bluuebunny/crossref_metadata_2025 huggingface dataset:
The Influence of Intestinal Microbiota on BDNF Levels
Authors: Molska Marta , Mruczyk Kinga , Cisek-Woźniak Angelika , Prokopowicz Wojciech , Szydełko Patrycja , Jakuszewska Zuzanna , Marzec Karolina , Trocholepsza Martyna
Published: August 2024

The regulation of neurogenesis, the complex process of producing and differentiating new brain tissue cells, is influenced by a complex interaction of internal and external factors. Over the past decade, extensive research has been conducted on neurotrophins and their key role in adult neurogenesis, as well as their impact on diseases such as depression. Among neurotrophins, the brain-derived neurotrophic factor (BDNF) has been the subject of comprehensive studies on adult neurogenesis, and scientific evidence supports its necessity for neurogenesis in the subventricular zone of the hippocampus. A novel area of research is the emerging role of gut microbiota as a significant contributor to neurogenesis and neurotrophin production. Studies have shown that reduced BDNF levels can lead to mood disorders, which are observed in intestinal dysbiosis, characterized by an imbalance in the composition and quantity of the intestinal microbiota. There is evidence in the literature that there is a link between brain function and gut microbiota. Physical activity, and especially the regularity and intensity of exercise, is important in relation to the level of BDNF and the intestinal microbiota. Probiotics, prebiotics and physical activity may have a positive effect on the intestinal microbiota, and therefore also on the level of the brain-derived neurotrophic factor.
Investigation of Human Milk as a Biological System in a Multicenter Mother–Infant Cohort: Protocol Design and Cohort Profile of the Phoenix Study
Authors: Wu Jieshu , Gan Junai , Zeng Guo , Luo Xiaoqin , Yang Nianhong , Zhang Zheqing , Sun Yongye , Shen Jian , Wei Wei , Yan Jingyu , Zhu Jing , Ludwig Thomas , Stahl Bernd , Zhao Xianfeng , Wang Zhixu
Published: August 2024

Breastfeeding and human milk are the gold standard for infant feeding. Studying human milk with a systems biology approach in a large longitudinal cohort is needed to understand its complexity and health implications. The Phoenix study is a multicenter cohort study focusing on the interactions of maternal characteristics, human milk composition, infant feeding practices, and health outcomes of Chinese mothers and infants. A total of 779 mother–infant dyads were recruited from November 2021 to September 2022, and 769 mother–infant dyads were enrolled in the study. Scheduled home visits took place at 1, 4, 6, and 12 months postpartum, and 696 dyads (90.5% participants) completed the 12-month visit. At each visit, maternal and infant anthropometry was assessed. Questionnaires were administered to collect longitudinal information on maternal characteristics and lifestyle, infant feeding, and health. Digital diaries were used to record maternal dietary intake, infant feeding, and stool character. Human milk, maternal feces, infant feces, and infant saliva were collected. An external pharmaceutical-level quality assurance approach was implied to ensure the trial quality. Multi-omics techniques (including glycomics, lipidomics, proteomics, and microbiomics) and machine learning algorithms were integrated into the sample and data analysis. The protocol design of the Phoenix study provides a framework for prospective cohort studies of mother–infant dyads and will provide insights into the complex dynamics of human milk and its interplay with maternal and infant health outcomes in the Chinese population.
Association of Polyamine Intake, Other Dietary Components, and Fecal Content of N-acetyl Putrescine and Cadaverine with Patients’ Colorectal Lesions
Authors: Barreiro-Alonso Eva , Castro-Estrada Paula , Sánchez Manuel , Peña-Iglesias Pablo , Suárez Lorena , Cantabrana Begoña
Published: August 2024

Colorectal cancer (CRC) is the second leading cause of cancer death worldwide. Early detection and the modification of risk factors, such as diet, can reduce its incidence. Among food components, polyamines are important for maintaining gastrointestinal health and are metabolites of gut microbiota. Their disruption is linked to CRC, making polyamines a potential marker of the disease. This study analyzed the relationship between dietary components, including polyamines, and the presence of polyamines in feces to determine whether their presence could contribute to predicting the occurrence of colorectal lesions in patients. In total, 59 participants of both sexes (aged 50 to 70 years) who had undergone colonoscopy screening for CRC (18 without and 41 with colorectal lesions) participated in the study. A nutritional survey and determination of fecal polyamine content were performed. Specific dietary components and putrescine levels were higher in patients with colorectal lesions. The diet ratio of putrescine–spermidine and the fecal content of N-acetyl putrescine and cadaverine were elevated in patients with precancerous lesions and adenocarcinomas, showing a potential predictive value for the presence of colorectal lesions. These findings suggest that N-acetyl putrescine and cadaverine could be complementary markers for the diagnosis of suspected colorectal lesions.
Garlic and Hypertension: Efficacy, Mechanism of Action, and Clinical Implications
Authors: Sleiman Christopher , Daou Rose-Mary , Al Hazzouri Antonio , Hamdan Zahi , Ghadieh Hilda E. , Harbieh Bernard , Romani Maya
Published: August 2024

Hypertension is a major risk factor for heart disease and stroke. Garlic has a long history of use in traditional medicine for various conditions, including hypertension. This narrative review examined the scientific evidence on the efficacy of garlic in lowering blood pressure. It explores the historical uses of garlic in different cultures for medicinal purposes and delves into the phytochemical composition of garlic, highlighting key components, like allicin and ajoene, that are believed to contribute to its potential health benefits. Clinical studies that investigated the effects of garlic and garlic-based supplements on blood pressure are presented, with the findings suggesting that garlic consumption may modestly reduce blood pressure, particularly in individuals with mild hypertension. Potential mechanisms of action include increased nitric oxide production, improved endothelial function, and antioxidant properties. While garlic may offer some benefits for blood pressure management, it should not be considered a substitute for conventional antihypertensive medications. Further large-scale, long-term clinical trials are warranted to establish the efficacy of garlic in managing hypertension, including the optimal dosage and formulation.
Development and Validation of a Pediatric Hospital-Acquired Malnutrition (PHaM) Risk Score to Predict Nutritional Deterioration in Hospitalized Pediatric Patients: A Secondary Analysis Based on a Multicenter Prospective Cohort Study
Authors: Saengnipanthkul Suchaorn , Sirikarn Prapassara , Chongviriyaphan Nalinee , Densupsoontorn Narumon , Phosuwattanakul Jeeraparn , Apiraksakorn Amnuayporn , Sitthikarnkha Phanthila , Techasatian Leelawadee , Uppala Rattapon , Lumbiganon Pagakrong
Published: August 2024

(1) Background: Hospital-acquired malnutrition in pediatric patients leads to adverse outcomes. This study aimed to develop and validate a pediatric hospital-acquired malnutrition (PHaM) risk score to predict nutritional deterioration. (2) Methods: This was a derivative retrospective cohort study for developing a PHaM risk score. The study included data from children aged 1 month–18 years admitted to pediatric wards in four tertiary care hospitals for at least 72 h between December 2018 and May 2019. Data on pediatric patients’ characteristics, medical history, nutritional status, gastrointestinal symptoms, and outcomes were used for tool development. Logistic regression identified risk factors for nutritional deterioration, defined as a decline in BMI z-score ≥ 0.25 SD and/or ≥2% weight loss. A PHaM risk score was developed based on these factors and validated with an independent prospective cohort from July 2020 to March 2021. (3) Results: The study used a derivative cohort of 444 patients and a validation cohort of 373 patients. Logistic regression identified gastrointestinal symptoms, disease severity, fever, lower respiratory tract infection, and reduced food intake as predictors. The PHaM risk score (maximum 9 points) showed good discrimination and calibration (AUC 0.852, 95% CI: 0.814–0.891). Using a cut-off at 2.5 points, the scale had 63.0% sensitivity, 88.6% specificity, 76.1% positive predictive value, and 80.6% negative predictive value (NPV) when applied to the derivative cohort. The accuracy improved on the validation cohort, with 91.9% sensitivity and 93.0% NPV. (4) Conclusions: This PHaM risk score is a novel and probably effective tool for predicting nutritional deterioration in hospitalized pediatric patients, and its implementation in clinical practice could enhance nutritional care and optimize outcomes.
The Properties of the Transient Outward, Inward Rectifier and Acetylcholine-Sensitive Potassium Currents in Atrial Myocytes from Dogs in Sinus Rhythm and Experimentally Induced Atrial Fibrillation Dog Models
Authors: Kohajda Zsófia , Corici Claudia , Kristóf Attila , Virág László , Husti Zoltán , Baczkó István , Sághy László , Varró András , Jost Norbert
Published: August 2024

Aims: Atrial fibrillation (AF) is the most common chronic/recurrent arrhythmia, which significantly impairs quality of life and increases cardiovascular morbidity and mortality. Therefore, the aim of the present study was to investigate the properties of three repolarizing potassium currents which were shown to contribute to AF-induced electrical remodeling, i.e., the transient outward (Ito), inward rectifier (IK1) and acetylcholine-sensitive (IK,ACh) potassium currents in isolated atrial myocytes obtained from dogs either with sinus rhythm (SR) or following chronic atrial tachypacing (400/min)-induced AF. Methods: Atrial remodeling and AF were induced by chronic (4–6 weeks of) right atrial tachypacing (400/min) in dogs. Transmembrane ionic currents were measured by applying the whole-cell patch-clamp technique at 37 °C. Results: The Ito current was slightly downregulated in AF cells when compared with that recorded in SR cells. This downregulation was also associated with slowed inactivation kinetics. The IK1 current was found to be larger in AF cells; however, this upregulation was not statistically significant in the voltage range corresponding with atrial action potential (−80 mV to 0 mV). IK,ACh was activated by the cholinergic agonist carbachol (CCh; 2 µM). In SR, CCh activated a large current either in inward or outward directions. The selective IK,ACh inhibitor tertiapin (10 nM) blocked the outward CCh-induced current by 61%. In atrial cardiomyocytes isolated from dogs with AF, the presence of a constitutively active IK,ACh was observed, blocked by 59% with 10 nM tertiapin. However, in “AF atrial myocytes”, CCh activated an additional, significant ligand-dependent and tertiapin-sensitive IK,ACh current. Conclusions: In our dog AF model, Ito unlike in humans was downregulated only in a slight manner. Due to its slow inactivation kinetics, it seems that Ito may play a more significant role in atrial repolarization than in ventricular working muscle myocytes. The presence of the constitutively active IK,ACh in atrial myocytes from AF dogs shows that electrical remodeling truly developed in this model. The IK,ACh current (both ligand-dependent and constitutively active) seems to play a significant role in canine atrial electrical remodeling and may be a promising atrial selective drug target for suppressing AF.
Physiological and Transcriptomic Analyses Demonstrate the Ca2+-Mediated Alleviation of Salt Stress in Magnolia wufengensis
Authors: Zhao Xiuting , Zhu Zhonglong , Sang Ziyang , Ma Luyi , Yin Qun , Jia Zhongkui
Published: August 2024

Magnolia wufengensis, a newly discovered ornamental species in the Magnoliaceae family, is susceptible to salinity. Moreover, Ca2+ is an essential element for plant growth and is receiving increasing attention for its ability to mitigate the negative effects of environmental stress on plants. In the present study, we investigated the effect of Ca2+ on the growth and transcriptome of M. wufengensis under salt stress. The treatments used here were as follows: control, NaCl (150 mmol/L), CaCl2 (5 mmol/L), and NaCl (150 mmol/L) + CaCl2 (5 mmol/L). After a 60-day treatment period, plant growth indices were determined, and leaves were collected for physiological analysis and transcriptome investigation. The combined application of NaCl and CaCl2 alleviated phenotypic damage and restored seedling growth. Moreover, RNA sequencing data revealed that in the Na vs. control group and the NaCa vs. Na group, there were 968 and 2632 differentially expressed genes, respectively, which were both primarily enriched in secondary metabolism, glutathione metabolism, signaling hormone metabolism, glucose metabolism, and amino acid metabolism. These pathways were analyzed to screen key genes: the adenosine triphosphate (ATP)-binding cassette efflux transporter G1 (ABCG1) genes, which are related to transmembrane transport; the calmodulin genes, which are related to signal transmission; and the glutathione S-transferase (GST), glutathione peroxidase (GPX), and peroxidase (POD) genes related to antioxidant enzymes. Lastly, we constructed a hypothesis model of Ca2+-enhanced salt tolerance in M. wufengensis. This study reveals the potential mechanisms by which Ca2+ enhances the salt tolerance of M. wufengensis and provides a theoretical reference for its cultivation in saline areas.
Dreams of American Christendom: White Evangelicals’ Political Pursuit of a Christian Order without Christ
Authors: Wong Jessica Wai-Fong
Published: August 2024

Religion has become an increasingly pronounced force in American politics, most notably among White evangelicals, nearly two-thirds of whom identify with Christian nationalism. This group contends that conservative, biblically rooted Christian values should determine the social and cultural landscape of our society and seeks to pass laws that help actualize this goal. This article explores the fundamental beliefs that enable White evangelicalism’s compatibility with Christian nationalism. More specifically, it considers how the myth of America’s Christian origins prompts a yearning for Christendom that—when coupled with a theological shift from a strict non-interventionist two kingdoms doctrine to a more fluid conception of kingdoms and laws—allows White evangelicals to cordon off Jesus’s life and teachings from their political activities. This relegation of Jesus to the Christian’s spiritual life enables White evangelicals to pursue a Christian ordering of society that is estranged from the person of Christ.
River Ice Mapping from Landsat-8 OLI Top of Atmosphere Reflectance Data by Addressing Atmospheric Influences with Random Forest: A Case Study on the Han River in South Korea
Authors: Han Hyangsun , Kim Taewook , Kim Seohyeon
Published: August 2024

Accurate river ice mapping is crucial for predicting and managing floods caused by ice jams and for the safe operation of hydropower and water resource facilities. Although satellite multispectral images are widely used for river ice mapping, atmospheric contamination limits their effectiveness. This study developed river ice mapping models for the Han River in South Korea using atmospherically uncorrected Landsat-8 Operational Land Imager (OLI) multispectral reflectance data, addressing atmospheric influences with a Random Forest (RF) classification approach. The RF-based river ice mapping models were developed by implementing various combinations of input variables, incorporating the Landsat-8 multispectral top-of-atmosphere (TOA) reflectance, normalized difference indices for snow, water, and bare ice, and atmospheric factors such as aerosol optical depth, water vapor content, and ozone concentration from the Moderate Resolution Imaging Spectroradiometer observations, as well as surface elevation from the GLO-30 digital elevation model. The RF model developed using all variables achieved excellent performance in the classification of snow-covered ice, snow-free ice, and water, with an overall accuracy and kappa coefficient exceeding 98.4% and 0.98 for test samples, and higher than 83.7% and 0.75 when compared against reference river ice maps generated by manually interpreting the Landsat-8 images under various atmospheric conditions. The RF-based river ice mapping model for the atmospherically corrected Landsat-8 multispectral surface reflectance was also developed, but it showed very low performance under atmospheric conditions heavily contaminated by aerosol and water vapor. Aerosol optical depth and water vapor content were identified as the most important variables. This study demonstrates that multispectral reflectance data, despite atmospheric contamination, can be effectively used for river ice monitoring by applying machine learning with atmospheric auxiliary data to mitigate atmospheric effects.
DIPHORM: An Innovative DIgital PHOtogrammetRic Monitoring Technique for Detecting Surficial Displacements of Landslides
Authors: Brezzi Lorenzo , Gabrieli Fabio , Vallisari Davide , Carraro Edoardo , Pol Antonio , Galgaro Antonio , Cola Simonetta
Published: August 2024

Monitoring surface displacements of landslides is essential for evaluating their evolution and the effectiveness of mitigation works. Traditional methods like robotic total stations (RTSs) and GNSS provide high-accuracy measurements but are limited to discrete points, potentially missing the broader landslide’s behavior. On the contrary, laser scanner surveys offer accurate 3D representations of slopes and the possibility of inferring their movements, but they are often limited to infrequent, high-cost surveys. Monitoring techniques based on ground-based digital photogrammetry may represent a new, robust, and cost-effective alternative. This study demonstrates the use of multi-temporal images from fixed and calibrated cameras to achieve the 3D reconstruction of landslide displacements. The method presented offers the important benefit of obtaining spatially dense displacement data across the entire camera view and quasi-continuous temporal measurement. This paper outlines the framework for this prototyping technique, along with a description of the necessary hardware and procedural steps. Furthermore, strengths and weaknesses are discussed based on the activities carried out in a landslide case study in northeastern Italy. The results from the photo-monitoring are reported, discussed, and compared with traditional topographical data, validating the reliability of this new approach in monitoring the time evolution of surface displacements across the entire landslide area.
From Do-It-Yourself Design to Discovery: A Comprehensive Approach to Hyperspectral Imaging from Drones
Authors: Hasler Oliver , Løvås Håvard S. , Oudijk Adriënne E. , Bryne Torleiv H. , Johansen Tor Arne
Published: August 2024

This paper presents an innovative, holistic, and comprehensive approach to drone-based imaging spectroscopy based on a small, cost-effective, and lightweight Unmanned Aerial Vehicle (UAV) payload intended for remote sensing applications. The payload comprises a push-broom imaging spectrometer built in-house with readily available Commercial Off-The-Shelf (COTS) components. This approach encompasses the entire process related to drone-based imaging spectroscopy, ranging from payload design, field operation, and data processing to the extraction of scientific data products from the collected data. This work focuses on generating directly georeferenced imaging spectroscopy datacubes using a Do-It-Yourself (DIY) imaging spectrometer, which is based on COTS components and freely available software and methods. The goal is to generate a remote sensing reflectance datacube that is suitable for retrieving chlorophyll-A (Chl-A) distributions as well as other properties of the ocean spectra. Direct georeferencing accuracy is determined by comparing landmarks in the directly georeferenced datacube to their true location. The quality of the remote sensing reflectance datacube is investigated by comparing the Chl-A distribution on various days with in situ measurements and satellite data products.
Newly Discovered NE-Striking Dextral Strike-Slip Holocene Active Caimashui Fault in the Central Part of the Sichuan-Yunnan Block and Its Tectonic Significance
Authors: Tan Xin , Liang Kuan , Ma Baoqi , He Zhongtai
Published: August 2024

The Sichuan-Yunnan block is a tectonically active region in China, with frequent large earthquakes occurring in and around it. Despite most earthquakes being concentrated along boundary faults, intraplate faults also have the potential to generate damaging earthquakes. Remote sensing makes it possible to identify these potential earthquake source faults. During an active fault investigation in the Liangshan area, a distinct lithological boundary named Caimashui fault was found. The geometric distribution and kinematic parameter of the fault is crucial for assessing seismic hazards and understanding the deformation pattern within the Sichuan-Yunnan block. The Caimashui fault is mapped with remote sensing interpretation, a field survey, and UAV measurement. Through trenching and Quaternary dating, the Late Quaternary active characteristics of the fault are studied. The fault is a Holocene active dextral strike-slip fault with a reverse component, exhibiting a dextral strike-slip rate of ~0.70 ± 0.11 mm/a. Paleoseismic investigation shows that the last surface rupture event of the Caimashui fault occurred later than 4150 ± 30a BP, with a magnitude of M ≥ 7.0. The fault may act as a secondary splitting fault, absorbing the deformation caused by various sinistral strike-slip rates of the boundary faults and the potential energy from the counterclockwise rotation of the Central Yunnan micro-block.
An Efficient Prediction Model on the Operation Quality of Medical Equipment Based on Improved Sparrow Search Algorithm-Temporal Convolutional Network-BiLSTM
Authors: Lin Zicong , Ji Zhiyong
Published: August 2024

Combining medical IoT and artificial intelligence technology is an effective approach to achieve the intelligence of medical equipment. This integration can address issues such as low image quality caused by fluctuations in power quality and potential equipment damage, and this study proposes a predictive model, ISSA-TCN-BiLSTM, based on a bi-directional long short-term memory network (BiLSTM). Firstly, power quality data and other data from MRI and CT equipment within a 6-month period are collected using current fingerprint technology. The key factors affecting the active power of medical equipment are explored using the Pearson coefficient method. Subsequently, a Temporal Convolutional Network (TCN) is employed to conduct multi-layer convolution operations on the input temporal feature sequences, enabling the learning of global temporal feature information while minimizing the interference of redundant data. Additionally, bidirectional long short-term memory (BiLSTM) is integrated to model the intermediate active power features, facilitating accurate prediction of medical equipment power quality. Additionally, an improved Sparrow Search Algorithm (ISSA) is utilized for hyperparameter optimization of the TCN-BiLSTM model, enabling optimization of the active power of different medical equipment. Experimental results demonstrate that the ISSA-TCN-BiLSTM model outperforms other comparative models in terms of RMSE, MSE, and R2, with values of 0.1143, 0.1157, 0.0873, 0.0817, 0.95, and 0.96, respectively, for MRI and CT equipment. This model exhibits both prediction speed and accuracy in power prediction for medical equipment, providing valuable guidance for equipment maintenance and diagnostic efficiency enhancement.
Advancing mHealth Research in Low-Resource Settings: Young Women’s Insights and Implementation Challenges with Wearable Smartwatch Devices in Uganda
Authors: Swahn Monica H. , Gittner Kevin B. , Lyons Matthew J. , Nielsen Karen , Mobley Kate , Culbreth Rachel , Palmier Jane , Johnson Natalie E. , Matte Michael , Nabulya Anna
Published: August 2024

In many regions globally, including low-resource settings, there is a growing trend towards using mHealth technology, such as wearable sensors, to enhance health behaviors and outcomes. However, adoption of such devices in research conducted in low-resource settings lags behind use in high-resource areas. Moreover, there is a scarcity of research that specifically examines the user experience, readiness for and challenges of integrating wearable sensors into health research and community interventions in low-resource settings specifically. This study summarizes the reactions and experiences of young women (N = 57), ages 18 to 24 years, living in poverty in Kampala, Uganda, who wore Garmin vívoactive 3 smartwatches for five days for a research project. Data collected from the Garmins included participant location, sleep, and heart rate. Through six focus group discussions, we gathered insights about the participants’ experiences and perceptions of the wearable devices. Overall, the wearable devices were met with great interest and enthusiasm by participants. The findings were organized across 10 domains to highlight reactions and experiences pertaining to device settings, challenges encountered with the device, reports of discomfort/comfort, satisfaction, changes in daily activities, changes to sleep, speculative device usage, community reactions, community dynamics and curiosity, and general device comfort. The study sheds light on the introduction of new technology in a low-resource setting and also on the complex interplay between technology and culture in Kampala’s slums. We also learned some insights into how wearable devices and perceptions may influence behaviors and social dynamics. These practical insights are shared to benefit future research and applications by health practitioners and clinicians to advance and enhance the implementation and effectiveness of wearable devices in similar contexts and populations. These insights and user experiences, if incorporated, may enhance device acceptance and data quality for those conducting research in similar settings or seeking to address population-specific needs and health issues.
Developing Machine Vision in Tree-Fruit Applications—Fruit Count, Fruit Size and Branch Avoidance in Automated Harvesting
Authors: Neupane Chiranjivi , Walsh Kerry B. , Goulart Rafael , Koirala Anand
Published: August 2024

Recent developments in affordable depth imaging hardware and the use of 2D Convolutional Neural Networks (CNN) in object detection and segmentation have accelerated the adoption of machine vision in a range of applications, with mainstream models often out-performing previous application-specific architectures. The need for the release of training and test datasets with any work reporting model development is emphasized to enable the re-evaluation of published work. An additional reporting need is the documentation of the performance of the re-training of a given model, quantifying the impact of stochastic processes in training. Three mango orchard applications were considered: the (i) fruit count, (ii) fruit size and (iii) branch avoidance in automated harvesting. All training and test datasets used in this work are available publicly. The mAP ‘coefficient of variation’ (Standard Deviation, SD, divided by mean of predictions using models of repeated trainings × 100) was approximately 0.2% for the fruit detection model and 1 and 2% for the fruit and branch segmentation models, respectively. A YOLOv8m model achieved a mAP50 of 99.3%, outperforming the previous benchmark, the purpose-designed ‘MangoYOLO’, for the application of the real-time detection of mango fruit on images of tree canopies using an edge computing device as a viable use case. YOLOv8 and v9 models outperformed the benchmark MaskR-CNN model in terms of their accuracy and inference time, achieving up to a 98.8% mAP50 on fruit predictions and 66.2% on branches in a leafy canopy. For fruit sizing, the accuracy of YOLOv8m-seg was like that achieved using Mask R-CNN, but the inference time was much shorter, again an enabler for the field adoption of this technology. A branch avoidance algorithm was proposed, where the implementation of this algorithm in real-time on an edge computing device was enabled by the short inference time of a YOLOv8-seg model for branches and fruit. This capability contributes to the development of automated fruit harvesting.
A Zero-Shot Learning Approach for Blockage Detection and Identification Based on the Stacking Ensemble Model
Authors: Li Chaoqun , Feng Zao , Jiang Mingkai , Wang Zhenglang
Published: August 2024

A data-driven approach to defect identification requires many labeled samples for model training. Yet new defects tend to appear during data acquisition cycles, which can lead to a lack of labeled samples of these new defects. Aiming at solving this problem, we proposed a zero-shot pipeline blockage detection and identification method based on stacking ensemble learning. The experimental signals were first decomposed using variational modal decomposition (VMD), and then, the information entropy was calculated for each intrinsic modal function (IMF) component to construct the feature sets. Second, the attribute matrix was established according to the attribute descriptions of the defect categories, and the stacking ensemble attribute learner was used for the attribute learning of defect features. Finally, defect identification was accomplished by comparing the similarity within the attribute matrices. The experimental results show that target defects can be identified even without targeted training samples. The model showed better classification performance on the six sets of experimental data, and the average recognition accuracy of the model for unknown defect categories reached 72.5%.
The Real-Time Detection of Vertical Displacements by Low-Cost GNSS Receivers Using Precise Point Positioning
Authors: Maciejewska Aleksandra , Lackowski Maciej , Hadas Tomasz , Maciuk Kamil
Published: August 2024

Vertical displacements are traditionally measured with precise levelling, which is inherently time consuming. Rapid or even real-time height determination can be achieved by the Global Navigation Satellite System (GNSS). Nevertheless, the accuracy of real-time GNSS positioning is limited, and the deployment of a network of continuously operating GNSS receivers is not cost effective unless low-cost GNSS receivers are considered. In this study, we examined the use of geodetic-grade and low-cost GNSS receivers for static and real-time GNSS levelling, respectively. The results of static GNSS levelling were processed in four different software programs or services. The largest differences for ellipsoidal/normal heights reached 0.054 m/0.055 m, 0.046 m/0.047 m, and 0.058 m/0.058 m for points WRO1, BM_ROOF, and BM_CP, respectively. In addition, the values depended on the software used and the location of the point. However, the multistage experiment was designed to analyze various strategies for GNSS data processing and to define a method for detecting vertical displacement in a time series of receiver coordinates. The developed method combined time differentiation of coordinates estimated for a single GNSS receiver using the Precise Point Positioning (PPP) technique and Butterworth filtering. It demonstrated the capability of real-time detection of six out of eight displacements in the range between 20 and 55 mm at the three-sigma level. The study showed the potential of low-cost GNSS receivers for real-time displacement detection, thereby suggesting their applicability to structural health monitoring, positioning, or early warning systems.
Asynchronous Code Division Multiplexing-Based Visible Light Positioning and Communication Network Using Successive Interference Cancellation Decoding
Authors: Liu Zhongxu , You Xiaodi , Yu Changyuan
Published: August 2024

In the evolving landscape of sixth-generation wireless communication, the integration of visible light communication (VLC) and visible light positioning (VLP), known as visible light positioning and communication (VLPC), emerges as a pivotal technology. This study addresses the challenges of asynchronous code division multiplexing (ACDM) in VLPC networks, focusing on the enhancement of data transmission quality and positioning accuracy. Firstly, we propose an orthogonal pseudo-random code (OPRC) for ACDM-based VLP systems. Leveraging its excellent correlation properties, VLP signals preserve orthogonality even amidst asynchronous transmissions, achieving sub-centimeter average positioning errors. Next, by combining OPRC with successive interference cancellation decoding (SICD), we propose an enhanced ACDM-based VLPC system that utilizes OPRC for improved signal orthogonality and SICD for progressive elimination of multiple access interference (MAI) among VLPC signals. The results show substantial improvements in bit-error rate (BER) and positioning error (PE), approaching the performance levels observed in synchronized VLPC systems. Specifically, the SICD-OPRC scheme reduces average BER to 4.3 × 10−4 and average PE to 2.7 cm, demonstrating its robustness and superiority in complex asynchronous scenarios.
Development of Optical Sensors Based on Neutral Red Absorbance for Real-Time pH Measurements
Authors: Olorounto Olaïtan Germaine , Deniau Guy , Zekri Elisabeth , Doizi Denis , Bertrand Johan , Corbas Vincent
Published: August 2024

Measuring pH with an optical sensor requires the immobilization of a chemical recognition phase on a solid surface. Neutral red (NR), an acid base indicator was used to develop two different optical probe configurations. The chemistry of aryl diazonium salts was chosen for the elaboration of this chemical phase, as it enables strong covalent bonds to be established on the surface of metallized glass or metallic surfaces. It also allows the formation of a thick film required to obtain an exploitable spectral response. The surfaces of interest (metallized optical fiber and 316 L stainless-steel mirror) are modelized by flat surfaces (metallized glass plates and 316 L stainless-steel plates). The analytical characterizations carried out (IR, XPS, UV-Visible, and profilometry) show that NR was covalently grafted onto the model surfaces as well as on the surfaces of interest. The supports grafted with NR to develop optical pH probes exhibit spectral changes, particularly the values of pKa, the pH range, and the isosbestic point wavelength. The experimental results show that the optical probe can be used for pH measurements between 4 and 8.
Mixed Grazing Increases Abundance of Arbuscular Mycorrhizal Fungi in Upland Welsh Grasslands
Authors: Buckle Annie Lesley , Crotty Felicity Victoria , Staddon Philip L.
Published: August 2024

Grasslands play a crucial role in exchanges between global ecosystems and the atmosphere and form an integral part of the agricultural industry. Arbuscular mycorrhizal fungi (AMF) are mutualistic symbionts of most grassland plant species and thereby influence the functional capacity of grassland systems. Agricultural grasslands are primarily used for livestock farming and are subjected to various management practices designed to increase production, but which also alter both plant and soil communities in the process. This research investigated the effects of a selection of management practices and environmental factors on the presence and abundance of AMF in upland Welsh grasslands. The aim was to identify how these management practices affected the abundance of AMF, assessed through microscopic observations of four AMF structures: spores, hyphae, vesicles and arbuscules. The results suggest grazing sheep and cattle together had the highest overall influence on AMF abundance compared to grazing sheep or cattle separately. High plant diversity correlated with high arbuscule and vesicle abundance, but conversely, the application of lime reduced vesicle abundance. These findings offer new insights into the effects of management practices on AMF. Mixing livestock, increasing plant diversity and reducing lime applications are shown here to improve the abundance of AMF and could, therefore, help to inform sustainable farm management decisions in the future.
A Dynamic Reliability Analysis for the Conditional Number of Working Components within a Structure
Authors: Triantafyllou Ioannis S.
Published: August 2024

In the present work, we study the number of working units of a consecutive-type structure at a specific time point under the condition that the system’s failure has not been observed yet. The main results of this paper offer some closed formulae for determining the distribution of the number of working components under the aforementioned condition. Several alternatives are considered for identifying the structure of the underlying system. The numerical investigation which is carried out takes into account different distributional assumptions for the lifetime of the components of the reliability system. Some concluding remarks and comments are provided for the performance of the resulting consecutive-type design.
Effects of Extreme Rainfall Change on Sediment Load in the Huangfuchuan Watershed, Loess Plateau, China
Authors: Li Erhui
Published: August 2024

Rainfall-induced erosion is a predominant factor contributing to land degradation, with extreme rainfall events exerting a significantly greater impact than average rainfall. This study investigates the variability of extreme rainfall events and their effects on sediment yields within the Huangfuchuan watershed, located in the middle reaches of the Yellow River. Utilizing daily rainfall data from ten rainfall stations and sediment load records from Huangfu Station spanning from 1980 to 2020, the Mann–Kendall non-parametric test, Pettitt test, and double mass curve analysis were carried out to assess four critical extreme rainfall indexes: daily rainfall exceeding the 95th percentile (R95p), maximum one-day rainfall (RX1day), maximum five-day rainfall (RX5day), and simple daily intensity index (SDII) and quantitatively evaluated the contribution rate of extreme rainfall to changes in sediment load within the watershed. The results revealed that during the period of study, all four extreme rainfall indexes demonstrated non-significant declining trends, whereas sediment load exhibited a highly significant decreasing trend, with abrupt changes in 1998. Prior to these changes, significant correlations were observed between extreme rainfall indexes and sediment load. From 1999 to 2020, the contribution rates of these indexes to changes in sediment load varied between 11.3% and 27.1%, with R95p showing the greatest impact and RX5day the least. The NDVI showed a significant increase (p < 0.05) and the amount of sediment retained and dam areas of check dams increased annually. This could be the main reason for the decrease in sediment load. This study clarifies the interactions between sediment load and extreme rainfall, which can be valuable for watershed management decisions.
Research Progress and Hotspots in Microbial Remediation for Polluted Soils
Authors: Zhao Shuai , Yuan Xue-Tao , Wang Xiao-Hong , Ai Yan-Jun , Li Fu-Ping
Published: August 2024

Microbial remediation has become a prominent focus in soil pollution control due to its environmental friendliness, cost-effectiveness, and high efficiency. The effectiveness of microbial remediation is rooted in the interactions between microbial metabolic activities and the soil environment. Various microorganisms employ distinct mechanisms for pollutant treatment, including surface adsorption, intracellular accumulation, and biomineralization. Using the Web of Science Core Collection database, tools such as CiteSpace 6.1.R6, VOSviewer 1.6.20, and HistCite Pro were employed to conduct a quantitative analysis of several key aspects: the volume and thematic distribution of research papers on microbial remediation of soils, the cooperative networks between countries and institutions, the leading journals, major research hotspots, and emerging trends. The analysis reveals that utilizing microbial regulatory mechanisms and functions to remediate inorganic pollutants, such as heavy metals, and organic pollutants, such as PAHs, is becoming a significant frontier in future research. This study provides a valuable reference for scholars aiming to understand the current status of microbial research in soil remediation, both domestically and internationally. It also offers guidance for developing efficient, sustainable, and safe remediation strategies while identifying directions for future innovative research. The specific results are as follows: (1) China, the USA, India, and other countries have a high frequency of citations in this field, and the research is more in-depth. (2) More and more attention has been paid to the use of microbial remediation of contaminated soil in the world, mainly in Environmental Sciences. (3) Major publications include Chemosphere, Journal of Hazardous Materials, and Science of The Total Environment. In the key literature, the use of microorganisms to restore the soil environment and the combination of microorganisms and plants to repair soil contaminated by heavy metals occupy a high proportion. (4) The key areas of focus include the application of microorganisms in soil inorganic pollution remediation, the application of microorganisms in remediation of soil organic pollution (crude oil and polycyclic aromatic hydrocarbons (PAHs)), and the contribution of microorganisms to soil pollutant degradation and toxicity assessment systems. The research and development of combined microbial remediation technology is the current research hotspot in the field of soil remediation, focusing on the symbiosis between mycorrhizal fungi and plant roots, the enhancement in the ability of microorganisms to absorb and degrade pollutants and their tolerance, and the interaction mechanism between indigenous microorganisms and plants.
Urban Guidelines and Strategic Plan for a UNESCO World Heritage Candidate Site: The Historical Centre of Sharjah (UAE)
Authors: Trusiani Elio , D’Onofrio Rosalba
Published: August 2024

This paper presents the results of theoretical and applied research that employs methodological experimentation in a project for the protection and integrated transformation of the downtown area of the city of Sharjah in the United Arab Emirates. The particular nature of this case relates to two factors: (a) strategies and policies to protect and enhance the cultural heritage as a driver for tourism and the cultural development of the entire Emirate, from archaeological goods to the urban fabrics in historical centres (Sharjah and Korfakkhan), in contrast to the surrounding Emirates; and (b) the client’s request to define guidelines to manage the urban cultural heritage during a time of transition while awaiting the results of UNESCO candidacy. This unique fact denotes a sensitivity and long-term policies regarding the cultural heritage which views the recovery of the urban historical heritage, assuming the cultural component as the fourth dimension of sustainability. The methodological approach, the results of the research, and design are organized on the dual urban and building scale to understand the structure and elements of the historical centre. The actions and interventions are differentiated with respect to urban fabric, building, archaeological good, and landscape, and translate the strategies of the guidelines into short-/mid-/long-term design actions.
Advancing Solar Power Forecasting: Integrating Boosting Cascade Forest and Multi-Class-Grained Scanning for Enhanced Precision
Authors: Boutahir Mohamed Khalifa , Farhaoui Yousef , Azrour Mourade , Sedik Ahmed , Nasralla Moustafa M.
Published: August 2024

Accurate solar power generation forecasting is paramount for optimizing renewable energy systems and ensuring sustainability in our evolving energy landscape. This study introduces a pioneering approach that synergistically integrates Boosting Cascade Forest and multi-class-grained scanning techniques to enhance the precision of solar farm power output predictions significantly. While Boosting Cascade Forest excels in capturing intricate, nonlinear variable interactions through ensemble decision tree learning, multi-class-grained scanning reveals fine-grained patterns within time-series data. Evaluation with real-world solar farm data demonstrates exceptional performance, reflected in low error metrics (mean absolute error, 0.0016; root mean square error 0.0036) and an impressive R-squared score of 99.6% on testing data. This research represents the inaugural application of these advanced techniques to solar generation forecasting, highlighting their potential to revolutionize renewable energy integration, streamline maintenance, and reduce costs. Opportunities for further refinement of ensemble models and exploration of probabilistic forecasting methods are also discussed, underscoring the significance of this work in advancing solar forecasting techniques for a sustainable energy future.
Study on the Development Status and Promotion Strategy of Zero-Emission Commercial Vehicles in China under the Background of the Dual Carbon Target
Authors: Ke Jia , Zhu Dezhao , Wang Yanjun , Hao Chunxiao , Ding Yan
Published: August 2024

The adoption of new energy vehicles (NEVs) is an effective strategy for pollution reduction, especially for high-emitting commercial vehicles. This paper systematically reviews the promotion policies and development status of zero-emission commercial vehicles (ZECVs) in China, with a focus on diverse application scenarios. Comprehensive policies, including subsidies, right-of-way, infrastructure development, and environmental protection incentives, have significantly advanced NEV adoption, as demonstrated by Shenzhen’s full electrification of buses and the extensive deployment of zero-emission trucks. Despite the overall slow development of ZECVs, regions in southern China and developed areas exhibit better progress. Medium and large passenger vehicles (MLPVs) have achieved a zero-emission rate of around 40%, contrasting with the significantly lower rates of 1.52% for mini and light trucks (MLTs) and 0.44% for medium and heavy trucks (MHTs). Electrification promotion varies significantly in different application scenarios, with buses leading at over 90% zero-emission rates, followed by the airport (24%) and port (16%) vehicles. The electrification of sanitation, logistics, and key industry transport, through lagging, is enhanced by targeted policies and local industry. Buses are designated as the highest priority (Level 1) for electrification transition while intercity logistics and vehicles in key industries are categorized as the lowest priority (Level 4). In addition, policy recommendations, including tailored strategies for ZECV promotion and emission reductions in traditional commercial vehicles, are put forward to provide guidance and reference for setting future zero-emission promotion goals and policy direction for commercial vehicles in subdivided application scenarios.