bluuebunny/crossref_metadata_2025 huggingface dataset:
Effectiveness and Applications of a Metal-Coated HNT/Polylactic Acid Antimicrobial Filtration System
Authors: McFarland Antwine W. , Elumalai Anusha , Miller Christopher C. , Humayun Ahmed , Mills David K.
Published: April 2022

A broad-spectrum antimicrobial respiration apparatus designed to fight bacteria, viruses, fungi, and other biological agents is critical in halting the current pandemic’s trajectory and containing future outbreaks. We applied a simple and effective electrodeposition method for metal (copper, silver, and zinc) coating the surface of halloysite nanotubes (HNTs). These nanoparticles are known to possess potent antiviral and antimicrobial properties. Metal-coated HNTs (mHNTs) were then added to polylactic acid (PLA) and extruded to form an mHNT/PLA 3D composite printer filament. Our composite 3D printer filament was then used to fabricate an N95-style mask with an interchangeable/replaceable filter with surfaces designed to inactivate a virus and kill bacteria on contact, thus reducing deadly infections. The filter, made of a multilayered antimicrobial/mHNT blow spun polymer and fabric, is disposable, while the mask can be sanitized and reused. We used several in vitro means of assessing critical clinical features and assessed the bacterial growth inhibition against commonly encountered bacterial strains. These tests demonstrated the capability of our antimicrobial filament to fabricate N95 masks and filters that possessed antibacterial capabilities against both Gram-negative and Gram-positive bacteria.
Effects of Modified Layered Double Hydroxides on the Thermal Degradation and Combustion Behaviors of Intumescent Flame Retardant Polyethylene Nanocomposites
Authors: Zhang Tiefeng , Wang Chunfeng , Wang Yue , Wang Yongliang , Han Zhidong
Published: April 2022

The flame retardancy of layered double hydroxides (LDHs) correlates with their structure and dispersion in a polymeric matrix. To improve the flame retardant effectiveness of Mg-Al LDH in polyethylene (PE), 2-carboxy ethyl (phenyl) phosphinic acid (CEPPA) was adopted as a flame retardant modifier to prepare CEPPA-intercalated LDH (CLDH) by the regeneration method, which was then exfoliated in PE by melt blending in the form of a masterbatch prepared from solution mixing. By compounding CLDH with intumescent flame retardant (IFR) composed of ammonium polyphosphate (APP) and pentaerythritol (PER), the thermal degradation and combustion behaviors of the flame retardant PE-based composites were investigated to reveal the flame retardant mechanism between CLDH and IFR in PE. The reactions between CLDH and IFR were revealed to make a predominant contribution to the compact and fully developed char of PE/IFR/CLDH, which enhanced the flame retardancy of the composites.
Application of Red Cabbage Anthocyanins as pH-Sensitive Pigments in Smart Food Packaging and Sensors
Authors: Abedi-Firoozjah Reza , Yousefi Shima , Heydari Mahshid , Seyedfatehi Faezeh , Jafarzadeh Shima , Mohammadi Reza , Rouhi Milad , Garavand Farhad
Published: April 2022

Anthocyanins are excellent antioxidant/antimicrobial agents as well as pH-sensitive indicators that provide new prospects to foster innovative smart packaging systems due to their ability to improve food shelf life and detect physicochemical and biological changes in packaged food. Compared with anthocyanins from other natural sources, red cabbage anthocyanins (RCAs) are of great interest in food packaging because they represent an acceptable color spectrum over a broad range of pH values. The current review addressed the recent advances in the application of RCAs in smart bio-based food packaging systems and sensors. This review was prepared based on the scientific reports found on Web of Science, Scopus, and Google Scholar from February 2000 to February 2022. The studies showed that the incorporation of RCAs in different biopolymeric films could affect their physical, mechanical, thermal, and structural properties. Moreover, the use of RCAs as colorimetric pH-responsive agents can reliably monitor the qualitative properties of the packaged food products in a real-time assessment. Therefore, the development of smart biodegradable films using RCAs is a promising approach to the prospect of food packaging.
Improved Mechanical Properties and Bioactivity of Silicate Based Bioceramics Reinforced Poly(ether-ether-ketone) Nanocomposites for Prosthetic Dental Implantology
Authors: Taymour Noha , Fahmy Amal E. , Gepreel Mohamed Abdel Hady , Kandil Sherif , El-Fattah Ahmed Abd
Published: April 2022

Polyether-ether-ketone (PEEK) biomaterial has been increasingly employed for orthopedic, trauma, spinal, and dental implants due to its biocompatibility and in vivo stability. However, a lack of bioactivity and binding ability to natural bone tissue has significantly limited PEEK for many challenging dental implant applications. In this work, nanocomposites based on PEEK reinforced with bioactive silicate-based bioceramics (forsterite or bioglass) as nanofillers were prepared using high energy ball milling followed by melt blending and compression molding. The influence of nanofillers type and content (10, 20 and 30 wt.%) on the crystalline structure, morphology, surface roughness, hydrophilicity, microhardness, elastic compression modulus, and flexural strength of the nanocomposites was investigated. The scanning electron microscopy images of the nanocomposites with low nanofillers content showed a homogenous surface with uniform dispersion within the PEEK matrix with no agglomerates. All nanocomposites showed an increased surface roughness compared to pristine PEEK. It was found that the incorporation of 20 wt.% forsterite was the most effective in the nanocomposite formulation compared with bioglass-based nanocomposites; it has significantly improved the elastic modulus, flexural strength, and microhardness. In vitro bioactivity evaluation, which used biomimetic simulated body fluid indicated the ability of PEEK nanocomposites loaded with forsterite or bioglass nanofillers to precipitate calcium and phosphate bone minerals on its surface. These nanocomposites are expected to be used in long-term load-bearing implant applications and could be recommended as a promising alternative to titanium and zirconia when used as a dental implant material.
Getting to Know the Other: Niqab-Wearing Women in Liberal Democracies
Authors: Bakht Natasha
Published: April 2022

Governments around the world have gone to great lengths to discourage and prohibit wearing of the niqab, often relying on the justification that this form of Muslim women’s dress represents and produces the oppression of women. Setting aside that these prohibitions are themselves detrimental to women’s equality, this article focuses on the voices of women who wear the niqab or face veil. I describe and analyze how women explain their decision to wear the niqab based on interviews in seven liberal democracies. For most women, the primary motivation for wearing the niqab is religious, though supplementary reasons are also offered. The niqab is an embodied practice that represents a personal spiritual journey. Women’s explanations for why and when they wear the niqab suggest a complex intermingling of doctrinal knowledge and practical lived experience that negotiates religion day to day. Women often pair their religious agency with a sophisticated rights-based framework to justify their sartorial choices. Women refute the idea that the niqab makes them submissive. Their empowered interpretations of their religion and their conviction to lead a life that is different from most, in countries with pervasive anti-Muslim racism, suggest a great deal of independence and courage. This research offers nuance to the depiction of women who are typically portrayed monotonously, dispelling inaccurate stereotypes used to support discriminatory decision making about niqab-wearing women.
Christ’s Wounded Body, Sorrowful Soul and Joyful Spirit: The Interpretation of Christ’s Passion in a Forgotten 16th Century Classic of Mystical Literature
Authors: Faesen Rob
Published: April 2022

The Passion of Christ is not only an important theme in Christian theological and devotional literature, iconography, and music, but it is likewise the focus of considerable attention in contemplative, mystical literature. This contribution focuses on a specific interpretation of the suffering of Christ, which is to be found in an important but now somewhat forgotten mystical text, namely the Evangelical Pearl. This text is to be situated within the broad mystical network and initiatives of the Cologne Carthusians in the early sixteenth century. The Pearl has a remarkable interpretation of Christ’s passion, namely that—simultaneously—his body was in terrible pain, his soul was deeply sorrowful and his spirit was joyful. These reflections culminate in a radical theology of deification.
Hybridized Surviving: The Diaspora Narratives of Joseph, Esther, and Daniel
Authors: Kolia Brian Fiu
Published: April 2022

There are a number of challenges faced by diasporic people, yet they all seem to be connected to one major issue: “identity”. Their narratives are built on questions surrounding who they are, when they are no longer living in/on their home/land. As they migrate to foreign lands, their notions of identity become clouded, and quite often they struggle to “belong”. Second-generation people could be heard asking: “Where do we belong?” “The lands our parents came from?” “Or the lands we now live?” “Is it both? Or is it neither?” “Do we even know who we are? How do we fit in? How do we survive?” The aim of this essay is to highlight the issue of diasporic identity in the narratives of three biblical migrants: Joseph, Esther, and Daniel. The purposes of these biblical accounts seem to reflect the ambivalence of diasporic existence, where they can achieve success but also experience adversity. Yet these narratives also deal with how identity is problematized in diasporic contexts. I will be engaging these narratives in conversation with my own story, in a bid to view alternative understandings and constructs of diasporic existence, particularly for second-generation migrants within religious communities. Furthermore, the hope is that a re-reading of these narratives may generate alternative theological considerations in light of the struggles of second-generation migrants.
Introduction to Special Issue: Islam and/in Education in The Netherlands
Authors: ter Avest Ina
Published: April 2022

This article provides information on the current Dutch educational system, paying special attention to the position of Islam in formal, non-formal and informal education. It briefly sketches the history of the so-called “pillarised educational system”, a system in which the 19th century Dutch Christian education system evolved into a compartmentalised system with the pillars of Catholic, Protestant and humanistic education. At the end of the 20th century, a fourth pillar of Islamic education was founded by Dutch Muslim parents. Convinced that religious upbringing in the family and participation in mosque youth clubs constituted only the beginning of the process of becoming a good Muslim, Moroccan and Turkish parents supported the foundation of formal Islamic education in Dutch Islamic schools. This article describes developments in formal, non-formal and informal Islamic education in the light of children’s rights to religious education and parents’ rights to religious upbringing. Religious identity development, including religious literacy training, is presented as an important aspect of educating children to be(come) good Muslims—a process in which parents at home, imams and volunteers at the mosque, as well as teachers at school, play an important role.
Agentic and Receptive Hope: Understanding Hope in the Context of Religiousness and Spirituality through the Narratives of Salvadoran Youth
Authors: Vaughn Jennifer Medina , King Pamela Ebstyne , Mangan Susan , Noe Sean , Hay Samuel , O’Neil Bridget , Tirrell Jonathan M. , Dowling Elizabeth M. , Iraheta Majano Guillermo Alfredo , Sim Alistair Thomas Rigg
Published: April 2022

Hope contributes to positive development in adolescents, and religious and spiritual contexts may be particularly important for developing and supporting hope. However, extant literature on hope, religion, and spirituality neglects their synergistic relation, leaving questions about how they work together to support development. In this study, we explore how religiousness and spirituality (R/S) inform hope by identifying unique synergies that might be particularly useful in difficult contexts. Multilevel qualitative content analyses of interviews conducted with 18 thriving Salvadoran adolescents (50% female, Mage = 16.39 years, SD = 1.83) involved in a faith-based program provided evidence that the ideological and relational resources associated with R/S informed these adolescents’ agentic and receptive hopes. Agentic hopes, identified through expressed hopeful future expectations, revealed that adolescents held beyond-the-self hopes focused on benefiting three distinct targets: God, community, and family. Youth also described “sanctified hopes”, which were hopes focused on fulfilling God’s purposes directly and indirectly. Analyses of receptive hopes, which consider how hope is shaped and empowered by context, revealed that for these youth, hope was experienced in seven key contexts: self, caring adult relationships, family, God, youth development sponsor, social activities, and peers. Implications for fostering hope in R/S contexts within low-to-middle-income countries are discussed.
Systemic Risk Management of Investments in Innovation Based on CSR
Authors: Lebedev Vladimir V. , Deberdeeva Nelia A. , Farkova Natalya A. , Korobeinikova Larisa S.
Published: April 2022

The problem studied in this paper consists in the fact that the social and financial risks of investments in innovations are managed in isolation, which leads to limited results (reduces certain risks but raises other risks). This paper is devoted to the search for a new strategy of managing the risks of investments in innovations, which would allow balancing the financial interests of business and the interests of employees and is aimed at developing a framework strategy of the systemic management of all risks based on corporate social responsibility. The methodology of this research is based on regression analysis. The research sample comprises data from 80 countries of the world in 2021. The social and financial risks of investments in innovations are identified, systematized, and quantitatively measured and reconsidered from the positions of the UN SDGs. The paper’s contribution consists in substantiating a systemic interconnection between the social and financial risks of investments in innovations and the possibility of complex management of all these risks based on corporate social responsibility. The theoretical value of this paper consists in overcoming the gap in studying the social and financial risks of investments in innovations. The practical value of the authors’ conclusions and recommendations consists in the developed framework strategy being a practical guide for the systemic management of the risks of investments based on corporate social responsibility.
Perspectives on the Special Issue for Applications of Remote Sensing for Livestock and Grazingland Management
Authors: Rhodes Edward C. , Perotto-Baldivieso Humberto L. , Reeves Matthew C. , Gonzalez Luciano A.
Published: April 2022

The use of geospatial sciences and technologies for the management of grazinglands has fostered a plethora of applications related to ecology, wildlife, vegetation science, forage productivity and quality, and animal husbandry. Some of the earliest use of remote sensing dates to the proliferation of aerial photography in the 1930s. Today, remote sensing using satellite imagery, global navigation satellite systems (GNSS), and internet-connected devices and sensors allow for real- and near real-time modeling and observation of grazingland resources. In this special issue of Remote Sensing, we introduce nine original publications focusing on varying aspects of grazingland management, such as animal health and telemetry, climate change, soil moisture, herbaceous biomass, and vegetation phenology. The work in this issue spans a diverse range of scale from satellite to unmanned aerial systems imagery, as well as ground-based measurements from mounted cameras, telemetry devices, and datalogging devices. Remote sensing-based technologies continue to evolve, allowing us to address critical issues facing grazingland management such as climate change, restoration, forage abundance and quality, and animal behavior, production, and welfare.
Few-Shot SAR-ATR Based on Instance-Aware Transformer
Authors: Zhao Xin , Lv Xiaoling , Cai Jinlei , Guo Jiayi , Zhang Yueting , Qiu Xiaolan , Wu Yirong
Published: April 2022

Few-shot synthetic aperture radar automatic target recognition (SAR-ATR) aims to recognize the targets of the images (query images) based on a few annotated images (support images). Such a task requires modeling the relationship between the query and support images. In this paper, we propose the instance-aware transformer (IAT) model. The IAT exploits the power of all instances by constructing the attention map based on the similarities between the query feature and all support features. The query feature aggregates the support features based on the attention values. To align the features of the query and support images in IAT, the shared cross-transformer keep all the projections in the module shared across all features. Instance cosine distance is used in training to minimize the distance between the query feature and the support features. In testing, to fuse the support features of the same class into the class representation, Euclidean (Cosine) Loss is used to calculate the query-class distances. Experiments on the two proposed few-shot SAR-ATR test sets based on MSTAR demonstrate the superiority of the proposed method.
Coastal Wetland Responses to Sea Level Rise: The Losers and Winners Based on Hydro-Geomorphological Settings
Authors: Wen Li , Hughes Michael G.
Published: April 2022

Many coastal wetlands are under pressure due to climate change and the associated sea level rise (SLR). Many previous studies suggest that upslope lateral migration is the key adaptive mechanism for saline wetlands, such as mangroves and saltmarshes. However, few studies have explored the long-term fate of other wetland types, such as brackish swamps and freshwater forests. Using the current wetland map of a micro-tidal estuary, the Manning River in New South Wales, Australia, this study built a machine learning model based on the hydro-geomorphological settings of four broad wetland types. The model was then used to predict the future wetland distribution under three sea level rise scenarios. The predictions were compared to compute the persistence, net, swap, and total changes in the wetlands to investigate the loss and gain potential of different wetland classes. Our results for the study area show extensive gains by mangroves under low (0.5 m), moderate (1.0 m), and high (1.5 m) sea level rise scenarios, whereas the other wetland classes could suffer substantial losses. Our findings suggest that the accommodation spaces might only be beneficial to mangroves, and their availability to saltmarshes might be limited by coastal squeeze at saline–freshwater ecotones. Furthermore, the accommodation spaces for freshwater wetlands were also restrained by coastal squeeze at the wetland-upland ecotones. As sea level rises, coastal wetlands other than mangroves could be lost due to barriers at the transitional ecotones. In our study, these are largely manifested by slope impacts on hydrology at a higher sea level. Our approach provides a framework to systematically assess the vulnerability of all coastal wetland types.
Why Is It Important to Consider Dust Aerosol in the Sevastopol and Black Sea Region during Remote Sensing Tasks? A Case Study
Authors: Kalinskaya Darya V. , Papkova Anna S.
Published: April 2022

Atmospheric correction of satellite optical data is based on an assessment of the optical characteristics of the atmosphere, such as the aerosol optical thickness of the atmosphere and the spectral slope, the so-called Angstrom parameter. Inaccurate determination of these parameters is one of the causes of error in the retrieval of remote-sensed reflectance spectra. In this work, a large array of field and satellite data measured in Sevastopol and the northeastern part of the Black Sea were used, including ship-based measurements of atmospheric characteristics and sea reflectance, MODIS Aqua/Terra, and VIIRS NOAA/NPP Level 2 remote-sensed reflectance and atmospheric data. In total, three episodes of Saharan dust transfer over the Black Sea region were considered, mainly in the autumn-winter period. The purpose of this study was to show the numerical differences between the atmospheric parameters measured at the surface level and by satellites, and show their relationship with the differences between in situ and satellite remote-sensed reflectance. Based on the information identified, we propose an algorithm for additional correction of satellite level 2 data that uses a two-parametric model of the Black Sea remote-sensed reflectance as a first approximation. Moreover, additional correction significantly reduces the discrepancy between in situ and retrieved remote-sensed reflectance, especially in short-wave spectral bands.
Application of an Improved YOLOv5 Algorithm in Real-Time Detection of Foreign Objects by Ground Penetrating Radar
Authors: Qiu Zhi , Zhao Zuoxi , Chen Shaoji , Zeng Junyuan , Huang Yuan , Xiang Borui
Published: April 2022

Ground penetrating radar (GPR) detection is a popular technology in civil engineering. Because of its advantages of non-destructive testing (NDT) and high work efficiency, GPR is widely used to detect hard foreign objects in soil. However, the interpretation of GPR images relies heavily on the work experience of researchers, which may lead to problems of low detection efficiency and a high false recognition rate. Therefore, this paper proposes a real-time detection technology of GPR based on deep learning for the application of soil foreign object detection. In this study, the GPR image signal is obtained in real time by the GPR instrument and software, and the image signals are preprocessed to improve the signal-to-noise ratio of the GPR image signals and improve the image quality. Then, in view of the problem that YOLOv5 poorly detects small targets, this study improves the problems of false detection and missed detection in real-time GPR detection by improving the network structure of YOLOv5, adding an attention mechanism, data enhancement, and other means. Finally, by establishing a regression equation for the position information of the ground penetrating radar, the precise localization of the foreign matter in the underground soil is realized.
Hole Filling of Single Building Point Cloud Considering Local Similarity among Floors
Authors: Min Xiangqiang , Wang Yanfeng , Zhang Ka , Sheng Yehua , Qin Jiarui , Huang Yi
Published: April 2022

In the process of acquiring a point cloud, due to the shielding of the building itself and other ground objects (such as vegetation), the collected point cloud cannot cover the building facades surface uniformly and completely, and can produce several holes of different sizes. The existing hole-filling methods cannot obtain satisfying repaired results. To solve this problem, this paper proposes a new hole-filling approach considering the local similarity among floors. The proposed approach first detects holes in the building facade surface and then identifies the building floors; next, according to the fact that building data are similar in the same position on different floors, the holes of the building facade point cloud can be filled using the data of different floors. The study examines three large buildings to verify the proposed method. The experimental results show that the proposed method outperforms the state-of-the-art filling methods; the filling results of the proposed method are closer to the real shape and can be smoothly connected with the original building point cloud. Moreover, the proposed method has greater accuracy when comparing the root mean square error (RMSE).
Remote Sensing Estimation and Spatiotemporal Pattern Analysis of Terrestrial Net Ecosystem Productivity in China
Authors: Liang Liang , Geng Di , Yan Juan , Qiu Siyi , Shi Yanyan , Wang Shuguo , Wang Lijuan , Zhang Lianpeng , Kang Jianrong
Published: April 2022

Net ecosystem productivity (NEP) plays an important role in understanding ecosystem function and the global carbon cycle. In this paper, the key parameters of the Carnegie Ames Stanford Approach (CASA) model, maximum light use efficiency (εmax), was optimized by using vegetation classification data. Then, the NEP was estimated by coupling the optimized CASA model, geostatistical model of soil respiration (GSMSR) and the soil respiration–soil heterotrophic respiration (Rs-Rh) relationship model. The ground observations from ChinaFLUX were used to verify the NEP estimation accuracy. The results showed that the R2 of the optimized CASA model increased from 0.411 to 0.774, and RMSE decreased from 21.425 gC·m−2·month−1 to 12.045 gC·m−2·month−1, indicating that optimizing CASA model by vegetation classification data was an effective method to improve the estimation accuracy of NEP. On this basis, the spatial and temporal distribution of NEP in China was analyzed. The research indicated that the monthly variation of NEP in China was a single peak curve with summer as the peak, which generally presented the pattern of southern region > northern region > Qinghai–Tibet region > northwest region. Furthermore, from 2001 to 2016, most regions of China showed a non-significant level upward trend, but main cropland (e.g., North China Plain and Northeast Plain) and some grassland (e.g., Ngari in Qinghai–Tibet Plateau and Xilin Gol League in Inner Mongolia) showed a non-significant-level downward trend. The study can deepen the understanding of the distribution of carbon sources/sinks in China, and provide a reference for regional carbon cycle research.
A Two-Step Approach to Blending GSMaP Satellite Rainfall Estimates with Gauge Observations over Australia
Authors: Chua Zhi-Weng , Kuleshov Yuriy , Watkins Andrew B. , Choy Suelynn , Sun Chayn
Published: April 2022

An approach to developing a blended satellite-rainfall dataset over Australia that could be suitable for operational use is presented. In this study, Global Satellite Mapping of Precipitation (GSMaP) satellite precipitation estimates were blended with station-based rain gauge data over Australia, using operational station data that has not been harnessed by other blended products. A two-step method was utilized. First, GSMaP satellite precipitation estimates were adjusted using rain gauge data through multiplicative ratios that were gridded using ordinary kriging. This step resulted in reducing dry biases, especially over topography. The adjusted GSMaP data was then blended with the Australian Gridded Climate Dataset (AGCD) rainfall analysis, an operational station-based gridded rain gauge dataset, using an inverse error variance weighting method to further remove biases. A validation that was performed using a 20-year range (2001 to 2020) showed the proposed approach was successful; the resulting blended dataset displayed superior performance compared to other non-gauge-based datasets with respect to stations as well as displaying more realistic patterns of rainfall than the AGCD in areas with no rain gauges. The average mean absolute error (MAE) against station data was reduced from 0.89 to 0.31. The greatest bias reductions were obtained for extreme precipitation totals and over mountainous regions, provided sufficient rain gauge availability. The newly produced dataset supported the identification of a general positive bias in the AGCD over the north-west interior of Australia.
A Spectral Mixture Analysis and Landscape Metrics Based Framework for Monitoring Spatiotemporal Forest Cover Changes: A Case Study in Mato Grosso, Brazil
Authors: Halbgewachs Magdalena , Wegmann Martin , da Ponte Emmanuel
Published: April 2022

An increasing amount of Brazilian rainforest is being lost or degraded for various reasons, both anthropogenic and natural, leading to a loss of biodiversity and further global consequences. Especially in the Brazilian state of Mato Grosso, soy production and large-scale cattle farms led to extensive losses of rainforest in recent years. We used a spectral mixture approach followed by a decision tree classification based on more than 30 years of Landsat data to quantify these losses. Research has shown that current methods for assessing forest degradation are lacking accuracy. Therefore, we generated classifications to determine land cover changes for each year, focusing on both cleared and degraded forest land. The analyses showed a decrease in forest area in Mato Grosso by 28.8% between 1986 and 2020. In order to measure changed forest structures for the selected period, fragmentation analyses based on diverse landscape metrics were carried out for the municipality of Colniza in Mato Grosso. It was found that forest areas experienced also a high degree of fragmentation over the study period, with an increase of 83.3% of the number of patches and a decrease of the mean patch area of 86.1% for the selected time period, resulting in altered habitats for flora and fauna.
Monitoring Optical Variability in Complex Inland Waters Using Satellite Remote Sensing Data
Authors: Du Yunxia , Song Kaishan , Liu Ge
Published: April 2022

Optical classification for water bodies was carried out based on satellite remote sensing data, which avoided the limitation of having a limited amount of in situ measured spectral data. Unsupervised cluster analysis was performed on 53,815 reflectance spectra extracted at 500-m intervals based on the same season or quasi-same season Landsat 8 SR data using the algorithm of fuzzy c-means. Lakes and reservoirs in the study area were comprehensively identified as three optical types representing different limnological features. The shape and amplitude characteristics of the reflectance spectra for the three optical water types indicated that one corresponds to the clearest water, one corresponds to turbid water, and the other is moderate clear water. The novelty detection technique was further used to label the match-ups of the in situ data set collected during 2006 to 2019 in 12 field surveys based on mathematical rules of the three optical water types. The results confirmed that each optical water type was associated with different bio-optical properties, and the total suspended matter of the clearest, moderate clear and turbid water types were 14.99 mg/L, 41.06 mg/L and 83.81 mg/L, respectively. Overall, the clearest, moderate clear and turbid waters in the study area accounted for 49.3%, 36.7% and 14.0%, respectively. The spatial distribution of optical water types in the study area was seamlessly mapped. Results showed that the bio-optical conditions of the water distributed across the southeast region were roughly homogeneous, but in most of other regions and within some water bodies, they showed a patchy distribution and heterogeneity. This study is useful for monitoring water quality and provides a useful foundation to develop or tuning algorithms to retrieve water quality parameters.
Automated Inventory of Broadleaf Tree Plantations with UAS Imagery
Authors: Chandrasekaran Aishwarya , Shao Guofan , Fei Songlin , Miller Zachary , Hupy Joseph
Published: April 2022

With the increased availability of unmanned aerial systems (UAS) imagery, digitalized forest inventory has gained prominence in recent years. This paper presents a methodology for automated measurement of tree height and crown area in two broadleaf tree plantations of different species and ages using two different UAS platforms. Using structure from motion (SfM), we generated canopy height models (CHMs) for each broadleaf plantation in Indiana, USA. From the CHMs, we calculated individual tree parameters automatically through an open-source web tool developed using the Shiny R package and assessed the accuracy against field measurements. Our analysis shows higher tree measurement accuracy with the datasets derived from multi-rotor platform (M600) than with the fixed wing platform (Bramor). The results show that our automated method could identify individual trees (F-score > 90%) and tree biometrics (root mean square error < 1.2 m for height and <1 m2 for the crown area) with reasonably good accuracy. Moreover, our automated tool can efficiently calculate tree-level biometric estimations for 4600 trees within 30 min based on a CHM from UAS-SfM derived images. This automated UAS imagery approach for tree-level forest measurements will be beneficial to landowners and forest managers by streamlining their broadleaf forest measurement and monitoring effort.
Seasonal and Interannual Variability of Tidal Mixing Signatures in Indonesian Seas from High-Resolution Sea Surface Temperature
Authors: Susanto Raden Dwi , Ray Richard D.
Published: April 2022

With their complex narrow passages and vigorous mixing, the Indonesian seas provide the only low-latitude pathway between the Pacific and Indian Oceans and thus play an essential role in regulating Pacific-Indian Ocean exchange, regional air-sea interaction, and ultimately, global climate phenomena. While previous investigations using remote sensing and numerical simulations strongly suggest that this mixing is tidally driven, the impacts of monsoon and El Niño Southern Oscillation (ENSO) on tidal mixing in the Indonesian seas must play an important role. Here we use high-resolution sea surface temperature from June 2002 to June 2021 to reveal monsoon and ENSO modulations of mixing. The largest spring-neap (fortnightly) signals are found to be localized in the narrow passages/straits and sills, with more vigorous tidal mixing during the southeast (boreal summer) monsoon and El Niño than that during the northwest (boreal winter monsoon) and La Niña. Therefore, tidal mixing, which necessarily responds to seasonal and interannual changes in stratification, must also play a feedback role in regulating seasonal and interannual variability of water mass transformations and Indonesian throughflow. The findings have implications for longer-term variations and changes of Pacific–Indian ocean water mass transformation, circulation, and climate.
Estimating Tree Defects with Point Clouds Developed from Active and Passive Sensors
Authors: Morgan Carli J. , Powers Matthew , Strimbu Bogdan M.
Published: April 2022

Traditional inventories require large investments of resources and a trained workforce to measure tree sizes and characteristics that affect wood quality and value, such as the presence of defects and damages. Handheld light detection and ranging (LiDAR) and photogrammetric point clouds developed using Structure from Motion (SfM) algorithms achieved promising results in tree detection and dimensional measurements. However, few studies have utilized handheld LiDAR or SfM to assess tree defects or damages. We used a Samsung Galaxy S7 smartphone camera to photograph trees and create digital models using SfM, and a handheld GeoSLAM Zeb Horizon to create LiDAR point cloud models of some of the main tree species from the Pacific Northwest. We compared measurements of damage count and damage length obtained from handheld LiDAR, SfM photogrammetry, and traditional field methods using linear mixed-effects models. The field method recorded nearly twice as many damages per tree as the handheld LiDAR and SfM methods, but there was no evidence that damage length measurements varied between the three survey methods. Lower damage counts derived from LiDAR and SfM were likely driven by the limited point cloud reconstructions of the upper stems, as usable tree heights were achieved, on average, at 13.6 m for LiDAR and 9.3 m for SfM, even though mean field-measured tree heights was 31.2 m. Our results suggest that handheld LiDAR and SfM approaches show potential for detection and measurement of tree damages, at least on the lower stem.
Atomicity and Regularity Principles Do Not Ensure Full Resistance of ECC Designs against Single-Trace Attacks
Authors: Kabin Ievgen , Dyka Zoya , Langendoerfer Peter
Published: April 2022

Elliptic curve cryptography (ECC) is one of the commonly used standard methods for encrypting and signing messages which is especially applicable to resource-constrained devices such as sensor nodes that are networked in the Internet of Things. The same holds true for wearable sensors. In these fields of application, confidentiality and data integrity are of utmost importance as human lives depend on them. In this paper, we discuss the resistance of our fast dual-field ECDSA accelerator against side-channel analysis attacks. We present our implementation of a design supporting four different NIST elliptic curves to allow the reader to understand the discussion of the resistance aspects. For two different target platforms—ASIC and FPGA—we show that the application of atomic patterns, which is considered to ensure resistance against simple side-channel analysis attacks in the literature, is not sufficient to prevent either simple SCA or horizontal address-bit DPA attacks. We also evaluated an approach which is based on the activity of the field multiplier to increase the inherent resistance of the design against attacks performed.
High-Precision Log-Ratio Spot Position Detection Algorithm with a Quadrant Detector under Different SNR Environments
Authors: Huo Li , Wu Zhiyong , Wu Jiabin , Gao Shijie , Chen Yunshan , Song Yinuo , Wang Shuaifei
Published: April 2022

In atmospheric laser communication, a beam is transmitted through an atmospheric channel, and the photocurrent output from a quadrant detector (QD) used as the tracking sensor fluctuates significantly. To ensure uninterrupted communication and to adapt to such fluctuations, in this paper we apply logarithmic amplifiers to process the output signals of a QD. To further improve the measurement accuracy of the spot position, we firstly propose an integral infinite log-ratio algorithm (IILRA) and an integral infinity log-ratio algorithm based on the signal-to-noise ratio (BSNR-IILRA) through analysis of the factors influencing the measurement error considering the signal-to-noise ratio (SNR) parameter. Secondly, the measurement error of the two algorithms under different SNRs and their variations are analyzed. Finally, a spot position detection experiment platform is built to correctly and efficiently verify the two algorithms. The experimental results show that when the SNR is 54.10 dB, the maximum error and root mean square error of the spot position of the IILRA are 0.0054 mm and 0.0039 mm, respectively, which are less than half those of the center approximation algorithm (CAA). When the SNR is 23.88 dB, the maximum error and root mean square error of the spot position of the BSNR-IILRA are 0.0046 mm and 0.0034 mm, respectively, which are one-thirtieth and one-twentieth of the CAA, respectively. The spot position measurement accuracy of the two proposed algorithms is significantly improved compared with the CAA.
Beyond the Backyard: GIS Analysis of Public Green Space Accessibility in Australian Metropolitan Areas
Authors: Hsu Yi-Ya , Hawken Scott , Sepasgozar Samad , Lin Zih-Hong
Published: April 2022

During times of stress and social pressure, urban green space provides social, cultural, and economic resources that help individuals and communities cope. Green space accessibility is, therefore, an important indicator related to people’s health and welfare. However, green space accessibility is not even throughout urban areas, with some areas better served with green space than others. Green space patterning is, therefore, a major environmental justice challenge. This research uses GIS approaches to analyze and understand urban green space access of urban communities in the Australian metropolitan areas of Adelaide, Melbourne, Sydney, and Brisbane. We calculate indicators to describe green space access in relation to different green space patterns within different metropolitan zones, including the inner urban, suburban, and peri urban. We use the best available open data from the Australian census of 2017 to calculate green space accessibility. Our results describe the relationship between population density and green space distribution and patterning in the four metropolitan areas. We find that even cities which are generally thought of as liveable have considerable environmental justice challenges and inequity and must improve green space access to address environmental inequity. We also find that a range type of measures can be used to better understand green space accessibility. Accessibility varies greatly both within metropolitan areas and also from city to city. Through improving our understanding of the green space accessibility characteristics of Australian metropolitan areas, the result of this study supports the future planning of more just and equal green cities.
Identifying the Challenges to Sustainable Urban Last-Mile Deliveries: Perspectives from Public and Private Stakeholders
Authors: Maxner Thomas , Dalla Chiara Giacomo , Goodchild Anne
Published: April 2022

While freight transportation is a necessary activity to sustain cities’ social and economic life—enabling the movement and deployment of goods and services in urbanized areas—it also accounts for a significant portion of carbon dioxide (CO2) emissions. The urban freight ecosystem is a complex network of agents, both public and private. Reducing CO2 emissions from urban freight requires the collaboration and coordination between those agents, but the motivations behind their goals, strategies for achieving those goals, and the challenges faced by each agent may differ. In this paper, we document the strategies aimed at reducing CO2 emissions considered by cities and private companies with the goal of understanding the challenges to progress faced by each. To accomplish this, we interviewed officials from purposefully sampled city departments in North America and private companies involved in city logistics. We found that cities face challenges related to a lack of strong leadership, resources, and policy tools. Companies must consider technological challenges, costs, and their workforce before reducing emissions. Cities and companies are challenged by the disaggregated nature of the urban freight “system”—a system that is not organized at the municipal scale and that is driven by performance and customer expectations.
An Investigation of the Challenges Faced by the Disabled Population and the Implications for Accessible Tourism: Evidence from a Mediterranean Destination
Authors: Kamyabi Marjan , Alipour Habib
Published: April 2022

The purpose of this study is to examine the challenges and deficits faced by people with disabilities and the implications for the development of accessible tourism in the case of North Cyprus. Although this destination market represents a significant portion of tourism in the Mediterranean, it is still poorly understood. In this study, 250 questionnaires were distributed to people with disabilities. Linear regressions, ANOVA, and t-tests were used for data analysis. The results show that despite the destination’s great potential in terms of attractions and recreational facilities, there are measurable deficits in accessible tourism. If tourism operators want to take advantage of the rising tide of accessible tourism to attract more tourists and have a competitive advantage in this growing niche market, they should improve infrastructure facilities to meet the needs of disabled tourists. In particular, this includes providing information for disabled tourists, improving the existing inadequate access to various venues, equipping transportation modes and refreshment facilities for the disabled population, and ensuring adequate access to public places. Last but not least, a cultural orientation approach that educates residents to respect and accept the rights of the disabled population must be adopted. This study provides insights into the needs of people with disabilities and formulates guidelines for adapting and developing this market for destinations that depend on tourism.
Decide to Take Entrepreneurial Action: Role of Entrepreneurial Cognitive Schema on Cognitive Process of Exploiting Entrepreneurial Opportunity
Authors: Wang Zhongming , Shao Yixuan
Published: April 2022

Given its impact on preference for different information, the cognitive schema is recognized as a critical mechanism for people to make up their minds on willingness to act. However, how entrepreneurial cognitive schema influences cognitive processes remains unclear. Based on entrepreneurial action theory and information processing theory, we delineate the relationship between entrepreneurial cognitive schema and decision of entrepreneurial action by decomposing the cognitive process of comprehending external information related to entrepreneurial opportunity. We randomized 123 participants into different priming groups and collected their decision policies with a conjoint analysis experiment. Firstly, we found the individuated cognitive process, since the positive effect of founding rates is strengthened, and dissolution rates are reduced by positive knowledge-relatedness. Further, we partly validated the moderating role of entrepreneurial cognitive schema, with a more positive relationship between founding rates and willingness to act, and between knowledge-relatedness and willingness to act when participants are primed with this future-focused schema. This paper proves one critical cognitive unit while making a decision to act on entrepreneurial opportunity and indicated an active role of entrepreneurial cognitive schema in enabling people to emphasize and make better use of relevant information.
Understanding Novice and Experienced Teachers’ Cognitions and Practices for Sustainable Teacher Development: The Case of Form-Focused Instruction in English Language Teaching
Authors: Sun Qiang , Zhang Lawrence Jun
Published: April 2022

Framed in Complexity Theory, this paper presents a multi-case study of Chinese university English teachers’ cognitions and practices about form-focused instruction in English language teaching. Four teachers, including two novice teachers and two experienced ones, were involved in the study. A triangulation method, including semi-structured interviews, classroom observations and stimulated recall interviews, was used to examine and compare their cognitions and practices. Research findings reveal that all teachers favoured focus on form instruction rather than focus on forms instruction in English teaching in their cognitions; however, the two novice teachers failed to implement focus on form instruction in practices, whereas the two experienced teachers carried it out consistently. The result calls for effective teacher education programmes for sustainable teacher development, particularly in sustaining the development of novice teachers’ knowledge about how to implement focus on form instruction in pedagogical practice. The implications arising from this study for L2 teacher education in China and similar L2 contexts are also discussed.