bluuebunny/crossref_metadata_2025 huggingface dataset:
Sociodemographic and Health Correlates of Multiple Health Behavior Adherence among Cancer Survivors: A Latent Class Analysis
Authors: Fong Angela J. , Llanos Adana A. M. , Ashrafi Adiba , Zeinomar Nur , Chokshi Sagar , Bandera Elisa V. , Devine Katie A. , Hudson Shawna V. , Qin Bo , O’Malley Denalee , Paddock Lisa E. , Stroup Antoinette M. , Evens Andrew M. , Manne Sharon L.
Published: May 2023

The study aimed to (a) assess current levels of adherence to the National Comprehensive Cancer Network’s multiple health behavior guidelines and (b) identify characteristics of cancer survivors associated with different adherence levels. Cancer survivors (N = 661) were identified through the state registry and completed questionnaires. Latent class analysis (LCA) was used to identify patterns of adherence. Associations between predictors with the latent classes were reported as risk ratios. LCA identified three classes: lower- (39.6%), moderate- (52.0%), and high-risk lifestyle (8.3%). Participants in the lower-risk lifestyle class had the highest probability of meeting most of the multiple health behavior guidelines compared to participants in the high-risk lifestyle class. Characteristics associated with membership in the moderate-risk lifestyle class included self-identifying as a race other than Asian/Asian American, being never married, having some college education, and having been diagnosed with later stage colorectal or lung cancer. Those in the high-risk lifestyle class were more likely to be male, never married, have a high school diploma or less, diagnosed with colorectal or lung cancer, and diagnosed with pulmonary comorbidities. Study findings can be used to inform development of future interventions to promote multiple health behavior adherence among higher risk cancer survivors.
An Ethanol Extract of Coptidis rhizoma Induces Apoptotic Cell Death in Induced Pluripotent Stem Cells and Suppresses Teratoma Formation
Authors: Kim Aeyung , Baek Su-Jin , Shin Sarah , Lee Seo-Young , Chung Sun-Ku
Published: May 2023

In cell-based regenerative medicine, induced pluripotent stem cells (iPSCs) generated from reprogrammed adult somatic cells have emerged as a useful cell source due to the lack of ethical concerns and the low risk of immune rejection. To address the risk of teratoma formation, which is a safety issue in iPSC-based cell therapy, it is essential to selectively remove undifferentiated iPSCs remaining in the iPSC-derived differentiated cell product prior to in vivo transplantation. In this study, we explored whether an ethanol extract of coptidis rhizoma (ECR) exhibited anti-teratoma activity and identified the active components involved in the selective elimination of undifferentiated iPSCs. Transcriptome analysis of iPSCs confirmed that cell death-related pathways were significantly altered by ECR treatment. Our results demonstrate that ECR effectively induced apoptotic cell death and DNA damage in iPSCs, and that reactive oxygen species generation, mitochondrial damage, caspase activation, and p53 activation were involved in ECR-mediated iPSC death. However, in iPSC-derived differentiated cells (iPSC-Diff), reduced cell viability and the DNA damage response were not observed after ECR treatment. We co-cultured iPSCs and iPSC-Diff and found that ECR treatment selectively removed iPSCs, whereas iPSC-Diff remained intact. Prior to in ovo implantation, ECR treatment of a mixed cell culture of iPSCs and iPSC-Diff significantly suppressed iPSC-derived teratoma formation. Among the main components of the ECR, berberine and coptisine showed selective cytotoxicity to iPSCs but not to iPSC-Diff. Together, these results indicate the usefulness of ECRs in preparing safe and effective iPSC-based therapeutic cell products with no risk of teratoma formation.
Screening and Elucidation of Chemical Structures of Novel Mammalian α-Glucosidase Inhibitors Targeting Anti-Diabetes Drug from Herbals Used by E De Ethnic Tribe in Vietnam
Authors: Nguyen Van Bon , Wang San-Lang , Phan Tu Quy , Pham Thi Huyen Thoa , Huang Hung-Tse , Liaw Chia-Ching , Nguyen Anh Dzung
Published: May 2023

Among ten extracts of indigenous medicinal plants, the MeOH extract of Terminalia triptera Stapf. (TTS) showed the most efficient mammalian α-glucosidase inhibition for the first time. The data of screening bioactive parts used indicated that the TTS trunk bark and leaves extracts demonstrated comparable and higher effects compared to acarbose, a commercial anti-diabetic drug, with half-maximal inhibitory concentration (IC50) values of 181, 331, and 309 µg/mL, respectively. Further bioassay-guided purification led to the isolation of three active compounds from the TTS trunk bark extract and identified as (−)-epicatechin (1), eschweilenol C (2), and gallic acid (3). Of these, compounds 1 and 2 were determined as novel and potent mammalian α-glucosidase inhibitors. The virtual study indicated that these compounds bind to α-glucosidase (Q6P7A9) with acceptable RMSD values (1.16–1.56 Å) and good binding energy (DS values in the range of −11.4 to −12.8 kcal/mol) by interacting with various prominent amino acids to generate five and six linkages, respectively. The data of Lipinski’s rule of five and absorption, distribution, metabolism, excretion and toxicity (ADMET)-based pharmacokinetics and pharmacology revealed that these purified compounds possess anti-diabetic drug properties, and the compounds are almost not toxic for human use. Thus, the findings of this work suggested that (−)-epicatechin and eschweilenol C are novel potential mammalian α-glucosidase inhibitor candidates for type 2 diabetes treatment.
Insulin-like Growth Factor-1 (IGF-1) Related Drugs in Pain Management
Authors: Jin Seokhyun , Cheng Jianguo
Published: May 2023

Objective. The aim of this review is to explore the role of IGF-1 and IGF-1R inhibitors in pain-related conditions and assess the effectiveness of IGF-1-related drugs in pain management. Specifically, this paper investigates the potential involvement of IGF-1 in nociception, nerve regeneration, and the development of neuropathic pain. Methods. We conducted a search of the PUBMED/MEDLINE database, Scopus, and the Cochrane Library for all reports published in English on IGF-1 in pain management from origination through November 2022. The resulting 545 articles were screened, and 18 articles were found to be relevant after reading abstracts. After further examination of the full text of these articles, ten were included in the analysis and discussion. The levels of clinical evidence and implications for recommendations of all the included human studies were graded. Results. The search yielded 545 articles, of which 316 articles were deemed irrelevant by reading the titles. There were 18 articles deemed relevant after reading abstracts, of which 8 of the reports were excluded due to lack of IGF-1-related drug treatment after reviewing the full text of the articles. All ten articles were retrieved for analysis and discussion. We found that IGF-1 may have several positive effects on pain management, including promoting the resolution of hyperalgesia, preventing chemotherapy-induced neuropathy, reversing neuronal hyperactivity, and elevating the nociceptive threshold. On the other hand, IGF-1R inhibitors may alleviate pain in mice with injury of the sciatic nerve, bone cancer pain, and endometriosis-induced hyperalgesia. While one study showed marked improvement in thyroid-associated ophthalmopathy in humans treated with IGF-1R inhibitor, two other studies did not find any benefits from IGF-1 treatment. Conclusions. This review highlights the potential of IGF-1 and IGF-1R inhibitors in pain management, but further research is needed to fully understand their efficacy and potential side effects.
Honey-Related Treatment Strategies in Dry Eye Disease
Authors: Prinz Julia , Maffulli Nicola , Fuest Matthias , Walter Peter , Hildebrand Frank , Migliorini Filippo
Published: May 2023

This systematic review and meta-analysis investigated whether honey-related treatment strategies improve the signs and symptoms of patients with dry eye disease (DED). In March 2023, the following databases were accessed for clinical trials investigating the efficacy of honey-related treatment strategies in DED: PubMed, Web of Science, Google Scholar, and EMBASE. The following data were extracted at baseline and at the last follow-up: Ocular Surface Disease Index, tear breakup time, Schirmer I test, and corneal staining. Data from 323 patients were retrieved (53.3% female, mean age 40.6 ± 18.1 years). The mean follow-up was 7.0 ± 4.2 weeks. All the endpoints of interest significantly improved from baseline to the last follow-up: tear breakup time (p = 0.01), Ocular Surface Disease Index (p < 0.0001), Schirmer I test (p = 0.0001), and corneal staining (p < 0.0001). No difference was found in tear breakup time (p = 0.3), Ocular Surface Disease Index (p = 0.4), Schirmer I test (p = 0.3), and corneal staining (p = 0.3) between the honey-related treatment strategies and the control groups. According to our main results, honey-related treatment strategies are effective and feasible to improve symptoms and signs of DED.
Triple-Therapy of Peritoneal Metastasis—Partial-Dehydration under Hyperthermic Condition Combined with Chemotherapy: The First Preliminary In-Vitro Results
Authors: Khosrawipour Carolina , Diakun Agata , Li Shiri , Lau Hien , Kulas Joanna , Khosrawipour Veria , Kielan Wojciech , Mikolajczyk-Martinez Agata
Published: May 2023

A newly introduced combination of intraperitoneal dehydration and hyperthermia has recently been shown to be feasible and cytotoxic for colon cancer cells in vivo. For the first time, our study now aims to evaluate dehydration under hyperthermic conditions combined with chemotherapy for potential use in the clinical setting. In this study, in vitro colon cancer cells (HT-29) were subjected to single or several cycles of partial dehydration under hyperthermic conditions (45 °C), followed by chemotherapy (triple exposure) with oxaliplatin or doxorubicin in various configurations. The viability, cytotoxicity, and proliferation of cells after the proposed protocols were assessed. Intracellular doxorubicin uptake was measured via flow cytometry. After one cycle of triple exposure, the viability of HT-29 cells was significantly reduced versus the untreated control (65.11 ± 5%, p < 0.0001) and versus only chemotherapy (61.2 ± 7%, p < 0.0001). An increased chemotherapeutic inflow into the cells after triple exposure was detected (53.4 ± 11%) when compared to cells treated with chemotherapy alone (34.23 ± 10%) (p < 0.001). Partial dehydration in a hyperthermic condition combined with chemotherapy increases the overall cytotoxicity of colon cancer cells significantly compared to chemotherapy alone. This could possibly be related to enhanced intracellular uptake of chemotherapeutic agents after partial dehydration. Further studies are required for the further evaluation of this new concept.
Photons as a Signal of Deconfinement in Hadronic Matter under Extreme Conditions
Authors: Nedelko Sergei , Nikolskii Aleksei
Published: May 2023

The photon production by conversion of gluons gg→γ via quark loop in the framework of the mean-field approach to the QCD (quantunm chromodynamics) vacuum is studied here. According to the domain model of QCD vacuum, the confinement phase is dominated by Abelian (anti-)self-dual gluon fields, while the deconfinement phase is characterized by a strong chromomagnetic field. In the confinement phase, photon production is impossible due to the random spacial orientation of the statistical ensemble of vacuum fields. However, the conditions of Furry theorem are not satisfied in the deconfinement phase, the conversion of gluons is nonzero and, in addition, photon distribution has a strong angular anisotropy. Thus, the photon production in the discussed process acts as one of the important features of transition in quark-gluon plasma to the deconfinement phase.
Orthorhombic Crystal Structure of Grossular Garnet (Suva Česma, Western Serbia): Evidence from the Rietveld Refinement
Authors: Tančić Pavle , Dušanić Slađana , Erić Suzana
Published: May 2023

The grossular garnet from rodingite-type rock from the Suva Česma area in western Serbia is characterized with its weak anisotropic nature. Because its anisotropy could indicate a non-cubic lower symmetry, SEM-EDS and Rietveld powder refinement methods were used. The SEM-EDS results have shown that the garnet has a (Ca3.00Mn0.01)3.01(Al1.82Fe0.15Ti0.02)1.99(Si2.97Al0.03)3.00O12 chemical composition (i.e., Grs91Adr08), which can be more specifically explained as ferric iron containing grossular. The next step further used Rietveld powder refinements of the various crystal structures in the Ia‾3d, R‾3c, R‾3, I41/a, Fddd, C2/c, and I‾1 space groups as well as a single mixture, which was followed by a comparative analysis of the R-values, site occupancy factors, and bond lengths and angles. The synthesis of these results showed both that the studied grossular garnet is not cubic and that it crystallized in the disordered Fddd space group with the final RB = 5.29% and RF = 1.75%. It was presumed that the grossular formed at temperatures between 150 and ~600 °C.
Finite-Difference Hermite WENO Scheme for Degasperis-Procesi Equation
Authors: Li Liang , Feng Yapu , Wang Yanmeng , Pang Liuyong , Zhu Jun
Published: May 2023

We present a fifth-order finite-difference Hermite weighted essentially non-oscillatory (HWENO) method for solving the Degasperis–Procesi (DP) equation in this paper. First, the DP equation can be rewritten as a system of equations consisting of hyperbolic equations and elliptic equations by introducing an auxiliary variable, since the equations contain nonlinear higher order derivative terms. Then, the auxiliary variable equations are solved using the Hermite interpolation, while the HWENO scheme is performed for the hyperbolic equations. Compared with the popular WENO-type scheme, the most important feature of the HWENO scheme mentioned in this paper is the compactness of its spatial reconstruction stencil, which can achieve the fifth-order accuracy of the expected design with only three points, while the WENO method requires five points. Finally, we demonstrate the effectiveness of the HWENO method in various aspects by conducting some benchmark numerical tests.
Optimal Design of Perforated Diversion Wall Based on Comprehensive Evaluation Indicator and Response Surface Method: A Case Study
Authors: Xu Bo , Xu Shuaipeng , Xia Hui , Liu Jianfeng , Shen Yiyun , Xu Lei , Xi Wang , Lu Weigang
Published: May 2023

To investigate the impact of parameters of diversion wall holes on the flow state in the forebay of a combined sluice-pumping station project and optimize the relevant parameters, a total of 50 numerical simulations based on the CFD technique were performed, adopting the design of orthogonal experiments with 25 schemes under self-draining conditions and pumping conditions, respectively. For synthesizing flow state evaluation indicators under self-draining and pumping conditions, the variation coefficient method was used, and the results were analyzed through the response surface method. Thus, the relationship between the parameters of the diversion wall holes and the comprehensive evaluation indicator was established. The steepest ascent method was used to obtain the optimal parameters, and the results showed that the optimized holes can balance the flow state under self-draining and pumping conditions in the combined sluice-pumping station project. Compared to the case with the diversion wall unperforated, the uniformity of axial velocity distribution in the 6# inlet channel and 7# sluice chamber increased by 6.6% and 5.2%, respectively, and the maximum transverse velocity decreased from 0.32 m/s to 0.21 m/s, with a fall of 34.4%. This study provides reference and technical support for the hydraulic characteristic analysis, optimization design and rectifying measures selection of the combined sluice-pumping station project.
“Our Freedom in Christ”: Revisiting Pauline Imagery of Freedom and Slavery in His Letter to the Galatians in Context
Authors: Hogeterp Albert L. A.
Published: May 2023

The Letter to the Galatians is a polemical correspondence about the course of gospel mission that is at stake in the view of the apostle Paul. When Paul represents his own contacts with the Jerusalem church, he defends “our freedom which we have in Christ Jesus” (Gal 2:4). In his aim to focus on the unity of all in Christ, Paul even goes at lengths to state that there is no difference between slave and free (Gal 3:28), while polemically associating both a former state of unbelievers (Gal 4:8) and the emphasis by missionary opponents on circumcision and the covenant of the law (Gal 4:12–31) with bondage and slavery. Yet, what did freedom (ἐλευθερία, Gal 2:4) and its opposite, slavery (δουλεία, Gal 4:24, 5:1), exactly mean in the ancient world in which Paul and his readers lived and communicated? Jews, Greeks, and Romans did not necessarily mean the same by these terms, nor did freedom necessarily mean exactly the same as modern conceptions of the term. This paper aims to contextualize Paul’s imagery with a view to biblical traditions, early Jewish notions of freedom, and Graeco-Roman registers of discourse, taking into account historical, literary, linguistic, and rhetorical-critical contexts of interpretation and revisiting the language of freedom and slavery with a view to insights from linguistic anthropology. The paper then revisits the Pauline position of “freedom in Christ” in relation to previous hypotheses of Paul’s gospel mission.
A New Approach to Estimate Fuel Budget and Wildfire Hazard Assessment in Commercial Plantations Using Drone-Based Photogrammetry and Image Analysis
Authors: Penglase Kim , Lewis Tom , Srivastava Sanjeev K.
Published: May 2023

Increased demand for sustainable timber products has resulted in large investments in agroforestry in Australia, with plantations growing various Pinus species, selected to suit a plantation’s environment. Juvenile Pinus species have a low fire tolerance. With Australia’s history of wildfires and the likelihood of climate change exacerbating that risk, the potential for a total loss of invested capital is high unless cost-effective targeted risk minimisation is part of forest management plans. Based on the belief that the understory profiles within the juvenile plantations are a major factor determining fuel hazard risks, an accurate assessment of these profiles is required to effectively mitigate those risks. At present, assessment protocols are largely reliant on ground-based observations, which are labour-intensive, time consuming, and expensive. This research project investigates the effectiveness of using geospatial analysis of drone-derived photographic data collected in the commercial pine plantations of south-eastern Queensland as a cost-saving alternative to current fuel hazard risk assessment practices. Understory composition was determined using the supervised classification of orthomosaic images together with derivations of canopy height models (CHMs). The CHMs were subjected to marker-controlled watershed segmentation (MCWS) analysis, isolating and removing the plantation pine trees, enabling the quantification of understory fuel profiles. The method used proved highly applicable to immature forest environments with minimal canopy closure, but became less reliable for close canopied older plantations.
Improved Object-Based Mapping of Aboveground Biomass Using Geographic Stratification with GEDI Data and Multi-Sensor Imagery
Authors: Chen Lin , Ren Chunying , Zhang Bai , Wang Zongming , Man Weidong , Liu Mingyue
Published: May 2023

Aboveground biomass (AGB) mapping using spaceborne LiDAR data and multi-sensor images is essential for efficient carbon monitoring and climate change mitigation actions in heterogeneous forests. The optimal predictors of remote sensing-based AGB vary greatly with geographic stratification, such as topography and forest type, while the way in which geographic stratification influences the contributions of predictor variables in object-based AGB mapping is insufficiently studied. To address the improvement of mapping forest AGB by geographic stratification in heterogeneous forests, satellite multisensory data from global ecosystem dynamics investigation (GEDI) and series of advanced land observing satellite (ALOS) and Sentinel were integrated. Multi-sensor predictors for the AGB modeling of different types of forests were selected using a correlation analysis of variables calculated from topographically stratified objects. Random forests models were built with GEDI-based AGB and geographically stratified predictors to acquire wall-to-wall biomass values. It was illustrated that the mapped biomass had a similar distribution and was approximate to the sampled forest AGB. Through an accuracy comparison using independent validation samples, it was determined that the geographic stratification approach improved the accuracy by 34.79% compared to the unstratified process. Stratification of forest type further increased the mapped AGB accuracy compared to that of topography. Topographical stratification greatly influenced the predictors’ contributions to AGB mapping in mixed broadleaf–conifer and broad-leaved forests, but only slightly impacted coniferous forests. Optical variables were predominant for deciduous forests, while for evergreen forests, SAR indices outweighed the other predictors. As a pioneering estimation of forest AGB with geographic stratification using satellite multisensory data, this study offers optimal predictors and an advanced method for obtaining carbon maps in heterogeneous regional landscapes.
Climate-Change-Driven Droughts and Tree Mortality: Assessing the Potential of UAV-Derived Early Warning Metrics
Authors: Ewane Ewane Basil , Mohan Midhun , Bajaj Shaurya , Galgamuwa G. A. Pabodha , Watt Michael S. , Arachchige Pavithra Pitumpe , Hudak Andrew T. , Richardson Gabriella , Ajithkumar Nivedhitha , Srinivasan Shruthi , Corte Ana Paula Dalla , Johnson Daniel J. , Broadbent Eben North , de-Miguel Sergio , Bruscolini Margherita , Young Derek J. N. , Shafai Shahid , Abdullah Meshal M. , Jaafar Wan Shafrina Wan Mohd , Doaemo Willie , Silva Carlos Alberto , Cardil Adrian
Published: May 2023

Protecting and enhancing forest carbon sinks is considered a natural solution for mitigating climate change. However, the increasing frequency, intensity, and duration of droughts due to climate change can threaten the stability and growth of existing forest carbon sinks. Extreme droughts weaken plant hydraulic systems, can lead to tree mortality events, and may reduce forest diversity, making forests more vulnerable to subsequent forest disturbances, such as forest fires or pest infestations. Although early warning metrics (EWMs) derived using satellite remote sensing data are now being tested for predicting post-drought plant physiological stress and mortality, applications of unmanned aerial vehicles (UAVs) are yet to be explored extensively. Herein, we provide twenty-four prospective approaches classified into five categories: (i) physiological complexities, (ii) site-specific and confounding (abiotic) factors, (iii) interactions with biotic agents, (iv) forest carbon monitoring and optimization, and (v) technological and infrastructural developments, for adoption, future operationalization, and upscaling of UAV-based frameworks for EWM applications. These UAV considerations are paramount as they hold the potential to bridge the gap between field inventory and satellite remote sensing for assessing forest characteristics and their responses to drought conditions, identifying and prioritizing conservation needs of vulnerable and/or high-carbon-efficient tree species for efficient allocation of resources, and optimizing forest carbon management with climate change adaptation and mitigation practices in a timely and cost-effective manner.
A CNN-Based Layer-Adaptive GCPs Extraction Method for TIR Remote Sensing Images
Authors: Zhao Lixing , Jiao Jingjie , Yang Lan , Pan Wenhao , Zeng Fanjun , Li Xiaoyan , Chen Fansheng
Published: May 2023

Ground Control Points (GCPs) are of great significance for applications involving the registration and fusion of heterologous remote sensing images (RSIs). However, utilizing low-level information rather than deep features, traditional methods based on intensity and local image features turn out to be unsuitable for heterologous RSIs because of the large nonlinear radiation difference (NRD), inconsistent resolutions, and geometric distortions. Additionally, the limitations of current heterologous datasets and existing deep-learning-based methods make it difficult to obtain enough precision GCPs from different kinds of heterologous RSIs, especially for thermal infrared (TIR) images that present low spatial resolution and poor contrast. In this paper, to address the problems above, we propose a convolutional neural network-based (CNN-based) layer-adaptive GCPs extraction method for TIR RSIs. Particularly, the constructed feature extraction network is comprised of basic and layer-adaptive modules. The former is used to achieve the coarse extraction, and the latter is designed to obtain high-accuracy GCPs by adaptively updating the layers in the module to capture the fine communal homogenous features of the heterologous RSIs until the GCP precision meets the preset threshold. Experimental results evaluated on TIR images of SDGSAT-1 TIS and near infrared (NIR), short wave infrared (SWIR), and panchromatic (PAN) images of Landsat-8 OLI show that the matching root-mean-square error (RMSE) of TIS images with SWIR and NIR images could reach 0.8 pixels and an even much higher accuracy of 0.1 pixels could be reached between TIS and PAN images, which performs better than those of the traditional methods, such as SIFT, RIFT, and the CNN-based method like D2-Net.
Joint Optimization of Data Transmission and Energy Harvesting in Relay Satellite Networks
Authors: Long Jun , Wan Ying , Guo Lin , Liu Limin , Ding Rui
Published: May 2023

Satellite network is considered a prominent architecture for future space-air-ground integrated networks, where the relay satellite network (RSN) plays an essential role in data transmission. However, the relay satellite network faces practical challenges. First, due to the dynamic network topology and limited resources such as storage capacity, antennas, and bandwidth, optimizing data transmission and resource allocation in a resource-constrained stochastic system is challenging. Second, satellites intermittently enter the eclipse zone, which leads to an unstable energy supply. Therefore, optimal energy management is required to balance energy supply and consumption. In this paper, we proposed an online optimal control algorithm, based on Lyapunov stability theory, to optimize data transmission and energy management jointly. Furthermore, the performance of our proposal is analyzed comprehensively, including the reasonable bounds for data and energy and the optimality of our proposed algorithm. Finally, extensive performance evaluation simulations are performed based on real-world satellite parameters. The simulation results indicate that the proposed method can achieve long-term network stability and energy sustainability. Moreover, the proposed algorithm shows an improvement of 9.6% and 20.3% in system utility compared to the non-optimized transmission method and non-optimized energy management algorithm, respectively.
Impact of Horizontal Resolution on the Robustness of Radiation Emulators in a Numerical Weather Prediction Model
Authors: Song Hwan-Jin , Roh Soonyoung
Published: May 2023

Developing a machine-learning-based radiative transfer emulator in a weather forecasting model is valuable because it can significantly improve the computational speed of forecasting severe weather events. To replace the radiative transfer parameterization in the weather forecasting model, the universal applicability of the radiation emulator is essential, indicating a transition from the research to the operational level. This study investigates the degradation of the forecast accuracy of the radiation emulator for the Korea peninsula when it is tested at different horizontal resolutions (100–0.25 km) concerning the accuracy attained at the training resolution (5 km) for universal applications. In real-case simulations (100–5 km), the forecast errors of radiative fluxes and precipitation were reduced at coarse resolutions. Ideal-case simulations (5–0.25 km) showed larger errors in heating rates and fluxes at fine resolutions, implying the difficulty in predicting heating rates and fluxes at cloud-resolving scales. However, all simulations maintained an appropriate accuracy range compared with observations in real-case simulations or the infrequent use of radiative transfer parameterization in ideal-case simulations. These findings demonstrate the feasibility of a universal radiation emulator associated with different resolutions/models and emphasize the importance of emulating high-resolution modeling in the future.
Removing Human Bottlenecks in Bird Classification Using Camera Trap Images and Deep Learning
Authors: Chalmers Carl , Fergus Paul , Wich Serge , Longmore Steven N. , Walsh Naomi Davies , Stephens Philip A. , Sutherland Chris , Matthews Naomi , Mudde Jens , Nuseibeh Amira
Published: May 2023

Birds are important indicators for monitoring both biodiversity and habitat health; they also play a crucial role in ecosystem management. Declines in bird populations can result in reduced ecosystem services, including seed dispersal, pollination and pest control. Accurate and long-term monitoring of birds to identify species of concern while measuring the success of conservation interventions is essential for ecologists. However, monitoring is time-consuming, costly and often difficult to manage over long durations and at meaningfully large spatial scales. Technology such as camera traps, acoustic monitors and drones provide methods for non-invasive monitoring. There are two main problems with using camera traps for monitoring: (a) cameras generate many images, making it difficult to process and analyse the data in a timely manner; and (b) the high proportion of false positives hinders the processing and analysis for reporting. In this paper, we outline an approach for overcoming these issues by utilising deep learning for real-time classification of bird species and automated removal of false positives in camera trap data. Images are classified in real-time using a Faster-RCNN architecture. Images are transmitted over 3/4G cameras and processed using Graphical Processing Units (GPUs) to provide conservationists with key detection metrics, thereby removing the requirement for manual observations. Our models achieved an average sensitivity of 88.79%, a specificity of 98.16% and accuracy of 96.71%. This demonstrates the effectiveness of using deep learning for automatic bird monitoring.
Joint Learning of Correlation-Constrained Fuzzy Clustering and Discriminative Non-Negative Representation for Hyperspectral Band Selection
Authors: Li Zelin , Wang Wenhong
Published: May 2023

Hyperspectral band selection plays an important role in overcoming the curse of dimensionality. Recently, clustering-based band selection methods have shown promise in the selection of informative and representative bands from hyperspectral images (HSIs). However, most existing clustering-based band selection methods involve the clustering of original HSIs, limiting their performance because of the high dimensionality of hyperspectral bands. To tackle this problem, a novel hyperspectral band selection method termed joint learning of correlation-constrained fuzzy clustering and discriminative non-negative representation for hyperspectral band selection (CFNR) is presented. In CFNR, graph regularized non-negative matrix factorization (GNMF) and constrained fuzzy C-means (FCM) are integrated into a unified model to perform clustering on the learned feature representation of bands rather than on the original high-dimensional data. Specifically, the proposed CFNR aims to learn the discriminative non-negative representation of each band for clustering by introducing GNMF into the model of the constrained FCM and making full use of the intrinsic manifold structure of HSIs. Moreover, based on the band correlation property of HSIs, a correlation constraint, which enforces the similarity of clustering results between neighboring bands, is imposed on the membership matrix of FCM in the CFNR model to obtain clustering results that meet the needs of band selection. The alternating direction multiplier method is adopted to solve the joint optimization model. Compared with existing methods, CFNR can obtain a more informative and representative band subset, thus can improve the reliability of hyperspectral image classifications. Experimental results on five real hyperspectral datasets demonstrate that CFNR can achieve superior performance compared with several state-of-the-art methods.
Infrared Evanescent Wave Sensing Based on a Ge10As30Se40Te20 Fiber for Alcohol Detection
Authors: Li Zijian , Zhao Yongkun , You Tianxiang , Zhu Jihong , Xia Mengling , Lu Ping , Zhang Xianghua , Xu Yinsheng
Published: May 2023

Infrared evanescent wave sensing based on chalcogenide fiber is an emerging technology for qualitative and quantitative analysis of most organic compounds. Here, a tapered fiber sensor made from Ge10As30Se40Te20 glass fiber was reported. The fundamental modes and intensity of evanescent waves in fibers with different diameters were simulated with COMSOL. The 30 mm length tapered fiber sensors with different waist diameters, 110, 63, and 31 μm, were fabricated for ethanol detection. The sensor with a waist diameter of 31 μm has the highest sensitivity of 0.73 a.u./% and a limit of detection (LoD) of 0.195 vol.% for ethanol. Finally, this sensor has been used to analyze alcohols, including Chinese baijiu (Chinese distilled spirits), red wine, Shaoxing wine (Chinese rice wine), Rio cocktail, and Tsingtao beer. It is shown that the ethanol concentration is consistent with the nominal alcoholicity. Moreover, other components such as CO2 and maltose can be detected in Tsingtao beer, demonstrating the feasibility of its application in detecting food additives.
Evaluation of the Accuracy of Contactless Consumer Sleep-Tracking Devices Application in Human Experiment: A Systematic Review and Meta-Analysis
Authors: Zhai Huifang , Yan Yonghong , He Siqi , Zhao Pinyong , Zhang Bohan
Published: May 2023

Compared with the gold standard, polysomnography (PSG), and silver standard, actigraphy, contactless consumer sleep-tracking devices (CCSTDs) are more advantageous for implementing large-sample and long-period experiments in the field and out of the laboratory due to their low price, convenience, and unobtrusiveness. This review aimed to examine the effectiveness of CCSTDs application in human experiments. A systematic review and meta-analysis (PRISMA) of their performance in monitoring sleep parameters were conducted (PROSPERO: CRD42022342378). PubMed, EMBASE, Cochrane CENTRALE, and Web of Science were searched, and 26 articles were qualified for systematic review, of which 22 provided quantitative data for meta-analysis. The findings show that CCSTDs had a better accuracy in the experimental group of healthy participants who wore mattress-based devices with piezoelectric sensors. CCSTDs’ performance in distinguishing waking from sleeping epochs is as good as that of actigraphy. Moreover, CCSTDs provide data on sleep stages that are not available when actigraphy is used. Therefore, CCSTDs could be an effective alternative tool to PSG and actigraphy in human experiments.
Vision-Based Automated Recognition and 3D Localization Framework for Tower Cranes Using Far-Field Cameras
Authors: Wang Jiyao , Zhang Qilin , Yang Bin , Zhang Binghan
Published: May 2023

Tower cranes can cover most of the area of a construction site, which brings significant safety risks, including potential collisions with other entities. To address these issues, it is necessary to obtain accurate and real-time information on the orientation and location of tower cranes and hooks. As a non-invasive sensing method, computer vision-based (CVB) technology is widely applied on construction sites for object detection and three-dimensional (3D) localization. However, most existing methods mainly address the localization on the construction ground plane or rely on specific viewpoints and positions. To address these issues, this study proposes a framework for the real-time recognition and localization of tower cranes and hooks using monocular far-field cameras. The framework consists of four steps: far-field camera autocalibration using feature matching and horizon-line detection, deep learning-based segmentation of tower cranes, geometric feature reconstruction of tower cranes, and 3D localization estimation. The pose estimation of tower cranes using monocular far-field cameras with arbitrary views is the main contribution of this paper. To evaluate the proposed framework, a series of comprehensive experiments were conducted on construction sites in different scenarios and compared with ground-truth data obtained by sensors. The experimental results show that the proposed framework achieves high precision in both crane jib orientation estimation and hook position estimation, thereby contributing to the development of safety management and productivity analysis.
Cyber-Enabled Optimization of HVAC System Control in Open Space of Office Building
Authors: Peng Bo , Hsieh Sheng-Jen
Published: May 2023

Thermal comfort is crucial to well-being and work productivity. Human thermal comfort is mainly controlled by HVAC (heating, ventilation, air conditioning) systems in buildings. However, the control metrics and measurements of thermal comfort in HVAC systems are often oversimplified using limited parameters and fail to accurately control thermal comfort in indoor climates. Traditional comfort models also lack the ability to adapt to individual demands and sensations. This research developed a data-driven thermal comfort model to improve the overall thermal comfort of occupants in office buildings. An architecture based on cyber-physical system (CPS) is used to achieve these goals. A building simulation model is built to simulate multiple occupants’ behaviors in an open-space office building. Results suggest that a hybrid model can accurately predict occupants’ thermal comfort level with reasonable computing time. In addition, this model can improve occupants’ thermal comfort by 43.41% to 69.93%, while energy consumption remains the same or is slightly reduced (1.01% to 3.63%). This strategy can potentially be implemented in real-world building automation systems with appropriate sensor placement in modern buildings.
UWV-Yolox: A Deep Learning Model for Underwater Video Object Detection
Authors: Pan Haixia , Lan Jiahua , Wang Hongqiang , Li Yanan , Zhang Meng , Ma Mojie , Zhang Dongdong , Zhao Xiaoran
Published: May 2023

Underwater video object detection is a challenging task due to the poor quality of underwater videos, including blurriness and low contrast. In recent years, Yolo series models have been widely applied to underwater video object detection. However, these models perform poorly for blurry and low-contrast underwater videos. Additionally, they fail to account for the contextual relationships between the frame-level results. To address these challenges, we propose a video object detection model named UWV-Yolox. First, the Contrast Limited Adaptive Histogram Equalization method is used to augment the underwater videos. Then, a new CSP_CA module is proposed by adding Coordinate Attention to the backbone of the model to augment the representations of objects of interest. Next, a new loss function is proposed, including regression and jitter loss. Finally, a frame-level optimization module is proposed to optimize the detection results by utilizing the relationship between neighboring frames in videos, improving the video detection performance. To evaluate the performance of our model, We construct experiments on the UVODD dataset built in the paper, and select mAP@0.5 as the evaluation metric. The mAP@0.5 of the UWV-Yolox model reaches 89.0%, which is 3.2% better than the original Yolox model. Furthermore, compared with other object detection models, the UWV-Yolox model has more stable predictions for objects, and our improvements can be flexibly applied to other models.
A Systematic Solution for Moving-Target Detection and Tracking While Only Using a Monocular Camera
Authors: Wang Shun , Xu Sheng , Ma Zhihao , Wang Dashuai , Li Weimin
Published: May 2023

This paper focuses on moving-target detection and tracking in a three-dimensional (3D) space, and proposes a visual target tracking system only using a two-dimensional (2D) camera. To quickly detect moving targets, an improved optical flow method with detailed modifications in the pyramid, warping, and cost volume network (PWC-Net) is applied. Meanwhile, a clustering algorithm is used to accurately extract the moving target from a noisy background. Then, the target position is estimated using a proposed geometrical pinhole imaging algorithm and cubature Kalman filter (CKF). Specifically, the camera’s installation position and inner parameters are applied to calculate the azimuth, elevation angles, and depth of the target while only using 2D measurements. The proposed geometrical solution has a simple structure and fast computational speed. Different simulations and experiments verify the effectiveness of the proposed method.
A Comparative Study of Smart THD-Based Fault Protection Techniques for Distribution Networks
Authors: Al Hanaineh Wael , Matas Jose , Guerrero Josep M.
Published: May 2023

The integration of Distributed Generators (DGs) into distribution systems (DSs) leads to more reliable and efficient power delivery for customers. However, the possibility of bi-directional power flow creates new technical problems for protection schemes. This poses a threat to conventional strategies because the relay settings have to be adjusted depending on the network topology and operational mode. As a solution, it is important to develop novel fault protection techniques to ensure reliable protection and avoid unnecessary tripping. In this regard, Total Harmonic Distortion (THD) can be used as a key parameter for evaluating the grid’s waveform quality during fault events. This paper presents a comparison between two DS protection strategies that employ THD levels, estimated amplitude voltages, and zero-sequence components as instantaneous indicators during the faults that function as a kind of fault sensor to detect, identify, and isolate faults. The first method uses a Multiple Second Order Generalized Integrator (MSOGI) to obtain the estimated variables, whereas the second method uses a single SOGI for the same purpose (SOGI-THD). Both methods rely on communication lines between protective devices (PDs) to facilitate coordinated protection. The effectiveness of these methods is assessed by using simulations in MATLAB/Simulink considering various factors such as different types of faults and DG penetrations, different fault resistances and fault locations in the proposed network. Moreover, the performance of these methods is compared with conventional overcurrent and differential protections. The results show that the SOGI-THD method is highly effective in detecting and isolating faults with a time interval of 6–8.5 ms using only three SOGIs while requiring only 447 processor cycles for execution. In comparison to other protection methods, the SOGI-THD method exhibits a faster response time and a lower computational burden. Furthermore, the SOGI-THD method is robust to harmonic distortion, as it considers pre-existing harmonic content before the fault and avoids interference with the fault detection process.
Changes in Soil Water Retention and Micromorphological Properties Induced by Wetting and Drying Cycles
Authors: Pires Luiz F.
Published: May 2023

Wetting and drying (W-D) cycles are responsible for significant changes in soil structure. Soil often undergoes irreversible changes affecting infiltration and solute retention through W-D cycles. Thus, it becomes essential to evaluate how soils under natural conditions are altered by W-D cycles. This study analyzed two non-cultivated (from grassland and secondary forest) Oxisols (Typic Hapludox and Rhodic Hapludox) of different textures under 0 and 6 W-D cycles. The main results obtained showed that soil water retention was mainly affected in the driest regions (smaller pore sizes). The contribution of residual pores to total porosity increased with 6 W-D and transmission pores decreased in both soils. The Rhodic Hapludox presented differences in water content at field capacity (increase), while the Typic Hapludox showed alterations at the permanent wilting point (increase), affecting the amount of free water (Rhodic Hapludox) and water available to plants (Typic Hapludox). Both soils showed increases in imaged porosity with 6 W-D. Variations in the contribution of small and medium rounded pores, mainly large and irregular (with an increase in both soils not significant in the Rhodic Hapludox), could explain the results observed. The micromorphological properties were mainly influenced by changes in the number of pores, in which smaller pores joined, forming larger ones, increasing the areas occupied by larger pores. Overall, this study showed that the investigated soils presented pore systems with adequate water infiltration and retention capacities before and after continuous W-D cycles.
Blueberries as a Source of Energy: Physical Chemistry Characterization of Their Anthocyanins as Dye-Sensitized Solar Cells’ Sensitizers
Authors: Montagni Tatiana , Rodríguez Chialanza Mauricio , Cerdá María Fernanda
Published: May 2023

This work aimed to show the possibility of applying anthocyanins extracted from blueberries following a straightforward path as potential impregnation dyes in dye-sensitized solar cells (DSSCs), particularly in the presence of co-adsorbents, such as silver nanoparticles, as an alternative in order to profit from large amounts of discarded fruits. Following a simple procedure, anthocyanins (mainly delphinidin-3-glucoside) were obtained from blueberries (Southern Highbush type). Complete characterization was carried out in order to prove the utility of delphinidin-3-glucoside as a sensitizer in DSSCs. The analyzed anthocyanin is suitable for sensitizing because of its high molar absorptivity values within the visible region of the light spectra, the adsorption ability to a FTO/TiO2 electrode (FTO, fluorine-doped tin oxide) as confirmed by Fourier transform infrared (FTIR) as well as thermogravimetry coupled to differential scanning calorimetry (TG-DSC), a potential oxidation value near 1 V, and adequate thermal as well as light stabilities. Moreover, the cell’s conversion efficiency is improved in the presence of silver nanoparticles, reaching 0.24% (nearly a 25% increase). The sum of all these characteristics points to the application of delphinidin-3-glucoside as a sensitizer in DSSCs, offering a technological use with potential interest for countries where agricultural production offers an abundant origin of extraction.