bluuebunny/crossref_metadata_2025_split huggingface dataset:
Raman and autofluorescence spectroscopy for in situ identification of neoplastic tissue during surgical treatment of brain tumors
Authors: Uckermann Ortrud , Ziegler Jonathan , Meinhardt Matthias , Richter Sven , Schackert Gabriele , Eyüpoglu Ilker Y. , Hijazi Mido M. , Krex Dietmar , Juratli Tareq A. , Sobottka Stephan B. , Galli Roberta 
Published: August 2024

Abstract
Purpose
Raman spectroscopy (RS) is a promising method for brain tumor detection. Near-infrared autofluorescence (AF) acquired during RS provides additional useful information for tumor identification and was investigated in comparison with RS for delineating brain tumors in situ.

Methods
Raman spectra were acquired together with AF in situ within the solid tumor and at the tumor border during routine brain tumor surgeries (218 spectra; glioma WHO II-III, n = 6; GBM, n = 10; metastases, n = 10; meningioma, n = 3). Tissue classification for tumor identification in situ was trained on ex vivo data (375 spectra; glioma/GBM patients, n = 20; metastases, n = 11; meningioma, n = 13; and epileptic hippocampi, n = 4).

Results
Both in situ and ex vivo data showed that AF intensity in brain tumors was lower than that in border regions and normal brain tissue. Moreover, a positive correlation was observed between the AF intensity and the intensity of the Raman band corresponding to lipids at 1437 cm− 1, while a negative correlation was found with the intensity of the protein band at 1260 cm− 1. The classification of in situ AF and RS datasets matched the surgeon’s evaluation of tissue type, with correct rates of 0.83 and 0.84, respectively. Similar correct rates were achieved in comparison to histopathology of tissue biopsies resected in selected measurement positions (AF: 0.80, RS: 0.83).

Conclusions
Spectroscopy was successfully integrated into existing neurosurgical workflows, and in situ spectroscopic data could be classified based on ex vivo data. RS confirmed its ability to detect brain tumors, while AF emerged as a competitive method for intraoperative tumor delineation.
Linearity of the Co-moving Velocity
Authors: Hansen Alex 
Published: August 2024

AbstractThe co-moving velocity is a new variable in the description of immiscible two-phase flow in porous media. It is the saturation-weighted average over the derivatives of the seepage velocities of the two immiscible fluids with respect to saturation. Based on analysis of relative permeability data and computational modeling, it has been proposed that the co-moving velocity is linear when plotted against the derivative of the average seepage velocity with respect to the saturation, the flow derivative. I show here that it is enough to demand that the co-moving velocity is characterized by an additive parameter in addition to the flow derivative to be linear. This has profound consequences for relative permeability theory as it leads to a differential equation relating the two relative permeabilities describing the flow. I present this equation together with two solutions.
Exploring multiple phases and first-order phase transitions in Kármán Vortex Street
Authors: Li Xu , Xiang Xing , Xue Tingting , Wang Limin , Chen Xiaosong 
Published: August 2024

Abstract
Kármán Vortex Street, a fascinating phenomenon of fluid dynamics, has intrigued the scientific community for a long time. Many researchers have dedicated their efforts to unraveling the essence of this intriguing flow pattern. Here, we apply the lattice Boltzmann method with curved boundary conditions to simulate flows around a circular cylinder and study the emergence of Kármán Vortex Street using the eigen microstate approach, which can identify phase transition and its order-parameter. At low Reynolds number, there is only one dominant eigen microstate W1 of laminar flow. At Re
c
1
= 53.6, there is a phase transition with the emergence of an eigen microstate pair W2,3 of pressure and velocity fields. Further at Re
c
2
. = 56, there is another phase transition with the emergence of two eigen microstate pairs W4,5 and W6,7. Using the renormalization group theory of eigen microstate, both phase transitions are determined to be first-order. The two-dimensional energy spectrum of eigen microstate for W1, W2,3 after Rec
1, W4–7 after Re
c
2
exhibit −5/3 power-law behavior of Kolnogorov’s K41 theory. These results reveal the complexity and provide an analysis of the Kármán Vortex Street from the perspective of phase transitions.
Assessment of groundwater quality using hydrochemical process, GIS and multivariate statistical analysis at central Rif, North Morocco
Authors: Benyoussef Said , Arabi Mourad , El Yousfi Yassine , Makkaoui Mohamed , Gueddari Hicham , El Ouarghi Hossain , Abdaoui Abdellali , Ghalit Mohammad , Zegzouti Younes Filali , Azirar Maryam , Himi Mahjoub , Alitane Abdennabi , Chahban Mohamed , Boughrous Ali Ait 
Published: August 2024

AbstractThis study investigated groundwater in the central Rif region of northern Morocco by analysing 55 water sampling points to assess its physicochemical and hydrogeochemical properties. Through hydrochemical analysis, GIS spatial exploration, and multivariate statistical analysis, a direct correlation was found between EC, TDS, and major ions, influencing overall water mineralization. The key findings included pH levels ranging from 6.10 to 8.52, EC from 828 to 4581 μS/cm, and varying concentrations of Ca2+, Mg2+, Na+, K+, HCO2–, Cl–, N–NO2–, and SO42–. Notably, TDS and TH ranged from 647.19–3609.36 mg/L and 64.23–1051.24 mg/L, respectively, with a significant portion of samples exceeding WHO guidelines, particularly chloride (61.81%), sulfate (92.72%), and nitrate (12.72%) samples. The Piper diagram highlights sodium chlorides (Na–Cl) as the predominant chemical facies (70.9%), while the Gibbs diagram emphasizes the impact of evaporation on water chemistry dynamics. This study revealed the complex influence of geological and anthropogenic factors on groundwater quality, potentially leading to seawater intrusion in coastal aquifers. The observed high mineralization and hardness levels, in addition to mild alkalinity, pose public health risks, underscoring the need for continuous monitoring and sustainable management practices in coastal groundwater management to protect human health and the environment.
The Moral Turing Test: a defense
Authors: Bohn Einar Duenger 
Published: August 2024

AbstractIn this paper, I raise the question whether an artificial intelligence can act morally. I first sketch and defend a general picture of what is at stake in this question. I then sketch and defend a behavioral test, known as the Moral Turing Test, as a good sufficiency test for an artificial intelligence acting morally. I end by discussing some general anticipated objections.
Multimodal music datasets? Challenges and future goals in music processing
Authors: Christodoulou Anna-Maria , Lartillot Olivier , Jensenius Alexander Refsum 
Published: August 2024

AbstractThe term “multimodal music dataset” is often used to describe music-related datasets that represent music as a multimedia art form and multimodal experience. However, the term “multimodality” is often used differently in disciplines such as musicology, music psychology, and music technology. This paper proposes a definition of multimodality that works across different music disciplines. Many challenges are related to constructing, evaluating, and using multimodal music datasets. We provide a task-based categorization of multimodal datasets and suggest guidelines for their development. Diverse data pre-processing methods are illuminated, highlighting their contributions to transparent and reproducible music analysis. Additionally, evaluation metrics, methods, and benchmarks tailored for multimodal music processing tasks are scrutinized, empowering researchers to make informed decisions and facilitating cross-study comparisons.
Predictive modelling of metabolic syndrome in Ghanaian diabetic patients: an ensemble machine learning approach
Authors: Acheampong Emmanuel , Adua Eric , Obirikorang Christian , Anto Enoch Odame , Peprah-Yamoah Emmanuel , Obirikorang Yaa , Asamoah Evans Adu , Opoku-Yamoah Victor , Nyantakyi Michael , Taylor John , Buckman Tonnies Abeku , Yakubu Maryam , Afrifa-Yamoah Ebenezer 
Published: August 2024

Abstract
Objectives
The burgeoning prevalence of cardiometabolic disorders, including type 2 diabetes mellitus (T2DM) and metabolic syndrome (MetS) within Africa is concerning. Machine learning (ML) techniques offer a unique opportunity to leverage data-driven insights and construct predictive models for MetS risk, thereby enhancing the implementation of personalised prevention strategies. In this work, we employed ML techniques to develop predictive models for pre-MetS and MetS among diabetic patients.

Methods
This multi-centre cross-sectional study comprised of 919 T2DM patients. Age, gender, novel anthropometric indices along with biochemical measures were analysed using BORUTA feature selection and an ensemble majority voting classification model, which included logistic regression, k-nearest neighbour, Gaussian Naive Bayes, Gradient boosting classification, and support vector machine.

Results
Distinct metabolic profiles and phenotype clusters were associated with MetS progression. The BORUTA algorithm identified 10 and 16 significant features for pre-MetS and MetS prediction, respectively. For pre-MetS, the top-ranked features were lipid accumulation product (LAP), triglyceride-glucose index adjusted for waist-to-height ratio (TyG-WHtR), coronary risk (CR), visceral adiposity index (VAI) and abdominal volume index (AVI). For MetS prediction, the most influential features were VAI, LAP, waist triglyceride index (WTI), Very low-density cholesterol (VLDLC) and TyG-WHtR. Majority voting ensemble classifier demonstrated superior performance in predicting pre-MetS (AUC = 0.79) and MetS (AUC = 0.87).

Conclusion
Identifying these risk factors reveals the complex interplay between visceral adiposity and metabolic dysregulation in African populations, enabling early detection and treatment. Ethical integration of ML algorithms in clinical decision-making can streamline identification of high-risk individuals, optimize resource allocation, and enable precise, tailored interventions.
Mathematical modeling of Ebola using delay differential equations
Authors: Raza Ali , Ahmed Nauman , Rafiq Muhammad , Akgül Ali , Cordero Alicia , Torregrosa Juan R. 
Published: August 2024

AbstractNonlinear delay differential equations (NDDEs) are essential in mathematical epidemiology, computational mathematics, sciences, etc. In this research paper, we have presented a delayed mathematical model of the Ebola virus to analyze its transmission dynamics in the human population. The delayed Ebola model is based on the four human compartments susceptible, exposed, infected, and recovered (SEIR). A time-delayed technique is used to slow down the dynamics of the host population. Two significant stages are analyzed in the said model: Ebola-free equilibrium (EFE) and Ebola-existing equilibrium (EEE). Also, the reproduction number of a model with the sensitivity of parameters is studied. Furthermore, the local asymptotical stability (LAS) and global asymptotical stability (GAS) around the two stages are studied rigorously using the Jacobian matrix Routh–Hurwitz criterion strategies for stability and Lyapunov function stability. The delay effect has been observed in the model in inverse relation of susceptible and infected humans (it means the increase of delay tactics that the susceptibility of humans increases and the infectivity of humans decreases eventually approaches zero which means that Ebola has been controlled into the population). For the numerical results, the Euler method is designed for the system of delay differential equations (DDEs) to verify the results with an analytical model analysis.
Characterization and differences of acoustic signals response of semi-circular red sandstone under combined monotonous and cyclic loadings
Authors: Zou Quanle , Chen Chunmei , Chen Zihan , Peng Kang , Lv Hong , Zhan Jinfei 
Published: August 2024

AbstractAfter underground coal mining, rocks are often subjected to tensile damage by the interaction of dynamic and static loadings. The process of rock fracture development under dynamic and static loadings will be released in the form of acoustic energy to form an acoustic signal. In addition, the acoustic signals in dynamic loading differ from that in static loading. Therefore, this study conducted three-point bending experiments with continuous dynamic loading and dynamic–static coupling loading on semi-circular red sandstone specimens. The acoustic signals during red sandstone specimens’ tensile damage were monitored in real-time. The results show that red sandstone’s tensile strength and deformation are enhanced under dynamic–static coupling loading. The red sandstone has a more effective acoustic emission hit rate, energy rate, and r during tensile damage under continuous dynamic loading. In dynamic loading, macroscopic fractures are developed in red sandstone, which has few acoustic emission events but releases strong acoustic signals. In static loading, the pores inside the red sandstone are compacted, the rock particles are rearranged, and the tiny fractures are closed, and its acoustic emission events are many but low in energy. In addition, the rock particles in the front area of the static loading fracture are tightly cemented, which increases the difficulty of separating the rock particles in the front area of the fracture under dynamic loading. Then weakening the red sandstone fracture development process and suppressing its acoustic signals. The research results provide more insight into the differences in tensile damage processes in red sandstone under the interaction of dynamic and static loadings.
On the interpretability of quantum neural networks
Authors: Pira Lirandë , Ferrie Chris 
Published: August 2024

AbstractInterpretability of artificial intelligence (AI) methods, particularly deep neural networks, is of great interest. This heightened focus stems from the widespread use of AI-backed systems. These systems, often relying on intricate neural architectures, can exhibit behavior that is challenging to explain and comprehend. The interpretability of such models is a crucial component of building trusted systems. Many methods exist to approach this problem, but they do not apply straightforwardly to the quantum setting. Here, we explore the interpretability of quantum neural networks using local model-agnostic interpretability measures commonly utilized for classical neural networks. Following this analysis, we generalize a classical technique called LIME, introducing Q-LIME, which produces explanations of quantum neural networks. A feature of our explanations is the delineation of the region in which data samples have been given a random label, likely subjects of inherently random quantum measurements. We view this as a step toward understanding how to build responsible and accountable quantum AI models.
Stability analysis for the anisotropic curve shortening flow of planar networks
Authors: Gößwein Michael , Novaga Matteo , Pozzi Paola 
Published: August 2024

AbstractIn this article we consider the anisotropic curve shortening flow for a planar network of three curves which meet at a triple junction. We show that the anisotropic energy fulfills a Łojasiewicz–Simon gradient inequality from which we derive a stability result for the evolution. Precisely, we show that, for initial data which are close to the energy minimizer, the flow exists globally and converges to the minimizer.
The Problematisation of Young People Within Existing Housing-Related Policy in Queensland
Authors: Keen Lilly , Newcomb Michelle 
Published: August 2024

AbstractMore young people are experiencing homelessness and housing stress in Australia than ever before, with policy responses failing to address a current housing and cost-of-living crisis. Of particular concern when considering increasing rates of youth homelessness and housing stress is the absence of research examining existing policy. This research was undertaken in the Australian state of Queensland and contributes to addressing this gap in knowledge by utilising Carol Bacchi’s (2009) ‘What’s the Problem Represented to be?’ approach to policy analysis to examine three state policies, namely Towards Ending Homelessness for Young Queenslanders 2022–2027, the Queensland Housing Strategy 2017–2027, and the Queensland Youth Strategy. A range of discourses were found which position young people as lacking knowledge and skills to obtain housing. Emphasis is also placed on education, training, and employment as solutions to youth housing issues rather than a genuine focus on empowering young people through policy and practice initiatives. The findings of this research mirror existing discourses found in global conversations about youth homelessness and housing stress and contribute to a growing knowledge base around the importance of engaging young people in decision making within public policy and social reform.
Associations of hair cortisol levels with violence, poor mental health, and harmful alcohol and other substance use among female sex workers in Nairobi, Kenya
Authors: Panneh Mamtuti , Ding Qingming , Kabuti Rhoda ,   The Maisha Fiti study champions, Bradley John , Ngurukiri Polly , Kungu Mary , Abramsky Tanya , Pollock James , Beksinska Alicja , Shah Pooja , Irungu Erastus , Gafos Mitzy , Seeley Janet , Weiss Helen A. , Elzagallaai Abdelbaset A. , Rieder Michael J. , Kaul Rupert , Kimani Joshua , Beattie Tara 
Published: August 2024

AbstractViolence, poor mental health, and harmful substance use are commonly experienced by female sex workers (FSWs) in sub-Saharan Africa, all of which are associated with increased HIV susceptibility. We aimed to investigate the associations between violence, poor mental health and harmful alcohol/substance use with hair cortisol concentration (HCC) levels as a potential biological pathway linking the experiences of these stressors and HIV vulnerability. We used the baseline data of the Maisha Fiti study of FSWs in Nairobi, Kenya. Participants reported recent violence, poor mental health, and harmful alcohol/substance use. Hair samples proximal to the scalp were collected to measure cortisol levels determined by ELISA. We analysed the data of 425 HIV-negative respondents who provided at least 2 cm of hair sample. The prevalence of recent violence was 89.3% (physical 54.6%; sexual 49.4%; emotional 77.0% and financial 66.5%), and 29.1% had been arrested due to sex work. 23.7% of participants reported moderate/severe depression, 11.6% moderate/severe anxiety, 13.5% PTSD and 10.8% recent suicidal thoughts and/or attempts. About half of the participants (48.8%) reported recent harmful alcohol and/or other substance use. In multivariable linear regression analyses, both physical and/or sexual violence (adjusted geometric mean ratio (aGMR) = 1.28; 95% CI 1.01–1.62) and harmful alcohol and/or other substance use (aGMR = 1.31; 95% CI 1.03–1.65) were positively and independently associated with increased HCC levels. Findings suggest a role of violence and substance use in elevated HCC levels, which could increase HIV risk due to cortisol-related T cell activation. However, longitudinal and mechanistic studies are needed to confirm this hypothesis.
THINKING ALOUD: THE SOLILOQUY CYCLE
Authors: Simaku Thomas 
Published: August 2024

AbstractBeginning with Soliloquy I for solo violin in 1998, the author has been engaged in creating a series of highly virtuosic solo pieces for various instruments. Each piece presents a different character, yet all are framed by a single protagonist who narrates in different languages.This article focuses particularly on analyses of Soliloquies II, VI, VII, VIII and IX, but also offers a discussion of the genesis of and processes involved in the whole cycle, which now embraces instruments from every section of the orchestra; the most recent, Soliloquy IX, for solo trumpet, was written in 2022. The suitability of the title Soliloquy is also considered; this article in turn could itself be considered a soliloquy.
PROPORTION AND SYMMETRY AS MUTUAL ANTAGONISTS IN TUNING: SOME QUARTER-TONE RESOURCES
Authors: Bates Joe 
Published: August 2024

AbstractQuarter-tones have the dubious honour of being the microtonal default in Western art music, yet they have been of little recent interest to those most involved with extended intonation. Other microtonal equal divisions have appealed as pragmatic approximations of consonant just-intonation intervals, something that quarter-tones do not offer. This article proposes that quarter-tones can be valued in a different way, for their ability to generate symmetrical harmonic resources that divide the fourth and fifth as the tritone does the octave. These resources are offered as examples of a broader aesthetic of symmetry, which is contrasted with an aesthetic of proportion. These antagonistic principles are explored through the case of the ever problematic tritone, illustrating how proportion and symmetry are best understood using the symbolic resources of just intonation and equal temperament respectively. Drawing on the work of Robert Hasegawa, Georg Friedrich Haas and Ivan Wyschnegradsky, the article argues for a hybrid approach that embraces both just intonation and equal temperament.
HABITUS, RESISTANCE AND THE PRODUCTION OF MUSICAL MEANING
Authors: Dell Niamh 
Published: August 2024

AbstractThis article defines and explores the concept of ‘resistance’ as a source of musical meaning in performance. Using Pierre Bourdieu's concept of ‘habitus’ as a framework, I examine my musical habitus: the embodied, internalised ways I play my instrument and think about music, which reflect my extensive musical histories and the fields in which these histories have taken place. Resistance arises in practice when this habitus is undermined. When the types of musicking undertaken circumvent my habituated understanding of acceptable performance and performative roles, it manifests as a pull towards more familiar modes of musical engagement. Making specific reference to resistance experienced in the development and performance of Alex Harker's Drift Shadow (2021), for solo oboe and electronics, the article outlines the ways in which my subjective relationship to my instrument and my role as a performer produce particular understandings of a work that can then nuance the way I play the piece.
Microbial Metabolism and Environmental Controls of Acetate Cycling in the Northwest Pacific Ocean
Authors: Mao Shi‐Hai , Zhou Zhen , Yan Shi‐Bo , Xu Gao‐Bin , Li Xiao‐Jun , Zhang Hong‐Hai , Yang Gui‐Peng , Zhuang Guang‐Chao 
Published: August 2024

AbstractMicrobial acetate metabolism is an important part of marine carbon cycling. We present a comprehensive study to constrain microbial acetate metabolism and its regulation in surface seawater of the northwest Pacific Ocean. We found that acetate oxidation (rate constant k: 0.016–0.506 day−1) accounted for 77.6%–99.4% of the total microbial acetate uptake, suggesting that acetate was predominantly used as a microbial energy source. Acetate also served as a significant biomass carbon source, as reflected by the elevated contribution of acetate assimilation to bacterial carbon production. Acetate turnover was largely influenced by water mass mixing and nutrient conditions. Atmospheric deposition was a source of acetate in surface water and this process can also impact the microbial acetate uptake. Microbial utilization of acetate could account for up to 25.9% of the bacterial carbon demand, suggesting the significant role of acetate metabolism in microbial carbon cycling in the open ocean.