bluuebunny/crossref_metadata_2025_split huggingface dataset:
Wear performance of aluminium hybrid nanocomposites using Taguchi
Authors: Venkata Subbaiah K , T SarithNaidu 
Published: May 2024

Abstract
This research explored AA 6351reinforced with varying amounts of nano silicon carbide (five wt%) and nanoZirconia powder (3to 9 in steps of three wt%) composites’ wear performance using the powder metallurgy technique. Wear tests were conducted on the specimens in a dry, ambient environment utilizing a tribometer(pin-on-disc). The impact of three factors—Zirconia wt percentage, load, and sliding velocity—on the wear rate and friction coefficient was investigated. An experimental design based on the Taguchi-nine-level orthogonal array was employed, allowing for efficient analysis of parameter significance. Optimum conditions for minimum wear were identified through a main effect plot, indicating 9% wt reinforcement (Level 3), 1.34 ms−1 sliding velocity (Level 3), and 10 N load (Level 1). Sliding velocity (72.027%) emerged as the primary determinant of wear- rate in the ANOVA analysis, followed by the contributions of reinforcement (16.056%) and load (10.92%). Optimization for the lowest friction coefficient, again via the main effect plot, pointed to 9% wt reinforcement (Level 3), 30 N load (Level3), and 0.84 ms−1 sliding velocity (Level2). ANOVA showed that reinforcement ZrO2(37.57%) strongly influenced friction, with sliding velocity (20.53%) and load (14.78%) playing more minor roles.
Enhancing blockchain security: a novel approach to integrated malware defence mechanisms
Authors: Sharma Aastha , Upadhyay Divya , Sharma Shanu 
Published: May 2024

Abstract
This paper introduces a novel integrated hybrid malware attack detection algorithm, focusing on enhancing cybersecurity within blockchain systems by addressing the prevalent challenges of Byzantine fault tolerance, Reentrancy, and DDOS attacks. The significance of this research lies in its contribution to safeguarding blockchain technology, a cornerstone for secure, decentralized digital transactions, against sophisticated malware threats. Current cybersecurity solutions frequently fall short of offering a complete defense mechanism, making it difficult to effectively combat a variety of dynamic malware attacks at the same time. Thus, the main objective of this research is to provide a hybrid framework that combines DDOS attack prevention, reentrancy attack detection, and Byzantine fault tolerance detection into a single, cohesive architecture. The proposed hybrid framework encompasses a detailed algorithmic approach integrating SHA-256 and DSA to analyze the aforementioned three malware attacks. A hybrid model combining these algorithms, implemented in one block, has been developed to mitigate malicious activity. These measures aim to improve computational complexity and expedite execution within the network of nodes. To test the efficacy of the proposed framework, the approach is tested on the NSL-KDD dataset to analyze the malicious activities. The performance analysis of the proposed frameworks presents a recall and F1 score of 73 and .68 respectively. Furthermore, for efficient mitigation, the time and space complexity analysis is performed on proposed algorithms for attack analysis, which resulted in a combination of constant and linear time complexity operations. The findings reveal that the proposed algorithm successfully identifies and mitigates the targeted malware attacks and maintains optimal performance in terms of time and space complexity. Specifically, the algorithm showcases linear and constant time complexities across different attack vectors, ensuring swift and scalable defense capabilities. This research’s contribution to the cybersecurity field is significant, offering a robust, scalable solution that enhances the resilience of blockchain networks against a broad spectrum of malware attacks.
Shafarevich-Tate groups of abelian varieties
Authors: Nikolaev Igor 
Published: May 2024

The Shafarevich-Tate group

Ш

(

A

)

\Sha (\mathscr {A})

measures the failure of the Hasse principle for an abelian variety

A

\mathscr {A}

. Using a correspondence between the abelian varieties and the higher dimensional non-commutative tori, we prove that

Ш

(

A

)
≅
C
l

(
Λ
)
⊕
C
l

(
Λ
)

\Sha (\mathscr {A})\cong Cl~(\Lambda )\oplus Cl~(\Lambda )

or

Ш

(

A

)
≅

(

Z

/

2
k

Z

)

⊕
C

l

o
d
d

(
Λ
)
⊕
C

l

o
d
d

(
Λ
)

\Sha (\mathscr {A})\cong \left (\mathbf {Z}/2^k\mathbf {Z}\right ) \oplus Cl_{~\mathbf {odd}}~(\Lambda )\oplus Cl_{~\mathbf {odd}}~(\Lambda )

, where

C
l

(
Λ
)

Cl~(\Lambda )

is the ideal class group of a ring

Λ
\Lambda

associated to the K-theory of the non-commutative tori and

2
k

2^k

divides the order of

C
l

(
Λ
)

Cl~(\Lambda )

. The case of elliptic curves with complex multiplication is considered in detail.
Introduction
Authors: Frie Roger 
Published: May 2024

AbstractReflecting on the contemporary growth of antisemitism and racial hatred, the author introduces the twentieth century public intellectual and psychoanalyst, Erich Fromm, who wrote extensively about the dangers of human destructiveness, racial narcissism and fascism. Yet until now, Fromm’s own family history of the Holocaust and the impact it had on him and his work has remained unexplored. The Holocaust correspondence in Fromm’s family is introduced and Fromm’s life as a German Jewish refugee who escaped Germany in 1934 is examined. The author brings his own German family history to bear and explains that the Nazi past obligates us to educate about the Holocaust and take a stand against right wing extremism. The author suggests that Fromm’s life and writings have much to teach us for the present moment.
Cultivating Love and Hope
Authors: Frie Roger 
Published: May 2024

AbstractThis chapter considers the meanings inherent in Fromm’s elaborations on love and solidarity against the backdrop of war and genocide. It sheds light on the powerful parallels that exist between Fromm’s exploration of human connection and the letters that his aunts, Gertrud Brandt and Sophie Engländer, wrote shortly before their deportations and deaths. These ideas are expressed in Fromm’s best known work, The Art of Loving (1956), and in his belief that love is a necessary countervailing force to cruelty and destructiveness. It also draws on Fromm’s psychoanalytic writings, which are often overlooked and are the source from which much of his thinking about love and solidarity emerged. The book and the chapter conclude by considering the nature of one’s ethical obligation to others and the moral responsibilities that are associated with belonging to a perpetrator group or inheriting a perpetrator history. The chapter asks what can be learned from Fromm and the Holocaust correspondence when seeking to respond to the social and political crises, and the renewed threat of fascism in the modern age.
Invited commentary: mixing multiple imputation and bootstrapping for variance estimation
Authors: Li Catherine X , Zivich Paul N 
Published: May 2024

Abstract
Multiple imputation (MI) is commonly implemented to mitigate potential selection bias due to missing data. The accompanying article by Nguyen and Stuart (Am J Epidemiol. 2024;193(10):1470-1476) examines the statistical consistency of several ways of integrating MI with propensity scores. As Nguyen and Stuart noted, variance estimation for these different approaches remains to be developed. One common option is the nonparametric bootstrap, which can provide valid inference when closed-form variance estimators are not available. However, there is no consensus on how to implement MI and nonparametric bootstrapping in analyses. To complement Nguyen and Stuart’s article on MI and propensity score analyses, we review some currently available approaches on variance estimation with MI and nonparametric bootstrapping.
Outdoor workers’ perceptions of skin cancer prevention: a qualitative study
Authors: Ward Jeanne , Hardin-Fanning Frances , LaJoie Andrew Scott , Harris Lesley , Simpson Anna 
Published: May 2024

Abstract

Objectives
Outdoor workers are at increased risk for skin cancer and melanoma. This qualitative study aimed to explore outdoor workers’ perspectives and experiences of primary (i.e. sun protection) and secondary prevention, i.e. skin self-examination (SSE) of skin cancer.

Methods
Purposive, snowball, and theoretical sampling was used to recruit outdoor workers in Kentucky and Indiana. Semi-structured interviews via telephone or videoconference of approximately 45 min were conducted with interviewer probes and questions about perceptions of cancer risk, prevention, and screening techniques conducted, perceived barriers and facilitators, and preferences for health dissemination venues. The recordings were transcribed verbatim and de-identified. Analysis involved constructivist grounded theory coding strategies. Using peer debriefing and consensus building around themes, the researcher established a codebook for all interviews to utilize within Dedoose software for systematizing and organizing data.

Results
Eighteen interviews were conducted. Interviewees (N = 18) ranged in age from 35 to 78 yr, with 3 females. Outdoor industries included agriculture, maintenance, and grounds maintenance. Themes derived from the data showed the underlying factors and perceptions that influence outdoor workers to conduct primary and secondary cancer prevention activities. The level of alarm attributed to disease and the level of trust in information contribute to intentions to conduct activities. The intentions and trust toward healthcare institutions and providers drive the primary or secondary prevention behaviors. Cultural and contextual factors included masculinity and self-sufficiency, familial and occupational priorities, and community ties.

Conclusions
These data provide a basis for developing future communications and interventions to decrease skin cancer incidence in outdoor workers. They indicate that secondary prevention and building self-efficacy in conducting SSE should be emphasized in tandem or over primary skin cancer prevention methods in this population. Trusted local healthcare providers should primarily provide prevention information, and materials should utilize testimonials from the local community to best influence this population. Communications and training interventions are needed in this population to induce a proactive level of alarm about cancer and result in the performance of SSE.
FERREG: ferroptosis-based regulation of disease occurrence, progression and therapeutic response
Authors: Zhou Yuan , Chen Zhen , Yang Mengjie , Chen Fengyun , Yin Jiayi , Zhang Yintao , Zhou Xuheng , Sun Xiuna , Ni Ziheng , Chen Lu , Lv Qun , Zhu Feng , Liu Shuiping 
Published: May 2024

Abstract
Ferroptosis is a non-apoptotic, iron-dependent regulatory form of cell death characterized by the accumulation of intracellular reactive oxygen species. In recent years, a large and growing body of literature has investigated ferroptosis. Since ferroptosis is associated with various physiological activities and regulated by a variety of cellular metabolism and mitochondrial activity, ferroptosis has been closely related to the occurrence and development of many diseases, including cancer, aging, neurodegenerative diseases, ischemia–reperfusion injury and other pathological cell death. The regulation of ferroptosis mainly focuses on three pathways: system Xc−/GPX4 axis, lipid peroxidation and iron metabolism. The genes involved in these processes were divided into driver, suppressor and marker. Importantly, small molecules or drugs that mediate the expression of these genes are often good treatments in the clinic. Herein, a newly developed database, named ‘FERREG’, is documented to (i) providing the data of ferroptosis-related regulation of diseases occurrence, progression and drug response; (ii) explicitly describing the molecular mechanisms underlying each regulation; and (iii) fully referencing the collected data by cross-linking them to available databases. Collectively, FERREG contains 51 targets, 718 regulators, 445 ferroptosis-related drugs and 158 ferroptosis-related disease responses. FERREG can be accessed at https://idrblab.org/ferreg/.
Genotype sampling for deep-learning assisted experimental mapping of a combinatorially complete fitness landscape
Authors: Wagner Andreas 
Published: May 2024

Abstract

Motivation
Experimental characterization of fitness landscapes, which map genotypes onto fitness, is important for both evolutionary biology and protein engineering. It faces a fundamental obstacle in the astronomical number of genotypes whose fitness needs to be measured for any one protein. Deep learning may help to predict the fitness of many genotypes from a smaller neural network training sample of genotypes with experimentally measured fitness. Here I use a recently published experimentally mapped fitness landscape of more than 260 000 protein genotypes to ask how such sampling is best performed.

Results
I show that multilayer perceptrons, recurrent neural networks, convolutional networks, and transformers, can explain more than 90% of fitness variance in the data. In addition, 90% of this performance is reached with a training sample comprising merely ≈103 sequences. Generalization to unseen test data is best when training data is sampled randomly and uniformly, or sampled to minimize the number of synonymous sequences. In contrast, sampling to maximize sequence diversity or codon usage bias reduces performance substantially. These observations hold for more than one network architecture. Simple sampling strategies may perform best when training deep learning neural networks to map fitness landscapes from experimental data.

Availability and implementation
The fitness landscape data analyzed here is publicly available as described previously (Papkou et al. 2023). All code used to analyze this landscape is publicly available at https://github.com/andreas-wagner-uzh/fitness_landscape_sampling
Dine and dash: how trophic ecology and migration shape functional locomotory traits in clupeiform fishes
Authors: Finnegan Darby L , Egan Joshua P , Bloom Devin D 
Published: May 2024

Abstract
Understanding how interactions between multiple selective forces influence traits at the macroevolutionary scale is key to understanding adaptive landscapes. Diadromy, an extreme form of migration between marine and freshwater environments, is thought to require locomotory traits conducive to long-distance migration. Yet, other selective forces, such as predator avoidance, habitat use, and prey acquisition, are also likely to shape locomotory adaptation in fishes. We examined how diadromy and trophic ecology together influenced locomotory trait diversity across Clupeiformes, a clade of fishes containing high trophic diversity and numerous transitions to diadromy. We found that both diadromy and trophic ecology influenced the pattern and pace of trait evolution. Diadromous taxa rapidly evolved traits characterized by high cruising efficiency, but the extent to which diadromous and non-diadromous taxa differed depended on their trophic ecology. Macropredators showed greater differences in locomotory traits between diadromous and non-diadromous taxa than phytodetritivores and micropredators, suggesting that traits conducive to migration might be most costly to consumers of evasive prey. This work shows that simultaneously characterizing the roles of multiple ecological or life-history factors in phenotypic evolution can bring the topography of adaptive landscapes into sharper focus and provide a more holistic view of the forces driving patterns of trait evolution.
LncRNA UCA1 promotes vasculogenic mimicry by targeting miR-1-3p in gastric cancer
Authors: Lu Yida , Yang Bo , Shen Aolin , Yu Kexun , Ma MengDi , Li Yongxiang , Wang Huizhen 
Published: May 2024

Abstract
Long noncoding RNA urothelial carcinoma-associated 1 (UCA1) has been implicated in several tumors. UCA1 promotes cell proliferation, migration, and invasion of gastric cancer (GC) cells, but the molecular mechanism has not been fully elucidated. This study revealed the oncogenic effects of UCA1 on cell growth and invasion. Furthermore, UCA1 expression was significantly correlated with the overall survival of GC patients, and the clinicopathological indicators, including tumor size, depth of invasion, lymph node metastasis, and TNM stage. Additionally, miR-1-3p was identified as a downstream target of UCA1, which was negatively regulated by UCA1. MiR-1-3p inhibited cell proliferation and vasculogenic mimicry (VM), and induced cell apoptosis by upregulating BAX, BAD, and tumor suppressor TP53 expression levels. Moreover, miR-1-3p almost completely reversed the oncogenic effect caused by UCA1, including cell growth, migration, and VM formation. This study also confirmed that UCA1 promoted tumor growth in vivo. In this study, we also revealed the correlation between UCA1 and VM formation, which is potentially crucial for tumor metastasis. Meanwhile, its downstream target miR-1-3p inhibited VM formation in GC cells. In summary, these findings indicate that the UCA1/miR-1-3p axis is a potential target for GC treatment.
Inverse association between serum chloride levels and the risk of atrial fibrillation in chronic kidney disease patients
Authors: Gan Yangang , Nie Sheng , Pang Mingzhen , Huang Rong , Xu Hong , Liu Bicheng , Weng Jianping , Chunbo Chen , Liu Huafeng , Li Hua , Kong Yaozhong , Li Guisen , Wan Qijun , Zha Yan , Hu Ying , Xu Gang , Shi Yongjun , Zhou Yilun , Su Guobin , Tang Ying , Gong Mengchun , Hou Fan Fan , Yang Qiongqiong 
Published: May 2024

ABSTRACT

Background
Electrolyte abnormalities are common symptoms of chronic kidney disease (CKD), but previous studies have mainly focussed on serum potassium and sodium levels. Chloride is an important biomarker for the prognosis of various diseases. However, the relationship between serum chloride levels and atrial fibrillation (AF) in CKD patients is unclear.

Objective
In this study, we sought to determine the association between serum chloride homeostasis and AF in CKD patients.

Methods
In this retrospective cohort study, we included patients who met the diagnostic criteria for CKD in China between 2000 and 2021. Competing risk regression for AF was performed. The associations of the baseline serum chloride concentration with heart failure (HF) and stroke incidence were also calculated by competing risk regression. The association of baseline serum chloride levels with all-cause death was determined by a Cox regression model.

Results
The study cohort comprised 20 550 participants. During a median follow-up of 350 days (interquartile range, 123–730 days), 211 of the 20 550 CKD patients developed AF. After multivariable adjustment, every decrease in the standard deviation of serum chloride (5.02 mmol/l) was associated with a high risk for AF [sub-hazard ratio (sHR) 0.78, 95% confidence interval (CI) 0.65–0.94, P = .008]. These results were also consistent with those of the stratified and sensitivity analyses. According to the fully adjusted models, the serum chloride concentration was also associated with a high risk for incident HF (sHR 0.85, 95% CI 0.80–0.91, P &lt; .001), a high risk for incident stroke (sHR 0.87, 95% CI 0.81–0.94, P &lt; .001), and a high risk for all-cause death [hazard ratio (HR) 0.82, 95% CI 0.73–0.91, P &lt; .001].

Conclusion
In this CKD population, serum chloride levels were independently and inversely associated with the incidence of AF. Lower serum chloride levels were also associated with an increased risk of incident HF, stroke, and all-cause death.
Vulnerability Localization Based On Intermediate Code Representation and Feature Fusion
Authors: Zhu Chenguang , Wei Renzheng , Chen Liwei , Wu Tongshuai , Du Gewangzi , Shi Gang 
Published: May 2024

Abstract
Vulnerability localization can assist security professionals in vulnerability validation and analysis. This study proposes an intelligent vulnerability localization method based on fine-grained program representation and feature fusion. Firstly, we generate efficient fine-grained program representations of the program. This involves transforming the source code into intermediate code. We use abstract syntax tree characteristics to correspond to the points of interest of the intermediate code. We slice the intermediate code file based on the point of interest and program dependency relationships. Subsequently, we use the word2vec model to the vectorization of the intermediate code slices. Then, we propose a vulnerability localization framework based on a feature fusion method, which can better combine the advantages of bidirectional gate recurrent unit and convolutional neural network to capture the syntax and semantics of program representation. Through comparing different program representations, we have discovered that the fine-grained representation based on intermediate code in this study provides a more accurate portrayal of program semantics. By comparing various methods, the proposed feature fusion approach in this paper improves vulnerability localization. We also conducted a visualization display of vulnerability localization. Furthermore, we have validated the effectiveness of this method in localizing vulnerabilities across five common vulnerability types.
Wall shear stress measured with 4D flow CMR correlates with biomarkers of inflammation and collagen synthesis in mild-to-moderate ascending aortic dilation and tricuspid aortic valves
Authors: Hammaréus Filip , Trenti Chiara , Björck Hanna M , Engvall Jan , Lekedal Hanna , Krzynska-Trzebiatowska Aleksandra , Kylhammar David , Lindenberger Marcus , Lundberg Anna K , Nilsson Fredrik , Nilsson Lennart , Swahn Eva , Jonasson Lena , Dyverfeldt Petter 
Published: May 2024

Abstract

Aims
Understanding the mechanisms underlying ascending aortic dilation is imperative for refined risk stratification of these patients, particularly among incidentally identified patients, most commonly presenting with tricuspid valves. The aim of this study was to explore associations between ascending aortic haemodynamics, assessed using four-dimensional flow cardiovascular magnetic resonance imaging (4D flow CMR), and circulating biomarkers in aortic dilation.

Methods and results
Forty-seven cases with aortic dilation (diameter ≥ 40 mm) and 50 sex-and age-matched controls (diameter &lt; 40 mm), all with tricuspid aortic valves, underwent 4D flow CMR and venous blood sampling. Associations between flow displacement, wall shear stress (WSS), and oscillatory shear index in the ascending aorta derived from 4D flow CMR, and biomarkers including interleukin-6, collagen type I α1 chain, metalloproteinases (MMPs), and inhibitors of MMPs derived from blood plasma, were investigated. Cases with dilation exhibited lower peak systolic WSS, higher flow displacement, and higher mean oscillatory shear index compared with controls without dilation. No significant differences in biomarkers were observed between the groups. Correlations between haemodynamics and biomarkers were observed, particularly between maximum time-averaged WSS and interleukin-6 (r = 0.539, P &lt; 0.001), and maximum oscillatory shear index and collagen type I α1 chain (r = −0.575, P &lt; 0.001 in cases).

Conclusion
Significant associations were discovered between 4D flow CMR derived whole-cardiac cycle WSS and circulating biomarkers representing inflammation and collagen synthesis, suggesting an intricate interplay between haemodynamics and the processes of inflammation and collagen synthesis in patients with early aortic dilation and tricuspid aortic valves.