bluuebunny/crossref_metadata_2025 huggingface dataset:
Man as a “Work of Art”: The Religious–Dialogical Dimension of Education as a Path of Education for Beauty/Goodness
Authors: Razum Ružica , Malović Nenad
Published: November 2023

Aiming to establish a dialogue with modern man, who lives in a culture marked by great challenges, church documents put a great emphasis on the via pulchritudinis. The via pulchritudinis, i.e., the way of beauty, is considered to be a privileged way of achieving dialogue. Awareness of the importance of beauty, in close connection with goodness and truth, is increasingly present in the theological and the religious–pedagogical thought. One of the specific questions related to education for beauty refers to the education of a person who is called to transform his or her life into a “work of art”. This paper reflects on only one specific aspect of the issue of shaping human beauty/goodness, that is, people’s “humanity”, in connection with the challenges of increasingly complex coexistence in diversity. Globalization and migration trends, primarily by complicating life together/coexistence, pose certain challenges to man as an individual, as well as to the entire society, especially the challenge that is coexistence of different cultures and religions. Since these problems also penetrate school classrooms, education systems are expected to provide appropriate responses. The paper consists of two parts. In the theoretical part, two specific fundamental issues related to the education of a person’s “humanity” in the atmosphere of “conflict culture” are considered: the issue of comprehensive education following the ancient connection of beauty and goodness, as well as the issue of education for coexistence. The second part presents the results of the research which was carried out in the Republic of Croatia and which aimed to examine the presence of curriculum content that enables the acquisition of religious–dialogical competence, using the method of text analysis. In more exact terms, faced with the challenges that arise from a society burdened with misunderstanding, violence and hostility, often linked with a religious affiliation and worldviews, we ask ourselves the following question: to what extent is the contemporary education system in the Republic of Croatia, at the level of its curricula, open to the comprehensive development of students, especially in terms of the development of the religious–dialogical dimension, necessary for living a good and beautiful life in the modern multicultural and multireligious world? The results reveal a different, mostly insufficient, openness of the curriculum to the religious dimension of intercultural education. That is one of the reasons why the education system does not seem to be open to the development of the knowledge, attitudes and skills necessary for a harmonious and “beautiful” coexistence in modern society.
Assessing the Impacts of Groundwater Depletion and Aquifer Degradation on Land Subsidence in Lahore, Pakistan: A PS-InSAR Approach for Sustainable Urban Development
Authors: Sajjad Meer Muhammad , Wang Juanle , Afzal Zeeshan , Hussain Sajid , Siddique Aboubakar , Khan Rehan , Ali Muhammad , Iqbal Javed
Published: November 2023

In various regions worldwide, people rely heavily on groundwater as a significant water source for daily usage. The resulting large-scale depletion of groundwater has triggered surface deformation in densely populated urban areas. This paper aims to employ Persistent Scattered Interferometry Synthetic Aperture Radar (PS-InSAR) techniques to monitor and quantify the land surface deformation (LSD), assess the relationships between LSD and groundwater levels (GWL), and provide insights for urban planning in Lahore, Pakistan, as the research area. A series of Sentinel-1 images from the ascending track between 2017 and 2020 were analyzed. Moreover, the Mann–Kendall (MK) test and coefficient of determination were computed to analyze the long-term trends and spatial relationships between GWL depletion and line of sight (LOS) displacement. Our findings reveal significant increases in land subsidence (LS) and GWL from 2017 to 2020, particularly in the city center of Lahore. Notably, the annual mean subsidence during this period rose from −27 mm/year to −106 mm/year, indicating an accelerating trend with an average subsidence of −20 mm/year. Furthermore, the MK test indicated a declining trend in GWL, averaging 0.49 m/year from 2003 to 2020, exacerbating LS. Regions with significant groundwater discharge are particularly susceptible to subsidence rates up to −100 mm. The LS variation was positively correlated with the GWL at a significant level (p < 0.05) and accounted for a high positive correlation at the center of the city, where the urban load was high. Overall, the adopted methodology effectively detects, maps, and monitors land surfaces vulnerable to subsidence, offering valuable insights into efficient sustainable urban planning, surface infrastructure design, and subsidence-induced hazard mitigation in large urban areas.
Optimization of Deep Learning Parameters for Magneto-Impedance Sensor in Metal Detection and Classification
Authors: Kim Hoijun , Chae Hobyung , Kwon Soonchul , Lee Seunghyun
Published: November 2023

Deep learning technology is generally applied to analyze periodic data, such as the data of electromyography (EMG) and acoustic signals. Conversely, its accuracy is compromised when applied to the anomalous and irregular nature of the data obtained using a magneto-impedance (MI) sensor. Thus, we propose and analyze a deep learning model based on recurrent neural networks (RNNs) optimized for the MI sensor, such that it can detect and classify data that are relatively irregular and diverse compared to the EMG and acoustic signals. Our proposed method combines the long short-term memory (LSTM) and gated recurrent unit (GRU) models to detect and classify metal objects from signals acquired by an MI sensor. First, we configured various layers used in RNN with a basic model structure and tested the performance of each layer type. In addition, we succeeded in increasing the accuracy by processing the sequence length of the input data and performing additional work in the prediction process. An MI sensor acquires data in a non-contact mode; therefore, the proposed deep learning approach can be applied to drone control, electronic maps, geomagnetic measurement, autonomous driving, and foreign object detection.
Efficient Underground Tunnel Place Recognition Algorithm Based on Farthest Point Subsampling and Dual-Attention Transformer
Authors: Chai Xinghua , Yang Jianyong , Yan Xiangming , Di Chengliang , Ye Tao
Published: November 2023

An autonomous place recognition system is essential for scenarios where GPS is useless, such as underground tunnels. However, it is difficult to use existing algorithms to fully utilize the small number of effective features in underground tunnel data, and recognition accuracy is difficult to guarantee. In order to solve this challenge, an efficient point cloud position recognition algorithm, named Dual-Attention Transformer Network (DAT-Net), is proposed in this paper. The algorithm firstly adopts the farthest point downsampling module to eliminate the invalid redundant points in the point cloud data and retain the basic shape of the point cloud, which reduces the size of the point cloud and, at the same time, reduces the influence of the invalid point cloud on the data analysis. After that, this paper proposes the dual-attention Transformer module to facilitate local information exchange by utilizing the multi-head self-attention mechanism. It extracts local descriptors and integrates highly discriminative global descriptors based on global context with the help of a feature fusion layer to obtain a more accurate and robust global feature representation. Experimental results show that the method proposed in this paper achieves an average F1 score of 0.841 on the SubT-Tunnel dataset and outperforms many existing state-of-the-art algorithms in recognition accuracy and robustness tests.
Signal Processing and Waveform Re-Tracking for SAR Altimeters on High Mobility Platforms with Vertical Movement and Antenna Mis-Pointing
Authors: Wang Qiankai , Jing Wen , Liu Xiang , Huang Bo , Jiang Ge
Published: November 2023

Synthetic aperture radar (SAR) altimeters can achieve higher spatial resolution and signal-to-noise ratio (SNR) than conventional altimeters by Doppler beam sharpening or focused SAR imaging methods. To improve the estimation accuracy of waveform re-tracking, several average echo power models for SAR altimetry have been proposed in previous works. However, these models were mainly proposed for satellite altimeters and are not applicable to high-mobility platforms such as aircraft, unmanned aerial vehicles (UAVs), and missiles, which may have a large antenna mis-pointing angle and significant vertical movement. In this paper, we propose a novel semi-analytical waveform model and signal processing method for SAR altimeters with vertical movement and large antenna mis-pointing angles. A new semi-analytical expression that can be numerically computed for the flat pulse response (FSIR) is proposed. The 2D delay–Doppler map is then obtained by numerical computation of the convolution between the proposed analytical function, the probability density function, and the time/frequency point target response of the radar. A novel delay compensation method based on sinc interpolation for SAR altimeters with vertical movement is proposed to obtain the multilook echo, which can optimally handle non-integer delays and maintain signal frequency characteristics. In addition, a height estimation method based on least squares (LS) estimation is proposed. The LS estimator does not have an analytical solution, and requires iterative solving through gradient descent. We evaluate the performance of the proposed estimation strategy using simulated data for typical airborne scenarios. When the mis-pointing angles are within 10 degrees, the normalized quadratic error (NQE) of the proposed model is less than 10−10 and the RMSE of τ obtained by the re-tracking method fitted by the proposed model is less than 0.2 m, which indicates the high applicability of the model and accuracy of the re-tracking method.
Small Sample Building Energy Consumption Prediction Using Contrastive Transformer Networks
Authors: Ji Wenxian , Cao Zeyu , Li Xiaorun
Published: November 2023

Predicting energy consumption in large exposition centers presents a significant challenge, primarily due to the limited datasets and fluctuating electricity usage patterns. This study introduces a cutting-edge algorithm, the contrastive transformer network (CTN), to address these issues. By leveraging self-supervised learning, the CTN employs contrastive learning techniques across both temporal and contextual dimensions. Its transformer-based architecture, tailored for efficient feature extraction, allows the CTN to excel in predicting energy consumption in expansive structures, especially when data samples are scarce. Rigorous experiments on a proprietary dataset underscore the potency of the CTN in this domain.
Anomaly Detection in Time Series Data Using Reversible Instance Normalized Anomaly Transformer
Authors: Baidya Ranjai , Jeong Heon
Published: November 2023

Anomalies are infrequent in nature, but detecting these anomalies could be crucial for the proper functioning of any system. The rarity of anomalies could be a challenge for their detection as detection models are required to depend on the relations of the datapoints with their adjacent datapoints. In this work, we use the rarity of anomalies to detect them. For this, we introduce the reversible instance normalized anomaly transformer (RINAT). Rooted in the foundational principles of the anomaly transformer, RINAT incorporates both prior and series associations for each time point. The prior association uses a learnable Gaussian kernel to ensure a thorough understanding of the adjacent concentration inductive bias. In contrast, the series association method uses self-attention techniques to specifically focus on the original raw data. Furthermore, because anomalies are rare in nature, we utilize normalized data to identify series associations and employ non-normalized data to uncover prior associations. This approach enhances the modelled series associations and, consequently, improves the association discrepancies.
Aberration Theory of a Flat, Aplanatic Metalens Doublet and the Design of a Meta-Microscope Objective Lens
Authors: Han Woojun , Jeong Jinsoo , Kim Jaisoon , Kim Sun-Je
Published: November 2023

A theoretical approach for reducing multiple monochromatic aberrations using a flat metalens doublet is proposed and verified through ray tracing simulations. The theoretical relation between the Abbe sine condition and the generalized Snell’s law is revealed in the doublet system. Starting from the Abbe aplanat design, minimization conditions of astigmatism and field curvature are derived. Based on the theory, a metalens doublet is semi-analytically optimized as a compact, practical-level meta-microscope objective lens working for a target wavelength. The proposed approach also reveals how to reduce lateral chromatism for an additional wavelength. The design degree of freedom and fundamental limits of the system are both rigorously analyzed in theory and verified through ray tracing simulations. It is expected that the proposed method will provide unprecedented practical opportunities for the design of advanced compact microscopic imaging or sensing systems.
A Simple Laser-Induced Breakdown Spectroscopy Method for Quantification and Classification of Edible Sea Salts Assisted by Surface-Hydrophilicity-Enhanced Silicon Wafer Substrates
Authors: Choi Han-Bum , Moon Seung-Hyun , Kim Hyang , Guthikonda Nagaraju , Ham Kyung-Sik , Han Song-Hee , Nam Sang-Ho , Lee Yong-Hoon
Published: November 2023

Salt, one of the most commonly consumed food additives worldwide, is produced in many countries. The chemical composition of edible salts is essential information for quality assessment and origin distinction. In this work, a simple laser-induced breakdown spectroscopy instrument was assembled with a diode-pumped solid-state laser and a miniature spectrometer. Its performances in analyzing Mg and Ca in six popular edible sea salts consumed in South Korea and classification of the products were investigated. Each salt was dissolved in water and a tiny amount of the solution was dropped and dried on the hydrophilicity-enhanced silicon wafer substrate, providing homogeneous distribution of salt crystals. Strong Mg II and Ca II emissions were chosen for both quantification and classification. Calibration curves could be constructed with limits-of-detection of 87 mg/kg for Mg and 45 mg/kg for Ca. Also, the Mg II and Ca II emission peak intensities were used in a k-nearest neighbors model providing 98.6% classification accuracy. In both quantification and classification, intensity normalization using a Na I emission line as a reference signal was effective. A concept of interclass distance was introduced, and the increase in the classification accuracy due to the intensity normalization was rationalized based on it. Our methodology will be useful for analyzing major mineral nutrients in various food materials in liquid phase or soluble in water, including salts.
A Method for Image Anomaly Detection Based on Distillation and Reconstruction
Authors: Luo Jiaxiang , Zhang Jianzhao
Published: November 2023

Image anomaly detection is a trending research topic in computer vision. The objective is to build models using available normal samples to detect various abnormal images without depending on real abnormal samples. It has high research significance and value for applications in the detection of defects in product appearance, medical image analysis, hyperspectral image processing, and other fields. This paper proposes an image anomaly detection algorithm based on feature distillation and an autoencoder structure, which uses the feature distillation structure of a dual-teacher network to train the encoder, thus suppressing the reconstruction of abnormal regions. This system also introduces an attention mechanism to highlight the detection objects, achieving effective detection of different defects in product appearance. In addition, this paper proposes a method for anomaly evaluation based on patch similarity that calculates the difference between the reconstructed image and the input image according to different regions of the image, thus improving the sensitivity and accuracy of the anomaly score. This paper conducts experiments on several datasets, and the results show that the proposed algorithm has superior performance in image anomaly detection. It achieves 98.8% average AUC on the SMDC-DET dataset and 98.9% average AUC on the MVTec-AD dataset.
Functional Polymeric Membranes with Antioxidant Properties for the Colorimetric Detection of Amines
Authors: Kossyvaki Despoina , Bustreo Matteo , Contardi Marco , Athanassiou Athanassia , Fragouli Despina
Published: November 2023

Herein, the ability of highly porous colorimetric indicators to sense volatile and biogenic amine vapors in real time is presented. Curcumin-loaded polycaprolactone porous fiber mats are exposed to various concentrations of off-flavor compounds such as the volatile amine trimethylamine, and the biogenic amines cadaverine, putrescine, spermidine, and histamine, in order to investigate their colorimetric response. CIELAB color space analysis demonstrates that the porous fiber mats can detect the amine vapors, showing a distinct color change in the presence of down to 2.1 ppm of trimethylamine and ca. 11.0 ppm of biogenic amines, surpassing the limit of visual perception in just a few seconds. Moreover, the color changes are reversible either spontaneously, in the case of the volatile amines, or in an assisted way, through interactions with an acidic environment, in the case of the biogenic amines, enabling the use of the same indicator several times. Finally, yet importantly, the strong antioxidant activity of the curcumin-loaded fibers is successfully demonstrated through DPPH● and ABTS● radical scavenging assays. Through such a detailed study, we prove that the developed porous mats can be successfully established as a reusable smart system in applications where the rapid detection of alkaline vapors and/or the antioxidant activity are essential, such as food packaging, biomedicine, and environmental protection.
Ecological Risks Arising in the Regional Water Resources in Inner Mongolia Due to a Large-Scale Afforestation Project
Authors: Chen Peng , Ma Rong , Shi Jiansheng , Si Letian , Zhao Lefan , Wu Jun
Published: November 2023

In recent years, a large-scale afforestation campaign has been implemented in Inner Mongolia, China, to control desertification and soil erosion. However, the water consumption associated with large-scale afforestation significantly impacts the water resources in Inner Mongolia, resulting in a major ecological risk. This study aimed to evaluate the ecological risk of water resources caused by afforestation in the region. In this study, using land cover data, normalized difference vegetation index (NDVI) data, and meteorological data, we performed trend analysis and used the water balance equation and water security index (WSI) to analyze the ecological risks of water resources caused by afforestation in Inner Mongolia from 2000 to 2020. The results show that (1) the afforestation area in Inner Mongolia was 5.37 × 104 km2 in 2000–2020; (2) afforestation in arid and semi-arid areas led to a reduction in water resources; (3) afforestation reduced water resources in the study area by 62 million cubic meters (MCM) per year; and (4) ~76% of afforestation regions faced ecological risks related to water resources. This study provides scientific suggestions for the sustainable development of regional water resources and afforestation.
Characterization of the Cattle Production Systems in the Department of Cundinamarca (Colombia), Proposals for Sustainability
Authors: Cruz Fabián , Horcada Alberto , Castel José María , Mena Yolanda
Published: November 2023

The aim of this document is to analyze the bovine production systems in the Department of Cundinamarca (Colombia) as an initial part of the strategic plan to implement sustainable and efficient technological proposals in this region of the Andes. Descriptive and productive agricultural data related to bovine production of the 116 municipalities were analyzed using a multivariate analysis method (principal component, cluster and variance analysis). The information contained quantitative variables regarding three topics: general information (geographical, cadastral and productive), a municipal bovine inventory, and productive information about the cattle farms. The analysis enabled us to generate three clusters of bovine production systems as follows: Cluster 1, representative of the dual-purpose activity, made up of 48 medium-climate municipalities, of which 64.6% of the municipal farms correspond to dual-purpose production with an average farm size of 5.2 ha, a carrying capacity of 1.2 UGM/ha and milk production per cow of 7.75 L/d; Cluster 2, made up of 36 cold-climate municipalities dedicated mainly to dairy production on farms (65.9%) of approximately 3.8 ha, with a carrying capacity of 2.3 UGM/ha and milk production per cow of 14.34 L/d.; and Cluster 3, made up of 32 warm-climate municipalities dedicated mainly to beef production on farms. In this cluster, 66.6% of the farms correspond to beef production of approximately 8.5 ha, with a carrying capacity of 1.2 UGM/ha and milk production of 6.35 L/d. Colombia’s climatic diversity and the wide range of bovine livestock activities are among the main strengths that make up the system’s advantages. However, the low technological development in the majority of the bovine livestock farms, which is related to variables such as low carrying capacity, as in Clusters 1 and 3 and with the low employment generated by bovine production in Colombia, are opportunities to improve the livestock industry. It is advisable to continue working to obtain data on important aspects of the system such as technology, nutrition, reproductive management (including artificial insemination), the economy and environmental and social aspects, in order to delve deeper into the sustainability of productive systems.
Spatial Model for Energy Consumption of LEED-Certified Buildings
Authors: Kim Jonghoon , Moon Soo-Young , Jang Daehee
Published: November 2023

In this research endeavor, we undertook a comprehensive examination of the factors influencing the energy consumption of LEED-certified buildings, employing both a general linear regression model and a spatial delayed regression model. Gaining a profound understanding of energy utilization patterns within LEED-certified structures can significantly contribute to advancing eco-friendly construction practices. Our investigation draws upon data from a 2010 study conducted at the University of Wisconsin—Madison (UW), encompassing various independent variables, such as temperature, that exhibit some degree of correlation with energy consumption in LEED-certified buildings. The principal objective of this study is twofold: firstly, to ascertain the significance of specific exogenous variables, notably temperature, and secondly, to explore the impact of spatial factors, such as function and location, on energy usage. Our research framework encompasses meticulous data collection and rigorous analysis, culminating in the presentation and discussion of our findings. Notably, our study unveils intriguing insights. Contrary to conventional assumptions, we discovered that the energy consumption of LEED-certified buildings does not exhibit a robust linear association with average annual temperature, the count of power plants within a 50 mile radius, or the LEED rating itself. However, our spatial regression models unveil a compelling narrative: the geographic distribution and functional diversity of distinct LEED buildings wield discernible influence over energy consumption patterns. The implications of our research resonate profoundly in the realm of LEED-certified building design and construction. Architects, builders, and stakeholders should consider the nuanced interplay of spatial variables and geographical positioning in the pursuit of optimal energy efficiency. Moreover, our findings stimulate further inquiry in this field, paving the way for future investigations aimed at refining sustainable building practices and enhancing our understanding of energy consumption within LEED-certified structures.
‘I Tweet about Our #GreenEnergy’—Automated Classification of Social Identity and Opinion Mining of the Dutch Twitter Discourse on Green-Energy Technologies
Authors: Lammers Romée , Jansma Sikke R. , Veldkamp Bernard P. , Machens Anna K. , de Visser Matthias , Gosselt Jordy F.
Published: November 2023

Understanding the complexities of public opinion is crucial for a green-energy transition. This present study examines the sentiment of public opinion towards various energy technologies on Twitter during the Dutch 2021 general elections. A dataset comprising 186,822 tweets and profile descriptions was analyzed using two automated text classifiers to explore how individuals with different self-proclaimed identities perceive green-energy technologies. The analysis involved the application of the sentiment and social identity classifier models, followed by a frequency and co-occurrence analysis. The findings revealed a negative overall sentiment towards green-energy technologies in the Twitter discourse. It further showed that perceptions may differ depending on a technology’s development stage, with emerging technologies generally receiving more favorable views compared to established ones. Furthermore, it was found that, although there is a general trend of negative sentiment based on political identity, and positive sentiment based on occupational identity, this trend did not consistently apply to specific energy technologies. This discrepancy can likely be attributed to varying implementation effects and contextual situations associated with the technologies. The findings suggest that personalized communication strategies for specific social groups may be beneficial for understanding and addressing public opinions, needs, and concerns within the energy transition. The complexity of understanding public opinion in the context of green-energy highlights the need for a nuanced approach in future research.
Effect of Fertilisation Regime on Maise Yields
Authors: Kuboń Maciej , Tymińska Magdalena , Skibko Zbigniew , Borusiewicz Andrzej , Filipkowski Jacek , Tabor Sylwester , Derehajło Stanisław
Published: November 2023

Using natural fertilisers in agriculture improves quantity and quality yields. They introduce macronutrients (nitrogen, phosphorus, and potassium) and micronutrients into the soil. Enriching the soil with organic substances through fertilisation with digestates requires the farmer to have considerable knowledge and accuracy in dosing due to the need to comply with permissible concentrations of macronutrients. The availability of nutrients in a digestate is closely dependent on the substrates used in the biogas plant, and it cannot be stated unequivocally that better yields of field crops will be achieved by using it as manure. Therefore, the authors conducted a two-year study of the effect of the fertilisation method on maise yields. Based on the research carried out, the fertiliser suitability of the digest was confirmed. Plants fertilised with it were characterised by the highest (compared to other fertilisation methods) grain yield (of 12.07 Mg per hectare on average). In addition, they were characterised by adequate plant height (3.15 m on average). The observations also indicate good emergence and satisfactory early vigour.
Tricyclic Graph with Minimum Randić Index
Authors: Tang Liangwen , Song Zhumei , Lin Mugang
Published: November 2023

The Randić index of a graph G is the sum of (dG(u)dG(v))−12 over all edges uv of G, where dG(u) denotes the degree of vertex u in G. In this paper, we investigate a few graph transformations that decrease the Randić index of a graph. By applying those transformations, we determine the minimum Randić index on tricyclic graphs and characterize the corresponding extremal graphs.
Development of a Displacement Prediction System for Deep Excavation Using AI Technology
Authors: Hsu Chia-Feng , Wu Chien-Yi , Li Yeou-Fong
Published: November 2023

This manuscript delineates an innovative artificial intelligence-based methodology for forecasting the displacement of retaining walls due to extensive deep excavation processes. In our selection of 17 training cases, we strategically chose a wall configuration that was not influenced by the corner effects. This careful selection was conducted with the intention of ensuring that each deep excavation instance included in our study was supported symmetrically, thereby streamlining the analysis in the ensuing phases. Our proposed multilayer functional-link network demonstrates superior performance over the traditional backpropagation neural network (BPNN), excelling in the precise prediction of displacements at predetermined observation points, peak wall displacements, and their respective locations. Notably, the predictive accuracy of our advanced model surpassed that of the conventional BPNN and RIDO assessment tools by a substantial 5%. The network process model formulated through this research offers a valuable reference for future implementations in diverse geographical settings. Furthermore, by utilizing local datasets for the training, testing, and validation phases, our system ensures the effective and accurate execution of displacement predictions.
Depicting the Profile of METTL3-Mediated lncRNA m6A Modification Variants and Identified SNHG7 as a Prognostic Indicator of MNNG-Induced Gastric Cancer
Authors: Liu Tong , Feng Yanlu , Yang Sheng , Ge Yiling , Zhang Tianyi , Li Jie , Li Chengyun , Ruan Ye , Luo Bin , Liang Geyu
Published: November 2023

As a representative example of an environmental chemical carcinogen, MNNG exposure is closely associated with the onset of gastric cancer (GC) where N6-methyladenosine (m6A) RNA methylation tends to be the critical epigenetic event. However, the effect of m6A modification on long non-coding RNAs (lncRNAs) in MNNG-induced GC onset is still unclear. To address the above issue, based on the Methylated RNA immunoprecipitation sequencing (MeRIP-seq) data of MNNG-induced malignant cells (MCs) and GC cells, we comprehensively analyzed the MNNG exposure-associated vital lncRNAs. MeRIP-seq analysis identified 1432 lncRNA transcripts in the MC cell, and 3520 lncRNA transcripts were found to be m6A modified in the GC cell, respectively. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that MNNG exposure could spark cellular localization change, which might be the critical cellular note variation for malignant transformation. We demonstrated that METTL3 is responsible for N6 methylation of lncRNAs and identified SNHG7 as a downstream target of METTL3. More importantly, we observed that SNHG7 was progressively up-regulated during gastric carcinogenesis by MNNG exposure. Finally, we investigated SNHG7 expression in different stages of GC malignancies and found that elevated SNHG7 expression correlated with advanced clinical features and poor prognosis in GC. In conclusion, our study found for the first time that METTL3 regulates the m6A methylation level of lncRNA SNHG7 and its expression in MNNG exposure-induced GC, suggesting that SNHG7 as a predictive biomarker or therapeutic target for GC.
Effect of Arsenic on Fluoride Tolerance in Microbacterium paraoxydans Strain IR-1
Authors: Mathur Megha , Rawat Neha , Saxena Tanushree , Khandelwal Renu , Jain Neha , Sharma Mukesh K. , Mohan Medicherla K. , Bhatnagar Pradeep , Flora Swaran J. S. , Kaushik Pallavi
Published: November 2023

Fluoride (F) and arsenic (As) are two major contaminants of water and soil systems around the globe, causing potential toxicity to humans, plants, animals, and microbes. These contaminated soil systems can be restored by microorganisms that can tolerate toxic stress and provide rapid mineralization of soil, organic matter, and contaminants, using various tolerance mechanisms. Thus, the present study was undertaken with the arsenic hyper-tolerant bacterium Microbacterium paraoxydans strain IR-1 to determine its tolerance and toxicity to increasing doses of fluoride, either individually or in combination with arsenic, in terms of growth inhibition using a toxicity unit model. The minimum inhibitory concentration (MIC)and half maximal inhibitory concentration (IC50) values for fluoride increased, from 9 g/L to 11 g/L and from 5.91 ± 0.1 g/L to 6.32 ± 0.028 g/L, respectively, in the combination (F + As) group. The statistical comparison of observed and expected additive toxicities, with respect to toxicity unit (TU difference), using Student’s t-test, was found to be highly significant (p < 0.001). This suggests the antagonistic effect of arsenic on fluoride toxicity to the strain IR-1. The unique stress tolerance of IR-1 ensures its survival as well as preponderance in fluoride and arsenic co-contaminated sites, thus paving the way for its possible application in the natural or artificial remediation of toxicant-exposed degraded soil systems.
Engineering a Novel Modular Adenoviral mRNA Delivery Platform Based on Tag/Catcher Bioconjugation
Authors: Geng Kexin , Rice-Boucher Paul J. , Kashentseva Elena A. , Dmitriev Igor P. , Lu Zhi Hong , Goedegebuure S. Peter , Gillanders William E. , Curiel David T.
Published: November 2023

mRNA vaccines have attracted widespread research attention with clear advantages in terms of molecular flexibility, rapid development, and potential for personalization. However, current mRNA vaccine platforms have not been optimized for induction of CD4/CD8 T cell responses. In addition, the mucosal administration of mRNA based on lipid nanoparticle technology faces challenges in clinical translation. In contrast, adenovirus-based vaccines induce strong T cell responses and have been approved for intranasal delivery. To leverage the inherent strengths of both the mRNA and adenovirus platforms, we developed a novel modular adenoviral mRNA delivery platform based on Tag/Catcher bioconjugation. Specifically, we engineered adenoviral vectors integrating Tag/Catcher proteins at specific locales on the Ad capsid proteins, allowing us to anchor mRNA to the surface of engineered Ad viruses. In proof-of-concept studies, the Ad-mRNA platform successfully mediated mRNA delivery and could be optimized via the highly flexible modular design of both the Ad-mRNA and protein bioconjugation systems.
Whitefly-Transmitted Viruses of Cucurbits in the Southern United States
Authors: Devendran Ragunathan , Kavalappara Saritha Raman , Simmons Alvin M. , Bag Sudeep
Published: November 2023

Cucurbits are economically important crops that are widely cultivated in many parts of the world, including the southern US. In recent years, higher temperatures have favored the rapid build-up of whiteflies in the fall-grown cucurbits in this region. As a result, whitefly-transmitted viruses (WTVs) have severely impacted the marketable yield of cucurbits. In this review, we discuss three major groups of WTVs negatively impacting cucurbit cultivation in the southern US, including begomoviruses, criniviruses, and ipomoviruses. Here, we discuss the available information on the biology, epidemiology and advances made toward detecting and managing these viruses, including sources of resistance and cultural practices.
Revealing Novel-Strain-Specific and Shared Epitopes of Infectious Bronchitis Virus Spike Glycoprotein Using Chemical Linkage of Peptides onto Scaffolds Precision Epitope Mapping
Authors: Sives Samantha , Keep Sarah , Bickerton Erica , Vervelde Lonneke
Published: November 2023

The avian coronavirus, infectious bronchitis virus (IBV), is an economically important infectious disease affecting chickens, with a diverse range of serotypes found globally. The major surface protein, spike (S), has high diversity between serotypes, and amino acid differences in the S1 sub-unit are thought to be responsible for poor cross-protection afforded by vaccination. Here, we attempt to address this, by using epitope mapping technology to identify shared and serotype-specific immunogenic epitopes of the S glycoprotein of three major circulating strains of IBV, M41, QX, and 4/91, via CLIPS peptide arrays based on peptides from the S1 sub-units. The arrays were screened with sera from chickens immunised with recombinant IBV, based on Beau-R backbone expressing heterologous S, generated in two independent vaccination/challenge trials. The screening of sera from rIBV vaccination experiments led to the identification of 52 immunogenic epitopes on the S1 of M41, QX, and 4/91. The epitopes were assigned into six overlapping epitope binding regions. Based on accessibility and location in the hypervariable regions of S, three sequences, 25YVYYYQSAFRPPNGWHLQGGAYAVVNSTN54, 67TVGVIKDVYNQSVASI82, and 83AMTVPPAGMSWSVS96, were selected for further investigation, and synthetic peptide mimics were recognised by polyclonal sera. These epitopes may have the potential to contribute towards a broader cross-protective IBV vaccine.
Sedimentation Characteristics of the Fluctuating Backwater Area at the Tail of Cascade Reservoirs: A Case Study of the Three Gorges Reservoir
Authors: Li Jun , Ge Hua , Ping Yanrong , Dong Xianyong , Zhu Lingling , Ma Yaochang
Published: November 2023

The construction of cascade reservoirs is associated with considerable uncertainty in sedimentation in the fluctuating backwater area of the terminal reservoir and poses challenges to water safety. The sedimentation characteristics under the influence of multiple factors in the main urban area of the Chongqing river section were analyzed as a case study for the operation of cascade reservoirs in the Jinsha River via the utilization of a large dataset spanning back to the normal storage of the Three Gorges Reservoir. The results of this study indicate that, owing to factors such as upstream water, sediment inflow, reservoir operation, and river sand mining, this river section experienced deposition on the sand bars and erosion in the main channel. The rate of sedimentation increased with sediment inflow, peak flow rate, and duration, while the location of sedimentation shifted as the concentration ratio changed. These results may provide technical support not only for the operation of the Three Gorges Reservoir, but also for the governance of the fluctuating backwater areas of other cascade reservoirs.
Application of Judgmental Sampling Approach for the Monitoring of Groundwater Quality and Quantity Evolution in Mediterranean Catchments
Authors: Ntona Maria Margarita , Chalikakis Konstantinos , Busico Gianluigi , Mastrocicco Micòl , Kalaitzidou Kyriaki , Kazakis Nerantzis
Published: November 2023

Groundwater monitoring is critically important, even though it is costly and often neglected. In this study, a judgmental monitoring of groundwater offering solutions based on a cost and time-effective research approach is presented. The method was performed in three Mediterranean areas in Greece and Italy to examine its advantages and disadvantages. As a first step, a multi-statistical analysis was practiced to assess and apportion the potential contributions of pollution sources of groundwater. Pearson correlation, principal component analysis, and factor analysis were applied to groundwater samples to characterize the evolution of hydrochemical processes. High concentrations of chlorides and nitrates highlight that salinization and the extensive use of nitrate fertilizers dominate in the coastal part of Eastern Thermaikos Gulf, the dissolution of carbonate rocks and livestock/industrial activities drive the groundwater quality status in the Upper Volturno basin, while in the Mouriki basin thermal power plant and the use of zinc fertilizers are the main factors of groundwater quality degradation. The determination of the critical sampling points was applied, considering the land use and hydrogeological and morphological characteristics of the areas. The application of the judgmental sampling approach provides reliable results regarding groundwater evolution. These results were compared to previous works and found that a non-probability sampling technique can provide the same results as a more costly method in the Mediterranean region. Thus, judgmental sampling is crucial for the optimal application of water resource management and control techniques in basins to avoid gaps in data collection.
Application of a U-Tube Oxygenator in a Litopenaeus vannamei Recirculating Aquaculture System: Efficiency and Management Models
Authors: Xu Jianping , Du Yishuai , Su Guogen , Wang Hexiang , Zhang Jiawei , Tian Huiqin , Zhou Li , Qiu Tianlong , Sun Jianming
Published: November 2023

This study investigated the dissolved oxygen (DO) variation pattern in a Litopenaeus vannamei recirculating aquaculture system (RAS) and established an oxygen-utilization rate (UROxygen) model, pure oxygen addition (QOxygen) model, and control model that linked a microscreen drum filter (MDF) with a U-tube oxygenator. The main objective was to promote the application of the U-tube oxygenator and achieve the efficient, accurate, and automated management of DO in an RAS. To avoid wasting oxygen and ensure production safety, it was recommended to maintain the effluent of the aquaculture pond at 6.9 ± 0.4 mg/L. The modeled relationship between the RAS flow (QRAS), QOxygen, and UROxygen was UROxygen = 0.9626 × (−105.3406 + 0.9911QRAS + 10.6202QOxygen − 0.05964QRASQOxygen − 1.2628 × 10−3QRAS2 − 0.1821QOxygen2 + 6.8888 × 10−5QRAS2QOxygen + 6.3993 × 10−4QRASQOxygen2). The modeled relationship between QRAS, daily feeding rate (MFeeding), and QOxygen was QOxygen = 1.09 × (−12.8633 − 0.02793QRAS + 0.9369 MFeeding − 8.9286 × 10−4MFeedingQRAS + 5.6122 × 10−5QRAS2 − 2.3281 × 10−3MFeeding2). The modeled relationship between the MDF backwashing period (TMDF) and QOxygen was QOxygen = −11.57ln(TMDF) + 78.319. This study provided a theoretical basis and novel methods for the management of DO in an RAS, thus promoting the healthy and stable development of an L. vannamei RAS.
Research on Temperature Control Index for High Concrete Dams Based on Information Entropy and Cloud Model from the View of Spatial Field
Authors: Yang Guang , Sun Jin , Zhang Jianwei , Niu Jingtai , Luan Bowen , Huang Zhendong , Zhao Ahui
Published: November 2023

It is significant to adopt scientific temperature control criteria for high concrete dams in the construction period according to practical experience and theoretical calculation. This work synthetically uses information entropy and a cloud model and develops novel in situ observation data-based temperature control indexes from the view of a spatial field. The order degree and the disorder degree of observation values are defined according to the probability principle. Information entropy and weight parameters are combined to describe the distribution characteristics of the temperature field. Weight parameters are optimized via projection pursuit analysis (PPA), and then temperature field entropy (TFE) is constructed. Based on the above work, multi-level temperature control indexes are set up via a cloud model. Finally, a case study is conducted to verify the performance of the proposed method. According to the calculation results, the change law of TFEs agrees with actual situations, indicating that the established TFE is reasonable, the application conditions of the cloud model are wider than those of the typical small probability method, and the determined temperature control indexes improve the safety management level of high concrete dams. Research results offer scientific reference and technical support for temperature control standards adopted at other similar projects.
Evolutionary Trends and Coordinated Development Analysis of Water Resources Systems and High-Quality Economic Growth in the Yangtze River Delta
Authors: Liu Di , Dai Qin , Yuan Guanghui
Published: November 2023

This article calculates the indices for high-quality economic development and water resource systems across 25 cities in the Yangtze River Delta from 2011 to 2021. Utilizing a multifaceted analytical framework comprising the CRITIC method, standard deviation ellipse, harmonious development coefficient, and coupling coordination coefficient, we investigate spatiotemporal evolutionary trends and overarching harmonious development states between the two systems. Results indicate: (1) Throughout the research period, mean values of high-quality economic development indices fluctuated within the range of 0.05 to 0.68, while water resource carrying capacity indices oscillated between 0.18 and 0.81. (2) The epicenter of high-quality economic development indices is situated in the periphery of Lake Tai, whereas the fulcrum of the water resource system indices is located in Huzhou City, both displaying a northwest-southeast orientation. (3) Coupling coordination development exhibits a propitious advancement trajectory, with certain locales attaining exemplary coordinated growth.
DETERMINATION OF THE CHARACTERISTIC FEATURES OF THE OPERATION OF A PERFORATED RUBBER-METALLIC VIBRATOR INSULATOR WITH THE USE OF SOFTWARE PACKAGES IMPLEMENTING THE FINITE ELEMENT METHOD
Authors:   NRU MGSU «Moscow State Construction University», MONDRUS V.L. , SIZOV D.K. ,   NRU MGSU «Moscow State Construction University», AKIMOVA I.V. ,   LLC «VIBROSEISMOZASCHITA»
Published: November 2023

The features of the static and dynamic behavior of rubber-metal vibration isolators planned for use for vibration isolation of buildings in a modern building complex are considered. The results of finite element modeling of vibration isolators are presented in order to determine the static and dynamic characteristics. Both single-layer vibration isolators and vibration isolators, including three rubber layers, are considered. As the calculation results showed, the presence of perforations significantly affects the bearing capacity of vibration isolators, significantly reducing it, however, the efficiency of such vibration isolators also increases compared to completely monolithic vibration isolators without holes. This is due to a number of reasons, one of which is the practical incompressibility of the rubber layers. In fact, rubber bodies can be subjected to compression only due to the deformation of the side surface, thus, by developing the side surface of the rubber layers, it is possible to achieve acceptable rigidity of the vibration isolator as a structural element, which will reduce the rigidity of the vibration isolation system. The spatial arrangement of the holes is also essential, since the placement of the holes close to the side surface of the rubber layer gives a significantly smaller effect compared to the placement of the holes in the center. In the process of calculation, it turned out that in the compressed rubber layers, the effect of the formation of pronounced zones of all-round compression is observed. The presence of central holes leads to the destruction of such zones in most samples, which makes it possible to reduce the first natural frequency of the vibration-isolated system to a greater extent, thereby contributing to an increase in the effectiveness of vibration protection measures. The choice of the hole configuration is an optimization problem, where, on the one hand, it is necessary to ensure the bearing capacity of vibration isolators acceptable from the point of view of vibration isolation for given dimensions of the vibration isolator in the plan, and, on the other hand, to minimize the rigidity of the system, thus increasing the effectiveness of vibration protection measures.