bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cryptographic Analysis of Blur-Based Encryption an in depth examination of resilience against various attack vectors
Authors: Umar Hafiz Gulfam Ahmad , Aoun Muhammad , Kaleem Muhammad Aftab , Rehman Shafiq Ur , khan Madiha Zahir , Younis Muhammad , jamil Muhammad 
Published: June 2023

Abstract
The study evaluates the encryption method's resistance to well-known cryptographic assaults and assesses its robustness against frequent image processing operations. In this paper we evaluate of the blur-based picture encryption method and demonstrates how it is resistant to image processing operations and cryptographic assaults the benefits of the blur-based picture encryption method, highlighting its effectiveness and ease of use. It demonstrates the method's appropriateness for secure multimedia transmission and storage applications while identifying any flaws and outlining prospective improvements. A variety of techniques used in the study, including the Arnold Transform, logistic Map, Henon Map, Modified Arnold Transform, and Baker Map. Additionally, it emphasizes the Gaussian blur algorithm's performance in compared to other methods, highlighting how quickly it encrypts data only 0.0006 seconds. It also emphasizes the Gaussian blur algorithm's faster speed as compared to other algorithms.
Dictatorship, Higher Education, and Social Mobility
Authors: Prem Mounu , Bautista María Angélica , Martínez Luis R. , Muñoz Pablo , González Felipe 
Published: June 2023

Abstract
We study the effect of political regime change on higher education and its distributional consequences. We focus on Chile’s military dictatorship under Augusto Pinochet. After coming to power through a coup in 1973, the Pinochet regime steadily reduced government funding for higher education, which led to fewer openings for new college students and lower tertiary enrollment. These cuts disproportionately affected college applicants from less affluent backgrounds. Exploiting the greater exposure to the contraction of higher education experienced by birth cohorts that reached college age shortly after the 1973 coup, we show that those affected had lower college enrollment, worse labor market outcomes, and struggled to climb the socioeconomic ladder. These findings suggest that the contraction of higher education hindered social mobility and plausibly contributed to the increase in inequality observed under Pinochet.
JEL codes: H52, I23, I24, I25
Structural characterization of biosurfactant produced by marine bacterium Pseudomonas fragi strain F1 (isolated from Persian Gulf) and evaluation of antimicrobial and antibiofilm activity
Authors: Amirinejad Nazanin , Shekarchizadeh Afrooz , Mousavi Maryam , Behzadi Mahla Askarinejad , Hassanshahian Mehdi , Ataie Seyed Ahmad , Hjazi Ahmad , Ibrahim Ahmed jaber 
Published: June 2023

Abstract
The marine environment is a rich source of bioactive compounds, including biosurfactant-producing bacteria that exhibit unique characteristics and functionalities. In this study, we focused on glycolipid biosurfactants produced bacteria in a commensal relationship with marine organisms. We isolated and characterized a biosurfactant-producing strain, Pseudomonas fragi strain F1, which displayed high hemolytic activity (27mm), oil spreading ability (4mm), emulsification index (40%), and decreasing surface tension (31.3 mN/m). Fourier transform infrared (FT-IR) analysis revealed the glycolipid nature of the produced biosurfactant. Elemental analysis using CHNS and Energy Dispersive Spectroscopy (EDS) confirmed the presence of carbon, hydrogen, nitrogen, sulfur, chlorine, potassium, oxygen, and some other elements in the biosurfactant. The critical micelle concentration (CMC) of the biosurfactant was measured at 350 mg.L− 1, indicating its high efficiency. Furthermore, the biosurfactant demonstrated significant antimicrobial activity against Gram-positive and Gram-negative bacteria (the largest obtained ZOI was associated to P. aeruginosa with 27 mm), making it a potential alternative to synthetic drugs. The biosurfactant also exhibited substantial inhibition of biofilm formation and disruption, as well as enzymatic activity reduction in treated bacteria. Moreover, the mixture of biosurfactant and F1 bacterium enhanced the degradation of crude oil (86%), indicating its potential for environmental remediation. These findings highlight the importance of exploring commensal biosurfactant-producing strains in marine environments for hydrocarbon degradation, combating antibiotic resistance, and disrupting microbial biofilms.
Implicating Anoikis and CXCR4 in Osteoarthritis: Predictive Modeling and Therapeutic Insights
Authors: Kuang Yulin , Kuang Haoming , Li Hongfang , Xiong Luojie , Gong Zhichao , Tan Junlan , Kuang Jianjun , Sun Shaoqiu 
Published: June 2023

Abstract
Background
Osteoarthritis (OA) is a globally prevalent joint disorder characterized by complex pathophysiology and diagnostic limitations. The present study aimed to elucidate the potential roles of anoikis-related genes in OA and develop a reliable diagnostic model. Additionally, we investigated the role of hub gene CXCR4 in immune response modulation within OA and explored potential therapeutic agents.
Methods
Gene expression datasets GSE207881 and GSE168505, were downloaded from Gene Expression Omnibus database and analyzed for potential disparities in immune cell infiltration between OA and control samples.
Results
We identified 94 DEGs involved in OA pathogenesis and pinpointed 6 hub genes (CXCR4, PECAM1, CCL5, VWF, MCAM, and CXCL12) with potential roles in OA. The machine learning model, which developed nine models and used SHAP method for interpreting the models, showed high predictive accuracy for OA risk, with CCL5, CXCL12, and CXCR4 emerging as key predictive factors. Notably, CXCR4, an immune system modulator, exhibited potential interactions with immune responses in OA. Furthermore, potential therapeutic compounds were examined using Connectivity Map (CMap) analysis and molecular docking. CMap analysis proposed potential therapeutic compounds, which require further validation.
Conclusions
Our study unveils the association between anoikis-related genes and OA, highlighting the utility of machine learning models for OA risk prediction. It also underscores the significance of CXCR4 in immune response modulation and potential therapeutic strategy in OA. These findings could spur the development of novel diagnostic tools and personalized therapies for OA, although further validations are necessary.
Extending the limits of the abatement cost
Authors: MEUNIER GUY , Ponssard Jean-Pierre 
Published: June 2023

Abstract
Public authorities have to decide whether to support projects to mitigate GHG emissions. In the context of the transition toward Net Zero Emissions, all polluting activities need be decarbonised one day or the other that is, projects should lead to a perpetual clean phase. The relevant questions are which clean technology should be used and when it should be launched. The paper proposes the relevant dynamic cost benefit framework to solve these questions. Under some specific assumptions we derive two metrics of abatement cost, the first one to determine when to implement a given technology, and the second one to compare alternative technologies. The first metric, called the dynamic abatement cost, is defined as the ratio between the annualized incremental cash cost of the new technology by the long term abatement. It is obtained through a marginal cost benefit analysis relative to the launch date. The second metric is an adjustement of the first one to integrate the impact of intermediary abatements along the transitory phase. These two metrics are not simple extensions of current abatement metrics, which ordinarily would provide spurious answers. We generalize our metrics to situations with exogenous technical change, a random arrival of a backstop technology, and when Hotelling's rule does not apply. We show how to incorporate endogenous technical change and spillovers between sub-components of a project. Two applied studies are revisited to highlight the operational interest of our approach.
JEL Classi cation: Q51, Q56, R58
Willingness and Motivation of Egyptian Patients with diabetic retinopathy to Participate in Clinical Trials
Authors: Khalil Ahmad S. , Salamah Moustafa A. , Kotb Ahmed N , Hegab Mohammed A. 
Published: June 2023

Abstract
Purpose
is to identify the motivational factors and barriers to clinical trial recruitment of the Egyptian DR patients.
Patients and methods:
Patients with DM either type I or II came to our outpatient clinic were subjected to fundus examination. Patients with any degree of diabetic retinopathy were included. A questionnaire was distributed to them. It included the sociodemographic, clinical characteristics and questions to identify the motivational factors or barriers to participate in a trial. We divided them according to their tendency for recruitment, the first group that accepts the participation; we asked them about the most motivational factors. The second group that refused the participation, we asked them about their potential barriers.
Results
Among the 206 recruited patients (145/206) (70.4%), accepted to participate while the remaining (61/206) (29.6%) refused to. Fear from blindness was the commonest motivational factor (93.1%) and the risk of side effects was the commonest barrier (100%). Acceptance to participate was higher among those with positive family history (P = 0.01). Refusal to participate was higher in mild NPDR (P < 0.001). Patients with PDR and macular edema accepted to participate (P < 0.001). High education was significantly associated with acceptance compared to those who refuse (81.1% versus 18.9% respectively) (P = 0.004). Ocular history of previous intervention significantly associated with accepting to paricipate (P = 0.001).
Conclusion
Acceptance was unpredictably high. The results of this questionnaire should encourage researchers to conduct more clinical trials.
A unified Bayesian inversion approach for a class of tumor growth models with different pressure laws
Authors: FENG YU , Liu Liu , Zhou Zhennan 
Published: June 2023

Abstract
In this paper, we use the Bayesian inversion approach to study the data assimilation problem for a family of tumor growth models described by porous-medium type equations. The models contain uncertain parameters and are indexed by a physical parameter $m$, which characterizes the constitutive relation between density and pressure. Based on these models, we employ the Bayesian inversion framework to infer parametric and nonparametric unknowns that affect tumor growth from noisy observations of tumor cell density. We establish the well-posedness and the stability theories for the Bayesian inversion problem and further prove the convergence of the posterior distribution in the so-called incompressible limit, $m \rightarrow \infty$. Since the posterior distribution across the index regime $m\in[2,\infty)$ can thus be treated in a unified manner, such theoretical results also guide the design of the numerical inference for the unknown. We propose a generic computational framework for such inverse problems, which consists of a typical sampling algorithm and an asymptotic preserving solver for the forward problem. With extensive numerical tests, we demonstrate that the proposed method achieves satisfactory accuracy in the Bayesian inference of the tumor growth models, which is uniform with respect to the constitutive relation.
Dynamic Modeling and Fault-Tolerant Reconfiguration Strategies for PneumaticallyActuated Soft Snake Robot: Enabling Robust Locomotion in the Presence of Air Leakage
Authors: Bhandari Garima , Yang Jung Min , Pathak Pushparaj Mani 
Published: June 2023

Abstract
Recently, the study of soft robots has become quite popular for their flexibility, safer interaction with humans, and low-cost adaptability to complex and uncertain environments. This paper presents a bond graph model of a pneumatically actuated soft snake robot and novel reconfiguration strategies for the soft snake robot to accommodate the faults caused by air leakage. With the proposed recon-figuration strategies, the soft snake robot can have robust locomotion along the desired trajectory even if an air leakage fault occurs during the locomotion. An efficient procedure of fault detection and isolation is also incorporated into the bond graph model of the robot. We conduct in-depth numerical experiments to validate the proposed robot model’s performance and reconfiguration strategies. Experimental results demonstrate that the soft snake robot, aided with reconfig-uration strategies, achieves straight-line locomotion with the lateral undulation gait despite air leakage faults.
Serum Humanin in Pediatric Septic Shock Associated Multiple Organ Dysfunction Syndrome
Authors: Atreya Mihir , Cvijanovich Natalie Z. , Fitzgerald Julie C. , Weiss Scott L. , Bigham Michael T. , Jain Parag N. , Schwarz Adam J. , Lutfi Riad , Nowak Jeffrey , Thomas Neal J. , Baines Torrey , Haileselassie Bereketeab , Zingarelli Basilia 
Published: June 2023

Abstract

Background
Multiple organ dysfunction syndrome (MODS) disproportionately contributes to pediatric sepsis morbidity. Humanin (HN) is a small peptide encoded by mitochondrial DNA and thought to exert cytoprotective effects in endothelial cells and platelets. We sought to test the association between serum HN (sHN) concentrations and MODS in a prospectively enrolled cohort of pediatric septic shock.
Methods
Human MT-RNR2 ELISA was used to determine sHN concentrations on day 1 and 3. The primary outcome was thrombocytopenia associated multi-organ failure (TAMOF). Secondary outcomes included individual organ dysfunctions on day 7. Associations across pediatric sepsis biomarker (PERSEVERE) based mortality risk strata and correlation with platelet and markers endothelial activation were tested.
Results
140 subjects were included in this cohort, of whom 39 had TAMOF phenotype. Concentration of sHN was higher on day 1 relative to day 3, and among those with TAMOF phenotype in comparison to those without. Although, the association between sHN and TAMOF phenotype was not significant after adjusting for age and PRISM-III score in multivariate models, we identified that sHN was independently associated with presence of day 7 sepsis-associated acute kidney injury (SA-AKI) (p = 0.032). Further, sHN was higher among those with high PERSEVERE-mortality risk strata and correlated with platelet counts and several markers of endothelial activation.
Conclusion
Among children with septic shock, sHN concentrations were higher among patients with TAMOF phenotype and independently associated with persistent SA-AKI. Pending further validation and rigorous mechanistic studies, interventions aimed at restoring humanin may have therapeutic implications in recovery of organ function among critically ill patients.
The fuzzy support vector data description based on tightness for noisy label detection
Authors: Wu Xiaoying , Liu Sanyang , Bai Yiguang 
Published: June 2023

Abstract

Machine learning is a data-driven approach and as machine learning research advances, noisy labels have become a widely studied issue. Noisy labels can significantly reduce the accuracy of supervised classification models, making it important to address this problem. In this study, we propose a new method for detecting noisy labels in datasets. This method first utilizes a deep pre-trained network to obtain a feature set from the image data. We then introduce a membership degree based on tightness into the support vector data description model to detect noisy data in the dataset. To further verify the accuracy of our method, we construct two noise sets: the density peak noise set and the random noise set. The experimental findings indicate that our proposed algorithm outperforms traditional support vector data description algorithms in detecting noisy labels. Moreover, we use confidence to correct noisy labels in the data. After correcting for noisy labels, the accuracy of image classification is significantly improved.
How to Personalize and Whether to Personalize? Candidate Documents Decide
Authors: Liu Wenhan , Zhou Yujia , Zhu Yutao , Dou Zhicheng 
Published: June 2023

Abstract

Personalized search plays an important role in satisfying users’ information needs owing to its ability to build user profiles based on users’ search histories. Most of the existing personalized methods built dynamic user profiles by emphasizing query-related historical behaviors rather than treating each historical behavior equally. Sometimes, the ambiguity and short nature of the query make it difficult to understand the potential query intent exactly, and the query-centric user profiles built in these cases will be biased and inaccurate. In this work, we propose to leverage candidate documents, which contain richer information than the short query text, to help understand the query intent more accurately and improve the quality of user profiles afterwards. Specifically, we intend to better understand the query intent through candidate documents, so that more relevant user behaviors from history can be selected to build more accurate user profiles. Moreover, by analyzing the differences between candidate documents, we can better control the degree of personalization on the ranking of results. This controlled personalization approach is also expected to further improve the stability of personalized search as blind personalization may harm the ranking results. We conduct extensive experiments on two datasets and the results show that our model significantly outperforms competitive baselines, which confirms the benefit of utilizing candidate documents for personalized web search.
Earliest isotopic evidence of high reliance on plant food in the Late Pleistocene hunter-gatherer population (Taforalt, Morocco)
Authors: Moubtahij Zineb , McCormack Jeremy , Bourgon Nicolas , Trost Manuel , Fuller Benjamin , Smith Geoff , Sinet-Mathiot Virginie , Temming Heiko , Steinbrenner Sven , Hublin Jean-Jacques , Bouzouggar Abdeljalil , Turner Elaine , Jaouen Klervia 
Published: June 2023

Abstract

The transition from hunting-gathering to agriculture stands as one of the most significant dietary revolutions in human history. Yet, due to a scarcity of well-preserved human remains from Pleistocene sites, little is known about the dietary practices of pre-agricultural human groups. Here, we present the first isotopic evidence of pronounced plant reliance among Late Pleistocene hunter-gatherers from North Africa, predating the advent of agriculture by several millennia. Employing a comprehensive multi-isotope approach, we conducted zinc (δ66Zn) and strontium (87Sr/86Sr) analysis on dental enamel, carbon (δ13C), and nitrogen (δ15N) isotope analysis on dentin and bone collagen, alongside single amino acid analysis on humans and fauna from Taforalt (Morocco). Our results unequivocally demonstrate a substantial plant-based component in the diets of these hunter-gatherers. This distinct dietary pattern challenges the prevailing notion of high reliance on animal proteins among pre-agricultural human groups. Additionally, it raises intriguing questions surrounding the absence of agricultural development in North Africa during the early Holocene. This study underscores the importance of investigating dietary practices during the transition to agriculture and provides novel insights into the complexities of human subsistence strategies across different regions.
Supernova Archaeology in a Black-Hole Wind
Authors: Keshet Noa , Behar Ehud 
Published: June 2023

Abstract
Supernovae (SNe) are responsible for the elemental enrichment of the galaxy [1, 2]. High-mass core-collapse SNe are postulated to leave behind a black hole (BH) [3, 4]. In a stellar binary the BH can accrete back its own debris, emit X-rays, and eject winds [5]. Measuring abundances of elements in the outflow, or of the companion [6, 7], can lead to inferences about the historical explosion and identify the long-gone progenitor of the black hole [8]. Here, we exploit a uniquely rich X-ray spectrum of the binary GRO J1655-40 [9-11] to measure seventeen different elements in its wind. The wind is unusually rich in odd-Z elements, such as Na, Al, P, Cl, and K. Such a composition has been predicted for core-collapse SNe of metal-rich massive stars of 40 M⊙ [12, 13], but never before observed. The ionization distribution in the wind [14, 15] features two distinct regions, which reflect changes in its radial profile, and perhaps entrainment of pristine circumstellar supernova debris. It can also explain why the wind differs in composition from that of the stellar companion, where SN debris is mixed with its atmosphere [7]. The difference between the current BH mass of 6.6 M⊙ and theoretical estimates for its birth mass of ∼ 3 M⊙ date the supernova at least 10 million years back if it grew by accretion.
Decoding the Relationship between Cow Milk Proteins and Type 1 Diabetes Mellitus Development
Authors: Andrade Luís Jesuino de Oliveira , de Oliveira Gabriela Correia Matos , de Oliveira Luísa Correia Matos , Bittencourt Alcina Maria Vinhaes , Sousa Maristella de Araújo Carvalho , de Oliveira Luís Matos 
Published: June 2023

Abstract
Introduction: Introduction: Type 1 diabetes mellitus (T1DM) is an autoimmune disease that develops due to the destruction of insulin-producing beta-cells in the pancreas by the immune system. Cow milk is one of the dietary factors associated with the development of T1DM, as it contains proteins that may trigger the autoimmune response.
Objective: To analyze in silico the evidence of molecular mimicry between Glutamic Acid Decarboxylase-65 (GAD-65)/ Human insulin/Zinc Transporter 8 (ZnT8) and bovine serum albumin (BSA) and beta-lactoglobulin (BLG) as a potential trigger for T1DM.
Method: The in silicoanalysis was performed using bioinformatics tools to compare the amino acid sequences of cow milk proteins (BSA and BLG) and human beta-cell autoantigens (GAD-65, Human insulin and ZnT8). The structural and functional characteristics of the proteins were analyzed to identify potential molecular mimicry mechanisms.
Results: The results of the in silico analysis showed significant sequence similarity between BSA, BLG, and GAD-65, Human insulin and ZnT8 ranging from 19.64% to 27.27%. The cow's milk proteins evaluated shared structural features with the beta cell antigens selected for comparison, indicating the potential for molecular mimicry between these proteins. Conclusion: The findings of this study provide further evidence for the potential role of cow milk proteins in the triggering of T1DM. The in silico analysis suggests that molecular mimicry mechanisms between cow milk proteins and human beta-cell antigens may contribute to the autoimmune response that leads to T1DM. This study highlights the importance of dietary factors in the development of T1DM and the need for further research to understand the mechanisms involved.