bluuebunny/crossref_metadata_2025 huggingface dataset:
Biosorption of Cr(VI) Using Cellulose Nanocrystals Isolated from the Waterless Pulping of Waste Cotton Cloths with Supercritical CO2: Isothermal, Kinetics, and Thermodynamics Studies
Authors: Mohamed Siti Hajar , Hossain Md. Sohrab , Kassim Mohamad Haafiz Mohamad , Balakrishnan Venugopal , Habila Mohamed A. , Zulkharnain Azham , Zulkifli Muzafar , Yahaya Ahmad Naim Ahmad
Published: February 2022

In the present study, supercritical carbon dioxide (scCO2) was utilized as a waterless pulping for the isolation of cellulose nanocrystals (CNCs) from waste cotton cloths (WCCs). The isolation of CNCs from the scCO2-treated WCCs’ fiber was carried out using sulphuric acid hydrolysis. The morphological and physicochemical properties analyses showed that the CNCs isolated from the WCCs had a rod-like structure, porous surface, were crystalline, and had a length of 100.03 ± 1.15 nm and a width of 7.92 ± 0.53 nm. Moreover, CNCs isolated from WCCs had a large specific surface area and a negative surface area with uniform nano-size particles. The CNCs isolated from WCCs were utilized as an adsorbent for the hexavalent chromium [Cr(VI)] removal from aqueous solution with varying parameters, such as treatment time, adsorbent doses, pH, and temperature. It was found that the CNCs isolated from the WCCs were a bio-sorbent for the Cr(VI) removal. The maximum Cr(VI) removal was determined to be 96.97% at pH 2, 1.5 g/L of adsorbent doses, the temperature of 60 °C, and the treatment time of 30 min. The adsorption behavior of CNCs for Cr(VI) removal was determined using isothermal, kinetics, and thermodynamics properties analyses. The findings of the present study revealed that CNCs isolated from the WCCs could be utilized as a bio-sorbent for Cr(VI) removal.
Sorption of Fluoride and Bacterial Disinfection Property of Biosynthesized Nanofibrous Cellulose Decorated Ag–MgO–Nanohydroxyapatite Composite for Household Water Treatment
Authors: Ayinde Wasiu B. , Gitari Mugera W. , Smith James A. , Samie Amidou
Published: February 2022

An innovative and sustainable approach to integrating modified Ag–MgO–nanohydroxyapatite on a nanofibrous cellulose template (CNF-AgMgOnHaP) as a multifunctional adsorbent via a hydrothermal bioreduction route using Citrus paradisi peel extract was developed and examined. The surface morphology and mineralogical properties of CNF-AgMgOnHaP by UV–vis spectroscopy, SEM-EDS, XRD, FTIR, TEM, and BET techniques are reported. Batch fluoride sorption studies and its disinfection potential against common bacteria in surface water were evaluated. The results showed the successful synthesis of a modified multistructural CNF-AgMgOnHaP composite with an improved BET surface area of 160.17 m2/g. The sorption of fluoride by the adsorbent was found to strongly depend on the different sorption conditions with a maximum F− sorption capacity of 8.71 mg/g at 303 K, and pH of 5 with 0.25 g dosage at 10 min contact time (25 ± 3 °C). Equilibrium fluoride sorption onto the CNF-AgMgOnHaP was best described by the Freundlich isotherm model across all the operating temperatures. The overall kinetic results showed that the adsorption mechanisms not only depend on using the pseudo-second-order process but are also governed by the mass transfer of the adsorbate molecules from the external surface onto the pores of the adsorbent. The thermodynamic parameters revealed that the adsorption process of F− onto CNF-AgMgOnHaP was endothermic and spontaneous at the sorbent/solution interface. The synthesized composite also provides some antibacterial activity against common infectious microbes from contaminated drinking water. The overall results suggested that the CNF-AgMgOnHaP nanocomposite possesses the potential for the simultaneous decontamination of pollutants and microbes in drinking water.
Phthalocyanines and Porphyrins/Polyaniline Composites (PANI/CuPctBu and PANI/TPPH2) as Sensing Materials for Ammonia Detection
Authors: Pauly Alain , Saad Ali Sahal , Varenne Christelle , Brunet Jérôme , Llobet Eduard , Ndiaye Amadou L.
Published: February 2022

We combined a conducting polymer, polyaniline (PANI), with an organic semiconducting macrocyclic (MCs) material. The macrocycles are the phthalocyanines and porphyrins used to tune the electrical properties of the PANI, which benefits from their ability to enhance sensor response. For this, we proceeded by a simple ultrasonically assisted reaction involving the two components, i.e., the PANI matrix and the MCs, to achieve the synthesis of the composite nanostructure PANI/MCs. The composite nanostructure has been characterized and deposited on interdigitated electrodes (IDEs) to construct resistive sensor devices. The isolated nanostructured composites present good electrical properties dominated by PANI electronic conductivity, and the characterization reveals that both components are present in the nanostructure. The experimental results obtained under gas exposures show that the composite nanostructures can be used as a sensing material with enhanced sensing properties. The sensing performance under different conditions, such as ambient humidity, and the sensor’s operating temperature are also investigated. Sensing behavior in deficient humidity levels and their response at different temperatures revealed unusual behaviors that help to understand the sensing mechanism. Gas sensors based on PANI/MCs demonstrate significant stability over time, but this stability is highly reduced after experiments in lower humidity conditions and at high temperatures.
Sugar as an Analogue for Snow in Penetration Testing: A Preliminary Comparison
Authors: McCallum Adrian B. , Kent Damon , Lee Denham
Published: February 2022

Snow is a sintered matrix of ice, the strength of which is determined by the number and size of bonds between ice grains. However, because snow is a thermally unstable material, it is problematic to transport and store samples for accurate ex situ testing of mechanical behaviour. As an analogue for snow, we examined the sintering behaviour of different types of granular sugar at different humidities over different temporal periods and then assessed the extent of sintering and resistance to penetration of these samples. Like snow, increased sintering occurs in sugar over time. Sintering extent and rate are affected by the humidity environment and penetration resistance generally increases after increased sintering time. This preliminary examination suggests that in the absence of snow testing facilities, humidity-controlled sintered sugar may serve as a valuable proxy for examining the temporal variation of penetration resistance in snow.
Reproducibility of Aerobic Granules in Treating Low-Strength and Low-C/N-Ratio Wastewater and Associated Microbial Community Structure
Authors: Zhang Hongxing , Liu Yong-Qiang , Mao Shichao , Steinberg Christain E. W. , Duan Wenyan , Chen Fangyuan
Published: February 2022

Long-term stability of the aerobic granular sludge system is essentially based on the microbial community structure of the biomass. In this study, the physicochemical and microbial characteristics of sludge and wastewater treatment performance were investigated regarding formation, maturation, and long-term maintenance of granules in two parallel sequencing batch reactors (SBR), R1 and R2, under identical conditions. The aim was to explore the linkage between microbial community structure of the aerobic granules, their long-term stability, as well as the reproducibility of granulation and long-term stability. The two reactors were operated with a COD concentration of 400 mg/L and a chemical oxygen demand to nitrogen (COD/N) ratio of 4:1 under anoxic–oxic conditions. It was found that although SVI30, sludge size, and distributions in R1 and R2 were different, aerobic granules were formed, and they maintained long-term stability in both reactors for 320 days, implying that a certain level of randomness of granulation does not affect the long-term stability and performance for COD and N removal. In addition, a significant reduction in the richness and diversity of microbial production was observed after the sludge was converted from inoculum or flocs to granules, but this did not negatively affect the performance of wastewater treatment. Among the predominant microbial species in aerobic granules, Zoogloea was identified as the most important bacteria present during the whole operation with the highest abundance, while Thauera was the important genus in the formation and maturation of the aerobic granules, but it cannot be maintained long-term due to the low food-to-microorganisms ratio (F/M) in the system. In addition, some species from Ohtaekwangia, Chryseobacterium, Taibaiella, and Tahibacter were found to proliferate strongly during long-term maintenance of aerobic granules. They may play an important role in the long-term stability of aerobic granules. These results demonstrate the reproducibility of granulation, the small influence of granulation on long-term stability, and the robustness of aerobic granulation for the removal of COD and N. Overall, our study contributes significantly to the understanding of microbial community structure for the long-term stability of aerobic granular sludge in the treatment of low-COD and low-COD/N-ratio wastewater in practice.
Macro-Batch and Continuously Operated Microfluidic Emulsification—Differences, Similarities and Optimization
Authors: Grgić Filip , Benković Maja , Valinger Davor , Jurina Tamara , Kljusurić Jasenka Gajdoš , Tušek Ana Jurinjak
Published: February 2022

In this work, the emulsification of oil-in-water two-phase systems with three emulsifiers (PEG1500, 6000 and 20000) was studied in a batch macro system and in a continuously operated microfluidic system. The effect of emulsifier concentration, oil concentration and mixing rate on zeta potential and average Feret diameter was analyzed for the macro-batch system, while the effect of emulsifier concentration, oil concentration and total flow rate on zeta potential and average Feret diameter was analyzed for the microfluidic system. The emulsions prepared in batch system were more stable, had smaller droplet diameter but higher values of polydispersity index (PDI) compared to those prepared by continuous method. In both cases, batch and continuous, the use of PEG with higher molecular weight resulted in emulsions with lower zeta potential values. In batch emulsification, all three optimization parameters (emulsifier concentration, oil concentration and mixing rate) had a significant influence on the average Feret diameter and zeta potential (depending on the PEG, used for emulsification), while the emulsifier concentration had the most significant influence on the zeta potential and average Feret diameter of emulsions prepared in the continuous microsystem process.
Special Issue “The Use of Recycled Materials to Promote Pavement Sustainability Performance”
Authors: Neves José , Freire Ana Cristina
Published: February 2022

Recycling road pavement materials allows for a more sustainable use of raw materials and contributes to creating a circular economy [...]
Evaluation of Forward Models for GNSS Radio Occultation Data Processing and Assimilation
Authors: Deng Nan , Bai Weihua , Sun Yueqiang , Du Qifei , Xia Junming , Wang Xianyi , Liu Congliang , Cai Yuerong , Meng Xiangguang , Yin Cong , Huang Feixiong , Hu Peng , Tan Guangyuan , Liu Xiaoxu
Published: February 2022

In radio occultation (RO) data processing and data assimilation, the forward model (FM) is used to calculate bending angle (BA) from refractivity (N). The accuracy and precision of forward modeled BA are affected by refractivity profiles and FM methods, including Abel integral algorithms (direct, exp, exp_T, linear) and methods of interpolating refractivity during integral (log-cubic spline and log-linear). Experiment 1 compares these forward model methods by comparing the difference and relative difference (RD) of the experimental value (forward modeled ECMWF analysis) and the true value (BA of FY3D RO data). Results suggested that the exp with log-cubic spline (log-cubic) interpolation is the most accurate FM because it has better integral accuracy (less than 2%) to inputs, especially when the input is lower than an order of magnitude of 1 × 10−2 (that is, above 60 km). By contrast, the direct induced a 10% error, and the improvement of exp T to exp is limited. Experiment 2 simulated the exact errors of an FM (exp) based on inputs on different vertical resolutions. The inputs are refractivity profiles on model levels of three widely used analyses, including ECMWF 4Dvar analysis, final operational global analysis data (FNL), and ERA5. Results demonstrated that based on exp and log-cubic interpolation, BA on model level of ECMWF 4Dvar has the highest accuracy, whose RD is 0.5% between 0–35 km, 4% between 35–58 km, and 1.8% between 58–80 km. By contrast, the other two analyses have low accuracy. This paper paves the way to better understanding the FM, and simulation errors on model levels of three analyses can be a helpful FM error reference.
Development of a Landscape-Based Multi-Metric Index to Assess Wetland Health of the Poyang Lake
Authors: Liu Dandan , Liu Lingling , You Qinghui , Hu Qiwu , Jian Minfei , Liu Guihua , Cong Mingyang , Yao Bo , Xia Ying , Zhong Jie , Yang Wenjing
Published: February 2022

Human-induced changes in landscapes are one of the major drivers of wetland loss and degradation. The Poyang Lake wetland in China has been experiencing severe degradation due to human disturbance and landscape modification. Indicators to assess the condition of this wetland are thus needed urgently. Here, a landscape-based multi-metric index (LMI) is developed to evaluate the condition of the Poyang Lake wetland. Twenty-three candidate metrics that have been applied to wetland health assessment in published studies were tested. Metrics that show strong discriminative power to identify reference and impaired sites, having significant correlations with either benthic macroinvertebrate- or vegetation-based indices of biotic integrity (B-IBI or V-IBI), were chosen to form the LMI index. Five of these metrics (largest patch index, modified normalized differential built-up index, Shannon’s diversity index, connectance index, and cultivated land stress index) were selected as our LMI metrics. A 2 km buffer zone around sample sites had the strongest explanatory power of any spatial scale on IBIs, suggesting that protecting landscapes at local scales is essential for wetland conservation. The LMI scores ranged between 1.05 and 5.00, with a mean of 3.25, suggesting that the condition of the Poyang Lake wetland is currently in the “fair” category. The areas along lakeshores were mainly in poor or very poor conditions, while the less accessible inner areas were in better conditions. This study demonstrates significant links between landscape characteristics and wetland biotic integrity, which validates the utility of satellite imagery-derived data in assessing wetland health. The LMI method developed in this study can be used by land managers to quickly assess broad regions of the Poyang Lake wetland.
Estimating Wildlife Density as a Function of Environmental Heterogeneity Using Unmarked Data
Authors: Connor Thomas , Division Wildlife , Tripp Emilio , Bean William T. , Saxon B. J. , Camarena Jessica , Donahue Asa , Sarna-Wojcicki Daniel , Macaulay Luke , Tripp William , Brashares Justin
Published: February 2022

Recent developments to spatial-capture recapture models have allowed their use on species whose members are not uniquely identifiable from photographs by including individual identity as a latent, unobserved variable in the model. These ‘unmarked’ spatial capture recapture (uSCR) models have also been extended to presence-absence data and modified to allow categorical environmental covariates on density, but a uSCR model, which allows fitting continuous environmental covariates to density, has yet to be formulated. In this paper, we fill this gap and present an extension to the uSCR modeling framework by modeling animal density on a discrete state space as a function of continuous environmental covariates and investigate a form of Bayesian variable selection to improve inference. We used an elk population in their winter range within Karuk Indigenous Territory in Northern California as a case study and found a positive credible effect of increasing forb/grass cover on elk density and a negative credible effect of increasing tree cover on elk density. We posit that our extensions to uSCR modeling increase its utility in a wide range of ecological and management applications in which spatial counts of wildlife can be derived and environmental heterogeneity acts as a control on animal density.
A Detection Method for Collapsed Buildings Combining Post-Earthquake High-Resolution Optical and Synthetic Aperture Radar Images
Authors: Wang Chao , Zhang Yan , Xie Tao , Guo Lin , Chen Shishi , Li Junyong , Shi Fan
Published: February 2022

The detection of collapsed buildings based on post-earthquake remote sensing images is conducive to eliminating the dependence on pre-earthquake data, which is of great significance to carry out emergency response in time. The difficulties in obtaining or lack of elevation information, as strong evidence to determine whether buildings collapse or not, is the main challenge in the practical application of this method. On the one hand, the introduction of double bounce features in synthetic aperture radar (SAR) images are helpful to judge whether buildings collapse or not. On the other hand, because SAR images are limited by imaging mechanisms, it is necessary to introduce spatial details in optical images as supplements in the detection of collapsed buildings. Therefore, a detection method for collapsed buildings combining post-earthquake high-resolution optical and SAR images was proposed by mining complementary information between traditional visual features and double bounce features from multi-source data. In this method, a strategy of optical and SAR object set extraction based on an inscribed center (OpticalandSAR-ObjectsExtraction) was first put forward to extract a unified optical-SAR object set. Based on this, a quantitative representation of collapse semantic knowledge in double bounce (DoubleBounceCollapseSemantic) was designed to bridge a semantic gap between double bounce and collapse features of buildings. Ultimately, the final detection results were obtained based on the improved active learning support vector machines (SVMs). The multi-group experimental results of post-earthquake multi-source images show that the overall accuracy (OA) and the detection accuracy for collapsed buildings (Pcb) of the proposed method can reach more than 82.39% and 75.47%. Therefore, the proposed method is significantly superior to many advanced methods for comparison.
Similar Sexual Behaviour yet Different Outcomes: Comparing Trans and Gender Diverse and Cis PrEP Users in Germany Based on the Outcomes of the PrApp Study
Authors: Appenroth Max Nicolai , Marcus Ulrich , Albrecht Stefan , Jansen Klaus , Gunsenheimer-Bartmeyer Barbara , Bremer Viviane , Koppe Uwe
Published: February 2022

Little knowledge about pre-exposure prophylaxis (PrEP) use in trans and gender diverse (TGD) communities in Germany exists. The PrApp Study collected data on PrEP use and sexual behaviour among PrEP users in Germany. Descriptive methods and logistic regression were used to describe PrEP use among TGD and cis persons. A total of 4350 PrEP users in Germany were included, with 65 (1.5%) identified as TGD. Compared to cis participants, TGD participants were younger (median age 29 vs. 37 years) and more likely to have a lower income (adjusted odds ratio (aOR) = 4.4; 95% confidence interval (CI) = 2.4–8.2) and be born outside Germany (aOR = 2.5; 95% CI = 1.3–4.5). On-demand PrEP use was higher in TGD participants (aOR = 1.9; 95% CI = 1.0–3.5) and numerically more TGD obtained PrEP from informal sources (aOR = 1.8; 95% CI = 0.9–3.5). Testing behaviour, condom use, and number of sexual partners were comparable between both groups. Socioeconomic disparities may constitute structural barriers for TGD people to access PrEP, leading to more informal and on-demand use. PrEP providers need to reduce access barriers for TGD PrEP users and provide information on safe PrEP use for this population.
Transition towards a Sustainable Mobility in a Suburbanising Urban Area: The Case of Barcelona
Authors: Gil-Alonso Fernando , López-Villanueva Cristina , Thiers-Quintana Jenniffer
Published: February 2022

This article aims to address the apparent contradiction between the urban demographic and migratory trends and the transition towards a more sustainable mobility that local and metropolitan governments seek. To that end, it uses the case of Barcelona, and its metropolitan area during the first decades of the 21st century, characterized by suburbanisation and gentrification. Employing demographic, mobility and transport, and air quality statistics, we intend to analyse: (a) the spatial demographic trends in the metropolitan area of Barcelona (AMB), particularly regarding the core and periphery population growth or decline; (b) trends in daily mobility and how the public and private transport mix has changed; and (c) pollution data changes confirming the success or failure of the private vehicle reduction policy. Findings confirm our initial hypothesis: the slow but steady transition towards sustainable forms of mobility in the core city and the dense contiguous municipalities is counterbalanced by what occurs in the peripheral suburbs. There, the use of private vehicles is still preeminent and growing. Nevertheless, the air quality has improved in the most central municipalities of the AMB (for which data are available), even if not all parameters have seen a similar pollution reduction.
Predicting Demand for Shared E-Scooter Using Community Structure and Deep Learning Method
Authors: Kim Sujae , Choo Sangho , Lee Gyeongjae , Kim Sanghun
Published: February 2022

The shared e-scooter is a popular and user-convenient mode of transportation, owing to the free-floating manner of its service. The free-floating service has the advantage of offering pick-up and drop-off anywhere, but has the disadvantage of being unavailable at the desired time and place because it is spread across the service area. To improve the level of service, relocation strategies for shared e-scooters are needed, and it is important to predict the demand for their use within a given area. Therefore, this study aimed to develop a demand prediction model for the use of shared e-scooters. The temporal scope was selected as October 2020, when the demand for e-scooter use was the highest in 2020, and the spatial scope was selected as Seocho and Gangnam, where shared e-scooter services were first introduced and most frequently used in Seoul, Korea. The spatial unit for the analysis was set as a 200 m square grid, and the hourly demand for each grid was aggregated based on e-scooter trip data. Prior to predicting the demand, the spatial area was clustered into five communities using the community structure method. The demand prediction model was developed based on long short-term memory (LSTM) and the prediction results according to the activation function were compared. As a result, the model employing the exponential linear unit (ELU) and the hyperbolic tangent (tanh) as the activation function produced good predictions regarding peak time demands and off-peak demands, respectively. This study presents a methodology for the efficient analysis of the wider spatial area of e-scooters.
The Wine Effects in Tourism Studies: Mapping the Research Referents
Authors: Campos-Andaur Paulina , Padilla-Lobo Karen , Contreras-Barraza Nicolás , Salazar-Sepúlveda Guido , Vega-Muñoz Alejandro
Published: February 2022

This research provides an empirical overview of articles and authors referring to research on wine tourism, analyzed from 2000 to 2021, and what they contribute to deepening the Sustainable Development Goals (SDGs) 8. The articles were examined through a bibliometric approach based on data from 199 records stored in the Web of Science (JCR), applying traditional bibliometric laws, and using VOSviewer for data processing and metadata. The results highlight an exponential increase in scientific production without interruptions between 2005 and 2020, with a concentration in only 35 highly cited authors, where the hegemony is held by Australia, among the co-authorship networks of worldwide relevance. The main topics observed in the literature are local development through wine tourism, sustainability and nature conservation, and strategies for sustainable development. Finally, there are six articles with great worldwide influence in wine tourism studies that maintain in their entirety the contribution made by researchers affiliated with Australian universities.
Challenges to the Circular Economy: Recovering Wastes from Simple versus Complex Products
Authors: Jacobs Carly , Soulliere Katie , Sawyer-Beaulieu Susan , Sabzwari Abir , Tam Edwin
Published: February 2022

The circular economy re-interprets the recovery of materials by promoting designing out waste from products, retaining materials for reuse, and emphasizing key elements universally accepted for sustainability. The current efforts to target, isolate, and reduce single-use items, particularly plastics, have only recently begun in earnest. Unfortunately, the recovery and recycling of materials have been disrupted by global market uncertainty, and recently, the COVID-19 pandemic. While the pandemic and its impacts complicate materials recovery, the core of the circular economy still depends on efficiently capturing and returning spent materials for production. Arguably, our perception and common understanding of the recovery process is influenced significantly by the recycling of simple consumer products, such as plastic bags and beverage bottles. However, there are greater difficulties when managing multiple materials from significantly more complex consumer products, for example, from end-of-life vehicles. This paper presents an overview of how waste recovery-related issues vary between simple versus complex consumer products. Using food packaging, tires, cell phones, furniture, and end-of-life vehicles as examples, this paper provides a commentary on the challenges facing complex product recovery compared to simple consumer products in the Canadian context in order to establish how this classification concept can be beneficial for describing a given product and its materials recovery prospects. A categorization framework is developed and applied to these case study products to provide a relative comparison of product complexity.
Differential Evolution Algorithm for Optimizing the Energy Usage of Vertical Transportation in an Elevator (VTE), Taking into Consideration Rush Hour Management and COVID-19 Prevention
Authors: Khonjun Surajet , Pitakaso Rapeepan , Sethanan Kanchana , Nanthasamroeng Natthapong , Pranet Kiatisak , Kaewta Chutchai , Sangkaphet Ponglert
Published: February 2022

This research aimed to develop an effective algorithm to minimize the energy use of vertical transportation in elevators while controlling the number of passengers in the elevator waiting area and the number of passengers in the elevator during rush hour, thus maintaining social distancing to limit the spread of COVID-19. A mobile application and Internet of Things (IoT) devices were used to electronically communicate between the elevator’s control system and the passengers. IoT devices were used to reduce the number of passengers waiting for an elevator and passengers’ waiting time, while the energy consumption of the lift was reduced by using passenger scheduling and elevator stopping strategies. Three mathematical models were formulated to represent the different strategies used to cause the elevator to stop. These strategies were normal (allowing the elevator to stop at every floor), odd–even (some elevators are allowed to stop at odd floors and others are allowed to stop at even floors of the building), and high–low (some elevators are allowed to stop at high floors and others are allowed to stop at low floors of the building). Lingo v.11 and the differential evolution algorithm (DE) were used to address the optimal scheduling of the passengers and the elevators. The computational results show that the odd–even strategy had a 13.91–23.71% lower energy consumption compared with the high–low and normal strategies. Furthermore, the use of DE consumed 6.67–7.99% less energy than the use of Lingo.v11. Finally, the combination of DE and the designed application reduced the number of waiting passengers, the average passenger waiting time, and the total energy consumption by 74.55%, 75.12%, and 45.01%, respectively.
Sustainability as an Emerging Paradigm in Universities
Authors: Gaitán-Angulo Mercedes , Gómez-Caicedo Melva Inés , Torres-Samuel Maritza , Correa-Guimaraes Adriana , Navas-Gracia Luis Manuel , Vásquez-Stanescu Carmen Luisa , Ramírez-Pisco Rodrigo , Luna-Cardozo Marisabel
Published: February 2022

This article aims to review the perspective of sustainability adoption in universities through two dimensions: firstly, from the educational and research process, and second, from their global positioning in terms of the performance of their university campus. For this purpose, a bibliometric analysis was carried out, referring to publications dating from 2006 to 2020, using the terms “Sustainability, green universities and curricular sustainability” as search keywords. In addition, an analysis of eight global university rankings was made, gathering information from their official websites on their evaluation fields, indicators, and volume of Ibero–American universities cataloged. The result is that, since 2007, the number of publications on this topic has increased, showing that the participation of Latin American in publications is very low (3.69%). Furthermore, only 12% of Latin American universities are included in world rankings. Sustainability has hardly been integrated into university academic programs; likewise, it is observed that the traditional world ranking of universities mainly take into account factors related to teaching and research, without considering criteria related to sustainability. Moreover, it is essential to develop policies that encourage universities to develop sustainability strategies in their academic and institutional processes in general, as well as in the global university evaluation systems, in order to value sustainability adequately in both in academics, research and institutional performance.
Impact of Pandemic COVID-19 on Air Quality at a Combustion Plant and Adjacent Areas
Authors: Cichowicz Robert , Wiśniewski Jacek
Published: February 2022

Following the emergence of the infectious disease COVID-19, caused by the coronavirus SARS-Cov-2, the WHO (World Health Organization) declared a pandemic in March 2020. The pandemic has affected people’s health, social behaviour, and the economy around the world. It has also had an indirect impact on the environment, including atmospheric air quality, related to changes in the levels of pollutant emissions and the amounts of greenhouse gases released into the atmosphere. The observed changes have, in part, been a consequence of restrictions on human movement, which has translated into an increase in water consumption, and consequently into an increase in the volume of wastewater. As a result, a new type of incoming load has appeared in sewage treatment plants. Municipal sewage sludge (MSS) is a waste product from the wastewater treatment process, containing substances that are hazardous to both the environment and humans (bacteria, pathogens, viruses). To dispose of these contaminants, MSS is thermally processed in specially designed installations. Thermal recycling technology is based on a fluidized bed, in which MSS is rapidly transformed at a temperature of at least 750 °C. Organic compounds are oxidized, gasified, and combusted. The exhaust fumes are emitted into the atmosphere. They also carry a load of pollutants, which can affect the air quality both on site and in the surroundings of the treatment plant. This paper presents measurements of air pollutant emissions and pollutant concentrations provided by the Group Sewage Treatment Plant in Łódź Itd. Łódź is a city located in Poland, in central Eastern Europe. The research covers the area of the wastewater treatment plant and its immediate surroundings within a radius of about 1.5 km. The data show the influence of the pandemic restrictions on the concentrations of gaseous substances, bacteria, fungi, and particulate matter on the state of air quality. Increased emissions of NOx (by 86%), PM10 (by 50%), HCl (by 37%), and SO2 (by 16%) were observed compared to the pre-COVID-19 period.
The Stimulation of Superoxide Dismutase Enzyme Activity and Its Relation with the Pyrenophora teres f. teres Infection in Different Barley Genotypes
Authors: Kunos Viola , Cséplő Mónika , Seress Diána , Eser Adnan , Kende Zoltán , Uhrin Andrea , Bányai Judit , Bakonyi József , Pál Magda , Mészáros Klára
Published: February 2022

Changes in superoxide dismutase (SOD) enzyme activity were examined in infected barley seedlings of five cultivars with the goal to study the role of SOD in the defense mechanism induced by Pyrenophora teres f. teres (PTT) infection. Our results showed that although there were differences in the responses of the cultivars, all three PTT isolates (H-618, H-774, H-949) had significantly increased SOD activity in all examined barley varieties at the early stages of the infection. The lowest SOD activity was observed in the case of the most resistant cultivar. Our results did not show a clear connection between seedling resistance of genotypes and SOD enzyme activity; however, we were able to find strong significant correlations between the PTT infection scores on the Tekauz scale and the SOD activity. The measurement of the SOD activity could offer a novel perspective to detect the early stress responses induced by PTT. Our results suggest that the resistance of varieties cannot be estimated based on SOD enzyme activity alone, because many antioxidant enzymes play a role in fine-tuning the defense response, but SOD is an important member of this system.
Digitally Sustainable Information Systems in Axiomatic Design
Authors: Pecoraro Fabrizio , Pourabbas Elaheh , Rolli Fernando , Parretti Chiara
Published: February 2022

Nowadays, information systems are evolving towards increasingly interconnected, smart, and self-adaptive models. This transformation has led to the representation of the systems themselves in terms of natural ecosystems. Similar to the natural environment, the virtual world can be threatened by specific forms of pollution, such as illegitimate access to the system, unwanted changes to data, and loss of information, which affect the only resource it possesses, i.e., data. In order to provide proactive protection of data integrity and confidentiality, in this paper we consider the well-known principles of privacy by design and privacy by default in the design phase of system development. To this end, we propose an approach based on axiomatic design, which allows us to implement these two principles through an appropriate reinterpretation of the information axiom, in terms of privacy impact assessment. We illustrate our approach by a case study, which implements the process of managing patients in home care. However, the proposed method can be applied to processing systems that provide services. The main result achieved is to select the most digitally sustainable design solution, i.e., the one that best prevents the threats mentioned above.
A New Methodology for Reference Evapotranspiration Prediction and Uncertainty Analysis under Climate Change Conditions Based on Machine Learning, Multi Criteria Decision Making and Monte Carlo Methods
Authors: Kadkhodazadeh Mojtaba , Valikhan Anaraki Mahdi , Morshed-Bozorgdel Amirreza , Farzin Saeed
Published: February 2022

In the present study, a new methodology for reference evapotranspiration (ETo) prediction and uncertainty analysis under climate change and COVID-19 post-pandemic recovery scenarios for the period 2021–2050 at nine stations in the two basins of Lake Urmia and Sefidrood is presented. For this purpose, firstly ETo data were estimated using meteorological data and the FAO Penman–Monteith (FAO-56 PM) method. Then, ETo modeling by six machine learning techniques including multiple linear regression (MLR), multiple non-linear regression (MNLR), multivariate adaptive regression splines (MARS), model tree M5 (M5), random forest (RF) and least-squares boost (LSBoost) was carried out. The technique for order of preference by similarity to ideal solution (TOPSIS) method was used under seven scenarios to rank models with evaluation and time criteria in the next step. After proving the acceptable performance of the LSBoost model, the downscaling of temperature (T) and precipitation (P) by the delta change factor (CF) method under three models ACCESS-ESM1-5, CanESM5 and MRI-ESM2-0 (scenarios SSP245-cov-fossil (SCF), SSP245-cov-modgreen (SCM) and SSP245-cov-strgreen (SCS)) was performed. The results showed that the monthly changes in the average T increases at all stations for all scenarios. Also, the average monthly change ratio of P increases in most stations and scenarios. In the next step, ETo forecasting under climate change for periods (2021–2050) was performed using the best model. Prediction results showed that ETo increases in all scenarios and stations in a pessimistic and optimistic state. In addition, the Monte Carlo method (MCM) showed that the lowest uncertainty is related to the Mianeh station in the MRI-ESM2-0 model and SCS scenario.
On the Dynamics of Higgins–Selkov, Selkov and Brusellator Oscillators
Authors: Giné Jaume
Published: February 2022

A complete algebraic characterization of the first integrals of the Higgins–Selkov, Selkov and Brusellator oscillators is given here. The existence of symmetries sometimes forces the existence of such first integrals. The nonexistence of centers for such oscillators is also proved. In order to determine the Puiseux integrability of such systems, the multiple Puiseux solutions are also studied.
Assessing the Dual Innovation Capability of National Innovation System: Empirical Evidence from 65 Countries
Authors: Lu Han , Du Debin , Qin Xionghe
Published: February 2022

Open innovation has drawn significant attention over the years, and there is a growing body of literature that highlights the importance of considering this phenomenon at the national level. Less appreciated, however, is the radiative capability of national innovation systems (NIS) and the linking inbound and outbound processes. We provide a measurement of the dual innovation capability (DIC) of NISs based on process-oriented concepts by using a multi-indicator approach, which provides a more comprehensive picture of sectoral NISs compared to currently used metrics. To assess the DIC of NISs, a composite weighting method was used to obtain the score of our selection of 65 countries. The results show the spatio-temporal evolution of DIC from 2010 to 2018 and explore the interactions among sub-elements within the framework. The 65 countries were grouped into 4 categories based on the sub-dimension scores, and we provided 3 possible paths that can be chosen to improve DIC. The index provides a powerful tool to enrich research on innovation systems, guide national positioning, and optimize policies.
Analyzing the Stock Exchange Markets of EU Nations: A Case Study of Brexit Social Media Sentiment
Authors: Maqsood Haider , Maqsood Muazzam , Yasmin Sadaf , Mehmood Irfan , Moon Jihoon , Rho Seungmin
Published: February 2022

Stock exchange analysis is regarded as a stochastic and demanding real-world setting in which fluctuations in stock prices are influenced by a wide range of aspects and events. In recent years, there has been a great deal of interest in social media-based data analytics for analyzing stock exchange markets. This is due to the fact that the sentiments around major global events like Brexit or COVID-19 significantly affect business decisions and investor perceptions, as well as transactional trading statistics and index values. Hence, in this research, we examined a case study from the Brexit event to assess the influence that feelings on the subject have had on the stock markets of European Union (EU) nations. Brexit has implications for Britain and other countries under the umbrella of the European Union (EU). However, a common point of debate is the EU’s contribution preferences and benefit imbalance. For this reason, the Brexit event and its impact on stock markets for major contributors and countries with minimum donations need to be evaluated accurately. As a result, to achieve accurate analysis of the stock exchanges of different EU nations from two different viewpoints, i.e., the major contributors and countries contributing least, in response to the Brexit event, we suggest an optimal deep learning and machine learning model that incorporates social media sentiment analysis regarding Brexit to perform stock market prediction. More precisely, the machine learning-based models include support vector machines (SVM) and linear regression (LR), while convolutional neural networks (CNNs) are used as a deep learning model. In addition, this method incorporates around 1.82 million tweets regarding the major contributors and countries contributing least to the EU budget. The findings show that sentiment analysis of Brexit events using a deep learning model delivers better results in comparison with machine learning models, in terms of root mean square values (RMSE). The outcomes of stock exchange analysis for the least contributing nations in relation to the Brexit event can aid them in making stock market judgments that will eventually benefit their country and improve their poor economies. Likewise, the results of stock exchange analysis for major contributing nations can assist in lowering the possibility of loss in relation to investments, as well as helping them to make effective decisions.
Understanding Separation Mechanisms of Monoatomic Gases, Such as Kr and Xe, via DD3R Zeolite Membrane Using Molecular Dynamics
Authors: Bashmmakh Bandar J. , Wang Xiaoyu , Jameson Cynthia J. , Murad Sohail
Published: February 2022

Noble gas fission byproducts, such as Kr and Xe, are generated within nuclear power reactors are currently being discharged into the atmosphere. This practice has a major economic drawback because of the high value associated with some of these gases. The separations of these gases are economically prohibitive because of the high energy requirement associated with cryogenic distillation. Zeolites, nanoporous materials suitable for gas separation processes, have exhibited high selectivity for such separations. We have used nonequilibrium molecular dynamics (MD) to investigate the separation performance of DD3R framework zeolitic membrane. The effects of pressure, temperature, and pure vs. mixture gas feed conditions are studied in this work to understand and explain, at the molecular level, the mechanisms of these (Kr/Xe) separations. Our studies have shown that the DD3R membrane shows promise for high selectivity ratios of Kr over Xe. MD runs show agreement with experimental trends of the permeation of Kr/Xe pure and mixed gases using DD3R zeolite with high separation factor. Despite the absence of Xe complete permeation through the membrane because of MD timescale limitations, our results are sufficient to describe the mechanisms of these separations.
Transient Post-Natal Exposure to Xenoestrogens Induces Long-Term Alterations in Cardiac Calcium Signaling
Authors: Tabasso Cassandra , Frossard Marie-Pauline , Ducret Camille , Chehade Hassib , Mauduit Claire , Benahmed Mohamed , Simeoni Umberto , Siddeek Benazir
Published: February 2022

Today, non-communicable disorders are widespread worldwide. Among them, cardiovascular diseases represent the main cause of death. At the origin of these diseases, exposure to challenges during developmental windows of vulnerability (peri-conception, in utero, and early infancy periods) have been incriminated. Among the challenges that have been described, endocrine disruptors are of high concern because of their omnipresence in the environment. Worrisomely, since birth, children are exposed to a significant number of endocrine disruptors. However, the role of such early exposure on long-term cardiac health is poorly described. In this context, based on a model of rats exposed postnatally and transiently to an estrogenic compound prototype (estradiol benzoate, EB), we aimed to delineate the effects on the adult heart of such transient early exposure to endocrine disruptors and identify the underlying mechanisms involved in the potential pathogenesis. We found that this transient post-natal exposure to EB induced cardiac hypertrophy in adulthood, with increased cardiomyocyte size. The evaluation of cardiac calcium signaling, through immunoblot approaches, highlighted decreased expression of the sarcoplasmic reticulum calcium ATPase 2 (SERCA2) and decreased Nuclear Factor of Activated T Cells (NFAT3) phosphorylation as a potential underlying mechanism of cardiac hypertrophy. Furthermore, the treatment of cardiomyocytes with EB in vitro induced a decrease in SERCA2 protein levels. Overall, our study demonstrates that early transient exposure to EB induces permanent cardiac alterations. Together, our data highlight SERCA2 down-regulation as a potential mechanism involved in the cardiac pathogenesis induced by EB. These results suggest programming of adult heart dysfunctions such as arrhythmia and heart failures by early exposure to endocrine disruptors and could open new perspectives for treatment and prevention.
Comparative Analysis of Circulating Levels of SARS-CoV-2 Antibodies and Inflammatory Mediators in Healthcare Workers and COVID-19 Patients
Authors: de-Oliveira-Pinto Luzia Maria , Fiestas Solórzano Victor Edgar , de Lourdes Martins Maria , Fernandes-Santos Caroline , Damasco Paula Hesselberg , de Siqueira Marilda Agudo Mendonça Teixeira , Dias Helver Gonçalves , Pauvolid-Corrêa Alex , Damasco Paulo Vieira , de Azeredo Elzinandes Leal
Published: February 2022

Advances in knowledge of the pathophysiology of COVID-19 have been acquired; however, the host factors that could explain the mild and severe forms of the disease are not fully understood. Thus, we proposed to evaluate anti-SARS-CoV-2 antibodies and the inflammatory response of different groups of individuals, including healthcare workers (HCW), sick and dead COVID-19 patients and also recovered patients to contribute to this knowledge gap. Our objective is to relate the clinical evolution of these individuals with the level of detection and functionality of specific antibodies and with the production of inflammatory mediators. As main findings, IgA and IgG anti-SARS-CoV-2 were detected in asymptomatic HCW. IFN-γ and TNF-α levels were higher in symptomatic HCWs than patients with COVID-19 and those who died. Patients who died had higher levels of IL-6, IL-10, and CCL2/MCP-1. We found an imbalance between antiviral and pro-inflammatory mediators in the groups, in which IFN-γ and TNF-α seem to be more associated with protection and IL-6 and CCL2/MCP-1 with pathology. Our work is pioneering the Brazilian population and corroborates data from people from other countries.