bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dataset: Cyberlaw and Copyright in the 21st Century: A Comprehensive Analysis of Scholarly Works
Authors: Sonia Citra , Multazam Mochammad Tanzil 
Published: March 2023

This data article presents a collection of scholarly works related to Cyberlaw and Copyright in the field of law, obtained through the Lens.org website. The data were obtained by searching for scholarly works using keywords Cyberlaw or Cyber Law and Copyright and filtering them by document type (journal article), date range (2012-2022), and subject matter (law). The data were exported in CSV and BibTex formats and are available in the Zenodo repository. The analysis of the data using VOSViewer and Lens.org tools revealed the top institutions, fields of study, active authors, countries/regions, publishers, and journals. The results of this study provide a valuable resource for researchers and practitioners interested in the legal aspects of Cyberlaw and Copyright.
Highlights:

Valuable resource for Cyberlaw and Copyright research
Comprehensive analysis of scholarly works from 2012-2022
Reveals top institutions, authors, and publishers in the field.
Dataset: Global Trends in Digital Forensics and Fingerprint Research: A Comprehensive Analysis
Authors: Azizah Aulia Sarah , Multazam Mochammad Tanzil 
Published: March 2023

The purpose of retrieving this data is to determine the number of journal articles related to digital forensics and fingerprinting. Through lens.org analysis with appropriate keywords and filters, 133 relevant documents were found. The study revealed that the University of Lausanne is the most active institution in this field, with the most research in 2019. The most explored fields of study include forensic science and computer security. The most active countries in this research were the UK, the US, and Switzerland. These results suggest that this data can serve as a quick guide to further research and development methods, such as forensic 3D modelling and photogrammetry. In addition, this data is useful for authors, readers, and researchers interested in the topic of digital forensics and fingerprinting.Highlights:

Dominant institutions and countries: University of Lausanne leads the research, with the United Kingdom, United States, and Switzerland as the most active countries.
Peak research activity: The highest number of journal articles published in 2019, focusing on various aspects of digital forensics and fingerprinting.
Interdisciplinary exploration: Research spans across forensic sciences, computer security, and law, indicating diverse applications and implications of digital forensics and fingerprinting techniques.
Dataset: Uncovering Trends in Digital Forensics and Criminal Law Research: A Decade of Insights
Authors: Hamdani Rizky , Multazam Mochammad Tanzil 
Published: March 2023

This data article explores the landscape of digital forensics and criminal law research from 2012 to 2022 by analyzing scholarly works available on Lens.org. By applying various filters such as release year, document type, and field of study, we identified 23 relevant journal articles. The analysis revealed insights into the most active institutions, authors, and publishers in the field, as well as the most prolific countries/regions. These findings offer a valuable resource for researchers, policymakers, and practitioners interested in digital forensics and criminal law.
Highlights:

A decade-long analysis of digital forensics and criminal law research from 2012 to 2022.
Identification of the most active institutions, authors, publishers, and countries/regions in the field.
Valuable insights for researchers and practitioners interested in digital forensics and criminal law.
Dataset: Digital Forensic Literature with a Focus on Software: Trends, Institutions, and Authors (2012-2022)
Authors: Sari Pandu Sarigati , Multazam Mochammad Tanzil 
Published: March 2023

This data article presents a thorough examination of digital forensic literature with a focus on software from 2012 to 2022, retrieved from lens.org, with the aim of identifying the most influential institutions, authors, and research trends. Using keywords "digital forensic AND software," the data collection process involved filtering by date range, document type, and subject matter, resulting in 427 journal articles. The analysis highlights the most productive institutions, years, fields of study, active authors, and publishers. This data is valuable for researchers and practitioners in digital forensics, particularly those interested in software applications, providing insights into the most significant contributions and aiding future research development.
Highlights:

Research in the field of digital forensics is growing rapidly, with the Université de Lausanne being the leading institution in the number of publications.
Computer science is the most popular field of study in digital forensics, with a focus on analysing software and file systems.
Elsevier B.V. is the leading publisher in digital forensics, with the journal Digital Investigation as the main source of publications.
Dataset: Mapping the Landscape of Cyber Law and Cyber-Harassment Research: A Comprehensive Data Analysis
Authors: Salsabila Nur Riska , Multazam Mochammad Tanzil 
Published: March 2023

This data article presents a comprehensive analysis of cyber law and cyber-harassment-related journal articles within the field of law. The data was collected using the lens.org platform, employing keyword searches for "cyberlaw" and "cyber-harassment," and subsequently filtering the results by document type (journal articles) and subject matter (law). The final dataset comprises 143 scholarly works, which were analyzed to identify the top institutions, fields of study, authors, countries, and publishers involved in this area of research. The results reveal that Cardiff University is the most prolific institution, with psychology being the most common field of study. The United Kingdom is the most active country, and Informa UK Limited is the top publisher. This data is valuable for researchers seeking literature related to cyber law and cyber-harassment, offering insights into the prevalent themes and trends in this rapidly evolving domain.
Highlights:

The prevalence of psychology as the top field of study, indicating the significant impact of cyber-harassment on mental well-being.
The United Kingdom's role as the most active country in publishing related research, demonstrating its commitment to addressing cyber law and harassment issues.
The rapid development of cyber-harassment and its association with increased risk factors, emphasizing the need for ongoing research and preventative measures.
Type I interferon-dependent IFIT3 signaling is critical for viral clearance in airway neutrophils
Authors: Gaggar Amit , Margaroli Camilla , Fram Timothy , Sharma Nirmal , Patel Siddharth , Tipper Jennifer , Robison Sarah , Russell Derek , Fortmann Seth , Banday Mudassir , Abdalla Tarek , Saitornuang Sawanan , Madison Matthew , Leal Sixto , Harrod Kevin , Erdmann Nathaniel 
Published: March 2023

Abstract
Neutrophilic inflammation characterizes several respiratory viral infections including COVID-19-related ARDS, although its contribution to disease pathogenesis remains poorly understood. Here, we identified two neutrophil subpopulations (A1 and A2) in the airway compartment of 52 severe COVID-19 subjects, where loss of the A2 subset correlated with increased viral burden and reduced 30-days survival. A2 neutrophils showcased a discrete antiviral response with an increased interferon signature. Blockade of type I interferon attenuated viral clearance in A2 neutrophils and downregulated IFIT3 and key catabolic genes, demonstrating direct antiviral neutrophil function. Knockdown of IFIT3 in A2 neutrophils led to loss of IRF3 phosphorylation with consequent reduced viral catabolism, providing the first discrete mechanism of type I interferon signaling in neutrophils. The identification of this novel neutrophil phenotype and its association with severe COVID-19 outcomes emphasizes its likely importance in other respiratory viral infections and potential for new therapeutic approaches in viral illness.
Examination of the Relationship Between Thanatophobia and Resilience Levels of Nurses Working in Intensive Care and Palliative Care Units
Authors: Rashidi Mahruk , Karaman Funda , Yildirim Gulay , Kiskac Nese , Jafarov Gulsah Unsal , Sahin Buse Saygin 
Published: March 2023

Abstract
Background: Nurses in critical care and palliative care units care for patients suffering from severe pain and suffering and at high mortality risk. For this reason, nurses working in these units should be psychologically resilient. However, nurses who are constantly exposed to the death process face the risk of thanatophobia. The aim of this study is to examine the relationship between thanatophobia levels and the psychological resilience of nurses working in intensive care and palliative care units.
Methods: The sample of this descriptive study included 158 nurses working in intensive care and palliative care units. Personal information form for nurses, Thanatophobia Scale and Psychological Resilience Scale for Adults were used and data were collected through an online questionnaire in the study. Percentage calculations, mean measurements, Kruskal Wallis test and Mann Whitney U test were used in the statistical evaluation of the data.
Results: Nurses had moderate mean scores from the Thanatophobia Scale and Psychological Resilience Scale, 31.74±10.08 and 108.34±7.12, respectively. A statistically significant difference was found between nurses’ age and whether they received training on psychological resilience (p<0.05). Those who received training on resilience had higher scores from the resilience scale subdimensions of personal competence and family coherence. A statistically negative and low-level significant correlation was determined between the psychological resilience scale and thanatophobia scale total scores.
Conclusions: As a result, it was determined that as the thanatophobia of the nurses increased, their psychological resilience decreased. This situation may negatively affect nurses working in critical departments to provide quality health care to patients. Establishing and maintaining training programs to reduce thanatophobia and increase psychological resilience of nurses working in intensive care and palliative care units will ensure that nurses provide quality health care to the patient and reduce the physiological and psychological wear of nurses.
The relationship between serum lipid levels and diabetic kidney injury in patients with type 2 diabetes mellitus
Authors: Zahedi Maryam , Amirkhanlou Saeid , Farahani Parisa , Talebi Zahra , Talebi Fateme 
Published: March 2023

Abstract
Background: Diabetic kidney injury (DKI), a complication of diabetes mellitus (DM) and a risk factor for the cardiovascular events, is affected by many metabolic factors, including dyslipidemia. This study investigated the relationship between serum lipid levels and DKI in patients with type 2 diabetes mellitus (T2DM) in Gorgan, north of Iran.
Materials and Methods: This case-control study was performed on 218 patients with T2DM in two groups with and without DKI as case and control groups, respectively. A questionnaire was used to gather demographic information, and the necessary laboratory results, such as fasting serum lipid levels, urine albumin, fasting plasma glucose, and serum creatinine, were also assessed. For group comparison, the Mann-Whitney test, Fisher's exact test, and Chi-square test were used.
Results: The results of this study did not show any statistically significant relationship between DKI and serum lipid levels (p>0.05). However, DKI was associated with age, duration of DM, type of glucose-lowering drugs, and body mass index (BMI) (p≤0.05).
Discussion and Conclusions: DKI is not significantly related to the serum lipid levels in the patients with T2DM, but older age, longer duration of DM, insulin-indicated hyperglycemia, and lower BMI are associated with it. Therefore, further attention to each of the associated factors may be helpful in the earlier detection of DKI in patients with T2DM.
A Comparative Study of Thin Film Flow of Fe3 O4 And Al2 O3 Nanoparticles over Stretching Surface Under the Effect of Viscous Dissipation and Magnetohydrodynamics(MHD)
Authors: Hayat Umer , Shaiq Shakil , Shahzad Azeem 
Published: March 2023

Abstract
This article presents a numerical investigation of thin film flow and heat transfer for lamina, tetrahedron, and hexahedron-shaped nanomaterials of Fe3 O4 and Al2 O3 over a time-dependent radially vertical stretching surface. Moreover, the magnetohydrodynamics and viscous dissipation effects are also incorporated. A similarity transformation is employed to produce the nonlinear governing system of equations, which is numerically solved using the BVP4C method in MATLAB. The study shows that film thickness depends on the unsteadiness parameter, with an increase in the parameter causing decrease in film thickness (β), velocity, and temperature. The lamina and hexahedron shapes provide maximum and minimum film thickness for Fe3 O4 and Al2 O3 both nanoparticles, while the hexahedron and lamina shapes generate maximum and minimum skin friction. The Nusselt numbers exhibit the opposite effect. These findings provide insights into thin film flow's fundamental mechanisms and applications.
The City Cluster Program and Strategic Fiscal Expenditure for FDI: Cooperative or Competitive?
Authors: Yang Yong , Sheng Yuxue 
Published: March 2023

Abstract
Whether and how the City Cluster Program (CCP) in China changes the public expenditure strategy for FDI. To answer this question, we propose an identifying mechanism on NEG theory and spatial econometrics, allowing us to overcome the unavailability of the disaggregate data of public fiscal expenditures. We find that members adjust from a competitive to cooperative expenditure strategy for FDI by reducing egoistic expenditure and increasing altruistic expenditure after the CCP. The spatial spillovers and decomposition between and within different subsamples confirm that the CCP alleviates the competition for FDI, and low-ranking members in the city hierarchy prefer competitive strategies for FDI in the pre-CCP period and make more adjustments to cooperative strategies in the post-CCP period.
JEL Classification: R58, H73, F23
Patient Embeddings From Diagnosis Codes for Health Care Prediction Tasks: Pat2Vec Machine Learning Framework
Authors: Steiger Edgar , Kroll Lars Eric 
Published: March 2023

BackgroundIn health care, diagnosis codes in claims data and electronic health records (EHRs) play an important role in data-driven decision making. Any analysis that uses a patient’s diagnosis codes to predict future outcomes or describe morbidity requires a numerical representation of this diagnosis profile made up of string-based diagnosis codes. These numerical representations are especially important for machine learning models. Most commonly, binary-encoded representations have been used, usually for a subset of diagnoses. In real-world health care applications, several issues arise: patient profiles show high variability even when the underlying diseases are the same, they may have gaps and not contain all available information, and a large number of appropriate diagnoses must be considered.ObjectiveWe herein present Pat2Vec, a self-supervised machine learning framework inspired by neural network–based natural language processing that embeds complete diagnosis profiles into a small real-valued numerical vector.MethodsBased on German outpatient claims data with diagnosis codes according to the International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10), we discovered an optimal vectorization embedding model for patient diagnosis profiles with Bayesian optimization for the hyperparameters. The calibration process ensured a robust embedding model for health care–relevant tasks by aggregating the metrics of different regression and classification tasks using different machine learning algorithms (linear and logistic regression as well as gradient-boosted trees). The models were tested against a baseline model that binary encodes the most common diagnoses. The study used diagnosis profiles and supplementary data from more than 10 million patients from 2016 to 2019 and was based on the largest German ambulatory claims data set. To describe subpopulations in health care, we identified clusters (via density-based clustering) and visualized patient vectors in 2D (via dimensionality reduction with uniform manifold approximation). Furthermore, we applied our vectorization model to predict prospective drug prescription costs based on patients’ diagnoses.ResultsOur final models outperform the baseline model (binary encoding) with equal dimensions. They are more robust to missing data and show large performance gains, particularly in lower dimensions, demonstrating the embedding model’s compression of nonlinear information. In the future, other sources of health care data can be integrated into the current diagnosis-based framework. Other researchers can apply our publicly shared embedding model to their own diagnosis data.ConclusionsWe envision a wide range of applications for Pat2Vec that will improve health care quality, including personalized prevention and signal detection in patient surveillance as well as health care resource planning based on subcohorts identified by our data-driven machine learning framework.
Understanding Older Adults’ Experiences With Technologies for Health Self-management: Interview Study
Authors: Garcia Reyes Elsy Paola , Kelly Ryan , Buchanan George , Waycott Jenny 
Published: March 2023

Background
Many older adults now use technologies such as wearable devices and telehealth services to support their health and well-being while living independently at home. However, older adults vary in how they use these technologies, and there is a lack of knowledge regarding the motivations that influence their acceptance and use of health-related technologies in home environments.

Objective
This study aimed to understand the types of technologies that older adults use to support their health and the factors that motivate them to use their chosen technologies to support their health. In addition, we aimed to understand the factors that enable the effective use of technologies for health self-management and to identify the barriers that can negatively affect the adoption of technologies.

Methods
A total of 22 older adults participated in semistructured interviews regarding their experiences of using technologies for health self-management. Interview transcripts were analyzed through an in-depth thematic analysis.

Results
The interviews revealed that a range of technologies, such as videoconferencing software, fitness trackers, and other devices, were being used by older adults to support their health. Interviews showed that participants were motivated to use technologies to monitor health issues, to stay active and connected, and to record and change their behavior in the light of foreseen risks related to their future health status. Enablers that facilitated the effective use of technologies include social and organizational influence, convenient access to health care and safety provided by the technology, and easy setup and low cost of the technology. Barriers include information overload and a sense of futility about future health decline; telehealth being an inadequate substitute for in-person consultation; concerns about trust related to privacy and accuracy; and technologies being stigmatizing, uncomfortable to use, expensive, and unfamiliar.

Conclusions
This study suggested that older adults were using a variety of technologies to prevent or prepare for future health decline, evidencing a resilient attitude toward health and aging. In addition, older adults were willing to continue using the technology when there was a perceived need. The enabler mentioned by most participants was the social and organizational influence that included health care staff, family, friends, and organizations. This analysis provides a better understanding of how older adults use technologies to support their health and can guide the provision of appropriate health technologies for them.
Genotypic characterization of Mycobacterium leprae strains resistant to rifampicin and ofloxacin in three health districts in Chad
Authors: Kirga Kabo Abakar , Nadlaou Bessimbaye , Mahamat Abakar , Cambau Emmanuelle , Penlap Véronique , Godreuil Sylvain 
Published: March 2023

Antimicrobial surveillance and identification of the genetic basis of antimicrobial resistance provides important information to optimize patient care. The present study was an analytical cross-sectional study aimed at determining the prevalence of rifampicin and ofloxacin resistance genes among Mycobacterium leprae strains in three health districts in Chad.
The determination of the folP1, rpoB and gyrA resistance genes was carried out by PCR-RLEP and confirmed by sequencing from 80 biopsy samples taken from patients with multibacillary leprosy, including 12 relapsed patients and 68 new cases. In the whole cohort, 1/80 (1.2%) showed resistance to rifampicin and 1/80 (1.2%) to ofloxacin. No mutations were detected for dapsone. The presence of M. leprae mutation associated with rifampicin resistance was observed in a relapsed patient and the mutation associated with ofloxacin resistance was observed in a patient with multibacillary leprosy who had not been sensitized by ofloxacin but should have used other quinolones. Both mutant strains revealed the emergence of secondary resistance.
This study, the first to highlight the emergence of resistance to rifampicin and ofloxacin in Chad. It raises the need to implement a robust surveillance system to detect resistance of Mycobacterium leprae in Chad and even in Central Africa.
Keywords: Mycobacterium leprae, resistance, Chad
The Effectiveness of SGLT2 Inhibitors in CKD Patients
Authors: Boddula Hema , Shivani R. , S P Srinivas Nayak , Vaghasia Jitendra , Chakraborthy G. S. , Mandal Snigdha Das , Ghatol Prajwal 
Published: March 2023

Sodium-glucose cotransporter-2 inhibitors, often known as SGLT2Is, are a class of medications used largely for anti-diabetic activity in oral dose form that lowers blood glucose levels. In recent years, numerous trials have documented the use of medications for conditions including renal and cardiovascular illness that go beyond only decreasing blood sugar. Other benefits of SGLT2Is' glucose-lowering activities include slowing or halting the progression of chronic kidney disease, lowering estimated glomerular filtration rate, lowering albuminuria, improving renal and cardiovascular health, and reducing estimated glomerular filtration rate. Published clinical trials reported all of these SGLT2I effects. The studies that we reviewed for this article are the Canagliflozin CardioVascular Assessment Study (CANVAS), Canagliflozin and Renal Events in Diabetes with Established Nephropathy Clinical Evaluation (CREDENCE), Dapagliflozin and Prevention of Adverse Outcomes in Chronic Kidney Disease (DAPA - CKD) trial, Effects of SGLT2I dapagliflozin on Proteinuria in Non-Diabetic Patients with The clinical studies, SGPLT2I class of medications, and their impact on cardiovascular and renal illnesses in diabetic and non-diabetic individuals are adequately covered in this review study.
Keywords: SGLT2Is, Chronic kidney disease, dapagliflozin, Canagliflozin