bluuebunny/crossref_metadata_2025 huggingface dataset:
Differentiating Co-Delivery of Bisphosphonate and Simvastatin by Self-Healing Hyaluronan Hydrogel Formed by Orthogonal “Clicks”: An In-Vitro Assessment
Authors: Ossipov Dmitri A. , Lüchow Mads , Malkoch Michael
Published: June 2021

Due to its unique properties resembling living tissues, hydrogels are attractive carriers for the localized and targeted delivery of various drugs. Drug release kinetics from hydrogels are commonly controlled by network properties and the drug-network interactions. However, and simultaneously, the programmable delivery of multiple drugs with opposing properties (hydrophilicity, molecular weight, etc.) from hydrogels with determined network properties is still challenging. Herein, we describe the preparation of injectable self-healing hyaluronic acid (HA) hydrogels that release hydrophobic simvastatin and hydrophilic aminobisphosphonate (BP) drugs independently in response to acidic and thiol-containing microenvironments, respectively. We apply a prodrug strategy to BP by conjugating it to HA via a self-immolative disulfide linker that is stable in the blood plasma and is cleavable in the cytoplasm. Moreover, we utilize HA-linked BP ligands to reversibly bind Ca2+ ions and form coordination hydrogels. Hydrazone coupling of hydrophobic ligands to HA permits the encapsulation of simvastatin molecules in the resulting amphiphilic HA derivative and the subsequent acid-triggered release of the drug. The conjugation of BP and hydrophobic ligands to HA enables preparation of both bulk self-healing hydrogels and nanogels. Moreover, the developed hydrogel system is shown to be multi-responsive by applying orthogonally cleavable linkers. The presented hydrogel is a potential candidate for the combination treatment of osteoporosis and bone cancers as well as for bone tissue regeneration since it can deliver bone anabolic and anti-catabolic agents in response to bone diseases microenvironments.
The Effect of Titanium Tetra-Butoxide Catalyst on the Olefin Polymerization
Authors: Alsuhybani Mohammed S. , Alosime Eid M.
Published: June 2021

The purpose of this study was to assess the ability of titanium Ti(IV) alkyloxy compounds supported by organic polymer polyvinyl chloride (PVC) to polymerize ethylene by feeding triethylaluminium (TEA) as a cocatalyst. Additionally, the impacts of the molar ratio of [Al]/[Ti] on the catalytic activities in ethylene’s polymerization and of the comonomer through utilization of diverse quantities of comonomers on a similar or identical activity were studied. The optimal molar ratio of [Al]/[Ti] was 773:1, and the prepared catalyst had an initial activity of up to 2.3 kg PE/mol Ti. h. when the copolymer was incorporated with 64 mmol of 1-octene. The average molecular weight (Mw) of the copolymer produced with the catalysts was between 97 kg/mol and 326 kg/mol. A significant decrease in the Mw was observed, and PDI broadened with increasing concentration of 1-hexene because of the comonomer’s stronger chain transfer capacity. The quick deactivation of titanium butoxide Ti(OBu)4 on the polymers was found to be associated with increasing oxidation when supported by the catalyst. The presence of Ti(III) after reduction with the aluminum alkyls cleaves the carbon-chlorine bonds of the polymer, producing an inactive polymeric Ti(IV) complex. The results show that synergistic effects play an important role in enhancing the observed rate of reaction, as illustrated by evidence from scanning electron microscopy (SEM). The diffusion of cocatalysts within catalytic precursor particles may also explain the progression of cobweb structures in the polymer particles.
Study on the Development of Antiviral Spandex Fabric Coated with Poly(Hexamethylene Biguanide) Hydrochloride (PHMB)
Authors: Wang Wen-Yi , Yim Sui-Lung , Wong Chun-Ho , Kan Chi-Wai
Published: June 2021

The spread of COVID-19 has brought about huge losses around the world. This study aims to investigate the applicability of PHMB used for developing antiviral spandex clothing against coronavirus. PHMB was qualitatively determined on the surface of spandex fabrics by using BPB. The antiviral analysis shows that the PHMB-treated spandex fabric can kill 99% of the coronavirus within 2 h of contact, which suggests that the spandex fabric treated with PHMB could be used for developing antiviral clothing against coronaviruses for containing the transmission of COVID-19 in high-risk places. Furthermore, PHMB-treated spandex fabrics were shown excellent antibacterial activity against gram-positive S. aureus and gram-negative K. pneumoniae. The hand feel properties of Spandex fabric were not significantly affected by the PHMB coating in addition to the wrinkle recovery, which was obviously improved after PHMB coating.
Fitting Terrestrial Laser Scanner Point Clouds with T-Splines: Local Refinement Strategy for Rigid Body Motion
Authors: Kermarrec Gaël , Schild Niklas , Hartmann Jan
Published: June 2021

T-splines have recently been introduced to represent objects of arbitrary shapes using a smaller number of control points than the conventional non-uniform rational B-splines (NURBS) or B-spline representatizons in computer-aided design, computer graphics and reverse engineering. They are flexible in representing complex surface shapes and economic in terms of parameters as they enable local refinement. This property is a great advantage when dense, scattered and noisy point clouds are approximated using least squares fitting, such as those from a terrestrial laser scanner (TLS). Unfortunately, when it comes to assessing the goodness of fit of the surface approximation with a real dataset, only a noisy point cloud can be approximated: (i) a low root mean squared error (RMSE) can be linked with an overfitting, i.e., a fitting of the noise, and should be correspondingly avoided, and (ii) a high RMSE is synonymous with a lack of details. To address the challenge of judging the approximation, the reference surface should be entirely known: this can be solved by printing a mathematically defined T-splines reference surface in three dimensions (3D) and modeling the artefacts induced by the 3D printing. Once scanned under different configurations, it is possible to assess the goodness of fit of the approximation for a noisy and potentially gappy point cloud and compare it with the traditional but less flexible NURBS. The advantages of T-splines local refinement open the door for further applications within a geodetic context such as rigorous statistical testing of deformation. Two different scans from a slightly deformed object were approximated; we found that more than 40% of the computational time could be saved without affecting the goodness of fit of the surface approximation by using the same mesh for the two epochs.
A Fused Radar–Optical Approach for Mapping Wetlands and Deepwaters of the Mid–Atlantic and Gulf Coast Regions of the United States
Authors: Lamb Brian T. , Tzortziou Maria A. , McDonald Kyle C.
Published: June 2021

Tidal wetlands are critically important ecosystems that provide ecosystem services including carbon sequestration, storm surge mitigation, water filtration, and wildlife habitat provision while supporting high levels of biodiversity. Despite their importance, monitoring these systems over large scales remains challenging due to difficulties in obtaining extensive up-to-date ground surveys and the need for high spatial and temporal resolution satellite imagery for effective space-borne monitoring. In this study, we developed methodologies to advance the monitoring of tidal marshes and adjacent deepwaters in the Mid-Atlantic and Gulf Coast United States. We combined Sentinel-1 SAR and Landsat 8 optical imagery to classify marshes and open water in both regions, with user’s and producer’s accuracies exceeding 89%. This methodology enables the assessment of marsh loss through conversion to open water at an annual resolution. We used time-series Sentinel-1 imagery to classify persistent and non-persistent marsh vegetation with greater than 93% accuracy. Non-persistent marsh vegetation serves as an indicator of salinity regimes in tidal wetlands. Additionally, we mapped two invasive species: wetlands invasive Phragmites australis (common reed) with greater than 80% accuracy and deepwater invasive Trapa natans (water chestnut) with greater than 96% accuracy. These results have important implications for improved monitoring and management of coastal wetlands ecosystems.
A Machine Learning Approach for Estimating the Trophic State of Urban Waters Based on Remote Sensing and Environmental Factors
Authors: Zhu Shijie , Mao Jingqiao
Published: June 2021

To improve the accuracy of remotely sensed estimates of the trophic state index (TSI) of inland urban water bodies, key environmental factors (water temperature and wind field) were considered during the modelling process. Such environmental factors can be easily measured and display a strong correlation with TSI. Then, a backpropagation neural network (BP-NN) was applied to develop the TSI estimation model using remote sensing and environmental factors. The model was trained and validated using the TSI quantified by five water trophic indicators obtained for the period between 2018 and 2019, and then we selected the most appropriate combination of input variables according to the performance of the BP-NN. Our results demonstrate that the optimal performance can be obtained by combining the water temperature and single-band reflection values of Sentinel-2 satellite imagery as input variables (R2 = 0.922, RMSE = 3.256, MAPE = 2.494%, and classification accuracy rate = 86.364%). Finally, the spatial and temporal distribution of the aquatic trophic state over four months with different trophic levels was mapped in Gongqingcheng City using the TSI estimation model. In general, the predictive maps based on our proposed model show significant seasonal changes and spatial characteristics in the water trophic state, indicating the possibility of performing cost-effective, RS-based TSI estimation studies on complex urban water bodies elsewhere.
Mapping Winter Crops Using a Phenology Algorithm, Time-Series Sentinel-2 and Landsat-7/8 Images, and Google Earth Engine
Authors: Pan Li , Xia Haoming , Zhao Xiaoyang , Guo Yan , Qin Yaochen
Published: June 2021

With the increasing population and continuation of climate change, an adequate food supply is vital to economic development and social stability. Winter crops are important crop types in China. Changes in winter crops planting areas not only have a direct impact on China’s production and economy, but also potentially affects China’s food security. Therefore, it is necessary to obtain information on the planting of winter crops. In this study, we use the time series data of individual pixels, calculate the temporal statistics of spectral bands and the vegetation indices of optical data based on the phenological characteristics of specific vegetation or crops and record them in the time series data, and apply decision trees and rule-based algorithms to generate annual maps of winter crops. First, we constructed a dataset combining all the available images from Landsat 7/8 and Sentinel-2A/B. Second, we generated an annual map of land cover types to obtain the cropland mask in 2019. Third, we generated a time series of a single cropland pixel, and calculated the phenological indicators for classification by extracting the differences in phenological characteristics of different crops: these phenological indicators include SOS (start of season), SDP (start date of peak), EOS (end of season), GUS (green-up speed) and GSL (growing-season length). Finally, we identified winter crops in 2019 based on their phenological characteristics. The main advantages of the phenology-based algorithm proposed in this study include: (1) Combining multiple sensor data to construct a high spatiotemporal resolution image collection. (2) By analyzing the whole growth season of winter crops, the planting area of winter crops can be extracted more accurately, and (3) the phenological indicators of different periods are extracted, which is conducive to monitoring winter crop planting information and seasonal dynamics. The results show that the algorithm constructed in this study can accurately extract the planting area of winter crops, with user, producer, overall accuracies and Kappa coefficients of 96.61%, 94.13%, 94.56% and 0.89, respectively, indicating that the phenology-based algorithm is reliable for large area crop classification. This research will provide a point of reference for crop area extraction and monitoring.
Feature Fusion Approach for Temporal Land Use Mapping in Complex Agricultural Areas
Authors: Wang Lijun , Wang Jiayao , Qin Fen
Published: June 2021

Accurate temporal land use mapping provides important and timely information for decision making for large-scale management of land and crop production. At present, temporal land cover and crop classifications within a study area have neglected the differences between subregions. In this paper, we propose a classification rule by integrating the terrain, time series characteristics, priority, and seasonality (TTPSR) with Sentinel-2 satellite imagery. Based on the time series of Normalized Difference Water Index (NDWI) and Vegetation Index (NDVI), a dynamic decision tree for forests, cultivation, urban, and water was created in Google Earth Engine (GEE) for each subregion to extract cultivated land. Then, with or without this cultivated land mask data, the original classification results for each subregion were completed based on composite image acquisition with five vegetation indices using Random Forest. During the post-reclassification process, a 4-bit coding rule based on terrain, type, seasonal rhythm, and priority was generated by analyzing the characteristics of the original results. Finally, statistical results and temporal mapping were processed. The results showed that feature importance was dominated by B2, NDWI, RENDVI, B11, and B12 over winter, and B11, B12, NDBI, B2, and B8A over summer. Meanwhile, the cultivated land mask improved the overall accuracy for multicategories (seven to eight and nine to 13 during winter and summer, respectively) in each subregion, with average ranges in the overall accuracy for winter and summer of 0.857–0.935 and 0.873–0.963, respectively, and kappa coefficients of 0.803–0.902 and 0.835–0.950, respectively. The analysis of the above results and the comparison with resampling plots identified various sources of error for classification accuracy, including spectral differences, degree of field fragmentation, and planting complexity. The results demonstrated the capability of the TTPSR rule in temporal land use mapping, especially with regard to complex crops classification and automated post-processing, thereby providing a viable option for large-scale land use mapping.
Quantitative Remote Sensing of Metallic Elements for the Qishitan Gold Polymetallic Mining Area, NW China
Authors: Cheng Gong , Huang Huikun , Li Huan , Deng Xiaoqing , Khan Rehan , SohTamehe Landry , Atta Asad , Lang Xuechong , Guo Xiaodong
Published: June 2021

The recent development in remote sensing imagery and the use of remote sensing detection feature spectrum information together with the geochemical data is very useful for the surface element quantitative remote sensing inversion study. This aim of this article is to select appropriate methods that would make it possible to have rapid economic prospecting. The Qishitan gold polymetallic deposit in the Xinjiang Uygur Autonomous Region, Northwest China has been selected for this study. This paper establishes inversion maps based on the contents of metallic elements by integrating geochemical exploration data with ASTER and WorldView-2 remote sensing data. Inversion modelling maps for As, Cu, Hg, Mo, Pb, and Zn are consistent with the corresponding geochemical anomaly maps, which provide a reference for metallic ore prospecting in the study area. ASTER spectrum covers short-wave infrared and has better accuracy than WorldView-2 data for the inversion of some elements (e.g., Au, Hg, Pb, and As). However, the high spatial resolution of WorldView-2 drives the final content inversion map to be more precise and to better localize the anomaly centers of the inversion results. After scale conversion by re-sampling and kriging interpolation, the modeled and predicted accuracy of the models with square interpolation is much closer compare with the ground resolution of the used remote sensing data. This means our results are much satisfactory as compared to other interpolation methods. This study proves that quantitative remote sensing has great potential in ore prospecting and can be applied to replace traditional geochemical exploration to some extent.
Modeling of Environmental Impacts on Aerial Hyperspectral Images for Corn Plant Phenotyping
Authors: Ma Dongdong , Rehman Tanzeel U. , Zhang Libo , Maki Hideki , Tuinstra Mitchell R. , Jin Jian
Published: June 2021

Aerial imaging technologies have been widely applied in agricultural plant remote sensing. However, an as yet unexplored challenge with field imaging is that the environmental conditions, such as sun angle, cloud coverage, temperature, and so on, can significantly alter plant appearance and thus affect the imaging sensor’s accuracy toward extracting plant feature measurements. These image alterations result from the complicated interaction between the real-time environments and plants. Analysis of these impacts requires continuous monitoring of the changes through various environmental conditions, which has been difficult with current aerial remote sensing systems. This paper aimed to propose a modeling method to comprehensively understand and model the environmental influences on hyperspectral imaging data. In 2019, a fixed hyperspectral imaging gantry was constructed in Purdue University’s research farm, and over 8000 repetitive images of the same corn field were taken with a 2.5 min interval for 31 days. Time-tagged local environment data, including solar zenith angle, solar irradiation, temperature, wind speed, and so on, were also recorded during the imaging time. The images were processed for phenotyping data, and the time series decomposition method was applied to extract the phenotyping data variation caused by the changing environments. An artificial neural network (ANN) was then built to model the relationship between the phenotyping data variation and environmental changes. The ANN model was able to accurately predict the environmental effects in remote sensing results, and thus could be used to effectively eliminate the environment-induced variation in the phenotyping features. The test of the normalized difference vegetation index (NDVI) calculated from the hyperspectral images showed that variance in NDVI was reduced by 79%. A similar performance was confirmed with the relative water content (RWC) predictions. Therefore, this modeling method shows great potential for application in aerial remote sensing applications in agriculture, to significantly improve the imaging quality by effectively eliminating the effects from the changing environmental conditions.
Satellite Retrieval of Air Pollution Changes in Central and Eastern China during COVID-19 Lockdown Based on a Machine Learning Model
Authors: Song Zigeng , Bai Yan , Wang Difeng , Li Teng , He Xianqiang
Published: June 2021

With the implementation of the 2018–2020 Clean Air Action Plan (CAAP) the and impact from COVID-19 lockdowns in 2020, air pollution emissions in central and eastern China have decreased markedly. Here, by combining satellite remote sensing, re-analysis, and ground-based observational data, we established a machine learning (ML) model to analyze annual and seasonal changes in primary air pollutants in 2020 compared to 2018 and 2019 over central and eastern China. The root mean squared errors (RMSE) for the PM2.5, PM10, O3, and CO validation dataset were 9.027 μg/m3, 20.312 μg/m3, 10.436 μg/m3, and 0.097 mg/m3, respectively. The geographical random forest (RF) model demonstrated good performance for four main air pollutants. Notably, PM2.5, PM10, and CO decreased by 44.1%, 43.2%, and 35.9% in February 2020, which was likely influenced by the COVID-19 lockdown and primarily lasted until May 2020. Furthermore, PM2.5, PM10, O3, and CO decreased by 16.4%, 24.2%, 2.7%, and 19.8% in 2020 relative to the average values in 2018 and 2019. Moreover, the reduction in O3 emissions was not universal, with a significant increase (~20–40%) observed in uncontaminated areas.
Pair Nodes Clock Synchronization Algorithm Based on Kalman Filter for Underwater Wireless Sensor Networks
Authors: Ni Xiaomeng , Lu Ting , Ye Sijia , Zheng Yunsi , Chen Pengfei , Chen Lingyu
Published: June 2021

Time synchronization is the basis of many applications. Aiming at the limitations of the existing clock synchronization algorithms in underwater wireless sensor networks, we propose a pairwise synchronization algorithm called K-Sync, which is based on the Kalman filter. The algorithm does not need the assistance of the position sensor or the speed sensor, and the high time synchronization accuracy can be realized only by utilizing the time-stamps information in the process of message exchange. The K-Sync uses the general constraints of the motion characteristics of the sensor nodes to establish the recursive equations of the clock skew, clock offset, relative mobility velocity, and relative distance. At the same time, the time-stamps are viewed as the observation variables and the system observation equation is obtained. The K-Sync estimates the normalized clock skew and offset of the node via the Kalman filter to achieve high-precision clock synchronization between the two nodes. The simulation shows that the K-Sync has obvious advantages in the key indicators such as the estimated accuracy of clock skew and clock offset, convergence speed, etc. In addition, the K-Sync is more robust to a variety of underwater motion scenes.
Optical-Based Foot Plantar Pressure Measurement System for Potential Application in Human Postural Control Measurement and Person Identification
Authors: Keatsamarn Tanapon , Visitsattapongse Sarinporn , Aoyama Hisayuki , Pintavirooj Chuchart
Published: June 2021

Plantar pressure, the pressure exerted between the sole and the supporting surface, has great potentialities in various research fields, including footwear design, biometrics, gait analysis and the assessment of patients with diabetes. This research designs an optical-based foot plantar pressure measurement system aimed for human postural control and person identification. The proposed system consists of digital cameras installed underneath an acrylic plate covered by glossy white paper and mounted with LED strips along the side of the plate. When the light is emitted from the LED stripes, it deflects the digital cameras due to the pressure exerted between the glossy white paper and the acrylic plate. In this way, the cameras generate color-coded plantar pressure images of the subject standing on the acrylic-top platform. Our proposed system performs personal identification and postural control by extracting static and dynamic features from the generated plantar pressure images. Plantar pressure images were collected from 90 individuals (40 males, 50 females) to develop and evaluate the proposed system. In posture balance evaluation, we propose the use of a posture balance index that contains both magnitude and directional information about human posture balance control. For person identification, the experimental results show that our proposed system can achieve promising results, showing an area under the receiver operating characteristic (ROC) curve of 0.98515 (98.515%), an equal error rate (EER) of 5.8687%, and efficiency of 98.515%.
Experimental Methods for Measuring the Viscous Friction Coefficient in Hydraulic Spool Valves
Authors: Rundo Massimo , Casoli Paolo , Lettini Antonio
Published: June 2021

In hydraulic components, nonlinearities are responsible for critical behaviors that make it difficult to realize a reliable mathematical model for numerical simulation. With particular reference to hydraulic spool valves, the viscous friction coefficient between the sliding and the fixed body is an unknown parameter that is normally set a posteriori in order to obtain a good agreement with the experimental data. In this paper, two different methodologies to characterize experimentally the viscous friction coefficient in a hydraulic component with spool are presented. The two approaches are significantly different and are both based on experimental tests; they were developed in two distinct laboratories in different periods of time and applied to the same flow compensator of a pump displacement control. One of the procedures was carried out at the Fluid Power Research Laboratory of the Politecnico di Torino, while the other approach was developed at the University of Parma. Both the proposed methods reached similar outcomes; moreover, neither method requires the installation of a spool displacement transducer that can significantly affect the results.
Assessment of Occupational Exposure to BTEX in a Petrochemical Plant via Urinary Biomarkers
Authors: Mihajlović Višnja , Grba Nenad , Suđi Jan , Eichert Diane , Krajinović Smilja , Gavrilov Milivoj B. , Marković Slobodan B.
Published: June 2021

This work presents the results of the first Serbian monitoring campaign performed to assess the occupational exposure of petrochemical industry workers to benzene (B), toluene (T), ethylbenzene (E), and xylene (X), known collectively as BTEX. The following urinary biomarkers were investigated: phenol, hippuric acid, o-Cresol, p-Cresol, and creatinine. BTEX compounds were collected in 2014 using Casella passive samplers. Multivariate statistical analysis was performed to put in evidence the correlation between the BTEX measured in air and the concentration of urinary biomarkers. While the results indicate an elevated presence of benzene in the air in the working environment studied that surpasses the national and European Occupational Exposure Limits (OEL), the levels of the remaining (TEX) parameters measured were below the OEL. The high relative standard deviations (RSD) for the concentrations of each BTEX compound (68–161 mg m−3) point toward an intensive occupational exposure to BTEX. This was confirmed by relevant urine biomarkers, particularly by the mean values of phenol, which were ten and fourteen times higher than the ones found in the control group (14–12 mg g−1 of creatinine). On average, workers are at a higher risk of developing cancer (6.1 × 10−3), with risk levels exceeding the US EPA limits. Benzene levels should therefore be maintained under tight controls and monitored via proper urinary biomarkers.
The Relevance of Grated Inlets within Surface Drainage Systems in the Field of Urban Flood Resilience. A Review of Several Experimental and Numerical Simulation Approaches
Authors: Russo Beniamino , Valentín Manuel Gómez , Tellez-Álvarez Jackson
Published: June 2021

Urban drainage networks should be designed and operated preferably under open channel flow conditions without flux return, backwater, or overflows. In the case of extreme storm events, urban pluvial flooding is generated by the excess of surface runoff that could not be conveyed by pressurized sewer pipes, due to its limited capacity or, many times, due to the poor efficiency of surface drainage systems to collect uncontrolled overland flow. Generally, the hydraulic design of sewer systems is addressed more for underground networks, neglecting the surface drainage system, although inadequate inlet spacings and locations can cause dangerous flooding with relevant socio-economic impacts and the interruption of critical services and urban activities. Several experimental and numerical studies carried out at the Technical University of Catalonia (UPC) and other research institutions demonstrated that the hydraulic efficiency of inlets can be very low under critical conditions (e.g., high circulating overland flow on steep areas). In these cases, the hydraulic efficiency of conventional grated inlets and continuous transverse elements can be around 10–20%. Their hydraulic capacity, expressed in terms of discharge coefficients, shows the same criticism with values quite far from those that are usually used in several project practice phases. The grate clogging phenomenon and more intense storm events produced by climate change could further reduce the inlets’ performance. In this context, in order to improve the flood urban resilience of our cities, the relevance of the hydraulic behavior of surface drainage systems is clear.
The Effects of Hot Blocks Geometry and Particle Migration on Heat Transfer and Entropy Generation of a Novel I-Shaped Porous Enclosure
Authors: Ghasemiasl Ramin , Molana Maysam , Armaghani Taher , Saffari Pour Mohsen
Published: June 2021

This paper studied the cooling performance of a hot electronic chip using nanofluids (NF) mixed convection, implementing Buongiorno’s model of the NF simulation. The NF were assumed water-Al2O3 nanoparticles (NP) in the range of 0 to 4% of volume concentration. Six different problems of the combinations of three internal hot blocks, including triangular, square, and circular geometries, and two porous media, including sand and compact metallic powder, were numerically solved. To discretize the governing equations, a finite control volume method was applied. As most of the proposed correlations for the thermophysical properties of the NF were inaccurate, especially for thermal conductivity, a new predictive correlation was proposed using the multi-variable regression method with acceptable accuracy. It was found that the cooling performance improved with any increase in the NP loading. A higher nanoparticle concentration yielded better cooling characteristics, which was 11.93% for 4% volume. The sand porous medium also yielded a much higher value of the normalized Nusselt number (Nu) compared to the other medium. The entropy generation (EG) enhancement was maximum for the triangular hot block in a sand porous cavity.
The Impact of B Corp Certification on Growth
Authors: Paelman Valerie , Van Cauwenberge Philippe , Vander Bauwhede Heidi
Published: June 2021

We empirically test whether B Corp certification affects the short- and medium-term growth rates of sustainable enterprises. These businesses are growing in popularity and prevalence but, due to their hybrid nature, often suffer from external credibility issues and competing internal logics. Because of the rigorous and time-involving audit procedure, B Corp certification potentially sends a credible signal about the sustainable nature of the enterprise to its stakeholders. In addition, the B Corp label could help to straighten out internal tensions and align the company towards its dual purpose. Hence, B Corp certification could contribute to company success. We observe 129 firms that were certified between 2013 and 2018 over a period between six years prior and five years post-certification. Using propensity score matching, we identify 129 non-certified matching companies. On this sample, we conduct a difference-in-differences panel regression analysis to investigate the effect of certification. Our dataset allows us to study how the effects of B Corp certification evolve over time, which was previously untested. Our study documents a positive effect of B Corp certification on turnover growth and also that this effect increases with the time since certification, implying that certification requires some time for its full effect to become apparent.
A Parametric Study on a Diesel Engine Fuelled Using Waste Cooking Oil Blended with Al2O3 Nanoparticle—Performance, Emission, and Combustion Characteristics
Authors: Ponnusamy Muruganantham , Ramani Bharathwaaj , Sathyamruthy Ravishankar
Published: June 2021

As the environment is humiliated at a disturbing rate, most governments have persistent calls following global energy policies for the utilization of biofuels. This paper essentially examines the portrayal investigations of fatty acid methyl esters and fatty acid pentyl esters obtained from palm oil. The characterization studies such as gas chromatogram, mass spectrometry, and Fourier transformed infrared spectrometry have been performed to study biodiesel’s chemical composition. This article likewise shows biodiesel’s physiochemical properties and concentrates on biodiesel blends’ hypothetical combustion properties with Al2O3 nanoparticles. The spectroscopic investigations demonstrate the contiguity of eight methyl esters and five pentyl esters prevalently of palmitic acid, oleic acid, octanoic acid, and stearic acid. The esters’ nearness was additionally affirmed by the FTIR range, where the peaks in the scope of 1700 cm−1 to 1600 cm−1 can be observed. Looking at the thermophysical properties of the mixes with that of the base diesel fuel yielded the compromising results by giving the comparative density to that of the diesel fuel. The palm oil biodiesel’s calorific value is, by all accounts, diminished by 10% when contrasted with diesel fuel. The addition of the nanoparticles up to 1 g has raised the calorific value most closely to the diesel’s value. Correspondingly, the theoretical burning examinations have demonstrated the limit of biodiesel to go about as an option compared to consistent diesel in the conventional DI–CI engine. This article talks about the combustion attributes of the blend containing 60% diesel, 20% fatty acid methyl ester (FAME), and 20% fatty acid pentyl ester (FAPE) with aluminium oxide (Al2O3) nanoparticles at two distinctive concentrations. This article primarily concerns the inquiry of combustion criterion, such as in-chamber pressure variation, rate of heat release, start of combustion, end of combustion, and ignition delay for considered fuel blends when contrasted with neat diesel fuel in a four-stroke, direct-injection, single-cylinder diesel engine. The results showed a decrease in in-cylinder pressure at all loads of engine operation for biodiesel blends when compared with neat diesel, irrespective of the nanoparticle concentration. Biodiesel blends at all nanoparticle concentrations showed an increase in ignition delay compared with diesel fuels at all engine operation loads. The performance results show a slight deterioration in the engine’s thermal efficiency using biodiesel blends, irrespective of the nanoparticle concentration. Additionally, the emissions show a considerable fall in trends for all loads in contrast with diesel fuel.
Optimal Operation of Low-Capacity Heat Pump Systems for Residential Buildings through Thermal Energy Storage
Authors: Franco Alessandro , Bartoli Carlo , Conti Paolo , Testi Daniele
Published: June 2021

The paper provides results from a hardware-in-the-loop experimental campaign on the operation of an air-source heat pump (HP) for heating a reference dwelling in Pisa, Italy. The system performances suffer from typical oversizing of heat emission devices and high water-supply temperature, resulting in HP inefficiencies, frequent on-off cycles, and relevant thermal losses on the hydronic loop. An experimentally validated HP model under different supply temperatures and part-load conditions is used to simulate the installation of a thermal storage between heat generator and emitters, in both series and parallel arrangements. Results relative to a typical residential apartment show that the presence of the thermal storage in series configuration ensures smoother heat pump operation and energy performance improvement. The number of daily on-off cycles can be reduced from 40 to 10, also saving one-third of electric energy with the same building loads. Preliminary guidelines are proposed for correctly sizing the tank in relation to the HP capacity and the average daily heating load of the building. A storage volume of about 70 L for each kilowatt of nominal heating capacity is suggested.
The Effect of CSR Attributes on CSR Authenticity: Focusing on Mediating Effects of Digital Transformation
Authors: Liu Huifang , Jung Jin-Sup
Published: June 2021

What corporate social responsibility (CSR) attributes determine the CSR authenticity of a company? In the face of the Fourth Industrial Revolution, what direction should the CSR strategy pursue? In the electronics industries in Korea and China, are there any differences in CSR attributes? In this study, we start with some of these basic questions. Considering the promotional and actual costs incurred from CSR activities, CSR strategy are not an issue that can be easily determined from the corporate perspective. However, now it is essential for companies to carry out CSR and sustainable development goals (SDGs) activities, and businesses cannot overlook social issues either. Companies cannot pursue only growth through corporate interests without social value. In this study, we derive three attributes of CSR fit, CSR sustainability, and CSR impact to verify the authenticity of CSR activities. Moreover, we demonstrated the impact of these three attributes on CSR authenticity for the electronics industries in Korea and China. As a result of empirical testing, most of three attributes above mentioned (i.e., CSR fit, CSR sustainability, and CSR impact) produce meaningful results for CSR authenticity. However, CSR sustainability was rejected for the Korea sample, and CSR fit was rejected for the Chinese sample, showing some differences between the two countries. Meanwhile, the digital transformation of the Fourth Industrial Revolution had strong partial mediating effects between CSR attributes and CSR authenticity. This means that digital transformation can be an important pathway to achieve CSR authenticity and suggests that important mediating effects can eventually lead to a firm’s competitiveness.
Effects of Industrial Land Conveyance on Coastal Marine Pollution: An Spatial Durbin Econometric Analysis
Authors: Hu Qiuguang , Shen Weiteng
Published: June 2021

Compared to inland areas, coastal areas display more frequent economic activity in China. Unfortunately, they also have the greatest impact on the coastal environment. Among the economic activities in coastal areas, industrial land conveyance not only has a profound impact on local economic growth, but also poses a greater threat to coastal water. Using panel data collected from 45 coastal cities during the period 2007–2017, this study constructed a spatial Durbin model to investigate the effects of industrial land conveyance on coastal marine pollution. Results show that the expansion of two-lagged agreement-based industrial land conveyance areas in a coastal city can increase coastal marine pollution. Meanwhile, the positive impacts of the two-lagged industrial land conveyance and the industrial land conveyance areas, through bidding, auction, and listing, on coastal marine pollution are statistically significant but economically insignificant. Furthermore, the two-lagged industrial land conveyance areas have a spatial spillover effect on coastal marine pollution. Specifically, the expansion of such areas from a coastal city can increase the marine pollution of other coastal cities.
Comparative Assessment of Sustainable Consumption Based on the Digital Information Environment Content-Thematic Component Differentiation
Authors: Li Yanjie , Terenteva Daria , Konnikova Olga , Konnikov Evgenii
Published: June 2021

The modern culture of consumption often does not correspond to the principles of sustainable development, which leads to environmental pollution. As a possible solution to this problem, the authors propose to analyze the concept of sustainable consumption, following which can reduce the negative impact of mankind on the environment, which is an urgent issue at the global level. The aim of the study is to build a tool for comparative analysis of the level of sustainable consumption. The analysis is carried out in the digital environment, since this space provides a relative freedom of expression of the opinion of individuals, and the obtained data reflect the real level of “sustainability” of the behavior of participants in thematic social communities. The result of the research is an analytical tool tested on thematic social communities of the VK.com social network. In the process of building an analytical tool, primary and secondary tokenization were carried out using computer linguistics tools, an analytical dataframe was formed for a source reflecting the studied content-thematic component. To automate the process of forming a set of tokens, Python 3 programming language was used. The proposed tool can be used to determine the level of sustainable consumption in different social communities relative to each other. This approach can be used by companies to find target audiences and to promote environmentally friendly products. Moreover, this tool can be applied to attract consumers by increasing the level of sustainability in the corporate culture based on the research results. A separate problematic of realizing the developed methodology is the ethical component of analyzing natural digital information and the use of the results obtained on the basis of its analysis.
Integration of Digital Economy and Circular Economy: Current Status and Future Directions
Authors: Liu Zhen , Liu Jing , Osmani Mohamed
Published: June 2021

Circular economy (CE) is a concept actively advocated by the European Union (EU), China, Japan, and the United Kingdom. At present, CE is considered to grant the most traction for companies to achieve sustainable development. However, CE is still rarely adopted by enterprises. As the backbone of the fourth industrial revolution, the digital economy (DE) is considered to have a disruptive effect. Studies have shown that digital technology has great potential in promoting the development of CE. Especially during the COVID-19 epidemic that has severely negatively affected the global economy, environment, and society, CE and DE are receiving high attention from policy makers, practitioners, and scholars around the world. However, the integration of CE and digital technology is a small and rapidly developing research field that is still in its infancy. Although there is a large amount of research in the fields of CE and DE, respectively, there are few studies that look into integrating these two fields. Therefore, the purpose of this paper is to explore the research progress and trends of the integration of CE and DE, and provide an overview for future research. This paper adopts a bibliometric research method, employs the Web of Science database as its literature source, and uses VOSviewer visual software to carry out keyword co-occurrence analysis, which focuses on publication trends, journal sources, keyword visualization, multidisciplinary areas, life cycle stages, and application fields.
Critical Leaf Water Content for Maize Photosynthesis under Drought Stress and Its Response to Rewatering
Authors: Song Xingyang , Zhou Guangsheng , He Qijin
Published: June 2021

Crop photosynthesis is closely related to leaf water content (LWC), and clarifying the LWC conditions at critical points in crop photosynthesis has great theoretical and practical value for accurately monitoring drought and providing early drought warnings. This experiment was conducted to study the response of LWC to drought and rewatering and to determine the LWC at which maize photosynthesis reaches a maximum and minimum and thus changes from a state of stomatal limitation (SL) to non-stomatal limitation (NSL). The effects of rehydration were different after different levels of drought stress intensity at different growth stages, and the maize LWC recovered after rewatering following different drought stresses at the jointing stage; however, the maize LWC recovered more slowly after rewatering following 43 days and 36 days of drought stress at the tasselling and silking stages, respectively. The LWC when maize photosynthesis changed from SL to NSL was 75.4% ± 0.38%, implying that the maize became rehydrated under physiologically impaired conditions. The LWCs at which the maize Vcmax25 reached maximum values and zero differed between the drought and rewatering periods. After exposure to drought stress, the maize exhibited enhanced drought stress tolerance, an obviously reduced suitable water range, and significantly weakened photosynthetic capacity. These results provide profound insight into the turning points in maize photosynthesis and their responses to drought and rewatering. They may also help to improve crop water management, which will be useful in coping with the increased frequency of drought and extreme weather events expected under global climate change.
Determining Food Stability to Achieve Food Security
Authors: García-Díez Juan , Gonçalves Carla , Grispoldi Luca , Cenci-Goga Beniamino , Saraiva Cristina
Published: June 2021

Food security, as part as public health protection, constitutes one of the main objectives for countries aiming to ensure the health of all their citizens. However, food security is compromised worldwide by conflict, political instability, or economic crises, both in developed and developing countries. Conversely, because of the importance of agriculture to the economies of rural areas both in developed and developing countries, this sector can contribute to improving food stability, as well as to furthering food security. Thus, livestock and traditional meat products represent a key factor in ensuring food availability. Overall, biosecurity measures improve animal welfare by decreasing the occurrence of diseases that compromise the stability by causing fluctuations in the availability of meat and animal-derived food products such as milk, eggs, or traditional fermented products. As a consequence, an absence of biosecurity measures affects food security (in its quantitative definition, as described above) as well as the productive, sanitary, and environmental sustainability of the rural environment. Products of animal origin support local trade and the regional economy, while contributing to the availability of foods without great external dependence. The manufacture of foods of animal origin aims to create products that are durable and that maintain food availability for long periods of time, even during seasons with scarce resources. Thus, dry-cured or fermented meat products play an important role in food availability. Food security also refers to food access under healthy economic conditions; therefore, knowledge of the main tools that guarantee the safety of these kinds of food products is essential to achieving food stability and further food security.
A Techno-Economic Evaluation of Municipal Solid Waste (MSW) Conversion to Energy in Indonesia
Authors: Azis Muhammad Mufti , Kristanto Jonas , Purnomo Chandra Wahyu
Published: June 2021

Municipal solid waste (MSW) processing is still problematic in Indonesia. From the hierarchy of waste management, it is clear that energy recovery from waste could be an option after prevention and the 5R (rethink, refuse, reduce, reuse, recycle) processes. The Presidential Regulation No 35/2018 mandated the acceleration of waste-to-energy (WtE) plant adoption in Indonesia. The present study aimed to demonstrate a techno-economic evaluation of a commercial WtE plant in Indonesia by processing 1000 tons of waste/day to produce ca. 19.7 MW of electricity. The WtE electricity price is set at USD 13.35 cent/kWh, which is already higher than the average household price at USD 9.76 cent/kWh. The capital investment is estimated at USD 102.2 million. The annual operational cost is estimated at USD 12.1 million and the annual revenue at USD 41.6 million. At this value, the internal rate of return (IRR) for the WtE plant is 25.32% with a payout time (PoT) of 3.47 years. In addition, this study also takes into account electricity price sales, tipping fee, and pretreatment cost of waste. The result of a sensitivity analysis showed that the electricity price was the most sensitive factor. This study reveals that it is important to maintain a regulated electricity price to ensure the sustainability of the WtE plant in Indonesia.