bluuebunny/crossref_metadata_2025_split huggingface dataset:
Realtime ransomware process detection using an advanced hybrid approach with machine learning within IoT ecosystems
Authors: El Hariri Ayyoub , Mouiti Mohammed , Lazaar Mohamed 
Published: December 2024

Abstract
Cybersecurity faces significant challenges from malicious attacks, malware, and ransomware variants, posing serious threats to computer systems, infrastructure, data centers, web and mobile applications across diverse sectors. Conventional anti-ransomware systems struggle to keep pace with evolving sophisticated threats. Therefore, advanced methodologies, including both traditional and artificial intelligence based approaches, are becoming increasingly crucial in developing innovative ransomware countermeasures. This study presents a novel hybrid detection framework for ransomware, combining entropy and frequency analysis with various machine learning algorithms, including Multi-Layer Perceptron MLP, Decision Trees DT, Random Forests RF, K-Nearest Neighbor KNN, and Logistic Regression LR. We evaluate the classification performance of these models using a specialized ransomware dataset. Our approach also incorporates data augmentation techniques to enhance the detection capabilities, generating synthetic data based on the original ransomware samples. Our experiments demonstrate that the DT and RF classifiers significantly outperform other methods in terms of accuracy, F1-score, and precision. Specifically, the DT classifier achieved an accuracy of 98.89%, an F1-score of 98.81%, and a precision of 98.90%, while the RF classifier achieved an accuracy of 98.78%, an F1-score of 98.23%, and a precision of 98.99%. The integration of data augmentation further boosted the model’s performance, resulting in substantial improvements across all metrics.
Micro aerial vehicle flapping actuation: an experimental analysis of crank and sliding lever mechanisms
Authors: Singh Spoorthi , Ali Tanweer , Zuber Mohammad , Basri Adi Azriff , Mazlan Norkhairunnisa , Hamidon Mohd Nizar , Basri Ernnie Illyani , Ahmad Kamarul Arifin , Hegde Navya Thirumaleshwar , Vaz Aldrin Claytus 
Published: December 2024

Abstract
Artificial flapping-wing robots necessitate a lightweight transmission mechanism with minimal interconnected parts, posing challenges to their development. This paper explores the design and analysis of a flapping actuation mechanism utilizing a crank and sliding lever configuration to convert rotational motion into angular flapping. The proposed mechanism represents a minimalist design concept with lightweight components specifically tailored for mosquito-sized flapping wing applications, contrasting with traditional, heavier four-bar mechanisms. Flight control is achieved through the crank slider design, facilitating essential maneuverability. Moreover, variations in forward and return stroke velocities contribute to enhanced lift generation. Structural and kinematic analysis of the flapping actuation mechanism are conducted to determine parameters such as wing angular velocity, acceleration, flapping angle, and frequency under maximum input voltage. Experimental validation of the concept is performed using data from a designed prototype, or flapping-wing testbed. Flapping angle measurements, similar to those of a mosquito, are verified using an ultrasonic sensor. Frequency validation involves separate flapping measurements on the testbench model using an infrared sensor and a laser tachometer, with validation of forward and reverse stroke durations. The return stroke consumed 37 percent of the cycle period, making it significantly faster than the forward stroke, which takes up 63 percent. Consequently, the time ratio between the forward and return strokes is 2:1, generating a favorable lift force throughout the wing's flapping cycle. This validates the sliding lever movement concept, with variations in the time and speed of flapping for both strokes observed in analytical results, simulation outcomes, and real-time testing.The suitability of the sliding lever mechanism for Micro Aerial Vehicle(MAV) flapping-wing applications is confirmed through these analysis and experiments.
Self-adaptive physics-informed quantum machine learning for solving differential equations
Authors: Setty Abhishek , Abdusalamov Rasul , Motzoi Felix 
Published: December 2024

Abstract
Chebyshev polynomials have shown significant promise as an efficient tool for both classical and quantum neural networks to solve linear and nonlinear differential equations (DEs). In this work, we adapt and generalize this framework in a quantum machine learning setting for a variety of problems, including the 2D Poisson’s equation, second-order linear DE, system of DEs, nonlinear Duffing and Riccati equation. In particular, we propose in the quantum setting a modified Self-Adaptive Physics-Informed Neural Network approach, where self-adaptive weights are applied to problems with multi-objective loss functions. We further explore capturing correlations in our loss function using a quantum-correlated measurement, resulting in improved accuracy for initial value problems. We analyse also the use of entangling layers and their impact on the solution accuracy for second-order DEs. The results indicate a promising approach to the near-term evaluation of DEs on quantum devices.
Validation of the Arabic Version of the Multiple Sclerosis Impact Scale (MSIS-29): a Rasch Analysis Study
Authors: Al-Qerem Walid , Basem Dunia , Khdair Sawsan , Jarab Anan , Eberhardt Judith 
Published: December 2024

Abstract

Background
Multiple sclerosis (MS) is a potentially disabling disease of the brain and spinal cord. This cross-sectional study aimed to validate the Arabic version of the Multiple Sclerosis Impact Scale-29 (MSIS-29) using Rasch analysis to assess quality of life in Jordanian MS patients.

Method
Rasch analysis was conducted to evaluate the suitability of the model for the present study. Model fit was assessed by computing item/person separation reliability, infit and outfit mean square (MSQ) values, Cronbach's alpha, and the Akaike Information Criterion.

Results
A total of 301 MS patients were enrolled in the study. Significant likelihood ratios for all three scales (MSIS-29-PHYSICAL, MSIS-29-PSYCHOLOGICAL, and MSIS-29-TOTAL) supported the use of a partial credit Rasch model. An issue with disordered thresholds was resolved by collapsing adjacent response categories. Item reliability scores for MSIS-29-PHYS and MSIS-29-PSYCH were 0.95 and 0.89, respectively, while person reliability scores were 0.92 and 0.84, respectively. Infit and outfit MSQ were within the acceptable range for all items on the MSIS-29-PSYCH scale. However, for the MSIS-29-PHYS scale, item MSIS-29_17 exceeded the acceptable range in both infit (1.93) and outfit (1.82) MSQs, and item MSIS-29_20 exceeded the acceptable range in infit (1.81). The Wright map also indicated that most items were considered relatively easy by the respondents, exhibiting various difficulty levels on the latent scale.

Conclusion
The Arabic version of the MSIS-29 is a valid and reliable tool for evaluating quality of life in Jordanian MS patients.
Predicting phage–host interactions via feature augmentation and regional graph convolution
Authors: Wei Ankang , Xiao Zhen , Fu Lingling , Zhao Weizhong , Jiang Xingpeng 
Published: December 2024

Abstract
Identifying phage–host interactions (PHIs) is a crucial step in developing phage therapy, which is the promising solution to addressing the issue of antibiotic resistance in superbugs. However, the lifestyle of phages, which strongly depends on their host for life activities, limits their cultivability, making the study of predicting PHIs time-consuming and labor-intensive for traditional wet lab experiments. Although many deep learning (DL) approaches have been applied to PHIs prediction, most DL methods are predominantly based on sequence information, failing to comprehensively model the intricate relationships within PHIs. Moreover, most existing approaches are limited for sub-optimal performance, due to the potential risk of overfitting induced by the highly data sparsity in the task of PHIs prediction. In this study, we propose a novel approach called MI-RGC, which introduces mutual information for feature augmentation and employs regional graph convolution to learn meaningful representations. Specifically, MI-RGC treats the presence status of phages in environmental samples as random variables, and derives the mutual information between these random variables as the dependency relationships among phages. Consequently, a mutual information-based heterogeneous network is construted as feature augmentation for sequence information of phages, which is utilized for building a sequence information-based heterogeneous network. By considering the different contributions of neighboring nodes at varying distances, a regional graph convolutional model is designed, in which the neighboring nodes are segmented into different regions and a regional-level attention mechanism is employed to derive node embeddings. Finally, the embeddings learned from these two networks are aggregated through an attention mechanism, on which the prediction of PHIs is condcuted accordingly. Experimental results on three benchmark datasets demonstrate that MI-RGC derives superior performance over other methods on the task of PHIs prediction.
NAT2 Slow Acetylator Phenotype as a Significant Risk Factor for Hepatotoxicity Caused by Antituberculosis Drugs: Results From a Multiethnic Nested Case-Control Study
Authors: Cheli Stefania , Torre Alessandro , Schiuma Marco , Montrasio Cristina , Civati Aurora , Galimberti Miriam , Battini Vera , Mariani Ilaria , Mosini Giulia , Carnovale Carla , Radice Sonia , Clementi Emilio , Gori Andrea , Antinori Spinello 
Published: December 2024

Abstract

Background
Under standard therapies, the incidence of drug-induced liver injury (DILI) in patients with tuberculosis ranges from 2% to 28%. Numerous studies have identified the risk factors for antituberculosis DILI; however, none have been conducted in a multiethnic real-world setting. The primary outcome of the current study was to identify the risk factors that could be used as the best predictors of DILI in a multiethnic cohort.

Methods
A nested case-control study was conducted in patients at the tuberculosis clinic of Luigi Sacco Hospital in Milan.

Results
The study included 102 patients (mean age [SD], 45.6 [15.6] years). For each patient with hepatotoxicity, 2 controls were matched for sex, age, body mass index, tuberculosis/tuberculosis infection diagnosis, and index date. We found that N-acetyltransferase 2 gene (NAT2) slow acetylator status was the best independent predictor of DILI (odds ratio, 5.97 [95% confidence interval, 1.38–25.76]; P = .02].

Conclusions
NAT2 genotype–guided dosing may help optimize antituberculosis drug treatment and prevent treatment failure.

Clinical Trials Registration
ClinicalTrials.gov NCT06539455
Understanding the role of oil and gas companies in the current sustainability trends: an application of the sustainable business model archetypes
Authors: Menéndez-Sánchez Jaime , Fernández-Gómez Jorge , Araujo-de-la-Mata Andrés 
Published: December 2024

Abstract
Oil and gas (O&G) companies face a complex process of adaptation to the new sustainability context. How their business models can successfully respond to sustainability requirements remains unclear. We studied the decarbonisation activities of relevant O&G companies and applied the sustainable business model archetypes (SBMAs) taxonomy to shed light on this transformation. Based on this, we focussed on one O&G firm with large socio-economic importance in northern Spain, gathering information via semi-structured interviews. Our analysis shows that O&G companies are developing innovative technologies aligned with the SBMAs. Multi-stakeholder collaboration and a regional focus on industrial clusters appear to be key elements of the sustainability strategies of O&G companies.
GeniePool 2.0: advancing variant analysis through CHM13-T2T, AlphaMissense, gnomAD V4 integration, and variant co-occurrence queries
Authors: Weintraub Grisha , Hadar Noam , Gudes Ehud , Dolev Shlomi , Birk Ohad S 
Published: December 2024

Abstract
Originally developed to meet the challenges of genomic data deluge, GeniePool emerged as a pioneering platform, enabling efficient storage, accessibility, and analysis of vast genomic datasets, enabled due to its data lake architecture. Building on this foundation, GeniePool 2.0 advances genomic analysis through the integration of cutting-edge variant databases, such as CHM13-T2T, AlphaMissense, and gnomAD V4, coupled with the capability for variant co-occurrence queries. This evolution offers an unprecedented level of granularity and scope in genomic analyses, from enhancing our understanding of variant pathogenicity and phenotypic associations to facilitating research collaborations. The introduction of CHM13-T2T provides a more accurate reference for human genetic variation, AlphaMissense enriches the platform with protein-level impact predictions of missense mutations, and gnomAD V4 offers a comprehensive view of human genetic diversity. Additionally, the innovative feature for variant co-occurrence analysis is pivotal for exploring the combined effects of genetic variations, advancing our comprehension of compound heterozygosity, epistasis, and polygenic risk factors in disease pathogenesis. GeniePool 2.0 is a comprehensive and scalable platform, which aims to enhance genomic data analysis and contribute to genomic research, potentially supporting new discoveries and clinical innovations.
Database URL: https://GeniePool.link
The meaning of Miles: knighthood as social signifier in Early Capetian France
Authors: Ó Súilleabháin Niall 
Published: December 2024

Abstract
The origins of knighthood are a much-debated topic in medieval history, with scholars divided on whether the emergence of milites (knights) in the documentary record of late tenth-century France represented a fundamental rupture in aristocratic society. This article argues that the emergence of the term should be understood as a social signifier, intended to identify its subject securely as a member of the social elite. The nuanced ways in which miles was deployed as an identifier is traced through a series of examples from the Loire valley and other regions of the Capetian kingdom, revealing the versatility of the term in claiming elite status. By viewing knighthood as a claim that was made, rather than a title that was conferred, the article argues that the aristocracy of early Capetian France was a social hierarchy characterized by flux and uncertainty, in which status needed to be constantly reasserted.
Under his protection: securing land, loyalty and sovereignty in thirteenth-century Champagne and Navarre
Authors: Bjerke Jillian 
Published: December 2024

Abstract
During the period 1234–74, when the counts of Champagne also ruled the Iberian kingdom of Navarre, dozens of monasteries, nobles, hospitals and city councils in both regions put themselves, their property and their belongings into the count–kings’ care. That they did so demonstrates the rulers’ perceived and actual power, for the count–kings could never be in both their principalities simultaneously. The people of Champagne and Navarre did not require the physical presence of their lord to benefit from his protection, which they sought primarily in times of precarity and in response to comital–royal movements. Likewise, through granting protection the count–kings established and reinforced bonds between themselves and their subjects that would endure even in their absence. For the count–kings of Champagne–Navarre, protecting their subjects was not just about securing their territory but also about engendering the loyalty of their subjects and maintaining (and sometimes extending) their sovereignty.
Dual clusters in dual economies: understanding innovation in clusters of developing countries
Authors: Galaso Pablo , Rodríguez-Miranda Adrián , Vázquez Barquero Antonio 
Published: December 2024

Abstract
In developing countries, clusters not only have a dual configuration with pronounced differences in company performance but are also embedded within the framework of dual economies. This restricts the capacity of networks to facilitate the innovation processes of local firms. We provide empirical evidence that supports this hypothesis by analyzing local and multinational firms in 18 Latin American clusters. Our findings can improve the understanding of innovation processes in underdeveloped countries, suggesting that dualism should be considered as a determining factor.
Urbanization as a Gendered Process: Theory, Evidence, and Implications
Authors: Anthony Robert M , Robison Kristopher K 
Published: December 2024

Abstract
This research note addresses the overlooked and undertheorized gendered dimensions of rural-urban migration in the developing world. Drawing on Ester Boserup's (1970/2007) framework, a macro-social theory is offered that links historic agricultural divisions of labor to gendered patterns of urbanization. Specifically, it is argued that nations with a history of male farming systems (MFS) are more likely to produce economic and cultural conditions that facilitate women's rural-urban migration when compared to nations with a history of female farming systems (FFS). From this, the notion of “open” and “closed” urban systems is conceptualized to help identify and categorize the gendered urbanization histories of developing nations, which are linked to women's rights. Empirical support for the concepts and their association with women's rights is presented using mapped data from 138 developing nations from 1985 to 2015. A nation-level t-test of the interactive proxy measure between nation-level male-to-female urban population ratios and the degree of women's exclusion reveals a significant difference between nations with open and closed urban systems (p &lt; 0.01). The conclusion discusses the limitations of the theory and evidence, the implications of the findings, and future research directions.
Is the 99th Percentile Cutoff Still Relevant? A Single-Center Assessment of Different Thresholds for Diagnosing Antiphospholipid Syndrome
Authors: Dadelahi Alexis , Walker Brandon S , Banerjee Dipanwita , Mahler Michael , Saadalla Abdulrahman , Nandakumar Vijayalakshmi 
Published: December 2024

Abstract

Background
The 2023 American College of Rheumatology and modified Sapporo criteria for antiphospholipid syndrome (APS) recommend ELISA to detect anticardiolipin (aCL) and anti-β2-glycoprotein I (aβ2GP1) IgG/IgM antibodies, focusing on moderate to high levels or exceeding the 99th percentile. This study aims to establish the 99th percentile threshold for anti-phospholipid (aPL) antibodies and compare the diagnostic accuracies of these thresholds with manufacturer cutoffs using 2 methodologies.

Methods
The 99th percentile cutoffs for aPL antibodies from 305 healthy donors were established using Aptiva, Particle-Based Multi-Analyte Technology (PMAT), and QUANTA Lite (QL) ELISA, following nonparametric reference interval estimation. Sera from 34 APS patients and 190 APS controls were tested. Diagnostic performances were compared at the 99th percentile-, manufacturer-, receiver operating characteristic (ROC) derived optimal-, and 95% specificity-optimized cutoffs. An expanded cohort of 61 APS patients and 1299 APS controls from a 2-year retrospective review was also included.

Results
For ELISA, the 99th percentile cutoffs for aCL (IgG/IgM) and aβ2GP1 (IgG) were at the assay limit of quantification. Optimal cutoffs from the ROC curves, 95% specificity-matched and manufacturer cutoffs, showed better diagnostic accuracy than the 99th percentile. On the Aptiva PMAT platform, the 99th percentile cutoffs were lower but provided comparable diagnostic accuracies to manufacturer and optimal cutoffs, although specificity was below 95%.

Conclusions
The clinical utility of 99th percentile cutoffs is assay dependent. For QL, these cutoffs were unsuitable, while Aptiva showed better alignment with clinical thresholds. Manufacturer-recommended cutoffs, supported by extensive validation, offer a reliable alternative when clinical studies are infeasible.
The International Criminal Court at a Crossroads
Authors: Zimmermann Andreas 
Published: December 2024

Abstract
More than 25 years after the adoption of the Rome Statute, the International Criminal Court (ICC) finds itself in the middle of turmoil between ambitious goals underlying its founding instrument and the increasingly diverse composition of its state parties, with both divergent interests and divergent perceptions of its role. At the same time, it is needed more than ever with a whole set of crimes committed during armed conflicts for which it has jurisdiction. It is against this background that the article focuses on the role of the Court in the international legal system, its interaction with the Security Council and states making referrals, as well as the development of substantive international criminal law through amendments to the Rome Statute and the Court’s jurisprudence. It argues for a somewhat cautious approach in order to safeguard its crucial role in the international legal system in the long term.
Management of intellectual property rights in Mainland Tanzania and Rwanda: reflecting on the one-stop centre strategy
Authors: Costantine Jovine 
Published: December 2024

Abstract
This article investigates how IP rights are managed in mainland Tanzania compared to Rwanda. Its main focus is exploring the significance of the one-stop centre strategy in managing IP. In Rwanda, since the year 2000, the one-stop centre has promoted IP and contributed to the economic growth of the country. On the other hand, in mainland Tanzania, the management of IP is mandated and controlled by various institutions responsible for implementing scattered legislation. Such institutions lack coordination and sufficient fund to manage IP. This situation prevents an effective exploitation of IP in mainland Tanzania. Thus, this article recommends the adoption of a one-stop centre strategy for managing IP in mainland Tanzania, learning from the experience of Rwanda.
Suicide deaths by occupation skill level and educational attainment in the United States
Authors: Messias Erick , Azasu Enoch K , Nayeem Nawar , Lin Ping-I , Grucza Richard 
Published: December 2024

Abstract

Objectives
To estimate the association between suicide deaths and both occupational skill level and educational attainment in the United States.

Methods
Suicide deaths, employment, education, and demographic data from the 2021 National Center for Health Statistics Multiple Cause of Death Files, for ages 18-64 with a lifetime history of employment, were combined with comparable participants from the 2020-2022 Current Population Survey. Outcomes of interest were associations between suicide death and occupational skill level, assessed as a 5-level variable, and educational attainment. Logistic regression models were used to estimate these associations before and after adjusting for educational attainment, age, and sex, in each racial/ethnic subpopulation.

Results
We found a significant gradient in suicide death across occupational skill levels, with lower-skill occupations associated with higher suicide rates than higher-skill occupations. This gradient was more pronounced among non-Hispanic White (NHW) people and non-Hispanic Black (NHB) people than Hispanic people. However, upon controlling for educational attainment, this association was attenuated, indicating that the initial link was likely confounded by education.

Conclusions
The results suggest that educational attainment is a more robust predictor of suicide risk than occupational skill level. Targeted interventions addressing educational and ethnic disparities within higher-risk occupational groups can mitigate suicide risk.