bluuebunny/crossref_metadata_2025 huggingface dataset:
Newspaper Leaders as Moral Exhortation: Understanding the Rhetoric of Civil Religion in Colonial Australia
Authors: Melleuish Greg , Stephen Chavura
Published: March 2023

This article argues that the leading article, or leader, of a newspaper played a role in the ‘secular’ society of colonial Australia not unlike that of the sermon in the religious sphere. One of its primary objectives was moral exhortation to encourage Australian colonists to follow a path that would enable the colony to fulfil providence and create an appropriate moral order. Their celebration of the British political order was a form of civil theology that matched the more dogmatic theology to be found in church sermons. This similarity was also assisted by the fact that a significant number of clergy either edited newspapers or wrote for them. This article considers several expressions of this civil theology, and then concentrates on the Rev John West who edited the Sydney Morning Herald and who used his leading articles to castigate his fellow colonists for their failure to live up to the ideals of their British political heritage. He was particularly harsh on the workings of colonial democracy which led him into conflict with another cleric, the Rev John Dunmore Lang.
Sites of Solitude: Situating the Wilderness of Nature in Wei-Jin Dark Learning and Emerson
Authors: Coles Benjamin
Published: March 2023

For Daoism, the wilderness of nature beyond human society has often been viewed as a site for eremitic retreat in spiritual solitude, a realm where an individual can transcend the limits of social existence. While this tradition flourished in the early medieval Wei-Jin period, Daoism-inspired Dark Learning thinkers of the time also explored ways in which such a realm of solitude could be attained and enjoyed without the necessity of leaving behind the mundane world, an endeavor that has clear parallels with the function of solitude in Emerson’s Transcendentalism. This paper focuses on three sites where both Emerson and Dark Learning thinkers located such access to solitude: aesthetic appreciation of nature, metaphysical speculation, and authentic social relationships. In both Emerson and Dark Learning, the universal implications of metaphysical speculation provided a path by which the solitude and independence attainable in the wilderness of nature could be connected to individuals in social life, providing a foundation for ethics outside of traditional authority that led both Emerson and Dark Learning to face similar criticisms from more conservative contemporaries.
Aseismic Creep, Coseismic Slip, and Postseismic Relaxation on Faults in Volcanic Areas: The Case of Ischia Island
Authors: Pino Nicola Alessandro , Carlino Stefano , Beccaro Lisa , De Martino Prospero
Published: March 2023

We performed a joined multitemporal and multiscale analysis of ground vertical movements around the main seismogenic source of Ischia island (Southern Italy) that, during historical and recent time, generated the most catastrophic earthquakes on the island, in its northern sector (Casamicciola fault). In particular, we considered InSAR (2015–2019) and ground-levelling data (1987–2010), attempting to better define the source that caused the recent 2017 earthquake and interpret its occurrence in the framework of a long-term behavior of the fault responsible for the major historical earthquakes in Casamicciola. Our results unambiguously constrain the location and the kinematics of the 2017 rupture and further confirm the presence of a relatively large sliding area west of the 2017 surface break. Overall, the studied seismogenic fault reveals a complex dynamic, moving differentially and aseismically in the pre- and post-seismic event, in response to the long-term subsidence of the central sector of the island, dominated by Mt. Epomeo. The fault segment that slipped coseismically also is evidence of post-seismic viscous relaxation. The long-term differential vertical movement on the apparently creeping eastern sector of the Casamicciola fault provides an estimate of the slip rate occurring on the fault (0.82 mm/y−1). The analysis of the time of occurrence and the magnitude of the known historical earthquakes reveals that this rate is consistent with the recurrence of the earthquakes that occurred during at least the past three centuries and suggests that the time to the next seismic event at Casamicciola might be a few decades. More generally, our findings provide evidence of the link between subsidence and earthquakes in volcanic areas indicating, in this case, a high hazard for the island of Ischia. Results might be also useful for characterizing capable faulting in similar volcano-tectonic settings worldwide.
A General Paradigm for Retrieving Soil Moisture and Surface Temperature from Passive Microwave Remote Sensing Data Based on Artificial Intelligence
Authors: Mao Kebiao , Wang Han , Shi Jiancheng , Heggy Essam , Wu Shengli , Bateni Sayed M. , Du Guoming
Published: March 2023

Soil moisture (SM) and land surface temperature (LST) are entangled, and the retrieval of one of them requires a priori specification of the other one. Due to insufficient observational information, retrieval of LST and SM from passive microwave remote sensing data is often ill-posed, and the retrieval accuracy needs to be improved. In this study, a novel fully-coupled paradigm is developed to robustly retrieve SM and LST from passive microwave data, which integrates deep learning, physical methods, and statistical methods. The key condition of the general paradigm proposed by us is that the output parameters of deep learning can be uniquely determined by the input parameters theoretically through a certain mathematical equation. Firstly, the physical method is deduced based on the energy radiation balance equation. The nine unknowns require the brightness temperatures of nine channels to construct nine equations, and the solutions of the physical method equations are obtained by model simulation. Based on the derivation of the physical method, the solution of the statistical method is constructed using multi-source data. Secondly, the solutions of physical and statistical methods constitute the training and test data of deep learning, which is used to obtain the solution curve of physical and statistical methods. The retrieval accuracy of LST and SM is greatly improved by smartly utilizing the mutual prior knowledge of SM and LST and cross iterative optimization calculations. Finally, validation indicates that the mean absolute error of the retrieved SM and LST data are 0.027 m3/m3 and 1.38 K, respectively, at an incidence angle of 0–65°. A model-data-knowledge-driven and deep learning method can overcome the shortcomings of traditional methods and provide a paradigm for retrieval of other geophysical variables. The proposed paradigm not only has physical meaning, but also makes deep learning physically interpretable, which is a milestone in the retrieval of geophysical remote sensing parameters based on artificial intelligence technology.
A Novel Distance Estimation Method for Near-Field Synthetic Aperture Interferometric Radiometer
Authors: Hu Hao , Zhu Dong , Hu Fei
Published: March 2023

The visibility samples generated by the synthetic aperture interferometric radiometer (SAIR) under near-field observation conditions contain information about the distance from the target to the instrument. This requires a precise understanding of the target–instrument distance to guarantee imaging quality in near-field SAIR applications. In this paper, we introduce a novel distance estimate approach for near-field SAIR systems, which achieves satisfactory imaging performance in the absence of prior information on target–instrument distance. First, we reformulate the signal model of near-field SAIR from the fractional Fourier transform (FRFT) perspective. This formulation ties the distance that is variable to the visibility function in a straightforward manner, offering an efficient solution for image reconstruction in near-field SAIR. Subsequently, we present an iterative strategy for target–instrument distance estimation based on simulated annealing (SA). In each iteration, the modified average gradient (MAG) of images reconstructed within the FRFT framework is evaluated, and based on the Metropolis criterion, the estimated target–instrument distance is optimally updated iteratively. Finally, the validity and effectiveness of the proposed distance estimation method for near-field SAIR imaging systems are demonstrated through numerical simulation and real experiments.
Skillful Seasonal Prediction of Typhoon Track Density Using Deep Learning
Authors: Feng Zhihao , Lv Shuo , Sun Yuan , Feng Xiangbo , Zhai Panmao , Lin Yanluan , Shen Yixuan , Zhong Wei
Published: March 2023

Tropical cyclones (TCs) seriously threaten the safety of human life and property especially when approaching a coast or making landfall. Robust, long-lead predictions are valuable for managing policy responses. However, despite decades of efforts, seasonal prediction of TCs remains a challenge. Here, we introduce a deep-learning prediction model to make skillful seasonal prediction of TC track density in the Western North Pacific (WNP) during the typhoon season, with a lead time of up to four months. To overcome the limited availability of observational data, we use TC tracks from CMIP5 and CMIP6 climate models as the training data, followed by a transfer-learning method to train a fully convolutional neural network named SeaUnet. Through the deep-learning process (i.e., heat map analysis), SeaUnet identifies physically based precursors. We show that SeaUnet has a good performance for typhoon distribution, outperforming state-of-the-art dynamic systems. The success of SeaUnet indicates its potential for operational use.
Hybrid Volcanic Episodes within the Orientale Basin, Moon
Authors: Patel Shreekumari Mukeshbhai , Harish  , Patel Deep , Solanki Paras M. , El-Maarry Mohamed Ramy
Published: March 2023

Basalts from Mare Orientale are representative of lunar flood volcanism, which sheds light on the lunar farside’s thermal and volcanic past. We use Chandrayaan’s Moon Mineralogy Mapper data to examine the spectral and chemical makeup of the volcanic units located in the Orientale basin; the analysis specifically focuses on three formations: Mare Orientale, Lacus Veris, and Lacus Autumni. The main assemblage in these basaltic units consists of calcic augite and ferroaugite. Pyroxenes in the Orientale volcanic units have an average chemical composition of En35.53 Fs34.11 Wo30.35. The trend in the composition of pigeonites and augites suggests that the magma was fractionated as it crystallized. The pyroxene quadrilateral plot’s distinct chemical trends indicate that the Orientale Basin underwent a number of volcanic eruptions from heterogeneous magma sources during the Imbrium to Eratosthenian period.
High-Performance Detection of Exosomes Based on Synergistic Amplification of Amino-Functionalized Fe3O4 Nanoparticles and Two-Dimensional MXene Nanosheets
Authors: Zhuang Linlin , You Qiannan , Su Xue , Chang Zhimin , Ge Mingfeng , Mei Qian , Yang Li , Dong Wenfei , Li Li
Published: March 2023

Exosomes derived from cancer cells have been recognized as a promising biomarker for minimally invasive liquid biopsy. Herein, a novel sandwich-type biosensor was fabricated for highly sensitive detection of exosomes. Amino-functionalized Fe3O4 nanoparticles were synthesized as a sensing interface with a large surface area and rapid enrichment capacity, while two-dimensional MXene nanosheets were used as signal amplifiers with excellent electrical properties. Specifically, CD63 aptamer attached Fe3O4 nanoprobes capture the target exosomes. MXene nanosheets modified with epithelial cell adhesion molecule (EpCAM) aptamer were tethered on the electrode surface to enhance the quantification of exosomes captured with the detection of remaining protein sites. With such a design, the proposed biosensor showed a wide linear range from 102 particles μL−1 to 107 particles μL−1 for sensing 4T1 exosomes, with a low detection limit of 43 particles μL−1. In addition, this sensing platform can determine four different tumor cell types (4T1, Hela, HepG2, and A549) using surface proteins corresponding to aptamers 1 and 2 (CD63 and EpCAM) and showcases good specificity in serum samples. These preliminary results demonstrate the feasibility of establishing a sensitive, accurate, and inexpensive electrochemical sensor for detecting exosome concentrations and species. Moreover, they provide a significant reference for exosome applications in clinical settings, such as liquid biopsy and early cancer diagnosis.
Design of Digital-Twin Human-Machine Interface Sensor with Intelligent Finger Gesture Recognition
Authors: Mo Dong-Han , Tien Chuen-Lin , Yeh Yu-Ling , Guo Yi-Ru , Lin Chern-Sheng , Chen Chih-Chin , Chang Che-Ming
Published: March 2023

In this study, the design of a Digital-twin human-machine interface sensor (DT-HMIS) is proposed. This is a digital-twin sensor (DT-Sensor) that can meet the demands of human-machine automation collaboration in Industry 5.0. The DT-HMIS allows users/patients to add, modify, delete, query, and restore their previously memorized DT finger gesture mapping model and programmable logic controller (PLC) logic program, enabling the operation or access of the programmable controller input-output (I/O) interface and achieving the extended limb collaboration capability of users/patients. The system has two main functions: the first is gesture-encoded virtual manipulation, which indirectly accesses the PLC through the DT mapping model to complete control of electronic peripherals for extension-limbs ability by executing logic control program instructions. The second is gesture-based virtual manipulation to help non-verbal individuals create special verbal sentences through gesture commands to improve their expression ability. The design method uses primitive image processing and eight-way dual-bit signal processing algorithms to capture the movement of human finger gestures and convert them into digital signals. The system service maps control instructions by observing the digital signals of the DT-HMIS and drives motion control through mechatronics integration or speech synthesis feedback to express the operation requirements of inconvenient work or complex handheld physical tools. Based on the human-machine interface sensor of DT computer vision, it can reflect the user’s command status without the need for additional wearable devices and promote interaction with the virtual world. When used for patients, the system ensures that the user’s virtual control is mapped to physical device control, providing the convenience of independent operation while reducing caregiver fatigue. This study shows that the recognition accuracy can reach 99%, demonstrating practicality and application prospects. In future applications, users/patients can interact virtually with other peripheral devices through the DT-HMIS to meet their own interaction needs and promote industry progress.
Graph Convolutional Network Using Adaptive Neighborhood Laplacian Matrix for Hyperspectral Images with Application to Rice Seed Image Classification
Authors: Orozco Jairo , Manian Vidya , Alfaro Estefania , Walia Harkamal , Dhatt Balpreet K.
Published: March 2023

Graph convolutional neural network architectures combine feature extraction and convolutional layers for hyperspectral image classification. An adaptive neighborhood aggregation method based on statistical variance integrating the spatial information along with the spectral signature of the pixels is proposed for improving graph convolutional network classification of hyperspectral images. The spatial-spectral information is integrated into the adjacency matrix and processed by a single-layer graph convolutional network. The algorithm employs an adaptive neighborhood selection criteria conditioned by the class it belongs to. Compared to fixed window-based feature extraction, this method proves effective in capturing the spectral and spatial features with variable pixel neighborhood sizes. The experimental results from the Indian Pines, Houston University, and Botswana Hyperion hyperspectral image datasets show that the proposed AN-GCN can significantly improve classification accuracy. For example, the overall accuracy for Houston University data increases from 81.71% (MiniGCN) to 97.88% (AN-GCN). Furthermore, the AN-GCN can classify hyperspectral images of rice seeds exposed to high day and night temperatures, proving its efficacy in discriminating the seeds under increased ambient temperature treatments.
Chained Deep Learning Using Generalized Cross-Entropy for Multiple Annotators Classification
Authors: Triana-Martinez Jenniffer Carolina , Gil-González Julian , Fernandez-Gallego Jose A. , Álvarez-Meza Andrés Marino , Castellanos-Dominguez Cesar German
Published: March 2023

Supervised learning requires the accurate labeling of instances, usually provided by an expert. Crowdsourcing platforms offer a practical and cost-effective alternative for large datasets when individual annotation is impractical. In addition, these platforms gather labels from multiple labelers. Still, traditional multiple-annotator methods must account for the varying levels of expertise and the noise introduced by unreliable outputs, resulting in decreased performance. In addition, they assume a homogeneous behavior of the labelers across the input feature space, and independence constraints are imposed on outputs. We propose a Generalized Cross-Entropy-based framework using Chained Deep Learning (GCECDL) to code each annotator’s non-stationary patterns regarding the input space while preserving the inter-dependencies among experts through a chained deep learning approach. Experimental results devoted to multiple-annotator classification tasks on several well-known datasets demonstrate that our GCECDL can achieve robust predictive properties, outperforming state-of-the-art algorithms by combining the power of deep learning with a noise-robust loss function to deal with noisy labels. Moreover, network self-regularization is achieved by estimating each labeler’s reliability within the chained approach. Lastly, visual inspection and relevance analysis experiments are conducted to reveal the non-stationary coding of our method. In a nutshell, GCEDL weights reliable labelers as a function of each input sample and achieves suitable discrimination performance with preserved interpretability regarding each annotator’s trustworthiness estimation.
Aqueous Two-Phase Systems Based on Cationic and Anionic Surfactants Mixture for Rapid Extraction and Colorimetric Determination of Synthetic Food Dyes
Authors: Smirnova Svetlana V. , Apyari Vladimir V.
Published: March 2023

In this study, aqueous two-phase systems (ATPSs) containing a cationic and anionic surfactants mixture were used for the preconcentration of the synthetic food dyes Allura Red AC, Azorubine, Sunset Yellow, Tartrazine, and Fast Green FCF. A rapid, simple, low cost, affordable, and environmentally friendly methodology based on microextraction in ATPSs, followed by spectrophotometric/colorimetric determination of the dyes, is proposed. The ATPSs are formed in mixtures of benzethonium chloride (BztCl) and sodium N-lauroylsarcosinate (NaLS) or sodium dihexylsulfosuccinate (NaDHSS) under the molar ratio close to equimolar at the total surfactant concentration of 0.01–0.20 M. The density, viscosity, polarity, and water content in the surfactant-rich phases at an equimolar ratio BztCl:NaA were determined. The effects of pH, total surfactant concentration, dye concentration, and time of extraction/centrifugation were investigated, and the optimum conditions for the quantitative extraction of dyes were established. The smartphone-based colorimetric determination was employed directly in the extract without separating the aqueous phase. The analytical performance (calibration linearity, precision, limits of detection and quantification, reproducibility, and preconcentration factor) and comparison of the spectrophotometric and smartphone-based colorimetric determination of dyes were evaluated. The method was applied to the determination of dyes in food samples and food-processing industrial wastewater.
An Experimental Method for Bio-Signal Denoising Using Unconventional Sensors
Authors: Aviles-Espinosa Rodrigo , Dore Henry , Rendon-Morales Elizabeth
Published: March 2023

In bio-signal denoising, current methods reported in the literature consider purely simulated environments, requiring high computational powers and signal processing algorithms that may introduce signal distortion. To achieve an efficient noise reduction, such methods require previous knowledge of the noise signals or to have certain periodicity and stability, making the noise estimation difficult to predict. In this paper, we solve these challenges through the development of an experimental method applied to bio-signal denoising using a combined approach. This is based on the implementation of unconventional electric field sensors used for creating a noise replica required to obtain the ideal Wiener filter transfer function and achieve further noise reduction. This work aims to investigate the suitability of the proposed approach for real-time noise reduction affecting bio-signal recordings. The experimental evaluation presented here considers two scenarios: (a) human bio-signals trials including electrocardiogram, electromyogram and electrooculogram; and (b) bio-signal recordings from the MIT-MIH arrhythmia database. The performance of the proposed method is evaluated using qualitative criteria (i.e., power spectral density) and quantitative criteria (i.e., signal-to-noise ratio and mean square error) followed by a comparison between the proposed methodology and state of the art denoising methods. The results indicate that the combined approach proposed in this paper can be used for noise reduction in electrocardiogram, electromyogram and electrooculogram signals, achieving noise attenuation levels of 26.4 dB, 21.2 dB and 40.8 dB, respectively.
Effect of Polymer Hydrophobicity in the Performance of Hybrid Gel Gas Sensors for E-Noses
Authors: Oliveira Ana , Costa Henrique , Ramou Efthymia , Palma Susana , Roque Ana
Published: March 2023

Relative humidity (RH) is a common interferent in chemical gas sensors, influencing their baselines and sensitivity, which can limit the performance of e-nose systems. Tuning the composition of the sensing materials is a possible strategy to control the impact of RH in gas sensors. Hybrid gel materials used as gas sensors contain self-assembled droplets of ionic liquid and liquid crystal molecules encapsulated in a polymeric matrix. In this work, we assessed the effect of the matrix hydrophobic properties in the performance of hybrid gel materials for VOC sensing in humid conditions (50% RH). We used two different polymers, the hydrophobic PDMS and the hydrophilic bovine gelatin, as polymeric matrices in hybrid gel materials containing imidazolium-based ionic liquids, [BMIM][Cl] and [BMIM][DCA], and the thermotropic liquid crystal 5CB. Better accuracy of VOC prediction is obtained for the hybrid gels composed of a PDMS matrix combined with the [BMIM][Cl] ionic liquid, and the use of this hydrophobic matrix reduces the effect of humidity on the sensing performance when compared to the gelatin counterpart. VOCs interact with all the moieties of the hybrid gel multicomponent system; thus, VOC correct classification depends not only on the polymeric matrix used, but also on the IL selected, which seems to be key to achieve VOCs discrimination at 50% RH. Thus, hybrid gels’ tunable formulation offers the potential for designing complementary sensors for e-nose systems operable under different RH conditions.
An Approach of Vibration Compensation for Atomic Gravimeter under Complex Vibration Environment
Authors: Che Hao , Li An , Zhou Zhu , Gong Wenbin , Ma Jinxiu , Qin Fangjun
Published: March 2023

Atomic gravimeter has been more frequently applied under complex and dynamic environments, but its measurement accuracy is seriously hampered by vibration-induced noise. In this case, vibration compensation provides a way to enhance the accuracy of gravity measurements by correcting the phase noise that resulted from the vibration of a Raman reflector, and improving the fitting of an interference fringe. An accurate estimation of the transfer function of vibration between the Raman reflector and the sensor plays a significant role in optimizing the effect of vibration compensation. For this reason, a vibration compensation approach was explored based on EO (equilibrium optimizer) for estimating the transfer function simplified model of a Raman reflector, and it was used to correct the interference fringe of an atomic gravimeter. The test results revealed that this approach greatly restored the actual vibration of the Raman reflector in a complex vibration environment. With a vibration compensation algorithm, it achieved the correction and fitting of the original interference fringe. In general, it dramatically reduced the RMSE (root mean square error) at the time of fitting and significantly improved the residual error in the gravity measurement. Compared with other conventional algorithms, such as GA (genetic algorithm) and PSO (particle swarm optimization), this approach realized a faster convergence and better optimization, so as to ensure more accurate gravity measurements. The study of this vibration compensation approach could provide a reference for the application of an atomic gravimeter in a wider and more complex environment.
Mixotrophy of Algae: More Algal Biomass and More Biofertilization for Plants
Authors: El Semary Nermin , Abd El-Sattar Amira Mohamed , Ahmed Eman Zakaria , Aldayel Munirah
Published: March 2023

Background: The use of algae as biofertilizers is fast-spreading in order to meet the excessive demands for agricultural products. To achieve this, enough algal biomass needs to be supplied year-round. Hence, algal nutritional components must be optimized through mixotrophic conditions. Materials and methods: Two algal isolates, namely, Phormidium sp. and Synechocystis sp. were tested for their ability to produce mixotrophic growth using different supplementations including molasses, aqueous Lepidium sativum, Trigonella foenum graecum seed extract and liquorice root extract, as well as acetate salt solution. The algae that showed highest growth under optimized mixotrophic conditions was further used in cantaloupe seed growth experiments. GC-MS was also carried out on the biomass of Phormidium on one of the fractions of extract using solvent system to reveal some dominant novel bioactive compounds in algal biomass. Results: The sugarcane molasses significantly enhanced the growth of the two algal strains, followed by Lepidium sativum extract only in case of Phormidium sp. Therefore, it was used in subsequent experiments. All growth parameters for that algae were significantly enhanced by the addition of these nutritional sources with molasses being the best supplement. The Phormidium sp. was rich in its content of chlorophyll, proteins, sugars as well as some novel bioactive compounds as revealed by GC–MS. The germination percentage of seeds treated with Phormidium sp. showed a significant increase over that of control. The different growth-related metabolites of total soluble proteins, total soluble sugars and all photosynthetic pigment contents of the seedlings were all significantly increased using this algal treatment. Discussion: The sugarcane molasses was superior in enhancing the algal growth due to its rich content not only of sugars but also of minerals and nitrogenous compounds. The use of aqueous extracts of seeds of Lepidium sativum enhanced growth significantly more than that of the control set as seeds are rich in proteins, omega-3 fatty acids, phytochemicals and other essential nutrients. In growth experiments carried out on cantaloupe seeds, there was a significant increase in germination percentage as well as all growth parameters due to the rich nutritional content of Phormidium sp. Conclusion: Mixotrophic growth achieved better algal biomass production than autotrophy in the case of Phormidium sp. The use of cheap resources such as sugarcane molasses, which is the waste from the sugar industry, as well as the common herb extract of Lepidium sativum, is a cost-effective approach. The use of this mixotrophically grown blue-green alga as a biofertilizer significantly enhanced plant growth and seed germination, indicating the usefulness of this eco-friendly agricultural strategy for achieving both food security and environmental sustainability.
Evaluation of Different Potassium Management Options under Prevailing Dry and Wet Seasons in Puddled, Transplanted Rice
Authors: Mohapatra Suchismita , Rout Kumbha Karna , Khanda Chandramani , Mishra Amit , Yadav Sudhir , Padbhushan Rajeev , Mishra Ajay Kumar , Sharma Sheetal
Published: March 2023

The present field experiment was conducted in both dry season (DS) and wet season (WS) from 2014–2015 to evaluate the influence of different potassium (K) management options (graded doses of inorganic K fertilizer alone and combined with foliar and straw incorporation) on the rice yield, nutrient uptake, and soil K balance under puddled, transplanted rice in acidic soil. The results showed that rice yields were higher under WS as compared to the DS crop. Among treatments, K40 + Kspray, i.e., the combination of inorganic K fertilizer (40 kg K2O ha−1) along with a foliar spray of K (1% KNO3) at the panicle initiation stage, produced the highest grain yield in both seasons; however, it was on par with treatments K80, i.e., the highest dose of inorganic K fertilizer (80 kg K2O ha−1) alone, and K30 + Kstraw i.e., integrated use of inorganic K fertilizer (30 kg K2O ha−1) and straw (3 t ha−1, 45 kg K2O ha−1). Application of 80 kg K2O ha−1 through inorganic fertilizer alone had the maximum K uptake at the harvest stage in both seasons. DS rice had a higher K/N and K/P ratio than the WS. The treatments applied with inorganic K fertilizers, either soil or foliar applications, had negative K balance in both seasons; however, treatments applied with organic sources of K, i.e., rice straw alone or integrated with inorganic K fertilizers, had positive K balances in the soil. Therefore, this study shows that the integrated use of inorganic K fertilizer and 3 t ha−1 rice straw (K30 + Kstraw) can be a recommended option for a better K management strategy for crop yields and soil sustainability in acid soils. However, in terms of greenhouse gas (GHG) estimation, incremental doses of soil-applied K fertilizer along with straw aggravate the GHGs emission in the rice–rice cropping system, and among all treatments, K40 + Kspray is the promising treatment which requires intensive investigation for drawing an overall conclusion.
Evaluation of Carbon Emission and Carbon Contribution Capacity Based on the Beijing–Tianjin–Hebei Region of China
Authors: Wang Junling , Qin Lihong , Chu Hanfang
Published: March 2023

In 2020, during the 75th United Nations General Assembly, China proposed the goal of “achieving a carbon peak by 2030 and achieving carbon neutrality by 2060”. The Beijing–Tianjin–Hebei region is the largest carbon emission metropolitan area in China. Its energy consumption and carbon emission status means the Beijing–Tianjin–Hebei region shoulders the important task of low-carbon transformation. Only by achieving a “carbon peak” and “carbon neutrality” can the economy of the Beijing–Tianjin–Hebei region be sustainable. Based on this, we analyzed and comprehensively evaluated the complete ability of the Beijing–Tianjin–Hebei region to achieve carbon neutrality in 2008–2020, that is, carbon achievement ability, status, and intensity of energy consumption and carbon emissions based on the CRITIC weighting method. The results show that the energy consumption and carbon emission capacity of the Beijing–Tianjin–Hebei region have basically formed a step difference. On this basis, the evaluation of carbon contribution capacity also shows that Hebei Province, as a weak link in the coordinated development of the Beijing–Tianjin–Hebei region, bears the main responsibility of improving carbon contribution capacity and thus achieving the goal of carbon neutrality. This research study suggests that intra-regional cooperation should be strengthened to achieve coordinated development. At the end of the paper, policy suggestions for regional cooperation are given from four aspects: government, industry, low-carbon technology, and regional carbon sinks.
Industry 4.0 Technologies for Sustainable Asset Life Cycle Management
Authors: Jasiulewicz-Kaczmarek Małgorzata , Antosz Katarzyna , Zhang Chao , Ivanov Vitalii
Published: March 2023

Asset life cycle management is not a new concept for industries [...]
Enhancing Drought Tolerance in Wheat Cultivars through Nano-ZnO Priming by Improving Leaf Pigments and Antioxidant Activity
Authors: Abbas Syed Farhat , Bukhari Muhammad Adnan , Raza Muhammad Aown Sammar , Abbasi Ghulam Hassan , Ahmad Zahoor , Alqahtani Mashael Daghash , Almutairi Khalid F. , Abd_Allah Elsayed Fathi , Iqbal Muhammad Aamir
Published: March 2023

Climate change, global warming, stagnant productivity of wheat and food security concerns owing to frequent spells of drought stress (DS) have necessitated finding biologically viable drought-mitigation strategies. A trial was conducted to test two promising wheat cultivars (Ujala-16 and Zincol-16) that were subjected to pre-sowing priming treatments with different doses of ZnO nanoparticles (NPs = 40, 80, 120 and 160 ppm) under 50% and 100% field capacity (FC) conditions. The ZnO NPs were prepared with a co-precipitation method and characterized through X-ray diffraction (XRD) and with a scanning electron microscope (SEM). For comparison purposes, untreated seeds were sown as the control treatment. The response variables included botanical traits (lengths, fresh and dry wrights of root and shoot), chlorophyll (a, b and total) contents, antioxidant and proline contents and nutrients status of wheat cultivars. The results showed that DS significantly decreased all traits of wheat cultivars, while ZnO NPs, especially the 120 ppm dose, remained superior by increasing all botanical traits at 100% FC. In addition, ZnO NPs increased the chlorophyll a (1.73 mg/g FW in Ujala-16 and 1.75 mg/g FW in Zincole-16) b (0.70 mg/g FW in Ujala-16 and 0.71 mg/g FW in Zincole-16) and total chlorophyll content (2.43 mg/g FW in Ujala-16 and 2.46 mg/g FW in Zincole-16) by improving the activity of antioxidant and proline content. Moreover, plant nutrients such as Ca, Mg, Fe, N, P, K, and Zn contents were increased by ZnO NPs, especially in the Zincol-16 cultivar. To summarize, Zincol-16 remains superior to Ujala-16, while ZnO NPs (120 ppm dose under 100% FC) increases the growth and mineral contents of both wheat varieties. Thus, this combination might be recommended to wheat growers after testing further in-depth evaluation of more doses of ZnO NPs.
Seismic Signal Characteristics and Numerical Modeling Analysis of the Xinmo Landslide
Authors: Yang Longwei , Xu Yangqing , Wang Luqi , Jiang Qiangqiang
Published: March 2023

Due to the high elevation and huge potential energy of high-level landslides, they are extremely destructive and have prominent kinetic-hazard effects. Studying the kinetic-hazard effects of high-level landslides is very important for landslide risk prevention and control. In this paper, we focus on the high-level landslide that occurred in Xinmo on 24 June 2017. The research is carried out based on a field geological survey, seismic signal analysis, and the discrete element method. Through ensemble empirical mode decomposition (EEMD) and Fourier transformation, it is found that the seismic signals of the Xinmo landslide are mainly located at low frequencies of 0–10 Hz, and the dominant frequency range is 2–8 Hz. In addition, the signal time-frequency analysis and numerical simulation calculation results reveal that the average movement distance of the sliding body was about 2750 m, and the average movement speed was about 22.9 m/s. The movement process can be divided into four main stages: rapid start, impact loading, fragmentation and migration, and scattered accumulation stages. We also provide corresponding suggestions for the zoning of high-level landslide geological hazards.
Climate and Land-Use Change Impacts on Flood Hazards in the Mono River Catchment of Benin and Togo
Authors: Houngue Nina Rholan , Almoradie Adrian Delos Santos , Thiam Sophie , Komi Kossi , Adounkpè Julien G. , Begedou Komi , Evers Mariele
Published: March 2023

Flooding is prominent in West Africa, and is expected to be exacerbated, due to global climate and land-use changes. This study assessed the impacts of future climate and land-use changes on flood hazards in the Mono river catchment area of Benin and Togo. Climate scenarios from the representative concentration pathways, RCP 4.5 and RCP 8.5, and land-use projection at the horizon of 2070 were used for runoff simulation at the Athiémé outlet, and flood mapping in the lower Mono river basin. The planned Adjarala dam was also simulated, to evaluate its potential impact. The Soil and Water Assessment Tool (SWAT) was used to investigate the impact of the projected changes on runoff, while the flood-water extent was simulated using the two-dimensional TELEMAC-2D model. TELEMAC-2D was validated with satellite observation and in a participatory way with local stakeholders. SWAT showed good performance during the calibration (KGE = 0.83) and validation (KGE = 0.68) steps. Results show an increase in the magnitude of flood extremes under future climate- and land-use-change scenarios. Events of 10-year return periods during 1987–2010 are expected to become 2-year return-period events under the climate- and land-use-change scenarios considered. The planned Adjarala dam showed potentials for extreme-peak and flood-extent reduction. However, flow-duration curves revealed that the discharge of the river during low-flow periods may also be reduced if the Adjarala dam is built. Adaptation measures as well as sustainable land-use and dam-management options should be identified, to alleviate the impacts of the projected changes.
The Effect of Responsible Tourism Perception on Place Attachment and Support for Sustainable Tourism Development: The Moderator Role of Environmental Awareness
Authors: Aytekin Arif , Keles Huseyin , Uslu Fatih , Keles Ali , Yayla Ozgur , Tarinc Abdullah , Ergun Gozde Seval
Published: March 2023

In this study, the effect of local people’s perceptions regarding responsible tourism on place attachment and the moderator role of environmental awareness in the effect of place attachment on support for sustainable tourism development has been determined. The research was conducted on local people in a sample of Antalya Manavgat, one of the most important tourism destinations in Turkey. The data were obtained through convenience sampling method, and the analysis was carried out with 482 questionnaires. The AMOS program was used to test the hypothetical model developed within the context of the research, and the Process macro (model 1) was preferred to determine the moderator effect. As a result of the evaluation, it has been found that the sub-dimensions of economic, social, and environmental perception positively affect the place attachment of local people, while the cultural perception sub-dimension has no effect. The effect of place attachment on support for sustainable tourism development is another finding of the study. Moreover, the moderator role of environmental awareness in the effect of place attachment on support for sustainable tourism development has also been determined.
Green Practices in Mega Development Projects of China–Pakistan Economic Corridor
Authors: Ullah Shakir , Barykin Sergey , Jianfu Ma , Saifuddin Taher , Khan Mohammed Arshad , Kazaryan Ruben
Published: March 2023

This research aimed to investigate the green practices in the mega construction project of the China–Pakistan Economic Corridor (CPEC). Over recent years, there has been an increasing need for adopting and implementing more green and sustainable practices, leading to national and international sustainable and green environmental agendas. To address the issue, green project practices were considered an independent variable comprising green design, procurement, and construction. The dependent variables were environmental performance and economic performance. Primary data were collected from respondents working on the CPEC project. A representative sample of 276 respondents was used. The analysis was conducted using PLS-SEM. The results indicated that green design significantly influences economic performance, green procurement has a positive and significant effect on environmental performance, and green construction has a positive and significant impact on both environmental and economic and financial performance. The research showed that construction management at CPEC should adopt all facets of green project practices together, reducing negative environmental effects, increasing environmental benefits, and improving long-term economic performance in the area.
Advanced Dance Choreography System Using Bidirectional LSTMs
Authors: Yoo Hanha , Sung Yunsick
Published: March 2023

Recently, the craze of K-POP contents is promoting the development of Korea’s cultural and artistic industries. In particular, with the development of various K-POP contents, including dance, as well as the popularity of K-POP online due to the non-face-to-face social phenomenon of the Coronavirus Disease 2019 (COVID-19) era, interest in Korean dance and song has increased. Research on dance Artificial Intelligent (AI), such as artificial intelligence in a virtual environment, deepfake AI that transforms dancers into other people, and creative choreography AI that creates new dances by combining dance and music, is being actively conducted. Recently, the dance creative craze that creates new choreography is in the spotlight. Creative choreography AI technology requires the motions of various dancers to prepare a dance cover. This process causes problems, such as expensive input source datasets and the cost of switching to the target source to be used in the model. There is a problem in that different motions between various dance genres must be considered when converting. To solve this problem, it is necessary to promote creative choreography systems in a new direction while saving costs by enabling creative choreography without the use of expensive motion capture devices and minimizing the manpower of dancers according to consideration of various genres. This paper proposes a system in a virtual environment for automatically generating continuous K-POP creative choreography by deriving postures and gestures based on bidirectional long-short term memory (Bi-LSTM). K-POP dance videos and dance videos are collected in advance as input. Considering a dance video for defining a posture, users who want a choreography, a 3D dance character in the source movie, a new choreography is performed with Bi-LSTM and applied. For learning, considering creativity and popularity at the same time, the next motion is evaluated and selected with probability. If the proposed method is used, the effort for dataset collection can be reduced, and it is possible to provide an intensive AI research environment that generates creative choreography from various existing online dance videos.
On the Viability of Diagrams and Drawings as System Requirements
Authors: Kolligs Jason , Thomas Lawrence Dale
Published: March 2023

Requirement expression media is an overlooked consideration in requirements innovation. The path to including media other than natural language requirement sentences begins with determining the viability of media to be used as requirement expressions in systems engineering. This research uses the INCOSE characteristics for individual requirements and sets of requirements as a basis for an assessment of the sufficiency of model diagrams and engineering drawings to express requirements. A critical review of high-impact sources is used to develop characteristic lists for natural language requirement sentences and for model diagrams and engineering drawings. A comparative analysis of the characteristic lists for requirement sentences, model diagrams, and engineering drawings shows that each have the same fundamental characteristics and the differences are based on the ability of the media to represent abstraction. The contribution of this research is the establishment of model diagrams and engineering drawings as viable alternatives to natural language sentences for system engineering requirements expressions.
Exopolysaccharides-Mediated ZnO Nanoparticles for the Treatment of Aquatic Diseases in Freshwater Fish Oreochromis mossambicus
Authors: Abinaya Muthukumar , Shanthi Sathappan , Palmy Jesudasan , Al-Ghanim Khalid , Govindarajan Marimuthu , Vaseeharan Baskaralingam
Published: March 2023

Bacterial fish disease outbreaks are a key concern for aquaculture. Complementary feed additives such as immunostimulants can serve as an ideal solution for disease prevention. Herein, we scrutinized the efficacy of exopolysaccharides (EPSs) from probiotic Bacillus licheniformis and EPS-mediated zinc oxide nanoparticles (EPS-ZnO NPs) for a diet to evaluate growth parameters, antioxidant enzyme activities, and immune stimulation together with disease resistance against Aeromonas hydrophila and Vibrio parahaemolyticus in Mozambique tilapia Oreochromis mossambicus. Fish were separated into seven groups, with six experimental groups fed with EPS and EPS-ZnO NPs at 2, 5, and 10 mg/g and a control fed a basal diet. The fish ingesting feed supplemented with EPS and EPS-ZnO NPs at 10 mg/g showed improved growth performance. Cellular and humoral-immunological parameters were tested in serum and mucus after 15 and 30 days of feeding. These parameters were substantially enriched with a 10 mg/g diet (p < 0.05) of EPS and EPS-ZnO NPs in comparison with the control. Furthermore, the EPS and EPS-ZnO NP supplemental diet actively enhanced the antioxidant response (glutathione peroxidase, superoxide dismutase, and catalase). In addition, the supplemental diet of EPS and EPS-ZnO NPs lowered the death rate and improved the disease resistance of O. mossambicus following assessment with A. hydrophila and V. parahaemolyticus at 50 µL. Hence, the overall results suggest that the supplemental diet of EPS and EPS-ZnO NPs might be used to ensure aquaculture feed additives.
Development of Phase and Seasonally Dependent Land-Use Regression Models to Predict Atmospheric PAH Levels
Authors: Tuerxunbieke Ayibota , Xu Xiangyu , Pei Wen , Qi Ling , Qin Ning , Duan Xiaoli
Published: March 2023

Polycyclic aromatic hydrocarbons (PAHs) are an important class of pollutants in China. The land use regression (LUR) model has been used to predict the selected PAH concentrations and screen the key influencing factors. However, most previous studies have focused on particle-associated PAHs, and research on gaseous PAHs was limited. This study measured representative PAHs in both gaseous phases and particle-associated during the windy, non-heating and heating seasons from 25 sampling sites in different areas of Taiyuan City. We established separate prediction models of 15 PAHs. Acenaphthene (Ace), Fluorene (Flo), and benzo [g,h,i] perylene (BghiP) were selected to analyze the relationship between PAH concentration and influencing factors. The stability and accuracy of the LUR models were quantitatively evaluated using leave-one-out cross-validation. We found that Ace and Flo models show good performance in the gaseous phase (Ace: adj. R2 = 0.14–0.82; Flo: adj. R2 = 0.21–0.85), and the model performance of BghiP is better in the particle phase (adj. R2 = 0.20–0.42). Additionally, better model performance was observed in the heating season (adj R2 = 0.68–0.83) than in the non-heating (adj R2 = 0.23–0.76) and windy seasons (adj R2 = 0.37–0.59). Those gaseous PAHs were highly affected by traffic emissions, elevation, and latitude, whereas BghiP was affected by point sources. This study reveals the strong seasonal and phase dependence of PAH concentrations. Building separate LUR models in different phases and seasons improves the prediction accuracy of PAHs.