatial-wise feature responses to achieve first-order spectral-spatial feature distillation. The latter is devised to heighten the representative ability of HSI by capturing the importance of feature cross-dimension, while learning more discriminative representations by exploiting the second-order statistics of HSI, thereby improving the classification performance. Massive experiments demonstrate that the proposed network achieves plausible results compared with the state-of-the-art classification methods.
Estimation of Greenhouse Lettuce Growth Indices Based on a Two-Stage CNN Using RGB-D Images
Authors: Gang Min-Seok , Kim Hak-Jin , Kim Dong-Wook
Published: July 2022

Growth indices can quantify crop productivity and establish optimal environmental, nutritional, and irrigation control strategies. A convolutional neural network (CNN)-based model is presented for estimating various growth indices (i.e., fresh weight, dry weight, height, leaf area, and diameter) of four varieties of greenhouse lettuce using red, green, blue, and depth (RGB-D) data obtained using a stereo camera. Data from an online autonomous greenhouse challenge (Wageningen University, June 2021) were employed in this study. The data were collected using an Intel RealSense D415 camera. The developed model has a two-stage CNN architecture based on ResNet50V2 layers. The developed model provided coefficients of determination from 0.88 to 0.95, with normalized root mean square errors of 6.09%, 6.30%, 7.65%, 7.92%, and 5.62% for fresh weight, dry weight, height, diameter, and leaf area, respectively, on unknown lettuce images. Using red, green, blue (RGB) and depth data employed in the CNN improved the determination accuracy for all five lettuce growth indices due to the ability of the stereo camera to extract height information on lettuce. The average time for processing each lettuce image using the developed CNN model run on a Jetson SUB mini-PC with a Jetson Xavier NX was 0.83 s, indicating the potential for the model in fast real-time sensing of lettuce growth indices.
A Sample of Resilient Intercultural Coexistence in Ethnic Hungarian, Serbian and Bulgarian Communities in Western Romania
Authors: Berceanu Iancu-Constantin , Popa Nicolae
Published: July 2022

This article sets out to highlight the way in which the phenomena of co-construction and territorial deconstruction make themselves apparent locally. We focused our study on Timiș County, core of the historical Banat region, for the reason that it is still an ethno-cultural mosaic linked to its cross-border space. We based our analysis on the exploitation of a specific bibliography and, especially, on a survey through questionnaire and interview. The regional socio-cultural identity of Banat was founded on the dialogue and intercultural co-construction that have been practised since 1718. The repeated processes of socio-spatial co-construction and deconstruction, due to the changes of sovereignty and limits, prove a remarkable identity resilience, Banat being a model of continuity of regional territoriality. In the current context of European integration and of regionalisation, these processes have been reactivated, with the ethnic minorities cultivating solidarity with their co-nationals over the border while also preserving solidarity with the present host country, Romania.
Mode Choice Modeling for Sustainable Last-Mile Delivery: The Greek Perspective
Authors: Polydoropoulou Amalia , Tsirimpa Athena , Karakikes Ioannis , Tsouros Ioannis , Pagoni Ioanna
Published: July 2022

As the private sector is under heavy pressure to serve the ever-growing e-commerce market, the potential of implementing new disruptive mobility/logistics services for increasing the level of the current last-mile delivery (LMD) services, is emerging. Vehicle automation technology, characterized by high-capacity utilization and asset intensity, appears to be a prominent response to easing this pressure, while contributing to mitigation of the adverse effects associated with the deployment of LMD activities. This research studied the perceptions of Greek end-users/consumers, regarding the introduction of autonomous/automated/driverless vehicles (AVs) in innovative delivery services. To achieve this, a mixed logit model was developed, based on a Stated Preferences (SP) experiment, designed to capture the demand of alternative last-mile delivery modes/services, such as drones, pods, and autonomous vans, compared to traditional delivery services. The results show that the traditional delivery, i.e., having a dedicated delivery person who picks up the parcels at a consolidation point and delivers them directly to the recipients while driving a non-autonomous vehicle—conventional van, bike, e-bike, e-scooter—remains the most acceptable delivery method. Moreover, the analysis indicated that there is no interest yet in deploying home deliveries with drones or AVs, and that participants are unwilling to pay extra charges for having access to more advanced last-mile delivery modes/services. Thus, it is important to promote the benefits of innovative modes and services for LMD, in order to increase public awareness and receptivity in Greece.
Best Practice of Using Digital Business Simulation Games in Business Education
Authors: Peterková Jindra , Repaská Zuzana , Prachařová Lenka
Published: July 2022

Information technologies play an important role in designing new ways of teaching, and, at the same time, the globalization of the business world affects the quality of human capital that the corporate sector requires. Apart from theoretical business understanding, multidisciplinary knowledge is also needed. Business simulation games belong among suitable educational tools, which are able to respond to contemporary business requirements and the requirements of students. Business simulation games provide a useful tool for experiential learning by university students studying business programs. For the effective development of students’ competencies in economic and managerial fields of study, it is necessary to apply appropriate steps in the implementation of simulation games and to understand the experience of students in the use of games in the teaching process. For that purpose, best practice for business simulation games has been determined. This introduced best practice includes description of the benefits from realized simulation games, from the lecturer point of view. A realized survey focused on the main benefits considered by students who completed the subject Managerial Simulation Game. The students’ approach to the implemented simulation games was gradually monitored over the course of five academic years. Research samples contain 148 students from the first year of a master’s study program. Our survey showed that the subject is more beneficial for students for their further study than for their future professions. At the same time, the vast majority of students perceive simulation games as a useful and interesting way to verify the dependencies between economic variables. To strengthen analytical skills, it is necessary to introduce tasks that support working with economic data through simulation games. The novelty of the paper consists of mapping the benefits from the implemented simulation games for the student’s own person, categorizing the identified benefits into six groups with the same characteristics, and, at the same time, implementing the research for students attending private and public schools.
Optimization Models of Actuated Control Considering Vehicle Queuing for Sustainable Operation
Authors: Wang Xinyue , Wu Xianyu , Liu Jiarui
Published: July 2022

How to sustainably conduct intersection operations is a key issue of the current research. For an actuated control intersection, queued vehicles, control parameters, and phase schemes all affect the operation effect. This paper discusses queued vehicles at actuated intersections and their influence on signal timing. First, this paper establishes an improved traffic wave model and proposes a vehicle queuing model on this basis. Second, by analyzing the queuing and dispersion process of queued vehicles, a minimal green time calculation model is proposed. Then, this paper establishes a maximal green time calculation model aiming at minimizing average vehicle delay and maximizing traffic capacity under different phase schemes, and considers the influence of queued vehicles. Lastly, the models are verified separately; results show that the average error of the minimal green time model was 4.18%, and the average optimization rate of the maximal green time model was 9.27%. It is proved that the models achieved great accuracy and optimization effects, which could potentially improve intersection sustainability.
Integrated Stochastic Life Cycle Assessment and Techno-Economic Analysis for Shrub Willow Production in the Northeastern United States
Authors: Frank Jenny , Therasme Obste , Volk Timothy A. , Brown Tristan , Malmsheimer Robert W. , Fortier Marie-Odile , Eisenbies Mark H. , Ha HakSoo , Heavey Justin
Published: July 2022

The refereed literature contains few studies that analyze life cycle assessment (LCA) and techno-economic analysis (TEA) methodologies together for lignocellulosic bioenergy systems, using a stochastic modeling approach. This study seeks to address this gap by developing an integrated framework to quantify the environmental and financial impacts of producing and delivering shrub willow in the Northeastern United States. This study analyses four different scenarios from a combination of two different initial land cover types (grassland, cropland) prior to willow establishment, and two harvesting conditions (leaf-on, leaf-off). Monte Carlo simulations were performed to quantify the uncertainty of the results based on a range of financial, logistical, and biophysical variable input parameters (e.g., land rental rates, transportation distance, biomass yield, etc.). Growing willow biomass on croplands resulted in net negative GHG emissions for both leaf on and leaf off scenarios for the baseline. The GHG emissions were lowest for the leaf-off harvest on cropland (−172.50 kg CO2eq Mg−1); this scenario also had the lowest MSP ($76.41 Mg−1). The baseline grassland scenario with leaf-on harvest, results in the highest net GHG emissions (44.83 kg CO2eq Mg−1) and greatest MSP ($92.97 Mg−1). The results of this analysis provide the bioenergy field and other interested stakeholders with both environmental and financial trade-offs of willow biomass to permit informed decisions about the future expansion of willow fields in the landscape, which have the potential to contribute to GHG reduction targets and conversion into fuels, energy, or bioproducts for carbon sequestration and financial benefits.
Knowledge Management-Based Mental Health Service Model: Sustainable Application during College Students’ Education
Authors: Zhang Cuixia , Yang Yaliu , Liu Conghu
Published: July 2022

In order to meet the dynamic mental health needs of college students, it is important to promote quality mental health services and to improve the development view of college students’ mental health. This paper uses a knowledge management method to construct college students’ developmental mental health service model. The model is informed by knowledge management, which comprehensively considers service-related components, namely, resources, content, approach, process, personnel, and objects. Furthermore, knowledge management constructs the system structure of the model and expands the research ideas and contents of the service resource pool. Moreover, knowledge management supports the platform, core technology system, and service process in the model. Finally, using Suzhou University as an example, this study examines the implementation and application of the service model to test the effectiveness of the knowledge management method. Thus, this study provides theoretical and methodological support for the construction, implementation, and application of a sustainable mental health service model for college students.
The Role of the Cultural and Creative Industries in Sustainable Development of Small Cities in Latvia
Authors: Zemite Ieva , Kunda Ilona , Judrupa Ilze
Published: July 2022

While sustainability is a much-researched issue, little has been written about the role of cultural and creative industries (CCIs) in implementing sustainable development, specifically in small cities. The authors pose the following questions: What is the interrelation between CCI practices and the four pillars of sustainability (economic, environmental, cultural, and social) in small cities? What are the practices that CCIs use, and which they perceive as contributions to sustainable development? The authors use a single case study strategy, methods including a theoretical study, a quantitative pilot survey, a focus group discussion, semi-structured interviews, and content analysis. Overall, the article indicates that there is a varied and diverse repertoire of small- and large-scale practices carried out by CCIs in small cities in Latvia, and thus contributes to the existing scholarly literature by “teasing out” those practices. The study indicates that each of the practices may contribute to two or more sustainability pillars, thus they are analyzed in pairs to find out what traits are reflected in these practices. Notably, CCI entrepreneurs believe that sustainable development is important and that they contribute to it.
Developing the Use of Wool Rope within Aquaculture—A Systematic Review
Authors: Drury Katherine Elizabeth , Crotty Felicity Victoria
Published: July 2022

To date, wool is an underutilised sustainable resource that has the potential to reduce the use of plastic within the environment. Wool can be manufactured as rope, but is this a viable innovation? To gain a comprehensive understanding of the economic viability of utilising wool rope in seaweed aquaculture, a systematic literature review was undertaken. The review focuses on wool, rope, natural and man-made fibres and seaweed farming, and used bibliometric and content analysis of peer-reviewed papers, with no timeframe requirements. It is important to explore alternative materials to reduce marine rope pollution; ghost gear, microplastics from abrasion and plasticrusts are now believed to be significant ecological problems. To date, the production of wool rope is limited, and its strength and durability within the fishing industry remain untested. It is important to understand whether wool rope is a useful alternative: does it have the same tensile strength, and can it be used within the industry without the risk of damage to the environment? There is currently a lack of research on natural rope fibres, resulting in limited access to commercial rope alternatives being used within the industry. This systematic review shows that there has been a large gap in wool research, with limited publications in recent years; however, the drive to increase sustainability (particularly within the marine environment) has increased. This is the first paper that combines both topics within one research study. Further research is needed to identify whether wool rope will provide a feasible alternative to polypropylene in terms of strength and durability, and how wool rope will perform, the length of time it can provide optimum service and within which seaweed farming practice it can offer a practical alternative to polypropylene.
Motivation and Performance of Students in School Physical Education in Which Mobile Applications Are Used
Authors: Maněnová Martina , Knajfl Pavel , Wolf Janet
Published: July 2022

The aim of the text is to discuss the use of technologies in Physical Education (PE) at schools. The research focused on the pupils of an upper-primary school/lower-secondary school, who were given experimental PE for a period of 10 weeks. The research objective was to identify typical groups of students on the basis of their physical performances and motivation. Unifittest 6-60, a standardized motor-skills test, was used to measure physical performances, and the Czech translation of SIMS, a Canadian–American standardized test, was used to specify the degree of motivation. Based on the obtained data, the method of cluster analysis identified three typical groups of pupils. These three groups differ in their approach to the use of mobile applications in the process of PE. The research results show that thanks to the implementation of mobile phones in the process of PE and thanks to a different approach taken by the teacher, increased internal motivation and an increase in identified regulation can be seen, as well as a decrease in amotivation and a rapid increase in motor performances, especially in the case of students whose performances are average or below average in usual PE classes.