bluuebunny/crossref_metadata_2025_split huggingface dataset:
Naturally‐occurring nematicides of plant origin: two decades of novel chemistries
Authors: Ibrahim Hashim , Nchiozem‐Ngnitedem Vaderament‐A. , Dandurand Louise‐Marie , Popova Inna 
Published: November 2024

AbstractPlant‐parasitic nematodes are among the most destructive plant pathogens, resulting in a global annual economic loss of about 358 billion dollars. Using synthetic nematicides to control plant‐parasitic nematodes has resulted in broad‐spectrum toxicity to the environment. Plant‐derived secondary metabolites have recently emerged as viable options that provide effective, greener, and renewable routes for managing plant‐parasitic nematodes in various cropping systems. However, limited comprehensive information on plant‐derived secondary metabolites sources, chemical structures, and nematicidal activities is available. This study aims to compile and analyze data on plant‐based secondary metabolites with nematicidal properties collected over the last two decades. In this review, we identified 262 plant‐based metabolites with nematicidal activities that were isolated from 35 plant families and 65 plant species. Alkaloids, terpenoids, saponins, flavonoids, coumarins, thiophenes, and annonaceous acetogenins were among the most studied compounds. In addition to the structure–activity relation for specific metabolites with nematicidal potency, various techniques for their extraction and isolation from plant material are discussed. Our findings demonstrate the potential of plants as a feedstock for sourcing nematicidal compounds and discovering new chemistries that could potentially be used for developing the next generation of nematicides. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
DMI fungicide resistance in Zymoseptoria tritici is unlinked to geographical origin and genetic background: a case study in Europe
Authors: Oreiro Eula Gems , Samils Berit , Kildea Steven , Heick Thies , Hellin Pierre , Legrève Anne , Rodemann Bernd , Berg Gunilla , Jørgensen Lise N , Friberg Hanna , Berlin Anna , Zhan Jiasui , Andersson Björn 
Published: November 2024

AbstractBACKGROUNDThe hemibiotrophic fungus Zymoseptoria tritici causing Septoria tritici blotch (STB), is a devastating foliar pathogen of wheat worldwide. A common group of fungicides used to control STB are the demethylation inhibitors (DMIs). DMI fungicides restrict fungal growth by inhibiting the sterol 14‐α‐demethylase, a protein encoded by CYP51 gene and essential for maintaining fungal cell permeability. However, the adaptation of Z. tritici populations in response to intensive and prolonged DMI usage has resulted in a gradual shift towards reduced sensitivity to this group of fungicides. In this study, 311 isolates were collected pre‐treatment from nine wheat‐growing regions in Europe in 2019. These isolates were analysed by high‐throughput amplicon‐based sequencing of nine housekeeping genes and the CYP51 gene.RESULTSAnalyses based on housekeeping genes and the CYP51 gene revealed a lack of population structure in Z. tritici samples irrespective of geographical origin. Minimum spanning network (MSN) analysis showed clustering of multilocus genotypes (MLGs) based on CYP51 haplotypes, indicating an effect of selection due to DMI fungicide use. The majority of the haplotypes identified in this study have been reported previously. The diversity and frequencies of mutations varied across regions.CONCLUSIONUsing a high‐throughput amplicon‐sequencing approach, we found several mutations in the CYP51 gene combined in different haplotypes that are likely to cause fungicide resistance. These mutations occurred irrespective of genetic background or geographical origin. Overall, these results contribute to the development of effective and sustainable risk monitoring for DMI fungicide resistance. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
High‐dose propranolol decreases aggression in young people with autism
Authors: Price Lawrence H. 
Published: November 2024

As many as two‐thirds of individuals with autism spectrum disorder (ASD) experience challenging symptoms of irritability, including aggression and self‐injury. The antipsychotics risperidone and aripiprazole are approved for the treatment of irritability associated with ASD; however, their adverse effects can compromise long‐term use in many patients. Based on longstanding case reports showing promising results for the beta‐blocker propranolol in reducing challenging symptoms in ASD, investigators conducted a randomized, double‐blind, placebo‐controlled crossover trial to evaluate the feasibility of high‐dose propranolol for treating aggression in patients with ASD. The investigators recruited youths and young adults aged 12 to 30 with ASD and a history of severe and chronic aggression, self‐injury, and disruptive behaviors that interfere with daily activities. Participants were required to have had an inadequate trial of at least two psychotropic medications, including at least one antipsychotic. Dosing of propranolol started at 10 mg three times a day and could be increased until adequate therapeutic response was achieved, to a maximum dose of 200 mg three times a day. Most study visits were conducted via telehealth in order to minimize patient schedule disruption. The primary outcomes were change in scores on the Clinical Global Impression‐Improvement (CGI‐I) and Aberrant Behavior Checklist‐Community (ABC‐C) scales from baseline to study endpoint. Six participants with a mean age of 16 years were enrolled. The investigators found that propranolol resulted in mean reductions of 50% in scores on the CGI‐I and 37% in scores on the ABC‐C. Effect sizes were large for both measures: –0.74 for the CGI‐I and –0.64 for the ABC‐C. “As this was a feasibility pilot study, we had a small sample that limits the generalization of our results to a wider population, and therefore, until a placebo‐controlled, double‐blind study with an adequate number of subjects is conducted, the clinical value of this report is limited,” the study's authors wrote. [London, E., et al. (2024). J Clin Psychopharmacol. https://doi.org/10.1097/JCP.0000000000001895]
The influence of student voice on teacher professional learning: A systematic literature review
Authors: Santos Ieda M. , Amatullah Tasneem , Agbenyega Joseph , de Souza Dayse Neri 
Published: November 2024

AbstractStudent voice has the potential to prompt changes in teaching and foster teacher development; however, it is underutilised in teacher professional learning. Research on its impact is emerging, and a systematic review is needed to identify trends and themes. This review investigates current trends and themes in the influence of student voice on teacher learning from 2012 to 2023 within K‐12 education. Analysis of 19 empirical papers revealed irregular patterns of publications, a predominant emphasis on secondary education, and qualitative methodologies. Participatory research designs emerged as practical approaches, engaging teachers in inquiry processes and collaboration. Student feedback led to a transformative process for many teachers, prompting them to reflect and change their practice. Supportive school structures and leadership are emphasised for embedding student feedback in classrooms, engaging teachers and students in collaboration, and overcoming obstacles. This review demonstrated that when student voice is valued and acted upon, it can stimulate teacher development. A proposed model for teacher development incorporating student voice consists of three interconnected levels—school leadership support, collaborative practice and learning outcomes—ultimately contributing to overall school improvement. Recommendations for future research are discussed.
Constraint‐Driven Multilane Merging Control for Underactuated Connected and Automated Vehicle System With Mismatched Uncertainty
Authors: Yang Qinwen , Li Jiawen , Xiao Gang , Li Xueyun , Ren Linjie , Huang Jin 
Published: November 2024

ABSTRACTThis article investigates the merging control for underactuated connected and automated vehicle (CAV) systems with mismatched uncertainty. The objective is to guarantee the safe and prescribed dynamic performance of the system during multilane merging. For CAV multidimensional motions, a strongly coupled vehicle dynamics with time‐varying uncertainties is constructed. For the nominal system, the control objectives are designed as system constraints, with equality constraints guaranteeing merging and time‐varying inequality constraints guaranteeing dynamic performance bounds. Based on the diffeomorphism method and bounded constraint, the system constraints are reconstructed to a unified representation. Combining system constraints and underactuated structure, the nominal controller is derived based on constraint‐following. For the uncertain system, the uncertainty is decomposed into matched and mismatched portions by orthogonal decomposition. The adaptive robust controller is designed based only on matched uncertainty. Through Lyapunov minimax analysis, the control renders the errors uniformly bounded and uniformly ultimately bounded. Simulation results show that merging and platooning are effectively achieved with the proposed control. The system has excellent transient and steady state performance even in the presence of time‐varying uncertainties.
Plant Agrobiodiversity, Agricultural and Phytosanitary Practices of Market Garden Crops in the Centre‐East Region of Burkina Faso
Authors: Zerbo Issouf , Dabiré Kounbo , Kaboré Sibiry Albert , Sawadogo Constant Martin , Thiombiano Adjima 
Published: November 2024

ABSTRACTIntroductionIn West Africa, market gardeners use various agricultural practices to increase yields. However, many of these practices do not comply with agroecological standards and cause intoxication, pollution, soil degradation and biodiversity loss. This study characterizes the plant agrobiodiversity of market garden crops grown during the rainy season and the agricultural and phytosanitary practices used for their management.Materials and MethodsThe study was carried out in Burkina Faso. Plant agrobiodiversity was assessed in 100 market gardens. Agricultural and phytosanitary practices were characterized using semi‐structured interviews. A Sankey diagram was used to highlight the relationships among market garden crops, bioaggressors and diseases. Principal component analyses were applied to highlight the agricultural and phytosanitary practices used.ResultsThe results revealed rich agrobiodiversity, including 16 market garden crops, 15 local agroforestry species, 17 planted species and 37 weed species. The main market garden crops grown in the rainy season were cabbage (20.30%), lettuce (16.62%), tomato (11.69%), and amaranth (10.15%). The most frequent agroforestry species were Azadirachta indica (18.20%) and Mangifera indica (15.03%). The most common weeds were Eleusine indica (11.02%) and Cyperus reduncus (9.70%). Eleven pests were identified, and the most frequently recorded were caterpillars (39.06%). Sixteen diseases were reported, the most common being leaf yellowing (15.67%) and leaf wilt (11.67%). Numerous market gardeners use mineral fertilizers such as Yaramila (NPK 23‐10‐5), NPK (14‐23‐14), urea (46.00% nitrogen), and liquid fertilizer as well as compost and organic manure. The most common agricultural practice was crop rotation (79.00%). To protect crops, 89.00% of producers used synthetic chemical pesticides in an uncontrolled manner, most of which are purchased on the local market. Only 11.00% of the market gardeners practiced the natural phytosanitary treatments.ConclusionThis study provides important information that can be used for the sustainable management of market gardens. Agroecological standards should be popularized to ensure food security for market garden crops.
Drug Efficacy Estimation for Follow‐on Companion Diagnostic Devices Through External Studies
Authors: Sun Jiarui , Hu Wenjie , Zhou Xiao‐Hua 
Published: November 2024

ABSTRACTA therapeutic product is usually not suitable for all patients but for only a subpopulation. The safe and effective use of such a therapeutic product requires the co‐approval of a companion diagnostic device which can be used to identify suitable patients. While the first‐of‐a‐kind companion diagnostic device is often developed in conjunction with its intended therapeutic product and simultaneously validated through a randomized clinical trial, there remains room for the innovation of new and improved follow‐on companion diagnostic devices designed for the same therapeutic product. However, conducting a new randomized trial or a bridging study for the follow on companion devices may be unethical, expensive or unpractical. Hence, there arises a need for an external study to evaluate the concordance between the FDA‐approved comparator companion diagnostic device (CCD) and the subsequent follow‐on companion diagnostic devices (FCD), indirectly validating the latter. In this article, we introduce a novel external study design, referred to as the targeted treatment design, as an extension of the existing concordance design. Additionally, we present corresponding statistical analysis methods. Our approach combines the CCD randomized trial data and the FCD external study data, enabling the estimation of drug efficacy within the FCD+ and FCD‐ subpopulations—the parameters crucial for the validation of the FCD. Theoretical results and simulation studies validate the proposed methods and we further illustrate the proposed methods through an application in a real example of non‐small‐cell lung cancer.
What Limits the Stability Performance of Polymeric Carbon Nitride Photoanode for Photoelectrochemical Water Splitting?
Authors: Jiang Lan , Zhang Jin , Chen Jinwei , Dong Changxue , Tan Han , Chen Qiuyan , Zhang Jie , Chen Xianchun , Wang Ruilin 
Published: November 2024

AbstractAlthough many researches have been reported about the high performance of polymeric carbon nitride (PCN) photoanode, but it is still limited by poor stability. In this work, PCN nanosheets photoanode is used as a platform to investigate the sources of this issue. Through a combination of photoelectrochemical, X‐ray Photoelectron Spectroscopy (XPS), and Potentiostatic Electrochemical Impedance Spectroscopy (PIES) measurements, it is shown that amounts of C═O bonds will form on the surface of PCN photoanodes, which limited the separation of the photogenerated carriers. To solve this problem, the TiO2 is deposited on PCN photoanode (named as PCN/TiO2) to improve the stability. And the PEC water splitting studies revealed that the stability of PCN/TiO2 photoanode is improved significantly as its photocurrent density can still maintain 90% after 3 h of reaction. This study provides a new way to understand the mechanism for the performance decrease of PCN photoanode and hope to inspire more powerful strategies to improve PCN photoanode stability.
Strain Effects and Crystalline‐Amorphous Interface of NiFe‐LDH@S‐NiFeOx/NF with Heterogeneous Structure for Enhancing Electrocatalytic Oxygen Evolution Reaction of Water‐Electrolysis
Authors: Xu Huan , Sun Xiao , Ding Lingtong , Liu Jingjing , Zhang Dan , Liu Minmin , Wang Xiao , Zhang Qixian , Zhang Jiujun 
Published: November 2024

AbstractElectrochemical water‐electrolysis for hydrogen generation often requires more energy due to the sluggish oxygen evolution reaction (OER). This work introduces a double‐layered nanoflower catalyst, NiFe‐LDH@S‐NiFeOx/NF, featuring a crystalline NiFe‐LDH coating on amorphous S‐NiFeOx on nickel foam. Strategically integrating a crystalline‐amorphous (c‐a) heterostructure leverages strain engineering to enhance OER activity with low overpotentials (η100 = 220 and η500 = 245 mV) and stability (135 h at η100 and 80 h at η500). Theoretical density functional theory (DFT) calculations reveal that the compressive strain can optimize the adsorption of oxygen‐containing intermediates to reduce the reaction energy barrier, thus improving the reaction kinetics and performance of OER. Moreover, its phosphated derivative, NiFeP@S‐NiFeOx/NF, exhibits high hydrogen evolution reaction (HER) performance (η10 = 64 mV, η100 = 187 mV). An alkaline water‐electrolysis cell of NiFeP@S‐NiFeOx/NF(−)||NiFe‐LDH@S‐NiFeOx/NF(+) requires only a cell voltage of 1.77 V at 100 mA cm−2, demonstrating excellent stability over 110 h (at both 10 and 100 mA cm−2). This work highlights the benefits of integrating crystal‐amorphous interfaces and strain effects, offering insights into the understanding and optimizing catalytic OER mechanism and advancing water‐electrolysis technology.
IG‐YOLOv8: Insulator Guardian Based on YOLO for Insulator Fault Detection
Authors: Li Shenwang , Wang Minjie , Zhou Yuyang , Su Qiuren , Liu Li , Wu Thomas 
Published: November 2024

AbstractInsulators have an extremely important role in transmission lines, and they are important components for ensuring the safe operation of transmission lines. In order to solve the difficult problem of insulator fault detection under complex background, IG‐YOLOv8 insulator fault detection algorithm is proposed in this paper. First, the Wise‐IoU (WIoU) loss function is introduced to mitigate the adverse impact of low‐quality images by employing a dynamic non‐monotonic focusing mechanism, thereby enhancing the detection performance of the entire model. Second, a novel C2f network is constructed by integrating the receptive field coordination attention (RFCA) convolutional module to address the parameter‐sharing issue associated with large convolutional kernels. Additionally, the data set has been reorganized using k‐fold cross‐validation to ensure that each subset undergoes training and testing, consequently reducing generalization errors. Finally, a deformable attention (DA) mechanism is employed to augment the feature extraction capability pertaining to insulator fault region information. In order to evaluate the detection performance of the improved IG‐YOLOv8 algorithm, this study constructed an insulator target detection data set containing four fault types: Normal, Defect, Dirty, and Aging. The experimental results show that the average accuracy of the improved model is increased from 89.7% to 96.9%, and the Recall value of the Aging type insulator is increased from 71.8% to 89.1%. The occurrence of missed detection is greatly reduced, and the accuracy of detection is improved. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.
One‐step synthesis of GO/AgNPs nanocomposite for diverse antimicrobial applications
Authors: Lan Nguyen Thi , Huong Chu Thi Lan , Kien Pham The , Van Nguyen Toan , Tam Le Thi 
Published: November 2024

AbstractDue to its diverse application potential, graphene oxide and silver nanoparticles (GO/AgNPs) nanocomposite material is currently under active research and scrutiny by scientists. This research synthesized the nanocomposite based on GO and AgNPs using a one‐step method with ascorbic acid's environment‐friendly reducing agent. Results indicated that the generated AgNPs, with a mean size of 20.3 nm, were deposited evenly upon the GO sheets' surface despite the absence of a stabilizer. The structural and chemical characteristics of GO/AgNP nanocomposites were studied using X‐ray diffraction, field‐emission scanning electron microscopy, atomic force microscopy, photoluminescence, and Raman analyses. The nanocomposites' antibacterial efficacy was tested with Escherichia coli (Gram‐negative) and Staphylococcus aureus (Gram‐positive). At a focus of 16 µg/L, the GO/AgNPs sample exhibited a width of inhibition zones (ZOI) of about 10 mm in diameter, larger than that of the AgNPs sample at a threefold higher concentration. These results show that the synthesized GO/AgNPs nanocomposite maintains and enhances its antimicrobial activity. Therefore, it holds promise as a safe and cost‐effective material resource for biomedicine or environmental treatment purposes.
Synthesis and characterization of Nd‐TiO2 and Nd‐ZnO nanostructures for photocatalytic degradation of textile wastewater
Authors: Lal Manmohan , Chander Subhash , Sharma Praveen , Ram Chhotu 
Published: November 2024

AbstractThis study was executed on textile wastewater degradation using laboratory‐prepared Nd‐TiO2 and Nd‐ZnO nanostructures by sol–gel and hydrothermal ultrasonication methods, respectively. The synthesized nano‐photocatalysts were fully characterized using XRD, FE‐SEM/EDX, FT‐IR, and UV‐DRS. The XRD analysis shows that TiO2 crystalline size with Nd doping is 6.14 nm with only the anatase phase, whereas ZnO is 29.59 nm. DRS spectra show that the energy band gap of the doped TiO2 nanostructure was 3.16 eV, whereas, in the case of the Nd‐ZnO nanostructure, it was 3.19 eV, which further indicates more photocatalytic activity. Photocatalytic application for textile wastewater degradation was tested regarding biological oxygen demand and chemical oxygen demand. The maximum degradation of textile wastewater at dilution 1:9 was observed to be 96% and 91% for Nd‐TiO2 and 89% and 87% for Nd‐ZnO under UV and solar irradiations, respectively, with the optimized catalyst dose of 0.2 g/L (Nd‐TiO2) and 0.3 g/L (Nd‐ZnO) at a pH of 7.52. The recyclability shows a slight decrease in efficiency throughout five cycles. The photocatalytic activity of Nd‐TiO2 was higher due to the favorable band gap and smaller crystallite size. The findings indicate that solar light may be a long‐term, cost‐effective renewable source for large‐scale wastewater treatment.
Intelligent adaptive nonlinear autoregressive eXogeneous neuro‐structure for ferromagnetic Powell‐Eyring fluidic involving cubic autocatalysis chemical reaction
Authors: Khan Maryam Pervaiz , Chang Chuan‐Yu , Raja Muhammad Asif Zahoor , Shoaib Muhammad 
Published: November 2024

AbstractThe scope of artificial intelligence in the field of fluid mechanics has been expanded with the development sophisticated technology to enhance the efficiency, reliability, solve complexities, introduced alternate transformation and enabling more dependable solutions with their analysis. The goal of this study is to investigate the ferromagnetic Powell‐Eyring fluids (FMPEFs) model with non‐Fourier heat flux by using artificial intelligence‐based scheme by exploiting the adaptive nonlinear autoregressive eXogenous (NARX) neuro‐architecture with backpropagation of Levenberg Marquart (LM), that is, NARX‐LM. The developed NARX‐LM methodology applied on synthetic datasets acquired with the help of Adams numerical method for FMPEF system by prudently changing physical quantities that is, material parameters of Eyring Powell, homogeneous reaction, heterogeneous reaction, dimensionless thermal relaxation time, Prandtl number, Schmidt number with fixed values parameter of ferrohydrodynamic interaction, rate of diffusion coefficient. Outcomes of NARX‐LM are regularly overlapping with the numerical results for the FMPEFs system having reasonable small error magnitude for each variant. The proficiency of intelligent computing anticipated on FMPEFs is depicted exhaustively with iterative mean squared error based iconvergence curves, analysis of adaptive controlling factors, error frequency distribution on the histograms, auto‐correlation, and correlation measures.