bluuebunny/crossref_metadata_2025 huggingface dataset:
The Arago–Poisson Spot: New Applications for an Old Concept
Authors: Emile Olivier , Emile Janine
Published: January 2024

Herein, we report some specific properties and applications of the so-called Arago–Poisson spot in optics. This spot results from the diffraction of a plane wave by an occulting disk that leads to a small bright spot in its shadow. We discuss some of the properties of such beams. In particular, we focus on the ultimate size that can be reached for these beams, which depends on the diameter of the disk, the wavelength, and the distance from the disk. We also highlight self-healing and faster-than-light properties. Applications are then proposed. The applications mainly deal with new traps with nanometer sizes dedicated to the trapping of nanoparticles. We also discuss beams that change frequency during propagation and their application for signal delivery in a precise and determined area.
Mlo-Mediated Broad-Spectrum and Durable Resistance against Powdery Mildews and Its Current and Future Applications
Authors: Dreiseitl Antonín
Published: January 2024

Mlo is a well-known broad-spectrum recessively inherited monogenic durable resistance to powdery mildew caused by Blumeria hordei found first in barley, originally in an induced mutant in 1942 and later in other mutants and also in Ethiopian landraces. The first commercial varieties possessing Mlo resistance were released during 1979–1986, but these often showed symptoms of necrotic leaf spotting associated with reduced grain yield. However, this yield penalty was successfully reduced by breeding Mlo-resistant varieties of spring barley predominate in Europe; for example, in the Czech Republic, their ratio surpassed 90% of the total number of newly released varieties. However, outside Europe, Mlo-varieties are not yet popular and can be exploited more widely. Winter barley varieties are generally non-resistant, but the use of Mlo for their breeding is controversial despite the limited adaptability of the pathogen to this resistance. The renewal of mechanically disturbed epidermal plant cell walls, including the penetration of mildews, is common in plants, and the Mlo-type resistance is exploited in many other crop species, including wheat.
Comparative Transcriptome Analysis Provides Insights into the Effect of Epicuticular Wax Accumulation on Salt Stress in Coconuts
Authors: Sun Xiwei , Kaleri Ghulam Abid , Mu Zhihua , Feng Yalan , Yang Zhuang , Zhong Yazhu , Dou Yajing , Xu Hang , Zhou Junjie , Luo Jie , Xiao Yong
Published: January 2024

The coconut is an important tropical economical crop and exhibits high tolerance to various types of salinity stress. However, little is known about the molecular mechanism underlying its salt tolerance. In this study, RNA-Seq was applied to examine the different genes expressed in four coconut varieties when exposed to a salt environment, resulting in the generation of data for 48 transcriptomes. Comparative transcriptome analysis showed that some genes involved in cutin and wax biosynthesis were significantly upregulated in salt treatment compared to the control, including CYP86A4, HTH, CER1, CER2, CER3, DCR, GPAT4, LTP3, LTP4, and LTP5. In particular, the expression of CER2 was induced more than sixfold, with an RPKM value of up to 205 ten days after salt treatment in Hainan Tall coconut, demonstrating superior capacity in salt tolerance compared to dwarf coconut varieties. However, for yellow dwarf and red dwarf coconut varieties, the expression level of the CER2 gene was low at four different time points after exposure to salt treatment, suggesting that this gene may contribute to the divergence in salt tolerance between tall and dwarf coconut varieties. Cytological evidence showed a higher abundance of cuticle accumulation in tall coconut and severe damage to cuticular wax in dwarf coconut.
Multivariate Analysis Compares and Evaluates Heat Tolerance of Potato Germplasm
Authors: Zhang Sujie , Ye Han , Kong Lingshuang , Li Xiaoyu , Chen Yeqing , Wang Shipeng , Liu Bailin
Published: January 2024

High temperature is the most important environmental factor limiting potato (Solanum tuberosum L.) yield. The tuber yield has been used to evaluate the heat tolerance of some potato cultivars, but potato yield was closely correlated with the maturation period. Therefore, it is necessary to employ different parameters to comprehensively analyze and evaluate potato tolerance to heat stress. This study aimed to investigate physiologic changes during growth and development, and develop accurate heat tolerance evaluation methods of potato cultivars under heat stress. About 93 cultivars (including foreign elite lines, local landraces and cultivars) were screened using an in vitro tuber-inducing system (continuous darkness and 8% sucrose in the culture medium) under heat stress (30 °C) and normal (22 °C) conditions for 30 days. The tuber yield and number decreased significantly under heat stress compared to the control. A total of 42 cultivars were initially selected depending on tuber formation, after in vitro screening, further testing of selected cultivars was conducted in ex vitro conditions. The screened cultivars were further exposed to heat stress (35 °C/28 °C, day/night) for 60 days. Heat stress led to an increase in the plant height growth rate, fourth internode growth rate, and membrane damage, and due to heat-induced damage to chloroplasts, decrease in chlorophyll biosynthesis and photosynthetic efficiency. Three principal components were extracted by principal component analysis. Correlation and regression analysis showed that heat tolerance is positively correlated with the plant height growth rate, fourth internode growth rate, the content of chlorophyll b, photosynthetic rate, stomatal conductance, transpiration rate, tuber number, and tuber yield, and negatively correlated with the cell membrane injury level. The nine traits are accurate and representative indicators for evaluating potato tolerance to heat stress and could determine a relatively high mean forecast accuracy of 100.0% for the comprehensive evaluation value. Through cluster analysis and screening, cultivar FA, D73, and C132 had the highest heat comprehensive evaluation value, which could be further selected as heat-resistant varieties. This study provides insights into the different physiological mechanisms and accurate evaluation methods of potato cultivars under heat stress, which could be valuable for further research and breeding.
Nutritional and Chemical Quality of Maize Hybrids from Different FAO Maturity Groups Developed and Grown in Serbia
Authors: Djalovic Ivica , Grahovac Nada , Stojanović Zorica , Đurović Ana , Živančev Dragan , Jakšić Snežana , Jaćimović Simona , Tian Caihuan , Prasad P. V. Vara
Published: January 2024

Maize is a globally significant cereal crop, contributing to the production of essential food products and serving as a pivotal resource for diverse industrial applications. This study investigated the proximate analysis of maize hybrids from different FAO maturity groups in Serbia, exploring variations in polyphenols, flavonoids, carotenoids, tocopherols, and fatty acids with the aim of understanding how agroecological conditions influence the nutritional potential of maize hybrids. The results indicate substantial variations in nutritional composition and antioxidant properties among different maturity groups. The levels of total polyphenols varied among FAO groups, indicating that specific hybrids may offer greater health benefits. Flavonoids and carotenoids also showed considerable variation, with implications for nutritional quality. Tocopherol content varied significantly, emphasizing the diversity in antioxidant capacity. Fatty acid analysis revealed high levels of unsaturated fatty acids, particularly linoleic acid, indicating favorable nutritional and industrial properties. The study highlights the importance of considering maturity groups in assessing the nutritional potential of maize hybrids.
Fruit Quality Attributes of Organically Grown Norwegian Apples Are Affected by Cultivar and Location
Authors: Natić Maja , Dabić Zagorac Dragana , Jakanovski Mihajlo , Smailagić Anita , Čolić Slavica , Meland Mekjell , Fotirić Akšić Milica
Published: January 2024

In this work, 12 apple cultivars grown organically in three regions of Norway (Telemark, Ullensvang, Viken) were analyzed in terms of fruit quality, with the aim of equating different growing regions under specific climatic conditions. Apples were analyzed for concentration levels of minerals, sugars, sugar alcohols, organic acids, total phenolic content (TPC), radical scavenging activity (RSA), and phenolic profiles. Discovery “Rose” from Telemark stored the highest level of minerals (24,094.5 mg/kg dry weight). Glucose, fructose, sucrose, and sorbitol were the major carbohydrates, whereas the predominant organic acids were quinic acid and malic acid. Cultivar Discovery from Ullensvang had the highest TPC (9.22 g/kg) and RSA (229.32 mmol TE/kg). Of the polyphenols quantified, chlorogenic acid and kaempferol-3-O-glucoside were the most abounded, accounting for 85.50%. Principal component analysis (PCA) shows that the Ullensvang region is the richest source of most carbohydrates, organic acids (quinic, shikimic, and galacturonic), and most polyphenols, whereas the highest content of minerals and maleic acid characterized Viken. Regardless of location, the Discovery cultivar had, on average, the highest sugar and polyphenol contents. The results obtained suggest that organic apples from Norway are a rich source of beneficial compounds that can have a positive impact on human health. In addition, these results may be useful for consumers in identifying apple cultivars with desirable characteristics and for the fruit industry in tracing back the origin of apples. The findings could also be of great interest for locations with similar climate and soil conditions worldwide.
Transboundary Central African Protected Area Complexes Demonstrate Varied Effectiveness in Reducing Predicted Risk of Deforestation Attributed to Small-Scale Agriculture
Authors: Bernhard Katie P. , Shapiro Aurélie C. , d’Annunzio Rémi , Kabuanga Joël Masimo
Published: January 2024

The forests of Central Africa constitute the continent’s largest continuous tract of forest, maintained in part by over 200 protected areas across six countries with varying levels of restriction and enforcement. Despite protection, these Central African forests are subject to a multitude of overlapping proximate and underlying drivers of deforestation and degradation, such as conversion to small-scale agriculture. This pilot study explored whether transboundary protected area complexes featuring mixed resource-use restriction categories are effective in reducing the predicted disturbance risk to intact forests attributed to small-scale agriculture. At two transboundary protected area complex sites in Central Africa, we used Google Earth Engine and a suite of earth observation (EO) data, including a dataset derived using a replicable, open-source methodology stemming from a regional collaboration, to predict the increased risk of deforestation and degradation of intact forests caused by small-scale agriculture. For each complex, we then statistically compared the predicted increased risk between protected and unprotected forests for a stratified random sample of 2 km sites (n = 4000). We found varied effectiveness of protected areas for reducing the predicted risk of deforestation and degradation to intact forests attributed to agriculture by both the site and category of protected areas within the complex. Our early results have implications for sustainable agriculture development, forest conservation, and protected areas management and provide a direction for future research into spatial planning. Spatial planning could optimize the configuration of protected area types within transboundary complexes to achieve both forest conservation and sustainable agricultural production outcomes.
Aerosol Optical Properties Retrieved by Polarization Raman Lidar: Methodology and Strategy of a Quality-Assurance Tool
Authors: Mao Song , Yin Zhenping , Wang Longlong , Wei Yubin , Bu Zhichao , Chen Yubao , Dai Yaru , Müller Detlef , Wang Xuan
Published: January 2024

Aerosol optical properties retrieved using polarization Raman lidar observations play an increasingly vital role in meteorology and environmental protection. The quality of the data products directly affects the impact of relevant scientific applications. However, the quality of aerosol optical properties retrieved from polarization Raman lidar signals is difficult to assess. Various factors, such as hardware system performance, retrieval algorithm, and meteorological conditions at the observation site, influence data quality. In this study, we propose a method that allows for assessing the reliability of aerosol optical properties derived from polarization Raman lidar observations. We analyze the factors that affect the reliability of retrieved aerosol optical properties. We use scoring methods combined with a weight-assignment scheme to evaluate the quality of the retrieved aerosol optical properties. The scores and weights of each factor are arranged based on our analysis of a simulation study and the characteristics of each factor. We developed an automatic retrieval algorithm that allows for deriving homogeneous aerosol optical data sets. We also assess with this method the quality of retrieved aerosol optical properties obtained with different polarization Raman lidars under different measurement scenarios. Our results show that the proposed quality assurance method can distinguish the reliability of the retrieved aerosol optical properties.
Design and Implementation of a Hybrid Optical Camera Communication System for Indoor Applications
Authors: Nguyen Huy , Le Nam Tuan , Le Duy Tuan Anh , Jang Yeong Min
Published: January 2024

Optical wireless communication is a promising emerging technology that addresses the limitations of radio-frequency-based wireless technologies. This study presents a new hybrid modulation method for optical camera communication (OCC), which integrates two waveforms transmitted from a single transmitter light-emitting diode (LED) and receives data through two rolling shutter camera devices on the receiver side. Then, a smart camera with a high-resolution image sensor captures the high-frequency signal, and a low-resolution image sensor from a smartphone camera captures the low-frequency signal. Based on this hybrid scheme, two data streams are transmitted from a single LED, which reduces the cost of the indoor OCC device compared with transmitting two signals from two different LEDs. In the proposed scheme, rolling-shutter orthogonal frequency-division multiplexing is used for the high-frequency signals, and M-ary frequency-shift keying is used for the low-frequency signals in the time domain. This proposed scheme is compatible with smartphone and USB cameras. By controlling the OCC parameters, the hybrid scheme can be implemented with high performance for a communication distance of 10 m.
Development of an Effective Corruption-Related Scenario-Based Testing Approach for Robustness Verification and Enhancement of Perception Systems in Autonomous Driving
Authors: Hsiang Huang , Chen Yung-Yuan
Published: January 2024

Given that sensor-based perception systems are utilized in autonomous vehicle applications, it is essential to validate such systems to ensure their robustness before they are deployed. In this study, we propose a comprehensive simulation-based process to verify and enhance the robustness of sensor-based perception systems in relation to corruption. Firstly, we introduce a methodology and scenario-based corruption generation tool for creating a variety of simulated test scenarios. These scenarios can effectively mimic real-world traffic environments, with a focus on corruption types that are related to safety concerns. An effective corruption similarity filtering algorithm is then proposed to eliminate corruption types with high similarity and identify representative corruption types that encompass all considered corruption types. As a result, we can create efficient test scenarios for corruption-related robustness with reduced testing time and comprehensive scenario coverage. Subsequently, we conduct vulnerability analysis on object detection models to identify weaknesses and create an effective training dataset for enhancing model vulnerability. This improves the object detection models’ tolerance to weather and noise-related corruptions, ultimately enhancing the robustness of the perception system. We use case studies to demonstrate the feasibility and effectiveness of the proposed procedures for verifying and enhancing robustness. Furthermore, we investigate the impact of various “similarity overlap threshold” parameter settings on scenario coverage, effectiveness, scenario complexity (size of training and testing datasets), and time costs.
A Method for Measuring Shaft Diameter Based on Light Stripe Image Enhancement
Authors: Li Chunfeng , Xu Xiping , Liu Siyuan , Ren Zhen
Published: January 2024

When the workpiece surface exhibits strong reflectivity, it becomes challenging to obtain accurate key measurements using non-contact, visual measurement techniques due to poor image quality. In this paper, we propose a high-precision measurement method shaft diameter based on an enhanced quality stripe image. By capturing two stripe images with different exposure times, we leverage their different characteristics. The results extracted from the low-exposure image are used to perform grayscale correction on the high-exposure image, improving the distribution of stripe grayscale and resulting in more accurate extraction results for the center points. The incorporation of different measurement positions and angles further enhanced measurement precision and robustness. Additionally, ellipse fitting is employed to derive shaft diameter. This method was applied to the profiles of different cross-sections and angles within the same shaft segment. To reduce the shape error of the shaft measurement, the average of these measurements was taken as the estimate of the average diameter for the shaft segment. In the experiments, the average shaft diameters determined by averaging elliptical estimations were compared with shaft diameters obtained using a coordinate measuring machine (CMM) the maximum error and the minimum error were respectively 18 μm and 7 μm; the average error was 11 μm; and the root mean squared error of the multiple measurement results was 10.98 μm. The measurement accuracy achieved is six times higher than that obtained from the unprocessed stripe images.
Accurate Path Loss Prediction Using a Neural Network Ensemble Method
Authors: Kwon Beom , Son Hyukmin
Published: January 2024

Path loss is one of the most important factors affecting base-station positioning in cellular networks. Traditionally, to determine the optimal installation position of a base station, path-loss measurements are conducted through numerous field tests. Disadvantageously, these measurements are time-consuming. To address this problem, in this study, we propose a machine learning (ML)-based method for path loss prediction. Specifically, a neural network ensemble learning technique was applied to enhance the accuracy and performance of path loss prediction. To achieve this, an ensemble of neural networks was constructed by selecting the top-ranked networks based on the results of hyperparameter optimization. The performance of the proposed method was compared with that of various ML-based methods on a public dataset. The simulation results showed that the proposed method had clearly outperformed state-of-the-art methods and that it could accurately predict path loss.
Accurate Robot Arm Attitude Estimation Based on Multi-View Images and Super-Resolution Keypoint Detection Networks
Authors: Zhou Ling , Wang Ruilin , Zhang Liyan
Published: January 2024

Robot arm monitoring is often required in intelligent industrial scenarios. A two-stage method for robot arm attitude estimation based on multi-view images is proposed. In the first stage, a super-resolution keypoint detection network (SRKDNet) is proposed. The SRKDNet incorporates a subpixel convolution module in the backbone neural network, which can output high-resolution heatmaps for keypoint detection without significantly increasing the computational resource consumption. Efficient virtual and real sampling and SRKDNet training methods are put forward. The SRKDNet is trained with generated virtual data and fine-tuned with real sample data. This method decreases the time and manpower consumed in collecting data in real scenarios and achieves a better generalization effect on real data. A coarse-to-fine dual-SRKDNet detection mechanism is proposed and verified. Full-view and close-up dual SRKDNets are executed to first detect the keypoints and then refine the results. The keypoint detection accuracy, PCK@0.15, for the real robot arm reaches up to 96.07%. In the second stage, an equation system, involving the camera imaging model, the robot arm kinematic model and keypoints with different confidence values, is established to solve the unknown rotation angles of the joints. The proposed confidence-based keypoint screening scheme makes full use of the information redundancy of multi-view images to ensure attitude estimation accuracy. Experiments on a real UR10 robot arm under three views demonstrate that the average estimation error of the joint angles is 0.53 degrees, which is superior to that achieved with the comparison methods.
Detecting Respiratory Viruses Using a Portable NIR Spectrometer—A Preliminary Exploration with a Data Driven Approach
Authors: Huang Jian-Dong , Wang Hui , Power Ultan , McLaughlin James A. , Nugent Chris , Rahman Enayetur , Barabas Judit , Maguire Paul
Published: January 2024

Respiratory viruses’ detection is vitally important in coping with pandemics such as COVID-19. Conventional methods typically require laboratory-based, high-cost equipment. An emerging alternative method is Near-Infrared (NIR) spectroscopy, especially a portable one of the type that has the benefits of low cost, portability, rapidity, ease of use, and mass deployability in both clinical and field settings. One obstacle to its effective application lies in its common limitations, which include relatively low specificity and general quality. Characteristically, the spectra curves show an interweaving feature for the virus-present and virus-absent samples. This then provokes the idea of using machine learning methods to overcome the difficulty. While a subsequent obstacle coincides with the fact that a direct deployment of the machine learning approaches leads to inadequate accuracy of the modelling results. This paper presents a data-driven study on the detection of two common respiratory viruses, the respiratory syncytial virus (RSV) and the Sendai virus (SEV), using a portable NIR spectrometer supported by a machine learning solution enhanced by an algorithm of variable selection via the Variable Importance in Projection (VIP) scores and its Quantile value, along with variable truncation processing, to overcome the obstacles to a certain extent. We conducted extensive experiments with the aid of the specifically developed algorithm of variable selection, using a total of four datasets, achieving classification accuracy of: (1) 0.88, 0.94, and 0.93 for RSV, SEV, and RSV + SEV, respectively, averaged over multiple runs, for the neural network modelling of taking in turn 3 sessions of data for training and the remaining one session of an ‘unknown’ dataset for testing. (2) the average accuracy of 0.94 (RSV), 0.97 (SEV), and 0.97 (RSV + SEV) for model validation and 0.90 (RSV), 0.93 (SEV), and 0.91 (RSV + SEV) for model testing, using two of the datasets for model training, one for model validation and the other for model testing. These results demonstrate the feasibility of using portable NIR spectroscopy coupled with machine learning to detect respiratory viruses with good accuracy, and the approach could be a viable solution for population screening.
Performance of Fluxgate Magnetometer with Cu-Doped CoFeSiB Amorphous Microwire Core
Authors: Wang Bin , Xu Weizhi , Zheng Xiaoping , Jiang Sida , Yi Zhong , Wang Peng , Tang Xiaojin
Published: January 2024

In this study, we investigated the effects of Cu doping on the performance of CoFeSiB amorphous microwires as the core of a fluxgate magnetometer. The noise performance of fluxgate sensors primarily depends on the crystal structure of constituent materials. CoFeSiB amorphous microwires with varying Cu doping ratios were prepared using melt-extraction technology. The microstructure of microwire configurations was observed using transmission electron microscopy, and the growth of nanocrystalline was examined. Additionally, the magnetic performance of the microwire and the noise of the magnetic fluxgate sensors were tested to establish the relationship between Cu-doped CoFeSiB amorphous wires and sensor noise performance. The results indicated that Cu doping triggers a positive mixing enthalpy and the reduced difference in the atomic radius that enhances the degree of nanocrystalline formation within the system; differential scanning calorimetry analysis indicates that this is due to Cu doping reducing the glass formation capacity of the system. In addition, Cu doping affects the soft magnetic properties of amorphous microwires, with 1% low-doping samples exhibiting better soft magnetic properties. This phenomenon is likely the result of the interaction between nanocrystalline organization and magnetic domains. Furthermore, a Cu doping ratio of 1% yields the best noise performance, aligning with the trend observed in the material’s magnetic properties. Therefore, to reduce the noise of the CoFeSiB amorphous wire sensor, the primary goal should be to reduce microscopic defects in amorphous alloys and enhance soft magnetic properties. Cu doping is a superior preparation method which facilitates control over preparation conditions, ensuring the formation of stable amorphous wires with consistent performance.
A Study of the Physical and Mechanical Properties of Yellow River Sediments and Their Impact on the Reclamation of Coal-Mined Subsided Land
Authors: Sun Huang , Hu Zhenqi , Wang Shuai
Published: January 2024

Coal mining in China has resulted in numerous subsided areas, exacerbating land scarcity issues. The Yellow River carries a high sediment load of nearly 1.6 billion tons annually. Cleaning up the accumulated silt is costly and takes up land. Reusing the sediment from the Yellow River to fill and reclaim the subsided areas caused by coal mining addresses both sedimentation and land reclamation issues, killing two birds with one stone. Nonetheless, technical challenges have emerged, such as machinery sinking into the soil, difficulty draining water, and poor soil quality improvement. To tackle these issues, understanding the physical and mechanical properties of Yellow River sediment is essential. Results show that the average particle size (D50) is 0.08 mm, categorized as fine-grained sandy soil with a relatively uniform particle size distribution. The permeability coefficient is 2.91 × 10−3 cm·s−1, similar to that of silty soil, indicating the feasibility for filling reclamation. However, the low permeability requires drainage improvement to accelerate construction timelines. The internal friction angle of the sediment ranges from 34.67° to 31.76°, with a cohesion from 20.79 to 23.92 kPa. To ensure safe and stable construction, machinery must not sink into the fill material. It is recommended to enhance drainage to about 13% for quicker drainage and stable construction. The sediment has a compression coefficient of 0.05 MPa−1, indicating low compressibility. Mechanical compression is not economically viable during the reclamation process. Design elevation (H) and fill elevation (h) should account for cumulative deformation settlement.
The Implementation of a Sustainable Online Course for the Development of Digital Citizenship Skills in Higher Education
Authors: Bal Erkan , Akcil Umut
Published: January 2024

This study aims to develop and evaluate the effectiveness of a digital citizenship curriculum developed using online teaching for undergraduate students. For this purpose, answers were sought to the following general research questions: “How are students performing their digital citizenship skills?”, “What is the efficiency level of the developed digital citizenship curriculum?”, “What are the students’ self-evaluations during the implementation process of the developed digital citizenship curriculum?” and “What are student opinions about the implemented digital citizenship course?”. A “parallel-simultaneous design”, one of the mixed research methods, was used in this research. The content of the curriculum was determined within the framework of a needs analysis consisting of university students and field experts, and a document review. A quasi-experimental design method was used to implement the programme. A total of 39 teacher candidates, registered in the spring semester of the 2022 academic year, participated in the experimental process. A Moodle learning management system was used as the teaching environment. Participants’ digital citizenship behaviours and attitude levels were measured before and after the experimental application. It was observed that there was a significant (positive) difference between the pre-test and post-test average scores in favour of the post-test scores, and the effect value of this difference was high. It turned out that the teacher candidates’ opinions on the effectiveness of the online digital citizenship programme were positive. It is understood that the digital citizenship teaching curriculum developed for higher education can be used sustainably for similar university student groups as in this study. However, it is anticipated that the developed programme can be updated along with technological evolutions.
Effects of Paleosol on the Collapsibility of Loess Sites under Immersion Test Conditions
Authors: Li Lin , Wang Jiading , Gu Qi , Zhang Dengfei
Published: January 2024

The existence of multiple layers of red paleosol within loess strata presents a unique challenge due to its high hardness, which resists settlement deformation upon exposure to water. This attribute significantly influences the subsidence measurements of the loess strata. Despite this, the current literature lacks reports on the control effect of paleosol on collapsibility, leading to a deficiency in the theoretical basis for scientifically selecting collapsibility in these strata. This paper seeks to bridge this gap by examining the differences in self-weight collapsibility under various conditions, both indoor and outdoor, across different paleosol layers and strata. The analysis is grounded on statistical results derived from immersion tests conducted in the Loess Plateau. Moreover, the research zeroes in on two test sites in Xi’an, conducting extensive immersion tests and considering measurements such as water diffusion, changes in water content, soil pressure, and cumulative collapsibility under different test conditions. The study probes into the influence of paleosol layers on water infiltration and their role in controlling total weight collapse. The final results suggest that the presence of a paleosol layer inhibits collapsibility transfer to the lower layer and restricts water infiltration, thereby reducing total collapsibility. Discrepancies between measured and calculated collapsibility values showed a positive correlation with the number of paleosol layers. This research offers valuable insights into the collapsibility mechanism of paleosol-loess strata.
Biosurfactants: Promising Biomolecules for Agricultural Applications
Authors: Silva Maria da Glória C. , Medeiros Anderson O. , Converti Attilio , Almeida Fabiola Carolina G. , Sarubbo Leonie A.
Published: January 2024

Population growth and the need for increased agricultural productivity pose a global problem. Therefore, the development of green compounds to ensure agricultural sustainability is an urgent necessity. Surfactant compounds hold significant commercial importance due to their diverse industrial uses. However, the synthetic origin of these agents limits their commercial application due to their toxicity. As a result, extensive research has focused on the production of microbial-originated green surfactants, known as biosurfactants, over the past fifteen years. These biomolecules not only offer a green alternative for agriculture but also exhibit reduced toxicity and excellent stability under specific environmental conditions. Biosurfactants can lower surface tension more effectively than synthetic surfactants. With properties such as detergency and foam formation, biosurfactants are suitable for various agricultural applications, particularly in pesticide and agrochemical formulations. They can function as biopesticides to manage pests, pathogens, phytopathogenic fungi, and weeds due to their antimicrobial activity. Moreover, plants can benefit from biosurfactant molecules and microorganisms as nutrients. They can also aid efficiently in the distribution of micronutrients and metals in the soil. They also stimulate plant immunity and are utilized for soil hydrophilization to ensure proper moisture levels and uniform fertilizer distribution. This review aims to provide valuable insights into the role and properties of biosurfactants as agricultural adjuvants, fostering the development of sustainable formulations to replace the chemical surfactants used in pesticides. For this purpose, the general aspects of global agricultural activity are initially described, followed by a discussion of pesticides, including herbicides, fungicides, and insecticide products. Next, the properties of chemical surfactants are discussed and the use of green surfactants, with emphasis on microbial biosurfactants, is demonstrated. The application of biosurfactants in the agricultural industry and trends are addressed and prospects for the application of these agents are discussed.
The Comet Assay as a Sustainable Method for Evaluating the Genotoxicity Caused by the Soluble Fraction Derived from Sewage Sludge on Diverse Cell Types, Including Lymphocytes, Coelomocytes and Allium cepa L. Cells
Authors: Costea Monica Adriana , Rosan Cristina Adriana , Laslo Vasile , Agud Eliza , Purcarea Cornelia , Vicas Simona Ioana
Published: January 2024

With the expansion of urban areas, the amount of sludge produced by sewage treatment plants is increasing, raising big problems regarding the reintroduction of this sludge into nature in order to fully solve the wastewater problem. The application of sludge to agricultural surfaces or degraded land is a controversial solution since, despite the well-known benefits, sludge can, in certain cases, represent a real threat to both human health and the environment, with long-term harmful effects. The present study evaluates the potential genotoxicity of sludge using the Comet Test and three cellular bioindicators (lymphocytes, coelomocytes, and Allium cepa L.) for its quantification. To perform the tests, the soluble fraction of the sludge was used at concentrations of 25%, 50%, 75%, and 100%, as well as a negative control (H2O) and a positive control (H2O2). The Comet test indicated an increase in DNA damage among cells exposed for 4 h in the following order: coelomocytes, lymphocytes, and Allium cepa L. cells. Our results indicate that Allium cepa L. nuclei are more sensitive, with genotoxic effects being evident at concentrations as low as 25%. In coelomocytes, we recorded nuclear damage starting at a concentration of 75%. These results indicate the necessity of using multiple genotoxicity tests, combined in a test battery, to achieve a greater level of relevance. The concentration of the soluble fraction of the sludge has an inverse relationship with the auxin content in leaves and roots, suggesting varying levels of stress. The results of this study can contribute to the creation of a genotoxic profile of sewage sludge, facilitating decisions related to reducing its negative impact.
A Drivers Framework of Organizational SDG Engagement
Authors: Mestdagh Björn , Van Liedekerke Luc , Sempiga Olivier
Published: January 2024

This paper constitutes a theoretical reflection on organizational engagement with the Sustainable Development Goals (SDGs). Despite the widespread adoption of such engagements, a precise definition and positioning of organizational SDG engagement are lacking in the literature. This gap also extends to the underlying motivations driving organizations to actively engage with the SDGs. To address these, this study aims to achieve two key objectives. Firstly, it seeks to establish a foundational understanding by defining and delineating the concept of organizational SDG engagement, recognizing its distinctiveness from Corporate Sustainability (CS) and Corporate Social Responsibility (CSR). Secondly, leveraging existing literature on CS and CSR, we propose a comprehensive driver framework for organizational SDG engagement. This framework underscores morality, efficiency, and legitimacy as primary drivers. The overarching goal of this reflective paper is, therefore, to enhance the theoretical comprehension of organizational SDG engagement by applying and integrating existing literature into the conceptual framework.
Construction Practices of Green Mines in China
Authors: Du Kun , Xie Junjie , Xi Wenqin , Wang Liang , Zhou Jian
Published: January 2024

To maintain high-level economic development, protect the ecological environment, and achieve carbon peaking and carbon neutrality goals, the construction of green mines has become a critical issue in China. In this study, the importance of mineral resources to human society is discussed, and the construction experiences and sustainable development directions of green mines are summarized, which can provide valuable references for the global mining industry. The entry and management process in China was introduced to help understand green mines’ construction objectives and tasks. Moreover, based on the successful construction cases of green mines, four typical green mine models are concluded: the green technology mining model, operation modernization mining model, stability mining model, and ecological restoration mining model. In addition, the key construction elements of green mines are concluded, for example, the mining environment, mining methods, comprehensive utilization of resources, energy conservation, emission reduction, scientific and technological innovation and intelligence, and enterprise-land stability, which provided the directions and guidance for green mine construction.
Exact Solutions of Population Balance Equation with Aggregation, Nucleation, Growth and Breakage Processes, Using Scaling Group Analysis
Authors: Lin Fubiao , Yang Yang , Yang Xinxia
Published: January 2024

Population balance equations may be employed to handle a wide variety of particle processes has certainly received unprecedented attention, but the absence of explicit exact solutions necessitates the use of numerical approaches. In this paper, a (2 + 1) dimensional population balance equation with aggregation, nucleation, growth and breakage processes is solved analytically by use of the methods of scaling transformation group, observation and trial function. Symmetries, reduced equations, invariant solutions, exact solutions, existence of solutions, evolution analysis of dynamic behavior for solutions are presented. The exact solutions obtained can be compared with the numerical scheme. The obtained results also show that the method of scaling transformation group can be applied to study integro-partial differential equations.
Special Issue: Symmetry beyond the Standard Models of Cosmology, High Energy Physics and Quantum Field Theory
Authors: Beylin Vitaly , Khlopov Maxim
Published: January 2024

Research into the nature of matter is gradually advancing to a scale that is still energetically inaccessible at ground-based colliders [...]
Oral Chagas Disease in Colombia—Confirmed and Suspected Routes of Transmission
Authors: Beatty Norman L. , Arango-Ferreira Catalina , Gual-Gonzalez Lídia , Zuluaga Sara , Nolan Melissa S. , Cantillo-Barraza Omar
Published: January 2024

Chagas disease (CD) remains endemic throughout many regions of Colombia despite implementing decades of vector control strategies in several departments. Some regions have had a significant decrease in vectorial transmission, but the oral ingestion of Trypanosoma cruzi through consumption of contaminated food and drink products is increasingly described. This form of transmission has important public health relevance in Colombia due to an increase in reported acute CD cases and clinical manifestations that often lead to significant morbidity and mortality. Oral CD in Colombia has been associated with the consumption of contaminated fruit juices, such as palm wine, sugar cane, or tangerine juice and water for consumption, or contaminated surfaces where food has been prepared. Another interesting route of oral transmission includes ingestion of unbeknownst infected armadillos’ blood, which is related to a traditional medicine practice in Colombia. Some earlier reports have also implemented consumption of infected bush meat as a source, but this is still being debated. Within the Amazon Basin, oral transmission is now considered the principal cause of acute CD in these regions. Furthermore, new cases of acute CD are now being seen in departments where CD has not been documented, and triatomine vectors are not naturally found, thus raising suspicion for oral transmission. The oral CD could also be considered a food-borne zoonosis, and odoriferous didelphid secretions have been implemented in contaminating the human dwelling environment, increasing the risk of consumption of infectious metacyclic trypomastigotes. In this article, we will discuss the complex transmission dynamics of oral CD in Colombia and further examine the unique clinical manifestations of this route of infection. New insights into the oral transmission of Trypanosoma cruzi are being discovered in Colombia, which can help bring increased awareness and a better understanding of this neglected tropical disease to reduce the burden of CD throughout Latin America.
Exploring the Genomic Dynamics of the Monkeypox Epidemic in Paraguay
Authors: Vazquez Cynthia , Fonseca Vagner , de la Fuente Andrea Gomez , Gonzalez Sandra , Fleitas Fatima , Lima Mauricio , Guimarães Natália R. , Iani Felipe C. M. , Rojas Analia , Alfonso Tania , Cantero Cesar , Barrios Julio , Villalba Shirley , Ortega Maria Jose , Torales Juan , Gamarra Maria Liz , Aquino Carolina , Franco Leticia , Rico Jairo Mendez , Alcantara Luiz Carlos Junior , Giovanetti Marta
Published: January 2024

In recent months, Paraguay has been grappled with a notable monkeypox outbreak, straining its healthcare infrastructure. The sudden spike in cases underlines the imperative need for a comprehensive understanding of the virus’s dynamics, enabling the formulation of robust containment measures. To address this challenge, our team joined forces with the Central Public Health Laboratory of Asunción and the Pan-American Health Organization. Through this collaboration, we employed portable whole-genome sequencing combined with phylodynamic analysis to examine the MPXV strains circulating in Paraguay. Our genomic monitoring approach has produced the first 30 whole-genome sequences from Paraguay, all of which were identified under lineage IIb. Interestingly, our data suggest that the origin of the monkeypox virus in Paraguay at the beginning of 2022 can be traced back to Brazil. This introduction subsequently catalyzed further community spread that was further exacerbated by several independent introduction events as time progressed. These findings not only shed light on the transmission patterns of the virus but also highlight the pivotal role such insights play in sculpting effective response strategies and driving impactful public health measures. Furthermore, our findings strongly advocate intensified surveillance at international borders, ensuring swift detection and proactive countermeasures against potential outbreaks in the future.
The Carbon Emission Intensity of Rainwater Bioretention Facilities
Authors: Wang Deqi , Liu Xuefeng , Li Huan , Chen Hai , Wang Xiaojuan , Li Wei , Cao Lianbao , Liu Jianlin , Zhang Tingting , Wei Bigui
Published: January 2024

To investigate the quantitative relationship between the volume capture of rainfall and carbon emissions from bioretention facilities, this study introduces the concept of the carbon intensity of volume capture of rainfall. The influence of four key factors—climatic conditions, aquifer height, permeability coefficient, and facility area—was investigated using a residential neighborhood in Tianshui, China, as an example. The results reveal that the carbon intensity value is influenced not only by external environmental changes but also by the inherent attributes of bioretention facilities, such as aquifer height, permeability coefficient, and facility area. The maximum carbon intensity value for the volume capture of rainfall was −0.0005 kg CO2/m3, while the minimum was −0.0852 kg CO2/m3, representing a substantial difference of approximately 169 times. Orthogonal experiments identified the facility area as the most significant influencing factor on carbon intensity, with a correlation coefficient of 0.0520. The area of bioretention facilities can be prioritized to meet deployment requirements, taking into account volume capture reduction effects and carbon emissions. For facilities with a high carbon intensity, an emphasis should be placed on enhancing carbon reduction benefits, and various initiatives can be implemented to achieve this goal.
Policy, Institutions and Regulation in Stormwater Management: A Hybrid Literature Review
Authors: Novaes Carlos , Marques Rui Cunha
Published: January 2024

Policies, Institutions and Regulation (PIR) aspects matter for different sectors’ growth and inclusive sustainable development, but there is little information in the literature on how to evaluate the effects of PIR on management options and outcomes or, on how positive results PIR changes can bring. In terms of stormwater management systems, or urban drainage, PIR is also a controversial and absent matter. Multidisciplinarity, several actors, countless formal and informal rules, and strong contextual path dependence make the subject complex and intricate. Considering the enabling environment, an alignment between policies, institutions and regulations is required to achieve good results and provide sustainable services. This study conducted a hybrid literature review of peer-reviewed papers in this field to provide an overview of how researchers have been studying PIR relations. The gaps show that the understanding of the PIR is fragile, as an important element for analyzing of results to be achieved, including SDG6, the financing and obtaining funds, guarantees and grants for the execution, delivery, operation and maintenance urban stormwater services and infrastructure. The contribution of this review is not only about what exists, but also mainly about what does not exist, since the void keeps waiting to be filled.
Speed Change Pattern Optimization for Improving the Electricity Consumption of an Electric Bus and Its Verification Using an Actual Vehicle
Authors: Fang Yiyuan , Yang Wei-hsiang , Kamiya Yushi , Imai Takehito , Ueki Shigeru , Kobayashi Masayuki
Published: January 2024

In this study, we focused on the eco-driving of electric vehicles (EVs). The target vehicle is an electric bus developed by our research team. Using the parameters of the bus and speed pattern optimization algorithm, we derived the EV’s eco-driving speed pattern. Compared to the eco-driving of internal combustion engine vehicles (ICVs), we found several different characteristics. We verified these characteristics with actual vehicle driving test data of the target bus, and the results confirmed its rationality. The EV’s eco-driving method can improve electricity consumption by about 10–20% under the same average speed.