bluuebunny/crossref_metadata_2025 huggingface dataset:
“Taking Action in Community Is Much, Much Preferable to Doing It Alone”: An Examination of Multi-Level Facilitators of and Barriers to Sustained Collective Climate Change Activism Among US Residents
Authors: Dayton Lauren , Parker Kelsie , Ross Julia , Tharmarajah Saraniya , Latkin Carl
Published: December 2024

To enact climate mitigation policies, sustained collective activism is essential to create political pressure and prioritize addressing climate change. Climate change activism includes behaviors such as contacting elected officials to urge them to take action on climate change, volunteering, and signing petitions. Climate change activism is often measured as a one-time event, not sustained activism efforts, which are necessary to enact sufficiently impactful policy changes. To examine barriers to and facilitators of sustained climate change activism, 23 in-depth interviews were conducted between August and December 2023 among members of an innovative national climate change-focused organization. Eligibility included being at least 18 years of age, English-speaking, a US resident, and highly engaged in a climate change activism group. Content analysis of interview transcripts was employed, and five themes emerged as barriers, four themes as facilitators, and five themes as both facilitators of and barriers to sustained climate change activism. The study identified strategies to promote the critical behavior of sustained climate change activism, which included fostering a community of climate change activists, clear instructions on how to engage in activism behaviors for all technical abilities, supporting mental health, and creating climate change activism as a habit and identity.
Mapping Methane—The Impact of Dairy Farm Practices on Emissions Through Satellite Data and Machine Learning
Authors: Bi Hanqing , Neethirajan Suresh
Published: December 2024

Methane emissions from dairy farms are a significant driver of climate change, yet their relationship with farm-specific practices remains poorly understood. This study employs Sentinel-5P satellite-derived methane column concentrations as a proxy to examine emission dynamics across 11 dairy farms in Eastern Canada, using data collected between January 2020 and December 2022. By integrating advanced analytics, we identified key drivers of methane concentrations, including herd genetics, feeding practices, and management strategies. Statistical tools such as Variance Inflation Factor (VIF) and Principal Component Analysis (PCA) addressed multicollinearity, stabilizing predictive models. Machine learning approaches—Random Forest and Neural Networks—revealed a strong negative correlation between methane concentrations and the Estimated Breeding Value (EBV) for protein percentage, demonstrating the potential of genetic selection for emissions mitigation. Our approach refined concentration estimates by integrating satellite data with localized atmospheric modeling, enhancing accuracy and spatial resolution. These findings highlight the transformative potential of combining satellite observations, machine learning, and farm-level characteristics to advance sustainable dairy farming. This research underscores the importance of targeted breeding programs and management strategies to optimize environmental and economic outcomes. Future work should expand datasets and apply inversion modeling for finer-scale emission quantification, advancing scalable solutions that balance productivity with ecological sustainability.
Comparative Assessments of New Hair-Straightening Cosmetic Formulations on Wavy Type 2 Hair
Authors: Junior Celso Martins , Vieira Matheus Henrique , Cacoci Érica Savassa Pinto , Abelan Ursulandrea Sanches , Sarruf Fernanda Daud , Lima Cibele Castro , Chin Chung Man
Published: December 2024

Hair straighteners are among the most technically complex products to be safely and effectively developed, and this challenge has increased even more with the higher incidence of resistant hair among consumers. This underscores the importance of studying new active ingredients, combinations and carrier formulations to improve performance without compromising safety. In this research, we compared eight hair-straightening formulations with different active ingredients and/or concentrations to develop new, safer and more effective texture modifiers. Eight formulations were developed and compared with each other and to controls (virgin and bleached hair) regarding mechanical and thermal resistance, cuticle morphology, hair shine and fiber diameter. Results showed that all formulations were safe and effective at straightening hair. Specifically, 13.3% and 9.4% ammonium thioglycolate (G03 and G04) were more suitable for wavy and curly hair, 12.5% and 7.9% amino methyl propanol thioglycolate (G05 and G06) for finer or chemically processed hair, 5% and 4% sodium cysteamine (G07 and G08) for curly and tight curly hair to control volume, and 2% and 1% of a combination of ammonium thioglycolate with sodium thioglycolate (G09 and G10) for more resistant wavy and curly hair.
Genome-Scale DNA Methylome and Transcriptome Profiles of Prostate Cancer Recurrence After Prostatectomy
Authors: Smith Jim , Ajithkumar Priyadarshana , Wilkinson Emma J. , Dutta Atreyi , Vasantharajan Sai Shyam , Yee Angela , Gimenez Gregory , Subramaniam Rathan M. , Lau Michael , Zarrabi Amir D. , Rodger Euan J. , Chatterjee Aniruddha
Published: December 2024

Prostate cancer (PCa) is a major health burden worldwide, and despite early treatment, many patients present with biochemical recurrence (BCR) post-treatment, reflected by a rise in prostate-specific antigen (PSA) over a clinical threshold. Novel transcriptomic and epigenomic biomarkers can provide a powerful tools for the clinical management of PCa. Here, we provide matched RNA sequencing and array-based genome-wide DNA methylome data of PCa patients (n = 17) with or without evidence of BCR following radical prostatectomy. Formalin-fixed paraffin-embedded (FFPE) tissues were used to generate these data, which included technical replicates to provide further validity of the data. We describe the sample features, experimental design, methods and bioinformatic pipelines for processing these multi-omic data. Importantly, comprehensive clinical, histopathological, and follow-up data for each patient were provided to enable the correlation of transcriptome and methylome features with clinical features. Our data will contribute towards the efforts of developing epigenomic and transcriptomic markers for BCR and also facilitate a deeper understanding of the molecular basis of PCa recurrence.
Design and Modeling of a High-Peak-Power Distributed Electric Propulsion System for a Super-STOL UAV
Authors: Zong Jia , Zhou Zhou , Zhu Jinhong , Shao Zhuang , Sun Sanya
Published: December 2024

Electric short takeoff and landing (eSTOL) aircraft utilize the slipstream generated by distributed propellers to significantly increase the effective lift coefficient and reduce the takeoff and landing distances. By utilizing the blown lift, eSTOL UAVs can achieve similar takeoff and landing site requirements as electric vertical takeoff and landing (eVTOL) UAVs, while having lower takeoff and landing energy consumption and thrust requirements. This research proposes a high-peak-power distributed electric propulsion (DEP) system model and overload design method for eSTOL UAVs to further improve the power and thrust of the propulsion system. The model considers motor temperature factors with the throttle input, which is solved through three-round iterative calculations. The experimental and simulation results indicate that the maximum error of the high-peak-power propulsion unit model without considering temperature is 19.52%, and the maximum error when considering temperature is 1.2%. The propulsion unit ground test indicates that the main factors affecting peak power are the duration of peak power and the temperature limit of the motor. Finally, the effectiveness of the propulsion system model is verified through ground tests and UAV flight tests.
A Near-Wall Methodology for Large-Eddy Simulation Based on Dynamic Hybrid RANS-LES
Authors: Tullis Michael , Walters D. Keith
Published: December 2024

Attempts to mitigate the computational cost of fully resolved large-eddy simulation (LES) in the near-wall region include both the hybrid Reynolds-averaged Navier–Stokes/LES (HRL) and wall-modeled LES (WMLES) approaches. This paper presents an LES wall treatment method that combines key attributes of the two, in which the boundary layer mesh is sized in the streamwise and spanwise directions comparable to WMLES, and the wall-normal mesh is comparable to a RANS simulation without wall functions. A mixing length model is used to prescribe an eddy viscosity in the near-wall region, with the mixing length scale limited based on local mesh size. The RANS and LES regions are smoothly blended using the dynamic hybrid RANS-LES (DHRL) framework. The results are presented for the turbulent channel flow at two Reynolds numbers, and comparison to the DNS results shows that the mean and fluctuating quantities are reasonably well predicted with no apparent log-layer mismatch. A detailed near-wall meshing strategy for the proposed method is presented, and estimates indicate that it can be implemented with approximately twice the number of grid points as traditional WMLES, while avoiding the difficulties associated with analytical or numerical wall functions and modified wall boundary conditions.
Axiomatic Approach to Measures of Total Correlations
Authors: Moraes Gabriel L. , Angelo Renato M. , Costa Ana C. S.
Published: December 2024

Correlations play a pivotal role in various fields of science, particularly in quantum mechanics, yet their proper quantification remains a subject of debate. In this work, we aimed to discuss the challenge of defining a reliable measure of total correlations. We first outlined the essential properties that an effective correlation measure should satisfy and reviewed existing measures, including quantum mutual information, the p-norm of the correlation matrix, and the recently defined quantum Pearson correlation coefficient. Additionally, we introduced new measures based on Rényi and Tsallis relative entropies, as well as the Kullback–Leibler divergence. Our analysis revealed that while quantum mutual information, the p-norm, and the Pearson measure exhibit equivalence for two-qubit systems, they all suffer from an ordering problem. Despite criticisms regarding its reliability, we argued that QMI remains a valid measure of total correlations.
Symplectic Bregman Divergences
Authors: Nielsen Frank
Published: December 2024

We present a generalization of Bregman divergences in finite-dimensional symplectic vector spaces that we term symplectic Bregman divergences. Symplectic Bregman divergences are derived from a symplectic generalization of the Fenchel–Young inequality which relies on the notion of symplectic subdifferentials. The symplectic Fenchel–Young inequality is obtained using the symplectic Fenchel transform which is defined with respect to the symplectic form. Since symplectic forms can be built generically from pairings of dual systems, we obtain a generalization of Bregman divergences in dual systems obtained by equivalent symplectic Bregman divergences. In particular, when the symplectic form is derived from an inner product, we show that the corresponding symplectic Bregman divergences amount to ordinary Bregman divergences with respect to composite inner products. Some potential applications of symplectic divergences in geometric mechanics, information geometry, and learning dynamics in machine learning are touched upon.
Research on the Primary Frequency-Regulation Strategy of Wind-Storage Collaborative Participation Systems Considering the State of Charge of Energy Storage
Authors: Kang Heran , Sun Yonghui , Liu Jianfei , Chen Zitao , Shi Xizhi , Zhang Xiulu , Shi Yong , Yang Peihong
Published: December 2024

The system inertia insufficiency brought on by a high percentage of wind power access to a power grid can be effectively resolved by wind-storage collaborative participation in primary frequency regulation (PFR). However, the impact of energy storage participation in system-frequency regulation is significantly influenced by its state of charge (SOC). In this paper, considering the SOC of energy storage (ES) and the stochastic characteristics of wind turbine (WT) output, the control strategy of wind-storage collaborative participation in the PFR of a system is proposed. Firstly, a WT adaptive inertia control and a model of storage droop control were constructed. Additionally, to prevent the problem of secondary frequency drop brought on by a separate rotational kinetic energy control, a wind-storage collaborative frequency-regulation control scheme was constructed. Secondly, considering changes in wind speed and the SOC of ES, an improved dynamic droop-control strategy for ES is proposed. This strategy was combined with the adaptive inertia control of the WT to establish the PFR of the WT collaborative participation system. Lastly, a simulation example of a two-region, four-machine system was used to validate the efficacy of the frequency-control strategy presented in this paper. The results show that a significant percentage of WTs connected to a power grid can effectively have their frequency-response ability improved by wind-storage collaborative control.
Carbon Soil Mapping in a Sustainable-Managed Farm in Northeast Italy: Geochemical and Geophysical Applications
Authors: Salani Gian Marco , Rizzo Enzo , Brombin Valentina , Fornasari Giacomo , Sobbe Aaron , Bianchini Gianluca
Published: December 2024

Recently, there has been increasing interest in organic carbon (OC) certification of soil as an incentive for farmers to adopt sustainable agricultural practices. In this context, this pilot project combines geochemical and geophysical methods to map the distribution of OC contents in agricultural fields, allowing us to detect variations in time and space. Here we demonstrated a relationship between soil OC contents estimated in the laboratory and the apparent electrical conductivity (ECa) measured in the field. Specifically, geochemical elemental analyses were used to evaluate the OC content and relative isotopic signature in collected soil samples from a hazelnut orchard in the Emilia–Romagna region of Northeastern Italy, while the geophysical Electromagnetic Induction (EMI) method enabled the in situ mapping of the ECa distribution in the same soil field. According to the results, geochemical and geophysical data were found to be reciprocally related, as both the organic matter and soil moisture were mainly incorporated into the fine sediments (i.e., clay) of the soil. Therefore, such a relation was used to create a map of the OC content distribution in the investigated field, which could be used to monitor the soil C sequestration on small-scale farmland and eventually develop precision agricultural services. In the future, this method could be used by farmers and regional and/or national policymakers to periodically certify the farm’s soil conditions and verify the effectiveness of carbon sequestration. These measures would enable farmers to pursue Common Agricultural Policy (CAP) incentives for the reduction of CO2 emissions.
Influence of Plant Protein Fining Agents on the Phenolic Composition of Organic Grape Musts
Authors: Szövényi Áron Pál , Sólyom-Leskó Annamária , Szabó Anna , Nagy Balázs , Varga Zsuzsanna , Nyitrainé Sárdy Diána Ágnes
Published: December 2024

Protein-based clarification agents were tested to clarify Chardonnay grape musts during sedimentation. The experiments were conducted in the Etyek–Buda Wine Region in Northwest Hungary over four vintages between 2020 and 2023. The performance of the treatment agents was influenced by several factors, such as the composition of the grape must (the absolute concentration and the relative ratio of phenolic compounds) which varied with the vintage characteristics, the physiological and phenolic ripeness of the grapes, and the composition of the clarifying agents itself. Recent investigations show that fully ripe fruit juices can be clarified more effectively, and the effectiveness increases when different types of clarification agents are combined with the plant proteins, e.g., PVPP greatly facilitates the removal of phenolic compounds. The tested plant protein-based clarification agents did not influence the YAN source of the grape musts before fermentation. Our investigations proved an effective impact of these preparations even during the first steps of wine technology. Sensory properties and chemical stability are improved by decreasing the polyphenol content before fermentation, and, besides the good technological effects, wines treated with plant protein agents can be included in the vegan diet.
Alternative Non-Destructive Approach for Estimating Morphometric Measurements of Chicken Eggs from Tomographic Images with Computer Vision
Authors: López Vargas Jean Pierre Brik , de Abreu Katariny Lima , Duarte de Paula Davi , Pinheiro Salvadeo Denis Henrique , Arantes de Souza Lilian Francisco , Bôa-Viagem Rabello Carlos
Published: December 2024

The egg has natural barriers that prevent microbiological contamination and promote food safety. The use of non-destructive methods to obtain morphometric measurements of chicken eggs has the potential to replace traditional invasive techniques, offering greater efficiency and accuracy. This paper aims to demonstrate that estimates derived from non-invasive approaches, such as 3D computed tomography (CT) image analysis, can be comparable to conventional destructive methods. To achieve this goal, two widely recognized deep learning architectures, U-Net 3D and Fully Convolutional Networks (FCN) 3D, were modeled to segment and analyze 3D CT images of chicken eggs. A dataset of real CT images was created and labeled, allowing the extraction of important morphometric measurements, including height, width, shell thickness, and volume. The models achieved an accuracy of up to 98.69%, demonstrating their effectiveness compared to results from manual measurements. These findings highlight the potential of CT image analysis, combined with deep learning, as a non-invasive alternative in industrial and research settings. This approach not only minimizes the need for invasive procedures but also offers a scalable and reliable method for egg quality assessment.
Optimization of Mushroom (Agaricus bisporus and Pleurotus ostreatus) By-Products Processing for Prospective Functional Flour Development
Authors: Bermúdez-Gómez Patricia , Fernández-López Juana , Pérez-Clavijo Margarita , Viuda-Martos Manuel
Published: December 2024

Stems are a major by-product of mushroom production. This study optimizes the transformation of Agaricus bisporus stems (ABS) and Pleurotus ostreatus stems (POS) into flour. ABS are attached to the peat, so, the process was divided into two steps. First, four cleaning methods were tested for ABS: pre-drying, brushing, abrasive peeling, and immersion in chlorinated water and brushing. Abrasive peeling was the most effective, showing the lowest color difference (9.18), total aerobic count (3.48 log cfu/g), and the highest profitability (1 kg/h). In the second step, ABS and POS were dried using a freeze-dryer, a dehydrator, and an oven. Dehydration resulted in stems with a lower browning index (24.57 in ABS and 29.95 in POS) than the oven, and a smaller energy consumption than the freeze-dryer. Finally, three dehydration temperatures (40, 50, and 60 °C) were compared. Dehydration at 50 °C resulted in faster moisture loss (24 h) and similar phenolic compound concentrations (3.35 and 7.69 mg GAE/100g fresh ABS and POS, respectively) than at 40 °C (32 h in ABS and 28 h in POS). In conclusion, the transformation of ABS and POS into flours requires processes that influence their chemical composition, physicochemical characteristics, and the profitability of their production. In this project, the optimal process involved cleaning ABS through abrasive peeling and dehydrating both ABS and POS at 50 °C for 24 h.
Effects of Pretreatment Methods on Gamma-Aminobutyric Acid Enrichment and Quality Improvement in Highland Barley Beverages
Authors: Yin Xiaoqing , Wang Shanshan , Wang Zhirong , Wen Huaying , Bai Ting , Zhang Yuhong
Published: December 2024

Gamma-aminobutyric acid (GABA) is an important neurotransmitter that promotes sleep and reduces anxiety, but its natural synthesis in the body is insufficient, necessitating dietary intake. This study utilized a combination of germination, the addition of active barley powder, and fermentation to enhance GABA content in an enzymatically hydrolyzed highland barley beverage. The samples were divided into five groups: highland barley (HB), germinated highland barley (GB), highland barley supplemented with another high-glutamic-acid decarboxylase-active highland barley powder TB13 (BT), germinated barley supplemented with TB13 (GBT), and germinated barley supplemented with TB13 followed by fermentation (GBTF). The results indicated that all the pretreatments significantly elevated GABA levels, with the GBT sample showing the highest GABA content, which was 2.4 times that of the HB sample. Germination had minimal impact on the taste and aroma of the beverage, while the addition of TB13 active barley powder caused only slight changes to the aroma. The GABA content in the GBTF sample was 2.2 times higher than in the HB sample, and the GBTF sample also exhibited the highest total phenolic content, demonstrating the strongest antioxidant and free-radical scavenging abilities. Furthermore, the GBTF treatment increased acidity, reduced bitterness, and significantly altered the flavor profile of the barley beverage, enhancing its overall quality and consumer appeal as a GABA-rich functional drink.
Investigation of Rheological and Flow Properties of Buckwheat Dough with and Without Xanthan and Guar Gums for Optimized 3D Food Printing Across Temperature Variations
Authors: Baimaganbetova Sholpan , Omirbekov Sagyn , Wang Yanwei , Chan Mei-Yen , Talamona Didier
Published: December 2024

Buckwheat (Fagopyrum esculentum) is a gluten-free crop valued for its protein, fiber, and essential minerals. This study investigates the rheological properties of buckwheat (BW) dough, both with and without the addition of gums (no gum, guar (GG), xanthan (XG)), at varying barrel temperatures (25, 55, and 85 °C) of the rheometer and at different water content levels (45, 50, and 55% w/w) to optimize dough formulations for 3D food printing. Using high shear stress capillary tests, the consistency coefficient (K) and flow behavior index (n) were measured. The results indicated that GG significantly increases the apparent viscosity of buckwheat dough across shear rates ranging from 200 to 2000 s−1, under all temperature and water content conditions. XG also enhanced viscosity but to a lesser extent at moderate temperatures (55 °C, 85 °C). All BW dough formulations exhibited a non-Newtonian shear-thinning behavior, crucial for 3D printing applications. In addition, computational fluid dynamics (CFD) simulations were conducted to analyze the extrusion process of BW dough formulations (50% W, 50% W + XG, and 50% W + GG), focusing on shear rate, viscosity, and pressure distribution. The simulations demonstrated that shear rates increased as the dough moved through the nozzle, while viscosity decreased, facilitating extrusion. However, gum-added formulations required higher pressures for extrusion, indicating an increased difficulty in dough flow. The study highlights the complex interactions between temperature, water content, and additive type on the rheological properties of buckwheat dough, while also incorporating CFD simulations to analyze the extrusion process. These insights provide a foundation for developing nutrient-dense, gluten-free 3D-printed foods tailored to specific dietary needs.
Healthier Traditional Green Natural Aloreña de Málaga Table Olives Through Mineral Chlorides Fortification During Packaging
Authors: López-López Antonio , Moreno-Baquero José María , Garrido-Fernández Antonio
Published: December 2024

Table olive processing implies losses of mineral nutrients and increased sodium levels due to using brine during fermentation and storage. This study investigated fortifying traditional Aloreña de Málaga table olives with mixtures of KCl, CaCl2, and MgCl2 during packaging to enhance mineral content while reducing NaCl. This research analyses the distribution of cations between olives and brines and employed the Response Surface Methodology (RSM) to model mineral content and their contributions to the Reference Daily Intake (RDI). These models also facilitated the identification of optimal salt combinations for specific goals. Potassium, calcium, and magnesium contents in the olives increased from 657 mg/kg pulp (traditional) to 2578–6349 mg/kg pulp (experimental), from 858 mg/kg pulp to 858–5801 mg/kg, and from 41 mg/kg pulp to 41–2010 mg/kg pulp, respectively. Meanwhile, sodium decreased markedly, from 11,915 mg/kg pulp to about 6665 mg/kg. These changes represent a substantial improvement in the nutritional profile of these olives. Additionally, Principal Component Analysis (PCA) and clustering techniques were used to group treatments based on their mineral nutrient profiles, facilitating the selection of formulations for industrial application. These findings promote the development of nutritionally enriched natural table olives, processed without lye treatment and washing.
Genome-Wide Identification and Expression Analysis of PaNRT Gene Family Under Various Nitrogen Conditions in Avocado (Persea americana Mill.)
Authors: Tian Yuan , Jiang Ruiyuan , Qin Jian
Published: December 2024

Background: Avocado is an important economic fruit tree that requires a lot of nitrogen (N) to support growth and development. Nitrate transporter (NRT) gene family plays an essential role in N uptake and use in plants. However, no systematic identification of the NRT gene family has been reported in avocado. Methods: Bioinformatic analysis was used to identify and characterize the NRT gene family in avocado. The five N additions (29.75, 59.50, 119.00, 178.50, and 238.00 mg/L N) were used to identify the N requirement of avocado seedlings based on physiological indexes, while RNA-seq was conducted to analyze the response of PaNRTs under low-N and high-N conditions. Results: Sixty-one members of the NRT gene family were identified and dispersed on 12 chromosomes in avocado. Many cis-regulatory elements (CREs) related to phytohormonal and stress response were found in the PaNRTs promoter regions. The avocado leaves in N3 have the highest activities of N-assimilating enzymes and N content as well as the lowest activities of antioxidant enzymes. Thus, 29.75 mg/L and 119.00 mg/L were chosen as low-N supply and normal-N supply for transcriptome analysis. The transcriptome analysis showed that PaNRT1.11, PaNRT1.22, PaNRT1.32, PaNRT1.33, PaNRT1.38, and PaNRT1.52 and PaNRT1.56 among PaNRT1 members were up-regulated under normal-N condition in the leaves or roots, suggesting that these genes might affect N absorption under nitrate-sufficient conditions in avocado. RT-qPCR analysis found the relative expression patterns of selected genes among four samples were consistent with transcriptome data, suggesting that transcriptome data were reliable. Conclusions: This study would provide valuable information for identifying the functions of the NRT gene family in avocado.
Genotypic Differences Among Scions and Rootstocks Involved with Oxidative Damage and Ionic Toxicity in Cashew Plants Under Salinity
Authors: Araújo Júnior Eugênio Silva , Silva Anselmo Ferreira , Maia Josemir Moura , Silva Elania Freire da , Jardim Alexandre Maniçoba da Rosa Ferraz , Santos Hugo Rafael Bentzen , Souza Carlos Alberto Vieira , Simões Adriano do Nascimento , Souza Eduardo , Ferreira-Silva Sérgio Luiz
Published: December 2024

The aim of this study was to evaluate the influence of scion/rootstock genotypes on ionic toxicity, oxidative damage, and photosynthesis in cashew plants subjected to salt stress. Scion/rootstock combinations (CCP 76/CCP 76, CCP 76/CCP 09, CCP 09/CCP 09 and CCP 09/CCP 76) were obtained by reciprocal grafting between two genotypes (CCP 76 and CCP 09) of dwarf cashew and subjected to increased NaCl (0, 50 and 100 mM) for 30 days. Plants with CCP 76 scions had higher leaf fresh weights compared to plants with CCP 09 scions in both moderate (50 mM)- and high (100 mM)-salinity conditions. Under moderate levels of salinity, CCP 76 scions showed lower stomatal conductance, which is associated with weaker leaf toxicity symptoms, as well as lower Na+ content and higher K+ content in the leaves. Thus, the better foliar exclusion of Na+ by CCP 76 scions can be attributed to greater stomatal control, which allows for better growth and sufficient foliar K+ nutrition to mitigate foliar toxicity. Under high levels of salinity, a reduction in net photosynthesis occurred in all scion/rootstock combinations, which was apparently due to stomatal and non-stomatal restrictions. The activities of the oxidative enzymes (superoxide dismutase—SOD; ascorbate peroxidase—APX; and phenol peroxidase—POD) were little influenced by salinity, while there was a significant increase in the non-enzymatic antioxidants ascorbate (AsA) and glutathione (GSH). In addition, a reduction in photochemical activity was observed under saline conditions, suggesting that photosystems possess a potential protective mechanism. It was observed that the stomatal closure exhibited by the CCP 76 scion genotype may exert relative control over the flow of Na+ to the shoots under salt stress conditions. Taken together, the data show that, in the two genotypes evaluated, oxidative protection was more associated with reduced photochemical activity and higher levels of non-enzymatic antioxidants (AsA and GSH) than it was with the SOD-APX-POD enzymatic system.
Refining Degree-Day Models for Sparganothis Fruitworm in Cranberry by Biofix and Variety
Authors: Shope James , Salazar-Mendoza Paolo , Ben-Zvi Yahel , Rodriguez-Saona Cesar
Published: December 2024

Timing insecticide applications with insect emergence is critical for the management of cranberry pests like Sparganothis fruitworm (Sparganothis sulfureana, Lepidoptera: Tortricidae). The annual peak flight of S. sulfureana has previously been predicted using a degree-day model with a biofix date of 1 March; however, this biofix is not suitable for regions where winter and spring temperatures are warmer and flooding of cranberry beds is relied upon, which inhibits S. sulfureana development. In this study, we present two new degree-day models for predicting S. sulfureana peak flight based on six years of trapping data from New Jersey (USA): one with a biofix of 15 April, a date when drainage of cranberry beds occurs on average, and another using individual bed drainage dates. These models project peak flights at 525.5 and 521.0 degree-days using 15 April and water draw date as biofixes, respectively. These models can be used interchangeably, with both biofixes being suitable for regional grower guidance. Furthermore, differences in S. sulfureana peak flight were observed across four cranberry varieties; however, the effect of variety was influenced by year (significant variety-by-year interaction). This year-to-year variation in peak flight was strongly associated with spring (April–May) temperatures. Using these models, we project that with climate change, the peak flight of S. sulfureana in New Jersey cranberry beds may occur up to a week earlier by 2050. The use of a region-specific biofix and variety-specific models will help to better refine degree-day models for S. sulfureana, allowing for improved timing of management strategies against this pest.
Impact of Aerated Irrigation Duration on the Growth of Greenhouse Grape Seedlings and Rhizosphere Soil Microorganisms
Authors: Liang Yinchi , Wang Wei , Xi Jinshan , Zhao Shiqiang , Zhou Yufan , Zhang Huanhuan , Yu Kun , Zheng Zhong , Zhao Fengyun
Published: December 2024

This study investigates the effects of varying durations of aerated irrigation, administered at a consistent frequency, on the growth of greenhouse grape seedlings and the structure of the rhizosphere soil microbial community. Using two-year-old ‘Flame Seedless’ grape seedlings as the test material, we established a control group with no aeration (CK) and three treatment groups with aeration durations of 10 min (T1), 20 min (T2), and 30 min (T3), respectively. We determined grape seedling growth under different aerating durations. Additionally, changes in the rhizosphere soil microbial community of the plants were analyzed using 16S and ITS high-throughput genome sequencing to further explore the correlation between microbial diversity and plant growth. The results revealed that: (1) Aerated irrigation significantly enhanced plant growth, with the T2 treatment yielding superior increases in plant height, above-ground dry weight, below-ground dry weight, total root length, and root volume compared to T1 and T3 treatments. (2) Aeration treatments notably elevated the Shannon and Chao1 indices of the rhizosphere soil fungal community, with the T2 treatment exhibiting the most substantial effects, and the Shannon index of the bacterial community was also significantly higher under the T2 treatment. (3) The T2 treatment significantly increased the relative abundance of beneficial aerobic bacterial genera such as Flavobacterium, Ellin6067, and Coniochaeta, while decreasing the relative abundance of detrimental fungal genera like Fusarium and Gibberella. In conclusion, a 20 min aeration duration can effectively promote grape seedling growth, enhance the diversity of rhizosphere soil microbial communities, increase beneficial aerobic microorganisms, and reduce harmful ones. This study provides a theoretical basis for optimizing aerated irrigation practices in facility grape cultivation.
Sex Differences in Depression: Insights from Multimodal Gray Matter Morphology and Peripheral Inflammatory Factors
Authors: Wang Wenjun , Liang Wenjia , Sun Chenxi , Liu Shuwei
Published: December 2024

Major depressive disorder (MDD) exhibits notable sex differences in prevalence and clinical and neurobiological manifestations. Though the relationship between peripheral inflammation and MDD-related brain changes is well studied, the role of sex as a modifying factor is underexplored. This study aims to assess how sex influences brain and inflammatory markers in MDD. We utilized voxel-based and surface-based morphometry to analyze gray matter (GM) structure, along with GM-based spatial statistics (GBSS) to examine GM microstructure among treatment-naive patients with depression (n = 174) and age-matched healthy controls (n = 133). We uncovered sex-by-diagnosis interactions in several limbic system structures, the frontoparietal operculum and temporal regions. Post hoc analyses revealed that male patients exhibit pronounced brain abnormalities, while no significant differences were noted in females despite their higher depressive scores. Additionally, heightened inflammation levels in MDD were observed in both sexes, with sex-specific effects on sex-specific brain phenotypes, particularly including a general negative correlation in males. Intriguingly, mediation analyses highlight the specific role of the parahippocampal gyrus (PHG) in mediating interleukin (IL)-8 and depression in men. The findings suggest that in clinical practice, it would be beneficial to prioritize sex-specific assessments and interventions for MDD. This includes recognizing the possibility that male patients may experience significant brain alterations, especially when identifying male patients who may underreport symptoms. Possible limitations encompass a small sample size and the cross-sectional design. In future research, the incorporation of longitudinal studies or diverse populations, while considering illness duration, will enhance our understanding of how inflammation interacts with brain changes in depression.
Tumor Metabolic Reprogramming and Ferroptosis: The Impact of Glucose, Protein, and Lipid Metabolism
Authors: Zhu Keyu , Cai Yuang , Lan Lan , Luo Na
Published: December 2024

Ferroptosis, a novel form of cell death discovered in recent years, is typically accompanied by significant iron accumulation and lipid peroxidation during the process. This article systematically elucidates how tumor metabolic reprogramming affects the ferroptosis process in tumor cells. The paper outlines the basic concepts and physiological significance of tumor metabolic reprogramming and ferroptosis, and delves into the specific regulatory mechanisms of glucose metabolism, protein metabolism, and lipid metabolism on ferroptosis. We also explore how complex metabolic changes in the tumor microenvironment further influence the response of tumor cells to ferroptosis. Glucose metabolism modulates ferroptosis sensitivity by influencing intracellular energetic status and redox balance; protein metabolism, involving amino acid metabolism and protein synthesis, plays a crucial role in the initiation and progression of ferroptosis; and the relationship between lipid metabolism and ferroptosis primarily manifests in the generation and elimination of lipid peroxides. This review aims to provide a new perspective on how tumor cells regulate ferroptosis through metabolic reprogramming, with the ultimate goal of offering a theoretical basis for developing novel therapeutic strategies targeting tumor metabolism and ferroptosis.
Contemporary Review of Minimally Invasive Mitral Valve Surgery: Current Considerations and Innovations
Authors: Alsheebani Sharifa , Goubran Daniel , de Varennes Benoit , Chan Vincent
Published: December 2024

Minimally invasive mitral valve surgery (MIMVS) has become a well-established alternative to traditional median sternotomy at high-volume surgical centers. Advancements in surgical instruments have led to further refinement of MIMVS. However, MIMVS remains limited to select patients in select settings. In this review, we provide a brief overview of the evolution of MIMVS, as well as a technical description of the most relevant aspects of minimally invasive mitral valve surgery.
An Integrated Framework for Real-Time Sea-State Estimation of Stationary Marine Units Using Wave Buoy Analogy
Authors: Majidiyan Hamed , Enshaei Hossein , Howe Damon , Wang Yiting
Published: December 2024

Understanding the impact of environmental factors, particularly seaway, on marine units is critical for developing efficient control and decision support systems. To this end, the concept of wave buoy analogy (WBA), which utilizes ships as sailing buoys, has captured practitioners’ attention due to its cost-effectiveness and extensive coverage. Despite extensive research, real-time sea-state estimation (SSE) has remained challenging due to the large observation window needed for statistical inferences. The current study builds on previous work, aiming to propose an AI framework to reduce the estimation time lag between exciting waves and respective estimation by transforming temporal/spectral features into a manipulated scalogram. For that, an adaptive ship response predictor and deep learning model were incorporated to classify seaway while minimizing network complexity through feature engineering. The system’s performance was evaluated using data obtained from an experimental test on a semi-submersible platform, and the results demonstrate the promising functionality of the approach for a fully automated SSE system. For further comparison of features of low- and high-fidelity modeling, the deficits with the feature transformation of the existing SSE models are discussed. This study provides a foundation for improving online SSE and promoting the seaway acquisition for stationary marine units.
Sustainability, Risk Management, and Innovation: Enhancing Performance in Indonesian Social Enterprises
Authors: Maksum Azhar , Munawarah  , Sitepu Yuni Lestari Br , Kumalasari Fauziah
Published: December 2024

This study investigates the integration of sustainability practices and risk management in Indonesian social enterprises, emphasizing the role of innovation as a mediator and operational type as a moderator. Social enterprises face unique challenges in balancing economic sustainability with social impact, especially in emerging markets like Indonesia. A structured survey was conducted with 118 social enterprises to assess their sustainable practices, risk management procedures, innovation scores, and operational models (permanent vs. project-based). Using Structural Equation Modeling (SEM) and Partial Least Squares (PLS) analysis, the results show that sustainability practices positively influence innovation, while both innovation and risk management significantly improve sustainable performance. Additionally, innovation mediates the relationship between sustainability practices, risk management, and performance. The operational type moderates the link between risk management and sustainable performance but does not influence the connection between sustainability practices and performance. These findings suggest that innovation is crucial for improving the sustainability of social enterprises and that risk management strategies should be tailored to the operational model. Social enterprises in Indonesia should prioritize innovative approaches and effective risk management to enhance their long-term sustainability and social impact.
Mapping of Forest Species Using Sentinel-2A Images in the Alentejo and Algarve Regions, Portugal
Authors: Isbaex Crismeire , Coelho Ana Margarida , Gonçalves Ana Cristina , Sousa Adélia M. O.
Published: December 2024

Land use and land cover (LULC) studies, particularly those focused on mapping forest species using Sentinel-2 (S2A) data, face challenges in delineating and identifying areas of heterogeneous forest components with spectral similarity at the canopy level. In this context, the main objective of this study was to compare and analyze the feasibility of two classification algorithms, K-Nearest Neighbor (KNN) and Random Forest (RF), with S2A data for mapping forest cover in the southern regions of Portugal, using tools with a free, open-source, accessible, and easy-to-use interface. Sentinel-2A data from summer 2019 provided 26 independent variables at 10 m spatial resolution for the analysis. Nine object-based LULC categories were distinguished, including five forest species (Quercus suber, Quercus rotundifolia, Eucalyptus spp., Pinus pinaster, and Pinus pinea), and four non-forest classes. Orfeo ToolBox (OTB) proved to be a reliable and powerful tool for the classification process. The best results were achieved using the RF algorithm in all regions, where it reached the highest accuracy values in Alentejo Central region (OA = 92.16% and K = 0.91). The use of open-source tools has enabled high-resolution mapping of forest species in the Mediterranean, democratizing access to research and monitoring.
Semantic Comparison of Online Texts for Historical and Newly Constructed Replica Ancient Towns from a Tourist Perception Perspective: A Case Study of Tongguan Kiln Ancient Town and Jinggang Ancient Town
Authors: Guo Ruimin , He Yiwen , Zhang Xin , He Lai , Zhou Qixuan , He Guojing
Published: December 2024

This study explores the dimensions of visitor perception by conducting a semantic analysis, Grounded Theory coding classification, and sentiment analysis on online texts related to Jinggang Ancient Town and Tongguanyao Ancient Town. It reveals the differences between newly constructed and historical ancient towns in terms of tourism experience perception, landscape spatial design, and the activation of cultural heritage preservation. The results indicated the following: (1) The differences in tourists’ perceptions stem from the different needs for the characteristics of the ancient towns. Tourists focus on the design innovation and experiential interest of Tongguanyao Ancient Town, while preferring the cultural depth and authenticity of Jinggang Ancient Town. (2) Tourists are highly concerned about the characteristics of “tourism development”, highlighting the challenge of balancing tourism development with the protection of ancient town heritage resources. (3) The study further emphasizes innovative forms of the reproduction of cultural heritage through multi-sensory, modern, and diverse approaches. This study enhances landscape design in ancient towns by integrating perspectives from both tourists and designers, promoting the protection of cultural heritage and facilitating deeper cultural tourism integration.
Impact of Different Microplastics on Soil Evaporation Rates: A Comparative Analysis Across Chernozem, Umbrisol, and Luvisol
Authors: Šurda Peter , Lincmaierová Karina , Botyanszká Lenka
Published: December 2024

In recent years, there has been a growing recognition of microplastics (MPs) as significant emerging pollutants. Soil contamination by MPs, comprising plastic particles smaller than 5 mm, originates from diverse sources. The introduction of foreign substances such as MPs can instantly modify the physical properties of soil or influence soil processes, depending upon the characteristics of the plastic. The limited available studies provide evidence that insufficient attention is being paid to the impact of plastic input on soil evaporation processes. The objective of this study was to assess the impact of contamination of three types of soil (Chernozem, Umbrisol, and Luvisol) with different MPs (high-density polyethylene, polyvinyl chloride, and polystyrene) at a concentration of 5% (w/w) on the evaporative mass loss. The presence of polyvinyl chloride (PVC), high-density polyethylene (HDPE), and polystyrene (PS) significantly altered evaporative soil loss, dry bulk density, and saturated water content in different soil types. Evaporative mass loss significantly increased in Luvisol and Umbrisol soils contaminated with HDPE and in Umbrisol contaminated with PVC. In Chernozem, contamination with all examined MPs significantly reduced dry bulk density. A similar decrease in dry bulk density was observed in Luvisol and Umbrisol with PVC and HDPE. Significant reductions in saturated water content were recorded in Chernozem contaminated with HDPE, Luvisol with PS, and Umbrisol with both HDPE and PS.
Spatial Position Reasoning of Image Entities Based on Location Words
Authors: Qin Xingguo , Zhou Ya , Li Jun
Published: December 2024

The endeavor of spatial position reasoning effectively simulates the sensory and comprehension faculties of artificial intelligence, especially within the purview of multimodal modeling that fuses imagery with linguistic data. Recent progress in visual image–language models has marked significant advancements in multimodal reasoning tasks. Notably, contrastive learning models based on the Contrastive Language-Image pre-training (CLIP) framework have attracted substantial interest. Predominantly, current contrastive learning models focus on nominal and verbal elements within image descriptions, while spatial locatives receive comparatively less attention. However, prepositional spatial indicators are pivotal for encapsulating the critical positional data between entities within images, which is essential for the reasoning capabilities of image–language models. This paper introduces a spatial location reasoning model that is founded on spatial locative terms. The model concentrates on spatial prepositions within image descriptions, models the locational interrelations between entities in images through these prepositions, evaluates and corroborates the spatial interconnections of entities within images, and harmonizes the precision with image–textual descriptions. This model represents an enhancement of the CLIP model, delving deeply into the semantic characteristics of spatial prepositions and highlighting their directive role in visual language models. Empirical evidence suggests that the proposed model adeptly captures the correlation of spatial indicators in both image and textual representations across open datasets. The incorporation of spatial position terms into the model was observed to elevate the average predictive accuracy by approximately three percentage points.