bluuebunny/crossref_metadata_2025 huggingface dataset:
Differences in Chronic Low-Grade Inflammation and Metabolic Disturbances between VDR Genotypes in an Ethnically Homogenous Postmenopausal Female Population from Poland
Authors: Bohdanowicz-Pawlak Anna , Lwow Felicja
Published: June 2023

(1) Vitamin D deficiency and changes in the endocrine system may stimulate systemic inflammation. VDR expression and the vitamin D concentration decrease with age, which is important in postmenopausal women for whom estrogen deficiency causes rapid bone loss. This group is, moreover, particularly at risk of developing atherosclerosis and its adverse consequences, such as chronic inflammation. The aim of this study was to assess the differentiation by the VDR genotype of the risk factors for so-called chronic low-grade inflammation and metabolic disorders. (2) We studied the differences between the anthropometric, metabolic, and inflammation parameters of VDR genotypes for Apa-I, Bsm-I, Fok-I, and Taq-I in a sample of 321 women aged 50–60 from an ethnically homogeneous urban population in Poland. (3) The TT Taq-I genotype presented a significantly higher rate of insulin resistance (HOMA) and lower serum levels of adiponectin than the other two genotypes. The AA genotype of the Bsm-I polymorphism was associated with a more atherogenic serum profile and significantly higher LDL and LDL/HDL values and Castelli Index. (4) Chronic low-grade inflammation was associated with the TT Taq-I genotype and presented a higher rate of insulin resistance. The AA genotype of the Bsm-I polymorphism presented a more atherogenic serum lipid profile and, therefore, a higher risk of developing cardiovascular disease.
Biocomposite for Prolonged Release of Water-Soluble Drugs
Authors: Meirelles Lyghia M. A. , de Melo Barbosa Raquel , de Almeida Júnior Renato Ferreira , Machado Paula Renata Lima , Perioli Luana , Viseras César , Raffin Fernanda Nervo
Published: June 2023

This study aimed to develop a prolonged-release system based on palygorskite and chitosan, which are natural ingredients widely available, affordable, and accessible. The chosen model drug was ethambutol (ETB), a tuberculostatic drug with high aqueous solubility and hygroscopicity, which is incompatible with other drugs used in tuberculosis therapy. The composites loaded with ETB were obtained using different proportions of palygorskite and chitosan through the spray drying technique. The main physicochemical properties of the microparticles were determined using XRD, FTIR, thermal analysis, and SEM. Additionally, the release profile and biocompatibility of the microparticles were evaluated. As a result, the chitosan–palygorskite composites loaded with the model drug appeared as spherical microparticles. The drug underwent amorphization within the microparticles, with an encapsulation efficiency greater than 84%. Furthermore, the microparticles exhibited prolonged release, particularly after the addition of palygorskite. They demonstrated biocompatibility in an in vitro model, and their release profile was influenced by the proportion of inputs in the formulation. Therefore, incorporating ETB into this system offers improved stability for the administered product in the initial tuberculosis pharmacotherapy dose, minimizing its contact with other tuberculostatic agents in the treatment, as well as reducing its hygroscopicity.
Effect of Agricultural Biomass Residues on the Properties of Recycled Polypropylene/Polyethylene Composites
Authors: Ābele Agnese , Merijs-Meri Remo , Žiganova Madara , Iesalniece Zanda , Bochkov Ivan
Published: June 2023

The aim of the study was to assess the usefulness of agricultural biomass residues as reinforcement in recycled polymer matrices. In this study, recycled polypropylene and high-density polyethylene composites (rPPPE) filled with three types of biomass residues, sweet clover straws (SCS), buckwheat straws (BS) and rapeseed straws (RS), are presented. The effects of the fiber type and the fibers content on the rheological behavior, mechanical properties (including tensile, flexural and impact strength), thermal stability and moisture absorbance were determined, in addition to morphological analysis. It was revealed that the addition of SCS, BS or RS increased the materials’ stiffness and strength. The reinforcement effect increased as the loading of the fibers was increased, especially for BS composites in the flexural test. After the moisture absorbance test, it was found that the reinforcement effect slightly increased for the composites with 10% fibers but decreases with 40% fibers. The results highlight that the selected fibers are a feasible reinforcement for recycled polyolefin blend matrices.
Extending Applications of Generalizability Theory-Based Bifactor Model Designs
Authors: Vispoel Walter , Lee Hyeryung , Chen Tingting , Hong Hyeri
Published: June 2023

In recent years, researchers have described how to analyze generalizability theory (GT) based univariate, multivariate, and bifactor designs using structural equation models. However, within GT studies of bifactor models, variance components have been limited to those reflecting relative differences in scores for norm-referencing purposes, with only limited guidance provided for estimating key indices when making changes to measurement procedures. In this article, we demonstrate how to derive variance components for multi-facet GT-based bifactor model designs that represent both relative and absolute differences in scores for norm- or criterion-referencing purposes using scores from selected scales within the recently expanded form of the Big Five Inventory (BFI-2). We further develop and apply prophecy formulas for determining how changes in numbers of items, numbers of occasions, and universes of generalization affect a wide variety of indices instrumental in determining the best ways to change measurement procedures for specific purposes. These indices include coefficients representing score generalizability and dependability; scale viability and added value; and proportions of observed score variance attributable to general factor effects, group factor effects, and individual sources of measurement error. To enable readers to apply these techniques, we provide detailed formulas, code in R, and sample data for conducting all demonstrated analyses within this article.
Network Collaborative Pruning Method for Hyperspectral Image Classification Based on Evolutionary Multi-Task Optimization
Authors: Lei Yu , Wang Dayu , Yang Shenghui , Shi Jiao , Tian Dayong , Min Lingtong
Published: June 2023

Neural network models for hyperspectral images classification are complex and therefore difficult to deploy directly onto mobile platforms. Neural network model compression methods can effectively optimize the storage space and inference time of the model while maintaining the accuracy. Although automated pruning methods can avoid designing pruning rules, they face the problem of search efficiency when optimizing complex networks. In this paper, a network collaborative pruning method is proposed for hyperspectral image classification based on evolutionary multi-task optimization. The proposed method allows classification networks to perform the model pruning task on multiple hyperspectral images simultaneously. Knowledge (the important local sparse structure of the network) is automatically searched and updated by using knowledge transfer between different tasks. The self-adaptive knowledge transfer strategy based on historical information and dormancy mechanism is designed to avoid possible negative transfer and unnecessary consumption of computing resources. The pruned networks can achieve high classification accuracy on hyperspectral data with limited labeled samples. Experiments on multiple hyperspectral images show that the proposed method can effectively realize the compression of the network model and the classification of hyperspectral images.
Imprint of Mesoscale Eddies on Air-Sea Interaction in the Tropical Atlantic Ocean
Authors: Aguedjou Habib Micaël A. , Chaigneau Alexis , Dadou Isabelle , Morel Yves , Baloïtcha Ezinvi , Da-Allada Casimir Y.
Published: June 2023

This study investigates the effect of mesoscale eddies on air–sea heat and fresh water exchange in the tropical Atlantic Ocean (TAO) using 8 years of satellite altimetry data, combined with sea surface temperature (SST), latent and sensible heat fluxes (LHF and SHF), infrared fluxes (IRF) and precipitation (PR) data. Results indicate that approximately ∼40% of cyclonic eddies contribute to warm SST anomalies, and ∼40% of anticyclonic eddies contribute to cold SST anomalies. Eddies were found to play a role in the variability in LHF, SHF and IRF, contributing 10–35% of their total variability, with the largest contributions observed beneath the intertropical convergence zone (ITCZ) and frontal SST areas. Composite analysis of SST and heat flux anomalies over eddies suggested that the anomalies created through horizontal advection processes may not significantly impact the overall LHF, SHF and IRF over eddies, contrary to vertical processes. Despite a lack of clear correlation between heat flux and PR anomalies over eddies in the TAO, significant correlations were found beneath the ITCZ, suggesting that eddies may impact both heat fluxes and PR in the ITCZ region. This study provides an original contribution to the understanding of the impact of ocean mesoscale eddies on the atmosphere in the TAO.
Quantitative Assessment of Sea Surface Salinity Estimates Using a High-Frequency Radar in Ise Bay, Japan
Authors: Toguchi Yu , Fujii Satoshi
Published: June 2023

Changes in sea surface salinity (SSS) caused by the discharge of freshwater plumes from rivers affect the marine environment in estuaries; therefore, monitoring SSS is essential for understanding the changes in physical phenomena within coastal ecosystems induced by river plume discharge. Previous studies showed that salinity could be estimated using a very-high-frequency radar; however, this method was only validated over a short period and few qualitative evaluations were performed. Therefore, to verify quantitative assessments of SSS estimates for practical use, we estimated SSS using the Doppler spectrum of a 24.5-MHz phased-array high-frequency (HF) radar installed in Ise Bay, Japan, and data of approximately 1 year were used for verification. The radar-estimated SSS map was consistent with the velocity field and salinity distribution reported in previous studies. The root mean square error (RMSE) of the SSS estimate for 1-h radar data compared with in situ observations was 4.42 psu when the effect of wind on the received power was removed and 5.04 psu when it was not. For the daily (25-h) average, the RMSE when the effect of wind was considered was 3.32 psu. These results were considered sufficiently applicable in closed coastal areas such as Ise Bay, where the SSS decreases rapidly by 10 psu or more due to river flooding. The results revealed that the HF radar, which can continuously measure sea surface velocity and SSS with a high spatiotemporal resolution, can be a useful tool for providing a deeper understanding of the physical and environmental phenomena that are greatly affected by river water discharge.
A Disturbance Frequency Index in Earthquake Forecast Using Radio Occultation Data
Authors: Zhang Tao , Tan Guangyuan , Bai Weihua , Sun Yueqiang , Wang Yuhe , Luo Xiaotian , Song Hongqing , Sun Shuyu
Published: June 2023

Earthquake forecasting is the process of forecasting the time, location, and magnitude of an earthquake, hoping to gain some time to prepare to reduce the disasters caused by earthquakes. In this paper, the possible relationship between the maximum electron density, the corresponding critical frequency, and the occurrence of earthquakes is explored by means of radio occultation data based on mechanism analysis and actual earthquake-nearby data. A new disturbance frequency index is proposed in this paper as a novel method to help forecast earthquakes. Forecasting of the location and timing of earthquakes is based on the connection between proven new frequency distributions and earthquakes. The effectiveness of this index is verified by backtracking observation around the 2022 Ya’an earthquake. Using this index, occultation data can forecast the occurrence of earthquakes five days ahead of detection, which can help break the bottleneck in earthquake forecasting.
Algorithms and Predictors for Land Cover Classification of Polar Deserts: A Case Study Highlighting Challenges and Recommendations for Future Applications
Authors: Desjardins Émilie , Lai Sandra , Houle Laurent , Caron Alain , Thériault Véronique , Tam Andrew , Vézina François , Berteaux Dominique
Published: June 2023

The use of remote sensing for developing land cover maps in the Arctic has grown considerably in the last two decades, especially for monitoring the effects of climate change. The main challenge is to link information extracted from satellite imagery to ground covers due to the fine-scale spatial heterogeneity of Arctic ecosystems. There is currently no commonly accepted methodological scheme for high-latitude land cover mapping, but the use of remote sensing in Arctic ecosystem mapping would benefit from a coordinated sharing of lessons learned and best practices. Here, we aimed to produce a highly accurate land cover map of the surroundings of the Canadian Forces Station Alert, a polar desert on the northeastern tip of Ellesmere Island (Nunavut, Canada) by testing different predictors and classifiers. To account for the effect of the bare soil background and water limitations that are omnipresent at these latitudes, we included as predictors soil-adjusted vegetation indices and several hydrological predictors related to waterbodies and snowbanks. We compared the results obtained from an ensemble classifier based on a majority voting algorithm to eight commonly used classifiers. The distance to the nearest snowbank and soil-adjusted indices were the top predictors allowing the discrimination of land cover classes in our study area. The overall accuracy of the classifiers ranged between 75 and 88%, with the ensemble classifier also yielding a high accuracy (85%) and producing less bias than the individual classifiers. Some challenges remained, such as shadows created by boulders and snow covered by soil material. We provide recommendations for further improving classification methodology in the High Arctic, which is important for the monitoring of Arctic ecosystems exposed to ongoing polar amplification.
DAFCNN: A Dual-Channel Feature Extraction and Attention Feature Fusion Convolution Neural Network for SAR Image and MS Image Fusion
Authors: Luo Jiahao , Zhou Fang , Yang Jun , Xing Mengdao
Published: June 2023

In the field of image fusion, spatial detail blurring and color distortion appear in synthetic aperture radar (SAR) images and multispectral (MS) during the traditional fusion process due to the difference in sensor imaging mechanisms. To solve this problem, this paper proposes a fusion method for SAR images and MS images based on a convolutional neural network. In order to make use of the spatial information and different scale feature information of high-resolution SAR image, a dual-channel feature extraction module is constructed to obtain a SAR image feature map. In addition, different from the common direct addition strategy, an attention-based feature fusion module is designed to achieve spectral fidelity of the fused images. In order to obtain better spectral and spatial retention ability of the network, an unsupervised joint loss function is designed to train the network. In this paper, the Sentinel 1 SAR images and Landsat 8 MS images are used as datasets for experiments. The experimental results show that the proposed algorithm has better performance in quantitative and visual representation when compared with traditional fusion methods and deep learning algorithms.
Research on SUnet Winter Wheat Identification Method Based on GF-2
Authors: Zhou Ke , Zhang Zhengyan , Liu Le , Miao Ru , Yang Yang , Ren Tongcan , Yue Ming
Published: June 2023

Introduction: Winter wheat plays a crucial role in ensuring food security and sustainable agriculture. Accurate identification and recognition of winter wheat in remote sensing images are essential for monitoring crop growth and yield estimation. In recent years, attention-based convolutional neural networks have shown promising results in various image recognition tasks. Therefore, this study aims to explore the application of attention-based convolutional neural networks for winter wheat identification on GF-2 high-resolution images and propose improvements to enhance recognition accuracy. Method: This study built a multi-band winter wheat sample dataset based on GF-2 images. In order to highlight the characteristics of winter wheat, this study added two bands, NDVI and NDVIincrease, to the dataset and proposed a SUNet network model. In this study, the batch normalization layer was added to the basic structure of the UNet convolutional network to speed up network convergence and improve accuracy. In the jump phase, shuffle attention was added to the shallow features extracted from the coding structure for feature optimization and spliced with the deep features extracted by upsampling. The SUNet made the network pay more attention to the important features to improve winter wheat recognition accuracy. In order to overcome the sample imbalance problem, this study used the focus loss function instead of the traditional cross-entropy loss function. Result: The experimental data show that its mean intersection over union, overall classification accuracy, recall, F1 score and kappa coefficient are 0.9514, 0.9781, 0.9707, 0.9663 and 0.9501, respectively. The results of these evaluation indicators are better than those of other comparison methods. Compared with the UNet, the evaluation indicators have increased by 0.0253, 0.0118, 0.021, 0.0185, and 0.0272, respectively. Conclusion: The SUNet network can effectively improve winter wheat recognition accuracy in multi-band GF-2 images. Furthermore, with the support of a cloud platform, it can provide data guarantee and computing support for winter wheat information extraction.
A 94 GHz Pulse Doppler Solid-State Millimeter-Wave Cloud Radar
Authors: Lin Hai , Wang Jie , Chen Zhenhua , Ge Junxiang
Published: June 2023

A 94 GHz pulse Doppler solid-state millimeter-wave cloud radar (MMCR), Tianjian-II (TJ-II), has been developed. It reduces the size and cost using a solid-state power amplifier (SSPA) and a single antenna. This paper describes the system design, including hardware and signal processing components. Pulse compression, segmented pulse, and dual pulse repetition frequency (PRF) technologies are employed to overcome the limitations imposed by the low power of the SSPA and the high frequency of 94 GHz. The TJ-II also features a dual-polarization, high-gain antenna for linear depolarization ratio detection and a time-division receive channel to improve channel consistency and save on costs. To achieve high flexibility and low interference in signal transmission and reception, the TJ-II uses software-defined radio technology, including direct digital synthesis, digital downconversion, and bandpass sampling. A series of Doppler power spectrum processing methods are proposed for detecting weak cloud signals and improving scene adaptability.
Detection and Attribution of Changes in Terrestrial Water Storage across China: Climate Change versus Vegetation Greening
Authors: Kong Rui , Zhang Zengxin , Zhang Ying , Wang Yiming , Peng Zhenhua , Chen Xi , Xu Chong-Yu
Published: June 2023

Whether or not large-scale vegetation restoration will lead to a decrease in regional terrestrial water storage is a controversial topic. This study employed the Geodetector model, in conjunction with observed and satellite hydro-meteorological data, to detect the changes in terrestrial water storage anomaly (TWSA) and to identify the contributions of climate change and vegetation greening across China during the years 1982–2019. The results revealed that: (1) during the period of 1982–2019, TWSA showed a downward trend in about two thirds of the country, with significant declines in North China, southeast Tibet, and northwest Xinjiang, and an upward trend in the remaining third of the country, with significant increases mainly in the Qaidam Basin, the Yangtze River, and the Songhua River; (2) the positive correlation between normalized vegetation index (NDVI) and TWSA accounts for 48.64% of the total vegetation area across China. In addition, the response of vegetation greenness lags behind the TWSA and precipitation, and the lag time was shorter in arid and semi-arid regions dominated by grasslands, and longer in relatively humid regions dominated by forests and savannas; (3) furthermore, TWSAs decreased with the increase in NDVI and evapotranspiration (ET) in arid and semi-arid areas, and increased with the rise in NDVI and ET in the humid regions. The Geodetector model was used to detect the effects of climate, vegetation, and human factors on TWSA. It is worth mentioning that NDVI, precipitation, and ET were some of the main factors affecting TWSA. Therefore, it is essential to implement rational ecological engineering to mitigate climate change’s negative effects and maintain water resources’ sustainability in arid and semi-arid regions.
Sensor-Based Classification of Primary and Secondary Car Driver Activities Using Convolutional Neural Networks
Authors: Doniec Rafał , Konior Justyna , Sieciński Szymon , Piet Artur , Irshad Muhammad Tausif , Piaseczna Natalia , Hasan Md Abid , Li Frédéric , Nisar Muhammad Adeel , Grzegorzek Marcin
Published: June 2023

To drive safely, the driver must be aware of the surroundings, pay attention to the road traffic, and be ready to adapt to new circumstances. Most studies on driving safety focus on detecting anomalies in driver behavior and monitoring cognitive capabilities in drivers. In our study, we proposed a classifier for basic activities in driving a car, based on a similar approach that could be applied to the recognition of basic activities in daily life, that is, using electrooculographic (EOG) signals and a one-dimensional convolutional neural network (1D CNN). Our classifier achieved an accuracy of 80% for the 16 primary and secondary activities. The accuracy related to activities in driving, including crossroad, parking, roundabout, and secondary activities, was 97.9%, 96.8%, 97.4%, and 99.5%, respectively. The F1 score for secondary driving actions (0.99) was higher than for primary driving activities (0.93–0.94). Furthermore, using the same algorithm, it was possible to distinguish four activities related to activities of daily life that were secondary activities when driving a car.
Pre-Computing Batch Normalisation Parameters for Edge Devices on a Binarized Neural Network
Authors: Phipps Nicholas , Shang Jin-Jia , Teo Tee Hui , Wey I-Chyn
Published: June 2023

Binarized Neural Network (BNN) is a quantized Convolutional Neural Network (CNN), reducing the precision of network parameters for a much smaller model size. In BNNs, the Batch Normalisation (BN) layer is essential. When running BN on edge devices, floating point instructions take up a significant number of cycles to perform. This work leverages the fixed nature of a model during inference, to reduce the full-precision memory footprint by half. This was achieved by pre-computing the BN parameters prior to quantization. The proposed BNN was validated through modeling the network on the MNIST dataset. Compared to the traditional method of computation, the proposed BNN reduced the memory utilization by 63% at 860-bytes without any significant impact on accuracy. By pre-computing portions of the BN layer, the number of cycles required to compute is reduced to two cycles on an edge device.
Enabling the ActiGraph GT9X Link’s Idle Sleep Mode and Inertial Measurement Unit Settings Directly Impacts Data Acquisition
Authors: Coyle-Asbil Hannah J. , Habegger Janik , Oliver Michele , Vallis Lori Ann
Published: June 2023

The ActiGraph GT9X has been implemented in clinical trials to track physical activity and sleep. Given recent incidental findings from our laboratory, the overall aim of this study was to notify academic and clinical researchers of the idle sleep mode (ISM) and inertial measurement unit (IMU)’s interaction, as well as their subsequent effect on data acquisition. Investigations were undertaken using a hexapod robot to test the X, Y and Z sensing axes of the accelerometers. Seven GT9X were tested at frequencies ranging from 0.5 to 2 Hz. Testing was performed for three sets of setting parameters: Setting Parameter 1 (ISMONIMUON), Setting Parameter 2 (ISMOFFIMUON), Setting Parameter 3 (ISMONIMUOFF). The minimum, maximum and range of outputs were compared between the settings and frequencies. Findings indicated that Setting Parameters 1 and 2 were not significantly different, but both were significantly different from Setting Parameter 3. Upon inspection, it was discovered that the ISM was only active during Setting Parameter 3 testing, despite it being enabled in Setting Parameter 1. Researchers should be aware of this when conducting future research using the GT9X.
Improved Palladium Extraction from Spent Catalyst Using Ultrasound-Assisted Leaching and Sulfuric Acid–Sodium Chloride System
Authors: Wang Jinjiao , Zhu Xiaoping , Fan Jiale , Xue Ke , Ma Shengyu , Zhao Ruiming , Wu Hao , Gao Qin
Published: June 2023

This paper presents a process for efficiently recovering palladium (Pd) from spent Pd/Al2O3 catalysts used for hydrogenation reactions, using ultrasound-assisted leaching (UAL). A system composed of H2SO4 and NaCl was investigated under ultrasound-enhanced conditions and compared to regular leaching methods to demonstrate the superiority of UAL. Single-factor experiments were conducted to determine the optimal conditions for leaching, which included an ultrasound power of 200 W, a liquid–solid ratio of 5:1, a leaching time of 1 h, a leaching temperature of 60 °C, H2SO4 concentration of 60%, and 0.1 mol of NaCl. The leaching rate under these conditions was found to be 99%. Additionally, kinetic analysis of the UAL process showed that the apparent activation energy of the Pd leaching reaction was 28.7 kJ/mol, and it was found that Pd leaching from spent catalysts was controlled by diffusion. The tailings were analyzed by SEM, revealing that during ultrasonic leaching, the specific surface area of the spent catalyst increased, the mass transfer rate of the solution was accelerated, the passivation film on the surface of the spent catalyst was peeled off, and a new reaction interface was formed. This improved the leaching rate of Pd and provided a new approach to efficiently leach precious metals such as Pd from spent catalysts.
Reassessing Resettlement-Associated Poverty Induced by Water Conservancy Projects in China: Case Study of the “Yangtze to Huai River Inter-Basin” Water Diversion Project
Authors: Lu Yu , Shangguan Ziheng
Published: June 2023

The displacement and resettlement-associated poverty caused by water conservancy projects (WCP) is a worldwide issue. Re-settlers are often impoverished for extended periods due to loss, difficult re-establishment, and insufficient compensation. Addressing poverty has become a worldwide concern, and accurate measurements of poverty remain a fundamental issue. Before 2020, the Chinese government used the absolute income method to measure re-settler poverty. However, this method reflected neither the overall income gap nor potential benefits of social development and poverty alleviation policies. Therefore, we used the relative income and multidimensional methods alongside the absolute income poverty method to measure the poverty in recently resettled households. Based on survey data from over resettled 1000 households we conclude that: (1) The remaining poor measured by the absolute poverty line were mainly caused by serious diseases, disabilities and loss of labor ability, which means they have no ability to be lifted out of poverty except through the bottom line of local governments. As a result, the absolute poverty line loses its distinction to poverty. (2) Rural re-settlers were more resilient to forced majeure because land guarantees employment and food supply, allowing households to avoid secondary livelihood destruction. (3) Income derived measurement of re-settler poverty masks the benefits of poverty alleviation and other socioeconomic aid programs. A few households showed improvements in child school attendance, child mortality, nutrition, cooking fuel, asset ownership, and social insurance following resettlement. (4) To reduce the multidimensional gap, government aid programs should focus on years of schooling (including training), nutrition, household savings, and household labor force rather than simply providing monetary assistance. At the same time, we suggest that the government adopt a variety of compensation methods, such as: sharing the benefits of water conservancy projects, industrial support and improving the bottom line guarantee.
Land-Use Change Effects on Soil Erosion: The Case of Roman “Via Herculia” (Southern Italy)—Combining Historical Maps, Aerial Images and Soil Erosion Model
Authors: Minervino Amodio Antonio , Gioia Dario , Danese Maria , Masini Nicola , Sabia Canio Alfieri
Published: June 2023

Land use and land cover (LULC) strongly influence soil erosion/sediment yield, and predicting changes in soil erosion is an important management strategy. Tracing the Earth’s past also helps us better understand the future evolution of the landscape, but research using modern mapping capabilities is hampered by the scarcity of historical landscape information. To fill the data gap and provide an example of how historical maps might be used in land-use change research, we combined an old paper map based on the IT Military Topographical Institute (ITM), aerial photos, and orthophotos to derive land-use history and landscape dynamics at fine scales for a segment of the Roman route “Via Herculia” located in the north-western sector of the Basilicata Region, Italy. Three LULC scenarios were then analysed to represent land use in 1870, 1974, and 2013. Starting from such scenarios, we applied a soil erosion model (Unit Stream Power Eosion and Deposition—USPED) to understand how land-use change over time has modified the areas subject to erosion and deposition. The results show an increase in erosion (from 17% to 20% of the total area) and sediment deposition (from 15% to 19%) over the period 1870–1974. In contrast, over the period of 1974–2013, the results show a decrease in gross erosion (from 20% to 14% of the total area) and sediment deposition (from 19% to 13%).
Progress in Realizing the Value of Ecological Products in China and Its Practice in Shandong Province
Authors: Wang Kuifeng , Liu Paul , Sun Fengsheng , Wang Shengwen , Zhang Gong , Zhang Taiping , Chen Guodong , Liu Jinqiu , Wang Gangchao , Cao Songkun
Published: June 2023

Establishing a mechanism for realizing the value of ecological products is important for implementing the concept of an ecological society in China. It is a key means of acting upon the idea that green mountains and clear waters are as valuable as gold and silver, and it is a necessary requirement to promote sustainable green development and encourage harmonious coexistence between humans and nature. This article summarizes the connotations of ecological products, the accounting of ecological product value, and the progress made nationally and in Shandong province in promoting the mechanisms for realizing the value of ecological products. Based on the analysis of Shandong’s practice in various means of realizing ecological product value, such as the “forest chief system +”, “two mountain banks”, “mining ecological restoration”, “health tourism”, “ecological agriculture, culture, and tourism”, and “forest ecological compensation”, this article summarizes and proposes three types of ecological product value realization paths: government-led, government + market, and market paths. It also proposes four types of ecological product value realization modes: ecological resource indicators and equity exchanges, ecological governance and value enhancement, ecological industrial operations, and ecological protection compensation. Furthermore, this article puts forward targeted suggestions and methods for value realization in four areas: policy, technology, industry, and markets, providing an experiential reference for exploring diversified ecological product value realization in various regions of China.
A Methodology for Classifying Attractive Sources Related to Airport Birdstrike by Using Geospatial Tools
Authors: Trifilò Domenico , D’Urso Provvidenza Rita , Arcidiacono Claudia
Published: June 2023

The urban and rural environment around airport grounds, being an attractive site for wildlife, is subjected to special attention in relation to the risk of wildlife collision with aircrafts according to specific aviation norms. Therefore, investigation into significant attractive sources in airport surroundings is needed to contribute to ‘wildlife strike’ monitoring in order to activate efficient countermeasures for limitation and control in view of aviation safety while at the same time increasing wildlife protection. On this basis, the study was focused on attractive sites related to the birdstrike hazard in airport surroundings. The methodology described in this paper investigated the spatial distribution characteristics of bird strike influencing factors with an open-access approach to data handling. Remote sensing imagery and open-source GIS tools were utilised to apply suitability analysis to the surfaces involved, such as airport obstacle limitation surfaces, protected areas, vegetation, and water bodies. The methodology was applied to a case study of the airport of Catania, Italy. The results showed that application of geospatial tools to suitability analysis allowed for the identification of areas that have the greatest influence on the birdstrike hazard for aviation. This approach has made it possible to analyse these areas from the point of view of airport safety and the monitoring of ecological areas and corridors of high naturalistic value in order to protect them, providing a contribution toward sustainable management of the birstrike issue.
Energy Efficiency as a Foundational Technology Pillar for Industrial Decarbonization
Authors: Sundaramoorthy Senthil , Kamath Dipti , Nimbalkar Sachin , Price Christopher , Wenning Thomas , Cresko Joseph
Published: June 2023

The U.S. government aims to achieve net-zero greenhouse gas emissions by 2050 to reduce the severe impacts of climate change. The U.S. industrial sector will become a focal point for decarbonization since it accounts for 33% of the nation’s primary energy use and 30% of its energy-related CO2 emissions. Industrial emissions are also expected to increase by 15% through 2050, making the industrial sector a logical target for decarbonization efforts. Energy efficiency technology pathways provide low-cost, foundational routes to decarbonization that can be implemented immediately. Energy efficiency technology pathways, such as strategic energy management, system efficiency, smart manufacturing, material efficiency, and combined heat and power, are well established and would immediately reduce energy use and emissions. However, their role in the aggressive net-zero decarbonization pathway for the industrial sector is still unclear. This study aims to address energy efficiency pathways for decarbonization, and reviews studies related to these technologies for industrial decarbonization through 2050. This study identifies different strategies for the industrial sector in general and that are specific to six energy-intensive industries: iron and steel; chemical; food and beverage; petroleum refining; pulp and paper; and cement. Finally, a path toward the successful implementation of energy efficiency technologies is outlined.
The Agricultural Potential of a Region with Semi-Dry, Warm and Temperate Subhumid Climate Diversity through Agroecological Zoning
Authors: Castorena Edgar Vladimir Gutiérrez , Gómez Gustavo Andrés Ramírez , Solorio Carlos Alberto Ortíz
Published: June 2023

The sustainability of the natural resources used in agricultural production is essential to meet the future food needs of the population. It is necessary to understand the characteristics of climate and soil changes through agroclimatic zoning models, even with non-existent or limited climatic and edaphic databases, to avoid a decline in production. The objective of the study was to determine the accuracy of the Global Agroecological Zoning (GAEZ), ECOCROP and Papadakis models for major cereals, vegetables and fruit trees in the state of Nuevo León, Mexico, using the databases of climatic stations and soil profiles collected by INEGI with random sampling in the field. The model with the best projection was ECOCROP, which predicted 37,609 km2 of irrigated area for sorghum and 34,796 km2 for wheat, in addition to identifying by soil characteristics rainfed areas with higher suitability for beans measuring 8470 km2 and orange measuring 6175 km2 with zoning predictions based on field information. In conclusion, the thematic maps obtained with ECOCROP had an accuracy greater than 50% for more than half of the crops analyzed, making it the best method for the study area. Therefore, the food production decisions of the producers must be directed towards cereal crops based on the projected area; however, it is necessary to establish an updating program and generate edaphoclimatic databases, updating thematic soil and climate maps with models that support the projections verified in the field.
Physicochemical Parameters of Water and Its Implications on Avifauna and Habitat Quality
Authors: Mishra Arun Pratap , Kumar Sipu , Patra Rounak , Kumar Amit , Sahu Himanshu , Chandra Naveen , Pande Chaitanya B. , Alshehri Fahad
Published: June 2023

Wetland ecosystems are essential for maintaining biological diversity and are significant elements of the global landscape. However, the biodiversity of wetlands has been significantly reduced by more than 50% worldwide due to the rapid expansion of urban areas and other human activities. The aforementioned factors have resulted in drastic antagonistic effects on species composition, particularly aquatic avifauna. The decline in wetland avifauna, which can be attributed to changes in water quality that impact aquatic habitats, is a major concern. In this study, we evaluated the impact of physicochemical parameters on aquatic avifauna in India’s first Conservation Reserve, a Ramsar site and an Important Bird Area. Water samples were collected on a monthly basis across nine different sites and various parameters, such as temperature, electrical conductivity, pH, biological oxygen demand, dissolved oxygen, total dissolved solids and salinity, were analyzed for pre-monsoon and post-monsoon seasons, while point count surveys were conducted to assess species richness and the density of waterbirds. Our findings show a positive correlation of species density with water temperature (r = 0.57), total dissolved solids (r = 0.56) and dissolved oxygen (r = 0.6) for pre-monsoon season and a negative correlation for dissolved oxygen (r = −0.62) and biological oxygen demand (r = −0.69) for post-monsoon season. We suggest that a synergistic effect of pH, salinity, biological oxygen demand and total dissolved solids may affect aquatic bird populations in Asan Conservation Reserve. Poor water quality was observed in a few sampling sites, which may negatively affect the number and density of waterbirds present. The findings of this study emphasize the importance of water quality in wetland conservation, particularly for aquatic avifauna.
Analysis of the Coordination Effects and Influencing Factors of Transportation and Tourism Development in Shaanxi Region
Authors: Zhang Weidi , Wen Lei
Published: June 2023

With the accelerated growth of global tourism and the increasing availability of transport, the coordination and interaction between the tourism economy and transport have become a topic of great interest. This study seeks to analyse the coordination effects and influencing factors of Shaanxi’s tourism economy and transportation, thereby contributing to the sustainable development of the region’s tourism economy. To achieve this, we develop a tourism economy–transportation evaluation index system and employ the system coupled with the coordination model and entropy method to conduct a thorough analysis. The research spans over the years 2003–2021. According to the findings of this study, the integration and coordination of tourism economy–transportation and tourism development in Shaanxi are exhibiting an upward development trend. Over the years, the degree of coupling coordination has progressed through the stages of uncoordinated development, transformational development, and coordinated development, with the recent epidemic upheaval resulting in a primary level of coordination. In addition, the transport system has a significant impact on the coupled and coordinated development of the tourism economy–, with the size of the transport base and transport efficiency serving as the driving factors and transport pressure and epidemic shocks serving as significant influencing factors. Due to the fluctuations of the global pandemic, the coordination of the tourism system declines sharply in 2020, but recovers in 2021 as the pandemic progressively stabilises. Through this study, we can gain a better understanding of the relationship between the tourism economy and transport in Shaanxi and devise strategies and policies to support the development of sustainable transport and tourism systems.
#ThisIsSustainable: The Effect of Disclosures in Influencer Marketing for Sustainable Food
Authors: De Keyzer Freya
Published: June 2023

Sustainable food consumption is seen by many as a significant challenge. Green marketers are trying to combine newer formats of marketing communications, such as influencer marketing, to change consumer’s behaviour to a more environmentally sustainable food choice. Especially, adolescents and young adults have been found to be relevant target groups. In this study, based on persuasion knowledge and reactance theory, we examined the moderating role of disclosures on the effectiveness of food influencer posts, both for sustainable and non-sustainable products. In an online 2 (non-sustainable vs. sustainable food) × 2 (no disclosure vs. disclosure) experiment (N = 332) this study finds that, surprisingly, sustainable food posts are more often recognized as advertising compared to non-sustainable food posts. Nevertheless, a disclosure increases the likelihood that a non-sustainable food post would be recognized as advertising compared to no disclosure. Finally, the recognition of selling intent decreases source credibility and ultimately decreases attitude towards the post and product, as well as liking intention.
Re-Thinking Ecological Flow in Romania: A Sustainable Approach to Water Management for a Healthier Environment
Authors: Ilinca Cornel , Anghel Cristian Gabriel
Published: June 2023

Water resources and aquatic ecosystems are facing significant threats due to unsustainable water management practices. To address this challenge in Romania, a sustainable approach to water management is necessary, re-thinking ecological flow. This article proposes a re-thinking of the current approach to ecological flow in Romania by advocating for a more holistic and integrated approach considering environmental factors. The objective of the article was to present a methodology for the establishment of ecological flow that took into account the natural variability of flows. Four ecological flow values related to flood, high-water, medium-water, and low-water hydrological regimes were defined. To establish them, the duration curve of average daily flows was used in conjunction with hydromorphological and biological indicators. The proposed methodology was applied and compared to the existing methodology for the Uz river developed with hydropower use. The methodology represents a transition from the anthropocentric perspective to the sustainability perspective. The proposed methodology is easy to apply, with rigorously defined hydrological, hydraulic, and biological criteria. This research was conducted within the Hydrotechnical Faculty to refine the Romanian legislation regarding the improvement of the ecological status of all rivers.
Improving CO2 Absorption Using Artificial Intelligence and Modern Optimization for a Sustainable Environment
Authors: Nassef Ahmed M.
Published: June 2023

One of the essential factors in maintaining environmental sustainability is to reduce the harmful effects of carbon dioxide (CO2) emissions. This can be performed either by reducing the emissions themselves or capturing and storing the emitted CO2. This work studies the solubility of carbon dioxide in the capturing solvent, which plays a crucial role in the effectiveness and cost-efficiency of carbon capture and storage (CCS). Therefore, the study aims to enhance the solubility of CO2 by integrating artificial intelligence (AI) and modern optimization. Accordingly, this study consists of two consecutive stages. In the first stage, an adaptive neuro-fuzzy inference system (ANFIS) model as an AI tool was developed based on experimental data. The mol fraction was targeted as the model’s output in terms of three operating parameters; the concentration of tetrabutylphosphonium methanesulfonate [TBP][MeSO3], temperature, and pressure of CO2. The operating ranges are (2–20 wt%), (30–60 °C), and (2–30 bar), respectively. Based on the statistical measures of the root mean squared error (RMSE) and the predicted R2, the ANFIS model outperforms the traditional analysis of variance (ANOVA) modeling technique, where the resulting values were found to be 0.126 and 0.9758 for the entire samples, respectively. In the second stage, an improved grey wolf optimizer (IGWO) was utilized to determine the optimal operating parameters that increase the solubility of CO2. The optimal values of the three operating parameters that improve the CO2 solubility were found to be 3.0933 wt%, 40.5 °C, and 30 bar, respectively. With these optimal values, the collaboration between the ANFIS and IGWO produced an increase of 13.4% in the mol fraction compared to the experimental data and the response surface methodology. To demonstrate the efficacy of IGWO, the obtained results were compared to the results of four competitive optimization techniques. The comparison showed that the IGWO demonstrates superior performance. Overall, this study provided a cost-efficient approach based on AI and modern optimization to enhance CO2 solubility in CCS.
Social and Environmental Sustainability, Workers’ Well-Being, and Affective Organizational Commitment in Palm Oil Industries
Authors: E-Vahdati Sahar , Noor Nor Azila Mohd , Mah Pei Yew , Chuah Francis , Md Isa Filzah
Published: June 2023

This paper examines the relationship between social and environmental sustainability and workers’ well-being as well as the mediation role of affective organizational commitment for those relationships through social exchange and stakeholder theories. A questionnaire was used to collect data from 112 workers employed in palm oil plantations in Malaysia. Structural equation modeling was then applied to examine the hypotheses. Findings show that social and environmental sustainability positively relates to workers’ well-being. We also found that affective commitment positively mediates social and environmental sustainability relationships with workers’ well-being. Our research findings have practical implications for various stakeholders, such as investors, policymakers, and managers in the palm oil industry. Our results highlight the importance of addressing the well-being of workers and the sustainability factors in palm oil plantations. This study suggests a widened perspective on sustainability factors and well-being which allows professionals to evaluate and enhance sustainability across their operations in a more comprehensive manner.