bluuebunny/crossref_metadata_2025_split huggingface dataset:
Perilaku dan Pengetahuan Remaja Indonesia tentang Merokok
Authors: Ade Ismayanti Syavina , Auliavika Khabibah Shela , Annisa Haq Tashaufa , Salsabilla Sofiah , Athilla Rahman Rafiif , Vanessa Hartono Thalia , Salzabilla Tasya , Wachidah Nur , Yuastita Tangnalloi Tresia , Yuda Ana 
Published: June 2024

Rokok dapat diartikan sebagai produk tembakau yang dibakar, berasal dari tanaman Nicotiana tabacum. Asap rokok mengandung nikotin, tar, dan bahan tambahan lainnya. Dalam satu batang rokok terkandung sekitar 4000 jenis senyawa kimia berbahaya, di antaranya 400 memiliki efek racun dan 43 lainnya dapat menyebabkan kanker. Alasan remaja mencoba merokok seringkali dipengaruhi oleh pergaulan teman sebaya dan paparan terhadap iklan di jalanan, televisi, atau internet. Penelitian ini dilakukan dengan tujuan untuk mengetahui pengetahuan serta perilaku remaja Indonesia terkait merokok. Desain penelitian yaitu deskriptif kuantitatif, dengan metode observasional, dan cross-sectional. Parameter yang digunakan pada penelitian ini berfokus pada perilaku dan pengetahuan terhadap kebiasaan merokok pada remaja. Dari 342 responden diantaranya 52,6% merupakan laki-laki dan 47,4% perempuan. Adapun 30,7% responden merupakan perokok serta 69,3% responden non-perokok. Responden berasal dari 34 provinsi dengan responden terbanyak yaitu dari Provinsi Jawa Timur diikuti Kalimantan Selatan dan DKI Jakarta. Penelitian ini menggunakan instrumen berupa google form. Perilaku merokok dalam usia 12-24 tahun kebanyakan disebabkan oleh faktor lingkungan pergaulan. Pengetahuan bahaya merokok pada masyarakat tergolong tinggi. Namun, tetap perlu ditingkatkan karena pengetahuan remaja pada beberapa topik terkait dampak merokok terhadap penyakit prevalensi tinggi masih kurang. Sebagian besar perokok (65,7%) juga menyadari dan masih memiliki rasa kepedulian atas tindakan merokok mereka terhadap non-perokok, tetapi kebiasaan merokok mereka tetap dilakukan (34,3%). Oleh karena itu perlu dilakukan peningkatan pengetahuan dan upaya untuk mencegah kebiasaan merokok sejak usia dini.
Analisis Hubungan Rasionalitas Penggunaan Obat Antihipertensi dengan Keberhasilan Terapi Pasien Rawat Inap Rumah Sakit X Tahun 2022
Authors: Mardika Dayatri Nur , Astuti Santi Dwi , Wijayanti Tri 
Published: June 2024

Hipertensi adalah penyakit tidak menular dan berbahaya apabila tidak ditangani dengan benar. Di RSUD X Surakarta, hipertensi termasuk dalam 10 penyakit terbesar. Rasionalitas penggunaan obat diindikasikan dengan 6 ketepatam yaitu tepat diagnosis, indikasi, obat, dosis, cara penggunaan, dan waktu pemberian. Tujuan penelitian ini untuk mengetahui hubungan antara rasionalitas dengan keberhasilan terapi pasien hipertensi. Penelitian ini adalah penelitian kuantitatif yang bersifat deskriptif. Sampling dengan metode purposive sampling, dengan cara retrospektif pada rekam medis tahun 2022 dari pasien hipertensi rawat inap di RSUD X. Analisis univariat untuk melihat jumlah penggunaan obat hipertensi yang rasional dan jumlah keberhasilan terapi dengan cara menghitung persentasenya. Sedangkan analisis bivariat untuk menentukan hubungan antara rasionalitas dengan keberhasilan terapi hipertensi di RSUD X, diolah dengan SPSS 26 menggunakan pengujian paired T-test dan chi-square. Hasil penelitian dari 97 sampel menunjukkan bahwa dari segi rasionalitas penggunaan obat semua pasien telah mendapat tepat obat, dosis, cara pemberian, dan waktu pemberian akan tetapi 11 pasien tidak tepat dalam diagnosis dan indikasinya. Keberhasilan terapi dapat dilihat dari parameter tekanan darah (TD), apakah TD pasien saat masuk rumah sakit dan setelah keluar rumah sakit mengalami perbaikan sampai keadaan normal. Hasil hasil paired T test maupun chi-square dengan nilai sig. 0,00 <0,05. Kesimpulan dari penelitian ini ada hubungan antara keberhasilan terapi dengan rasionalitas terapi obat yang diberikan.
Pengetahuan Mahasiswa Perokok Aktif tentang Stain Gigi dan pasta gigi Charcoal sebagai Dasar Pemilihan Pasta Gigi
Authors: Maharani Arina , Fayza Zahra Nabilla , Mayla Kristia Erfika , Davindra Widiantoro Arya , Bharti Rosyadi Devia , Tazkiyya Adillia Firma , Shakira Putri Sanjaya Naila , Ayu Purbiastuti Putri , Salma Falihah Anisah , Fahmi U Mohammad , Faris Alfaruqi Salman , Rahem Abdul 
Published: June 2024

Mahasiswa banyak berstatus sebagai perokok aktif. Hal itu dikarenakan pada kelompok umur 17-23 tahun merupakan target pemasaran rokok. Selain itu, mereka sedang berada pada fase coba-coba sehingga memiliki keinginan yang tinggi untuk mengikuti trend merokok. Merokok berkaitan dengan masalah kesehatan mulut dan gigi, salah satunya stain gigi. Pada perokok aktif kejadian stain gigi dua kali lebih banyak daripada bukan perokok. Kejadian stain gigi dapat dikurangi dengan penggunaan pasta gigi berbahan charcoal. Charcoal dapat menyerap karbon aktif sehingga dapat mengurangi stain gigi. Tujuan dari penelitian ini untuk mengetahui hubungan pengetahuan responden laki-laki mengenai stain gigi dan manfaat charcoal terhadap pemilihan pasta gigi berbahan charcoal. Metode yang digunakan yaitu analisis kuantitatif dengan pengambilan data pada 110 responden secara accidental sampling menggunakan kuesioner. Hasil penelitian menunjukkan 57,3% responden memiliki pengetahuan yang baik mengenai stain gigi dan 46,4% responden memiliki pengetahuan yang baik mengenai manfaat charcoal. Namun, 57,3% responden tidak memilih pasta gigi dengan kandungan charcoal. Data tersebut dianalisis menggunakan uji regresi logistik berganda yang menunjukkan nilai (p) > 0,05 (Î±), serta analisis range Spearman yang menunjukkan nilai (p) = 0,03. Tidak ada hubungan antara tingkat pengetahuan responden tentang stain gigi dan pemilihan pasta gigi berbahan charcoal, tetapi terdapat hubungan antara pengetahuan tentang stain gigi dan pengetahuan tentang manfaat charcoal dalam pasta gigi. Maka dapat dilakukan promosi kesehatan dengan tujuan untuk memotivasi mahasiswa perokok aktif Universitas Airlangga untuk memilih pasta gigi berbahan charcoal.
Kepuasan Penggunaan Aplikasi Med-Pharm Games dalam Pembelajaran
Authors: Rani Tiara Desty  , Dessy Ratna Sari  , Desi Fujiana  
Published: June 2024

Teknologi dan pendidikan menjadi kesatuan dalam perkembangan zaman. Game edukasi adalah permainan yang diciptakan untuk memicu kekuatan berpikir. Salah satu perkembangan game edukasi bagi mahasiswa adalah Aplikasi Med-Pharm Games berfungsi untuk mengetahui nama-nama obat dan kegunaanya. Tujuan penelitian ini adalah untuk mengetahui bagaimana kepuasan mahasiswa terhadap penggunaan aplikasi Med-Pharm Games. Penelitian ini adalah deskriptif kuantitatif dan pengambilan data secara cross-sectional. Populasi dan sampel dari penelitian ini adalah adalah mahasiswa semester 1 Jurusan Farmasi Kampus 3 Poltekkes Kemenkes Surakarta berjumlah 40 mahasiswa. Variabel yang diteliti adalah kepuasan pengguna aplikasi yang mencakup dimensi isi dan kemudahan penggunaan. Analisis data menggunakan analisis univariat secara statistik. Hasil penelitian menunjukkan lebih banyak responden yang berjenis kelamin perempuan (92,5%) dibanding laki-laki. Sebagian besar (72,5%) responden berusia 18 tahun. Pada dimensi isi bahwa hampir seluruh responden menilai susunan bahasa yang digunakan pada aplikasi sudah sesuai dengan kaidah bahasa Indonesia maupun bahasa asing dengan sangat baik. Lebih dari separuh responden (70,0%) menyatakan game ini dapat membantu mahasiswa untuk memahami materi farmakologi dengan sangat baik. Sebagian besar responden (47,5%) menyatakan sangat puas saat menggunakan Med-Pharm Games. Hal akurasi dari sistem perlu diperbaiki dari aplikasi. Dengan demikian, dapat meningkatkan kinerja operasi dari aplikasi Med-Pharm Games.
Complex Segment Linkage Along the Sevier Normal Fault, Southwestern Utah
Authors: Taylor Wanda J. , Surpless Benjamin , Schiefelbein Kerscher Ilsa M. 
Published: June 2024

Abstract
Major normal fault systems are composed of segments that link as displacement accumulates, with linkage zone characteristics that reveal fault zone evolution. The steeply west-dipping Sevier fault zone in southwestern Utah, displays a complex fault network that developed between two long (&gt;10 km), en echelon segments near the town of Orderville. Geologic map data and cross-sections of the transfer zone between the Mt. Carmel segment in the south and the Spencer Bench segment in the north reveal more than ten normal faults and four relay ramps displaying a range of geometries, including two relay ramps that display ramp-parallel folds. We suggest that transfer zone deformation was initially dominated by faults subparallel to the primary segments with later cross-faults that hard-linked these faults across most of the transfer zone. When the transfer zone was a soft-linked system, a displacement deficit likely existed relative to fault segments to the north and south. This early fault configuration would have reduced the efficiency of slip propagation associated with major earthquakes (&gt;M7.0). In contrast, the present-day transfer zone, with a complex but hard-linked fault network, shows displacements that transition smoothly from the higher displacement (~800 m) southern segment to the lower displacement (~400 m) northern segment. That transition, combined with extensional strain within the zone, suggests that the Orderville fault network would be unlikely to impede propagation associated with future major earthquakes. The kinematic model of fault evolution presented here has implications for those investigating geothermal energy potential, groundwater flow, natural gas and oil reservoirs, mineral deposit formation, or seismic hazards.
Coagulation and Platelet Profiles of COVID-19 Patients admitted to a COVID Referral Center from March 2020 to December 2022
Authors: Ungajan-Galapon Ivana , Damian Karen , Geraldino Nelson 
Published: June 2024

Objective. This study aimed to determine the demographic profiles of admitted COVID-19 patients, the association of coagulation and platelet tests on COVID-19 severity and compare the coagulation and platelet profile across the spectrum of the disease in terms of severity among adult COVID-19 patients admitted to the Philippine General Hospital from March 2020 to December 2022.
Methodology. Medical records of a sample of adult COVID-19 patients admitted to the emergency room of the Philippine General Hospital from March 2020 to December 2022 were reviewed. The demographics, initial COVID-19 diagnosis and initial coagulation and platelet test results were gathered and tabulated. Comparison of the initial coagulation and initial platelet results were made per disease category.
Results. Three hundred eighty-five (385) patients were included; 194 were males, and 191 were females. The mean age of all patients was 56.18 years old. There was a total of 30 patients classified as mild and 105 patients are under moderate category. 141 patients were classified as severe, whereas 109 patients were classified as critical. Platelet count test and Activated Partial Thromboplastin Time (APTT) were mostly normal in all disease categories. Prothrombin time was normal in a majority of patients from the mild and severe categories. INR and D-dimer were all elevated mostly in all disease categories.
Conclusion. Platelet counts and APTT were mostly normal in all disease categories. Prothrombin time and D-dimer had a significant association with disease severity. Platelet count, APTT and INR did not show significant association with disease severity. Prothrombin time, APTT, INR and D-dimer means had significant differences versus disease categories.
Machine Learning Techniques in Enhanced Oil Recovery Screening Using Semisupervised Label Propagation
Authors: Vaziri Pouya , Ahmadi Sanyar , Daneshfar Fatemeh , Sedaee Behnam , Alimohammadi Hamzeh , Rasaei Mohammad Reza 
Published: June 2024

Summary
Efficiently choosing the optimal enhanced oil recovery (EOR) technique is a critical requirement in reservoir engineering. Machine learning (ML) methods, with a well-established history of application, serve as a swift and dependable tool for EOR screening. In this paper, we aim to evaluate the effectiveness of various ML algorithms for EOR screening, utilizing a comprehensive database of nearly 1,000 EOR projects. This study delves into a comprehensive evaluation of regression and classification-based algorithms to develop a reliable screening system for EOR predictions and address challenges such as limited labeled data and missing values. Our analysis considered various EOR processes, including gas injection, chemical, and thermal EOR techniques. Various ML methods such as random forest (RF), K-nearest neighbors (KNN), support vector machine (SVM), shallow artificial neural networks (SANN), naive Bayes classifier (NBC), logistic regression (LR), and decision tree (DT) are applied, enabling both intermethod comparisons and evaluations against advanced methods, multiobjective deep artificial neural networks (MDANN), and multiobjective artificial neural networks (MANN). These advanced techniques provide the unique capability to concurrently address both regression and classification tasks. Considering that conventional methods can only be implemented on a single task, the RF, MANN, MDANN, and KNN algorithms demonstrated top-tier performance in our classification analysis. Regarding the regression task, KNN, RF, and MDANN displayed exceptional performance, signifying their prowess in predictive accuracy. However, MANN exhibited moderate performance in regression analysis. In addition, our study identified areas where certain algorithms, such as support vector regression (SVR), exhibited weaker performance, highlighting the importance of comprehensive model evaluation. This paper contributes novel insights into the application of ML techniques for EOR screening in the petroleum industry. By addressing challenges such as limited labeled data and missing values and by providing a thorough evaluation of various ML algorithms, our study offers valuable information for decision-makers in the oil and gas sector, aiding in the selection of suitable algorithms for EOR projects. In addition, the use of semisupervised label propagation and advanced techniques like KNN imputation adds to the existing body of literature, enhancing the state of knowledge in this domain.
Hua-Feng-Dan Alleviates LPS-induced Neuroinflammation by Inhibiting the TLR4/Myd88/NF-κB Pathway: Integrating Network Pharmacology and Experimental Validation
Authors: Zhang Zehan , Pei Yuying , Zheng Yuxiao , Liu Ying , Guo Yixuan , He Yanhui , Cheng Fafeng , Wang Xueqian 
Published: June 2024

Background:
Neuroinflammation is the pathological basis of many neurological diseases, including
neurodegenerative diseases and stroke. Hua-Feng-Dan (HFD) is a well-established traditional Chinese
medicine that has been used for centuries to treat stroke and various other brain-related ailments.

Objective:
Our study aims to elucidate the molecular mechanism by which HFD mitigates neuroinflammation
by combining network pharmacology and in vitro experiments.

Methods:
TCMSP and SymMap databases were used to extract active compounds and their related targets.
The neuroinflammation-related targets were obtained from the GeneCards database. The common targets of
HFD and neuroinflammation were used to construct a protein-protein interaction (PPI) network. MCODE
plug-in was used to find the hub module genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and
Genomes (KEGG) analyses were used to dissect the hub module genes. The lipopolysaccharide (LPS)-induced
BV2 microglial neuroinflammation model was utilized to assess the therapeutic effects of HFD on neuroinflammation.
Western blotting analysis was performed to examine the core target proteins in the TLR4/My-
D88/NF-κB signaling pathway, potentially implicated in HFD's therapeutic effects on neuroinflammation.
Hoechst 33342 staining and JC-1 staining were employed to evaluate neuronal apoptosis.

Results:
Through network pharmacology, 73 active compounds were identified, with quercetin, beta-sitosterol,
luteolin, and (-)-Epigallocatechin-3-Gallate recognized as important compounds. Meanwhile, 115 common
targets of HFD and neuroinflammation were identified, and 61 targets were selected as the hub targets utilizing
the MCODE algorithm. The results of in vitro experiments demonstrated that HFD significantly inhibited
microglial-mediated neuronal inflammation induced by LPS. Integrating the predictions from network pharmacology
with the in vitro experiment results, it was determined that the mechanism of HFD in mitigating neuroinflammation
is closely related to the TLR4/MyD88/NF-κB pathway. Furthermore, HFD demonstrated the
capacity to shield neurons from apoptosis by curbing the secretion of pro-inflammatory factors subsequent to
microglial activation.

Conclusion:
The findings demonstrated that HFD had an inhibitory effect on LPS-induced neuroinflammation
in microglia and elucidated its underlying mechanism. These findings will offer a theoretical foundation for
the clinical utilization of HFD in treating neurodegenerative diseases associated with neuroinflammation.
LC-MS/MS of Dexamethasone in Rabbit Vitreous Liquid Delivered through Novel Self-nanoemulsifying Drug Delivery Systems
Authors: Komesli Yelda , Gozet Fatma Tuba , Sen Behiye Ozturk 
Published: June 2024

Background:
Dexamethasone (DEX), delivered through newly developed selfnanoemulsifying
drug delivery systems, which is administered to rabbit eyes, has been presented.
The instrumental parameters of the multiple LC-MS/MS methods in the literature are modified
according to rabbit vitreous liquid and current laboratory conditions.

Methods:
Quick optimization of the chromatographic and mass spectrometric parameters was done
by inspecting the available literature for the analysis of DEX by LC-MS/MS from biological
matrices. Chromatographic separation was achieved in the reverse mode using C18 (50x2.1mm,
5μm) as a stationary phase and acetonitrile and water with ammonium acetate as a mobile phase in
gradient elution. Quantitation was done in multiple reaction monitoring (MRM) mode by following
the transition of m/z 393 > m/z 373 in positive ion mode. The method was also validated in terms of
selectivity, within-day accuracy and precision, linearity, and limit of detection (LOD). The extraction
of DEX from rabbit vitreous liquid samples was carried out by protein precipitation using
acetonitrile: water (70:30, v/v).

Results:
DEX and beclomethasone (IS) were successfully separated and detected under optimized
experimental settings. The method was selective for DEX and linear in the range of 0.5 and 250
ng/ml. The lower limit of quantification (LLOQ) was determined to be 0.238 ng/ml. The percent
relative standard deviation (RSD) and recovery (%) of the low, medium, and high calibration levels
were below 10% and within the range of 111%-114%, respectively. RSD (%) and recovery (%) of
the LLOQ were below 17% and 82%, respectively. The validated method was successfully applied
for the determination of pharmacokinetic properties of newly formulated dexamethasone selfnanoemulsifying
drug delivery systems (DEXSNEDDS) used to administer DEX intravitreally to the
rabbit.

Conclusion:
LC-MS/MS conditions for the analysis of LC-MS/MS were determined by examining
relevant literature for accomplishing simple and practical optimization of the experimental
parameters, followed by method validation and analysis of rabbit vitreous liqiud. As conclusion,
pharmacokinetic data of DEXSNEDDS has been obtained in the most accurate, sensitive,
economical and rational way possible.
Interaction between Enzymatic Detergent and Textile Metals/Metal Oxide Nanoparticles
Authors: Mirzajani Fateme , Mohseni Nora 
Published: June 2024

Introduction:
Nanoparticles are used in industrial products, such as textiles, to induce
novel properties, such as antibacterial, antistatic, UV blocking, self-cleaning properties, wrinkle resistance,
and water and oil repellent. Moreover, using enzymes (protease, lipase, amylase, and cellulase)
is widespread in detergent industries for washing conditions.

Methods:
This research examines the interactions between metal (Ag) and metal oxide nanoparticles
(TiO2 and ZnO NPs) and amylase, cellulase, protease, and lipase as detergent enzymes and their
impacts on enzyme activity. Using a central composite design, a total of 320 experiments under different
conditions were conducted to determine the extent of change in enzyme activity. Results indicated
that lipase had the lowest activity under interaction with silver nanoparticles, while cellulase
and protease were most affected by interactions with Ag NPs and a-TiO2.

Results:
The surface response of the examined parameters showed the most effect from the interaction
time and temperature and the enzyme/nanoparticle ratio and temperature parameters. This research
result demonstrated that physical, chemical, and biological differences existed between nanoparticle
and enzyme interface.

Conclusion:
The findings can be used to improve the interaction between nanoparticles and detergent
enzymes in washing conditions, aiming to retain their traits.
Relationship Between Social Relationships Quality, Emotional Intelligence, and Work Environment to Psychological Well-Being
Authors: Roellyanti Maria Valeria 
Published: June 2024

This study used a quantitative approach with a cross sectional design. The aim was to explore the relationship between the quality of social relationships, emotional intelligence, and work environment and psychological well-being. A total of 145 respondents who actively worked from various sectors or industries were selected through the purposive sampling method. The research instrument was a questionnaire with five Likert scales 1-5. Data collection will be conducted from December 15, 2023 to January 15, 2024. The data was analyzed using Structural Equation Modeling (SEM) with the help of AMOS software. Path analysis is used to test the relationship between the variables studied, while the validity and reliability of the instrument are examined through factor analysis. The results showed that the quality of good social relationships, high levels of emotional intelligence, and a supportive work environment have a strong and positive influence on the psychological well-being of working individuals. This research makes an important contribution in deepening our understanding of how the interaction between these factors together affects psychological well-being. With a deeper understanding of these dynamics, it is expected to develop strategies that are more effective in improving the quality of the work environment and psychological well-being of employees. Therefore, the results of this study not only provide empirical findings on the relationship between these variables, but also have the potential to be the basis for the development of policies and management practices that are more oriented towards employee welfare. By adjusting the work environment and paying greater attention to aspects such as the quality of social relationships and the building of emotional intelligence, organizations can strengthen the psychological well-being of their employees. This not only means improving an individual's working life, but also having a wider positive impact on productivity and overall work quality.