bluuebunny/crossref_metadata_2025 huggingface dataset:
Artificial Intelligence as a Tool Supporting Prayer Practices
Authors: Gruchoła Małgorzata , Sławek-Czochra Małgorzata , Zieliński Robert
Published: February 2024

This article attempts to describe Poles’ attitudes towards AI in the development of Christian prayer as a technology supporting prayer practices. Four research questions were formulated: 1. Do the frequency of prayer and engagement in religious practices influence the attitudes of Poles towards prayer programs/applications based on AI technology? 2. Does believers’ age affect Poles’ attitudes towards prayer programs/applications based on AI? 3. Does believers’ place of residence affect the attitude of Poles towards AI-based prayer programs/applications? 4. Do current users of the prayer-supporting applications plan to continue using it, and are new believers considering using it in the future? Research hypotheses were adopted to verify the research problem, with the first, second, and third being positively verified. H1: The higher the level of prayer frequency and engagement in religious practices of respondents, the more conservative the attitude towards prayer programs/applications based on AI; H2: The age of respondents differentiates the attitudes of Poles towards prayer programs/applications. H3: The respondents’ place of residence differentiates Poles’ attitudes towards prayer programs/applications. H4: Most AI users plan to continue such usage in the future, while new practitioners will appear.
Estimating Sugarcane Aboveground Biomass and Carbon Stock Using the Combined Time Series of Sentinel Data with Machine Learning Algorithms
Authors: Suwanlee Savittri Ratanopad , Pinasu Dusadee , Som-ard Jaturong , Borgogno-Mondino Enrico , Sarvia Filippo
Published: February 2024

Accurately mapping crop aboveground biomass (AGB) in a timely manner is crucial for promoting sustainable agricultural practices and effective climate change mitigation actions. To address this challenge, the integration of satellite-based Earth Observation (EO) data with advanced machine learning algorithms offers promising prospects to monitor land and crop phenology over time. However, achieving accurate AGB maps in small crop fields and complex landscapes is still an ongoing challenge. In this study, the AGB was estimated for small sugarcane fields (<1 ha) located in the Kumphawapi district of Udon Thani province, Thailand. Specifically, in order to explore, estimate, and map sugarcane AGB and carbon stock for the 2018 and 2021 years, ground measurements and time series of Sentinel-1 (S1) and Sentinel-2 (S2) data were used and random forest regression (RFR) and support vector regression (SVR) applied. Subsequently, optimized predictive models used to generate large-scale maps were adapted. The RFR models demonstrated high efficiency and consistency when compared to the SVR models for the two years considered. Specifically, the resulting AGB maps displayed noteworthy accuracy, with the coefficient of determination (R2) as 0.85 and 0.86 with a root mean square error (RMSE) of 8.84 and 9.61 t/ha for the years 2018 and 2021, respectively. In addition, mapping sugarcane AGB and carbon stock across a large scale showed high spatial variability within fields for both base years. These results exhibited a high potential for effectively depicting the spatial distribution of AGB densities. Finally, it was shown how these highly accurate maps can support, as valuable tools, sustainable agricultural practices, government policy, and decision-making processes.
The Expanding of Proglacial Lake Amplified the Frontal Ablation of Jiongpu Co Glacier since 1985
Authors: Zhao Xuanru , Cheng Jinquan , Guan Weijin , Zhang Yuxuan , Cao Bo
Published: February 2024

In High Mountain Asia, most glaciers and glacial lakes have undergone rapid variations throughout changes in the climate. Unlike land-terminating glaciers, lake-terminating glaciers show rapid shrinkage due to dynamic interactions between proglacial lakes and glacier dynamics. In this study, we conducted a detailed analysis of the changes in the surface elevation, velocity, and especially frontal ablation on Jiongpu Co lake-terminating glacier. The results show that the Jiongpu Co glacier has twice as much negative mass balance compared to other glaciers, and the annual surface velocity has anomalously increased (3.6 m a−1 per decade) while other glaciers show a decreased trend. The frontal ablation fraction in the net mass loss of the Jiongpu Co glacier increased from 26% to 52% with the accelerated expansion of the proglacial lake. All available evidence indicates the presence of positive feedback between the proglacial lake and its host glacier. Our findings highlight the existence of proglacial lake affects the spatial change patterns of the lake-terminating glacier. Furthermore, the ongoing enlargement of the lake area amplifies the changes associated with the evolution of the lake-terminating glacier.
Efficient Blind Hyperspectral Unmixing Framework Based on CUR Decomposition (CUR-HU)
Authors: Abdelgawad Muhammad A. A. , Cheung Ray C. C. , Yan Hong
Published: February 2024

Hyperspectral imaging captures detailed spectral data for remote sensing. However, due to the limited spatial resolution of hyperspectral sensors, each pixel of a hyperspectral image (HSI) may contain information from multiple materials. Although the hyperspectral unmixing (HU) process involves estimating endmembers, identifying pure spectral components, and estimating pixel abundances, existing algorithms mostly focus on just one or two tasks. Blind source separation (BSS) based on nonnegative matrix factorization (NMF) algorithms identify endmembers and their abundances at each pixel of HSI simultaneously. Although they perform well, the factorization results are unstable, require high computational costs, and are difficult to interpret from the original HSI. CUR matrix decomposition selects specific columns and rows from a dataset to represent it as a product of three small submatrices, resulting in interpretable low-rank factorization. In this paper, we propose a new blind HU framework based on CUR factorization called CUR-HU that performs the entire HU process by exploiting the low-rank structure of given HSIs. CUR-HU incorporates several techniques to perform the HU process with a performance comparable to state-of-the-art methods but with higher computational efficiency. We adopt a deterministic sampling method to select the most informative pixels and spectrum components in HSIs. We use an incremental QR decomposition method to reduce computation complexity and estimate the number of endmembers. Various experiments on synthetic and real HSIs are conducted to evaluate the performance of CUR-HU. CUR-HU performs comparably to state-of-the-art methods for estimating the number of endmembers and abundance maps, but it outperforms other methods for estimating the endmembers and the computational efficiency. It has a 9.4 to 249.5 times speedup over different methods for different real HSIs.
Multi-Modal Spectroscopic Assessment of Skin Hydration
Authors: Gidado Iman M. , Nwokoye Ifeabunike I. , Triantis Iasonas F. , Qassem Meha , Kyriacou Panicos A.
Published: February 2024

Human skin acts as a protective barrier, preserving bodily functions and regulating water loss. Disruption to the skin barrier can lead to skin conditions and diseases, emphasizing the need for skin hydration monitoring. The gold-standard sensing method for assessing skin hydration is the Corneometer, monitoring the skin’s electrical properties. It relies on measuring capacitance and has the advantage of precisely detecting a wide range of hydration levels within the skin’s superficial layer. However, measurement errors due to its front end requiring contact with the skin, combined with the bipolar configuration of the electrodes used and discrepancies due to variations in various interfering analytes, often result in significant inaccuracy and a need to perform measurements under controlled conditions. To overcome these issues, we explore the merits of a different approach to sensing electrical properties, namely, a tetrapolar bioimpedance sensing approach, with the merits of a novel optical sensing modality. Tetrapolar bioimpedance allows for the elimination of bipolar measurement errors, and optical spectroscopy allows for the identification of skin water absorption peaks at wavelengths of 970 nm and 1450 nm. Employing both electrical and optical sensing modalities through a multimodal approach enhances skin hydration measurement sensitivity and validity. This layered approach may be particularly beneficial for minimising errors, providing a more robust and comprehensive tool for skin hydration assessment. An ex vivo desorption experiment was carried out on fresh porcine skin, and an in vivo indicative case study was conducted utilising the developed optical and bioimpedance sensing devices. Expected outcomes were expressed from both techniques, with an increase in the output of the optical sensor voltage and a decrease in bioimpedance as skin hydration decreased. MLR models were employed, and the results presented strong correlations (R-squared = 0.996 and p-value = 6.45 × 10−21), with an enhanced outcome for hydration parameters when both modalities were combined as opposed to independently, highlighting the advantage of the multimodal sensing approach for skin hydration assessment.
Phased Array Ultrasonic Method for Robotic Preload Measurement in Offshore Wind Turbine Bolted Connections
Authors: Javadi Yashar , Mills Brandon , MacLeod Charles , Lines David , Abad Farhad , Lotfian Saeid , Mehmanparast Ali , Pierce Gareth , Brennan Feargal , Gachagan Anthony , Mineo Carmelo
Published: February 2024

This paper presents a novel approach for preload measurement of bolted connections, specifically tailored for offshore wind applications. The proposed method combines robotics, Phased Array Ultrasonic Testing (PAUT), nonlinear acoustoelasticity, and Finite Element Analysis (FEA). Acceptable defects, below a pre-defined size, are shown to have an impact on preload measurement, and therefore conducting simultaneous defect detection and preload measurement is discussed in this paper. The study demonstrates that even slight changes in the orientation of the ultrasonic transducer, the non-automated approach, can introduce a significant error of up to 140 MPa in bolt stress measurement and therefore a robotic approach is employed to achieve consistent and accurate measurements. Additionally, the study emphasises the significance of considering average preload for comparison with ultrasonic data, which is achieved through FEA simulations. The advantages of the proposed robotic PAUT method over single-element approaches are discussed, including the incorporation of nonlinearity, simultaneous defect detection and stress measurement, hardware and software adaptability, and notably, a substantial improvement in measurement accuracy. Based on the findings, the paper strongly recommends the adoption of the robotic PAUT approach for preload measurement, whilst acknowledging the required investment in hardware, software, and skilled personnel.
A Three-Wavelength Optical Sensor for Measuring the Multi-Particle-Size Channel Mass Concentration of Thermal Power Plant Emissions
Authors: Xiao Xiao , Zhu Ming , Wang Qiuyu , Yuan Xiaodong , Lin Mengxue
Published: February 2024

Emissions from thermal power plants have always been the central consideration for environmental protection. Existing optical sensors in thermal power plants usually measure the total mass concentration of the particulate matter (PM) by a single-wavelength laser, bearing intrinsic errors owing to the variation in particle size distribution (PSD). However, the total mass concentration alone cannot characterize all the harmful effects of the air pollution caused by the power plant. Therefore, it is necessary to measure the mass concentration and PSD simultaneously, based on which we can obtain multi-particle-size channel mass concentration. To achieve this, we designed an optical sensor based on the three-wavelength technique and tested its performance in a practical environment. Results showed that the prototype cannot only correctly measure the mass concentration of the emitted PM but also determine the mean diameter and standard deviation of the PSDs. Hence, the mass concentrations of PM10, PM2.5, and PM1 are calculated, and the air pollutants emission by a thermal power plant can be estimated comprehensively.
Immunoassay System Based on the Technology of Time-Resolved Fluorescence Resonance Energy Transfer
Authors: Xu Zhengping , Zhou Hong , Li Li , Chen Zhang , Zhang Xin , Feng Yongtong , Wang Jianping , Li Yuan , Wu Yanfan
Published: February 2024

To enhance the specificity and sensitivity, cut the cost, and realize joint detection of multiple indicators, an immunoassay system based on the technology of time-resolved fluorescence resonance energy transfer (TR-FRET) was studied. Due to the FRET of the reagent, the donor probe and acceptor probe emitted specific fluorescence to enhance specificity. Long-lifetime specific fluorescence from the acceptor probe was combined with time-resolved technology to enhance sensitivity. A xenon flash lamp and a photomultiplier tube (PMT) were selected as the light source and detector, respectively. A filter-switching mechanism was placed in the light path, so the fluorescence signal from the donor and acceptor was measured alternately. The instrument’s design is given, and some specificI parts are described in detail. Key technical specifications of the instrument and procalcitonin (PCT), C-reactive protein (CRP), and interleukin-6(IL-6) were tested, and the test results were presented subsequently. The CV value of the self-designed counting module is better than 0.01%, and the instrument noises for 620 nm and 665 nm are 41.44 and 10.59, respectively. When set at 37 °C, the temperature bias (B) is 0.06 °C, and the temperature fluctuation is 0.10 °C. The CV and bias are between ±3% and 5%, respectively, when pipetting volumes are between 10 μL and 100 μL. Within the concentration range of 0.01 nM to 10 nM, the luminescence values exhibit linear regression correlation coefficients greater than 0.999. For PCT detection, when the concentration ranges from 0.02 ng/mL to 50 ng/mL, the correlation coefficient of linear fitting exceeds 0.999, and the limit of quantification is 0.096 ng/mL. For CRP and IL-6, the detection concentration ranges from 0 ng/mL to 500 ng/mL and 0 ng/mL to 20 ng/mL, respectively, with limits of quantification of 2.70 ng/mL and 2.82 ng/mL, respectively. The experimental results confirm the feasibility of the technical and instrumental solutions.
Using Probabilistic Machine Learning Methods to Improve Beef Cattle Price Modeling and Promote Beef Production Efficiency and Sustainability in Canada
Authors: Rahmani Elham , Khatami Mohammad , Stephens Emma
Published: February 2024

Accurate agricultural commodity price models enable efficient allocation of limited natural resources, leading to improved sustainability in agriculture. Because of climate change, price volatility and uncertainty in the sector are expected to increase in the future, increasing the need for improved price modeling. With the emergence of machine learning (ML) algorithms, novel tools are now available to enhance the modeling of agricultural commodity prices. This research explores both univariate and multivariate ML techniques to perform probabilistic price prediction modeling for the Canadian beef industry, taking into account beef production, commodity markets, and international trade features to enhance accuracy. We model Alberta fed steer prices using three multivariate ML algorithms (support vector regression (SVR), random forest (RF), and Adaboost (AB)) and three univariate ML algorithms (autoregressive integrated moving average (ARIMA), seasonal ARIMA (SARIMA), and the seasonal autoregressive integrated moving average with exogenous factors (SARIMAX)). We apply these models to monthly fed steer price data between January 2005 and September 2023 and compare predicted prices with observed prices using several validation metrics. The outcomes indicate that both random forest (RF) and Adaboost (AB) show superior overall performance in accurately predicting Alberta fed steer prices in comparison to other algorithms. To better account for the variance of the best model performance, we subsequently adopted a probabilistic approach by considering uncertainty in our best-selected ML model. The beef industry can use these improved price models to minimize resource waste and inefficiency in the sector and improve the long-term sustainability prospects for beef producers in Canada.
Evaluation of Ecological Function Restoration Effect for Degraded Natural Forests in Xiaoxinganling, China
Authors: Qu Hangfeng , Dong Xibin , Zhang Baoshan , Liu Hui , Gao Tong , Meng Yuan , Ren Yunze , Zhang Ying
Published: February 2024

To study the effect of ecological function restoration in degraded natural forests in Xiaoxinganling, Heilongjiang Province, China, we set up 90 plots of degraded natural forests of different types and ages in the Xinqing Group Branch of Yichun Forestry Industry Group in Xiaoxinganling, Heilongjiang Province, China. Moreover, 43 evaluation indexes, including litter characteristics, species diversity, soil physical properties, soil chemical properties, and canopy structural parameters, were selected to determine the effect of ecological function restoration in the degraded natural forests in the study area. Principal component analysis (PCA) was used to comprehensively evaluate the ecological function of the degraded forests. The results of the study showed that, based on the forest type scores, mixed coniferous and broadleaf forests, mixed coniferous forests, and broadleaf forests had higher scores, while the scores of pure Betula platyphylla forests, pure Larix gmelinii forests, and the three low-quality forests were lower. This showed that the ecological restoration effect for mixed forests in the Xinqing Group Branch of Yichun Sengyong Group of Xinjiangqing Group, Xiaoxinganling, Heilongjiang Province, China, was better than that for pure forests and low-quality forests. Based on forest age, the scores of near-mature forests and mature forests were generally higher than those of young forests and over-mature forests, indicating that the ecological restoration effect for near-mature forests and mature forests in Xinqing Group Branch of Yichun Forestry Industry Group in Xiaoxinganling, Heilongjiang Province, China, was better than that for young forests and over-mature forests. These evaluation results can provide a theoretical basis for subsequent research on the ecological restoration effect in degraded natural forests in Xiaoxinganling, Heilongjiang Province, China.
Exploring the Influence of the Built Environment on the Demand for Online Car-Hailing Services Using a Multi-Scale Geographically and Temporally Weighted Regression Model
Authors: Cheng Rongjun , Zeng Wenbao , Wu Xingjian , Chen Fuzhou , Miao Baobin
Published: February 2024

Online car-hailing is gradually shifting towards a predominant use of electric vehicles, a change that is advantageous for developing a sustainable society. Understanding the patterns of changes in online car-hailing travel can assist transportation authorities in optimizing vehicle dispatching, reducing idle rates, and minimizing resource wastage. The built environment influences the demand for online car-hailing travel. Previous studies have commonly employed the geographically weighted regression (GWR) model and the geographically and temporally weighted regression (GTWR) model to examine the relationship between the demand for online car-hailing trips and the built environment. However, these studies have ignored that the impact range of the built environment also varies with time and space. To fully consider the variations in the impact range of the built environment, this study established multi-scale geographically and temporally weighted regression (MGTWR) to examine the spatiotemporal impacts of urban built environments on the demand for online car-hailing travel. An empirical study was conducted to assess the effectiveness of the MGTWR model using point of interest (POI) data and online car-hailing order data from Haikou. The evaluation indicators showed that the MGTWR model has higher fitting accuracy than the GTWR model. Moreover, the impact of each type of POI on the demand for online car-hailing travel was analyzed by examining the temporal and spatial distribution of the regression coefficients. Additionally, we observed that transport facility POIs and healthcare service POIs exerted the most pronounced influence on the demand for online car-hailing. In contrast, the impact of shopping service POIs and catering service POIs was relatively weaker.
Optimal Resource Assignment in Hybrid Microgrids Based on Demand Response Proposals
Authors: Garcia Edwin , Águila Alexander , Ortiz Leony , Carrión Diego
Published: February 2024

The energy consumption of buildings has been affected by the increase in new loads, which is where emerging technologies have become important. In this sense, microgrids have become a solution that has reduced the loadability of power systems. Thus, the Salesian Polytechnic University in Quito has implemented a hybrid microgrid with three photovoltaic plants (PV), two battery storage systems (BESS), and a connection to the public grid. This research shows a methodology to minimize the energy consumption of the public grid by taking advantage of the existing resources in the microgrid through the allocation of resources and demand management, for which a domotic system based on a z-wave protocol was implemented to monitor and control the loads. The initial state and the state after the implementation of the management equipment were compared, and the reduction of electricity consumption in the public grid was quantified, which was around 63%.
Numerical Simulation of Habitat Restoration for Floating Fish Eggs in the Upper Yangtze River Tributaries
Authors: Wang Pingyi , Zhang Haofeng , Li Jian , Tian Ye
Published: February 2024

The upper reaches of the Yangtze River not only serve as a crucial waterway in China’s southwestern region but also function as a conservation area for rare fish species. Recognizing the tendency of current navigation channel improvement projects to overlook the impact on aquatic habitats and the limitations of existing habitat assessment systems, this study specifically focuses on the bifurcation section of the upper Yangtze River. To address these issues, a two-dimensional mathematical model is established to simulate and validate various improvement schemes. An analysis of the flow conditions necessary for fish migration and spawning in this section is conducted, determining optimal flow rates and water levels during spawning and migration periods. A suitability assessment system for spawning and migration is then established, utilizing the four major Chinese carps as representative fish species for evaluation. Through a comprehensive analysis of the results, rational improvement schemes are identified. The findings underscore the importance of considering elevation of dam crest during the construction of sub-dams to regulate the navigation channel, particularly regarding its impact on fish habitats during the dry season. In this plan, the weighted available area of the spawning ground increased by 189,251 m2, 165,860 m2, 89,527 m2, 66,542 m2, and 47,182 m2 under five conditions. Additionally, the evaluation indexes PPA, HFI, and CQI showed increases of 5.011%, 4.176%, and 2.901%, respectively. Moreover, this study refines fish habitats based on their reproductive and living habits, thereby enhancing existing habitat assessment models.
Study on the Application of a Multi-Energy Complementary Distributed Energy System Integrating Waste Heat and Surplus Electricity for Hydrogen Production
Authors: Yu Shuai , Yang Yi , Chen Shuqin , Xing Haowei , Guo Yinan , Feng Weijia , Zhang Jianchao , Zhang Junhan
Published: February 2024

To improve the recovery of waste heat and avoid the problem of abandoning wind and solar energy, a multi-energy complementary distributed energy system (MECDES) is proposed, integrating waste heat and surplus electricity for hydrogen storage. The system comprises a combined cooling, heating, and power (CCHP) system with a gas engine (GE), solar and wind power generation, and miniaturized natural gas hydrogen production equipment (MNGHPE). In this novel system, the GE’s waste heat is recycled as water vapor for hydrogen production in the waste heat boiler, while surplus electricity from renewable sources powers the MNGHPE. A mathematical model was developed to simulate hydrogen production in three building types: offices, hotels, and hospitals. Simulation results demonstrate the system’s ability to store waste heat and surplus electricity as hydrogen, thereby providing economic benefit, energy savings, and carbon reduction. Compared with traditional energy supply methods, the integrated system achieves maximum energy savings and carbon emission reduction in office buildings, with an annual primary energy reduction rate of 49.42–85.10% and an annual carbon emission reduction rate of 34.88–47.00%. The hydrogen production’s profit rate is approximately 70%. If the produced hydrogen is supplied to building through a hydrogen fuel cell, the primary energy reduction rate is further decreased by 2.86–3.04%, and the carbon emission reduction rate is further decreased by 12.67–14.26%. This research solves the problem of waste heat and surplus energy in MECDESs by the method of hydrogen storage and system integration. The economic benefits, energy savings, and carbon reduction effects of different building types and different energy allocation scenarios were compared, as well as the profitability of hydrogen production and the factors affecting it. This has a positive technical guidance role for the practical application of MECDESs.
Study on the Coordinated Development of Tourism Industry–Regional Economy–Ecological Environment in the Yili River Valley
Authors: Zhao Xinyu , Sun Haojie , Hu Jiangling , Xie Yuxin , Zhao Pengkai , Sui Qingqing
Published: February 2024

This study aims to clarify the relationship among the three systems of tourism industry, regional economy, and ecological environment in the Yili River Valley, which is essential for the sustainable development of the region. We explore the spatio-temporal evolution characteristics and influencing factors of the tourism–economy–ecosystem in the Yili River Valley using the center of gravity model, spatial mismatch index model, spatial variance model, and obstacle degree model, based on panel data from 2010 to 2019. The study shows that (1) the comprehensive development indices of the tourism industry, regional economy, and ecological environment in the Yili River Valley exhibit varying degrees of growth trends. Smaller increases are observed in ecological environment indices, while larger increases are found in regional economy and tourism industry indices. Both the regional economy and tourism industry indices share a strong correlation and similar development trends. (2) At the macro-regional scale, during the study period, the centers of gravity of the tourism industry, regional economy, and ecological environment in the Yili River Valley have consistently been separated from the spatial geometric center of the region. The degree of misalignment of the centers of gravity of the three systems as a whole has gradually reduced, indicating that the level of coordinated development of the region has continuously improved. (3) At the micro-regional scale, during the study period, most of the spatial misalignment indices of the Yili River Valley regions showed positive and negative fluctuations, and the types of misalignment varied to different degrees. However, the gap in spatial misalignment indices between different regions gradually narrowed, and the divergent characteristics of “east-west concentration, north-south dispersion” were gradually broken, with the overall indices showing a balanced development trend. (4) The spatial dislocation index of each region in the Yili River Valley is affected by multiple systems and factors, and the overall spatial dislocation factors are mainly the comprehensive utilization rate of general solid waste, exhaust gas emission, dust removal amount, etc., which mostly originate from the ecological environment system.
Using Lean in Deconstruction Projects for Maximising the Reuse of Materials: A Canadian Case Study
Authors: Boukherroub Tasseda , Nganmi Tchakoutio Audrey , Drapeau Nathalie
Published: February 2024

The construction sector is considered a major consumer of virgin materials and a contributor to waste generation. Therefore, it is essential to rethink current waste management practices, for example, by applying circular economy principles to building demolition, such as deconstruction. Deconstruction involves dismantling a building with the aim of maintaining the highest possible value for its materials and maximising their recovery potential. This study aims to guide the construction sector towards deconstruction to support its efforts to transform itself toward a more sustainable industry. It focuses on a regional case study in the province of Québec (Canada), presenting five buildings to be deconstructed. First, this study presents the outcomes of our analysis of the current situation. Second, it identifies the issues and obstacles encountered and proposes avenues to improve the current process based on solutions identified in the literature and the recommendations of the manager, the contractor involved in the deconstruction project, as well as experts in the construction industry. Finally, it proposes an improved deconstruction process. Our research approach is inspired from Lean thinking and follows the Action Research methodology.
Blockchain Traceability Adoption in Low-Carbon Supply Chains: An Evolutionary Game Analysis
Authors: Zhang Chen , Xu Yaoqun , Zheng Yi
Published: February 2024

Blockchain technology has brought innovation to supply chain management, particularly in managing carbon emissions in the manufacturing sector. However, there is a research gap regarding the policy tools and the role of local governments in implementing blockchain technology to achieve carbon emissions traceability. Additionally, the strategic relationships and policy implications resulting from the implementation of blockchain technology are not examined systematically. An effective method for examining the strategies used in interactions between supply chain stakeholders and governments is evolutionary game theory, or EGT. This paper employs mathematical modelling and MATLAB 2016 software simulation to examine the decision-making process of manufacturing companies when considering implementing blockchain technology traceability. Specifically, the subjects in the model include product manufacturers (PM), product suppliers (PS), and local governments (LGs). The aim is to examine the decision-making behavior of carbon traceability participants in blockchain technology. This paper analyses the most effective blockchain-based traceability strategies for low-carbon supply chain members under a variety of scenarios by modifying the parameters. The findings suggest the following: (1) Manufacturers and suppliers need to manage the cost of blockchain traceability, collaborate to create an environmentally friendly product certification system, and improve brand image. (2) Local governments should set up efficient reward and punishment systems to incentivize supply chain stakeholders to engage in the blockchain traceability system. The aforementioned discoveries furnish policymakers with guidance to encourage the implementation of blockchain-based carbon footprint traceability technology, thereby establishing a transparent carbon footprint traceability framework across the entire supply chain.
Sustainable Ultrasound-Assisted Extraction and Encapsulation of Phenolic Compounds from Sacha Inchi Shell for Future Application
Authors: Mehta Shilka Kumari , Jafari Saeid , Shiekh Khursheed Ahmad , Gulzar Saqib , Assatarakul Kitipong
Published: February 2024

Sacha inchi shell (SIS), an underutilized by-product of sacha inchi oil processing, is a rich source of phenolic compounds. In this study, ultrasound-assisted extraction (UAE) was optimized by response surface methodology (RSM) with a Box–Behnken design to investigate the effects of time (15–25 min), temperature (25–45 °C), and ethanol concentration (40–80%) on the total phenolic content (TPC), total flavonoid content (TFC) and antioxidant activity by DPPH assay of the obtained extracts. The maximum TPC was at 15 min, 45 °C and 60%, TFC at 25 min, 45 °C and 60% and DPPH at 15 min, 35 °C and 80%. The optimized condition selected for encapsulation purposes was at 25 min, 35 °C and 80% ethanol concentration. RSM analysis showed that all models analyzed for all three assays were significant at 95% confidence. The SIS extract had a greater inhibitory zone against Escherichia coli measuring 15.34 mm at a concentration of 30 µg/mL than Staphylococcus aureus among the samples. The spray-dried microcapsules using different combinations of gum arabic and maltodextrin (GMM 1 and GMM2) resulted in a proper encapsulation layer and a smoother surface and shape obtained at 1000× magnification. Also, GMM 1 and GMM2 had particle sizes ranging from 2.95 ± 0.02 to 27.73 ± 0.38 and from 5.20 ± 0.01 to 29.30 ± 0.42 µm, respectively. The microcapsules were in the acceptable ranges for moisture content (<5%) and water activity (<0.6). It has been concluded that SIS extract showed high antioxidant and antimicrobial properties and its encapsulation could be further used in food and nutraceutical formulations.
Comment on Senthilkumaran et al. Bilateral Simultaneous Optic Neuritis Following Envenomations by Indian Cobra and Common Krait. Toxins 2022, 14, 805
Authors: Jalink Maarten B.
Published: February 2024

It is with interest that I read the case report by Senthilkumaran et al [...]
Fast-Track Discovery of SARS-CoV-2-Neutralizing Antibodies from Human B Cells by Direct Functional Screening
Authors: Hillenbrand Matthias , Esslinger Christoph , Seidenberg Jemima , Weber Marcel , Zingg Andreas , Townsend Catherine , Eicher Barbara , Rutkauskaite Justina , Riese Peggy , Guzman Carlos A. , Fischer Karsten , Schmitt Simone
Published: February 2024

As the COVID-19 pandemic revealed, rapid development of vaccines and therapeutic antibodies are crucial to guarantee a quick return to the status quo of society. In early 2020, we deployed our droplet microfluidic single-cell-based platform DROPZYLLA® for the generation of cognate antibody repertoires of convalescent COVID-19 donors. Discovery of SARS-CoV-2-specific antibodies was performed upon display of antibodies on the surface of HEK293T cells by antigen-specific sorting using binding to the SARS-CoV-2 spike and absence of binding to huACE2 as the sort criteria. This efficiently yielded antibodies within 3–6 weeks, of which up to 100% were neutralizing. One of these, MTX-COVAB, displaying low picomolar neutralization IC50 of SARS-CoV-2 and with a neutralization potency on par with the Regeneron antibodies, was selected for GMP manufacturing and clinical development in June 2020. MTX-COVAB showed strong efficacy in vivo and neutralized all identified clinically relevant variants of SARS-CoV-2 at the time of its selection. MTX-COVAB completed GMP manufacturing by the end of 2020, but clinical development was stopped when the Omicron variant emerged, a variant that proved to be detrimental to all monoclonal antibodies already approved. The present study describes the capabilities of the DROPZYLLA® platform to identify antibodies of high virus-neutralizing capacity rapidly and directly.
Effect of Freeze–Thaw Cycles on Microstructure and Hydraulic Characteristics of Claystone: A Case Study of Slope Stability from Open-Pit Mines in Wet Regions
Authors: Liu Zhifang , Xiang Yang , Liu Wei , Huang Jianyu , Liang Zhu , Zhang Qinghua , Li Wenlong
Published: February 2024

The action of freeze–thaw (F–T) cycles of claystone exerts a profound impact on the slope stability of open-pit mines in water-rich regions. Microstructural changes are observed as a crucial factor in determining the hydraulic characteristics and mechanical behaviors of claystone. The present work integrates a micro-X-ray computed tomography (Micro-CT) scanner, equipped with image processing and three-dimensional (3D) reconstruction capabilities, employed to observe the microstructure of claystone under varying numbers of F–T cycles (0, 10, 20, 30, and 50). Furthermore, seepage numerical simulations based on Micro-CT measurements are conducted to evaluate the hydraulic characteristics. Through meticulous microscopic observation and mechanical analysis, the damage mechanism induced by F–T cycles is revealed and the evolutionary characteristics are analyzed. The two-dimensional (2D) images of 3D reconstructed models unveil the gradual initiation propagation and coalescence of an intricate fissuring network in claystone during the F–T cycles. As the number of F–T cycles increases from 0 to 50, the 3D porosity exhibits exponential growth. Additionally, the influence of F–T cycles substantially enhances the connectivity of fissures. The seepage numerical simulations demonstrate that the evolutionary progression of fissures substantially augments the number of flow paths and enhances permeability. The increase in permeability follows an exponential trend, reflecting the distribution and evolution of fissures under F–T cycles. The impact on permeability arises from a combination of micromechanical properties and the microstructure of claystones. The present research tries to elucidate the microscopic evolution of fissures and their corresponding hydraulic properties in water-saturated claystone, offering significant insights for investigating the slope stability of open-pit mines in regions.
Effect of Combined Application of Lanthanum-Based Capping Material and Biochemical Oxidant on Control of Internal Phosphorus
Authors: Liu Yvlu , Geng Bing , Wu Guoyi , Si Jingyi , Liu Yi , Ning Dongliang , Lin Juan
Published: February 2024

In situ capping and biochemical oxidation are two of the most commonly used methods for internal phosphorus (P) control, but there are few studies on the combined use of these two methods. In this study, two lanthanum (La)-based materials, La-modified bentonite (LMB) and the La-modified attapulgite and chitosan composite (LMA&C), were combined with calcium nitrate (CN) to investigate the effect on sediment P control. Results showed that SRP removal rates by LMB+CN and LMA&C+CN were much higher than that by LMB, LMA&C and CN alone. LMB+CN and LMA&C+CN decreased DGT-labile P flux both in overlying water and surface 65 mm sediment, while LMB and LMA&C had an effect only on overlying water and surface 10~40 mm sediment, and CN was effective only on sediments. LMB and LMA&C transformed NH4Cl-P, BD-P, NaOH-SRP and NaOH-NRP in surface 20 mm sediment to HCl-P and Residual-P on day 60. CN transformed NaOH-SRP and NaOH-NRP to BD-P, resulting in the increase in NH4Cl-P. LMB+CN and LMA&C+CN sequestered P in the surface 20 mm mainly as HCl-P and Residual-P, and mainly as BD-P in −20~−60 mm. Results indicate that the combination of capping by La-based material and oxidation by CN is a promising method for sediment P control.
Treatment Wetland Plant Harvests as a Tool for Soil Phosphorus Reduction in North Central US Agricultural Watersheds
Authors: Alsadi Nadia , Lenhart Christian
Published: February 2024

Agricultural watersheds in the North Central United States have been intensively farmed for decades with widespread application of fertilizer and extensive tilling practices. Soil phosphorus built up in sediments over time as a result of these practices may be released under anaerobic conditions, such as flood events. These floods are increasing in frequency and intensity due to climate change, leading to downstream water-quality concerns. Edge-of-field best management practices, including constructed treatment wetlands, provide a natural buffer for excess phosphorus runoff, but may only be a temporary solution if soil becomes oversaturated with phosphorus over extended periods of time. Preventing wetlands from becoming sources of phosphorus to water bodies may be essential for management in future years when considering impacts from climate change. This research assesses how wetland plant harvesting can reduce soil phosphorus accumulation (measured as Olsen phosphorus) in edge-of-field treatment wetlands, thereby preventing these systems from becoming phosphorus sources and ensuring the longevity of water-quality benefits from these systems. Using several 380 L controlled wetland mesocosm experiments in 2018–2019, we assessed above-ground plant material (S. tabernaemontani and B. fluviatilis) and soil Olsen P through the growing season and after harvest. We observed a reduction in soil phosphorus from wetland plant harvesting between 1–50% over one year, with a mean reduction of 7.9 mg/kg. B. fluviatilis initially contained higher P concentration early in the season (0.82% P content) compared to S. tabernaemontani (0.76% P), but S. tabernaemontani retained higher P later in the season (0.3% P content) compared to B. fluviatilis (0.25%). Time of season may significantly impact plant P removal potential, including accessibility of treatment wetland sites. While controlled mesocosm experiments may not always be applicable to real landscape-level management, this study highlights the potential for reductions in soil phosphorus and corresponding downstream phosphorus fluxes in edge-of-field treatment wetlands through plant harvest during the growing season. Plant harvesting can be used by land managers in edge-of-field treatment wetlands as an adaptation mechanism for shifting environmental conditions, such as increased heavy rainfall occurrences and flood events, that are exacerbated by climate change in this region.
The Temporal-Stability-Based Irrigation MAPping (TSIMAP) Method: A Virtuous Trade-Off between Accuracy, Flexibility, and Facility for End-Users
Authors: Dari Jacopo , Morbidelli Renato , Quintana-Seguí Pere , Brocca Luca
Published: February 2024

Remote sensing technology is an essential tool for tracking human-induced alterations on the water cycle, among which irrigation prevails. The possibility of obtaining detailed and accurate information on the actual irrigation extent through remote-sensing-based approaches is of paramount importance for water resources management. In this study, an update of the TSIMAP (Temporal-Stability-derived Irrigation MAPping) method, originally developed with satellite soil moisture as an input, is proposed. To demonstrate that the flexibility of the approach does not affect its main strength point (i.e., good accuracy in the face of high simplicity for users), a dual analysis relying on 1 km NDVI (Normalised Difference Vegetation Index) instead of soil moisture is carried out over the Ebro basin (Spain); data delivered by the Copernicus Global Land Service (CGLS) are used. First, results of this work are compared with outcomes from the method’s original implementation obtained over a focus area (denominated “Ebro_CATAR”) through satellite soil moisture. In the proposed configuration relying on NDVI, an overall accuracy (OA) up to 93% is found. Results highlight an increase in OA ranging from +2% to +6% depending on the validation strategy with respect to the TSIMAP implementation relying on soil moisture. Then, a basin-scale application is performed, providing performances still satisfactory (OA = 75%) notwithstanding a higher degree of heterogeneity.
Spatial Distribution and Relationship between Slope Micro-Topography Changes and Soil Aggregate Stability under Rainfall Conditions
Authors: Zhang Shangxuan , Li Long , Zhu Zhizhuo , Zhang Peng
Published: February 2024

Natural rainfall affects the stability of soil aggregates by the kinetic energy of the rain changing the morphological characteristics of slope micro-topographic factors. Although the relationship between the stability of soil aggregates and micro-topography is not very significant at the slope scale, there are also rules to be found. This study aims to explore the relationship between slope micro-topography and aggregate stability, and to observe the spatial distribution of aggregate stability after water erosion. In this study, a digital elevation model of slope micro-topography was established by using a three-dimensional laser scanner to observe the slope erosion changes after rainfall events and clarify the spatial changes of soil aggregate stability and its relationship with slope micro-topography by combining geostatistics and generalized additive model (GAM). The results showed that the area of serious water erosion in the lower part of the slope accounted for 38.67% of the slope, and the micro-topography index of the slope changed obviously after rainfall, with the slope increasing by 3.1%, the surface roughness increasing by 5.34%, the surface cutting degree increasing by 26.67%, and the plane curvature decreasing by 61.7%. In addition, the GAM model was used to fit the multivariate variables. The results revealed that the slope and surface roughness were the key factors affecting the stability of water-stable aggregate. The slope and surface roughness were negatively correlated with the stability of water-stable aggregates.
Electro-Assisted Fe3+/Persulfate System for the Degradation of Bezafibrate in Water: Kinetics, Degradation Mechanism, and Toxicity
Authors: Gao Yuqiong , Li Kexuan , Zhong Xiangmei , Ning Han
Published: February 2024

In this study, an electrochemical-assisted ferric ion/persulfate (EC/Fe3+/PS) process was proposed to degrade bezafibrate (BZF), a widespread hypolipidemic drug, in water. By promoting the reduction of Fe3+ to Fe2+ at the cathode, the introduction of an electric field successfully overcomes the limitation of non-regenerable Fe2+ inherent in Fe2+/PS systems, significantly improving the degradation efficiency of BZF. The predominant reactive species identified were •OH and SO4●−, with 1O2 also playing a role. Various key operational parameters were investigated and optimized, including the current intensity, Fe3+ dosage, PS concentration, and initial pH. With a current intensity of 50 mA, an Fe3+ concentration of 50 μΜ, a PS dosage of 50 μM, and an initial pH of 3, the degradation efficiency of BZF demonstrated an exceptional achievement, reaching up to 98.8% within 30 min. The influence of anions and humic acid was also assessed. An LC/TOF/MS analysis revealed four major degradation pathways of BZF: hydroxylation, amino bond cleavage, dechlorination, and fibrate chain removal. The acute and chronic toxicities of BZF and its degradation intermediates were then assessed using the ECOSAR program. These findings highlight the wide-ranging applications of the EC/Fe3+/PS system and its potential for remediating water contaminated with micropollutants.