bluuebunny/crossref_metadata_2025 huggingface dataset:
Extraction and Characterization of Hemicelluloses from a Softwood Acid Sulfite Pulp
Authors: Vincent Pauline , Ham-Pichavant Frédérique , Michaud Christelle , Mignani Gérard , Mastroianni Sergio , Cramail Henri , Grelier Stéphane
Published: June 2021

Hemicelluloses were extracted from a softwood acid sulfite pulp in a three-step procedure. Further delignification step resulted in a holocellulose pulp containing only 1.7 wt.% of the lignin left. Cold caustic extraction (CCE) with 18 wt.% NaOH at 60 °C for 1 h was performed to solubilize hemicelluloses of the holocellulose. An unbleached cellulose pulp was then obtained 97% pure, which indicates that 89% of the hemicelluloses were removed. After purification, extraction yields between 1.1 wt.% and 9.5 wt.% were obtained from the delignified pulp and the hemicelluloses’ chemical compositions and structures were investigated by 1H, 13C nuclear magnetic resonance spectroscopy (NMR) and two-dimensional NMR by correlation spectroscopy (2D-COSY) and proton-detected heteronuclear single-quantum correlation (2D-HSQC), high-performance anion-exchange chromatography coupled with a pulsed amperometry detector (HPAEC-PAD), size-exclusion chromatography coupled with a refractive index detector (SEC-RI) and thermogravimetric analyses (TGA). Hemicelluloses were obtained with a purity of 96%, with short cellulosic chains as the only residue. Sulfite pulping modified the hemicelluloses’ structure, and it was found that two types of hemicelluloses were isolated, glucomannans, predominant at 67%, and methylglucuronoxylans. Finally, alkali-soluble hemicelluloses displayed relatively narrow size distributions and low molar masses, Mw varying between 18,900 and 30,000 g/mol after acid sulfite pulping.
Fabrication of Flexible pH-Responsive Agarose/Succinoglycan Hydrogels for Controlled Drug Release
Authors: Hu Yiluo , Kim Yohan , Hong Inki , Kim Moosung , Jung Seunho
Published: June 2021

Agarose/succinoglycan hydrogels were prepared as pH-responsive drug delivery systems with significantly improved flexibility, thermostability, and porosity compared to agarose gels alone. Agarose/succinoglycan hydrogels were made using agarose and succinoglycan, a polysaccharide directly isolated from Sinorhizobium meliloti. Mechanical and physical properties of agarose/succinoglycan hydrogels were investigated using various instrumental methods such as rheological measurements, attenuated total reflection–Fourier transform infrared (ATR-FTIR) spectroscopic analysis, X-ray diffraction (XRD), and field-emission scanning electron microscopy (FE-SEM). The results showed that the agarose/succinoglycan hydrogels became flexible and stable network gels with an improved swelling pattern in basic solution compared to the hard and brittle agarose gel alone. In addition, these hydrogels showed a pH-responsive delivery of ciprofloxacin (CPFX), with a cumulative release of ~41% within 35 h at pH 1.2 and complete release at pH 7.4. Agarose/succinoglycan hydrogels also proved to be non-toxic as a result of the cell cytotoxicity test, suggesting that these hydrogels would be a potential natural biomaterial for biomedical applications such as various drug delivery system and cell culture scaffolds.
Novel Crosslinked Sulfonated PVA/PEO Doped with Phosphated Titanium Oxide Nanotubes as Effective Green Cation Exchange Membrane for Direct Borohydride Fuel Cells
Authors: Gouda Marwa H. , Elessawy Noha A. , Toghan Arafat
Published: June 2021

A direct borohydride fuel cell (DBFC) is a type of low temperature fuel cell which requires efficient and low cost proton exchange membranes in order to commercialize it. Herein, a binary polymer blend was formulated from inexpensive and ecofriendly polymers, namely polyethylene oxide (PEO) and poly vinyl alcohol (PVA). Phosphated titanium oxide nanotube (PO4TiO2) was synthesized from a simple impregnation–calcination method and later embedded for the first time as a doping agent into this polymeric matrix with a percentage of 1–3 wt%. The membranes’ physicochemical properties such as oxidative stability and tensile strength were enhanced with increasing doping addition, while the borohydride permeability, water uptake, and swelling ratio of the membranes decreased with increasing PO4TiO2 weight percentage. However, the ionic conductivity and power density increased to 28 mS cm−1 and 72 mWcm−2 respectively for the membrane with 3 wt% of PO4TiO2 which achieved approximately 99% oxidative stability and 40.3 MPa tensile strength, better than Nafion117 (92% RW and 25 MPa). The fabricated membrane with the optimum properties (PVA/PEO/PO4TiO2-3) achieved higher selectivity than Nafion117 and could be efficient as a proton exchange membrane in the development of green and low cost DBFCs.
The Effect of the Temperature and Moisture to the Permeation Properties of PEO-Based Membranes for Carbon-Dioxide Separation
Authors: Nedeljkovic Dragutin
Published: June 2021

An increased demand for energy in recent decades has caused an increase in the emissions of combustion products, among which carbon-dioxide is the most harmful. As carbon-dioxide induces negative environmental effects, like global warming and the greenhouse effect, a decrease of the carbon-dioxide emission has emerged as one of the most urgent tasks in engineering. In this work, the possibility for the application of the polymer-based, dense, mixed matrix membranes for flue gas treatment was tested. The task was to test a potential decrease in the permeability and selectivity of a mixed-matrix membrane in the presence of moisture and at elevated temperature. Membranes are based on two different poly(ethylene oxide)-based polymers filled with two different zeolite powders (ITR and IWS). An additive of detergent type was added to improve the contact properties between the zeolite and polymer matrix. The measurements were performed at three different temperatures (30, 60, and 90 °C) under wet conditions, with partial pressure of the water equal to the vapor pressure of the water at the given temperature. The permeability of carbon-dioxide, hydrogen, nitrogen, and oxygen was measured, and the selectivity of the carbon-dioxide versus other gases was determined. Obtained results have shown that an increase of temperature and partial pressure of the vapor slightly increase both the selectivity and permeability of the synthesized membranes. It was also shown that the addition of the zeolite powder increases the permeability of carbon-dioxide while maintaining the selectivity, compared to hydrogen, oxygen, and nitrogen.
Tribological Behavior of a Rubber-Toughened Wood Polymer Composite
Authors: Mazzanti Valentina , Fortini Annalisa , Malagutti Lorenzo , Ronconi Giulia , Mollica Francesco
Published: June 2021

Wood polymer composites or WPCs are increasingly used as substitutes for natural wood in outdoor applications due to their better environmental sustainability and the consequent reduction in carbon footprint. In this paper, the presence of an elastomer used as a toughening agent (Santoprene by Exxon Mobil) in a polypropylene-based WPC containing 50 wt % wood flour was investigated in terms of its tribological behavior by dry sliding wear tests. These were performed after two environmental pre-conditioning treatments, i.e., drying and water soaking. The ball-on-disk configuration under a constant load was chosen along two sliding distances. Dynamic mechanical thermal analyses were used to reveal the effect of the toughening agent on the storage modulus and damping factor of the composites. Results in terms of weight loss measurement and coefficient of friction were obtained, together with surface morphology analysis of the worn surfaces at the scanning electron microscope and 3D profilometer. An abrasive wear mechanism was identified, and it was shown that the toughening agent improved wear resistance after both pre-treatments. This beneficial effect can be explained by the increase in strain at break of the WPC containing the elastomer. On the other hand, the water soaking pre-treatment produced severe damage, and the loss of material cannot be completely compensated by the presence of the toughening agent.
Effect of Friction Stir Welding Techniques and Parameters on Polymers Joint Efficiency—A Critical Review
Authors: Pereira Miguel A. R. , Amaro Ana M. , Reis Paulo N. B. , Loureiro Altino
Published: June 2021

The objective of current work is to analyse the influence of different welding techniques and welding parameters on the morphology and mechanical strength of friction stir welds (FSW) in polymers, based on data collected in the literature. In the current work, only articles that provide data on the joint efficiency, or sufficient information to estimate it are considered. The process using conventional tool is presented and compared with new procedures developed for FSW of polymers, such as those using tools with heated stationary shoulder, preheating of the polymer or double-side passage of the tool. The influence of tool rotational speed (w), welding speed (v), tilt angle and geometry of the pin are discussed. This work focuses on the polymers most studied in the literature, polyethylene (PE) and polypropylene (PP). The use of external heating and tools with stationary shoulder proved to be of great importance in improving the surface finish, reducing defects, and increasing the mechanical strength of the welds. The increase in the w/v ratio increased the joint efficiency, especially when using conventional tools on PE. A trend was obtained for conventional FSW, but it was difficult to establish mathematical relationships, because of the variability of welding conditions.
Thermal Stability of Nanosilica-Modified Poly(vinyl chloride)
Authors: Tomaszewska Jolanta , Sterzyński Tomasz , Walczak Damian
Published: June 2021

The thermal stability of PVC with 1 wt % of spherical porous nanosilica, prepared by roll milling at processing time varied from 1 to 20 min, was investigated by means of visual color changes, Congo red, and thermogravimetric tests (TGA and DTG), as a function of rolling time and composition of PVC matrix. The melt flow rate (MFR) measurements were realized to identify the degradation-induced changes of processing properties. A high level of gelation of the PVC matrix for all samples was verified by DSC (differential scanning calorimetry). It was found that the addition of porous nanosilica to absorb a certain volume of HCl, produced by dehydrochlorination reaction, leads to an improvement of thermal stability, an effect observed in a form of minor color changes of the samples, lower evolution of gas hydrogen chloride, and slight changes of the MFR value. It was demonstrated that the TGA measurements are not sufficiently sensible to detect the degradation of PVC at the processing conditions, i.e., at the temperature equal to 220 °C and below this temperature.
Vertical Orientation of Liquid Crystal on Polystyrene Substituted with n-Alkylbenzoate-p-oxymethyl Pendant Group as a Liquid Crystal Precursor
Authors: Seo Kyutae , Kang Hyo
Published: June 2021

We synthesized a series of polystyrene derivatives modified with precursors of liquid crystal (LC) molecules via polymer modification reactions. Thereafter, the orientation of the LC molecules on the polymer films, which possess part of the corresponding LC molecular structure, was investigated systematically. The precursors and the corresponding derivatives used in this study include ethyl-p-hydroxybenzoate (homopolymer P2BO and copolymer P2BO#, where # indicates the molar fraction of ethylbenzoate-p-oxymethyl in the side chain (# = 20, 40, 60, and 80)), n-butyl-p-hydroxybenzoate (P4BO), n-hexyl-p-hydroxybenzoate (P6BO), and n-octyl-p-hydroxybenzoate (P8BO). A stable and uniform vertical orientation of LC molecules was observed in LC cells fabricated with P2BO#, with 40 mol% or more ethylbenzoate-p-oxymethyl side groups. In addition, the LC molecules were oriented vertically in LC cells fabricated with homopolymers of P2BO, P4BO, P6BO, and P8BO. The water contact angle on the polymer films can be associated with the vertical orientation of the LC molecules in the LC cells fabricated with the polymer films. For example, vertical LC orientation was observed when the water contact angle of the polymer films was greater than ~86°. Good orientation stability was observed at 150 °C and with 20 J/cm2 of UV irradiation for LC cells fabricated with the P2BO film.
Linear/Ladder-Like Polysiloxane Block Copolymers with Methyl-, Trifluoropropyl- and Phenyl- Siloxane Units for Surface Modification
Authors: Ostanin Stepan A. , Kalinin Alexei V. , Bratsyhin Yurij Yu. , Saprykina Natalia N. , Zuev Vjacheslav V.
Published: June 2021

Multiblock copolymers containing linear polydimethylsiloxane or polymethyltrifluoropropylsiloxane and ladder-like polyphenylsiloxane were synthesized in a one-step pathway. The functional homopolymer blocks and final multiblock copolymers were characterized using solution and solid-state multinuclear 1H, 13C, 19F, and 29Si NMR spectroscopy. It was shown that the ladder-like block contains silanol units, which influence the adhesion properties of multiblock copolymers and morphology of their casted films. The adhesion to metals and mechanical properties of multiblock copolymers were tested. The SEM study of casted films of multiblock copolymers shows the variety of formed morphologies, including long-strip-like or globular.
Merezhkovsky’s Neo-Christianity of the Third Testament: From Symbolist Historiosophy to Radical Politics
Authors: Polonsky Vadim
Published: June 2021

This article places Dmitry Merezhkovsky’s Chiliastic concept of Three Testaments into a unified structure. The author analyzes the writer’s integral system of Christological, anthropological, and historiosophicidiomyths and meta-symbols. He studies the religious, philosophical, and aesthetic genesis of the semantic transformation of traditional theological constructions and the doctrinal compilation of Russian fin de siècle culture dominant elements. It is shown how religious Modernist mythmaking alters political reality in Merezhkovsky’s mind and draws him towards radical ideologies of the extreme left and right.
Satellite Image Time Series Analysis for Big Earth Observation Data
Authors: Simoes Rolf , Camara Gilberto , Queiroz Gilberto , Souza Felipe , Andrade Pedro R. , Santos Lorena , Carvalho Alexandre , Ferreira Karine
Published: June 2021

The development of analytical software for big Earth observation data faces several challenges. Designers need to balance between conflicting factors. Solutions that are efficient for specific hardware architectures can not be used in other environments. Packages that work on generic hardware and open standards will not have the same performance as dedicated solutions. Software that assumes that its users are computer programmers are flexible but may be difficult to learn for a wide audience. This paper describes sits, an open-source R package for satellite image time series analysis using machine learning. To allow experts to use satellite imagery to the fullest extent, sits adopts a time-first, space-later approach. It supports the complete cycle of data analysis for land classification. Its API provides a simple but powerful set of functions. The software works in different cloud computing environments. Satellite image time series are input to machine learning classifiers, and the results are post-processed using spatial smoothing. Since machine learning methods need accurate training data, sits includes methods for quality assessment of training samples. The software also provides methods for validation and accuracy measurement. The package thus comprises a production environment for big EO data analysis. We show that this approach produces high accuracy for land use and land cover maps through a case study in the Cerrado biome, one of the world’s fast moving agricultural frontiers for the year 2018.
Mapping the Location and Extent of 2019 Prevent Planting Acres in South Dakota Using Remote Sensing Techniques
Authors: Lawal Afolarin , Kerner Hannah , Becker-Reshef Inbal , Meyer Seth
Published: June 2021

The inability of a farmer to plant an insured crop by the policy’s final planting date can pose financial challenges for the grower and cause reduced production for a widely impacted region. Prevented planting is primarily caused by excess moisture or rainfall such as the catastrophic flooding and widespread conditions that prevented active field work in the midwestern region of United States in 2019. While the Farm Service Agency reports the number of such “prevent plant” acres each year at the county scale, field-scale maps of prevent plant fields—which would enable analyses related to assessing and mitigating the impact of climate on agriculture—are not currently available. The aim of this study is to demonstrate a method for mapping likely prevent plant fields based on flood mapping and historical cropland maps. We focused on a study region in eastern South Dakota and created flood maps using Landsat 8 and Sentinel 1 images from 2018 and 2019. We used automatic threshold-based change detection using NDVI and NDWI to accentuate changes likely caused by flooding. The NDVI change detection map showed vegetation loss in the eastern parts of the study area while NDWI values showed increased water content, both indicating possible flooding events. The VH polarization of Sentinel 1 was also particularly useful in identifying potential flooded areas as the VH values for 2019 were substantially lower than those of 2018, especially in the northern part of the study area, likely indicating standing water or reduced biomass. We combined the flood maps from Landsat 8 and Sentinel 1 to form a complete flood likelihood map over the entire study area. We intersected this flood map with a map of fallow pixels extracted from the Cropland Data Layer to produce a map of predicted prevent plant acres across several counties in South Dakota. The predicted figures were within 10% error of Farm Service Agency reports, with low errors in the most affected counties in the state such as Beadle, Hanson, and Hand.
Coastal Remote Sensing: Merging Physical, Chemical, and Biological Data as Tailings Drift onto Buffalo Reef, Lake Superior
Authors: Kerfoot W. Charles , Hobmeier Martin M. , Swain Gary , Regis Robert , Raman Varsha K. , Brooks Colin N. , Grimm Amanda , Cook Chris , Shuchman Robert , Reif Molly
Published: June 2021

On the Keweenaw Peninsula of Lake Superior, two stamp mills (Mohawk and Wolverine) discharged 22.7 million metric tonnes (MMT) of tailings (1901–1932) into the coastal zone off the town of Gay. Migrating along the shoreline, ca. 10 MMT of the tailings dammed stream and river outlets, encroached upon wetlands, and contaminated recreational beaches. A nearly equal amount of tailings moved across bay benthic environments into critical commercial fish spawning and rearing grounds. In the middle of the bay, Buffalo Reef is important for commercial and recreational lake trout and lake whitefish production (ca. 32% of the commercial catch in Keweenaw Bay, 22% along southern Lake Superior). Aerial photographs (1938–2016) and five LiDAR and multispectral over-flights (2008–2016) emphasize: (1) the enormous amounts of tailings moving along the beach; and (2) the bathymetric complexities of an equal amount migrating underwater across the shelf. However, remote sensing studies encounter numerous specific challenges in coastal environments. Here, we utilize a combination of elevation data (LiDAR digital elevation/bathymetry models) and in situ studies to generate a series of physical, chemical, and biological geospatial maps. The maps are designed to help assess the impacts of historical mining on Buffalo Reef. Underwater, sand mixtures have complicated multispectral bottom reflectance substrate classifications. An alternative approach, in situ simple particle classification, keying off distinct sand end members: (1) allows calculation of tailings (stamp sand) percentages; (2) aids indirect and direct assays of copper concentrations; and (3) permits determinations of density effects on benthic macro-invertebrates. The geospatial mapping shows how tailings are moving onto Buffalo Reef, the copper concentrations associated with the tailings, and how both strongly influence the density of benthic communities, providing an excellent example for the International Maritime Organization on how mining may influence coastal reefs. We demonstrate that when large amounts of mine tailings are discharged into coastal environments, temporal and spatial impacts are progressive, and strongly influence resident organisms. Next steps are to utilize a combination of hi-resolution LiDAR and sonar surveys, a fish-monitoring array, and neural network analysis to characterize the geometry of cobble fields where fish are successful or unsuccessful at producing young.
An Adaptive Capsule Network for Hyperspectral Remote Sensing Classification
Authors: Ding Xiaohui , Li Yong , Yang Ji , Li Huapeng , Liu Lingjia , Liu Yangxiaoyue , Zhang Ce
Published: June 2021

The capsule network (Caps) is a novel type of neural network that has great potential for the classification of hyperspectral remote sensing. However, the Caps suffers from the issue of gradient vanishing. To solve this problem, a powered activation regularization based adaptive capsule network (PAR-ACaps) was proposed for hyperspectral remote sensing classification, in which an adaptive routing algorithm without iteration was applied to amplify the gradient, and the powered activation regularization method was used to learn the sparser and more discriminative representation. The classification performance of PAR-ACaps was evaluated using two public hyperspectral remote sensing datasets, i.e., the Pavia University (PU) and Salinas (SA) datasets. The average overall classification accuracy (OA) of PAR-ACaps with shallower architecture was measured and compared with those of the benchmarks, including random forest (RF), support vector machine (SVM), 1-dimensional convolutional neural network (1DCNN), two-dimensional convolutional neural network (CNN), three-dimensional convolutional neural network (3DCNN), Caps, and the original adaptive capsule network (ACaps) with comparable network architectures. The OA of PAR-ACaps for PU and SA datasets was 99.51% and 94.52%, respectively, which was higher than those of benchmarks. Moreover, the classification performance of PAR-ACaps with relatively deeper neural architecture (four and six convolutional layers in the feature extraction stage) was also evaluated to demonstrate the effectiveness of gradient amplification. As shown in the experimental results, the classification performance of PAR-ACaps with relatively deeper neural architecture for PU and SA datasets was also superior to 1DCNN, CNN, 3DCNN, Caps, and ACaps with comparable neural architectures. Additionally, the training time consumed by PAR-ACaps was significantly lower than that of Caps. The proposed PAR-ACaps is, therefore, recommended as an effective alternative for hyperspectral remote sensing classification.
Continuously Vegetation Greening over Inner Mongolia for the Past Three Decades
Authors: Zhang Hui , Zhang Xin , Shang Yi , Kattel Giri , Miao Lijuan
Published: June 2021

The warming climate has rapidly altered vegetation growth in drylands, and consequently, has put great pressure on sustainable livelihoods. Various datasets have been applied from local to global scale to study vegetation dynamics and there is a lack of solid comparison among multiple datasets. Note that vegetation growth might shift over time and the greening and browning components over a long-time span might be masked by a linear trend. Here, we aim to monitor the long-term and nonlinear dynamics in vegetation greenness for Inner Mongolia (an important part of dryland Asia). As a useful tool that indicates vegetation greenness, NDVI (Normalized Difference Vegetation Index) and LAI (Leaf Area Index) integrals derived from the GIMMS (Global Inventory Modelling and Mapping Studies) NDVI3g and the GIMMS LAI3g products are applied. During the period of 1982-2016, NDVI/LAI integrals have an overall acceptable consistency in characterizing the trends of vegetation greenness, with NDVI large/small integrals and LAI large/small integrals increase at a rate of 0.96, 1.72, 2.23, and 3.13 per decade, respectively. Inner Mongolia experienced a noticeable greening process (71% and 82% greening area in NDVI large/small integrals, 67% and 73% greening area in LAI large/small integrals), despite the fragmentally distributed browning trends in eastern and partial northern Inner Mongolia. As inferred from nonlinear trend analysis, we found the greening process is still prevalent. The browning of eastern Inner Mongolia under the linear analysis was actually transferring from browning to greening, while the greening trend in northern Inner Mongolia was changing to browning. Increased occurrences in the frequency of breakpoints after 1999 suggest that previously stable vegetation ecology is more sensitive to external disturbances such as altered climatic impact and anthropogenic intervention.
Comparison of Machine Learning Methods to Up-Scale Gross Primary Production
Authors: Yu Tao , Zhang Qiang , Sun Rui
Published: June 2021

Eddy covariance observation is an applicable way to obtain accurate and continuous carbon flux at flux tower sites, while remote sensing technology could estimate carbon exchange and carbon storage at regional and global scales effectively. However, it is still challenging to up-scale the field-observed carbon flux to a regional scale, due to the heterogeneity and the unstable air conditions at the land surface. In this paper, gross primary production (GPP) from ground eddy covariance systems were up-scaled to a regional scale by using five machine learning methods (Cubist regression tree, random forest, support vector machine, artificial neural network, and deep belief network). Then, the up-scaled GPP were validated using GPP at flux tower sites, weighted GPP in the footprint, and MODIS GPP products. At last, the sensitivity of the input data (normalized difference vegetation index, fractional vegetation cover, shortwave radiation, relative humidity and air temperature) to the precision of up-scaled GPP was analyzed, and the uncertainty of the machine learning methods was discussed. The results of this paper indicated that machine learning methods had a great potential in up-scaling GPP at flux tower sites. The validation of up-scaled GPP, using five machine learning methods, demonstrated that up-scaled GPP using random forest obtained the highest accuracy.
Applying an Adaptive Signal Identification Method to Improve Vessel Echo Detection and Tracking for SeaSonde HF Radar
Authors: Chuang Laurence Zsu-Hsin , Chen Yu-Ru , Chung Yu-Jen
Published: June 2021

To enhance remote sensing for maritime safety and security, various sensors need to be integrated into a centralized maritime surveillance system (MSS). High-frequency (HF) radar systems are a type of mainstream technology widely used in international marine remote sensing and have great potential to detect distant sea surface targets due to their over-the-horizon (OTH) capability. However, effectively recognizing targets in spectra with intrinsic strong disturbance echoes and random environmental noise is still challenging. To avoid the above problem, this paper proposes an adaptive signal identification method to detect target signals based on a rapid and flexible threshold. By integrating a watershed segmentation algorithm, the subsequent direction result can be used to automatically compute the direction of arrival (DOA) of the targets. To assist in the orientation of the object, forward intersections are integrated with the technique. Hence, the proposed technique can effectively recognize vessel echoes with automatic identification system (AIS) verification. Experiments have demonstrated the promising feasibility of the proposed method’s performance.
The Reshaping of Daily Time during the COVID-19 Pandemic: Lone Parent’s Work-Family Articulation in a Low-Intensity Lockdown
Authors: Sánchez-Mira Núria , Bernardi Laura , Moles-Kalt Benjamin , Sabot Cléolia
Published: June 2021

The COVID-19 pandemic and related restrictions have triggered simultaneous changes across multiple life domains within a very short timeframe. This major shock has seriously challenged the ability of families to adapt to unanticipated changes over which they had little control. Switzerland instigated a low-intensity lockdown in response to COVID-19 in the spring of 2020. The resulting alterations to family life included changes to employment situations and working conditions (such as layoffs, temporary unemployment and home-based work) and the need to arrange home-schooling and childcare. This study examines how a sample of individuals with a trajectory of lone parenthood living in French-speaking Switzerland adapted their everyday lives to accommodate the shifting demands in the domains of employment and family responsibilities. Interviews were conducted between April and June 2020 for the longitudinal project “The multiple paths of lone parenthood”. Using this data, we analysed the COVID-related changes to work and family life, focusing on their time structuring. We found that parents who remained employed faced the greatest time pressures, although their experiences varied significantly depending on the adaptability of their work schedules, as well as the child(ren)’s age(s) and degree of autonomy. Home-based work and home-schooling resulted in more flexible schedules, although parents with the greatest work and family demands sought more time-structured organisation to facilitate their articulation. Social support was a crucial buffer for parents with conflicting demands across domains.
Optimization Model of Regional Traffic Signs for Inducement at Road Works
Authors: Wang Lianzhen , Zhang Han , Shi Lingyun , He Qingling , Xu Huizhi
Published: June 2021

A variety of pipelines are distributed under urban roads. The upgrading of pipelines is bound to occupy certain road resources, compress the driving space of motor vehicles for a long time, aggravate the traffic congestion in the construction section, and then affect the traffic operation of the whole region. A reasonable layout of traffic signs for inducement to guide the traffic flow in the area where the construction section is located is conducive to promoting a balanced distribution of traffic flow in the regional road network, so as to achieve the reduction of automobile exhaust emissions and the sustainable development of traffic. In this paper, the layout optimization method of regional traffic signs for inducement is proposed. Taking the maximum amount of guidance information that the regional traffic signs can provide as the objective function, and taking the traffic volume, the characteristics of intersection nodes and the standard deviation of road saturation as the independent variables, the layout optimization model of guidance facilities is constructed, which can optimize the layout of traffic guidance signs in the area affected by the construction section, and achieve the goal that the minimum number of facilities can provide the maximum amount of guidance information. The results of the case study show that among the 64 alternative locations where traffic guidance signs can be set in the study area, eight optimal locations are finally determined as the setting points of guidance facilities through this model, and the effective increment of guidance information is the largest at this time. The model proposed in this paper can be used for reference to promote the sustainable development of traffic in the area where the construction section is located.
A Driving Behavior Distribution Fitting Method Based on Two-Stage Hybrid User Classification
Authors: Su Han , Zhang Qian , Wang Wanying , Tang Xiaoan
Published: June 2021

Determining the distribution fitting of traditional private vehicle user driving behavior is an effective way to understand the differences between different users and provides valuable information on user travel demands. The classification of users is significant to product improvement, precision marketing, and driving recommendations. This study proposed a method which includes four aspects: (1) data collection; (2) data preprocessing; (3) data analysis—a two-stage hybrid user classification, and (4) distribution fitting method. A two-stage hybrid user classification method is used to cluster traditional vehicle users. First, the first-stage classification of the classification method extracts the daily typical time–mileage-series travel patterns (TMTP) to obtain user driving time characteristics. This first-stage classification also extracts the mean and standard deviation of the daily vehicle mileage traveled (DVMT) to express user driving demands. Next, users are divided by K-means based on the driving time characteristics and driving demands from the first stage. Finally, a three-parameter log-normal distribution is used to fit the DVMT of different user types. Comparison with traditional clustering based on the mean and standard deviation and the proportion of each vehicle’s time series in the TMTP types, this study reveals that the new methods provide significant advantages in analyzing driving behavior and high reference value for enterprises making electric vehicle driving range recommendations, car market segmentation, and policy making decisions.
Fostering Self-Protection against Impacts of Heavy Rain at the Municipal Level
Authors: Werg Jana Lorena , Grothmann Torsten , Löchtefeld Stefan
Published: June 2021

Local governments are highly relevant actors when it comes to mitigating climate change impacts such as flooding. Not only do they need to implement regulatory and infrastructural measures, but they also need to promote complementing self-protective measures at the household level. The individual motivation of municipal actors to pursue climate adaptation can be important for the implementation of such measures, obviously alongside several other factors, such as financial and administrative issues. A questionnaire survey with a non-random sample of 77 local government actors from 15 of the 16 German federal states was conducted, focusing on potential key factors concerning the motivation to implement adaptation measures against hazardous impacts of heavy rain. Additionally, the perceived effectiveness and realizability of selected municipal structural measures and of activation measures promoting self-protective behavior were collected. It can be shown that the perceived realizability of adaptation measures as well as knowledge of risk and adaptation may be key factors in the motivation to implement both activation and structural measures, while motivation and implementation are only partially related. The results imply a need for the evaluation of activation measures and a need for further research on the motivation of municipal actors to implement activation measures.
The Monitoring of Selected Heavy Metals Content and Bioavailability in the Soil-Plant System and Its Impact on Sustainability in Agribusiness Food Chains
Authors: Feszterová Melánia , Porubcová Lýdia , Tirpáková Anna
Published: June 2021

This study assisted in identifying and preventing the increase in heavy metals in soil and winter wheat. Its accumulation can affect cultivated crops, quality and crop yields, and consumers’ health. Selected heavy metals were analyzed using the GTAAS method. They were undertaken on selected heavy metals content (Cd, Cu, Pb, and Zn) in arable soils at three sites in Slovakia and their accumulation in parts of cultivated winter wheat. Our study showed that the limit value of Cd in soil samples was exceeded in the monitored arable soils from 2017–2019. The average content values of Cu and Zn did not exceed the limit values, even in Pb values (except for the spring period). The analyses also showed that the heavy metals content for plants bioavailable in soil did not exceed the statutory critical values for Cd, Cu, and Zn’s average content values. However, Pb content exceeded permitted critical values. Heavy metals bioaccumulation (Zn, Cu) was within the limit values in wheat. Analyzed Cd content in wheat roots and Pb content were determined in all parts of wheat except grain. The study showed that grain from cultivated winter wheat in monitored arable soils is not a risk for consumers.
Macau Squares: Discerning the Triadic Sign Model of Built-Heritage
Authors: Chua Mark Hansley Yang
Published: June 2021

Despite an objectivist vision by many heritage conservation bodies, the extant literature mostly dwells on the value of heritage as something subjective and arbitrary. Semiotically treating built-heritage as a Peircian triadic sign, instead of a dyadic sign, could reconcile this apparent dichotomy. Some squares of Macau]’s Historic Centre are taken as case study. Using a Coasian perspective, this paper argues how the meaning-delimiting consequences of a triadic semiotic framework allow for a lower transaction cost in valuation and eventually a more sustainable conservation. This has been confirmed by an expert decision in designating the relatively new squares as heritage protected areas.
Role Reversal! Financial Performance as an Antecedent of ESG: The Moderating Effect of Total Quality Management
Authors: Chams Nour , García-Blandón Josep , Hassan Khaled
Published: June 2021

Shifting from short-term profit maximizing strategies to more sustainable long-term ones, the corporate world has been exerting extra effort to adopt environmental, social, and governance (ESG) performances. However, the loop question remains unsolved: is ESG financially-driven or is financial performance (FIN) ESG-driven? Building on the slack resources theory and bridging three management literatures, this analysis relies on a six-year panel dataset of multinational organizations from different industries. A distributed lag regression model is proposed to empirically investigate the impact of FIN performance on ESG and to test the moderator effect of total quality management (TQM). The findings reveal a stimulus effect between free cash flow (FCF) and ESG scores. While the interaction between TQM and FCF has a negative effect on ESG, the interaction between TQM and Tobin’s Q reveals a positive relationship with ESG. This study sheds further insights for both research and practice towards the operationalization of sustainability management.
Understanding People−Forest Relationships: A Key Requirement for Appropriate Forest Governance in South Sumatra, Indonesia
Authors: Harbi Jun , Cao Yukun , Milantara Noril , Gamin  , Mustafa Ade Brian , Roberts Nathan James
Published: June 2021

Indonesian forestry challenges in attributional land-use conflicts of overlapping villages and state forests have affected community livelihoods and forest sustainability for decades. This empirical research uncovers the socio-economic attributes of villages in order to gain a better understanding of people−forest relationships in order to guide improved forest management and governance for long-term sustainability. Data were obtained from 69 villages located in the forest management unit of Lakitan Bukit Cogong in South Sumatra Province. Spatially-explicit quantitative measurements and qualitative approaches were employed to explore the interrelationships between human footprint, village development, and conflict resolution strategies over two decades. The results confirmed that utilization of forest areas as part of the village territory (such as for building settlements, public/social infrastructure facilities, plantations and agricultural fields) has long been administered without permits, destabilizing forest functions. Moreover, aspects such as human population size, proximity of villages to the national road and sub-district capital, and the transmigration settlement units have an impact on the Human Footprint Index and Village Development Index. Furthermore, our analyses identified three distinctive forms of conflict based on village type: (1) villages which are administratively included in the forest area; (2) villages for transmigration settlement; and (3) villages adjacent to company management concession areas. In these villages, the clarity of land/forest boundaries and property rights are predominant conflict issues. Several recommendations are proposed to support sustainable forest development; namely, controlling human activities in the forest, improving village management governance, and resolving associated conflicts.
New Approach for Managing Sustainability in Projects
Authors: de la Cruz López María Pilar , Cartelle Barros Juan José , del Caño Gochi Alfredo , Lara Coira Manuel
Published: June 2021

Despite the work done to date, project sustainability management (PSM) is still at an embryonic stage. The existing literature considers sustainability as a transversal aspect to be incorporated into the traditional management functions (scope, time, cost, quality, etc.). This article proposes sustainability as a key aspect of project management, with three essential components: principles, processes and competences. Regarding principles, the principle of sustainable development should be added to those generally suggested. As for processes, seven are proposed for (1) planning sustainability management; (2) establishing a sustainability breakdown structure; (3) defining the sustainability objective; (4) identifying project alternatives to achieve it; (5) planning and (6) implementing the sustainability strategy; and (7) monitoring and control. The main interrelationships between these processes and those of project initiation, planning, implementation, control, and closure are also analysed. In addition, the competences that the project manager should have in this field are identified, as well as the main criteria to take into account in order to adapt PSM processes to the characteristics of the project and the organisation. Finally, the results of a Delphi analysis carried out to validate these proposals are presented.
A Note on Solitons with Generalized Geodesic Vector Field
Authors: Blaga Adara M. , Ishan Amira , Deshmukh Sharief
Published: June 2021

We consider a general notion of an almost Ricci soliton and establish some curvature properties for the case in which the potential vector field of the soliton is a generalized geodesic or a 2-Killing vector field. In this vein, we characterize trivial generalized Ricci solitons.
Android Malware Detection Using TCN with Bytecode Image
Authors: Zhang Wenhui , Luktarhan Nurbol , Ding Chao , Lu Bei
Published: June 2021

With the rapid increase in the number of Android malware, the image-based analysis method has become an effective way to defend against symmetric encryption and confusing malware. At present, the existing Android malware bytecode image detection method, based on a convolution neural network (CNN), relies on a single DEX file feature and requires a large amount of computation. To solve these problems, we combine the visual features of the XML file with the data section of the DEX file for the first time, and propose a new Android malware detection model, based on a temporal convolution network (TCN). First, four gray-scale image datasets with four different combinations of texture features are created by combining XML files and DEX files. Then the image size is unified and input to the designed neural network with three different convolution methods for experimental validation. The experimental results show that adding XML files is beneficial for Android malware detection. The detection accuracy of the TCN model is 95.44%, precision is 95.45%, recall rate is 95.45%, and F1-Score is 95.44%. Compared with other methods based on the traditional CNN model or lightweight MobileNetV2 model, the method proposed in this paper, based on the TCN model, can effectively utilize bytecode image sequence features, improve the accuracy of detecting Android malware and reduce its computation.
A Class of Novel Mann-Type Subgradient Extragradient Algorithms for Solving Quasimonotone Variational Inequalities
Authors: Wairojjana Nopparat , Argyros Ioannis K. , Shutaywi Meshal , Deebani Wejdan , Argyros Christopher I.
Published: June 2021

Symmetries play an important role in the dynamics of physical systems. As an example, quantum physics and microworld are the basis of symmetry principles. These problems are reduced to solving inequalities in general. That is why in this article, we study the numerical approximation of solutions to variational inequality problems involving quasimonotone operators in an infinite-dimensional real Hilbert space. We prove that the iterative sequences generated by the proposed iterative schemes for solving variational inequalities with quasimonotone mapping converge strongly to some solution. The main advantage of the proposed iterative schemes is that they use a monotone and non-monotone step size rule based on operator knowledge rather than a Lipschitz constant or some line search method. We present a number of numerical experiments for the proposed algorithms.
Effect of the Location of Fault Fracture Zones on the Stability of Symmetrical Submarine Tunnels
Authors: Fang Wei , Wang Gang , Wang Chang
Published: June 2021

In this paper, we aim to reveal the influence of fault fracture zones on the stability of submarine tunnels and the surrounding rock under different water and drainage measures. Firstly, four typical working conditions of submarine tunnels intersecting with fault fracture zones were selected. On the basis of the typical cross section of the intersections of submarine tunnels and faults, they were divided into four working conditions. Then, the displacement and plastic zones of the surrounding rock of the tunnel were studied, and the stability of the rock surrounding the submarine tunnel was discussed. This research structure indicates that the bending moment and axial force of the lining structure of the submarine tunnel increase with increasing sealing degree, but the safety factor exhibits a downward trend. When the fault fracture zone goes through the section above the tunnel axis, the bending moment and axial force at the lining vault are greater than the other working conditions, and the displacement of the surrounding rock at the vault and spandrel is prominent. When the fault fracture zone completely passes through the tunnel, the safety factor of the lining structure is at its lowest, and the displacement of the surrounding rock at the arch waist develops laterally. When the fault fracture zone passes through the part below the tunnel axis, the arch foot displacement converges significantly, and the surrounding rock displacement exhibits a downward inclination. In addition, the plastic zone is mainly developed in the arch and the shoulder. These research results provide a reliable reference for tunnel design and excavation support.