bluuebunny/crossref_metadata_2025 huggingface dataset:
High-Throughput Plot-Level Quantitative Phenotyping Using Convolutional Neural Networks on Very High-Resolution Satellite Images
Authors: Victor Brandon , Nibali Aiden , Newman Saul Justin , Coram Tristan , Pinto Francisco , Reynolds Matthew , Furbank Robert T. , He Zhen
Published: January 2024

To ensure global food security, crop breeders conduct extensive trials across various locations to discover new crop varieties that grow more robustly, have higher yields, and are resilient to local stress factors. These trials consist of thousands of plots, each containing a unique crop variety monitored at intervals during the growing season, requiring considerable manual effort. In this study, we combined satellite imagery and deep learning techniques to automatically collect plot-level phenotypes from plant breeding trials in South Australia and Sonora, Mexico. We implemented two novel methods, utilising state-of-the-art computer vision architectures, to predict plot-level phenotypes: flowering, canopy cover, greenness, height, biomass, and normalised difference vegetation index (NDVI). The first approach uses a classification model to predict for just the centred plot. The second approach predicts per-pixel and then aggregates predictions to determine a value per-plot. Using a modified ResNet18 model to predict the centred plot was found to be the most effective method. These results highlight the exciting potential for improving crop trials with remote sensing and machine learning.
Flicker Noise in Resistive Gas Sensors—Measurement Setups and Applications for Enhanced Gas Sensing
Authors: Smulko Janusz , Scandurra Graziella , Drozdowska Katarzyna , Kwiatkowski Andrzej , Ciofi Carmine , Wen He
Published: January 2024

We discuss the implementation challenges of gas sensing systems based on low-frequency noise measurements on chemoresistive sensors. Resistance fluctuations in various gas sensing materials, in a frequency range typically up to a few kHz, can enhance gas sensing by considering its intensity and the slope of power spectral density. The issues of low-frequency noise measurements in resistive gas sensors, specifically in two-dimensional materials exhibiting gas-sensing properties, are considered. We present measurement setups and noise-processing methods for gas detection. The chemoresistive sensors show various DC resistances requiring different flicker noise measurement approaches. Separate noise measurement setups are used for resistances up to a few hundred kΩ and for resistances with much higher values. Noise measurements in highly resistive materials (e.g., MoS2, WS2, and ZrS3) are prone to external interferences but can be modulated using temperature or light irradiation for enhanced sensing. Therefore, such materials are of considerable interest for gas sensing.
An Investigation into the Application of Acceleration Responses’ Trendline for Bridge Damage Detection Using Quadratic Regression
Authors: Kordestani Hadi , Zhang Chunwei , Arab Ali
Published: January 2024

It has been proven that structural damage can be successfully identified using trendlines of structural acceleration responses. In previous numerical and experimental studies, the Savitzky–Golay filter and moving average filter were adjusted to determine suitable trendlines and locate structural damage in a simply supported bridge. In this study, the quadratic regression technique was studied and employed to calculate the trendlines of the bridge acceleration responses. The normalized energies of the resulting trendlines were then used as a damage index to identify the location and severity of the structural bridge damage. An ABAQUS model of a 25 m simply supported bridge under a truckload with different velocities was used to verify the accuracy of the proposed method. The structural damage was numerically modeled as cracks at the bottom of the bridge, so the stiffness at the damage positions was decreased accordingly. Four different velocities from 1 m/s to 8 m/s were used. The proposed method can identify structural damage in noisy environments without monitoring the dynamic modal parameters. Moreover, the accuracy of the newly proposed trendline-based method was increased compared to the previous method. For velocities up to 4 m/s, the damage in all single- and multiple-damage scenarios was successfully identified. For the velocity of 8 m/s, the damage in some scenarios was not located accurately. Additionally, it should be noted that the proposed method can be categorized as an online, quick, and baseline-free structural damage-detection method.
Characterization of Temperature and Strain Changes in Lithium-Ion Batteries Based on a Hinged Differential Lever Sensitization Fiber Bragg Grating Strain–Temperature Simultaneous-Measurement Sensor
Authors: Li Meng , Chen Weigen , Shen Zhiwei , Wang Ziyi , Ming Zifeng , Wang Changding , Tian Haoyuan , Sang Tianyi , Song Ruimin
Published: January 2024

Li-ion batteries are expected to become the mainstream devices for green energy storage or power supply in the future due to their advantages of high energy and power density and long cycle life. Monitoring the temperature and strain change characteristics of Li-ion batteries during operation is conducive to judging their safety performance. The hinged differential lever sensitization structure was used for strain sensitization in the design of an FBG sensor, which also allowed the simultaneous measurement of strain and temperature. The temperature and strain variation characteristics on the surface of a Li-ion soft-packed battery were measured using the des.igned sensor. This report found that the charging and discharging processes of Li-ion batteries are both exothermic processes, and exothermic heat release is greater when discharging than when charging. The strain on the surface of Li-ion batteries depends on electrochemical changes and thermal expansion effects during the charge and discharge processes. The charging process showed an increasing strain, and the discharging process showed a decreasing strain. Thermal expansion was found to be the primary cause of strain at high rates.
Sensor-to-Bone Calibration with the Fusion of IMU and Bi-Plane X-rays
Authors: Gasparutto Xavier , Rose-Dulcina Kevin , Grouvel Gautier , DiGiovanni Peter , Carcreff Lena , Hannouche Didier , Armand Stéphane
Published: January 2024

Inertial measurement units (IMUs) need sensor-to-segment calibration to measure human kinematics. Multiple methods exist, but, when assessing populations with locomotor function pathologies, multiple limitations arise, including holding postures (limited by joint pain and stiffness), performing specific tasks (limited by lack of selectivity) or hypothesis on limb alignment (limited by bone deformity and joint stiffness). We propose a sensor-to-bone calibration based on bi-plane X-rays and a specifically designed fusion box to measure IMU orientation with respect to underlying bones. Eight patients undergoing total hip arthroplasty with bi-plane X-rays in their clinical pathway participated in the study. Patients underwent bi-plane X-rays with fusion box and skin markers followed by a gait analysis with IMUs and a marker-based method. The validity of the pelvis, thigh and hip kinematics measured with a conventional sensor-to-segment calibration and with the sensor-to-bone calibration were compared. Results showed (1) the feasibility of the fusion of bi-plane X-rays and IMUs in measuring the orientation of anatomical axes, and (2) higher validity of the sensor-to-bone calibration for the pelvic tilt and similar validity for other degrees of freedom. The main strength of this novel calibration is to remove conventional hypotheses on joint and segment orientations that are frequently violated in pathological populations.
Two Proposals of a Simple Analog Conditioning Circuit for Remote Resistive Sensors with a Three-Wire Connection
Authors: Reverter Ferran
Published: January 2024

This article proposes and experimentally characterizes two implementations of a novel front-end circuit for three-wire connected resistive sensors with a wire-resistance compensation. The first implementation relies on two twin diodes, whereas the second on a switch; in both cases, those devices are non-remote (i.e., they are placed at the circuit end). The two circuit proposals have a square-wave input excitation so that a constant current with the two polarities is alternatively generated. Then, depending on that polarity, the current goes through either the sensor and the wire parasitic resistances or just the parasitic resistances. This generates a square-wave bipolar output signal whose average value, which is obtained by a low-pass filter, is proportional to the sensor resistance and only depends on the mismatch between two of the three wire resistances involved. Experimental tests applied to resistances related to a Pt100 thermal sensor show a remarkable linearity. For example, the switch-based front-end circuit offers a non-linearity error lower than 0.01% full-scale span, and this is practically insensitive to both the presence and the mismatch between the wire resistances.
Rapid Geometric Evaluation of Transportation Infrastructure Based on a Proposed Low-Cost Portable Mobile Laser Scanning System
Authors: Wang Haochen , Feng Dongming
Published: January 2024

Efficient geometric evaluation of roads and tunnels is crucial to traffic management, especially in post-disaster situations. This paper reports on a study of the geometric feature detection method based on multi-sensor mobile laser scanning (MLS) system data. A portable, low-cost system that can be mounted on vehicles and utilizes integrated laser scanning devices was developed. Coordinate systems and timestamps from numerous devices were merged to create 3D point clouds of objects being measured. Feature points reflecting the geometric information of measuring objects were retrieved based on changes in the point cloud’s shape, which contributed to measuring the road width, vertical clearance, and tunnel cross section. Self-developed software was used to conduct the measuring procedure, and a real-time online visualized platform was designed to reconstruct 3D models of the measured objects, forming a 3D digital map carrying the obtained geometric information. Finally, a case study was carried out. The measurement results of several representative nodes are discussed here, verifying the robustness of the proposed system. In addition, the main sources of interference are also discussed.
Efficient Cross-Modality Insulator Augmentation for Multi-Domain Insulator Defect Detection in UAV Images
Authors: Liu Yue , Huang Xinbo
Published: January 2024

Regular inspection of the insulator operating status is essential to ensure the safe and stable operation of the power system. Unmanned aerial vehicle (UAV) inspection has played an important role in transmission line inspection, replacing former manual inspection. With the development of deep learning technologies, deep learning-based insulator defect detection methods have drawn more and more attention and gained great improvement. However, former insulator defect detection methods mostly focus on designing complex refined network architecture, which will increase inference complexity in real applications. In this paper, we propose a novel efficient cross-modality insulator augmentation algorithm for multi-domain insulator defect detection to mimic real complex scenarios. It also alleviates the overfitting problem without adding the inference resources. The high-resolution insulator cross-modality translation (HICT) module is designed to generate multi-modality insulator images with rich texture information to eliminate the adverse effects of existing modality discrepancy. We propose the multi-domain insulator multi-scale spatial augmentation (MMA) module to simultaneously augment multi-domain insulator images with different spatial scales and leverage these fused images and location information to help the target model locate defects with various scales more accurately. Experimental results prove that the proposed cross-modality insulator augmentation algorithm can achieve superior performance in public UPID and SFID insulator defect datasets. Moreover, the proposed algorithm also gives a new perspective for improving insulator defect detection precision without adding inference resources, which is of great significance for advancing the detection of transmission lines.
From Anomaly Detection to Defect Classification
Authors: Klarák Jaromír , Andok Robert , Malík Peter , Kuric Ivan , Ritomský Mário , Klačková Ivana , Tsai Hung-Yin
Published: January 2024

This paper proposes a new approach to defect detection system design focused on exact damaged areas demonstrated through visual data containing gear wheel images. The main advantage of the system is the capability to detect a wide range of patterns of defects occurring in datasets. The methodology is built on three processes that combine different approaches from unsupervised and supervised methods. The first step is a search for anomalies, which is performed by defining the correct areas on the controlled object by using the autoencoder approach. As a result, the differences between the original and autoencoder-generated images are obtained. These are divided into clusters using the clustering method (DBSCAN). Based on the clusters, the regions of interest are subsequently defined and classified using the pre-trained Xception network classifier. The main result is a system capable of focusing on exact defect areas using the sequence of unsupervised learning (autoencoder)–unsupervised learning (clustering)–supervised learning (classification) methods (U2S-CNN). The outcome with tested samples was 177 detected regions and 205 occurring damaged areas. There were 108 regions detected correctly, and 69 regions were labeled incorrectly. This paper describes a proof of concept for defect detection by highlighting exact defect areas. It can be thus an alternative to using detectors such as YOLO methods, reconstructors, autoencoders, transformers, etc.
Transparency-Aware Segmentation of Glass Objects to Train RGB-Based Pose Estimators
Authors: Weidenbach Maira , Laue Tim , Frese Udo
Published: January 2024

Robotic manipulation requires object pose knowledge for the objects of interest. In order to perform typical household chores, a robot needs to be able to estimate 6D poses for objects such as water glasses or salad bowls. This is especially difficult for glass objects, as for these, depth data are mostly disturbed, and in RGB images, occluded objects are still visible. Thus, in this paper, we propose to redefine the ground-truth for training RGB-based pose estimators in two ways: (a) we apply a transparency-aware multisegmentation, in which an image pixel can belong to more than one object, and (b) we use transparency-aware bounding boxes, which always enclose whole objects, even if parts of an object are formally occluded by another object. The latter approach ensures that the size and scale of an object remain more consistent across different images. We train our pose estimator, which was originally designed for opaque objects, with three different ground-truth types on the ClearPose dataset. Just by changing the training data to our transparency-aware segmentation, with no additional glass-specific feature changes in the estimator, the ADD-S AUC value increases by 4.3%. Such a multisegmentation can be created for every dataset that provides a 3D model of the object and its ground-truth pose.
Cloud Digital Forensics: Beyond Tools, Techniques, and Challenges
Authors: Malik Annas Wasim , Bhatti David Samuel , Park Tae-Jin , Ishtiaq Hafiz Usama , Ryou Jae-Cheol , Kim Ki-Il
Published: January 2024

Cloud computing technology is rapidly becoming ubiquitous and indispensable. However, its widespread adoption also exposes organizations and individuals to a broad spectrum of potential threats. Despite the multiple advantages the cloud offers, organizations remain cautious about migrating their data and applications to the cloud due to fears of data breaches and security compromises. In light of these concerns, this study has conducted an in-depth examination of a variety of articles to enhance the comprehension of the challenges related to safeguarding and fortifying data within the cloud environment. Furthermore, the research has scrutinized several well-documented data breaches, analyzing the financial consequences they inflicted. Additionally, it scrutinizes the distinctions between conventional digital forensics and the forensic procedures specific to cloud computing. As a result of this investigation, the study has concluded by proposing potential opportunities for further research in this critical domain. By doing so, it contributes to our collective understanding of the complex panorama of cloud data protection and security, while acknowledging the evolving nature of technology and the need for ongoing exploration and innovation in this field. This study also helps in understanding the compound annual growth rate (CAGR) of cloud digital forensics, which is found to be quite high at ≈16.53% from 2023 to 2031. Moreover, its market is expected to reach ≈USD 36.9 billion by the year 2031; presently, it is ≈USD 11.21 billion, which shows that there are great opportunities for investment in this area. This study also strategically addresses emerging challenges in cloud digital forensics, providing a comprehensive approach to navigating and overcoming the complexities associated with the evolving landscape of cloud computing.
Effect of Sustainable Supply Chain Management on Procurement Environmental Performance: A Perspective on Resource Dependence Theory
Authors: Chiang Chi , Chuang Mei-Chen
Published: January 2024

To reduce medical waste, attention must be paid to the environmental friendliness of products during procurement. Thus, environmental awareness among hospital procurement personnel is crucial. Sustainable development, which effectively utilizes limited external resources, is the common goal of hospitals and suppliers. This study aims to establish a research framework that combines the theories of resource dependence and environmental relationship quality, incorporating environmental factors, subjective environmental norms, and perceived environmental values. Whether the environmental awareness of hospital procurement personnel is related to the quality of supplier relationships was investigated using a questionnaire survey method with hospital procurement personnel as the subjects. A total of 443 valid questionnaires were collected, and structural equation modeling was used to verify the hypotheses. The results show that (1) substitutability and uncertainty have a positive and significant effect on environmental relationship quality; (2) environmental subjective norms have a positive and significant effect on environmental relationship quality; (3) importance and perceived environmental value have a positive and significant effect on environmental commitment; (4) environmental relationship quality has a positive and significant effect on environmental performance. These results provide a reference for the promotion of relevant policies, education, and training in medical institutions.
An Electrochemical Performance Model Considering of Non-Uniform Gas Distribution Based on Porous Media Method in PEMFC Stack
Authors: Zhang Zhiming , Quan Chenfu , Wu Sai , Zhang Tong , Zhang Jinming
Published: January 2024

Proton exchange membrane fuel cell (PEMFC) is significant and favorable to the long-range and short refueling time in the vehicle industry. However, the non-uniform distribution of gas flow supply, particularly in the fuel cell stack is neglected in the electrochemical model for PEMFC performance optimization. The purpose of this study is to break through this limitation to establish an optimized electrochemical fuel cell performance model, with porous media methods considering the non-uniform gas flow distribution in fuel cell stack with different compression of the gas distribution layer (GDL). The numerical models are validated by experimentation of a practical fuel cell stack. For the established fuel cell model, there is a 5% difference between the maximum and minimum speeds of various flow channels in the anode flow field under 10% GDL compression. Furthermore, the single-channel electrochemical performance model is optimized by considering the non-uniform gas flow distribution of the fuel cell stack. The results of the optimized electrochemical fuel cell performance model demonstrate that the correlation coefficient between the experiment results and the simulation results is nearly 99.50%, which is higher than that of the original model under 20% GDL compression. This established model is effective in enhancing the prediction accuracy of the PEMFC performance.
The High-Resolution Calibration of the Topographic Wetness Index Using PAZ Satellite Radar Data to Determine the Optimal Positions for the Placement of Smart Sustainable Drainage Systems (SuDS) in Urban Environments
Authors: Allende-Prieto Cristina , Roces-García Jorge , Sañudo-Fontaneda Luis Ángel
Published: January 2024

This study addresses the growing interest in utilizing remote sensing tools for locating sustainable drainage systems (SuDS) in urban environments. SuDS, recognized as Nature-based Solutions (NbS), play a crucial role in enhancing urban resilience against climate change. This study focuses on the calibration process required to establish a correlation between the Topographic Wetness Index (TWI), derived from high-precision digital elevation models (DEMs), and soil moisture (SM) data obtained from satellite imaging. This calibration serves as a method to optimize the placement of sustainable urban drainage system vegetated techniques in urban areas. This study leveraged the exceptional resolution of PAZ satellite radar data to effectively detect variations in SM, particularly in grass-type vegetated land. The sensitivity of the X-band radar signal to moisture levels and changes in ground roughness proved valuable in tracking SM dynamics. The core of the study involved deriving the TWI from a high-resolution digital terrain model (DTM). The correlation between the TWI and SM values demonstrates robustness, with an R2 value of 0.77. These findings significantly advance the calibration of TWI values with SM measurements, enhancing their practicality in identifying areas prone to water accumulation. The study’s outcomes provide valuable insights for guiding the strategic placement of SuDS in urban environments, contributing to the effective management of water-related challenges in the face of urbanization and climate change.
Assessing Environmental Management Plan Implementation in Water Supply Construction Projects: Key Performance Indicators
Authors: Radzi Afiqah R. , Farouk Abdelrahman M. , Romali Noor Suraya , Farouk Mohamed , Elgamal Mohamed , Rahman Rahimi A.
Published: January 2024

Assessing the implementation of environmental management plans (EMPs) in construction projects is crucial for meeting environmental sustainability goals and reducing potential adverse impacts. By using performance indicators (PIs), stakeholders can objectively measure the performance of EMP implementation, identifying areas of success and areas that may require improvement. Therefore, this study aims to examine the PIs for assessing EMP implementation in water supply construction projects, using Saudi Arabia as a case study. Data from semi-structured interviews and a systematic literature review were used to develop a potential list of PIs. Then, the PIs were used to create a survey and distributed to industry professionals. Data from 112 respondents were analyzed using mean ranking analysis, the normalization method, exploratory factor analysis (EFA), and fuzzy synthetic evaluation (FSE). Eighteen critical PIs for assessing EMP implementation in water supply construction projects were identified, including public safety, road safety hazards, construction waste, clogged drainage, irregular flooding, the spilling of chemical substances, slope failures, soil erosion, landslide occurrence, increased schedule waste, changes in the color of bodies of water, oil/fuel spills, restricted site accessibility, the smell of run-off water, traffic accidents on construction sites, the spread of disease, changes in the color of run-off water, and overflowing silt traps. The EFA revealed that PIs can be grouped into three underlying constructs: fluid-related indicators, health and safety-related indicators, and site environment-related indicators. The FSE results confirmed that all PIs are between moderately critical to critical. This study’s significance lies in its examination of PIs that aim to improve the environmental performance of water supply construction projects. Understanding which indicators are most effective allows for targeted improvements, helping to minimize negative environmental impacts and ensuring sustainable practices. Finally, this study is a pioneer in examining the critical PIs for assessing EMP implementation in water supply construction projects.
Metabolism and Urban Design: Insights from the Champs–Elysées, Paris
Authors: Doussard Claire , Rowe Peter G. , Detavernier Pauline , Guo Boya
Published: January 2024

The urban metabolism concept is crucial for understanding city–environment interactions. Yet, its use in urban design is limited, and the examination of diverse design hypotheses with the potential to influence metabolic activities is seldom undertaken. This research addresses this gap and aims to analyze how the concept of metabolism (1) Can be leveraged by professionals for making urban design hypotheses, and (2) allows for the assessment of each of these hypotheses to reduce adverse environmental impacts and inform urban design decisions. Focusing on Paris’ Champs–Elysées redesign, in collaboration with PCA-STREAM, an urban design and architecture firm, this research employs fieldwork observations, tenant/store owner interviews, and specific metabolic models for water, energy, and materials. The results demonstrate that while redesigning the avenue’s public space potentially impacts the whole Champs–Elysées metabolism, this impact remains relatively limited. Intervening on objects with higher metabolic activities and using more efficient technologies might be more fruitful in terms of adverse environmental impact reduction, at least in this context.
Evaluation, Driving Mechanism and Spatial Correlation Analysis of Atmospheric Environmental Efficiency in the “2+26” Cities Based on the Nonradial MEA Model
Authors: Jiang Yiru , Wang Xinjun
Published: January 2024

The “2+26” cities are 26 cities in Beijing, Tianjin and the surrounding cities, constituting a region characterized by economic prosperity and diverse industries but plagued by severe atmospheric pollution. As a focal area for atmospheric pollution control, a scientific assessment of atmospheric environmental efficiency in the “2+26” cities that measures the degree of coordination between the economy and air pollution is very important for winning the battle of blue sky defense. Based on this, this study comprehensively used the nonradial multi-directional efficiency analysis (MEA) model, Global Reference Malmquist Model and spatial correlation analysis to evaluate the atmospheric environmental efficiency, calculate the driving factors and explore the spatiotemporal distribution characteristics of the “2+26” cities from 2009 to 2018. The research findings indicate the following: (1) Atmospheric environmental efficiency showed a trend of first decreasing and then increasing, with a significant improvement potential of 26.7% in the future. (2) There was a significant discrepancy between the best- and worst-performing cities, with the best being 0.910 and the worst being 0.573, demonstrating imbalanced development between cities. The relatively low-efficiency cities were mainly located in Hebei, Shanxi and Henan provinces. (3) A value of technological efficiency change (EC) less than 1 was the main restrictive factor for improving atmospheric environmental efficiency, whereas a value of technological change (TC) greater than 1 enhanced it. (4) The atmospheric environmental efficiency presented a distinct spatial distribution pattern of high–high and low–low aggregation, forming high-value areas centered in the Beijing–Tianjin region and along the Zibo–Zhengzhou line. The western and central regions were relatively low, whereas the northern and eastern regions were relatively high, with significant regional differences in spatial distribution. The conclusions from this article’s empirical analysis can help concerned developing countries determine key factors to improve their atmospheric environmental efficiency and then formulate policies for sustainable economic and environmental development.
Anti-Software Attack Ear Identification System Using Deep Feature Learning and Blockchain Protection
Authors: Xu Xuebin , Liu Yibiao , Liu Chenguang , Lu Longbin
Published: January 2024

Ear recognition has made good progress as an emerging biometric technology. However, the recognition performance, generalization ability, and feature robustness of ear recognition systems based on hand-crafted features are relatively poor. With the development of deep learning, these problems have been partly overcome. However, the recognition performance of existing ear recognition systems still needs to be improved when facing unconstrained ear databases in realistic scenarios. Another critical problem is that most systems with ear feature template databases are vulnerable to software attacks that disclose users’ privacy and even bring down the system. This paper proposes a software-attack-proof ear recognition system using deep feature learning and blockchain protection to address the problem that the recognition performance of existing systems is generally poor in the face of unconstrained ear databases in realistic scenarios. First, we propose an accommodative DropBlock (AccDrop) to generate drop masks with adaptive shapes. It has an advantage over DropBlock in coping with unconstrained ear databases. Second, we introduce a simple and parameterless attention module that uses 3D weights to refine the ear features output from the convolutional layer. To protect the security of the ear feature template database and the user’s privacy, we use Merkle tree nodes to store the ear feature templates, ensuring the determinism of the root node in the smart contract. We achieve Rank-1 (R1) recognition accuracies of 83.87% and 96.52% on the AWE and EARVN1.0 ear databases, which outperform most advanced ear recognition systems.
Covering Factor of the Dust-Driven Broad-Line Region Clouds
Authors: Naddaf Mohammad-Hassan , Czerny Bożena
Published: January 2024

The origin of the broad-line region (BLR) clouds in active galactic nuclei is still under discussion. We develop a scenario in which the clouds in the outer, less ionized part of the BLR are launched by the radiation pressure acting on dust. Most of the outflow forms a failed wind, so we refer to it as failed radiatively accelerated dusty outflow (FRADO), but, for a certain parameter range, actual outflow also takes place. We aim to test the model predictions. In this paper, we present the calculation of the angular distribution of clouds and the net covering factor as this affects the fraction of radiation that can be intercepted and reprocessed in the form of the Hβ or Mg II emission line. The results reveal that the covering factor is intricately linked to the mass, accretion rate, and metallicity of the clouds. Notably, as these parameters increase, so does the covering factor, shedding light on the dynamic interplay between the central engine and the surrounding material in AGNs.
Timely Monitoring of SARS-CoV-2 RNA Fragments in Wastewater Shows the Emergence of JN.1 (BA.2.86.1.1, Clade 23I) in Berlin, Germany
Authors: Bartel Alexander , Grau José Horacio , Bitzegeio Julia , Werber Dirk , Linzner Nico , Schumacher Vera , Garske Sonja , Liere Karsten , Hackenbeck Thomas , Rupp Sofia Isabell , Sagebiel Daniel , Böckelmann Uta , Meixner Martin
Published: January 2024

The importance of COVID-19 surveillance from wastewater continues to grow since case-based surveillance in the general population has been scaled back world-wide. In Berlin, Germany, quantitative and genomic wastewater monitoring for SARS-CoV-2 is performed in three wastewater treatment plants (WWTP) covering 84% of the population since December 2021. The SARS-CoV-2 Omicron sublineage JN.1 (B.2.86.1.1), was first identified from wastewater on 22 October 2023 and rapidly became the dominant sublineage. This change was accompanied by a parallel and still ongoing increase in the notification-based 7-day-hospitalization incidence of COVID-19 and COVID-19 ICU utilization, indicating increasing COVID-19 activity in the (hospital-prone) population and a higher strain on the healthcare system. In retrospect, unique mutations of JN.1 could be identified in wastewater as early as September 2023 but were of unknown relevance at the time. The timely detection of new sublineages in wastewater therefore depends on the availability of new sequences from GISAID and updates to Pango lineage definitions and Nextclade. We show that genomic wastewater surveillance provides timely public health evidence on a regional level, complementing the existing indicators.
Genetic Characteristics of Wuxiang Virus in Shanxi Province, China
Authors: Zheng Yuke , Tian Xiaodong , Wang Ruichen , Yao Xiaohui , Zhang Weijia , Yin Qikai , Li Fan , Nie Kai , Cui Qianqian , Xu Songtao , Fu Shihong , Li Hao , Cheng Jingxia , Wang Huanyu
Published: January 2024

Wuxiang virus (WUXV) is the first sandfly-borne Phlebovirus isolated from Phlebotomus chinensis collected in China and has been established as a consistent viral presence in the local sandfly populations of both Wuxiang County and Yangquan City. However, its distribution in the Shanxi Province remains unclear. In this study, three novel WUXV strains were isolated from sandflies collected from Jiexiu City, Shanxi Province, China, in 2022. Subsequently, whole-genome sequences of these novel strains were generated using next-generation sequencing. The open reading frame (ORF) sequences of the WUXV strains from the three locations were subjected to gene analysis. Phylogenetic analysis revealed that WUXV belongs to two distinct clades with geographical differences. Strains from Wuxiang County and Yangquan City belonged to clade 1, whereas strains from Jiexiu City belonged to clade 2. Reassortment and recombination analyses indicated no gene reassortment or recombination between the two clades. However, four reassortments or recombination events could be detected in clade 1 strains. By aligning the amino acid sequences, eighty-seven mutation sites were identified between the two clades, with seventeen, sixty, nine, and one site(s) in the proteins RdRp, M, NSs, and N, respectively. Additionally, selection pressure analysis identified 17 positively selected sites across the entire genome of WUXV, with two, thirteen, one, and one site(s) in the proteins RdRp, M, NSs, and N, respectively. Notably, sites M-312 and M-340 in the M segment not only represented mutation sites but also showed positive selective pressure effects. These findings highlight the need for continuous nationwide surveillance of WUXV.
Haemato-Immunological Response of Immunized Atlantic Salmon (Salmo salar) to Moritella viscosa Challenge and Antigens
Authors: Ghasemieshkaftaki Maryam , Cao Trung , Hossain Ahmed , Vasquez Ignacio , Santander Javier
Published: January 2024

Winter ulcer disease is a health issue in the Atlantic salmonid aquaculture industry, mainly caused by Moritella viscosa. Although vaccination is one of the effective ways to prevent bacterial outbreaks in the salmon farming industry, ulcer disease related to bacterial infections is being reported on Canada’s Atlantic coast. Here, we studied the immune response of farmed immunized Atlantic salmon to bath and intraperitoneal (ip) M. viscosa challenges and evaluated the immunogenicity of M. viscosa cell components. IgM titers were determined after infection, post boost immunization, and post challenge with M. viscosa. IgM+ (B cell) in the spleen and blood cell populations were also identified and quantified by 3,3 dihexyloxacarbocyanine (DiOC6) and IgM-Texas red using confocal microscopy and flow cytometry. At 14 days post challenge, IgM was detected in the serum and spleen. There was a significant increase in circulating neutrophils 3 days after ip and bath challenges in the M. viscosa outer membrane vesicles (OMVs) boosted group compared to non-boosted. Lymphocytes increased in the blood at 7 and 14 days after the ip and bath challenges, respectively, in OMVs boosted group. Furthermore, a rise in IgM titers was detected in the OMVs boosted group. We determined that a commercial vaccine is effective against M. viscosa strain, and OMVs are the most immunogenic component of M. viscosa cells.
Characteristics of the Spatial and Temporal Distribution of Drought in Northeast China, 1961–2020
Authors: Wang Rui , Zhang Xiaoxuan , Guo Enliang , Cong Longpeng , Wang Yilin
Published: January 2024

Under global climate warming, the global water cycle is further accelerating, the risk of drought is increasing, and the instability and sustainability of agricultural production are seriously threatened. Northeast China, as the “granary” of China, located in the mid-high latitudes of the Northern Hemisphere, is one of the regions strongly influenced by droughts. Thus, studying the spatial and temporal distribution of drought is helpful for the development of methods for forecasting potential drought hazards in Northeast China. This study used observed data from 86 meteorological stations in Northeast China from 1961 to 2020 to calculate the standardized precipitation evapotranspiration index (SPEI) at different time scales for the past 60 years and analyzed the spatial and temporal characteristics of drought in Northeast China based on the run theory and the Mann-Kendall test. The SPEI at the annual scale showed decreasing trends with no significant mutation point. Seasonally, there was a decreasing trend of the SPEI in summer and autumn and an increasing trend in spring and winter, which indicates that drought in Northeast China has decreased in winter and spring. The annual drought frequency ranged from 25.5% to 37.6%, and the spatial characteristics of the frequency of moderate drought, severe drought, and extreme drought, respectively, showed the following distribution patterns from the western region to the central region and then to the eastern region of Northeast China: “high-low-high”, “low-high-low”, and “gradually decreasing”.
Thermal Effects on the Soil Water Retention Curves and Hydraulic Properties of Benggang Soil in Southern China
Authors: Yang Yuke , Yang Lu , Zhao Dongfeng , Guo Yongjia , Lin Jinshi , Jiang Fangshi , Huang Yanhe , Zhang Yue
Published: January 2024

Soil hydraulic properties significantly affect the occurrence and development of collapsing gully walls. The effect of temperature on the hydraulic properties of soil in collapsing gully walls remains unclear. In this study, the hydraulic properties of the red soil layer, the sandy soil layer and the detritus layer in a collapsing gully wall were investigated using the filter paper method, and the soil water retention curves of the different soil layers at 25 and 40 °C were determined. The aim of this study was to investigate the impact of temperature on the soil hydraulic properties of different soil layers in collapsing gully walls. The study found that when the water content in the red soil layer and sandy soil layer exceeded 20% and in the detritus layer exceeded 10%, the soil’s matric suction significantly decreased as the temperature increased from 25 to 40 °C. Additionally, the parameters of θs, α, n and m all exhibited a decreasing trend, and the soil water content in the detritus layer was primarily influenced by the temperature change, which resulted in a decrease of 38.10%. The unsaturated hydraulic conductivity of the detritus layer exhibited higher values than that of the sandy layer and red soil layer under identical temperature conditions. Moreover, the unsaturated hydraulic conductivity of the red soil layer, sandy soil layer and detritus layer increased with increasing temperature. It was observed that the unsaturated hydraulic conductivity of the detritus layer increased by 0.18 cm h−1 at a soil water content of 44%. This increase in conductivity was more pronounced than the corresponding changes in the red soil layer and sandy soil layer. An elevated temperature caused the water-holding capacity of the different soil layers of the collapsing gully wall to decrease and the unsaturated hydraulic conductivity to increase. However, the influence of the clay particle content within the soil of the collapsing gully wall rendered the temperature effect more distinct. Therefore, the destabilizing deformation of the soil in the collapsing gully wall during the summer under high temperatures and precipitation may have played a key role in its collapse.
The COVID-19 Pandemic Impact of Hospital Wastewater on Aquatic Systems in Bucharest
Authors: Banciu Alina Roxana , Pascu Luoana Florentina , Radulescu Dragos Mihai , Stoica Catalina , Gheorghe Stefania , Lucaciu Irina , Ciobotaru Florin Valentin , Novac Laura , Manea Catalin , Nita-Lazar Mihai
Published: January 2024

The COVID-19 pandemic reshaped the global response to a pandemic, including the way of using chemical compounds such as disinfectants and antibiotics. The large-scale use of antibiotics and disinfectants during the COVID-19 pandemic caused environmental pressure not only due to the chemicals themselves but also due to their effect on bacterial communities, inducing resistance to chemicals and changing the population structure of bacterial communities, especially in aquatic environments. The dissemination of fecal bacteria, including antibiotic-resistant bacteria, and pathogens from hospital wastewater into the environment, via wastewater treatment plants (WWTPs), triggered the premises of a major public health issue. Rivers flowing through cities are natural streams for WWTP discharges, and they directly bear the impact of anthropic activities, disseminating domestic and industrial pollution over large areas. The aim of the present study was to assess the microbiological bacterial structure of municipal and hospital wastewaters as well as their impact on natural streams, covering the pre-to post-COVID-19 pandemic period of time. The results indicated that the COVID-19 pandemic had a direct impact on hospital wastewater microbiological quality and the environment due to an excessive use of antibiotics and disinfectants. In addition, the constant presence of antibacterial compounds increased the rate of bacterial selection and induced population structural changes in the bacterial communities from aquatic systems.
Creation of virtual models of buildings for the formation of unified real estate complexes as a part of land and cadastral works
Authors:   Department of Geodesy and Remote Sensing, Federal State Budgetary Educational Institution of Higher Education Omsk State Agrarian University, Parkhomenko N. A. , Nugmanov A. A. ,   Department of Geodesy and Remote Sensing, Federal State Budgetary Educational Institution of Higher Education Omsk State Agrarian University, Garagul A. S. ,   Department of Geodesy and Remote Sensing, Federal State Budgetary Educational Institution of Higher Education Omsk State Agrarian University
Published: January 2024

The article presents the results of the research project to create 3D models of buildings from digital images using a smartphone camera and the Agisoft Photoscan Professional software, comparing them with data obtained with an electronic total station. The authors outlined the possibilities of using the described technologies for the development of 3D cadastre, which can simplify creation of virtual models through the adaptation of modern widgets. The technological sequence of creating a building model in a virtual format and the accuracy of linear measurements are considered here. The paper contains the results of determining the area and the value of the mean square error. The authors presume that these technologies can be used for the development of 3D cadastre in the formation of unified real estate complexes as a part of land cadastral works, as well as for design and reconstruction solutions.
Influence of feed mixtures on the productivity of cows and chemical composition of milk during the period of increasing the milk yield
Authors:   Federal State Budgetary Educational Institution of Higher Education “Northern Trans-Ural State Agricultural University”, Russia, Tyumen, Karmatskikh Yu. A. , Ivanova I. E. ,   Federal State Budgetary Educational Institution of Higher Education “Northern Trans-Ural State Agricultural University”, Russia, Tyumen, Kostomakhin N. M. ,   Federal State Budgetary Educational Institution of Higher Education “Russian State Agrarian University – Moscow Timiryazev Agricultural Academy”, Russia, Moscow
Published: January 2024

There is a wide variety of climatic zones in the huge territories of our country, which require special approaches to feeding and housing of animals. Providing animals with adequate and rationed feeding under the conditions of the Northern Trans-Urals and Siberia is a difficult task due to the long stall period. The purpose of the work was to determine the infl uence of diff erent methods of feed distribution such as separate and feed mixture on milk productivity of cows and the chemical composition of milk during the period of increasing the milk yield. It was found that the milk yield of natural fat content during the fi rst 100 days of lactation in the experimental group of cows was 325 kg or 10,21 % higher than in the control group. Milk fat yield was obtained from the cows of the experimental group by 16,5 kg or 13,80 % more compared to the animals of the control group. The mass fraction of fat in the milk of cows in the experimental group was higher by 0,12 abs.%. However, the difference between groups in milk yield, milk fat content and milk fat yield was statistically insignificant. The difference in the content of protein, ash, calcium and phosphorus in the milk of the experimental animals was also insignificant, although there was some advantage in the content of these indicators in the experimental group, where the feed was fed in the form of the feed mixture. It was found when analyzing economic indicators that for cows in the control group the prime-cost of 1 kg of milk was 16,49 rubles, which was by 1,53 rubles or 3,91 % more than in the experimental group. At the same time, the level of profitability of milk production in the experimental group was higher than 12,66 abs.% compared to the control group.