bluuebunny/crossref_metadata_2025 huggingface dataset:
The Influence of Intermolecular Interactions between Maleic Anhydride, Cellulose Nanocrystal, and Nisin-Z on the Structural, Thermal, and Antimicrobial Properties of Starch-PVA Plasticized Matrix
Authors: Oliveira Taíla V. de , Freitas Pedro A. V. de , Pola Cicero C. , Terra Larissa R. , Silva José O. R. da , Badaró Amanda T. , Junior Nelson S. , Oliveira Marciano M. de , Silva Rafael R. A. , Soares Nilda de F. F.
Published: August 2021

On behalf of a circular economy, regular plastics have been replaced by biodegradable packagings. Besides, active films have been applied to improve the shelf-life and quality of foods. In this work, blends were developed using starch as a low-cost natural polymer, mixed with poly(vinyl alcohol) due to its physical-chemical and biodegradable properties. Moreover, maleic anhydride (MaAh), cellulose-nanocrystal (CN), and nisin-z (N-Z) were added, respectively, as a compatibilizer, a mechanical-reinforce, and antimicrobial agents. The thermal stability of the films was analyzed, which blends’ melting temperature occurred around 200–207 °C, and it was influenced by CN, N-Z, and MaAh amounts. N-Z and MaAh acted against S. aureus and P. aeruginosa by compound diffusion (inhibition-halo around 1.85 and 2.18 cm); while S. Choleraesuis and E. coli were inhibited by contact. Therefore, these blends presented the potential to be used as active biodegradable packaging in the food industry.
“They Remembered That They Had Seen It in a Jewish Midrash”: How a Samaritan Tale Became a Legend of the Jews
Authors: Fine Steven
Published: August 2021

This article relates the transmission history of a single Samaritan text and its fascinating trajectory from a Samaritan legend into early modern rabbinic tradition, and on to nineteenth and early twentieth century Jewish studies circles. It focuses on the only Samaritan narrative cited in all of Louis Ginzberg’s monumental Legends of the Jews (1909–1938). Often called the “Epistle of Joshua son of Nun,” I trace the trajectory of this story from a medieval Samaritan chronicle to Samuel Sulam’s 1566 publication of Abraham Zacuto’s Sefer Yuḥasin. From there, we move to early modern belles lettres in Hebrew and Yiddish, western scholarship and then to the great Jewish anthologizers of the fin de siècle, Micha Yosef Berdyczewski, Judah David Eisenstein and Louis Ginzberg. I will suggest reasons why this tale was so appealing to Sulam, a Sephardi scholar based in Istanbul, that he appended it to Sefer Yuḥasin, and what about this tale of heroism ingratiated it to early modern European and then early Zionist readers. The afterlife of this tale is a rare instance of Samaritan influence upon classical Jewish literature, undermining assumptions of unidirectional Jewish influence upon the minority Samaritan culture from antiquity to modern times.
Innovative UAV LiDAR Generated Point-Cloud Processing Algorithm in Python for Unsupervised Detection and Analysis of Agricultural Field-Plots
Authors: Polák Michal , Miřijovský Jakub , Hernándiz Alba E. , Špíšek Zdeněk , Koprna Radoslav , Humplík Jan F.
Published: August 2021

The estimation of plant growth is a challenging but key issue that may help us to understand crop vs. environment interactions. To perform precise and high-throughput analysis of plant growth in field conditions, remote sensing using LiDAR and unmanned aerial vehicles (UAV) has been developed, in addition to other approaches. Although there are software tools for the processing of LiDAR data in general, there are no specialized tools for the automatic extraction of experimental field blocks with crops that represent specific “points of interest”. Our tool aims to detect precisely individual field plots, small experimental plots (in our case 10 m2) which in agricultural research represent the treatment of a single plant or one genotype in a breeding trial. Cutting out points belonging to the specific field plots allows the user to measure automatically their growth characteristics, such as plant height or plot biomass. For this purpose, new method of edge detection was combined with Fourier transformation to find individual field plots. In our case study with winter wheat, two UAV flight levels (20 and 40 m above ground) and two canopy surface modelling methods (raw points and B-spline) were tested. At a flight level of 20 m, our algorithm reached a 0.78 to 0.79 correlation with LiDAR measurement with manual validation (RMSE = 0.19) for both methods. The algorithm, in the Python 3 programming language, is designed as open-source and is freely available publicly, including the latest updates.
Performance Evaluation of Long NDVI Timeseries from AVHRR, MODIS and Landsat Sensors over Landslide-Prone Locations in Qinghai-Tibetan Plateau
Authors: Sajadi Payam , Sang Yan-Fang , Gholamnia Mehdi , Bonafoni Stefania , Brocca Luca , Pradhan Biswajeet , Singh Amit
Published: August 2021

The existence of several NDVI products in Qinghai-Tibetan Plateau (QTP) makes it challenging to identify the ideal sensor for vegetation monitoring as an important factor for landslide detection studies. A pixel-based analysis of the NDVI time series was carried out to compare the performances of five NDVI products, including ETM+, OLI, MODIS Series, and AVHRR sensors in QTP. Harmonic analysis of time series and wavelet threshold denoising were used for reconstruction and denoising of the five NDVI datasets. Each sensor performance was assessed based on the behavioral similarity between the original and denoised NDVI time series, considering the preservation of the original shape and time series values by computing correlation coefficient (CC), mean absolute error (MAE), root mean square error (RMSE), and signal to noise ratio (SNR). Results indicated that the OLI slightly outperformed the other sensors in all performance metrics, especially in mosaic natural vegetation, grassland, and cropland, providing 0.973, 0.015, 0.022, and 27.220 in CC, MAE, RMSE, and SNR, respectively. AVHRR showed similar results to OLI, with the best results in the predominant type of land covers (needle-leaved, evergreen, closed to open). The MODIS series performs lower across all vegetation classes than the other sensors, which might be related to the higher number of artifacts observed in the original data. In addition to the satellite sensor comparison, the proposed analysis demonstrated the effectiveness and reliability of the implemented methodology for reconstructing and denoising different NDVI time series, indicating its suitability for long-term trend analysis of different natural land cover classes, vegetation monitoring, and change detection.
Feature Merged Network for Oil Spill Detection Using SAR Images
Authors: Fan Yonglei , Rui Xiaoping , Zhang Guangyuan , Yu Tian , Xu Xijie , Poslad Stefan
Published: August 2021

The frequency of marine oil spills has increased in recent years. The growing exploitation of marine oil and continuous increase in marine crude oil transportation has caused tremendous damage to the marine ecological environment. Using synthetic aperture radar (SAR) images to monitor marine oil spills can help control the spread of oil spill pollution over time and reduce the economic losses and environmental pollution caused by such spills. However, it is a significant challenge to distinguish between oil-spilled areas and oil-spill-like in SAR images. Semantic segmentation models based on deep learning have been used in this field to address this issue. In addition, this study is dedicated to improving the accuracy of the U-Shape Network (UNet) model in identifying oil spill areas and oil-spill-like areas and alleviating the overfitting problem of the model; a feature merge network (FMNet) is proposed for image segmentation. The global features of SAR image, which are high-frequency component in the frequency domain and represents the boundary between categories, are obtained by a threshold segmentation method. This can weaken the impact of spot noise in SAR image. Then high-dimensional features are extracted from the threshold segmentation results using convolution operation. These features are superimposed with to the down sampling and combined with the high-dimensional features of original image. The proposed model obtains more features, which allows the model to make more accurate decisions. The overall accuracy of the proposed method increased by 1.82% and reached 61.90% compared with the UNet. The recognition accuracy of oil spill areas and oil-spill-like areas increased by approximately 3% and reached 56.33%. The method proposed in this paper not only improves the recognition accuracy of the original model, but also alleviates the overfitting problem of the original model and provides a more effective monitoring method for marine oil spill monitoring. More importantly, the proposed method provides a design principle that opens up new development ideas for the optimization of other deep learning network models.
Joint Retrieval of Winter Wheat Leaf Area Index and Canopy Chlorophyll Density Using Hyperspectral Vegetation Indices
Authors: Xing Naichen , Huang Wenjiang , Ye Huichun , Ren Yu , Xie Qiaoyun
Published: August 2021

Leaf area index (LAI) and canopy chlorophyll density (CCD) are key biophysical and biochemical parameters utilized in winter wheat growth monitoring. In this study, we would like to exploit the advantages of three canonical types of spectral vegetation indices: indices sensitive to LAI, indices sensitive to chlorophyll content, and indices suitable for both parameters. In addition, two methods for joint retrieval were proposed. The first method is to develop integration-based indices incorporating LAI-sensitive and CCD-sensitive indices. The second method is to create a transformed triangular vegetation index (TTVI2) based on the spectral and physiological characteristics of the parameters. PROSAIL, as a typical radiative transfer model embedded with physical laws, was used to build estimation models between the indices and the relevant parameters. Validation was conducted against a field-measured hyperspectral dataset for four distinct growth stages and pooled data. The results indicate that: (1) the performance of the integrated indices from the first method are various because of the component indices; (2) TTVI2 is an excellent predictor for joint retrieval, with the highest R2 values of 0.76 and 0.59, the RMSE of 0.93 m2/m2 and 104.66 μg/cm2, and the RRMSE (Relative RMSE) of 12.76% and 16.96% for LAI and CCD, respectively.
Raindrop Size Distributions of North Indian Ocean Tropical Cyclones Observed at the Coastal and Inland Stations in South India
Authors: Seela Balaji Kumar , Janapati Jayalakshmi , Kalath Unnikrishnan Chirikandath , Lin Pay-Liam , Le Loh Jui , Chang Wei-Yu , Kumar Utpal , Reddy K. Krishna , Lee Dong-In , Venkatrami Reddy Mannem
Published: August 2021

The current study summarizes the raindrop size distributions (RSDs) characteristic of the North Indian Ocean (NIO) tropical cyclones (TCs) measured with ground-based disdrometers installed at the coastal (Thiruvananthapuram, 8.5335°N, 76.9047°E) and inland (Kadapa, 14.4742°N, 78.7098°E) stations in south India. The NIO TCs observed at the coastal station showed more mid- and large-size drops (>1 mm) than the inland station. On the other hand, for both inland and coastal stations, small and mid-size drops (<3 mm) primarily contributed to the total number concentration and rainfall rate. The RSDs of the NIO TCs segregated into precipitation types (stratiform and convective) demonstrated the presence of more mid- and large-size drops at the coastal station. The RSD relations of the NIO TCs, which are used in rain retrieval algorithms of remote sensing (global precipitation measurement) radars, exhibited contrasts between the coastal and inland station. Further, the NIO TCs’ rainfall kinetic energy relations, which are crucial in rainfall erosivity studies, estimated for the coastal station revealed dissimilar characteristics to that of the inland station. The conceivable thermo-dynamical and microphysical processes that are accountable for the disparities in the NIO TCs RSDs measured at the coastal and inland stations are also elucidated in this work.
Elongated Small Object Detection from Remote Sensing Images Using Hierarchical Scale-Sensitive Networks
Authors: He Zheng , Huang Li , Zeng Weijiang , Zhang Xining , Jiang Yongxin , Zou Qin
Published: August 2021

The detection of elongated objects, such as ships, from satellite images has very important application prospects in marine transportation, shipping management, and many other scenarios. At present, the research of general object detection using neural networks has made significant progress. However, in the context of ship detection from remote sensing images, due to the elongated shape of ship structure and the wide variety of ship size, the detection accuracy is often unsatisfactory. In particular, the detection accuracy of small-scale ships is much lower than that of the large-scale ones. To this end, in this paper, we propose a hierarchical scale sensitive CenterNet (HSSCenterNet) for ship detection from remote sensing images. HSSCenterNet adopts a multi-task learning strategy. First, it presents a dual-direction vector to represent the posture or direction of the tilted bounding box, and employs a two-layer network to predict the dual direction vector, which improves the detection block of CenterNet, and cultivates the ability of detecting targets with tilted posture. Second, it divides the full-scale detection task into three parallel sub-tasks for large-scale, medium-scale, and small-scale ship detection, respectively, and obtains the final results with non-maximum suppression. Experimental results show that, HSSCenterNet achieves a significant improved performance in detecting small-scale ship targets while maintaining a high performance at medium and large scales.
Smart Health-Enhanced Early Mobilisation in Intensive Care Units
Authors: Ferre Maria , Batista Edgar , Solanas Agusti , Martínez-Ballesté Antoni
Published: August 2021

Critically ill patients that stay in Intensive Care Units (ICU) for long periods suffer from Post-Intensive Care Syndrome or ICU Acquired Weakness, whose effects can decrease patients’ quality of life for years. To prevent such issues and aiming at shortening intensive care treatments, Early Mobilisation (EM) has been proposed as an encouraging technique: the literature includes numerous examples of the benefits of EM on the prevention of post-operative complications and adverse events. However, the appropriate application of EM programmes entails the use of scarce resources, both human and technical. Information and Communication Technologies can play a key role in reducing cost and improving the practice of EM. Although there is rich literature on EM practice and its potential benefits, there are some barriers that must be overcome, and technology, i.e., the use of sensors, robotics or information systems, can contribute to that end. This article reviews the literature and analyses on the use of technology in the area of EM, and moreover, it proposes a smart health-enhanced scenario.
Endoscopic Image-Based Skill Assessment in Robot-Assisted Minimally Invasive Surgery
Authors: Lajkó Gábor , Nagyné Elek Renáta , Haidegger Tamás
Published: August 2021

Objective skill assessment-based personal performance feedback is a vital part of surgical training. Either kinematic—acquired through surgical robotic systems, mounted sensors on tooltips or wearable sensors—or visual input data can be employed to perform objective algorithm-driven skill assessment. Kinematic data have been successfully linked with the expertise of surgeons performing Robot-Assisted Minimally Invasive Surgery (RAMIS) procedures, but for traditional, manual Minimally Invasive Surgery (MIS), they are not readily available as a method. 3D visual features-based evaluation methods tend to outperform 2D methods, but their utility is limited and not suited to MIS training, therefore our proposed solution relies on 2D features. The application of additional sensors potentially enhances the performance of either approach. This paper introduces a general 2D image-based solution that enables the creation and application of surgical skill assessment in any training environment. The 2D features were processed using the feature extraction techniques of a previously published benchmark to assess the attainable accuracy. We relied on the JHU–ISI Gesture and Skill Assessment Working Set dataset—co-developed by the Johns Hopkins University and Intuitive Surgical Inc. Using this well-established set gives us the opportunity to comparatively evaluate different feature extraction techniques. The algorithm reached up to 95.74% accuracy in individual trials. The highest mean accuracy—averaged over five cross-validation trials—for the surgical subtask of Knot-Tying was 83.54%, for Needle-Passing 84.23% and for Suturing 81.58%. The proposed method measured well against the state of the art in 2D visual-based skill assessment, with more than 80% accuracy for all three surgical subtasks available in JIGSAWS (Knot-Tying, Suturing and Needle-Passing). By introducing new visual features—such as image-based orientation and image-based collision detection—or, from the evaluation side, utilising other Support Vector Machine kernel methods, tuning the hyperparameters or using other classification methods (e.g., the boosted trees algorithm) instead, classification accuracy can be further improved. We showed the potential use of optical flow as an input for RAMIS skill assessment, highlighting the maximum accuracy achievable with these data by evaluating it with an established skill assessment benchmark, by evaluating its methods independently. The highest performing method, the Residual Neural Network, reached means of 81.89%, 84.23% and 83.54% accuracy for the skills of Suturing, Needle-Passing and Knot-Tying, respectively.
Pelvis-Toe Distance: 3-Dimensional Gait Characteristics of Functional Limb Shortening in Hemiparetic Stroke
Authors: Haruyama Koshiro , Kawakami Michiyuki , Okada Kohsuke , Okuyama Kohei , Tsuzuki Keita , Liu Meigen
Published: August 2021

We aimed to investigate whether a newly defined distance in the lower limb can capture the characteristics of hemiplegic gait compared to healthy controls. Three-dimensional gait analyses were performed on 42 patients with chronic stroke and 10 age-matched controls. Pelvis-toe distance (PTD) was calculated as the absolute distance between an anterior superior iliac spine marker and a toe marker during gait normalized by PTD in the bipedal stance. The shortening peak during the swing phase was then quantified as PTDmin. The sagittal clearance angle, the frontal compensatory angle, gait speed, and the observational gait scale were also collected. PTDmin in the stroke group showed less shortening on the affected side and excessive shortening on the non-affected side compared to controls. PTDmin on the affected side correlated negatively with the sagittal clearance peak angle and positively with the frontal compensatory peak angle in the stroke group. PTDmin in stroke patients showed moderate to high correlations with gait speed and observational gait scale. PTDmin adequately reflected gait quality without being affected by apparent improvements due to frontal compensatory patterns. Our results showed that various impairments and compensations were included in the inability to shorten PTD, which can provide new perspectives on gait rehabilitation in stroke patients.
Wearables and Internet of Things (IoT) Technologies for Fitness Assessment: A Systematic Review
Authors: Passos João , Lopes Sérgio Ivan , Clemente Filipe Manuel , Moreira Pedro Miguel , Rico-González Markel , Bezerra Pedro , Rodrigues Luís Paulo
Published: August 2021

Wearable and Internet of Things (IoT) technologies in sports open a new era in athlete’s training, not only for performance monitoring and evaluation but also for fitness assessment. These technologies rely on sensor systems that collect, process and transmit relevant data, such as biomarkers and/or other performance indicators that are crucial to evaluate the evolution of the athlete’s condition, and therefore potentiate their performance. This work aims to identify and summarize recent studies that have used wearables and IoT technologies and discuss its applicability for fitness assessment. A systematic review of electronic databases (WOS, CCC, DIIDW, KJD, MEDLINE, RSCI, SCIELO, IEEEXplore, PubMed, SPORTDiscus, Cochrane and Web of Science) was undertaken according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. From the 280 studies initially identified, 20 were fully examined in terms of hardware and software and their applicability for fitness assessment. Results have shown that wearable and IoT technologies have been used in sports not only for fitness assessment but also for monitoring the athlete’s internal and external workloads, employing physiological status monitoring and activity recognition and tracking techniques. However, the maturity level of such technologies is still low, particularly with the need for the acquisition of more—and more effective—biomarkers regarding the athlete’s internal workload, which limits its wider adoption by the sports community.
Visual Sensor Fusion Based Autonomous Robotic System for Assistive Drinking
Authors: Try Pieter , Schöllmann Steffen , Wöhle Lukas , Gebhard Marion
Published: August 2021

People with severe motor impairments like tetraplegia are restricted in activities of daily living (ADL) and are dependent on continuous human assistance. Assistive robots perform physical tasks in the context of ADLs to support people in need of assistance. In this work a sensor fusion algorithm and a robot control algorithm for localizing the user’s mouth and autonomously navigating a robot arm are proposed for the assistive drinking task. The sensor fusion algorithm is implemented in a visual tracking system which consists of a 2-D camera and a single point time-of-flight distance sensor. The sensor fusion algorithm utilizes computer vision to combine camera images and distance measurements to achieve reliable localization of the user’s mouth. The robot control algorithm uses visual servoing to navigate a robot-handled drinking cup to the mouth and establish physical contact with the lips. This system features an abort command that is triggered by turning the head and unambiguous tracking of multiple faces which enable safe human robot interaction. A study with nine able-bodied test subjects shows that the proposed system reliably localizes the mouth and is able to autonomously navigate the cup to establish physical contact with the mouth.
Light Absorption in Nanowire Photonic Crystal Slabs and the Physics of Exceptional Points: The Shape Shifter Modes
Authors: Trendafilov Simeon , Allen Jeffery W. , Allen Monica S. , Dev Sukrith U. , Li Ziyuan , Fu Lan , Jagadish Chennupati
Published: August 2021

Semiconductor nanowire arrays have been demonstrated as promising candidates for nanoscale optoelectronics applications due to their high detectivity as well as tunable photoresponse and bandgap over a wide spectral range. In the infrared (IR), where these attributes are more difficult to obtain, nanowires will play a major role in developing practical devices for detection, imaging and energy harvesting. Due to their geometry and periodic nature, vertical nanowire and nanopillar devices naturally lend themselves to waveguide and photonic crystal mode engineering leading to multifunctional materials and devices. In this paper, we computationally develop theoretical basis to enable better understanding of the fundamental electromagnetics, modes and couplings that govern these structures. Tuning the photonic response of a nanowire array is contingent on manipulating electromagnetic power flow through the lossy nanowires, which requires an intimate knowledge of the photonic crystal modes responsible for the power flow. Prior published work on establishing the fundamental physical modes involved has been based either on the modes of individual nanowires or numerically computed modes of 2D photonic crystals. We show that a unified description of the array key electromagnetic modes and their behavior is obtainable by taking into account modal interactions that are governed by the physics of exceptional points. Such models that describe the underlying physics of the photoresponse of nanowire arrays will facilitate the design and optimization of ensembles with requisite performance. Since nanowire arrays represent photonic crystal slabs, the essence of our results is applicable to arbitrary lossy photonic crystals in any frequency range.
Statistical Characterization of Temperature and Pressure Vertical Profiles for the Analysis of Laser Heterodyne Radiometry Data
Authors: Flores Monica M. , Bomse David S. , Miller J. Houston
Published: August 2021

The statistical analysis of historic pressure and temperature profiles from radiosonde launches for use in the fitting of molecular oxygen line shapes is presented. As the O2 mixing ratio is nearly constant throughout the lower atmosphere, only variations in pressure and temperature profiles will affect the fit of observed O2 features in Laser Heterodyne Radiometry (LHR) spectra. Radiosonde temperature and pressure data are extracted from the Integrated Global Radiosonde Archive (IGRA) for a given station, date, and launch time. Data may be extracted for a single launch, for the same date over several years, and/or within a window centered on a target date. The temperature and pressure profiles are further characterized by the statistical variation in coefficients of polynomial fits in altitude. The properties of the probability distributions for each coefficient are used to constrain fits of O2 line shapes through Nelder–Mead optimization. The refined temperature and pressure profiles are then used in the retrieval of vertically resolved mixing ratios for greenhouse gases (GHGs) measured in the same instrument. In continuous collections, each vertical profile determination may be treated as a Bayesian prior to inform subsequent measurements and provide an estimate of uncertainties.
Centralised and Decentralised Sensor Fusion-Based Emergency Brake Assist
Authors: Deo Ankur , Palade Vasile , Huda Md. Nazmul
Published: August 2021

Many advanced driver assistance systems (ADAS) are currently trying to utilise multi-sensor architectures, where the driver assistance algorithm receives data from a multitude of sensors. As mono-sensor systems cannot provide reliable and consistent readings under all circumstances because of errors and other limitations, fusing data from multiple sensors ensures that the environmental parameters are perceived correctly and reliably for most scenarios, thereby substantially improving the reliability of the multi-sensor-based automotive systems. This paper first highlights the significance of efficiently fusing data from multiple sensors in ADAS features. An emergency brake assist (EBA) system is showcased using multiple sensors, namely, a light detection and ranging (LiDAR) sensor and camera. The architectures of the proposed ‘centralised’ and ‘decentralised’ sensor fusion approaches for EBA are discussed along with their constituents, i.e., the detection algorithms, the fusion algorithm, and the tracking algorithm. The centralised and decentralised architectures are built and analytically compared, and the performance of these two fusion architectures for EBA are evaluated in terms of speed of execution, accuracy, and computational cost. While both fusion methods are seen to drive the EBA application at an acceptable frame rate (~20 fps or higher) on an Intel i5-based Ubuntu system, it was concluded through the experiments and analytical comparisons that the decentralised fusion-driven EBA leads to higher accuracy; however, it has the downside of a higher computational cost. The centralised fusion-driven EBA yields comparatively less accurate results, but with the benefits of a higher frame rate and lesser computational cost.
Bioinformatics Analysis Confirms the Target Protein Underlying Mitotic Catastrophe of 4T1 Cells under Combinatorial Treatment of PGV-1 and Galangin
Authors: Hasbiyani Nurul Awali Fauziyah , Wulandari Febri , Nugroho Eri Prasetyo , Hermawan Adam , Meiyanto Edy
Published: August 2021

Pentagamavunon-1 (PGV-1), a potential chemopreventive agent with a strong cytotoxic effect, modulates prometaphase arrest. Improvement to get higher effectiveness of PGV-1 is a new challenge. A previous study reported that the natural compound, galangin, has antiproliferative activity against cancer cells with a lower cytotoxicity effect. This study aims to develop a combinatorial treatment of PGV-1 and galangin as an anticancer agent with higher effectiveness than a single agent. In this study, 4T1, a TNBC model cell, was treated with a combination of PGV-1 and galangin. As a result, PGV-1 and galangin showed a cytotoxic effect with IC50 values of 8 and 120 µM, respectively. Combining those chemicals has a synergistic impact, as shown by the combination index (CI) value of 1. Staining with the May Grunwald-Giemsa reagent indicated mitotic catastrophe evidence, characterized by micronuclear and multinucleated morphology. Moreover, the senescence percentage was higher than the single treatment. Furthermore, bioinformatics investigations showed that PGV-1 and galangin target CDK1, PLK1, and AURKB, overexpression proteins in TNBC that are essential in regulating cell cycle arrest. In conclusion, the combination of PGV-1 and galangin exhibit a synergistic effect and potential to be a chemotherapeutic drug by the mechanism of mitotic catastrophe and senescence induction.
Socio-Cultural Determinants and the Moderating Effect of Gender in Adopting Sustainable Consumption Behavior among University Students in Iran and Japan
Authors: Salehi Sadegh , Telešienė Audronė , Pazokinejad Zahra
Published: August 2021

This article explores the underlying factors of sustainable consumption behavior. Survey data are employed to test the impacts of environmental attitude, knowledge, social awareness, perceived credibility of information sources, self-efficacy and gender on sustainable consumption patterns among samples of university students in Iran and Japan. This contributes to the scientific search for valid explanatory models that could be employed to foster lifestyle transformations towards sustainability. Our findings confirm positive relationship between self-efficacy, social awareness and sustainable consumption in both Japanese and Iranian samples. Other predicators did not have a consistent effect in both samples. This article also presents the results of moderated regression and discusses which impacts were moderated by gender. The discussion presents with interpretation of the findings and proposes possible alternative explanations.
Location and Expansion of Electric Bus Charging Stations Based on Gridded Affinity Propagation Clustering and a Sequential Expansion Rule
Authors: Zhang Yajun , Deng Jie , Zhu Kangkang , Tao Yongqiang , Liu Xiaolin , Cui Ligang
Published: August 2021

With the escalating contradiction between the growing demand for electric buses and limited supporting resources of cities to deploy electric charging infrastructure, it is a great challenge for decision-makers to synthetically plan the location and decide on the expansion sequence of electric charging stations. In light of the location decisions of electric charging stations having long-term impacts on the deployment of electric buses and the layout of city traffic networks, a comprehensive framework for planning the locations and deciding on the expansion of electric bus charging stations should be developed simultaneously. In practice, construction or renovation of a new charging station is limited by various factors, such as land resources, capital investment, and power grid load. Thus, it is necessary to develop an evaluation structure that combines these factors to provide integrated decision support for the location of bus charging stations. Under this background, this paper develops a gridded affinity propagation (AP) clustering algorithm that combines the superiorities of the AP clustering algorithm and the map gridding rule to find the optimal candidate locations for electric bus charging stations by considering multiple impacting factors such as land cost, traffic conditions, and so on. Based on the location results of the candidate stations, the expansion sequence of these candidate stations is proposed. In particular, a sequential expansion rule for planning the charging stations is proposed that considers the development trends of the charging demand. To verify the performance of the gridded AP clustering and the effectiveness of the proposed sequential expansion rule, an empirical investigation of Guiyang City, the capital of Guizhou province in China, is conducted. The results of the empirical investigation demonstrate that the proposed framework that helps find optimal locations for electric bus charging stations and the expansion sequence of these locations are decided with less capital investment pressure. This research shows that the combination of gridded AP clustering and the proposed sequential expansion rule can systematically solve the problem of finding the optimal locations and deciding on the best expansion sequence for electric bus charging stations, which denotes that the proposed structure is pretty pragmatic and would benefit the government for long-term investment in electric bus station deployment.
Main Cross-Cutting Training Contents of LEISURE and Free Time Schools: Acceptance of Groups Involved in the Leisure Time Instructor Courses
Authors: Valdivia-Vizarreta Paloma , Rodrigo-Moriche María Pilar , Sánchez-Cabrero Roberto , Villaseñor-Palma Karla , Moreno-Rodríguez Vanessa
Published: August 2021

Time atomisation trends, leisure economy, and social and technological changes are causing a reframe of the leisure and free-time industry. This study aims to analyse the assessment of nine cross-cutting contents by the main agents involved in leisure-time instructor courses, and a group of young subjects in Spain. The study sample consisted of 1049 individuals, including management and technical teams, leisure and free-time schoolteachers, leisure and free-time school students (receiving the leisure-time instructor course), and finally a group of external young subjects. An ad hoc questionnaire was used, and the results were analysed through a correlational study using contingency tables and chi-square and Somers’ D statistics, Spearman’s correlation to determine within-population correlations, and the Kruskal–Wallis test to establish that these relationships were not randomly established. The results show that all the analysed agents valued the training proposal of cross-cutting contents as a consolidated item. This indicates that the nine cross-cutting contents should be maintained in these courses. Social Skills content was crowned as the defining content of this training, and there was dissonance in the ICT-Use content, which was not highly valued by main agents but was highly valued by young people, leading to the need to review this content to adjust it to the real needs of the young population.
Evaluation of the Use of a Road Diet Design: An Urban Corridor Case Study in Washington, DC
Authors: Aljamal Mohammad A. , Voight Derek , Green Jacob , Wang Jianwei , Ashqar Huthaifa I.
Published: August 2021

A traditional road diet design converts a four-lane two-way road to a three-lane road consisting of two through lanes and a center two-way left turn lane. This paper introduces a new application of the road diet design in an urban corridor. Specifically, the new application converts a four-lane two-way road into a two-lane two-way road with full-time parking lanes in both directions. The paper analyzed the traffic impacts of the road diet application on the corridor of New Jersey Avenue, northwest, in the city of Washington, District of Columbia. The corridor included five signalized and one unsignalized intersections. Before-and-after analyses using Synchro 11 simulation and Site-Specific Empirical Bayes analysis were used to evaluate and compare existing and proposed scenarios. The proposed scenario provided various benefits including offering accessibility to the businesses in the area and acting as a traffic calming strategy. For signalized intersections, the overall performance remained the same for most intersections except for one intersection (on P Street), as it is significantly impacted by the road diet design due to the dramatic increase of traffic volumes in its minor streets as a result of diverting traffic volumes from the unsignalized intersection for left and through movements. Results showed that the use of a road diet design enhanced the unsignalized intersection performance due to the traffic volume divergence from its minor streets and enhanced the safety of the study area by decreasing the annual number of predicted crashes. To achieve better operational benefits and reflect traffic demands, the paper recommends to re-optimize signal timings when a road diet design is adopted.
Aligning Resilience and Wellbeing Outcomes for Locally-Led Adaptation in Tanzania
Authors: Beauchamp Emilie , Sainsbury Nigel C. , Greene Sam , Chaigneau Tomas
Published: August 2021

Interventions to address climate adaptation have been on the rise over the past decade. Intervention programmes aim to build the resilience of local communities to climate shocks, and ultimately their wellbeing by helping them to better prepare, adapt and recover. Resilience, similar to human wellbeing, is a multidimensional construct grounded in local realities and lived experiences. Yet current evaluation frameworks used in resilience programming rarely consider what resilience means in local contexts prior to implementation. This means policy designs risk failing to improve resilience of communities and creating unintended negative consequences for communities’ wellbeing. Better processes and indicators for assessing resilience are needed. This paper explores the interplay between local predictors of resilience and wellbeing to assess the validity of self-assessed indicators as part of frameworks to measure resilience. We draw from research on the Devolved Climate Finance (DCF) mechanism implemented between 2014 and 2018 in Tanzania. We find that different factors explain resilience when compared to wellbeing; while resilience is primarily influenced by relationships, wellbeing is correlated with livelihoods. This shows that incentives to improve resilience differ from those of wellbeing. Climate and development practitioners must adopt locally grounded framings for resilience and wellbeing to ensure interventions track appropriate indicators, towards positive outcomes.
Mapping Participatory Methods in the Urban Development Process: A Systematic Review and Case-Based Evidence Analysis
Authors: Geekiyanage Devindi , Fernando Terrence , Keraminiyage Kaushal
Published: August 2021

Despite the fact that vulnerable communities are the most affected by unplanned cities, considerably less attention has been given to involving them in urban development in order to ensure equitable outcomes. In this regard, there is an urgent need for governments to introduce and enforce processes that allow citizens, including vulnerable communities, to participate in development planning and policymaking. However, at present, there is a lack of guidance for practitioners regarding the definition of a clear purpose of community engagement and the selection of appropriate participatory methods to fulfil the set purpose. This study provides a thorough account of the participatory methods that can be used to achieve various engagement goals throughout the urban development process. This structured literature review used 71 reports published from 2000 to 2020. The review revealed 34 participatory methods, wherein most of the methods are devoted to informing, consulting and involving communities, whilst only a few methods are available for interactive public participation that supports true collaboration and empowerment. The study identified 12 purposes of community engagement in urban development, and mapped the 34 participatory methods for achieving them. The analysed case studies showed that the current community engagement practices are mainly in the pre-design and briefing stages of the urban development processes, and that most projects are aiming to achieve the ‘inform’ and ‘consult’ levels of engagement, with a few aiming to achieve the ‘involve’ and ‘collaborate’ levels. This study shows that community engagement is often overlooked during the professional design, development and post-development phases. The paper presents an onion model which can be used by practitioners to choose appropriate participatory methods based on the intended urban development phase, the engagement level and the purpose of the community engagement.
Experimental Evidence of Ciguatoxin Accumulation and Depuration in Carnivorous Lionfish
Authors: Leite Isabel do Prado , Sdiri Khalil , Taylor Angus , Viallon Jérôme , Gharbia Hela Ben , Mafra Júnior Luiz Laureno , Swarzenski Peter , Oberhaensli François , Darius Hélène Taiana , Chinain Mireille , Bottein Marie-Yasmine Dechraoui
Published: August 2021

Ciguatera poisoning is a food intoxication associated with the consumption of fish or shellfish contaminated, through trophic transfer, with ciguatoxins (CTXs). In this study, we developed an experimental model to assess the trophic transfer of CTXs from herbivorous parrotfish, Chlorurus microrhinos, to carnivorous lionfish, Pterois volitans. During a 6-week period, juvenile lionfish were fed naturally contaminated parrotfish fillets at a daily dose of 0.11 or 0.035 ng CTX3C equiv. g−1, as measured by the radioligand-receptor binding assay (r-RBA) or neuroblastoma cell-based assay (CBA-N2a), respectively. During an additional 6-week depuration period, the remaining fish were fed a CTX-free diet. Using r-RBA, no CTXs were detectable in muscular tissues, whereas CTXs were measured in the livers of two out of nine fish sampled during exposure, and in four out of eight fish sampled during depuration. Timepoint pooled liver samples, as analyzed by CBA-N2a, confirmed the accumulation of CTXs in liver tissues, reaching 0.89 ng CTX3C equiv. g−1 after 41 days of exposure, followed by slow toxin elimination, with 0.37 ng CTX3C equiv. g−1 measured after the 6-week depuration. These preliminary results, which need to be pursued in adult lionfish, strengthen our knowledge on CTX transfer and kinetics along the food web.
Promoting Bicycling in Car-Oriented Cities: Lessons from Washington, DC and Frankfurt Am Main, Germany
Authors: Buehler Ralph , Teoman Denis , Shelton Brian
Published: August 2021

This paper compares bicycling in Washington, DC and Frankfurt am Main, Germany, two car-oriented cities that had adapted their urban transport system to car travel during the 20th century. Our comparative case study shows that both cities have been successful in increasing the percentage of trips made by bicycle between the late 1990s and 2018: Washington, DC from 1% to 5% and Frankfurt from 6% to 20% of trips. Both cities had detailed bike plans and specific mode share goals for bicycling. However, those plans were only used as guideposts for a step-by-step approach to bicycle promotion that focused on integrating bicycling into everyday decision making in transport, traffic engineering, and urban development. This step-by-step approach successfully garnered political, public, and administrative support over time. The downside of this incrementalist approach is that bike route networks in both cities still have many gaps because bikeway infrastructure was built when individual opportunities arose and not as part of an integrated network. Bicycle promotion in both cities used a combination of bikeway infrastructure and soft policy, including marketing measures. In both cities, the quality of newly installed bikeway infrastructure increased over time from simple bike lanes to protected bike lanes separating cyclists from traffic. In contrast to Washington, DC, Frankfurt has a longer history of car-restrictive policies and overall has been more strict in limiting car use.
Nuances of Whitefly Vector–Crinivirus Interactions Revealed in the Foregut Retention and Transmission of Lettuce Chlorosis Virus by Two Bemisia tabaci Cryptic Species
Authors: Chen Angel Y. S. , Zhou Jaclyn S. , Liu Jin-Xiang , Ng James C. K.
Published: August 2021

Lettuce infectious yellows virus is the first crinivirus for which the retention of purified virions ingested into the whitefly (Bemisia tabaci New World (NW)) vector’s foregut, has been demonstrated to be a requisite for successful virus transmission. This key finding supports the hypothesis that the determinant of foregut retention and transmission is present on the virion itself. However, whether this is also true for other criniviruses has not been established. Here, we provide evidence that lettuce chlorosis virus (LCV) acquired from plants is retained in the foreguts of both the B. tabaci NW and Middle East–Asia Minor 1 (MEAM1) vector species and transmitted upon inoculation feeding. An association between foregut retention and transmission by NW vectors is also observed following the acquisition and inoculation feeding of LCV virions purified using a standard procedure involving 2% or 4% (v/v) Triton™ X-100 (TX-100). However, while virions purified with 2% or 4% TX-100 are also retained in the foreguts of MEAM1 vectors, transmission is observed with the 4% TX-100-purified virions or when more vectors are used for acquisition and inoculation feeding. These results suggest that an intrinsic difference exists between NW and MEAM1 vectors in their interactions with, and transmission of, LCV virions.
Comparable Infection Level and Tropism of Measles Virus and Canine Distemper Virus in Organotypic Brain Slice Cultures Obtained from Natural Host Species
Authors: Laksono Brigitta M. , Tran Diana N. , Kondova Ivanela , van Engelen Harry G. H. , Michels Samira , Nambulli Sham , de Vries Rory D. , Duprex W. Paul , Verjans Georges M. G. M. , de Swart Rik L.
Published: August 2021

Measles virus (MV) and canine distemper virus (CDV) are closely related members of the family Paramyxoviridae, genus Morbillivirus. MV infection of humans and non-human primates (NHPs) results in a self-limiting disease, which rarely involves central nervous system (CNS) complications. In contrast, infection of carnivores with CDV usually results in severe disease, in which CNS complications are common and the case-fatality rate is high. To compare the neurovirulence and neurotropism of MV and CDV, we established a short-term organotypic brain slice culture system of the olfactory bulb, hippocampus, or cortex obtained from NHPs, dogs, and ferrets. Slices were inoculated ex vivo with wild-type-based recombinant CDV or MV expressing a fluorescent reporter protein. The infection level of both morbilliviruses was determined at different times post-infection. We observed equivalent infection levels and identified microglia as main target cells in CDV-inoculated carnivore and MV-inoculated NHP brain tissue slices. Neurons were also susceptible to MV infection in NHP brain slice cultures. Our findings suggest that MV and CDV have comparable neurotropism and intrinsic capacity to infect CNS-resident cells of their natural host species.