bluuebunny/crossref_metadata_2025_split huggingface dataset:
Anethum graveolens L. (dill) seed polyphenolic fractions: Assessment of high‐voltage electrical discharges, subcritical water, and microwave‐assisted extraction systems
Authors: Nastić Nataša , Lončarić Ante , Simić Siniša , Pastor Kristian , Banožic Marija , Jokić Stela , Aladić Krunoslav , Vladić Jelena 
Published: February 2025

AbstractContinuous exploration of innovative and sustainable solutions within green chemistry is imperative to tackle challenges inherent in traditional production processes. This study examined three novel methods for obtaining polyphenolic extracts from dill seeds: nonthermal high voltage electric discharge (HVED), subcritical water extraction (SWE), and microwave‐assisted extraction (MAE). SWE was conducted at temperatures ranging from 100 to 200°C under 30 bar pressure, while MAE utilized a hydroethanolic solvent at temperatures from 40 to 120°C. HVED extraction was performed at varying frequencies (40–100 Hz) and durations (5–15 min) in water. The total phenolic and flavonoid content of the extracts was quantified, and antioxidant activity was evaluated via 2,2‐diphenyl‐1‐picrylhydrazyl (DPPH) assay. Polyphenol content and DPPH radical scavenging capacity varied across techniques, with MAE at 40°C yielding the highest values. Increasing MAE temperature caused a steep decline in total phenol and flavonoid contents and a rise in DPPH IC50 values. Conversely, SWE significantly increased phenolic recovery at temperatures between 150–200°C. HVED extraction revealed frequency as the most critical parameter for phenolic recovery. Catechin (224.88 µg/mL), epicatechin (120.62 µg/mL), epigallocatechin (107.56 µg/mL), and procyanidin B1 (116.36 µg/mL) emerged as the primary phenolics. SWE demonstrated superior suitability for individual phenolic recovery compared with the other two techniques. Multivariate data analysis reveals relationships between extraction parameters and polyphenol recovery, underscoring the potential for eco‐friendly and efficient extraction processes. This study highlights the transition toward sustainable extraction methods in modern industrial processing.Practical ApplicationThis study provides insights into innovative extraction techniques for obtaining polyphenols from dill seeds, which could be applied in the food, cosmetic, and pharmaceutical industries. The findings suggest that these eco‐friendly methods can improve the efficiency of extracting antioxidants, offering manufacturers a greener and more effective approach to producing health‐promoting ingredients.
Detection methods and control measures of Burkholderia gladioli and its toxins: A review
Authors: Gao Bin , Deng Haotian , Wang Yuehua , Zhang Chunhong , Zhu Jinyan 
Published: February 2025

AbstractBurkholderia gladioli is a widely distributed Gram‐negative bacterium. Under suitable environmental conditions, it can produce harmful toxins bongkrekic acid (BKA) and toxoflavin (TF) in food carriers (such as fermented cereal products, spoiled fresh Tremella and Auricularia auricula, and fermented potatoes), posing a serious threat to the safety of food producers and consumers. Food poisoning caused by B. gladioli can manifest as comprehensive symptoms such as diarrhea, and in severe cases, symptoms such as convulsions and shock may occur. Therefore, it is necessary to conduct a comprehensive and in‐depth exploration of the food safety issues it causes. First, this article summarizes the clinical cases and prevalence caused by B. gladioli. Second, the detection methods for BKA and the methods for simultaneous detection of BKA and TF were reviewed. Finally, the methods that can inhibit the proliferation of B. gladioli and effective measures to control its production of BKA in different food carriers were reviewed. This review will help to comprehensively understand the spread of B. gladioli and its toxins and preventive measures, aiming to reduce their harm to human health.
A novel real‐time crayfish weight grading method based on improved Swin Transformer
Authors: Wen Ke , Chen Yan , Zhu Zhengwei , Yang Jinzhou , Bao Jinjin , Fu Dandan , Hu Zhigang , Peng Xianhui , Jiao Ming 
Published: February 2025

AbstractThis study proposed a novel detection method for crayfish weight classification based on an improved Swin‐Transformer model. The model demonstrated a Mean Intersection over Union (MIOU) of 90.36% on the crayfish dataset, outperforming the IC‐Net, DeepLabV3, and U‐Net models by 17.44%, 5.55%, and 1.01%, respectively. Furthermore, the segmentation accuracy of the Swin‐Transformer model reached 99.0%, surpassing the aforementioned models by 1.25%, 1.73%, and 0.46%, respectively. To facilitate weight prediction of crayfish from segmented images, this study also investigated the correlation between the projected area and the weight of each crayfish part, and developed a multiple regression model with a correlation coefficient of 0.983 by comparing the total projected area and the relationship between the projected area and the actual weight of each crayfish part. To validate this model, a test set of 40 samples was employed, with the average prediction accuracy reaching 98.34% based on 10 representative data points. Finally, grading experiments were carried out on the crayfish weight grading system, and the experimental results showed that the grading accuracy could reach more than 86.5%, confirming the system's feasibility. The detection method not only predicts the weight based on the area but also incorporates the proportional relationship of the area of each part to improve the accuracy of the prediction further. This innovation makes up for the limitations of traditional inspection methods and shows higher potential for application. This study has important applications in industrial automation, especially for real‐time high‐precision weight grading in the aquatic processing industry, which can improve production efficiency and optimize quality control.
Effect of Eurotium cristatum fermentation on chemical composition and hypoglycemic and sedative activities of Anji Baicha (Camellia sinensis)
Authors: Qiu Yue , Liu Xiaolin , Huang Zhiye , Lyu Fei , Hu Xinyu , Han Shenghua , Ren Hao , Zhang Anqiang 
Published: February 2025

AbstractAnji Baicha (Camellia sinensis), one of the top 10 teas in China, possesses old leaves rich in bioactive ingredients yet is frequently discarded due to inferior taste. This study evaluated the effects of fermentation with Eurotium cristatum, a probiotic known to enhance bioactivity, on the primary nutrients and on the hypoglycemic and sedative properties of old leaves of Anji Baicha. Results indicated a considerable reduction in free amino acids and tea polyphenols post‐fermentation. Conversely, the concentrations of flavonoids and theabrownins increased significantly, showing a positive correlation with the in vitro hypoglycemic effect. The contents of L‐theanine and γ‐aminobutyric acid (γ‐GABA), known for their sedative effects, increased after fermentation, while caffeine and glutamate, renowned for their neural stimulation effect, decreased. Molecular docking revealed that L‐theanine and γ‐GABA may act as a sedative and sleep aid by competing for receptors with caffeine and glutamate, specifically NMDAR2A. This study not only introduces a novel approach for utilizing old leaves of Anji Baicha but also establishes a foundation for further investigating the hypoglycemic, sedative, and sleep‐aiding effects of tea fermented with Eurotium cristatum.Practical ApplicationThis research offers a sustainable solution for repurposing the underutilized old leaves of Anji Baicha, enhancing their market value and contributing to the circular economy within the tea industry. The fermented tea could be integrated into health‐conscious food and beverage products, targeting consumers seeking natural hypoglycemic and sleep‐aiding alternatives. Additionally, the findings open avenues for the development of functional teas that cater to specific health needs, such as diabetes management and sleep improvement.
Efficacy and Safety of Low‐Dose Oral Etoposide Combined With Capecitabine for Patients With Postoperative Metastatic Breast Cancer Resistant to Anthracycline/Taxanes
Authors: Chen Xue , He Yingjian , Fan Tie , Wei Yan 
Published: February 2025

ABSTRACTIntroductionThe purpose of this study is to determine the efficacy and safety of metronomic chemotherapy with all‐oral combination of low‐dose etoposide/capecitabine in patients with metastatic breast cancer (MBC) previously treated with anthracyclines and/or taxanes.MethodsMetronomic chemotherapy, giving lower, more frequent doses of chemotherapy drugs over an extended period, often without long breaks between cycles. With oral low‐dose etoposide + capecitabine was administered to patients who had postoperative MBC resistant to anthracycline/taxanes: etoposide 30 mg/m2/day, qd for 7 days + capecitabine 1400 mg/m2/day, administered in two equal dose for 14 days, with 21 days as a cycle. Patients received treatments if complete response, partial response, or stable disease was obtained until disease progressed or became intolerable. RECIST criteria were used for standard efficacy evaluation and NCI‐CTC version 3.0 was used for evaluation of side effects.ResultsFrom June 2008 to May 2020, 85 patients received the aforesaid treatment; 67 of these patients were eligible for efficacy and side effects evaluation. After treatment, 6 (8.96%) patients obtained partial response, 41 (61.19%) patients had stable disease, and 20 (29.85%) patients had disease progression. The overall response rate (complete response + partial response) was 8.96%, and disease control rate (complete response + partial response + stable of disease) was 70.15%. Clinical benefits (complete response + partial response + stable of disease ≥ 24 weeks) were obtained for 50% of the patients. The median and mean treatment to progression time was 5 months and 6.06 months (95% CI: 3.43~8.70), respectively. The most common grade I/II side effects were leukopenia and fatigue (15.8%).ConclusionsFor patients with postoperative MBC resistant to anthracycline/taxanes, oral low‐dose etoposide + capecitabine was effective with tolerable safety. The patients did not need antiemetics or leukocytic drugs, and the treatment was cost‐effective because the patients did not need to be hospitalized for intravenous infusion.
Rapid ecological data collection from 360‐degree imagery using visualisation and immersive sampling in the R pannotator package
Authors: Godfree Robert , Knerr Nunzio 
Published: February 2025

Abstract

With rapid environmental change occurring globally there is an urgent need for new field survey methods that enable fast and efficient collection of ecological information from impacted systems. Advances in 360‐degree (panospheric) camera technology now allow the collection of geospatially explicit visual records of ecological properties far more cheaply, quickly and efficiently than traditional field survey methods. However, generalisable workflows and software platforms to manage, extract, process and use ecological information from large panospheric image datasets are still lacking.

Here we develop a flexible, integrative workflow for rapid acquisition, preparation and extraction of macroscopic data from 360‐degree imagery. We introduce the open‐source R package Panospheric Image Annotator in R (pannotator), which allows the user to visualise and annotate images and extract cropped geocoded sub‐images in a repeatable, systematic way using customisable drop‐down menus and help files.

We demonstrate the workflow and pannotator package using panoramic images collected from a study area at Uluṟu‐Kata Tjuṯa National Park in central Australia, which was affected by severe drought and fire in 2018–2020. In this study, 180 images were captured using GoPro Max cameras and imported into the pannotator package for data annotation. We extracted data for three key ecological attributes (plant species distribution, understorey cover and tree health) and show how these data can be used to spatially reconstruct species richness and community structure, plant size class, mortality and burn history.

Modern 360‐degree cameras and immersive sampling using the pannotator package now offer a transformative solution for efficiently capturing and extracting macroscopic ecological and biogeographical data from field surveys. More generally, the package may be used to visualise and extract data from any georeferenced panospheric imagery and generate cropped images with embedded geolocation data for use in downstream artificial intelligence/machine learning–based applications.
Cooperative learning of Pl@ntNet's Artificial Intelligence algorithm: How does it work and how can we improve it?
Authors: Lefort Tanguy , Affouard Antoine , Charlier Benjamin , Lombardo Jean‐Christophe , Chouet Mathias , Goëau Hervé , Salmon Joseph , Bonnet Pierre , Joly Alexis 
Published: February 2025

Abstract

Deep learning models for plant species identification rely on large annotated datasets. The Pl@ntNet system enables global data collection by allowing users to upload and annotate plant observations, leading to noisy labels due to diverse user skills. Achieving consensus is crucial for training, but the vast scale of collected data (number of observations, users and species) makes traditional label aggregation strategies challenging. Existing methods either retain all observations, resulting in noisy training data or selectively keep those with sufficient votes, discarding valuable information. Additionally, as many species are rarely observed, user expertise cannot be evaluated as an inter‐user agreement: otherwise, botanical experts would have a lower weight in the AI training step than the average user.

Our proposed label aggregation strategy aims to cooperatively train plant identification AI models. This strategy estimates user expertise as a trust score per user based on their ability to identify plant species from crowdsourced data. The trust score is recursively estimated from correctly identified species given the current estimated labels. This interpretable score exploits botanical experts' knowledge and the heterogeneity of users. Subsequently, our strategy removes unreliable observations but retains those with limited trusted annotations, unlike other approaches.

We evaluate Pl@ntNet's strategy on a newly released large subset of the Pl@ntNet database focused on European flora, comprising over 6 M observations and 800 K users. This anonymized dataset of votes and observations is released openly via Lefort, Affouard, et al. (2024). We demonstrate that estimating users' skills based on the diversity of their expertise enhances labelling performance.

Our findings emphasize the synergy of human annotation and data filtering in improving AI performance for a refined training dataset. We explore incorporating AI‐based votes alongside human input in the label aggregation. This can further enhance human‐AI interactions to detect unreliable observations (even with few votes).
An integrative framework to combine migratory connectivity and demographic data
Authors: Gregory Killian A. , Francesiaz Charlotte , Jiguet Frédéric , Crochet Pierre‐André , Bocher Pierrick , Düttmann Heinz , Elts Jaanus , Fartmann Thomas , Garthe Stefan , Kämpfer Steffen , Kruckenberg Helmut , Marja Riho , Piha Markus , Schwemmer Philipp , Besnard Aurélien 
Published: February 2025

Abstract

Migratory species experience various conditions and events throughout their annual cycle that influence their spatial and demographic dynamics. To understand these dynamics, it is essential to describe the origin and destination of individuals. Migratory connectivity, which is defined as the geographic linkage between populations across the annual cycle, is increasingly incorporated in population models to relate population trends to environmental variables at different stages of the cycle. However, such information on migratory movements is obtained independently from the study of population dynamics despite the interaction between both processes. Expanding on the growing use of integrated modelling approaches, we developed an integrated framework that allows the sharing of information between migratory connectivity and population data.

We first assembled an integrated migratory connectivity model and an integrated population model to join the analysis of GPS, live‐reencounter, dead‐recovery, capture–mark–recapture, and population count data within a unified framework. Based on simulated data, we assessed the ability of the resulting integrated connectivity and population model to produce unbiased and precise connectivity and demographic estimates. We then applied the same assessment to real data using the Eurasian Curlew (Numenius arquata) as a case study.

On simulated data, the integrated connectivity and population model estimated connectivity and survival parameters with no bias and similar precision to the connectivity model alone. However, it outperformed the population model in estimating fecundity in the absence of explicit productivity data. When applied to the Eurasian Curlew, the integrated connectivity and population model produced overall similar migratory connectivity and more accurate demographic estimates than the connectivity model alone, consistent with previous studies. Additionally, the model was able to estimate fecundity, whereas the data were too sparse for the population model alone to disentangle juvenile survival and fecundity.

The sharing of information between migratory connectivity and population data improved the estimation of demographic parameters by the population model and improved connectivity parameter estimates when data were scarce. This flexible framework can be generalised to include diverse data on migration movements, population structure, individual heterogeneity or environmental variables, allowing further investigation of the interaction between migration patterns and population dynamics.
Does more uncertainty incentivize risk diversification in conservation?
Authors: Sims Charles B. , Mingie James C. , Armsworth Paul R. , Papeş Mona , Giam Xingli , Zhu Gengping , Cho Seong‐Hoon 
Published: February 2025

AbstractConservation investments must balance risk and return as the benefits and costs of conservation are becoming increasingly difficult to predict. This article investigates whether a more uncertain world will strengthen the case for conservation investments strategies that diversify risk. We consider two ways the world could be more uncertain: (1) a more uncertain future climate that increases uncertainty in conservation benefits and (2) broader market uncertainties affecting conservation costs. We use concepts from expected utility theory to highlight that, as there is more risk to diversify, the incentive and ability to diversify risk depend on relative changes in expected payoffs at each site and covariances across sites as uncertainty increases. We then illustrate our findings using an application to land protection investments in southern Appalachia. In this biodiversity hotspot, we find risk diversification is most cost‐effective when conservation agencies face multiple uncertainties, and market uncertainty creates greater incentives to diversify risk than climate uncertainty.
Effect of the COVID‐19 pandemic on diabetic retinopathy and referral levels in the English National Health Service Diabetic Eye Screening Programme
Authors: Scanlon P. H. , Norridge C. F. E. , Prentis D. , Holman N. , Rankin P. , Valabhji J. 
Published: February 2025

AbstractAimsThe aim was to determine the effect of the COVID‐19 pandemic on diabetic retinopathy and referral rates in the English National Health Service (NHS) Diabetic Eye Screening Programme (DESP).MethodsNon‐patient identifiable data are submitted centrally from the 57 regional centres in the NHS DESP on a quarterly basis and analysed using STATA, comparing 01/04/2019–31/03/2020 and 01/04/2021–31/03/2022. Patient characteristics were analysed from National Diabetes Audit (NDA) data.ResultsThere were 2,274,635 grades from the 57 centres in 2019–2020 and 2,199,623 grades in 2021–2022. The proportion of eyes with referable DR increased from 3.1% in 2019–2020 to 3.2% in the 2021–2022 NHS year (p < 0.01) with a small increase in the level of non‐referable DR from 24.6% to 24.8% (p < 0.01). The median proportion of ungradable eyes in 2019–2020 was 2.6% (IQR: 2.3% to 3.3%) increasing to 3.1% (IQR: 2.5% to 3.7%) in 2021–2022. NDA data demonstrated that the proportions with type 1 diabetes receiving eye screening were higher in the latter year (8.3% vs. 7.3%).ConclusionThe COVID‐19 pandemic was associated with small increases in referable retinopathy rates from 3.1% to 3.2%, non‐referable DR from 24·6% to 24.8% and an increase in the ungradable image rate from 2.6% to 3.1%, the latter increase possibly being caused by untreated cataract during the pandemic. Risk stratification of invitations in the recovery period was believed to have contributed to keeping the referable rates low and supports a similar approach in extension of the screening interval for low‐risk groups.
Coconut rhinoceros beetle, Oryctes rhinoceros (Coleoptera: Scarabaeidae), continues to devastate coconut palms around Port Moresby, Papua New Guinea
Authors: Jackson Trevor , Kemoi Marjorie , Asigau Bala , Oki Laurie , Tenakanai David , Sar Solomon , Paudel Sulav 
Published: February 2025

AbstractThe coconut rhinoceros beetle (Oryctes rhinoceros) is an invasive pest from South‐East Asia that poses a significant threat to coconut palms in tropical regions. First detected on the mainland of Papua New Guinea in 2009 near Jacksons International Airport, located on the southern coast of the mainland near the city of Port Moresby, coconut rhinoceros beetle spread rapidly throughout Port Moresby and along the coast. This study utilized historical records, satellite imagery, on‐site surveys and stakeholder interviews to assess the impact of coconut rhinoceros beetle in three Port Moresby locations: the Gateway Hotel gardens, the Kilakila settlement and the Pacific Adventist University plantation. Results indicated severe coconut palm losses, over 90%, 80% and 40% at the three sites, respectively, with significant economic repercussions, including a sharp rise in local coconut prices. These findings highlight the urgent need for comprehensive management and mitigation strategies to protect Papua New Guinea's coconut palm ecosystems and dependent livelihoods.
The utilization of biological control against regulated pests in the EPPO region: challenges and opportunities
Authors: Tanner R. , Bluemel S. , Kapranas A. , Kenis M. , Matosevic D. , Horn N. 
Published: February 2025

AbstractBiological control is a pest control method that can offer an environmentally safer alternative to chemical pesticides. The proven safety record of both augmentative and classical biological control technologies allows its utilization against indigenous and non‐indigenous but well‐established pests, whether under protected conditions (e.g., glasshouses) or in open field cropping systems. This manuscript has been developed by the Joint European and Mediterranean Plant Protection Organization (EPPO) and the International Organization for Biological and Integrated Control (IOBC) Panel on Biological Control Agents and presents an assessment on the current use of classical and augmentative biological control for the control of regulated plant pests. The paper discusses challenges for the uptake of biological control for regulated pests and provides recommendations to increase the safe use of biological control agents in the EPPO region.