bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantifying vegetation cover on coastal active dunes using nationwide aerial image analysis
Authors: Ryan Cate , Buckley Hannah L. , Bishop Craig D. , Hinchliffe Graham , Case Bradley S. 
Published: July 2024

AbstractCoastal active dunes provide vital biodiversity, habitat, and ecosystem services, yet they are one of the most endangered and understudied ecosystems worldwide. Therefore, monitoring the status of these systems is essential, but field vegetation surveys are time‐consuming and expensive. Remotely sensed aerial imagery offers spatially continuous, low‐cost, high‐resolution coverage, allowing for vegetation mapping across larger areas than traditional field surveys. Taking Aotearoa New Zealand as a case study, we used a nationally representative sample of coastal active dunes to classify vegetation from red‐green‐blue (RGB) high‐resolution (0.075–0.75 m) aerial imagery with object‐based image analysis. The mean overall accuracy was 0.76 across 21 beaches for aggregated classes, and key cover classes, such as sand, sandbinders, and woody vegetation, were discerned. However, differentiation among woody vegetation species on semi‐stable and stable dunes posed a challenge. We developed a national cover typology from the classification, comprising seven vegetation types. Classification tree models showed that where human activity was higher, it was more important than geomorphic factors in influencing the relative percent cover of the different active dune cover classes. Our methods provide a quantitative approach to characterizing the cover classes on active dunes at a national scale, which are relevant for conservation management, including habitat mapping, determining species occupancy, indigenous dominance, and the representativeness of remaining active dunes.
Resilience in action: Kosovo's National Development Strategy to incorporate sustainable development goals
Authors: Alibašić Haris 
Published: July 2024

AbstractThrough resilience theory, this paper explores the integration and alignment of the United Nations sustainable development goals (SDGs) within Kosovo's National Development Strategy (NDS). It highlights how adaptability and strategic planning underpin sustainable development in emerging national contexts like Kosovo, offering a qualitative analysis to identify gaps and suggest improvements for SDG integration. Utilizing a qualitative analysis, this study identifies gaps and provides recommendations for better SDG integration within Kosovo's national development agenda. Data analysis involves the thematic coding of qualitative data and synthesis of case study findings by examining existing documents, strategies, and plans as manifestations of Kosovo's commitment to fostering resilience and achieving a sustainable future. Key insights include recommendations for enhancing governance, environmental protection mechanisms, and social inclusivity to achieve resilient and sustainable economic growth. The study contributes to the discourse on resilience theory in national sustainable development strategies amidst political uncertainty.
The relationship between culture and sustainable development goal compliance at the municipal level
Authors: Benito Bernardino , Guillamón María‐Dolores , Ríos Ana‐María , Cifuentes‐Faura Javier 
Published: July 2024

AbstractThis study assesses the role of culture in achieving the sustainable development goals (SDGs) in the Spanish public sector, focusing on the influence of local government cultural spending and education levels on SDG compliance in municipalities. Cultural spending, considered as a percentage of total non‐financial local government spending, municipal education levels and SDG implementation indicators from the Sustainable Development Solutions Networks (SDSN)‐Spain are used in this research, which employs an ordinary least squares regression and two‐stage least squares analysis for robustness. The results suggest that higher levels of education correlate with SDG compliance, while increased spending on culture does not. Since the existing research about the impact of culture on the SDGs is limited, this study addresses this gap. It suggests that policymakers should promote culture and integrate sustainability into education to increase SDG awareness and implementation.
Developing theoretically grounded causal maps to examine and improve policy narratives about global challenges
Authors: Buzogany Raquel Froese , Kopainsky Birgit , Gonçalves Paulo 
Published: July 2024

AbstractThe Sustainable Development Goals present a call to action for all countries to accelerate the implementation of solutions to address the world's biggest challenges. While policy portfolios to achieve such goals should be varied, often dominant policy narratives cluster around limited themes. We use a grounded theory approach to elicit causality from qualitative data to visualize interactions across variables spanning multiple domains influencing global challenges. We develop a comprehensive causal loop diagram, where we assess the impact of dominant policy narratives and expand the formulation of policy options. Our approach serves as an exemplar application of qualitative system dynamics to distill the operational logic of policy narratives that can subsequently be considered in model‐based policy analysis. We illustrate our approach by focusing on the interactions among poverty and hunger and compare policy implications arising from the dominant narratives only versus those arising from a more comprehensive understanding of the interactions. © 2024 The Author(s). System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society.
Benzothiazole‐Piperazine Hybrids Effectively Target C4‐2 Castration‐Resistant Prostate Cancer Cells in vitro Implicated through Computational Studies
Authors: Amin Andleeb , Bhat Basharat Ahmad , Ul‐Khazir Zubaid , Hurrah Aaqib A. , Bhat Imtiyaz A. , Sharma Praveen Kumar , Masoodi Khalid Z. 
Published: July 2024

AbstractA series of new analogs based on benzothiazole‐piperazine conjugates were synthesized and assessed to investigate their anticancer properties using in vitro and in silico techniques. The compounds 3 a–3 h were tested against prostate (C4‐2) cancer cells, and the results revealed that all the compounds showed significant inhibitory activity against C4‐2 cells (>50 % inhibition at 20 μM). Among all, 2‐(4‐(pyrimidin‐2‐yl) piperazin‐1‐yl) benzo[d]thiazole demonstrated the most prominent activity in the cell viability assay conducted displaying an IC50 value of 19.98 μM. In vitro studies have demonstrated that the compound can selectively target the androgen receptor (AR) and reduce the expression of several androgen‐responsive genes, including EAF2, ELL2, PSA and CALR genes, in castration‐resistant prostate cancer cells. Molecular docking results also revealed that all the compounds exhibited good energy binding scores against the androgen receptor target (PB ID: 2PNU) particularly compound 3 g which showed a maximum binding energy of −9.87 kcal/mol followed by other compounds as well as the established prostate cancer drug, enzalutamide, with a binding energy of −5.66 kcal/mol. Docking results were further supported by MD simulation studies, which confirmed that the ligand+protein complex was in stable conformation throughout the simulation time of 100 nanoseconds. Collectively, the present results, stemming from a combination of in vitro and in silico examinations, demonstrate that compound 3 g displays notable anti‐cancer characteristics, implying its viability as a prospective anti‐cancer pharmaceutical subject to clinical validation and subsequent development.
Study on the Effects of Fe Doping on C‐ZFe Catalyst for Catalytic Removal of NO from the Low‐Temperature Flue Gas
Authors: Cao Wan , Zhang Weijun , Guo Ziyang , Sun Ximei 
Published: July 2024

AbstractThe denitrification efficiency of carbon‐based zero valent iron catalyst (C‐ZFe) for low‐temperature selective catalytic reduction (SCR) (<140°C) highly depends on the structural species of iron oxide (FexOy) and the physicochemical properties of the catalyst. In the study, we investigated the main factors affecting the low‐temperature denitrification efficiency of C‐ZFe such as temperature, iron content and O2. The results showed that the average NOX conversion was 72.6 % at 135°C when the space velocity was 459 h−1 and the mass ratio of carbon to iron was 15 % to 85 %. The surface morphology and structure of C‐ZFe were characterized by the surface area and pore size distribution measurements, X‐ray diffraction (XRD), fourier transform infrared spectroscopy (FTIR) and X‐ray photoelectron spectroscopy (XPS). The results indicated that the iron on the catalyst surface was oxidized by O2 to Fe2O3, which could retain NO and then formed intermediate products. NO entered the mesoporous structure along C‐ZFe surface and proceeded a catalytic reduction reaction with the adjacent carbon.
Interfacial Membranization of Regenerated Cellulose Nanoparticles and a Protein Renders Stable Water‐in‐Water Emulsion
Authors: Zhu Ya , Beaumont Marco , Solin Katariina , Spiliopoulos Panagiotis , Zhao Bin , Tao Han , Kontturi Eero , Bai Long , Rojas Orlando J. 
Published: July 2024

AbstractPickering water‐in‐water (W/W) emulsions stabilized by biobased colloids are pertinent to engineering biomaterials with hierarchical and confined architectures. In this study, stable W/W emulsions are developed through membranization utilizing biopolymer structures formed by the adsorption of cellulose II nanospheres and a globular protein, bovine serum albumin (BSA), at droplet surfaces. The produced cellulose II nanospheres (NPcat, 63 nm diameter) bearing a soft and highly accessible shell, endow rapid and significant binding (16 mg cm−2) with BSA. NPcat and BSA formed complexes that spontaneously stabilized liquid droplets, resulting in stable W/W emulsions. It is proposed that such a system is a versatile all‐aqueous platform for encapsulation, (bio)catalysis, delivery, and synthetic cell mimetics.
Direct Zeptomole Detection of RNA Biomarkers by Ultrabright Fluorescent Nanoparticles on Magnetic Beads
Authors: Cruz Da Silva Elisabete , Gaki Paraskevi , Flieg Fabien , Messmer Melanie , Gucciardi Floriane , Markovska Yevheniia , Reisch Andreas , Fafi‐Kremer Samira , Pfeffer Sébastien , Klymchenko Andrey S. 
Published: July 2024

AbstractNucleic acids are important biomarkers in cancer and viral diseases. However, their ultralow concentration in biological/clinical samples makes direct target detection challenging, because it leads to slow hybridization kinetics with the probe and its insufficient signal‐to‐noise ratio. Therefore, RNA target detection is done by molecular (target) amplification, notably by RT‐PCR, which is a tedious multistep method that includes nucleic acid extraction and reverse transcription. Here, a direct method based on ultrabright dye‐loaded polymeric nanoparticles in a sandwich‐like hybridization assay with magnetic beads is reported. The ultrabright DNA‐functionalized nanoparticle, equivalent to ≈10 000 strongly emissive rhodamine dyes, is hybridized with the magnetic bead to the RNA target, providing the signal amplification for the detection. This concept (magneto‐fluorescent sandwich) enables high‐throughput detection of DNA and RNA sequences of varied lengths from 48 to 1362 nt with the limit of detection down to 0.3 fm using a plate reader (15 zeptomoles), among the best reported for optical sandwich assays. Moreover, it allows semi‐quantitative detection of SARS‐CoV‐2 viral RNA directly in clinical samples without a dedicated RNA extraction step. The developed technology, combining ultrabright nanoparticles with magnetic beads, addresses fundamental challenges in RNA detection; it is expected to accelerate molecular diagnostics of diseases.
Multiscale Materials Engineering via Self‐Assembly of Pentapeptide Derivatives from SARS CoV E Protein
Authors: Sarkar Dibakar , Khan Aftab Hossain , Polepalli Sainath , Sarkar Riddhiman , Das Prasanta Kumar , Dutta Somnath , Sahoo Nirakar , Bhunia Anirban 
Published: July 2024

AbstractShort peptide‐based supramolecular hydrogels hold enormous potential for a wide range of applications. However, the gelation of these systems is very challenging to control. Minor changes in the peptide sequence can significantly influence the self‐assembly mechanism and thereby the gelation propensity. The involvement of SARS CoV E protein in the assembly and release of the virus suggests that it may have inherent self‐assembling properties that can contribute to the development of hydrogels. Here, three pentapeptide sequences derived from C‐terminal of SARS CoV E protein are explored with same amino acid residues but different sequence distributions and discovered a drastic difference in the gelation propensity. By combining spectroscopic and microscopic techniques, the relationship between peptide sequence arrangement and molecular assembly structure are demonstrated, and how these influence the mechanical properties of the hydrogel. The present study expands the variety of secondary structures for generating supramolecular hydrogels by introducing the 310‐helix as the primary building block for gelation, facilitated by a water‐mediated structural transition into β‐sheet conformation. Moreover, these Fmoc‐modified pentapeptide hydrogels/supramolecular assemblies with tunable morphology and mechanical properties are suitable for tissue engineering, injectable delivery, and 3D bio‐printing applications.
Enhancing concrete durability and strength: An innovative approach integrating abrasion and cement slurry treatment for recycled coarse aggregates
Authors: Panghal Harish , Kumar Awadhesh 
Published: July 2024

AbstractThis study introduces a novel approach to enhance the durability and strength of concrete by integrating abrasion and cement slurry treatments on surface‐treated recycled coarse aggregates (STRCA). Initial abrasion treatment removes aged mortar from the recycled coarse aggregate (RCA) surface, while subsequent cement slurry modification provides a fresh surface, reinforcing the bond with the concrete matrix. Through detailed material analyses including x‐ray diffraction, scanning electron microscopy, and energy‐dispersive x‐ray, microstructural changes are evaluated alongside compressive strength, drying shrinkage, electrical resistivity, and chloride ion penetration of STRCA‐based concrete. Results indicate significant improvements in mechanical properties and durability as the treatments eliminate mortar and enhance the interfacial connection with cement paste. Notably, a substantial 29.37% strength enhancement is observed at 25% replacement (STRCA 25), demonstrating treatment efficacy. While a reduction of 11.58% occurs at 100% replacement (STRCA 100), up to 75% replacement shows minimal strength loss, with optimal enhancements at 50% replacement. Additionally, STRCA concrete exhibits lower drying shrinkage (11%–20% reduction) and increased electrical resistivity (28%–36% rise), indicating improved durability at 100% replacement. Enhanced resistance to chloride ion penetration is also evident, with a 22%–28% increase at 100% replacement compared to conventional RCA. Overall, this study highlights the effectiveness of dual treatments for enhancing concrete properties using STRCA.
Noise Enhances Excitability of a Neuronal Population with Heterogeneous Excitatory Neurons
Authors: Zheng Tianyi , Li Bin , Jimbo Yasuhiko , Shimba Kenta , Kotani Kiyoshi 
Published: July 2024

AbstractCortical excitability is sensitive to noise perturbations despite homeostatic regulation. However, modeling the effect of noise in a heterogeneous neuronal population is a mathematical challenge. Using a mean‐field model of a randomly connected excitatory population, we investigated how noise affects excitability at the resting state. Stable equilibrium analysis revealed that increasing noise intensity enhances excitability, indexed by synaptic conductance. Further, this enhancement disappeared when excitability is sufficiently high due to strong mean input current, but not influenced by the connection probability of the population. Finally, the mechanism of noise‐induced enhancement was explained by eigenvalues moving toward the imaginary axis. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.
Fluorescence imaging‐guided pelvic lymph node localization and resection of bladder cancer after intracutaneous injection of indocyanine green into the lower limbs and perineum
Authors: Wei Yangbing , Liu Chao , Cao Xiaoming , Wu Bo , Wei Liang , Yang Hua , Liu Chen , Hao Haifeng , Jing Qiang , Liu Fan , Sun Libing , Xing Nianzeng , Yang Xiaofeng 
Published: July 2024

AbstractBackgroundPelvic lymph node dissection (PLND) in radical cystectomy (RC) is of great significance, but the method and scope of PLND remain controversial. Based on the principle of indirect lymphadenography, we designed a method to localize the whole pelvic lymph nodes by intradermal injection of indocyanine green (ICG) through the lower limbs and perineum, and to evaluate the effectiveness of this method.MethodsIn a single center, 54 bladder cancer patients who underwent RC and PLND participated in a prospective clinical trial, which began on February 28, 2022 and ended on December 30, 2022. ICG solution was injected subcutaneously at the medial malleolus of both lower extremities and at both sides of the midline of the perineum. The fluorescent laparoscopy was used to trace, locate, and remove the targeted areas under the image fusion mode. The consistency of lymph node resection was determined by histopathological diagnosis. The impact of ICG guidance on the surgical time of PLND was compared with that of 11 bladder cancer patients who underwent RC and PLND without ICG injection, serving as the control group.ResultsPerineal lower limb combined injection can provide comprehensive visualization of pelvic lymph nodes. This technique reduces PLND surgical time and increases the accuracy of PLND.ConclusionIntracutaneous injection of ICG into the lower limbs and perineum can specifically mark pelvic lymph nodes. Intraoperative fluorescence imaging can accurately identify, locate, and resect lymph nodes in the pelvic region, reducing PLND surgical time and increasing the accuracy of PLND.
Synthesis, characterization, and phosphorus adsorption of Mg/Fe‐modified biochar from cotton stalk pretreated with Coriolus versicolor
Authors: Deveci Ece Ümmü , Öz Derya , Madenli Özgecan 
Published: July 2024

AbstractIn recent years, the research potential in utilizing biochars as adsorbents in adsorption processes has grown due to their eco‐friendly and economical nature. However, biochar often possesses a negative surface charge that limits its affinity for binding anions. Nitric acid washing and pretreatment with Coriolus versicolor can break down the lignocellulosic structure in cotton stalk waste, facilitating the subsequent impregnation of Mg and Fe metal oxides. These pretreatment steps can lead to the production of diverse and functionalized biochars with higher adsorption capacities. In this study, cotton stalk waste was first washed with diluted nitric acid and then subjected to biological pretreatment by incubation with C. versicolor, followed by impregnation with Mg and Fe to obtain CV‐CS/Fe and CV‐CS/Mg biochars. The results showed that the applied pretreatments altered the physicochemical properties and significantly increased the phosphorus adsorption capacity. The adsorption capacities of CV‐CS/Fe and CV‐CS/Mg biochars were found to be 277.88 and 507.01 mg g−1, respectively. The results indicate that the incorporation of multiple metal oxide impregnates enhances P adsorption. Furthermore, in the kinetic study, pseudo‐first‐order and pseudo‐second‐order models provided a well fit, determining chemical adsorption as the main adsorption mechanism for phosphorus adsorption. The biochars demonstrated compatibility with Langmuir–Freundlich models. Overall, the findings suggest the possibility of synthesizing biochars with improved adsorptive properties through pretreatment, and these engineered biochars hold promising potential as effective adsorbents in the field.Practitioner Points
Eco‐friendly, natural, and economical biochar was synthesized.
Biochar was produced via Coriolus versicolor pretreatment.
High adsorption capacities of CV‐PS/Mg biochars were found to be 507.01 mg g−1.
Adsorption capacities of biochars can be improved by pretreatment.
A systematic review and research recommendations on artificial intelligence for automated cervical cancer detection
Authors: Khare Smith K. , Blanes‐Vidal Victoria , Booth Berit Bargum , Petersen Lone Kjeld , Nadimi Esmaeil S. 
Published: July 2024

AbstractEarly diagnosis of abnormal cervical cells enhances the chance of prompt treatment for cervical cancer (CrC). Artificial intelligence (AI)‐assisted decision support systems for detecting abnormal cervical cells are developed because manual identification needs trained healthcare professionals, and can be difficult, time‐consuming, and error‐prone. The purpose of this study is to present a comprehensive review of AI technologies used for detecting cervical pre‐cancerous lesions and cancer. The review study includes studies where AI was applied to Pap Smear test (cytological test), colposcopy, sociodemographic data and other risk factors, histopathological analyses, magnetic resonance imaging‐, computed tomography‐, and positron emission tomography‐scan‐based imaging modalities. We performed searches on Web of Science, Medline, Scopus, and Inspec. The preferred reporting items for systematic reviews and meta‐analysis guidelines were used to search, screen, and analyze the articles. The primary search resulted in identifying 9745 articles. We followed strict inclusion and exclusion criteria, which include search windows of the last decade, journal articles, and machine/deep learning‐based methods. A total of 58 studies have been included in the review for further analysis after identification, screening, and eligibility evaluation. Our review analysis shows that deep learning models are preferred for imaging techniques, whereas machine learning‐based models are preferred for sociodemographic data. The analysis shows that convolutional neural network‐based features yielded representative characteristics for detecting pre‐cancerous lesions and CrC. The review analysis also highlights the need for generating new and easily accessible diverse datasets to develop versatile models for CrC detection. Our review study shows the need for model explainability and uncertainty quantification to increase the trust of clinicians and stakeholders in the decision‐making of automated CrC detection models. Our review suggests that data privacy concerns and adaptability are crucial for deployment hence, federated learning and meta‐learning should also be explored.This article is categorized under:
Fundamental Concepts of Data and Knowledge > Explainable AI
Technologies > Machine Learning
Technologies > Classification