bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Statistical-based Stability-Indicating Assay for the Estimation of
Salbutamol and Ketotifen using HPLC and HPTLC Methods
Authors: Ghosh Manik , Bandewar Reetu , Mondal Arijit , Dey Suddhasattya , Sarkar Saptarshy , Behera Padma Charan , Jha Sajal Kumar , Mandal Sudip Kumar 
Published: February 2024

Background::
There are very few methods for simultaneously determining a combined dose
of SAL and KET.

Objectives::
The current study aims to explore accurate, precise, simple, and cost-effective HPLC and
HPTLC techniques for the simultaneous assessment of Salbutamol (SAL) and Ketotifen (KET).

Methods::
The determination of Salbutamol and Ketotifen was performed by HPLC and HPTLC methods
using 280 nm and 258 nm as the determination wavelength, respectively. Methanol was used to
dissolve the drug for estimation in HPLC using mobile phase methanol: 10mM di-Potassium hydrogen
orthophosphate in the ratio of 55:45 v/v of pH 4 at a flow rate of 1mL/min and in chloroform: toluene:
methanol (7: 2: 3 v/v/v) for the estimation in HPTLC. Moreover, a statistical comparison was made between
the results obtained through HPLC and HPTLC of Salbutamol (SAL) and Ketotifen (KET) using
the Student’s t-test and F-test.

Results::
A linear response was observed in the range of 4-24 μg/mL and 2-12 μg/mL, respectively, for
SAL and KET for HPLC. R2 was found to be 0.9998 and 0.9999, respectively. For HPTLC, the linear
response was observed in the concentration range of 20-120 ng/ spot and 10 - 60 ng/ spot for SAL and
KET, respectively. R2 was found to be 0.9988 and 0.9998, respectively. The limit of detection (LOD)
for HPLC was estimated as 0.34 μg/ml and 0.10 μg/ml for SAL and KET, respectively, and for the
HPTLC method, the LOD was estimated as 4.8 μg/ml and 1.5 μg/ml, respectively. Analysing the marketed
formulation by using both methods, SAL and KET within the range of 100 ± 2% were recovered.
The results obtained after the estimation of the Mastifen S tablet by applying both methods were according
to nominal content. Degradation studies were performed using both methods. It was found that
Salbutamol was unstable in hydrolytic, oxidative and thermal degradation, whereas stable in photolytic
conditions. Ketotifen was found to be stable in thermal and photolytic conditions and unstable in hydrolytic
and oxidative conditions.

Conclusion::
The proposed stability indicating HPLC and HPTLC methods for SAL and KET was
found to be simple, accurate, and reproducible for quantitative estimation in pharmaceutical dosage
form, without interference from the excipients or degradation products from the main drug component.
Nanostructured Lipid Carriers: A Novel Platform in the Formulation of Targeted Drug Delivery Systems
Authors: Putchakayala Naga Sri Devi , Morusu Keerthana , Ramisetty Sireesha , Ravoru Nagaraju 
Published: February 2024

Background:
Lipid-based formulations, such as Nanostructured lipid carriers (NLCs),
have been thoroughly studied as drug delivery platforms. NLCs are binary systems composed of
both solid and liquid lipids that aim to produce a lipidic core that is less ordered. Components of
NLCs particularly influence the physicochemical characteristics and efficacy of the final product.

Morphology:
They contain a solid matrix at room temperature and are thought to be superior to
many other conventional lipids-based nanocarriers, such as solid lipid nanoparticles (SLNs), nanoemulsions,
and liposomes because of their improved stability, drug loading capacity, good biocompatibility,
enhanced permeability, bioavailability, extended half-life, fewer side effects, tissue-
specific delivery and wide range of potential applications.

Significance:
NLCs have multiple applications in the manufacturing of pharmaceuticals and cosmetics
due to their ease of preparation, the feasibility of scale-up, non-toxic, improved targeting efficiency
and potential for site-specific delivery via various routes of administration.

Scope of Review:
This review enlightens about the most recent developments of NLCs as a drug
delivery system, types of NLCs, current techniques to prepare NLCs, and characterization techniques
that are essential for the development of safe, effective and stable formulation. It also encompasses
the potential of using NLCs for various administration routes and recent developments
in pharmaceutical applications with successful outcomes.

Conclusion:
This review certainly provide great insight into formulation considerations using design
experts and modification strategies for improved targeting. On the whole, NLCs are broadly
explored and preferred lipid nanocarrier systems with several advantages.
DHA and EPA in Sickle Cell Disease Favor Clinical Improvement and Contribute to Better Quality of Life: A Qualitative Systematic Review
Authors: da Conceicao Souza. Jamille , Azevêdo Macêdo Ana Paula , dos Santos Gonçalves Mariane , de Souza Santos Monteiro Adriano , Gomes Barbosa Cynara , David Couto Fábio , David Couto Ricardo 
Published: February 2024

Background:
Sickle cell disease is a severe genetic disorder, and searching for therapeutic
strategies is indispensable for prolonged and improved life for people affected by this condition.

Objective:
This qualitative systematic review aimed to highlight the therapeutic potential of omega-
3 (n-3) in people with sickle cell disease.

Methods:
The search was performed by combining sickle cell disease and n-3 descriptors in DeCS/
MeSH databases, including Scopus, PubMed, ScienceDirect, Web of Science, and Virtual
Health Library. The risk of bias assessment in the primary studies was performed using the
Cochrane risk of bias tool for randomized controlled trials. The evidence quality was evaluated using
the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) tool.

Results:
From the 187 records identified, seven were selected for data collection. Based on the evidence,
n-3 supplementation contributes to lower activation of pro-inflammatory biomarkers, improves
the concentration of docosahexaenoic and eicosapentaenoic acids in the erythrocyte membrane,
provides better hemostatic response, and helps in vaso-occlusive crisis, pain episodes, and
hospitalization reduction.

Conclusion:
The findings suggest that n-3 adjuvant therapy favors the clinical and general aspects
of people with sickle cell disease.
Integration of Patient-Reported Outcome Data Collected Via Web Applications and Mobile Apps Into a Nation-Wide COVID-19 Research Platform Using Fast Healthcare Interoperability Resources: Development Study
Authors: Oehm Johannes Benedict , Riepenhausen Sarah Luise , Storck Michael , Dugas Martin , Pryss Rüdiger , Varghese Julian 
Published: February 2024

Background
The Network University Medicine projects are an important part of the German COVID-19 research infrastructure. They comprise 2 subprojects: COVID-19 Data Exchange (CODEX) and Coordination on Mobile Pandemic Apps Best Practice and Solution Sharing (COMPASS). CODEX provides a centralized and secure data storage platform for research data, whereas in COMPASS, expert panels were gathered to develop a reference app framework for capturing patient-reported outcomes (PROs) that can be used by any researcher.

Objective
Our study aims to integrate the data collected with the COMPASS reference app framework into the central CODEX platform, so that they can be used by secondary researchers. Although both projects used the Fast Healthcare Interoperability Resources (FHIR) standard, it was not used in a way that data could be shared directly. Given the short time frame and the parallel developments within the CODEX platform, a pragmatic and robust solution for an interface component was required.

Methods
We have developed a means to facilitate and promote the use of the German Corona Consensus (GECCO) data set, a core data set for COVID-19 research in Germany. In this way, we ensured semantic interoperability for the app-collected PRO data with the COMPASS app. We also developed an interface component to sustain syntactic interoperability.

Results
The use of different FHIR types by the COMPASS reference app framework (the general-purpose FHIR Questionnaire) and the CODEX platform (eg, Patient, Condition, and Observation) was found to be the most significant obstacle. Therefore, we developed an interface component that realigns the Questionnaire items with the corresponding items in the GECCO data set and provides the correct resources for the CODEX platform. We extended the existing COMPASS questionnaire editor with an import function for GECCO items, which also tags them for the interface component. This ensures syntactic interoperability and eases the reuse of the GECCO data set for researchers.

Conclusions
This paper shows how PRO data, which are collected across various studies conducted by different researchers, can be captured in a research-compatible way. This means that the data can be shared with a central research infrastructure and be reused by other researchers to gain more insights about COVID-19 and its sequelae.
Asynchronous Versus Synchronous Screening for Depression and Suicidality in a Primary Health Care System: Quality Improvement Study
Authors: Sattler Amelia , Dunn Julia , Albarran Marleni , Berger Charlotte , Calugar Ana , Carper John , Chirravuri Lalitha , Jawad Nadine , Zein Mira , McGovern Mark 
Published: February 2024

Abstract

Background
Despite being a debilitating, costly, and potentially life-threatening condition, depression is often underdiagnosed and undertreated. Previsit Patient Health Questionnaire-9 (PHQ-9) may help primary care health systems identify symptoms of severe depression and prevent suicide through early intervention. Little is known about the impact of previsit web-based PHQ-9 on patient care and safety.

Objective
We aimed to investigate differences among patient characteristics and provider clinical responses for patients who complete a web-based (asynchronous) versus in-clinic (synchronous) PHQ-9.

Methods
This quality improvement study was conducted at 33 clinic sites across 2 health systems in Northern California from November 1, 2020, to May 31, 2021, and evaluated 1683 (0.9% of total PHQs completed) records of patients endorsing thoughts that they would be better off dead or of self-harm (question 9 in the PHQ-9) following the implementation of a depression screening program that included automated electronic previsit PHQ-9 distribution. Patient demographics and providers’ clinical response (suicide risk assessment, triage nurse connection, medication management, electronic consultation with psychiatrist, and referral to social worker or psychiatrist) were compared for patients with asynchronous versus synchronous PHQ-9 completion.

Results
Of the 1683 patients (female: n=1071, 63.7%; non-Hispanic: n=1293, 76.8%; White: n=831, 49.4%), Hispanic and Latino patients were 40% less likely to complete a PHQ-9 asynchronously (odds ratio [OR] 0.6, 95% CI 0.45-0.8; P<.001). Patients with Medicare insurance were 36% (OR 0.64, 95% CI 0.51-0.79) less likely to complete a PHQ-9 asynchronously than patients with private insurance. Those with moderate to severe depression were 1.61 times more likely (95% CI 1.21-2.15; P=.001) to complete a PHQ-9 asynchronously than those with no or mild symptoms. Patients who completed a PHQ-9 asynchronously were twice as likely to complete a Columbia-Suicide Severity Rating Scale (OR 2.41, 95% CI 1.89-3.06; P<.001) and 77% less likely to receive a referral to psychiatry (OR 0.23, 95% CI 0.16-0.34; P<.001). Those who endorsed question 9 “more than half the days” (OR 1.62, 95% CI 1.06-2.48) and “nearly every day” (OR 2.38, 95% CI 1.38-4.12) were more likely to receive a referral to psychiatry than those who endorsed question 9 “several days” (P=.002).

Conclusions
Shifting depression screening from in-clinic to previsit led to a dramatic increase in PHQ-9 completion without sacrificing patient safety. Asynchronous PHQ-9 can decrease workload on frontline clinical team members, increase patient self-reporting, and elicit more intentional clinical responses from providers. Observed disparities will inform future improvement efforts.
Fraud Pentagon in Detecting Financial Statement Fraud
Authors: Arizanda Rahayu Ruci , Nurasik  , Arista Firana Riza , Biduri Sarwenda 
Published: February 2024

Purpose: This study aims to prove the influence of the fraud pentagon on the existence of fraudulent financial statements.
Methodology/approach: This research approach is quantitative with secondary data in the form of company annual reports in the manufacturing sector with the food & beverage sub-sector listed on the IDX for the 2016-2020 period. Purposive sampling as sampling with a total of 12 companies for 5 periods and a total sample of 60. The analysis technique uses multiple linear regression assisted by SPSS 26.
Findings: The findings prove that there is an influence of the variables of pressure, opportunity, rationalization, competence, and dualism position on financial statement fraud, while the variable frequent number of CEO's picture does not affect the existence of fraudulent financial statements.
Practical implications: The findings of this study have an impact on the company's stakeholders and stake holders to detect fraud in the financial statements.
Originality/value: This research has the novelty of adding a dualism position proxy variable to the arrogance element.
Research on Physical Education Teaching in Universities Based on Deep Learning
Authors: Wang Tao 
Published: February 2024

Abstract
In this paper, we utilize deep learning methods to perform automatic feature learning from multi-source heterogeneous data, mapping different data into the same hidden space, and obtaining the deep features of the data associated with students and sports. A small amount of information is filtered from a large amount of input information by assigning weights in the attention mechanism and higher weights are assigned to it, and a collaborative filtering recommendation algorithm based on deep learning and algorithm evaluation index is proposed. The deep learning algorithm is integrated into the classroom of “basketball one-handed in situ over-the-shoulder shooting” in college B for empirical analysis, and the teaching effect is compared with that of the traditional teaching mode. The results show that the average scores of 50 meters, sit-ups, pull-ups, 800 meters, 1,000 meters, seated forward bending, and cross-direction running of the students in the physical education classroom based on deep learning are higher than those of the students in the traditional physical education classroom by 5.94, 6.83, 7.69, 6.56, 5.87, 5.1, and 3.68 in the physical fitness comparison analysis. Study shows that physical education teaching based on deep learning can improve students’ various physical qualities, which is of great significance and value in accelerating the high-quality development of physical education and promoting students’ comprehensive development.
Traffic Flow Pattern Recognition in Beijing-Tianjin-Hebei Multi-Airport Airspace
Authors: Ye Zhijian , Pang Qin 
Published: February 2024

Abstract
This paper proposes a flight data-driven model to identify air traffic flow patterns based on multi-layer cluster analysis for identifying and characterizing traffic flow patterns in the airspace of the Beijing-Tianjin-Hebei multi-airport system. The spatial and temporal trends of flight data are mined to capture the air traffic flow characteristics, and the busyness of waypoints help air traffic managers to understand the reuse status of runways and airspace for capacity planning decision support in the complex airspace of Beijing-Tianjin-Hebei.
A safety evaluation model of open-pit mine dust based on subjective and objective weighting method
Authors: Li Jun 
Published: February 2024

Abstract
By analyzing the dust safety of open-pit mines, five primary indicators and 20 secondary indicators are determined for evaluation, and the subjective weights determined by the hierarchical analysis method and the objective weights determined by the entropy weighting method are combined to determine the subjective and objective weights; the scores of experts are integrated using fuzzy numbers to determine the final scores, and the combination of the two is used to construct the evaluation model of the dust safety of open-pit mines. Taking three mines as an example, the results show that the open pit mine dust safety of Mine is A
1 significantly better than that of the remaining two mines. The study shows that the model is suitable for open pit mine dust safety evaluation, considering the typical characteristics of subjectivity and objectivity, better reflecting the intention of the decision makers and the actual importance of the indicators, and making the results more scientific and objective. The proposed method provides a reference for determining dust safety in open pit mines.
Research on Medical Image Enhancement Method Based on Conditional Entropy Generative Adversarial Networks
Authors: Li Hui 
Published: February 2024

Abstract
This study proposes an image enhancement method combining conditional entropy and generative adversarial network, aiming to improve the image quality while avoiding overfitting through the negative training of dependent generative adversarial network and introducing dependent entropy distance loss. Through NIQMC, NIQE and BTMQI evaluation indexes, this paper evaluates the effects of different parameter combinations and image chunk sizes on the enhancement results. It utilizes information entropy as an evaluation index to measure the impact of conditional entropy distance loss. The effectiveness of adversarial learning and conditional entropy in image enhancement is verified by comparing the experimental results. The experiments show that the system can achieve the best image quality of SSIM=0.9852, PSNR=27.58, and SNROI=21.34 with the parameters S=50 and R=4.0%, indicating that the method can effectively retain the detailed information and realism of the Image while enhancing the clarity of the Image, demonstrating a significant performance advantage.
Educational Practices to Enhance Learners’ Intrinsic Motivation — Based on the Learning Process of Medical Students in a Specialized Creative Integration Project
Authors: Zhang Jingliang , Chen Wenqian , Wang Jingjing , Wang Ying 
Published: February 2024

Abstract
In innovation and entrepreneurship education, personalized Education is achieved through specialized creative integration and project-based learning to cultivate college students’ abilities in innovation, creation, and entrepreneurship. However, besides providing a wide range of course options and resources on the supply side, it is crucial to emphasize enhancing learners’ intrinsic motivation on the demand side of project-based learning. We conducted an educational practice to enhance students’ personalized learning inherent motivation in the medical school. Through assigning one project per student, we aimed to stimulate students’ curiosity, empathy, and sense of responsibility by focusing on the authenticity of project topics. Furthermore, the uniqueness of projects in innovation and creation was used to enhance students’ understanding of identification and ownership. Additionally, we promoted students’ courage to transform old habits, products, and services through a sense of belonging and conformity fostered within the student community. The timely supervision and rewards in competitions also contributed to students’ understanding of rhythm, fulfillment, and respect. After a project-based Practice, significant progress and improvements were observed in students’ professional abilities, multiple intelligences, creativity, and competition results.
Optimization of network security protection posture based on data clustering
Authors: Zhu Jiancheng 
Published: February 2024

Abstract
This paper focuses on the challenges facing network security in the digital era and proposes a network security posture optimization method based on data clustering. Three mainstream network security models, namely, P2DR security operation and maintenance model, line defense model, and three-dimensional defense model, are analyzed, and the limitations of existing security products are pointed out. The application potential of big data technology in network security is emphasized, and a comprehensive technical process containing information extraction, posture modeling, security trend prediction, and security policy deployment is constructed. The ARMA model and reinforcement learning building model are introduced, and the improved K-means algorithm is proposed to address the shortcomings of traditional methods. Experiments are conducted using the DARPA2000 dataset, and the results show the enhanced algorithm’s significant improvement in clustering accuracy and stability, with a maximum threat value of about 160, demonstrating better stability and effectiveness than the traditional method. The posture value exceeds 500 in a specific period, highlighting the dynamic changes in network security and confirming the practicality and effectiveness of the technique. The results of this study provide new strategies and perspectives for network security protection, and have essential reference and guidance value for practical applications and future research.
Anxiety, Sports Motivation, and Coping Styles Based on Sports Competition Video Analysis
Authors: Liu Fang 
Published: February 2024

Abstract
Emotional problems such as anxiety, stress and tension may have a long-term impact on athletes’ competitive performance and physical and mental health. The identification method of athletes’ psychological state based on video analysis has the advantages of objectivity, real-time and high efficiency. It provides a more accurate evaluation tool for coaches and psychologists. This article aims to design an efficient facial emotion identification model for athletes to improve the accuracy and real-time performance of emotion identification. The results show that the accuracy and recall rate of the convolutional neural network (CNN) algorithm are higher than those of the traditional algorithm in most cases, and the CNN model has high real-time and fast response ability. This research result is valuable for athletes’ psychological state monitoring and performance analysis. By studying athletes’ psychological state, coaches can better understand their inner world in the competition and provide them with more accurate psychological support and intervention. This will not only help to improve athletes’ competitive performance, but also help them better cope with the challenges and pressures in the competition and protect their physical and mental health.