bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cell-type-specific response in host plants to the co-infection by sweet potato viruses
Authors: Wang Hongxia , Lyu Ruiqing , Fan Weijuan , Wang Yuqin , Pattanaik Sitakanta , Zhou Xuguo , Yu Yang , Liu Yongliang , Yang Jun , Li Yongqing , Yuan Ling 
Published: September 2024

Abstract

Host-virus interactions determine infection outcomes, with cellular heterogeneity playing a critical role in the dynamic interplay between host immune responses and viral evasion strategies. While animal and plant viruses use different mechanisms for cell entry, viral tropism is essential for pathogenesis across both kingdoms. To examine this overarching hypothesis, we studied sweet potato virus disease, the most devastating disease affecting sweet potato (Ipomoea batatas), which involves synergistic co-infection by the aphid-transmitted sweet potato feathery mottle virus and the whitefly-transmitted sweet potato leaf curl virus. By integrating single-cell RNA-Seq profiling with phenotypic assessments, we mapped virus specificity to a particular cell type within the host plant. As a result, we: 1) generated a comprehensive cellular atlas of sweet potato leaves, documenting the transcriptional response of 38,526 cells during co-infection; 2) traced virus-infected cells by examining viral genomic reads in each cell; 3) identified a tissue tropism in mesophyll, suggesting that selectively targeting cells with highly active cellular machinery is a common theme during infection by both plant and animal viruses; and finally 4) identified and characterized VIPE1, an AP2/ERF family transcription factor that contributes to viral resistance in sweet potato. These findings highlight the differential susceptibility and immune responses at both host and virus levels, underscoring the importance of understanding specific cellular and molecular features in developing targeted strategies for managing plant viruses.
Agronomy, not genetics nor climate change, explains wheat yield plateaus in Northwest Europe
Authors: Silva Joao , Rijk Bert , Berghuijs Herman , de Wit Allard , Reidsma Pytrik , Ittersum Martin van 
Published: September 2024

Abstract

Northwest Europe experienced considerable increases in wheat yield until the mid-1990s, but no further progress was reported since then. Estimating the relative contributions of improved genetics, historical climate change, and agronomic management to this yield plateau is required to understand if yield increases are possible in future. Analysis of high-quality experimental data (1972-2013) revealed yield gains due to improved genetics of 90 kg ha-1 yr-1. Thus far, yield gains due to historical climate change (1972-2016) of 55 kg ha-1 yr-1 were estimated using a well-validated crop model. Given the absence of genetic and climatic yield ceilings, we conclude agronomic management is responsible for the yield plateau in Northwest Europe, constraining yield progress by 100 kg ha-1 yr-1 or more. Breaking the wheat yield plateau in Northwest Europe will require incentives for farmers to prioritize investments in wheat production over other, more profitable, crops.
Comparison of Algorithms for the Recognition of ChatGPT Paraphrased Texts
Authors: Kartelj Aleksandar , Mladenovic Miljana , Stankovic Stasa Vujicic 
Published: September 2024

Abstract

The rapid development of artificial intelligence, especially chatbots, is leading to new forms of plagiarism that are difficult to detect using existing methods. Paraphrasing tools make this problem even more difficult and are incredible in minor languages with inadequate resources and tools. This study explores strategies that can help detect plagiarism generated by ChatGPT 4.0 and altered by paraphrasing tools. We propose two new datasets consisting of abstracts of doctoral theses in English and Serbian. Both datasets were subjected to ChatGPT paraphrasing, which allowed us to form two classes of texts: human-generated and AI-generated, i.e. AI-paraphrased. We then perform a comprehensive comparison of 19 widely used classification algorithms based on two feature sets, namely word unigrams and character multigrams. In addition, we compare these to the results of a commercially available pre-trained ChatGPT content detector, ZeroGPT. The results on the English corpus turn out to be very accurate, achieving an accuracy of 95% or more. In contrast, the results on the Serbian corpus were less accurate, achieving an accuracy of just over 85%. We attribute this difference to the lower ability of ChatGPT to parahprase in minor languages such as Serbian.
Introduction of Nicotine Analogue-Containing Oral Pouch Products in the United States
Authors: Jordt Sven E. , Jabba Sairam V. 
Published: September 2024

Abstract

Background: In 2023, 6-methyl nicotine (6MN), a synthetic nicotine analogue, was introduced in US-marketed electronic cigarette products advertised as exempt from regulation. It is unknown whether the use of 6MN has spread to the oral nicotine pouch product category that has become increasingly popular.
Methods: Industry reports and the USPTO database were searched for informationon 6-methyl nicotine products. The search terms “Metatine”, “Nixotine”, “Imotine” and “pouches” were shortlisted and used to identify US-marketed pouch products. Ingredient contents were compared to popular products, and safety warnings and regulatory statements assessed in context with US state and federal regulations.
Results: Two US-based brands, "MG" and "Hippotine" pouches, were identified in August 2024, advertised to contain "Imotine"-trademarked 6MN. MG Pouches are marketed in four youth-appealing flavors. "Hippotine"-branded pouches are marketed in two flavors. 6MN contents ranged between 8mg - 25mg with almost identical ingredient lists otherwise. Products list extensive addiction and health warnings, including warnings not to operate vehicles. Vendors state that these are not a tobacco product, implicating that federal and state tobacco regulations do not apply.
Conclusions:
The spread of nicotine analogues to additional product categories such as oral pouches is concerning, especially given the high 6MN contents that exceed nicotine contents in popular US-marketed oral nicotine pouch products. Legislators and regulators need to provide certainty about the regulatory status of nicotine analogues to prevent further erosion of tobacco flavor bans and other regulations.
Impact of land cover changes on land surface temperature variations in Adama City, Ethiopia
Authors: Roba Zenebe Reta , Aiymeku Tigist Girum , Gurmessa Tekalign Tadesse 
Published: September 2024

ABSTRACT

Land surface temperature (LST) is becoming a serious environmental issue, since it is an essential controller of city climate. Currently, addressing this challenge in urban planning has gained worldwide importance. The study aims to analyze the effect of land cover dynamics on LST using geographic information system and remote sensing techniques. In this study, Landsat 7 ETM+ (2002) and Landsat 8 TIRS (2022) data were used. The LST was retrieved from Landsat datasets. The correlation analyses were conducted on LST, normalized difference vegetation index (NDVI), and normalized difference built-up index (NDBI). The findings suggested that there was a negative correlation between LST and the NDVI, while a positive correlation existed with the NDBI. Moreover, NDBI was found to be a better predictor of LST than NDVI. Additionally, it was revealed that the proportion of dense and sparse vegetation cover was reduced from 24.14 km2 (17.47%) in 2002 to 18.17 km2 (13.15%) in 2022. Similarly, the average LST increased from 28.25 to 31.78°C. This indicated that the rapid growth of urban development was the primary factor behind the rise in LST. Therefore, it was deemed crucial to create a smart urban land use plan to mitigate the impacts of microclimate change.
Conjunctive use in water resource management: current trends and future directions
Authors: sekar Aakash , Valliammai A. , Nagarajan M. , Sivakumar S. D. , Baskar M. , Sujitha E. 
Published: September 2024

ABSTRACT

Water scarcity and the nееd for sustainable water management practices are pressing global challenges. Conjunctive use, a united management of both surface water and groundwater resources, is being progressively considered as one of the fundamental approaches to solving these issues. This paper gives a detailed overview of the conjunctive use in water resource management considering the present tendencies and directions of development in this sphere. The present study relies on a diverse variety of literature resources which integrate the new techniques, equipment, and policies in respect to conjunctive use. It covers important issues like hydrological modeling, innovative groundwater recharge methods, and integrating conjunctive use techniques into adaptive management system. Moreover, the review also evaluates the roles of different parties, such as government agencies, communities, and industries, involved in the conjunctive use approaches and the promotion of collaborative governance mechanisms. This review identifies that while the conjunctive use approaches are very promising for solutions to water security, fragmented management and poor data integration constrain them. The paper conducts an all-embracing analysis that pinpoints the upcoming problems and solutions, and discovers the need for extensive research and innovation to make the conjunctive water resources management more efficient and resilient.
Network Pharmacology and Validation of the Combinative Therapy of
Ligusticum striatum DC. and Borneolum against Cerebral Ischemia
Authors: Ruan Ming , Lv Gaohong , Wang Xueqing , Deng Fengjiao , Xia Tianya , Yu Bin , Liu Shengjin 
Published: September 2024

Background:
Ligusticum striatum DC. (LDC) is often prescribed for Cerebral Ischemia (CI) and is commonly combined with Borneolum (BO) to enhance therapeutic outcomes.
However, its specific active ingredients and underlying mechanisms remain unclear.

Objective:
This study aimed to identify the active ingredients and mechanisms of LDC and BO
combination therapy against CI using network pharmacology, molecular docking, and in vivo
experiments.

Methods:
Potential active ingredients and targets were sourced from relevant databases, and a
drug-component-target-disease network was constructed to pinpoint key ingredients. Subsequently, a protein-protein interaction analysis was conducted to confirm the key targets. Following enrichment analyses of Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG), molecular docking was employed to evaluate binding energies. Finally, the
therapeutic effects and mechanisms of the combination against CI were validated through in vivo
experiments using male ICR mice

Results:
Venn analysis identified a total of 41 components and 292 potential targets. The drugcomponent-target-disease network revealed that the key components in LDC were palmitic acid,
tetramethylpyrazine, and (Z)-ligustilide, while those in BO were (+)-borneol, β-elemene, and (-)-
borneol. The PPI analysis highlighted seven crucial targets. Docking results confirmed a stable
affinity between these components and their targets. KEGG enrichment analysis indicated that
the mechanism involved the PI3K/AKT signaling pathway. Subsequently, in vivo experiments
confirmed that the combination ameliorated abnormal hippocampus morphology and reduced the
release of inflammatory factors through the activation of the PI3K/AKT signaling pathway

Conclusion:
The combination of LDC and BO markedly improved CI and inhibited inflammation response via activating the PI3K/AKT pathway
Innovative Bedaquiline-Based Delivery Systems for Multidrug-Resistant Tuberculosis Treatment
Authors: Ahmad Asad , Akhtar Juber , Ahmad Mohammad , Islam Anas , Badruddeen  , Khan Mohammad Irfan , Khan Mohsin Vahid , Owais Mohammad 
Published: September 2024

Abstract:
The increasing incidence of multidrug-resistant tuberculosis (MDR-TB) is one of the most challenging tasks in tuberculosis treatment. Conventional TB treatment regimens have proven ineffective in treating MDR-TB, thus demanding the development of new drugs followed by delivery systems. Bedaquiline, a novel anti-TB drug, has been reported to inhibit the ATP synthase required for the growth and replication of TB bacteria. Bedaquiline is able to target the persistent or latent form of TB, which remains difficult to treat with conventional drugs. This makes bedaquiline an important drug in the fight against MDR-TB. The drug has been approved by the US FDA as well as European Medicines Agency and is now widely used as part of combination therapy for the treatment of MDR-TB. Bedaquiline and its ad-vanced drug delivery system play a key role in tackling MDR-TB, providing a much-needed boost to control and eventually eliminate the disease. However, the cost of the drug remains a concern, and efforts are underway to make bedaquiline more accessible and affordable to patients in resource-limited settings. Nevertheless, the development of bedaquiline nanofor-mulations represents a significant step forward in the fight against TB and offers hope to millions of patients across the globe.
Nanoemulgel: A Comprehensive Review of Formulation Strategies, Characterization, Patents and Applications
Authors: Ansari Afshan , Verma Madhu , Majhi Sagarika 
Published: September 2024

Background:
Delivering hydrophobic or poorly soluble drugs has become increasingly
challenging, with issues like stability and bioavailability complicating the process. Among various
strategies devised to address these problems, nanoemulgels have proven effective. Nanoemulgels
combine a gel base and an emulsion at the nanoscale, making them excellent for drug delivery. The
nanoemulsion component protects the active ingredient from degradative reactions like hydrolysis
and enzymatic degradation. Meanwhile, the gel base enhances the emulsion's thermodynamic stability
by increasing the viscosity of the aqueous phase and reducing surface and interfacial tension.

Objective:
The primary objective of this review was to explore nanoemulgels as a drug delivery system
in the pharmaceutical industry. It delves into the advantages and applications of nanoemulgels
in various medical fields, compares them with conventional emulgel, and examines formulation
strategies, preparation methods, patent trends, future prospects, and evaluation methods in detail.

Methods:
An exhaustive literature survey was conducted keeping in view the various aspects of
nanoemulgel. Information from various resources, such as books, review articles, scientific reports,
research articles, and patents, were searched, read, analyzed, and summarized.

Conclusion:
This review article thoroughly examines nanoemulgels, discussing their formulation
strategies, characterization techniques, and applications in various fields. It highlights their benefits,
such as enhanced drug solubility, controlled release, improved stability, and targeted delivery. The
article also covers patents related to nanoemulgel technology and explores its future prospects, emphasizing
potential applications in pharmaceuticals, cosmetics, dermatology, and other industries.
Deep Ensemble Learning using Transfer Learning for Food Classification
Authors: Nijhawan Rahul , Koundal Deepika , Kaur Anoop , Thukral Anshika , Verma Amit 
Published: September 2024

Aim:
Deep learning models, such as deep convolutional neural networks (CNNs),
have undergone extensive scrutiny in the context of food classification because of their exceptional
feature extraction capabilities.

Background:
Similarly, ensemble-based learning approaches have exhibited great potential for
achieving effective supervised classification.

Objective:
We suggest an innovative approach to improve the effectiveness of deep learningbased
food classification.

Method:
Our proposal involves a novel deep learning ensemble framework that draws inspiration
from the fusion of deep learning models with ensemble learning based on random subspaces.
The random subspaces play a role in diversifying the ensemble system in a straightforward
but impactful way. Moreover, to enhance the classification accuracy even more, we explore
transfer learning, employing the migration of acquired weights from a single classifier to
another (namely, CNNs). This approach expedites the process of learning.

Result:
Results from experiments conducted using well-established food datasets illustrate that
the suggested deep learning ensemble system delivers competitive performance compared to
state-of-the-art techniques, as evidenced by its classification accuracy.

Conclusion:
The amalgamation of deep learning and ensemble learning holds substantial
promise for dependable food categorization.
Leading-Edge Sentiment Analysis: A Survey of Application Context, Challenges and Advanced Techniques
Authors: Wadhvani Barkha , Mehta Jigesh , Singh Kaushal , Oza Ankit , Kumar Sandeep , Gupta Sarita , Sobti Rajeev 
Published: September 2024

Background:
Data is rapidly expanding in today's digital age. The reason for the
expansion of data is due i to social media sites. The Internet produces an enormous quantity of
unstructured data every second. Numerous users have many opinions and reviews to impart on
everything from items and services to common pastimes. Opinions, feelings, attitudes, impressions,
etc., concerning subjects, products, and services are collected and analyzed through a
method called sentiment analysis. Web-based networking mediums that rely on textual communication
can be overwhelming. Understanding human psychology requires the real-time
processing of data using techniques like sentiment analysis.

Aim:
This study provides a thorough examination of the differences between methods of sentiment
analysis, as well as its obstacles and emerging trends. The paper exemplifies the analysis's
practical uses, examines its challenges, and outlines common methods of conducting it.

Objective:
The objective of the current overview is to better understand the market, gauge public
opinion, and make strategic decisions. In addition, enterprises, governments, and scholars
can all benefit from conducting a sentiment analysis.

Methods:
In this research, we review and categorize the most widely applied methods of deep
learning and machine learning for analyzing sentiment. From the paper, we learn that which
sentiment analysis technique is the best depends on the data at hand. When confronted with
large amounts of data and a lengthy procedure, traditional machine learning-based algorithms
flop. The ability to train deep learning models to learn more features using larger datasets is
why they currently beat machine learning methodologies. Considerations include textual and
temporal context, as well as data volume.

Results:
Regardless of the fact that the English language has traditionally been the focus of research
in this field, other spoken languages have recently attracted a growing amount of interest.
The lack of resources for these languages continues to present numerous obstacles. Consequently,
it can be an intriguing line of future effort to tackle other natural languages outside English by
generating beneficial resources like building databases and addressing the problems with Natural
language processing that have been stated in the context of sentiment examination.

Conclusion:
The difficulties of sentiment analysis are examined as well, with the goal of illuminating
potential solutions.
Your Tax Dollars at Work: The Effectiveness of the Public Service Loan Forgiveness Program
Authors: Cather William D. , Harris Erica E. , Romney Miles A. 
Published: September 2024

ABSTRACT
As of March 2024, the Federal government has forgiven $62.5 billion of Federal student loans for over 871,000 individuals—roughly $72,000 per borrower—enrolled in the Public Service Loan Forgiveness (PSLF) program. We study the impact of the PSLF program on nonprofit effectiveness. We find the program ratio, defined as the proportion of dollars directed toward mission fulfillment, increases after PSLF implementation. Additionally, we document program ratios increase because of newly hired program employees, consistent with nonprofits expanding their workforce to provide more mission related services. Finally, we estimate the incremental program employee output attributable to the PSLF program, finding it exceeds the average loan forgiveness by the Federal government in 94 percent of nonprofits in our sample. Overall, we provide evidence consistent with the PSLF program promoting nonprofit employment and increasing organizational effectiveness across the nonprofit sector.
Data Availability: Data are available from the public sources cited in the text.
Peningkatan Kemampuan Bahasa Anak Menggunakan Media Boneka Tangan Di PAUD Kasiah Bundo Padang Selatan
Authors: Prillishyntia Prillishyntia , Rakimahwati Rakimahwati 
Published: September 2024

Berdasarkan permasalahan yang peneliti temukan peneliti melihat ada beberapa permasalahan yang peneliti temukan yaitu, kemampuan bahasa eksperesif anak yang masih kurang dalam menggunakan media boneka tangan, anak kurang tertarik karena metode yang digunakan kurang menarik, dan sebagian anak tidak bisa mengungkapkan kalimat kepada guru dan teman. Hal tersebut dapat dilihat dari tidak beraninya anak untuk bertanya dan cenderung hanya duduk pasif dan diam saja saat proses pembelajaran di dalam kelas. Kemudian peneliti melihat kurangnya media yang tersedia di sekolah tersebut, dan media yang sudah adapun tidak di fasilitasi untuk anak dengan baik, akibatnya anak kurang tertarik dalam pembelajaran, sehingga anak tidak mampu mendorong anak untuk berbicara.Penelitian ini memakai metode tindakan kelas. Subjek penelitian ini yaitu peserta didik yang berada di paud kasiah bundo padang selatan yang berjumlah 10 orang anak. Pengumpulan data penelitian melalui pengamatan kepada objek yang diteliti. Penelitian tindakan kelas ini mempunyai campuran data kuantitatif dan kualitatif.Hasil observasi pada siklus I didapat kemampuan anak dalam mengungkapkan kata masih ada yang tergolong kategori baik, yang dibuktikan pada nilai rata-rata siklus I yang menyentuh 62%. Dalam siklus I masih ada beberapa anak yang belum mampu menjalankan indikator penilaian dengan baik alhasil bisa dinyatakan pembelajaran yang dijalankan di siklus I belum mampu untuk mengembangkan kemampuan anak dalam berbahasa. Nilai persentase rata-rata anak sudah termasuk dalam kategori baik dan mencapai target. Sementara itu, pada siklus II kegiatan pembelajaran yang dilakukan terjadi peningkatan yang signifikan di bandingkan terhadap siklus I. Anak-anak sudah mulai beradaptasi dan terbiasa dalam kegiatan bercerita memakai boneka tangan yang diterapkan oleh guru. Sesuai dengan hasil observasi dalam siklus II nilai rata-rata diperoleh yaitu 83%. Hal ini didapat pada persentase rata-rata dari siklus II dengan pencapaian kriteria keberhasilan penelitian sebesar 75%.