bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of innovative policy for Nature-based Solutions: Analysis from three European city case studies
Authors: Petersen Carolyn Jane , Russel Duncan John , Jensen Anne , Pedersen Anders Branth , Kirsop-Taylor Nick 
Published: October 2024

Abstract

Addressing the current unprecedented climate and environmental challenges and stimulating sustainable development in our urban areas and beyond entails experimentation and innovation in policy making, instead of the siloing that has often been the status quo. Nature-based Solutions (NBS) are well suited to fostering integrated and multi-functional policy solutions to current challenges but are subject to complex governance influences. Through a comparative analysis of interview and policy workshop data in three European city case studies with differing governance structures, this paper examines the external, societal and governing influences on NBS innovation, and the governance structures from which innovation and experimentation in NBS are likely to occur—including the political side of NBS which has hitherto been relatively unexplored. The results indicate a number of important facilitating and hindering factors across the range of governing, societal and external influences, and show some association between NBS innovation and decentralized policy making. They highlight the importance of policy coherence of NBS initiatives with government policy strategy; and of the willingness by policy makers / local government officials to engage with and appeal strategically to political decision-makers regarding external policy drivers—e.g. climate adaptation and health. The data also indicates that where citizen participation and consultation were built into NBS projects, this brought both innovation and additionality—in terms of the design, quality, biodiversity, multi-functionality and co-benefits of green / blue spaces. Key differences that led to differing NBS outcomes included size and complexity of the urban area, and characteristics of the governing architecture.
Optimization of Faber Polynomial based Propagators via Proper Orthogonal Decomposition
Authors: Plotnikov Wladimir , Inci Bernd Levent , Schulz Dirk 
Published: October 2024

Abstract

The focus of this research lies on the extrapolation of the time dependent Faber polynomial based propagator applied on Maxwell’s equations with the Proper Orthogonal Decomposition approach. In particular, when investigating a system in the application area of THz-technology or nanophotonics it is common to have geometries, which require an extraordinary fine spatial resolution. Unfortunately,this is accompanied by the temporal resolution, which is restricted accordingly. For this reason, the explicit Faber approach is chosen to approximate the computationally intensive matrix exponential in order to enable large time stepsizes. To achieve a further acceleration of the computation time, the Proper Orthogonal Decomposition approach is used to enormously reduce the complexity of the evaluation. In this context, a hybrid model is examined to establish abalance between the calculation time by means of a reduced order model and the error accuracy via a full order model.
Phytohormones and microbial elicitation on glycyrrhizin production and gene expression in the hairy root of Glycyrrhiza glabra L.
Authors: Behdad Assieh , Ganjeali Ali 
Published: October 2024

Abstract

Glycyrrhiza glabra (licorice) is a valuable and endangered medicinal plant recognized for its rich saponin content, particularly glycyrrhizin. Hairy root culture offers a sustainable alternative for continuous glycyrrhizin production while preserving the species' biodiversity. This study aimed to determine the most effective Agrobacterium rhizogenes strain (ATCC 15834, A4, and A13) for hairy root induction and to assess the influence of Rhizobium leguminosarum (R) and Pseudomonas putida (P) on glycyrrhizin and saponin production. Additionally, the combined effects of the most efficient biotic elicitor with methyl jasmonate (MeJA) and gibberellin (GA) on the phytochemical and physiological responses of licorice hairy roots were investigated. The expression of genes related to glycyrrhizin biosynthesis was also analyzed. The hairy root transformation was confirmed in all strains through rolB gene amplification, with strain A13 identified as the most efficient. R. leguminosarum was more effective than P. putida in increasing glycyrrhizin and saponin content. Treatments with Rhizobium, MeJA, and GA increased oxidative stress markers, membrane damage, and the activity of enzymatic and non-enzymatic antioxidants. The highest glycyrrhizin and saponin levels were found in the MeJA×R and R treatments, respectively. RT‒PCR analysis demonstrated that the gene expression of bAS, CYP88D6, and CYP72A154 elevated under MeJA×R treatment compared to the control. The PCA-biplot analysis showed that DPPH (IC50) and H2O2 levels had the most difference in assayed traits. In summary, the MeJA×R combination may activate a complex signaling network that scavenges ROS, leading to higher glycyrrhizin accumulation and upregulation of its biosynthetic pathway in licorice hairy roots.
Fabrication of g-C3N4/NiO/ZnO based Ternary Nanocomposite for Efficient Photocatalytic Degradation of Methylene Blue
Authors: Bano Nargis , Fatima Rida , Bilal Uzma , Abbas Taimoor , Bilal Abu Summama Sadavi , Hussain Ijaz 
Published: October 2024

Abstract

Photocatalysis has emerged as a widely recognized and environmentally friendly technique for the degradation of biological contaminants into less hazardous substances. The technique offers a sustainable path for contamination reduction by utilizing sunlight-activated catalysts to initiate reactions for the degradation of pollutants. In this work, a facile co-precipitation approach was utilized to synthesize a ternary nanocomposite-based photocatalyst to improve photocatalytic performance. The metal oxide semiconductors ZnO and NiO were successfully integrated into the g-C3N4 matrix to develop a photocatalyst that showed substantially increased photocatalytic activity. The synthesized ternary nanocomposite was investigated for different physicochemical techniques such as photoluminescence (PL), ultraviolet-visible (UV-Vis) absorption spectroscopy, scanning electron microscopy (SEM), Raman spectroscopy, and X-ray diffraction (XRD). The structural, morphological, and optical characteristics of the ternary nanocomposite were thoroughly explored by these physiochemical techniques. The synthesized CNZ ternary nanocomposites-based photocatalyst revealed a significantly enhanced photocatalytic degradation rate of 92%, outperforming all other samples. The ternary nanocomposite demonstrated excellent reusability even after five successive reaction cycles, unveiling the superior potential in the photocatalytic application for an extended period without significantly losing its effectiveness. The synergistic integration of NiO and ZnO into g-C3N4 boosted the photocatalytic activity by enhancing electron-hole separation and reducing recombination reactions. The hybrid photocatalyst offers a great deal of promise for effectively eliminating harmful pollutants from aqueous solutions.
Afaan Oromo Fake News Detection on Social Media: - Using Deep Learning Approach
Authors: Bedada Hundaol Bedada , Waldesanbet Abebe 
Published: October 2024

Abstract

Due to the rapid growth of the internet in recent years, social media has made it easier to create and share information via computer-mediated technologies. As a result of the social media revolution, people's communication and acquaintances have changed. The majority of people nowadays use social media to find and consume news rather than traditional news agencies. On the other hand, while online social media has grown in importance as a source of information and a method of connecting people together, detecting fake information remains a difficult problem to address. The majority of previous works presented appropriate machine learning models of fake news detections are concerned with specific group of language such as English. Despite the fact, the problem is not constricted to language. As a result, we implemented deep learning models on the Afaan Oromo language news dataset extracted from twitter and Facebook pages, to detect fake news on social media. In this study we annotated dataset of 1838 news text for train and testing purposes. Three popular deep learning methods used in the experiments: LSTM, GRU, and Bi-LSTM, to determine the best performing models, and each of the model performance is evaluated with various parameters. Then, when it came to recognizing fake news in news content written in the Afaan Oromo language, bidirectional-LSTM beat the other algorithms, namely unidirectional LSTM and GRU. The model is capable of making predictions on our dataset, with an f-1 score of 90%. Finally, python flask API server with spyder IDE was used for the web-based prototype development of the trained Bi-LSTM models for prediction of news.
Diversity and ecology of fungi in the sediments and surface water of brackish and salt marshes
Authors: Thompson Madeleine A. , Pfirrmann Bruce W. , Strosnider William H.J. , Pinckney James L. , Peng Xuefeng 
Published: October 2024

Abstract

Fungi are key drivers of biogeochemical processes, yet marine fungi remain understudied. While various regions of fungal ribosomal RNA have been targeted to study fungal diversity, the ITS region has been the most prevalent region in the literature since 2012. However, ITS metabarcoding has limitations in marine environments, partly due to database biases. We conducted a metabarcoding survey targeting the small and large subunit rRNA genes and the internal transcribed spacer region of fungi (18S, 28S, and ITS2) in the sediment and surface water of salt and brackish marshes in South Carolina, USA. The 28S primer set (LR0R and LF402) excelled at identifying early diverging fungal lineages, including Chytridiomycota, Mucoromycota, Zoopagomycota, and Blastocladiomycota; however, only the ITS2 primer set amplified Cryptomycota and Olpidiomycota. The universal 18S/16S primer set (515F-Y and 926R) identified few fungal taxa because most reads were prokaryotic. The results based on 28S rRNA amplicons revealed that Dikarya fungi dominated salt marshes, whereas early diverging fungi dominated brackish marshes, suggesting Dikarya are more salt-tolerant. Over half of the fungal OTUs identified by the 28S primer set were from early diverging lineages. A FUNGuild analysis found that saprotrophic fungi are the function of most lineages, but in the brackish marsh, saprotrophic fungi from Zoopagomycota, Blastocladiomycota, and Chytridiomycota were more prevalent. Differential abundance analysis revealed that early diverging fungi were key drivers of community composition between the various marsh types. This study advances our understanding of marine fungal diversity by identifying early diverging lineages that were previously overlooked in marine environments. Our study highlights the vast, unexplored fungal diversity in marine environments.
Synthesis of CHA from MFI by three interzeolite transformation strategies and its Application in NH 3 -SCR reaction
Authors: Liu Yufeng , Li Yuping , Chen Ze , Ji Fuchao , Liang Xiaohong , Han Lina , Han Peide 
Published: October 2024

Abstract

CHA Zeolites are currently considered as the most effective catalysts to meet the increasingly stringent emission requirements of diesel vehicles. Herein, the synthesis of SSZ-13 zeolites(CHA topology) using ZSM-5 (MFI topology) with various SiO2/Al2O3 ratios as parent zeolites were investigated in the presence of N,N,N, trimethtyl-1-adamantammonium hydroxide (TMAdaOH). The crystallization processes of three different strategies, that is, high silica ZSM-5 with additional Al source(HSZ + Al), completely zeolite to zeolite(CZTZ) transformation and low silica ZSM-5 with additional Si source(LSZ + Si) were compared. The results show that pure SSZ-13 zeolites with high crystallinity can be synthesized at 160°C for only 6 h by CZTZ strategy. While for the HSZ + Al and LSZ + Si synthesis systems, the complete transformation from MFI to CHA can even be shortened to 4.5 h at 160°C, suggesting the promoting effect of additional Al- or Si- source for MFI-CHA transformation. The rapid MFI-CHA transformation may be related to fast disintegration of parent ZSM-5 under the promotion of TMAdaOH template. Meanwhile, the five-membered rings predominating in the MFI framework rapidly disassembled and rearranged into favorable double six-membered ring and CHA cage composite building units, thus facilitate the rapid formation the CHA framework. Additionally, the resultant samples, after Cu2+ exchange, showed superior catalytic activity and hydrothermal stability for the selective catalytic reduction of NOx with NH3. The operation temperature window (NOx conversion > 90%) of HSZ-4.5 h, CZTZ-6.0 h and LSZ-4.5 h samples were all about 200 ~ 500°C. Among three samples, the HSZ-4.5 h presents best low-temperature catalytic activity, while CZTZ-6.0 h and LSZ-4.5 h samples show more superior hydrothermal stability.
Determination of yield and water use productivity of sesame irrigated with subsurface drip irrigation under different water deficit conditions
Authors: AKIN Filiz , CEMEK Bilal 
Published: October 2024

Abstract

This study investigates the effects of subsurface drip irrigation (SDI) at varying lateral depths (D1: 20 cm, D2: 30 cm, and D3: 40 cm) on evapotranspiration, water use productivity (WUP), and plant water stress index of the Muganlı-57 sesame variety. The experiments were conducted under different irrigation regimes: S1 (full irrigation without water stress), S2 (mild water stress), S3 (moderate water stress), and S4 (severe water stress). The research was conducted in 2019 and 2020 in a clay loam soil under Mediterranean climate conditions, with irrigation water quantities adjusted according to the percentage of plant cover. The average evapotranspiration values recorded for D1 at S1, S2, S3, and S4 were 338.5, 241, 143.5, and 14 mm, respectively; for D2 the values were 263, 188.5, 113.5, and 14 mm; and for D3, they were 257, 184, 111, and 14 mm. In the first year, the highest water use productivity (WUP) was recorded at D3 for S2 (8.4 kg ha⁻¹ mm⁻¹), and in the second year, the highest WUP was again at D3 for S2, measuring 9.0 kg ha⁻¹ mm⁻¹. Over both years, the WUP for S2 at D3 was significantly higher. In contrast, the lowest WUP values were obtained from D1 at S1, with values of 4.2 and 4.6 kg ha⁻¹ mm⁻¹ in the respective years. The highest irrigation water use productivity (IWUP) was achieved at D3 for S2, yielding 12.5 kg ha⁻¹ mm⁻¹ in the first year and 13.1 kg ha⁻¹ mm⁻¹ in the second year. Coversely, the lowest IWUP values were found at D1 for S1 measuring 5.1 and 5.6 kg ha⁻¹ mm⁻¹ in two years. The yield response factor (Ky) for sesame plants was determined to be 1.27 in the first year and 1.21 in the second year. In conclusion, the findings of this study highlight the significant impact of lateral depth in subsurface drip irrigation on evapotranspiration and water use productivity in Muganlı-57 sesame cultivation. The results indicate that optimizing lateral depth, particularly at 40 cm with mild water stress conditions, can enhance water productivity and overall crop performance under Mediterranean climate conditions.
Development and Validation of an AI-based model to predict the assessment outcomes of pre-clinical MBBS/BDS students
Authors: Ehsan Hafiz Rabbi Ul , Khan Rehan Ahmed , Yasmeen Rahila , Arif Marium 
Published: October 2024

Abstract

Accurately predicting student performance is crucial in medical education, especially in the critical pre-clinical years when foundations are laid. This study employed artificial intelligence (AI) to develop a predictive model for assessment outcomes of 4th-year MBBS/BDS students, aiming to provide educators with a tool for proactive intervention. A quantitative, cross-sectional study design was employed, involving 144 students from two institutions in Rawalpindi, Pakistan. A comprehensive dataset of academic and demographic variables was analyzed using various machine learning algorithms, including Random Forest, AdaBoost, Logistic Regression, SVM, and XGBoost. The Random Forest model emerged as the most effective machine learning model while year 2 exam scores and weekly study hours as key predictors of student success. This model allows educators to shift from traditional reactive approaches to a proactive, data-driven approach to student support by providing a framework for AI driven student support system. By identifying at-risk students early, personalized interventions can be implemented, potentially improving overall success rates and nurturing a more supportive learning environment. This study highlights the potential of AI to revolutionize medical education by enabling personalized learning pathways, optimizing resource allocation, and enhancing teaching effectiveness. However, the ethical considerations of AI in education are also addressed to ensure responsible implementation that maximizes student success and creates a more inclusive learning environment.
Drivers of Hygienic Menstrual Practices among Reproductive-Age Women: Evidence from Nepal Demographic Health Survey-2022
Authors: Hasan Nihal , Kumar Pradeep , Rajak Rahul 
Published: October 2024

Abstract

Background: Exclusive use of hygienic methods during menstruation has not received adequate attention in Nepal, with limited research utilizing nationally representative data. Therefore, this study explored the prevalence and factors influencing exclusive hygienic menstrual practices among women of reproductive age in Nepal.
Methods: This study included 13,066 reproductive-age women from the Nepal Demographic and Health Survey (NDHS-2022). A binary logistic regression model was applied to identify significant factors of exclusive use of hygienic methods among women in Nepal. To quantify the proportion of the total variance attributable to differences between communities. The concentration Index (CI) and Concentration curve (CC) were also calculated to measure the socio-economic inequality of exclusive use of hygienic methods among reproductive agewomen.
Results: Only 48% of Nepalese women aged 15- 49 years used exclusively hygienic methods to prevent bloodstains during menstruation. The results of the multivariate model revealed that young women aged 15-24 (AOR=2.51, p<0.001), women with 10 years and above education (AOR=1.98, p<0.001) from the richest wealth quintile (AOR=2.16, p<0.001), never married women (AOR=1.44, p<0.001), owned a smartphone (AOR=1.41, p<0.001) and women with exposure to mass media at least once a week (AOR=1.36, p<0.001) are more likely to use hygienic methods as compared with their counterparts. The results from the concentration curve also demonstrated that exclusive use of hygiene methods among women is concentrated in women from higher economic backgrounds (CI: 0.21). Among the geographical regions of Nepal, the highest inequality was witnessed in Madhesh province (CI: 0.25), followed by Bagmati province (CI: 0.22).
Conclusions: The findings suggest the need for multidimensional interventions and educational programs targeting socioeconomically vulnerable women to address unhygienic menstrual practices. Also, there is a need to educate adult women on biological facts and good hygienic practices, as they can impose cultural taboos and restrictions on the next generation.
Can bear corridors support mammalian biodiversity? A case study on Central Italian Apennines
Authors: Dragonetti Chiara , Ceci Niccolò , Von Kempis Stefan , Trei Jan-Niklas , Cipollone Mario , Visconti Piero , Marco Moreno Di 
Published: October 2024

Abstract

Ecological corridors are essential for maintaining ecosystem functionality, allowing species movement between protected areas. In the Central Italian Apennines, five corridors have been identified to enhance habitat connectivity for the critically endangered Marsican brown bear (Ursus arctos marsicanus). This study focuses on two of these corridors to investigate their support of other mammal species populations. We collected data from camera traps over four months, and applied the Random Encounter Model to estimate the population densities of eight meso- and macro-mammal species. We compared the densities we estimated with those reported in the literature for different locations across Europe. The results indicated higher-than-average densities for several species compared to published data, especially for ungulates. These findings underscore the importance of Marsican bear corridors for a number of other mammals, as they provide important habitats for several of them. Effective management of these corridors, with a focus on reducing human disturbance and improving habitat connectivity, will be critical for the long-term survival of both the Marsican bear and its coexisting species.
Ethnobotanical Study of Medicinal Plants Used to Treat Human and Livestock Ailments in Yeki District and Its Environs, Southwestern Ethiopia
Authors: Melese Daniel , Asnakew Muluye , Getachew Samuel 
Published: October 2024

Abstract

Background Yeki District and its environs have long been inhabited by people who have a long tradition of using medicinal plants to treat human and livestock ailments. Overexploitation of medicinal plants coupled with ever-increasing population growth, deforestation and agricultural land expansion threatens plants in the area. Hence, the study aims to documents indigenous medicinal plant utilization, management and the threats affecting them.
Methodology Both systematic random and purposive sampling were used to select general respondents (130) and key informants (30) respectively. Data were collected through semi-structured interviews, focus group discussion, guided field walk, preference ranking and paired comparison. Standard ethnobotanical tools, including preference ranking, pair-wise comparison, ICF, FL, direct matrix ranking, and the Chi-square test using R software, were applied for analysis. Result A total of 102 medicinal plants, belonging to 57 families were identified. Asteraceae, Fabaceae and Lamiaceaerepresented by eleven and five species each were identified as the leading families. Herbs contributed the most (45.1%) to the growth forms followed by shrubs (21.57%). Out of the total medicinal plants, 58 species (56.86%) were collected from the wild, 24 were obtained from home garden, and 20 species were from both home garden and wild habitats. Fresh leaves of the plants were parts that are used most frequently in the area. The highest ICF value (0.91) was recorded for dermal problem categories. The majority of medicinal plants (65.69%) were used to treat human ailments, whereas 10.78% were used to treat livestock ailments, and 23.53% were used to treat both human and livestock ailments. Agricultural expansion was the major threat to medicinal plants, followed by grazing.
ConclusionThe current study underscores the intricate relationship between the local community and medicinal plants, emphasizing the critical role of biodiversity conservation in sustaining healthcare practices and ecosystem health. The findings contribute to the development of sustainable conservation strategies, the preservation of traditional knowledge, and emphasize the interdependence between human societies and their natural environments. Community-based conservation efforts, involving active participation from local populations and relevant institutions, are vital for the sustainable use and preservation of medicinal plant species and their habitats. Raising public awareness about the sustainable harvesting of exploited medicinal plants and establishing botanical gardens will safeguard these resources, contributing to both environmental protection and socioeconomic development.