bluuebunny/crossref_metadata_2025_split huggingface dataset:
From Scraps to Solutions: Harnessing the Potential of Vegetable and Fruit
Waste in Pharmaceutical Formulations
Authors: Mittal Vishnu , Sharma Anjali 
Published: February 2024

Background::
Food waste is a major worldwide problem due to the increasing population
and imbalances in supply chains. Waste from fruits and vegetables are a substantial proportion of
the overall food waste generated, accounting for approximately 42% of the waste produced. Methane,
a strong greenhouse gas with a significant potential for global warming, is produced when
these waste products are typically dumped in landfills.

Objectives::
The study's goal is to present a thorough overview of the most recent findings and developments
in the use of vegetable and fruit waste for creating therapeutic formulations. Recognizing
the opportunities and challenges in this developing area of study, as well as the promise that
vegetable and fruit waste contains for the creation of environmentally friendly and economically
advantageous pharmaceutical formulations.

Methods::
A comprehensive review of existing literature on the utilization of vegetable and fruit
waste in pharmaceutical formulations was conducted. The review included studies on the chemical
composition and bioactive compounds present in various types of vegetable and fruit waste, their
extraction methods, and their potential applications in pharmaceutical formulations. Additionally,
current waste management practices and challenges associated with waste disposal were also analyzed.

Conclusion::
The review highlights the significant potential of vegetable and fruit waste in the development
of pharmaceutical formulations. Fruit and vegetable waste offer a wide range of bioactive
compounds, such as antioxidants, antimicrobials, and antiinflammatory agents, which could be
utilized in drug formulation. Moreover, this approach can promote environmental sustainability by
reducing waste generation and enhancing waste utilization. Further research and development efforts
should focus on optimizing extraction methods, evaluating the efficacy and safety of wastederived
compounds, and addressing regulatory requirements for integrating vegetable and fruit
waste into pharmaceutical products. Harnessing the potential of vegetable and fruit waste in pharmaceutical
formulations can lead to sustainable advancements in the pharmaceutical industry while
addressing environmental concerns.
Bioactive Compounds from Kinnow Processing Waste and their Associated
Benefits: A Review
Authors: Pulparambil Adethi , Rasane Prasad , Singh Jyoti , Kaur Sawinder , Bakshi Manish , Mahato Dipendra Kumar , Kaur Jaspreet , Gunjal Mahendra , Bhadariya Vishesh 
Published: February 2024

Abstract:
We have explored the expansive possibilities of kinnow peel, a frequently ignored
by-product of the fruit processing industry, in this thorough analysis. The production of kinnow
generates a significant amount of waste, including peel, seeds, and pulp. The disposal of this
waste is a major environmental issue, as it can lead to pollution and greenhouse gas emissions.
Due to the presence of bioactive substances that may be used in a variety of sectors, kinnow
processing waste has the potential to provide a number of advantages. In the culinary, pharmaceutical,
and cosmetic industries, the peel, seeds, and pulp from kinnow can be used as natural
sources of antioxidants, aromatics, pectin, and dietary fibre. Utilizing kinnow waste promotes
eco-innovation, increases sustainability, and aids in waste reduction. The development of a circular
economy can be sped up with more study and commercialization of kinnow waste products.
This analysis emphasises how important it is to understand and utilise the unrealized potential
of agricultural byproducts, like kinnow peel.
Automated Category and Trend Analysis of Scientific Articles on Ophthalmology Using Large Language Models: Development and Usability Study
Authors: Raja Hina , Munawar Asim , Mylonas Nikolaos , Delsoz Mohammad , Madadi Yeganeh , Elahi Muhammad , Hassan Amr , Abu Serhan Hashem , Inam Onur , Hernandez Luis , Chen Hao , Tran Sang , Munir Wuqaas , Abd-Alrazaq Alaa , Yousefi Siamak 
Published: February 2024

Background
In this paper, we present an automated method for article classification, leveraging the power of large language models (LLMs).

Objective
The aim of this study is to evaluate the applicability of various LLMs based on textual content of scientific ophthalmology papers.

Methods
We developed a model based on natural language processing techniques, including advanced LLMs, to process and analyze the textual content of scientific papers. Specifically, we used zero-shot learning LLMs and compared Bidirectional and Auto-Regressive Transformers (BART) and its variants with Bidirectional Encoder Representations from Transformers (BERT) and its variants, such as distilBERT, SciBERT, PubmedBERT, and BioBERT. To evaluate the LLMs, we compiled a data set (retinal diseases [RenD] ) of 1000 ocular disease–related articles, which were expertly annotated by a panel of 6 specialists into 19 distinct categories. In addition to the classification of articles, we also performed analysis on different classified groups to find the patterns and trends in the field.

Results
The classification results demonstrate the effectiveness of LLMs in categorizing a large number of ophthalmology papers without human intervention. The model achieved a mean accuracy of 0.86 and a mean F1-score of 0.85 based on the RenD data set.

Conclusions
The proposed framework achieves notable improvements in both accuracy and efficiency. Its application in the domain of ophthalmology showcases its potential for knowledge organization and retrieval. We performed a trend analysis that enables researchers and clinicians to easily categorize and retrieve relevant papers, saving time and effort in literature review and information gathering as well as identification of emerging scientific trends within different disciplines. Moreover, the extendibility of the model to other scientific fields broadens its impact in facilitating research and trend analysis across diverse disciplines.
Beekeepers’ resilience as a key to ecosystem sustainability, empirical evidence from Hungary
Authors: Mucha László , Oravecz Titanilla , Horská Elena , Illés Csaba Bálint 
Published: February 2024

Abstract
The beekeeping sector plays an important role in maintaining biodiversity and the ecosystem, in addition to its production function. The European beekeeping sector is facing a number of constraints that make it difficult to operate, and the Covid-19 pandemic has posed new challenges for beekeepers. The purpose of the study is to examine the resilience of beekeeping businesses to the most important problems affecting beekeepers and the Covid-19 pandemic. The research analyses the role of marketing and profitability and how they influence the resilience. Variables obtained from online questioning of a representative sample of Hungarian beekeepers (N = 297). Cluster analysis was used to validate the results. Using a Two-step clustering model, three clusters of beekeepers were identified: a non-resilient; a resilient, but not proactive and not very profitable and a resilient, proactive and profitable cluster. According to the research, the resilience of beekeepers is shaped by several factors. Well-trained, long-established beekeepers who seek to differentiate their products from their competitors’ overcome the difficulties caused by the pandemic and other beekeeping problems much more easily. Very important factors resulting in remarkable business resilience are the number of used subsidies and the number of cooperations.
Machine Learning based Estimator for Ground Shaking Maps in South Iceland Seismic Zone (SISZ)
Authors: Monterrubio-Velasco Marisol , Blanco-Prieto Rut , Callaghan Scott , Modesto David , Puente Josep de la 
Published: February 2024

Pre-print:
Ground Motion Shaking Predictions Based on Machine Learning and
Physics-based Simulations

Earthquakes constitute a major threat to human lives and infrastructure,
hence it is crucial to quickly assess the intensity of ground motions
after a major seismic event. Rapid estimation of the intensity of ground
vibrations is essential to assess the impact after a major earthquake
occurs.
The Machine Learning Estimator for Ground Shaking Maps (MLESmap)
introduces an innovative approach that harnesses the predictive
capabilities of Machine Learning (ML) algorithms, utilizing high-quality
physics-based seismic scenarios. MLESmap aims to provide ground
intensity measures within seconds following an earthquake. The inferred
information can produce shaking maps of the ground providing
quasi-real-time affectation information to help us explore uncertainties
quickly and reliably.
To develop the MLESmap technology, we used ground-motion simulations
generated by the CyberShake platform. Originally designed for Southern
California, this physics-based Probabilistic Seismic Hazard Methodology
was migrated to the South Iceland Seismic Zone recently.
Our methodology follows a three-step process: simulation, training, and
deployment. By employing this approach, we can generate the next
generation of ground shake maps, incorporating essential physical
information derived from wave propagation, such as directivity,
topography, and site effects. Remarkably, the evaluation times for
MLESmap are comparable to empirical Ground Motion Models, whereas the
predictive capacity of the former is superior for the Mw >
5 earthquakes.
In this work, we present the application of the MLESmap methodology in
South West Iceland.
ASPETAR – Women’s Football (Summaries)
Authors:   Revista de Medicina Desportiva informa, Ribeiro Basil 
Published: February 2024

Summaries of: 1.	“Female athlete health in women’s football” 2.	“ACL rehabilitation in elite female footballers” 3.	“Groin Pain in women’s football” 4.	“Embracing women’s football growth at your club”.
PENGARUH SUPLEMENTASI MINERAL MIKRO ORGANIK TERHADAP JUMLAH ERITROSIT, HEMOGLOBIN, DAN HEMATOKRIT KAMBING PERAH JAWARANDU
Authors: Ekasari Yustia , Muhtarudin Muhtarudin , Siswanto Siswanto , Suharyati Sri 
Published: February 2024

Tujuan penelitian ini adalah untuk mengetahui jumlah eritrosit, kadar hemoglobin, dan nilai hematokrit kambing perah Jawarandu yang diberi suplementasi mineral mikro organik dalam ransum di Mulia Farm, Negrisakti, Kabupaten Pesawaran Lampung. Penelitian ini merupakan penelitian eksperimental dengan menggunakan Rancangan Acak Kelompok (RAK) yang terdiri dari 4 perlakuan yaitu R0: Ransum Basal, R1: Ransum Basal + (Zn-Lysinat 20 ppm, Cu-Lysinat 5 ppm), R2: Ransum Basal + (Zn-Lysinat 40 ppm, Cu-Lysinat 10 ppm), R3: Ransum Basal + (Zn-Lysinat 60 ppm, Cu-Lysinat 15 ppm) setiap kelompok berisi 4 ekor kambing perah Jawarandu dengan 3 ulangan. Pemeriksaan sampel darah dilakukan di Laboratorium, Balai Besar Laboratorium Kesehatan, Palembang (BBLK Palembang) mengguakan metode B. Cell Counter dan Manual. Data yang diperoleh ditabulasikan dan kemudian dianalisis dengan analisis ragam (ANOVA) dengan taraf 5%. Hasil analisis menunjukkan bahwa suplementasi mineral mikro organik dalam pakan tidak memberikan pengaruh yang nyata (P>0,05) terhadap jumlah eritrosit, hemoglobin dan hematokrit kambing perah Jawarandu. Dari hasil analisis statistik sampel darah kambing perah Jawarandu didapatkan rata-rata jumlah eritrosit pada perlakuan (R0) 2,41±0,52 x 106/μL; (R1) 1,63±0,19 x 106/μL; (R2) 2,19±0,31 x 106/μL ; (R3) 1,92±0,28 x 106/μL. Rata-rata kadar hemoglobin pada perlakuan (R0) 9,37±0,05 g/dL ; (R1) 8,23±0,58 g/dL ; (R2) 8,5±0,87 g/dL ; (R3) 7,63±2,11 g/dL. kemudian rata-rata nilai hematokrit (±SD) pada perlakuan (R0) 9,00±2% Vol; (R1) 5,67±0,58% Vol; (R2) 8,33±0,58% Vol; (R3) 6,67±1,15 % Vol. Dari hasil penelitian disimpulkan bahwa jumlah eritrosit, hemoglobin dan hematokrit pada kambing perah Jawarandu yang diberi suplementasi mineral mikro organik dalam ransum masih berada pada kisaran normal meskipun mendekati batas minimal.
EFEKTIVITAS SUPLEMENTASI JINTAN HITAM (Nigella sativa) TERHADAP TITER ANTIBODI AVIAN INFLUENZA (AI) DAN NEWCASTLE DISEASE (ND) PADA AYAM ULU BETINA
Authors: Habiahan Renta Enjelina , Siswanto Siswanto , Santosa Purnama Edy , Hartono Madi 
Published: February 2024

Penelitian ini bertujuan untuk mengetahui efektivitas suplementasi Jintan Hitam (Nigella sativa) yang ditambahkan dalam pakan komersil terhadap titer antibodi Avian Influenza (AI) dan Newcastle Disease (ND) pada ayam Unggas Lestari Unggul (ULU) betina. Penelitian ini dilaksanakan pada Desember 2022 hingga Februari 2023 di Kandang Laboratorium Lapang Terpadu Fakultas Pertanian, Universitas Lampung dan Laboratorium Medilab PT. Medion Lampung. Bahan yang digunakan terdiri dari Day Old Chick (DOC) ayam ULU betina, ekstrak Jintan Hitam, vaksin dan lainnya. Penelitian ini dilaksanakan secara eksperimental terdiri dari 4 perlakuan dan 3 ulangan yaitu P0 sebagai kontrol, P1 diberi ekstrak Jintan Hitam sebanyak 36 mg/kg BB/hari; P2 sebanyak 72 mg/kg BB/hari; dan P3 sebanyak144 mg/kg BB/hari. Data pengamatan yang telah diperoleh disajikan dalam bentuk tabulasi dan histogram kemudian dianalisis secara deskriptif. Hasil penelitian ini menunjukkan nilai rata-rata titer antibodi Avian Influenza tertinggi yaitu pada P3 (log 255,22) dan titer antibodi Newcastle Disease tertinggi pada P3 (log 743,11).
A Discussion About the Health Work Process
Authors: Netto Nelson de Franceschi , Campos Tiago Aparecido de Melo , Lopes Gabriel César Dias 
Published: February 2024

Objective: The objective of this bibliographical research is to investigate the health work process, with an emphasis on caring acts, aiming to understand their significant contribution to the formation of protagonists in the construction of a fairer and more humanized health system.

Methods: The bases of this research consisted of the analysis of legal documents from the Ministry of Health and public policies aimed at collective health. The research focused on issues related to the health work process. Data collection involved bibliographical surveys in magazines, scientific articles and books that address the topic investigated, including reference works such as those by KUMAR et al. (2018), PENNISI et al. (2020) and DAI et al. (2016).

Results: The research results indicate that Primary Health Care workers often face stressful conditions in the work environment. In this context, quality of life is considered a multidimensional construct, influenced by several aspects, such as working conditions, personal life, physical and psychological health, social relationships and living environment.

Conclusion: Given the evidence presented, it is possible to conclude that an in-depth understanding of the health work process, with a focus on caring acts, is essential to promote a healthier work environment and contribute to the construction of a fairer and more humanized health system . The constant exposure of Primary Health Care professionals to stressful conditions highlights the importance of strategies that aim to improve quality of life, considering the various factors that influence this multidimensional construct.
PENGARUH HERDING BEHAVIOR, LOSS AVERSION, DAN FINANCIAL LITERACY TERHADAP INVESTMENT DECISION
Authors: Limarus Victor Hofa , Pamungkas Ary 
Published: February 2024

Tujuan dari penelitian ini adalah untuk mengetahui pengaruh Herding Behavior, Loss Aversion, dan Financial Literacy terhadap Investment Decision. Sampel penelitian ini sebanyak 210 responden Gen Z yang tinggal di Jakarta. Pengambilan sampel dilakukan melalui penyebaran kuesioner secara online melalui Google form, dengan menggunakan teknik convenience sampling dan teknik analisis data PLS-SEM yang diolah dengan Smart-PLS Software versi 4. Hasil penelitian ini menunjukkan bahwa Herding Behavior, Loss Aversion, dan Financial Literacy berpengaruh positif terhadap Investment Decision. Investor yang memiliki tingkat Herding Behavior yang tinggi akan cenderung mengikuti investor lain yang lebih berpengalaman dan mempunyai reputasi yang baik dalam membuat keputusan investasi. Semakin tinggi tingkat Loss Aversion pada investor maka investor akan lebih berhati-hati dan berusaha untuk menghindari kerugian dalam membuat keputusan investasi. Semakin tinggi tingkat Financial Literacy investor maka semakin tinggi pemahaman investor tentang konsep dasar keuangan, sehingga investor akan dapat membuat keputusan investasi yang baik.

The purpose of this study is to determine the influence of Herding Behavior, Loss Aversion, and Financial Literacy on Investment Decision. The sample for this study was 210 Gen Z respondents who lived in Jakarta. Sampling was carried out by distributing questionnaires online via Google form, using convenience sampling techniques and PLS-SEM data analysis techniques processed with Smart-PLS Software version 4. The results of this study show that Herding Behavior, Loss Aversion, and Financial Literacy have a positive effect on Investment Decision. Investors who have a high level of Herding Behavior will tend to follow other investors who are more experienced and have a good reputation in making investment decisions. The higher the level of Loss Aversion in investors, the more careful investors will be and try to avoid losses in making investment decisions. The higher the investor's level of Financial Literacy, the higher the investor's understanding of basic financial concepts, so that investors will be able to make good investment decisions.
PERAN CORPORATE IMAGE DAN TRUST DALAM MEMEDIASI PENGARUH SOCIAL MEDIA INFLUENCER TERHADAP BEHAVIOURAL INTENTION E-PAYMENT
Authors: Ryan  , Keni Keni 
Published: February 2024

Penelitian ini bertujuan untuk menguji peran dari Corporate Image dan Trust dalam memediasi pengaruh Social Media Influencer terhadap Behavioural Intention E-Payment OVO di Jakarta. Populasi dalam penelitian ini adalah seluruh penguna E-Payment OVO di Jakarta. Penelitian ini menggunakan 193 pengguna E-Payment OVO sebagai responden. Penelitian ini menggunakan metode Partial Least Square-Strustural Equation Modelling (PLS-SEM) sebagai metode teknik analisis data. Penelitian ini menunjukkan bahwa Social Media Influencer, Corporate Image, dan Trust berpengaruh secara signifikan dan positif terhadap Behavioural Intention, lalu Social Media Influencer memiliki pengaruh signifikan dan positif terhadap Corporate Image dan Trust. Social Media Influencer berpengaruh secara tidak langsung dan signifikan positif terhadap Behavioural Intention melalui Corporate Image dan Trust sebagai variabel mediasi.

This study aims to examine the role of Corporate Image and Trust in mediating the effect of Social Media Influencer on Behavioural Intention E-Payment OVO in Jakarta. The population of this study is all users of E-Payment OVO in Jakarta. This study employs 193 users as the respondents. The data collection has been conducted by using a convenience sampling method. This research analyses the data by using the Structural Equation Modelling (SEM) with Partial Least Square (PLS). The research showed that Social Media Influencer, Corporate Image, and Trust had a positive and significant impact on Behavioural Intention, then Social Media Influencer had a positive and significant impact on Corporate Image and Trust. Social Media Influencer has a significant indirect impact on Behavioural Intention through Corporate Image and Trust as an mediating variable.
Freedom of choice and network "echo effects" of information consumption
Authors: Leontyev Gleb Dmitrievich , Leontieva Ludmila Stanislavovna 
Published: February 2024

The mechanisms of media personalization and separation in network communication on the principle of like-mindedness stimulate the formation of "echo chambers" and "filter bubbles". The social network phenomenon indicated by these metaphors is the subject of research, and the concepts themselves are considered as close, but not identical. The purpose of the study is to identify factors affecting the effectiveness of filtering algorithms, the user's ability to make informed choices and self–organization in the process of information consumption. The analysis of the causes and consequences of selective strategies of online information consumption is carried out on the basis of the communicative - activity approach, the theory of virtual reality Zh. Baudrillard, concepts of digital media by K. Sunstein, E. Pariser and R. Fletcher. The results of foreign and domestic studies of communication practices on various social platforms are used as an empirical basis. The research approaches presented in the scientific literature allow us to focus on the technological and logical-semantic perspective of the analysis of stable forms of network communication. According to the authors, the interdependence of filtering algorithms and value dominants of information consumption leaves the user with a chance to independently choose a "consumer basket". The duality in obtaining personalized content is emphasized: on the one hand, it is convenience, saving effort, on the other - the one-dimensionality of the world picture in the information bubble. Based on this, freedom of choice is characterized as the right to active choice and the right not to choose, consciously delegating it to neural network filters. In conclusion, the authors identified internal and external network factors for reducing the effectiveness of filtering algorithms: the interpretation of user behavior by artificial intelligence; the functioning of rational confrontational communication; the opportunistic conceptualization of echo effects; the availability of means of conscious counteraction. Incentives for reasonable information consumption, technological and cognitive ways of protecting and rationalizing user behavior are highlighted.