bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing the Operational Feasibility of Integrating Point-of-Care G6PD Testing into Plasmodium vivax Malaria Management in Vietnam
Authors: Gerth-Guyette Emily , Nguyen Huyen Thanh , Nowak Spike , Hoang Nga Thu , Mai Đặng Thị Tuyết , Thị Sang Vũ , Long Nguyễn Đức , Mvundura Mercy , Nguyen Nhu , Domingo Gonzalo J. , Phúc Bùi Quang
Published: May 2023

Plasmodium vivax cases represent more than 50% of a diminishing malaria case load in Vietnam. Safe and effective radical cure strategies could support malaria elimination by 2030. This study investigated the operational feasibility of introducing point-of-care quantitative glucose-6-phosphate dehydrogenase (G6PD) testing into malaria case management practices. A prospective interventional study was conducted at nine district hospitals and commune health stations in Binh Phuoc and Gia Lai provinces in Vietnam over the period of October 2020 to October 2021. The STANDARD™ G6PD Test (SD Biosensor, Seoul, Republic of Korea) was incorporated to inform P. vivax case management. Case management data and patient and health care provider (HCP) perspectives, as well as detailed cost data were collected. The G6PD test results were interpreted correctly by HCP and the treatment algorithm was adhered to for the majority of patients. One HCP consistently ran the test incorrectly, which was identified during the monitoring and resulted in provision of refresher training and updating of training materials and patient retesting. There was wide acceptability of the intervention among patients and HCP albeit with opportunities to improve the counseling materials. Increasing the number of facilities to which the test was deployed and decreases in the malaria cases resulted in higher per patient cost for incorporating G6PD testing into the system. Commodity costs can be reduced by using the 10-unit kits compared to the 25 unit kits, particularly when the case loads are low. These results demonstrate intervention feasibility while also highlighting specific challenges for a country approaching malaria elimination.
Design, Synthesis, and Anti-Proliferative Action of Purine/Pteridine-Based Derivatives as Dual Inhibitors of EGFR and BRAFV600E
Authors: El-Kalyoubi Samar A. , Gomaa Hesham A. M. , Abdelhafez Elshimaa M. N. , Ramadan Mohamed , Agili Fatimah , Youssif Bahaa G. M.
Published: May 2023

The investigation of novel EGFR and BRAFV600E dual inhibitors is intended to serve as targeted cancer treatment. Two sets of purine/pteridine-based derivatives were designed and synthesized as EGFR/BRAFV600E dual inhibitors. The majority of the compounds exhibited promising antiproliferative activity on the cancer cell lines tested. Compounds 5a, 5e, and 7e of purine-based and pteridine-based scaffolds were identified as the most potent hits in anti-proliferative screening, with GI50 values of 38 nM, 46 nM, and 44 nM, respectively. Compounds 5a, 5e, and 7e demonstrated promising EGFR inhibitory activity, with IC50 values of 87 nM, 98 nM, and 92 nM, respectively, when compared to erlotinib’s IC50 value of 80 nM. According to the results of the BRAFV600E inhibitory assay, BRAFV600E may not be a viable target for this class of organic compounds. Finally, molecular docking studies were carried out at the EGFR and BRAFV600E active sites to suggest possible binding modes.
Versatility of Liposomes for Antisense Oligonucleotide Delivery: A Special Focus on Various Therapeutic Areas
Authors: Gupta Raghav , Salave Sagar , Rana Dhwani , Karunakaran Bharathi , Butreddy Arun , Benival Derajram , Kommineni Nagavendra
Published: May 2023

Nucleic acid therapeutics, specifically antisense oligonucleotides (ASOs), can effectively modulate gene expression and protein function, leading to long-lasting curative effects. The hydrophilic nature and large size of oligonucleotides present translational challenges, which have led to the exploration of various chemical modifications and delivery systems. The present review provides insights into the potential role of liposomes as a drug delivery system for ASOs. The potential benefits of liposomes as an ASO carrier, along with their method of preparation, characterization, routes of administration, and stability aspects, have been thoroughly discussed. A novel perspective in terms of therapeutic applications of liposomal ASO delivery in several diseases such as cancer, respiratory disease, ophthalmic delivery, infectious diseases, gastrointestinal disease, neuronal disorders, hematological malignancies, myotonic dystrophy, and neuronal disorders remains the major highlights of this review.
Application of Physiologically Based Pharmacokinetic Modeling to Predict Drug–Drug Interactions between Elexacaftor/Tezacaftor/Ivacaftor and Tacrolimus in Lung Transplant Recipients
Authors: Hong Eunjin , Carmanov Eugeniu , Shi Alan , Chung Peter S. , Rao Adupa P. , Forrester Kevin , Beringer Paul M.
Published: May 2023

Elexacaftor/tezacaftor/ivacaftor (ETI) treatment has potential benefits in lung transplant recipients, including improvements in extrapulmonary manifestations, such as gastrointestinal and sinus disease; however, ivacaftor is an inhibitor of cytochrome P450 3A (CYP3A) and may, therefore, pose a risk for elevated systemic exposure to tacrolimus. The aim of this investigation is to determine the impact of ETI on tacrolimus exposure and devise an appropriate dosing regimen to manage the risk of this drug–drug interaction (DDI). The CYP3A-mediated DDI of ivacaftor–tacrolimus was evaluated using a physiologically based pharmacokinetic (PBPK) modeling approach, incorporating CYP3A4 inhibition parameters of ivacaftor and in vitro enzyme kinetic parameters of tacrolimus. To further support the findings in PBPK modeling, we present a case series of lung transplant patients who received both ETI and tacrolimus. We predicted a 2.36-fold increase in tacrolimus exposure when co-administered with ivacaftor, which would require a 50% dose reduction of tacrolimus upon initiation of ETI treatment to avoid the risk of elevated systemic exposure. Clinical cases (N = 13) indicate a median 32% (IQR: −14.30, 63.80) increase in the dose-normalized tacrolimus trough level (trough concentration/weight-normalized daily dose) after starting ETI. These results indicate that the concomitant administration of tacrolimus and ETI may lead to a clinically significant DDI, requiring the dose adjustment of tacrolimus.
Future Climate CO2 Reduces the Tungsten Effect in Rye Plants: A Growth and Biochemical Study
Authors: Alsherif Emad , Hajjar Dina , AbdElgawad Hamada
Published: May 2023

Heavy metal pollution is one of the major agronomic challenges. Tungsten (W) exposure leads to its accumulation in plants, which in turn reduces plant growth, inhibits photosynthesis and induces oxidative damage. In addition, the predicted increase in CO2 could boost plant growth under both optimal and heavy metal stress conditions. The aim of the present study was to investigate the effect of W on growth, photosynthetic parameters, oxidative stress and redox status in rye plants under ambient and elevated (eCO2) levels. To this end, rye plants were grown under the following conditions: ambient CO2 (aCO2, 420 ppm), elevated CO2 (eCO2, 720 ppm), W stress (350 mg kg−1 soil) and W+eCO2. W stress induced significant (p < 0.05) decreases in growth and photosynthesis, increases in oxidative damages (lipid peroxidation) and the antioxidant defense system, i.e., ascorbate (ASC), reduced glutathione (GSH), GSH reductase (GR), peroxidase (POX), catalase (CAT), superoxide dismutase (SOD), ASC peroxide (APX) and dehydroascorbate reductase (DHAR). On the other hand, eCO2 decreased W uptake and improved photosynthesis, which sequentially improved plant growth. The obtained results showed that eCO2 can decrease the phytotoxicity risks of W in rye plants. This positive impact of eCO2 on reducing the negative effects of soil W was related to their ability to enhance plant photosynthesis, which in turn provided energy and a carbon source for scavenging the reactive oxygen species (ROS) accumulation caused by soil W stress.
Preparation of Bio-Foam Material from Steam-Exploded Corn Straw by In Situ Esterification Modification
Authors: Pan Yu , Zhou Yufan , Du Xiaoqing , Xu Wangjie , Lu Yuan , Wang Feng , Jiang Man
Published: May 2023

In this work, we engineered a corn-straw-based bio-foam material under the inspiration of the intrinsic morphology of the corn stem. The explosion pretreatment was applied to obtain a fibrillated cellulose starting material rich in lignin. The in situ esterification of cellulose was adopted to improve the cross-linking network of the as-developed foam bio-material. The esterification of lignin was observed in the same procedure, which provides a better cross-linking interaction. The esterified corn-straw-derived bio-foam material showed excellent elastic resilience performance with an elastic recovery ratio of 83% and an elastic modulus of 20 kPa. Meanwhile, with surface modification by hexachlorocyclotriphosphazene-functionalized lignin as the flame retardant (Lig-HCCP), the as-obtained bio-foam material demonstrated quite a good flame retardancy (with 27.3% of the LOI), as well as a heat insulation property. The corn-straw-derived bio-foam material is prospected to be a potential substitution packaging material for widely used petroleum-derived products. This work provides a new value-added application of the abundant agricultural straw biomass resources.
Comparative Studies on the Structure and Biological Activities of Two New Polysaccharides from Tricholoma sinoportentosum (TS-P) and Termitomyces albuminosus (TA-P)
Authors: Chen Xi , Yang Tong , Huang Qinghua , Li Biao , Ding Xiang , Hou Yiling
Published: May 2023

Polysaccharides are important active ingredients of living organisms. In this study, two new polysaccharides, Tricholoma sinoportentosum polysaccharide (TS-P) and Termitomyces albuminosus (TA-P), were extracted and purified using anion exchange column chromatography. The structure of each polysaccharide was identified by HPGPC, FT-IR, HPLC, GC-MS and NMR, and the biological activities were also investigated. The results of the structure identification showed that TS-P was composed of arabinose, mannose, glucose and galactose at a ratio of 1:1:3:2 and its main chain was composed of (1→4)-Arap residues, (1→4,6)-D-Manp residues and two (1→6)-Galp residues. The TA-P was composed of arabinose, glucose and galactose at a ratio of 2:4:8. Its main chain was composed of two (1→4)-β-L-Arap residues, one (1→4)-Glcp residues, three (1→2,6)-Galp residues and five (1→6)-Galp residues. The immunoassay showed that TS-P and TA-P could significantly promote the proliferation of T cells, B cells and RAW264.7 cells. The cell cycle results showed that for B cells and macrophages, TS-P and TA-P mainly affected the G0/G1 phases of the cell cycle; for T cells, TS-P affected G2/M phase, while TA-P mainly affected the G0/G1 phases. TS-P could significantly promote B cells to secrete IgA, IgG and IgD (p < 0.01), while TA-P could significantly promote the secretion of IgA and IgG (p < 0.01). The chemical structure and biological activity of TS-P and TA-P were first studied and compared to lay a theoretical foundation for the application of fungal polysaccharide.
Enhancement of LVRT Ability of DFIG Wind Turbine by an Improved Protection Scheme with a Modified Advanced Nonlinear Control Loop
Authors: Loulijat Azeddine , Chojaa Hamid , El marghichi Mouncef , Ettalabi Naoufl , Hilali Abdelilah , Mouradi Abderrahman , Abdelaziz Almoataz Y. , Elbarbary Zakaria M. Salem , Mossa Mahmoud A.
Published: May 2023

One of the problems with the doubly-fed induction generator (DFIG) is its high vulnerability to network perturbations, notably voltage dips, because of its stator windings being coupled directly to the network. As the DFIG’s stator and rotor are electromagnetically mated, the stator current peak occurs during a voltage dip causing an inrush current to the critical converter back-to-back and an overload of the DC-link capacitor. For this purpose, a series of researchers have achieved a linear and non-linear controller with a crowbar-based protection scheme. With this type of protection, the Rotor Side Converter (RSC) is disconnected momentarily, and consequently, its control of both the active and reactive output power of the stator is totally lost, leading to incorrect power quality at the point of common coupling (PCC). In this document, a robust nonlinear controller by Advanced Backstepping with Integral Action Control (ABIAC) is initially employed to monitor the rotor and the network side converters under normal network operations. In the presence of a network fault, an improved protection scheme (IPS) is tacked on to the robust nonlinear control to help enforce the behavior of the DFIG system to be able to overcome the fault. The IPS, which is formed by a crowbar and an RL series circuit, is typically located in the space between the rotor coils and the RSC converter. Compared to a standard crowbar, the developed scheme is successful to limit the rotor transient current and DC-link voltage, also an RSC disengagement to rotor windings can be prevented during the fault. Furthermore, the controllers of both the RSC and the Network Side Converter (NSC) are modified to boost the supply voltage at the PCC. A comparative study is also performed between the IPS without and with modification of the reactive power control loops. The simulation results mean that with the modified controllers during the fault, the amount of reactive power sustainment with ABIAC at the PCC is optimized to 17.5 MVAr instead of 15 MVAr with proportional-integral control (PIC). Therefore, the voltage at the PCC is fort increased in order to comply with the voltage requirements of the farm and absolutely to maintain the connection to the network in case of voltage dip.
OCI-OLSR: An Optimized Control Interval-Optimized Link State Routing-Based Efficient Routing Mechanism for Ad-Hoc Networks
Authors: Singh Jaspreet , Singh Gurpreet , Gupta Deepali , Muhammad Ghulam , Nauman Ali
Published: May 2023

MANET (Mobile Ad hoc Networks) functionality is determined by routing protocols’ ability to adjust to atypical changes in information and communication technologies, topological systems, and connection status. Due to interference, node migration, the growth of several pathways, security, and propagation loss, MANET network configurations are dynamic. The proactive routing protocol enhances the message flow utilized in the neighborhood discovery process by using the multipoint relays (MPR) approach. In order to increase the protocol’s effectiveness and efficiency while maintaining the OLSR protocol’s reliability, the research presented in this paper proposed an improved OCI-OLSR (Optimized Control Interval-Optimized Link State Routing) that focuses on better control interval management, an advanced MPR selection process, reducing neighbor hold time as well as decreasing flooding. The suggested proposed protocol was examined using the NS3 simulator, and it was compared to the standard OLSR version and AODV(Ad-hoc On-Demand Routing) routing protocol. According to the analysis’s findings, the suggested system has a lot of promise in terms of a variety of performance metrics under diverse conditions. Overall, the article makes the case that the OCI-OLSR protocol may enhance the performance of the regular OLSR protocol in wireless ad hoc networks by addressing a number of the protocol’s flaws.
Activation Energy of Ion Diffusion in an Electrode Material: Theoretical Calculation and Experimental Estimation with LiCoVO4 as an Example
Authors: Rybakov Kirill S. , Ushakov Arseni V. , Kabanov Artem A.
Published: May 2023

The development of electrode materials for metal-ion batteries is a complex and resource-demanding process. The optimization of this development process requires a combination of theoretical and experimental methods. The former is used to predict the properties of materials and the latter to confirm them. Thus, it is very important to understand how the results of the modeling and experiment are related. In this study, we compare the results of determining the activation energies of lithium ion diffusion in cobalt(II)-lithium vanadate(V), which we obtained by calculations from first principles within the framework of density functional theory (DFT), with the experimental results, which we achieved by applying electrochemical methods such as cyclic voltammetry and galvanostatic and potentiostatic pulses. Based on the experimental and theoretical data obtained for LiCoVO4, we hypothesize that the limitation of the practically realizable capacity of the material at about 1/3 of the theoretical one is due to its structural limitations that lead to the impossibility of involving all lithium ions in the current-forming process. This reason is fixed by the simulation results, but is not detected by the experimental results.
Artificial Intelligent Power Forecasting for Wind Farm Based on Multi-Source Data Fusion
Authors: Wang Qingtian , Wang Yunjing , Zhang Kegong , Liu Yaxin , Qiang Weiwei , Han Wen Qiuzi
Published: May 2023

Wind power forecasting is a typical high-dimensional and multi-step time series prediction problem. Data-driven prediction methods using machine learning show advantages over traditional physical or statistical methods, especially for wind farms with complex meteorological conditions. Thus, effective use of different data sources and data types will help improve power forecasting accuracy. In this paper, a multi-source data fusion method is proposed, which integrates the static information of the wind turbine with observational and forecasting meteorological information together to further improve the power forecasting accuracy. Firstly, the characteristics of each time step are re-characterized by using the self-attention mechanism to integrate the global information of multi-source data, and the Res-CNN network is used to fuse multi-source data to improve the prediction ability of input variables. Secondly, static variable encoding and feature selection are carried out, and the time-varying variables are combined with static variables for collaborative feature selection, so as to effectively eliminate redundant information. A forecasting model based on the Encoder–Decoder framework is constructed with LSTM as the basic unit, and the Add&Norm mechanism is introduced to further enhance the input variable information. In addition, the self-attention mechanism is used to integrate the global time information of the decoded results, and the Time Distributed mechanism is used to carry out multi-step prediction. Our training and testing data are obtained from an operating wind farm in northwestern China. Results show that the proposed method outperforms a classic AI forecasting method such as that using the Seq2Seq+attention model in terms of prediction accuracy, thus providing an effective solution for multi-step forecasting of wind power in wind farms.
Progress of the Analytical Methods and Application of Plutonium Isotopes in the Environment
Authors: Liu Xidong , Shao Yang , Luo Min , Ma Lingling , Xu Gang , Wu Minghong
Published: May 2023

Since the beginning of the use of nuclear energy in the twentieth century, atmospheric nuclear weapons testing, nuclear accidents, and spent fuel reprocessing have released large amounts of radioisotopes into the environment, especially plutonium isotopes. As an important anthropogenic radionuclide, plutonium is mainly produced by neutron irradiation of uranium. Plutonium isotopes and their ratios from different sources have a specific ‘fingerprint’, which is determined by irradiation time and intensity. Accordingly, several methods have been developed for the analysis of plutonium isotopes. As a popular new tracer in recent years, plutonium isotopes could be used for environmental tracer applications and source identification of regional environmental contamination sources. This paper summarizes and compares the pretreatment of plutonium isotopes in various samples and the detection and analysis methods in recent years. Plutonium isotopes in various environmental samples were enriched by chemical treatments, such as ashing, acid digestion, and alkali fusion. Then it was purified and separated by extraction resins to remove interfering nuclides for the subsequent mass spectrometry. The practical applications of plutonium isotopes and their related ratios in the environment are summarized, such as the determination of plutonium isotopes and their related ratios in the environment near two representative nuclear power plant accidents and the monitoring of the safe operation of nuclear power plants; the establishment of a plutonium isotope database in the vicinity of Chinese waters; and the traceability of plutonium isotopes in environmental regions through the global atmosphere and sand and dust. Finally, the outlook for subsequent research in plutonium isotope detection and applications is presented.
Adsorption Behavior and Adsorption Dynamics of Micrometer-Sized Polymer Microspheres on the Surface of Quartz Sand
Authors: Li Jun , Luo Taotao , Yan Wende , Cheng Tingting , Cheng Keyang , Yu Lu , Cao Jiannan , Yang Zhongquan
Published: May 2023

The adsorption of polymer microspheres in a stratum can directly affect its action mode and performance in the actual application process. Understanding the adsorption pattern of polymer microspheres and their adsorption mechanism can facilitate optimization of the application mode and enhance the use efficiency. Ultraviolet spectrophotometry was employed to measure the static adsorption characteristics of polymer microspheres (PMS) on the surface of quartz sand. The PMS adsorption capacity on the surface of quartz sand increased with increasing concentration. When the concentration was 1000 mg/L, the static equilibrium adsorption capacity was 402 μg/g, and monolayer adsorption was dominant. The effect of the contact time on the adsorption was investigated, and the fitting was performed using the isothermal adsorption thermodynamic equilibrium model and the adsorption kinetic model. The adsorption of 800 mg/L PMS tended to equilibrate after 0.8 h of adsorption on the surface of quartz sand, and the adsorption of 1400 mg/L PMS tended to equilibrate after 1 h of adsorption on the surface of quartz sand. Good fitting results of the kinetic adsorption process were obtained using the pseudo-first-order (PFO) model, pseudo-second-order (PSO) model, Elovich model, and mixed-order (MO) model. The effects of the temperature, particle size of the quartz sand, solid–liquid ratio, and salinity on the adsorption of PMS on the surface of quartz sand were examined. The PMS adsorption capacity on the surface of quartz sand decreased with increasing environmental temperature. The adsorption of PMS at the solid–liquid interface was an exothermic process, and the enthalpy of adsorption was negative. As the mass of the quartz sand in the solid–liquid ratio increased, the adsorption capacity decreased; a low salinity and neutral pH were conducive to the adsorption of PMS on the surface of quartz sand.
Multi-Temporal SamplePair Generation for Building Change Detection Promotion in Optical Remote Sensing Domain Based on Generative Adversarial Network
Authors: Li Yute , Chen He , Dong Shan , Zhuang Yin , Li Lianlin
Published: May 2023

Change detection is a critical task in remote sensing Earth observation for identifying changes in the Earth’s surface in multi-temporal image pairs. However, due to the time-consuming nature of image collection, labor-intensive pixel-level labeling with the rare occurrence of building changes, and the limitation of the observation location, it is difficult to build a large, class-balanced, and diverse building change detection dataset, which can result in insufficient changed sample pairs for training change detection models, thus degrading their performance. Thus, in this article, given that data scarcity and the class-imbalance issue lead to the insufficient training of building change detection models, a novel multi-temporal sample pair generation method, namely, Image-level Sample Pair Generation (ISPG), is proposed to improve the change detection performance through dataset expansion, which can generate more valid multi-temporal sample pairs to overcome the limitation of the small amount of change information and class-imbalance issue in existing datasets. To achieve this, a Label Translation GAN (LT-GAN) was designed to generate complete remote sensing images with diverse building changes and background pseudo-changes without any of the complex blending steps used in previous works. To obtain more detailed features in image pair generation for building change detection, especially the surrounding context of the buildings, we designed multi-scale adversarial loss (MAL) and feature matching loss (FML) to supervise and improve the quality of the generated bitemporal remote sensing image pairs. On the other hand, we also consider that the distribution of generated buildings should follow the pattern of human-built structures. The proposed approach was evaluated on two building change detection datasets (LEVIR-CD and WHU-CD), and the results proved that the proposed method can achieve state-of-the-art (SOTA) performance, even if using plain models for change detection. In addition, the proposed approach to change detection image pair generation is a plug-and-play solution that can be used to improve the performance of any change detection model.
Annual and Seasonal Trends of Vegetation Responses and Feedback to Temperature on the Tibetan Plateau since the 1980s
Authors: Wang Fangfang , Ma Yaoming , Darvishzadeh Roshanak , Han Cunbo
Published: May 2023

The vegetation–temperature relationship is crucial in understanding land–atmosphere interactions on the Tibetan Plateau. Although many studies have investigated the connections between vegetation and climate variables in this region using remote sensing technology, there remain notable gaps in our understanding of vegetation–temperature interactions over different timescales. Here, we combined site-level air temperature observations, information from the global inventory modeling and mapping studies (GIMMS) dataset, and moderate-resolution imaging spectroradiometer (MODIS) products to analyze the spatial and temporal patterns of air temperature, vegetation, and land surface temperature (LST) on the Tibetan Plateau at annual and seasonal scales. We achieved these spatiotemporal patterns by using Sen’s slope, sequential Mann–Kendall tests, and partial correlation analysis. The timescale differences of vegetation-induced LST were subsequently discussed. Our results demonstrate that a breakpoint of air temperature change occurred on the Tibetan Plateau during 1994–1998, dividing the study period (1982–2013) into two phases. A more significant greening response of NDVI occurred in the spring and autumn with earlier breakpoints and a more sensitive NDVI response occurred in recent warming phase. Both MODIS and GIMMS data showed a common increase in the normalized difference vegetation index (NDVI) on the Tibetan Plateau for all timescales, while the former had a larger greening area since 2000. The most prominent trends in NDVI and LST were identified in spring and autumn, respectively, and the largest areas of significant variation in NDVI and LST mostly occurred in winter and autumn, respectively. The partial correlation analysis revealed a significant negative impact of NDVI on LST during the annual scale and autumn, and it had a significant positive impact during spring. Our findings improve the general understanding of vegetation–climate relationships at annual and seasonal scales.
Feature Selection for Edge Detection in PolSAR Images
Authors: De Borba Anderson A. , Muhuri Arnab , Marengoni Mauricio , Frery Alejandro C.
Published: May 2023

Edge detection is one of the most critical operations for moving from data to information. Finding edges between objects is relevant for image understanding, classification, segmentation, and change detection, among other applications. The Gambini Algorithm is a good choice for finding evidence of edges. It finds the point at which a function of the difference of properties is maximized. This algorithm is very general and accepts many types of objective functions. We use an objective function built with likelihoods. Imaging with active microwave sensors has a revolutionary role in remote sensing. This technology has the potential to provide high-resolution images regardless of the Sun’s illumination and almost independently of the atmospheric conditions. Images from PolSAR sensors are sensitive to the target’s dielectric properties and structures in several polarization states of the electromagnetic waves. Edge detection in polarimetric synthetic-aperture radar (PolSAR) imagery is challenging because of the low signal-to-noise ratio and the data format (complex matrices). There are several known marginal models stemming from the complex Wishart model for the full complex format. Each of these models renders a different likelihood. This work generalizes previous studies by incorporating the ratio of intensities as evidence for edge detection. We discuss solutions for the often challenging problem of parameter estimation. We propose a technique which rejects edge estimates built with thin evidence. Using this idea of discarding potentially irrelevant evidence, we propose a technique for fusing edge pieces of evidence from different channels that only incorporate those likely to contribute positively. We use this approach for both edge and change detection in single- and multilook images from three different sensors.
A Novel Wide-Band Directional MUSIC Algorithm Using the Strength Proportion
Authors: Xu Wencong , Chen Bingshu , Hu Yue , Li Jianxun
Published: May 2023

The directional multiple signal classification (Dir-MUSIC) algorithm based on the antenna gain array manifold has been proposed to find the direction of the partial discharge (PD) source in substations. However, PD signals are wideband signals and the antenna gain pattern functions are always different at different frequencies; therefore, the accuracy can be improved using a wideband Dir-MUSIC algorithm. In this paper, wideband Dir-MUSIC algorithms are discussed and a novel wideband Dir-MUSIC algorithm using the strength proportion (DirSP) is proposed. This algorithm estimates a focusing PD signal at a certain frequency using the strength proportion among different directions, and then the Dir-MUSIC algorithm can process the focusing PD signal at this frequency. In simulations, when the antenna gain functions among different frequency bins are quite different, the Dir-MUSIC algorithm loses accuracy; meanwhile, DirDP performs very well. In the experiments, we deal with six sets of samples, and the mean error and standard deviation are both smaller than 4° better than other methods.
Margined Horn-Shaped Air Chamber for Body-Conduction Microphone
Authors: Muramatsu Shun , Kohata Yuki , Hira Emi , Momoi Yasuyuki , Yamamoto Michitaka , Takamatsu Seiichi , Itoh Toshihiro
Published: May 2023

The sound amplification ratios of sealed air chambers with different shapes were quantitatively compared to design a body-conduction microphone to measure animal scratching sounds. Recently, quantitative monitoring of scratching intensity in dogs has been required. We have already developed a collar with a body-conduction microphone to measure body-conducted scratching sounds. However, the air chamber, one of the components of the body-conduction microphone, has not been appropriately designed. This study compared the amplification ratios of air chambers with different shapes through numerical analysis and experiments. According to the results, the horn-shaped air chamber achieved the highest amplification performance, at least for sound frequencies below 3 kHz. The simulated amplification ratio of the horn-shaped air chamber with a 1 mm height and a 15 mm diameter was 52.5 dB. The deformation of the bottom of the air chamber affected the amplification ratio. Adjusting the margin of the margined horn shape could maintain its amplification ratio at any pressing force. The simulated and experimental amplification ratios of the margined horn-shaped air chamber were 53.4 dB and 19.4 dB, respectively.
Scenario Generation for Autonomous Vehicles with Deep-Learning-Based Heterogeneous Driver Models: Implementation and Verification
Authors: Gao  Li , Zhou Rui , Zhang Kai
Published: May 2023

Virtual testing requires hazardous scenarios to effectively test autonomous vehicles (AVs). Existing studies have obtained rarer events by sampling methods in a fixed scenario space. In reality, heterogeneous drivers behave differently when facing the same situation. To generate more realistic and efficient scenarios, we propose a two-stage heterogeneous driver model to change the number of dangerous scenarios in the scenario space. We trained the driver model using the HighD dataset, and generated scenarios through simulation. Simulations were conducted in 20 experimental groups with heterogeneous driver models and 5 control groups with the original driver model. The results show that, by adjusting the number and position of aggressive drivers, the percentage of dangerous scenarios was significantly higher compared to that of models not accounting for driver heterogeneity. To further verify the effectiveness of our method, we evaluated two driving strategies: car-following and cut-in scenarios. The results verify the effectiveness of our approach. Cumulatively, the results indicate that our approach could accelerate the testing of AVs.
Automatic Branch–Leaf Segmentation and Leaf Phenotypic Parameter Estimation of Pear Trees Based on Three-Dimensional Point Clouds
Authors: Li Haitao , Wu Gengchen , Tao Shutian , Yin Hao , Qi Kaijie , Zhang Shaoling , Guo Wei , Ninomiya Seishi , Mu Yue
Published: May 2023

The leaf phenotypic traits of plants have a significant impact on the efficiency of canopy photosynthesis. However, traditional methods such as destructive sampling will hinder the continuous monitoring of plant growth, while manual measurements in the field are both time-consuming and laborious. Nondestructive and accurate measurements of leaf phenotypic parameters can be achieved through the use of 3D canopy models and object segmentation techniques. This paper proposed an automatic branch–leaf segmentation pipeline based on lidar point cloud and conducted the automatic measurement of leaf inclination angle, length, width, and area, using pear canopy as an example. Firstly, a three-dimensional model using a lidar point cloud was established using SCENE software. Next, 305 pear tree branches were manually divided into branch points and leaf points, and 45 branch samples were selected as test data. Leaf points were further marked as 572 leaf instances on these test data. The PointNet++ model was used, with 260 point clouds as training input to carry out semantic segmentation of branches and leaves. Using the leaf point clouds in the test dataset as input, a single leaf instance was extracted by means of a mean shift clustering algorithm. Finally, based on the single leaf point cloud, the leaf inclination angle was calculated by plane fitting, while the leaf length, width, and area were calculated by midrib fitting and triangulation. The semantic segmentation model was tested on 45 branches, with a mean Precisionsem, mean Recallsem, mean F1-score, and mean Intersection over Union (IoU) of branches and leaves of 0.93, 0.94, 0.93, and 0.88, respectively. For single leaf extraction, the Precisionins, Recallins, and mean coverage (mCoV) were 0.89, 0.92, and 0.87, respectively. Using the proposed method, the estimated leaf inclination, length, width, and area of pear leaves showed a high correlation with manual measurements, with correlation coefficients of 0.94 (root mean squared error: 4.44°), 0.94 (root mean squared error: 0.43 cm), 0.91 (root mean squared error: 0.39 cm), and 0.93 (root mean squared error: 5.21 cm2), respectively. These results demonstrate that the method can automatically and accurately measure the phenotypic parameters of pear leaves. This has great significance for monitoring pear tree growth, simulating canopy photosynthesis, and optimizing orchard management.
A Machine Learning Specklegram Wavemeter (MaSWave) Based on a Short Section of Multimode Fiber as the Dispersive Element
Authors: Inalegwu Ogbole C. , II Rex E. Gerald , Huang Jie
Published: May 2023

Wavemeters are very important for precise and accurate measurements of both pulses and continuous-wave optical sources. Conventional wavemeters employ gratings, prisms, and other wavelength-sensitive devices in their design. Here, we report a simple and low-cost wavemeter based on a section of multimode fiber (MMF). The concept is to correlate the multimodal interference pattern (i.e., speckle patterns or specklegrams) at the end face of an MMF with the wavelength of the input light source. Through a series of experiments, specklegrams from the end face of an MMF as captured by a CCD camera (acting as a low-cost interrogation unit) were analyzed using a convolutional neural network (CNN) model. The developed machine learning specklegram wavemeter (MaSWave) can accurately map specklegrams of wavelengths up to 1 pm resolution when employing a 0.1 m long MMF. Moreover, the CNN was trained with several categories of image datasets (from 10 nm to 1 pm wavelength shifts). In addition, analysis for different step-index and graded-index MMF types was carried out. The work shows how further robustness to the effects of environmental changes (mainly vibrations and temperature changes) can be achieved at the expense of decreased wavelength shift resolution, by employing a shorter length MMF section (e.g., 0.02 m long MMF). In summary, this work demonstrates how a machine learning model can be used for the analysis of specklegrams in the design of a wavemeter.
Determining the Factors Affecting Filipinos’ Acceptance of the Use of Renewable Energies: A Pro-Environmental Planned Behavior Model
Authors: Gumasing Ma. Janice J. , Bayola Alyssa , Bugayong Sebastian Luis , Cantona Keithzi Rhaz
Published: May 2023

Renewable energies (RE) are naturally replenishable and sustainable energy sources. Solar, wind, hydro, geothermal, biomass, and ocean energy are among these sources. This study sought to determine the factors influencing the acceptance of Filipinos’ renewable energy utilization using the Pro-Environmental Planned Behavior (PEPB) model. A questionnaire survey was disseminated to obtain the required information and ascertain the variables affecting the behavioral intention of Filipinos in accepting RE. In examining the results, Structural Equation Modeling (SEM) was utilized with Partial Least Squares SEM (PLS-SEM) to identify other existing relationships. Findings revealed that Perceived Authority Support (PAS) is the most significant variable affecting Perceived Environmental Concern (PEC), inducing an indirect effect on the Behavioral Intention (BI) of Filipinos. The factor with the highest significance affecting BI is the Subjective Norm (SN). Accordingly, such results suggest that the government should implement incentive-based strategies, while considering the impact of SN, by gaining the public’s favor on the transition from traditional energy sources to green alternatives. In addition, educational programs and campaigns may be administered to spread awareness and fill in information gaps among Filipino citizens.
Digital Transformation and Green Innovation of Energy Enterprises
Authors: Liu Yutong , Song Peiyi
Published: May 2023

The era of the digital economy has ushered in a new development opportunity for the energy industry, and the role of digitalization in the green and low-carbon transformation process of the energy industry has received increasing attention. Based on the panel data of 55 energy enterprises in China, this study explores the mechanism by which energy enterprises’ digital transformation impacts enterprise green innovation from the perspective of dynamic capability and adopts the double-fixed-effects regression model to empirically analyze the impact of energy enterprises’ digital transformation on enterprise green innovation. The study explores the mediating role of dynamic capability between energy enterprise digital transformation and enterprise green innovation and conducts heterogeneity analysis. The empirical results show that there is a significant positive correlation between the digital transformation level and the green innovation level of energy enterprises. The mechanism test shows that the digital transformation of energy enterprises can promote their green innovation ability by improving their dynamic capability. Heterogeneity analysis shows that the digital transformation of energy enterprises has a significant promotional effect on the green innovation of state-owned enterprises but has no significant effect on non-state-owned enterprises. The results of this study provide a reference for promoting the green development of enterprises, enhancing the green and low-carbon transformation of the energy industry and realizing the sustainable development of enterprises.
Microbial Preparations Combined with Humic Substances Improve the Quality of Tree Planting Material Needed for Reforestation to Increase Carbon Sequestration
Authors: Nazarov Aleksey , Chetverikov Sergey , Chetverikova Darya , Tuktarova Iren , Ivanov Ruslan , Urazgildin Ruslan , Garankov Ivan , Kudoyarova Guzel
Published: May 2023

Restoring forests in areas where they once stood is an important step towards increasing carbon sequestration. However, reforestation requires an increase in current levels of seedling production in the tree nurseries. The purpose of this work was to study the effectiveness of preparations based on bacteria and humic substances (HSs) to stimulate the growth of tree seedlings in a nursery. Two selected strains of Pseudomonas and humic substances were used to treat pine and poplar plants. The treatment of seedlings was carried out during their transplantation and after it, and the effects of treatment on shoot elongation, shoot and root mass were evaluated. Treatments with both bacterial strains enhanced the growth of poplar and pine shoots and roots, which was explained by their ability to synthesize auxins. P. protegens DA1.2 proved to be more effective than P. sp. 4CH. The treatment of plants with humic substances increased the nitrogen balance index and the content of chlorophyll in the leaves of poplar seedlings, which can elevate carbon storage due to the higher rate of photosynthesis. In addition, the combination of humic substances with P. protegens DA1.2 increased shoot biomass accumulation in newly transplanted pine plants, which indicates the possibility of using this combination in plant transplantation. The increase in length and weight of shoots and roots serves as an indicator of the improvement in the quality of planting material, which is necessary for successful reforestation to increase capture of carbon dioxide.
Competition between Green and Non-Green Travel Companies: The Role of Governmental Subsidies in Green Travel
Authors: Tu Jun , Du Juan , Huang Min
Published: May 2023

The problem of carbon emissions in transportation is an increasing concern, and consumers need to be encouraged towards green modes of travel to achieve low-carbon travel. To compete with non-green travel companies, green travel companies have considered implementing expensive green efforts to attract consumers. Decisions on travel prices, the green efforts of green travel companies to maintain their competitiveness, and the role of governmental subsidies in promoting green travel must be thoroughly investigated. To consider travel competitiveness and the role of governmental subsidies that support the increased expenses of green travel, this study defined four different decision-making scenarios. The Nash game model without governmental subsidies and the Stackelberg–Nash game model with governmental subsidies were built and solved to understand the effects on the pricing and green efforts of travel companies. The equilibrium results and the role of governmental subsidies were analyzed theoretically and numerically. The results showed that governmental subsidies could boost green efforts while increasing green and non-green travel prices. The competition between green and non-green travel companies both undermined the role of the governmental subsidies and reduced the green and non-green travel prices. A sufficiently large cost-sharing coefficient from the government caused the green travel demand to be higher than the non-green travel demand.
Research on Beijing Manufacturing Green-Oriented Transition Path under “Double Carbon” Goal-Based on the GML-SD Model
Authors: Chi Yuanying , Xu Situo , Yang Xiaolei , Li Jialin , Zhang Xufeng , Chen Yahui
Published: May 2023

Accelerating the “double carbon” transformation of the manufacturing industry is the key to achieving the strategic goal of “double carbon” in China, among which the low-carbon development of the Beijing manufacturing industry is the top priority. To achieve high-quality development of the manufacturing industry in Beijing, the main task is to reduce carbon emissions and improve efficiency. Therefore, on the basis of the Global Malmquist–Luenberger (GML) index and the system dynamics (SD) method, this study analyzes the green total-factor energy efficiency trends of 25 manufacturing sub-sectors in Beijing from 2006 to 2020 and incorporates the GML index as a key variable into the construction of the SD model. It then explores the path optimization of Beijing’s manufacturing low-carbon development in the 14th Five-Year Plan period via scenario simulation and offers policy recommendations for the green-oriented transition of Beijing’s manufacturing industry. The study finds that Beijing’s manufacturing industry needs to prioritize energy structure optimization and efficient energy utilization and give full play to the city’s advantages in technological innovation and investment while supporting high-end scientific research and innovation projects to confirm the capital city’s strategic position.
Factors Affecting the Purchase Intention of Products with Environmentally Friendly Packaging of Urban Residents in Ho Chi Minh City, Vietnam
Authors: Lan Bui Thi Hoang , Phuong Tran Thi Lan , Dat Tran Tho , Truong Dinh Duc
Published: May 2023

The study’s objective is to determine the factors affecting the intention to buy products with environmentally friendly packaging in the urban area of Vietnam with a specific case study in Ho Chi Minh City. The study uses the theory of planned behavior (TPB) to build an empirical model to evaluate the factors affecting consumer behavior. Primary data were collected through a direct survey of 485 customers in the city using a convenience sampling method. We built and tested the scale of variables using Cronbach Alpha analysis and used exploratory factor analysis (EFA) to select the main factors to be included in the impact regression model. The research results show the impact of five factors: (1) the price of products with environmentally friendly packaging on the customers’ sense of community, (2) the consumer’s attitude toward products with eco-friendly packaging with customers’ conception of effectiveness, (3) social influence, (4) personal image concerns, and (5) quality of environmentally friendly packaging to intention to buy products with environmentally friendly packaging of urban residents in Ho Chi Minh City. The factor related to the attitude and perception of the effectiveness for the environment has the most substantial impact, followed by the quality of environmentally friendly packaging, the price factor, and the sense of community.