bluuebunny/crossref_metadata_2025 huggingface dataset:
Computer-aided diagnosis of early-stage Retinopathy of Prematurity in neonatal fundus images using artificial intelligence
Authors: Raja Sankari V M , Umapathy Snekhalatha
Published: November 2024

Retinopathy of Prematurity (ROP) is a retinal disorder affecting preterm babies, which can lead to permanent blindness without treatment. Early-stage ROP diagnosis is vital in providing optimal therapy for the neonates. The proposed study predicts early-stage ROP from neonatal fundus images using Machine Learning (ML) classifiers and Convolutional Neural Networks (CNN) based pre-trained networks. The characteristic demarcation lines and ridges in early stage ROP are segmented utilising a novel Swin U-Net. 2000 Scale Invariant Feature Transform (SIFT) descriptors were extracted from the segmented ridges and are dimensionally reduced to 50 features using Principal Component Analysis (PCA). Seven ROP-specific features, including six Gray Level Co-occurrence Matrix (GLCM) and ridge length features, are extracted from the segmented image and are fused with the PCA reduced 50 SIFT features. Finally, three ML classifiers, such as Support Vector Machine (SVM), Random Forest (RF), and k- Nearest Neighbor (k-NN), are used to classify the 50 features to predict the early-stage ROP from Normal images. On the other hand, the raw retinal images are classified directly into normal and early-stage ROP using six pre-trained classifiers, namely ResNet50, ShuffleNet V2, EfficientNet, MobileNet, VGG16, and DarkNet19. It is seen that the ResNet50 network outperformed all other networks in predicting early-stage ROP with 89.5% accuracy, 87.5% sensitivity, 91.5% specificity, 91.1% precision, 88% NPV and an Area Under the Curve (AUC) of 0.92. Swin U-Net Convolutional Neural Networks (CNN) segmented the ridges and demarcation lines with an accuracy of 89.7% with 80.5% precision, 92.6% recall, 75.76% IoU, and 0.86 as the Dice coefficient. The SVM classifier using the 57 features from the segmented images achieved a classification accuracy of 88.75%, sensitivity of 90%, specificity of 87.5%, and an AUC of 0.91. The system can be utilised as a point-of-care diagnostic tool for ROP diagnosis of neonates in remote areas.
Numerical study of runaway current impact on sawtooth oscillations in tokamaks
Authors: MA 马 Ruirui 瑞瑞 , ZHAO 赵 Chen 忱 , ZHOU 周 Yao 尧 , LIU 刘 Chang 畅
Published: November 2024

This study investigates the influence of runaway current in runaway plasmas on the dynamics of sawtooth oscillations and resultant loss of runaway electrons (RE) using the 3D magnetohydrodynamic (MHD) code M3D-C

(Jardin et al 2012 J. Comput. Sci. Discovery
6 014002). Using an HL-2A-like equilibrium, we confirm that in the linear phase, the impact of REs on resistive internal kink instabilities is consistent with previous research. In the nonlinear phase, as the runaway current fully replaces the plasmas current, we observe a significant suppression of sawtooth oscillations, with the first sawtooth cycle occurring earlier compared to the case without runaway current. Following the first sawtooth collapse, plasma current density, runaway current density, and safety factor (

) flatten within the

surface, albeit displaying fine structures. Subsequently, the growing high torodial (

) and poloidal (

) mode number modes disrupt the magnetic surfaces, leading to the loss of REs outside the

surface, while minimally affecting the majority of REs well-confined within it. Thus, in the current model, the physical processes associated with the presence of sawtooth oscillations do not effectively dissipate runaway current, as REs are assumed to be collisionless. In addition, the final profile of runaway current density exhibits increased steepening near the

surface in contrast to the initial profile, displaying a distinctive corrugated inhomogeneity influenced by the growing fluctuation of the

component. Finally, detailed convergence tests are conducted to validate the numerical simulations.
Unlocking mode programming with multi-plane light conversion using computer-generated hologram optimisation
Authors: Rothe Stefan , Barbosa Fabio A , Czarske Jürgen W , Ferreira Filipe M
Published: November 2024

Programmable optical devices provide performance enhancement and flexibility to spatial multiplexing systems enabling transmission of tributaries in high-order eigenmodes of spatially-diverse transmission media, like multimode fibre (MMF). Wavefront shaping with spatial light modulators (SLMs) facilitates scalability of the transmission media by allowing for channel diagonalization and quasi-single-input single-output operation. Programmable mode multiplexing configurations like multi-plane light conversion (MPLC) utilise the SLM and offer the potential to simultaneously launch an arbitrary subset of spatial tributaries in any N-mode MMF. Such programmable optical processor would enable the throughput of space-division multiplexing systems to be progressively increased by addressing a growing number of tributaries over one MMF and in this way meet a growing traffic demand—similarly to the wavelength-division multiplexing evolution path. Conventionally, MPLC phasemasks are calculated using the wavefront matching algorithm (WMA). However, this method does not exploit the full potential of programmable mode multiplexers. We show, that computer-generated hologram algorithms like direct search enable significant improvement compared to the traditional WMA-approach. Such gains are enabled by tailored cost functions with dynamic constraints concerning insertion loss as well as mode extinction ratio. We show that average mode extinction ratio can be greatly improved by as much as

≈

15

dB

at the expense of insertion loss deterioration of less than

3

dB

. One particular feature of programmable mode multiplexers is the adaptability to optimised transmission functions. Besides conventional linearly polarized modes transmission, we employ our approach on Schmidt modes, which are spatial eigenchannels with minimum crosstalk derived from a measured transmission matrix.
Advanced multi-nozzle electrohydrodynamic printing: mechanism, processing, and diverse applications at micro/nano-scale
Authors: Li Yin , Zhang Guangming , Zhang Jinrun , Song Daosen , Guo Chenxu , Zhou Wei , Fu Zhiguo , Zhu Xiaoyang , Wang Fei , Duan Yongqing , Dong Jingyan , Lan Hongbo
Published: November 2024

Electrohydrodynamic (EHD) jet printing represents a novel micro/nano-scale additive manufacturing process that utilises a high-voltage induced electric field between the nozzle and the substrate to print micro/nanoscale structures. EHD printing is particularly advantageous for the fabrication on flexible or non-flat substrates and of large aspect ratio micro/nanostructures and composite multi-material structures. Despite this, EHD printing has yet to be fully industrialised due to its low throughput, which is primarily caused by the limitations of serial additive printing technology. The parallel multi-nozzle array-based process has become the most promising option for EHD printing to achieve large-scale printing by increasing the number of nozzles to realise multichannel parallel printing. This paper reviews the recent development of multi-nozzle EHD printing technology, analyses jet motion with multi-nozzle, explains the origins of the electric field crosstalk effect under multi-nozzle and discusses several widely used methods for overcoming it. This work also summarises the impact of different process parameters on multi-nozzle EHD printing and describes the current manufacturing process using multi-nozzle as well as the method by which they can be realised independently. In addition, it presents an additional significant utilisation of multi-nozzle printing aside from enhancing single-nozzle production efficiency, which is the production of composite phase change materials through multi-nozzle. Finally, the future direction of multi-nozzle EHD printing development is discussed and envisioned.
Fabrication of 3D-printed coiled PCL microfibrous bundles using alginate-based biocomposites for bone tissue engineering applications
Authors: Pei Mohan , Hwangbo Hanjun , Kim GeunHyung
Published: November 2024

Biomedical scaffold fabrication has seen advancements in mimicking the native extracellular matrix through intricate three-dimensional (3D) structures conducive to tissue regeneration. Coiled fibrous scaffolds have emerged as promising substrates owing to their ability to provide unique topographical cues. In this study, coiled poly (ϵ-caprolactone) (PCL) fibrous bundles were fabricated using an alginate-based composite system, and processed with 3D printing. The unique structure was obtained through the die-swell phenomenon related to the release of residual stresses from the printed strut, thereby transforming aligned PCL fibers into coiled structures. The effects of printing parameters, such as pneumatic pressure and nozzle moving speed, on fiber morphology were investigated to ensure a consistent formation of coiled PCL fibers. The resulting coiled PCL fibrous scaffold demonstrated higher activation of mechanotransduction signaling as well as upregulation of osteogenic-related genes in human adipose stem cells (hASCs), supporting its potential in bone tissue engineering.
Optimal balanced-norm error estimate of the LDG method for reaction-diffusion problems II: The two-dimensional case with layer-upwind flux
Authors: Cheng Yao , Wang Xuesong , Stynes Martin
Published: November 2024

A singularly perturbed reaction-diffusion problem posed on the unit square in

R

2

\mathbb {R}^2

is solved numerically by a local discontinuous Galerkin (LDG) finite element method. Typical solutions of this class of 2D problems exhibit boundary layers along the sides of the domain; these layers generally cause difficulties for numerical methods. Our LDG method handles the boundary layers by using a Shishkin mesh and also introducing the new concept of a “layer-upwind flux”—a discrete flux whose values are chosen on the fine mesh (which lies inside the boundary layers) in the direction where the layer weakens. On the coarse mesh, one can use a standard central flux. No penalty terms are needed with these fluxes, unlike many other variants of the LDG method. Our choice of discrete flux makes it feasible to derive an optimal-order error analysis in a balanced norm; this norm is stronger than the usual energy norm and is a more appropriate measure for errors in computed solutions for singularly perturbed reaction-diffusion problems. It will be proved that the LDG method is usually convergent of order

O
(
(

N

−
1

ln
⁡
N

)

k
+
1

)

O((N^{-1}\ln N)^{k+1})

in the balanced norm, where

N
N

is the number of mesh intervals in each coordinate direction and tensor-product piecewise polynomials of degree 

k
k

in each coordinate variable are used in the LDG method. This result is the first of its kind for the LDG method applied to this class of problem and is optimal for convergence on a Shishkin mesh. Its sharpness is confirmed by numerical experiments.
Stability, convergence, and pressure-robustness of numerical schemes for incompressible flows with hybrid velocity and pressure
Authors: Botti Lorenzo , Botti Michele , Di Pietro Daniele , Massa Francesco
Published: November 2024

In this work we study the stability, convergence, and pressure-robustness of discretization methods for incompressible flows with hybrid velocity and pressure. Specifically, focusing on the Stokes problem, we identify a set of assumptions that yield inf-sup stability as well as error estimates which distinguish the velocity- and pressure-related contributions to the error. We additionally identify the key properties under which the pressure-related contributions vanish in the estimate of the velocity, thus leading to pressure-robustness. Several examples of existing and new schemes that fit into the framework are exhibited, and extensive numerical validation of the theoretical properties is provided.
Complex-valued solutions of the mKdV equations in generalized Fourier-Lebesgue spaces
Authors: Chen Zijun , Guo Zihua , Huang Chunyan
Published: November 2024

We study the complex-valued solutions to the Cauchy problem of the modified Korteweg-de Vries equation on the real line. To study the low-regularity problems, we introduce a generalized Fourier-Lebesgue space

M
^

r
,
q

s

(

R

)

\widehat {M}^{s}_{r,q}(\mathbb {R})

that unifies the modulation spaces and the Fourier-Lebesgue spaces. We then prove sharp local well-posedness results in this space by perturbation arguments using

X

s
,
b

X^{s,b}

-type spaces. Our results improve the previous one in Grünrock and Vega [Trans. Amer. Math. Soc. 361 (2009), pp. 5681–5694].
Thick embeddings of graphs into symmetric spaces via coarse geometry
Authors: Barrett Benjamin , Hume David , Guth Larry , Portnoy Elia
Published: November 2024

We prove estimates for the optimal volume of thick embeddings of finite graphs into symmetric spaces, generalising results of Kolmogorov-Barzdin and Gromov-Guth for embeddings into Euclidean spaces. We distinguish two very different behaviours depending on the rank of the non-compact factor. For rank at least 2, we construct thick embeddings of

N
N

-vertex graphs with volume

C
N
ln
⁡
(
1
+
N
)

CN\ln (1+N)

and prove that this is optimal. For rank at most

1
1

we prove lower bounds of the form

c

N
a

cN^a

for some (explicit)

a
>
1

a>1

which depends on the dimension of the Euclidean factor and the conformal dimension of the boundary of the non-compact factor. The main tool is a coarse geometric analogue of a thick embedding called a coarse wiring, with the key property that the minimal volume of a thick embedding is comparable to the “minimal volume” of a coarse wiring for symmetric spaces of dimension at least

3
3

. In the appendix it is proved that for each

k
≥
3

k\geq 3

every bounded degree graph admits a coarse wiring into

R

k

\mathbb {R}^k

with volume at most

C

N

1
+

1

k
−
1

CN^{1+\frac {1}{k-1}}

. As a corollary, the same upper bound holds for real hyperbolic space of dimension

k
+
1

k+1

and in both cases this result is optimal.
Residue formula for logarithmic foliations along a divisor with isolated singularities and applications
Authors: da Silva Machado Diogo
Published: November 2024

In this work we prove a Baum-Bott type formula for non-compact complex manifolds of the form

X
~

=
X
−
D

\widetilde {X} = X - D

, where

X
X

is a complex compact manifold and

D
D

is an analytic divisor contained in

X
X

with isolated singularities. As applications, we provide some results related to Poincaré’s problem for foliations. We obtain a Poincaré inequality in terms of the degree and other characters associated to invariant hypersurface

D
D

. Moreover we show that the non-negativity of the GSV-index is the obstruction to the Poincaré problem in any even dimension. Other applications are also obtained beyond the scope of the Poincaré’s problem.
Generalized partial-slice monogenic functions
Authors: Xu Zhenghua , Sabadini Irene
Published: November 2024

The two function theories of monogenic and of slice monogenic functions have been extensively studied in the literature and were developed independently; the relations between them, e.g. via Fueter mapping and Radon transform, have been studied. The main purpose of this article is to describe a new function theory which includes both of them as special cases. This theory allows to prove nice properties such as the identity theorem, a Representation Formula, the Cauchy (and Cauchy-Pompeiu) integral formula, the maximum modulus principle, a version of the Taylor series and Laurent series expansions. As a complement, we shall also offer two approaches to these functions via generalized partial-slice functions and via global differential operators. In addition, we discuss the conformal invariance property under a proper group of Möbius transformations preserving the partial symmetry of the involved domains.
On matrix Kloosterman sums and Hall–Littlewood polynomials
Authors: Zelingher Elad
Published: November 2024

We prove an identity relating twisted matrix Kloosterman sums to modified Hall–Littlewood polynomials evaluated at the roots of the characteristic polynomial associated to a twisted Kloosterman sheaf. This solves a conjecture of Erdélyi and Tóth [Algebra Number Theory 18 (2024), pp. 2247–2308, Conjecture 5.9].
Algebraic Montgomery-Yang problem and smooth obstructions
Authors: Jo Woohyeok , Park Jongil , Park Kyungbae
Published: November 2024

Let

S
S

be a rational homology complex projective plane with quotient singularities. The algebraic Montgomery-Yang problem conjectures that the number of singular points of

S
S

is at most three if its smooth locus is simply-connected. In this paper, we leverage results from the study of smooth 4-manifolds, including the Donaldson diagonalization theorem and Heegaard Floer correction terms, to establish additional conditions on

S
S

. As a result, we eliminate the possibility of a rational homology complex projective plane of specific types with four singularities. Moreover, we identify large families encompassing infinitely many types of singularities that satisfy the orbifold BMY inequality, a key property in algebraic geometry, yet are obstructed from being a rational homology complex projective plane due to smooth conditions. Additionally, we discuss computational results related to this problem, offering new insights into the algebraic Montgomery-Yang problem.
Science of Science
Authors: Krauss Alexander
Published: November 2024

How do we drive new knowledge and science? What are their present boundaries? And how can we improve science? We still do not understand these essential questions about science well, even though science is at the foundation of modern society. The field of science of science can provide answers to these foundational questions. The central challenge of the field is integrating the different empirical and theoretical knowledge across disciplines into a holistic field and uncovering the general mechanism driving science across fields. This is the first book to offer an integrated framework for the science of science and thus aims to provide a comprehensive understanding of the foundations and limits of science. The book integrates 14 scientific fields and illustrates how our evolved mind (that enables us to observe, experiment and solve problems) makes doing science possible but also shapes what and how we observe. Our scientific methods and instruments (such as statistics and telescopes) enable us to study a much larger range of phenomena but also have constraints to how we measure them. Institutions and funding shape what knowledge we produce and how we evaluate our evidence, among other influences. By integrating the fields together, we are able to identify the common mechanism that underpins the different factors studied across all these fields: our powerful scientific methods and instruments. The book explains how the sophisticated scientific tools we develop are the main driving force for creating new knowledge and advancing science. This methodological toolbox of ours sets the scope and present limits of what we can know and what is possible in science—while economic, social and historical influences help shape what we study within that scope and those limits. The book offers a unifying theory for the field of science of science—the new-methods-drive-science theory. By better understanding the foundations of science we will also show how we can reduce the constraints and biases that we and our scientific methods and instruments face to advance science and push its present boundaries. This book is written in an easily accessible way for readers interested in understanding how science works.
Describing Science of Science
Authors: Krauss Alexander
Published: November 2024

Here we describe the existing landscape of the 14 disparate fields studying science and outline what an integrated science of science can look like by providing a framework for the field. Science of science involves scientists doing science to understand science. When studying science itself, we thus practice the activity being studied. We use scientific evidence to explain what science is and how it works. Different researchers studying science use a different method and unit of analysis and thus study different features of science, including publications and citations, paradigm shifts in scientific theories, criteria for evaluating scientific theories, the social practices of scientists, and so on. Disciplinary isolation has led to simplified and at times contradictory views. Here we illustrate a unified field, without disciplinary divisions, which can be defined as: the field of science of science is the study of science, and especially the foundations, limits and advancement of science and scientific methods, that integrates methods and evidence from across the natural, behavioural and social sciences.
Biology of Science
Authors: Krauss Alexander
Published: November 2024

What are the evolutionary origins of science and how can they help us understand how we do science today? This chapter illustrates that, like other animals, our ancestors evolved abilities for vision and other senses that enable us to perceive the world. Species like ours require making observations and acquiring knowledge about the world to be able to survive and meet basic needs. Using tools to solve problems, human and non-human animals have a toolkit that they acquire through social learning and experimenting. Our evolution lays the basis for our methodological abilities that we use to be able to do science.
Archaeology of Science
Authors: Krauss Alexander
Published: November 2024

Archaeological artefacts that include increasingly sophisticated tools developed by early humans provide evidence for the origin of science. They offer historical evidence of the evolution of our methodological abilities to reason and acquire knowledge that are needed to construct those artefacts and to do science today. We humans have evolved abilities to observe, solve problems, experiment, categorise, reason causally and test ideas or hypotheses. These, together, account for our methodological abilities of the mind we use to be able to develop knowledge and make sense of the world around us. Using these abilities, early humans such as Homo erectus and Neanderthals created complex tools such as hand axes, and early humans also later developed fire-hardened spears and controlled fire, which required making mental representations, inferences and predictions. These evolved human abilities have enabled us to start science and are commonly used in contemporary scientific practice.
Psychology of Science
Authors: Krauss Alexander
Published: November 2024

When we do science and acquire knowledge about the world, our mind also faces psychological biases. We face limited mental resources, time constraints and incomplete information, so we use simplified heuristics like rules of thumb or shortcuts when reasoning. We for example often rely on existing assumptions and evidence when formulating a hypothesis or applying a given scientific method rather than questioning and testing them every time. In general, our mind has largely evolved to be able to absorb and process a limited amount of information and then make quick assumptions, decisions and conclusions based on that (incomplete) information. We think fast, are habit-based and use heuristics most of the time, which can result in unconscious biases. Our reasoning is influenced not only by psychological biases but also by personality traits.
Sociology of Science
Authors: Krauss Alexander
Published: November 2024

If the cognitive abilities of children at birth a few hundred or even thousand years ago and today are likely not very different, what can explain the large differences in their theories of the world as adults? While our mind’s methodological abilities to observe, solve problems and experiment are a precondition of science and we have used them more systematically over time, changes in broader demographic, social and economic factors have fostered developing vast knowledge and methods. There were hundreds of scientists a few centuries ago. Today, there are about nine million full-time scientists worldwide. Demographic growth and complex social organisation have been crucial for the scientific community to grow and for greater collaboration, cumulative knowledge and methodological development. Doing science has become an increasingly complex social activity. We are also not disinterested and detached observers of reality but guided by institutions, shaped by scientific norms and motivated by values that can influence our research.
Economics of Science
Authors: Krauss Alexander
Published: November 2024

We can foster science through economies of scale, a reward system, science policy and targeted research funding. As society becomes more productive, diversified and efficient in providing goods and services, more individuals can dedicate themselves to scientific activities. Science can function like an economy: just as a growing and more specialised labour force generally develops more diversified goods and technologies, a growing and more specialised scientific community generally develops more diversified knowledge and methods. Economies of scale and agglomeration facilitate greater division of labour across and within scientific fields—and thus greater methodological diversity and knowledge. Public institutions also help plan, finance and manage how we produce, distribute and use knowledge.
Methodology of Science
Authors: Krauss Alexander
Published: November 2024

Over our species’ history, we evolved methodological abilities of the mind (observation, problem solving and experimentation) that we use together with increasingly complex methods developed using these abilities (controlled experimentation, statistics and X-ray methods). Science has always been grounded in these evolved methodological abilities (our universal methodological toolbox) that have enabled us to develop vast bodies of knowledge by creating sophisticated methods and tools (our adaptive methodological toolbox). As we face constraints when using our evolved abilities to do science, we design tools to reduce these constraints and greatly extend our evolved mind. Such constraints are cognitive (such as limited sensory abilities, cognitive bandwidth and memory), social (such as cultural values, norms and interests), geographic (such as differences across contexts that require conducting studies in multiple contexts) and so forth. Controlled experimentation and randomisation are for example used across fields, from biomedicine to psychology, to reduce human biases in designing, implementing and analysing studies. Magnetic resonance imaging (MRI) enables us to detect phenomena like magnetic fields and radio waves that we do not have sensory receptors for. Electron microscopes vastly enhance our visual capability and enable us to perceive miniscule objects using the wavelength of an electron. Yet our tools of science can also face constraints in how we represent and model the dynamic character of phenomena using them and they have a set scope with which we can design, implement and evaluate experiments, and interpret results.
Scientometrics and Network Science
Authors: Krauss Alexander
Published: November 2024

Science describes and explains the world through research articles and books that are organised into scientific fields. Scientometricians including network scientists analyse this scientific literature. To do so, they rely on the indicators of citations and publication counts to study issues such as research productivity, team collaborations, career dynamics, networks of scientists and institutions, and novelty in science. They use large-scale data (big data) and network analysis and search for patterns in such data. That is scientometrics in a nutshell. Scientometrics is of interest to all researchers as citations and publication counts largely determine whether researchers get research grants, academic jobs and promotions. Most current measures of scientific impact and success still use citations. Our current reward system in science is deeply embedded in this metric.
Statistics and Mathematics of Science
Authors: Krauss Alexander
Published: November 2024

Statistics and mathematics are arguably the two most widely used methods across science and they have fundamentally transformed how we do science and how we understand the world. Statistics involves the collection, analysis and interpretation of data, whereas most scientific theories are formalised using the mathematical methods of algebra and calculus, such as the equation E = mc2. In many fields of science, inferential statistics has become synonymous with the scientific method. Modern statistics has revolutionised empirical sciences by enabling us to study the world with vast amounts of data in more complex ways, conduct and analyse larger-scale experiments and generate causal evidence. We apply statistical methods to study basically any phenomenon in science, from cells and viruses in populations, to planets, economic markets and science itself. Yet a central limitation of statistical and mathematical methods is that many aspects of the world cannot be easily studied using them since they cannot be captured well quantitatively. There are also a number of problems that commonly face statistical studies and affect the quality of our evidence. These involve small samples and small effect sizes in studies, p-hacking and statistical standards including the statistical significance level that researchers apply in their studies. Such statistical issues have contributed to a replication crisis in science.
Science of Science: An Integrated and Methods-Driven Understanding of Science
Authors: Krauss Alexander
Published: November 2024

A unified account of the field of science of science is presented here that enables a more comprehensive understanding of the origins, foundations and limits of science—and thus a holistic picture of science. This is done by synthesising the evidence and approaches across the 14 discussed subfields of science of science—namely evidence across the natural, behavioural and social sciences. What enables and constrains science cannot be explained from a single disciplinary perspective alone. Taking such a holistic approach represents the most comprehensive understanding we have of science for the following reason: the range of disciplinary approaches apply different methods and focus on different features of science, and there is coherence across the independent strands of evidence, in particular in the role of methodological features in shaping science. Our methodological toolbox is at the centre of science and enables us to do and advance science in new ways.
Conclusion and Implications
Authors: Krauss Alexander
Published: November 2024

Viewing the field of science of science through an integrated lens can provide answers to fundamental questions about science: its origins, foundations and limits and how to push those limits. This book aims to offer a foundation for the integrated field of science of science by combining methods and evidence from across the natural, behavioural and social sciences. Science of science, conceived here as an integrated field, provides a unified understanding of science and how to improve science by identifying the abilities and conditions that drive and constrain science. Our methodological toolbox underlies the different factors across disciplinary perspectives. Four main implications are outlined here of this meta-approach to studying science, including the need to establish a society, journals, conferences and interdisciplinary institutes, better train researchers studying science and conduct research in a more interdisciplinary way, better understand the constraints we face in science to better reduce them, and adopt a broader set of empirical methods to better address foundational questions about science.
Changing perspective from being to becoming—An alternative approach to language development and speaker categorization based on longitudinal data
Authors: Stopfner Maria
Published: November 2024

In the face of transnational mobility and migration, globally networked communities and super-diverse social environments, traditional research practices of speaker categorization such as the distinction between native and non-native speakers, first, second, and third language users and mono-, bi-, and pluri-/multilinguals, which rest on the assumption of categorical differences between types of speakers and the general stability of speaker categories as biographical fact, are increasingly called into question. Critical voices point out that in real life, differences between language users turn out to be fuzzy, gradient, and continuous, and that conventional speaker categorizations are conceptualized from a monolingual perspective, providing grounds for discriminatory practices. Based on a longitudinal study design, the paper aims to offer an alternative quantitative approach for researchers who are dissatisfied with common practices of speaker categorization and wish to shift perspective to a more comprehensive way of studying language development within communities. The analysis draws on the results of c-tests for German, Italian, and English that were specifically designed for the study and administered to the same students (n = 170) in their first and final year at lower secondary school.
Phospholipid dynamics in Aspergillus species: relations between biological membrane composition and cellular morphology
Authors: Iwama Ryo
Published: November 2024

Biological membranes, primarily composed of phospholipid bilayers, are essential structures that compartmentalize the cell from the extracellular environment. The biosynthesis and regulation of membrane lipids have been extensively studied in model organisms such as Saccharomyces cerevisiae and mammalian cells. However, our understanding of biological membrane regulation in filamentous fungi, some of which are significant in medicine, pharmacy, and agriculture, remains limited. This minireview provides a comprehensive overview of the latest knowledge, focusing on filamentous fungi of Aspergillus species. Recent progress in understanding dynamic changes in membrane lipid profiles, driven by improvements in analytical techniques for lipidomics, is also presented. Furthermore, known that the cell morphology of filamentous fungi is closely linked to its harmful and beneficial characteristics, the influence of membrane composition on cell morphology is discussed. The integration of these findings will further enhance our understanding of the biological functions of membranes in filamentous fungi.
Ultrasound S-detect system can improve diagnostic performance of less experienced radiologists in differentiating breast masses: a retrospective dual-centre study
Authors: Du Liwen , Liu Hongli , Cai Mengjun , Pan Jiazhen , Zha Hailing , Nie Chenlei , Lin Minjia , Li Cuiying , Zong Min , Zhang Bo
Published: November 2024

Objective

To compare the performance of radiologists when assisted by an S-detect system with that of radiologists or an S-detect system alone in diagnosing breast masses on US images in a dual-centre setting.

Methods

US images were retrospectively identified 296 breast masses (150 benign, 146 malignant) by investigators at 2 medical centres. Six radiologists from the 2 centres independently analysed the US images and classified each mass into categories 2-5. The radiologists then re-reviewed the images with the use of the S-detect system. The diagnostic value of radiologists alone, S-detect alone, and radiologists + S-detect were analysed and compared.

Results

Radiologists had significantly decreased the average false negative rate (FNR) for diagnosing breast masses using S-detect system (−10.7%) (P < .001) and increased the area under the receiver operating characteristic curve (AUC) from 0.743 to 0.788 (P < .001). Seventy-seven out of 888 US images from 6 radiologists in this study were changed positively (from false positive to true negative or from false negative to true positive) with the S-detect, whereas 39 out of 888 US images were altered negatively.

Conclusion

Radiologists had better performance for the diagnosis of malignant breast masses on US images with an S-detect system than without.

Advances in knowledge

The study reported an improvement in sensitivity and AUC particularly for low to intermediate-level radiologists, involved cases and radiologists from 2 different centres, and compared the diagnostic value of using S-detect system for masses of different sizes.
Recurrence-free survival prediction for anal squamous cell carcinoma after chemoradiotherapy using planning CT-based radiomics model
Authors: Tang Shanshan , Wang Kai , Hein David , Lin Gloria , Sanford Nina N , Wang Jing
Published: November 2024

Objectives

Approximately 30% of non-metastatic anal squamous cell carcinoma (ASCC) patients will experience recurrence after chemoradiotherapy (CRT), and currently available clinical variables are poor predictors of treatment response. We aimed to develop a model leveraging information extracted from radiation pretreatment planning CT to predict recurrence-free survival (RFS) in ASCC patients after CRT.

Methods

Radiomics features were extracted from planning CT images of 96 ASCC patients. Following pre-feature selection, the optimal feature set was selected via step-forward feature selection with a multivariate Cox proportional hazard model. The RFS prediction was generated from a radiomics-clinical combined model based on an optimal feature set with 5 repeats of nested 5-fold cross validation. The risk stratification ability of the proposed model was evaluated with Kaplan-Meier analysis.

Results

Shape- and texture-based radiomics features significantly predicted RFS. Compared to a clinical-only model, radiomics-clinical combined model achieves better performance in the testing cohort with higher concordance index (0.80 vs 0.73) and AUC (0.84 vs 0.78 for 1-year RFS, 0.84 vs 0.79 for 2-year RFS, and 0.85 vs 0.81 for 3-year RFS), leading to distinctive high- and low-risk of recurrence groups (P < .001).

Conclusions

A treatment planning CT based radiomics and clinical combined model had improved prognostic performance in predicting RFS for ASCC patients treated with CRT as compared to a model using clinical features only.

Advances in knowledge

The use of radiomics from planning CT is promising in assisting in personalized management in ASCC. The study outcomes support the role of planning CT-based radiomics as potential imaging biomarker.
Artificial intelligence research in radiation oncology: a practical guide for the clinician on concepts and methods
Authors: Hoebers Frank J P , Wee Leonard , Likitlersuang Jirapat , Mak Raymond H , Bitterman Danielle S , Huang Yanqi , Dekker Andre , Aerts Hugo J W L , Kann Benjamin H
Published: November 2024

The use of artificial intelligence (AI) holds great promise for radiation oncology, with many applications being reported in the literature, including some of which are already in clinical use. These are mainly in areas where AI provides benefits in efficiency (such as automatic segmentation and treatment planning). Prediction models that directly impact patient decision-making are far less mature in terms of their application in clinical practice. Part of the limited clinical uptake of these models may be explained by the need for broader knowledge, among practising clinicians within the medical community, about the processes of AI development. This lack of understanding could lead to low commitment to AI research, widespread scepticism, and low levels of trust. This attitude towards AI may be further negatively impacted by the perception that deep learning is a “black box” with inherently low transparency. Thus, there is an unmet need to train current and future clinicians in the development and application of AI in medicine. Improving clinicians’ AI-related knowledge and skills is necessary to enhance multidisciplinary collaboration between data scientists and physicians, that is, involving a clinician in the loop during AI development. Increased knowledge may also positively affect the acceptance and trust of AI. This paper describes the necessary steps involved in AI research and development, and thus identifies the possibilities, limitations, challenges, and opportunities, as seen from the perspective of a practising radiation oncologist. It offers the clinician with limited knowledge and experience in AI valuable tools to evaluate research papers related to an AI model application.
BS O03 - One-stage conversion of Adjustable Gastric band (AGB) to One-anastomosis Gastric Bypass (cOAGB) versus Sleeve Gastrectomy (cSG): A single-center experience with a short and mid-term Follow-up
Authors: Hassan Basma , Awad Philobater
Published: November 2024

Background

Laparoscopic adjustable gastric band was a common bariatric procedure . However; due to its failure rate some patients sought another revisional surgery. In which, we compared two of the most common Bariatric metabolic surgery (BMS) performed nowadays: the laparoscopic sleeve gastrectomy and laparoscopic one- anastomosis gastric bypass.

Method

A prospective cohort study was conducted from June 2020 to June 2022 at a single medical center, which included 77 patients undergoing single-stage conversion to (cOAGB) vs (cSG). Patients were reassessed for weight loss, associated medical problems remission and post-operative complications at 6, 12, and 18 months.

Results

Group (I) was 43 patients who underwent cOAGB and Group (II) was 34 patients who underwent cSG. The BMI was calculated post-operative at three visits. Both groups had no statistically significant values at 6 and 12 months follow-up. However, patients who underwent cOAGB after 18 months of follow-up achieved lower BMI than those who underwent cSG . Regarding EBWL% there was a statistically significant difference between the two groups after 6, 12 and 18 months follow-up. Regarding associated medical problems remission with follow-up 18 months post-operative , there were no statistically significant differences between the two groups

Conclusion

This study suggests that the conversion of LAGB to either cOAGB or cSG could be feasibly performed in a single-stage operation. cOAGB had a significant difference as regards the weight loss results than cSG among the mid-term follow-up. However, there is no significant difference in the postoperative complications and the resolution of the co-morbidities. Therefore, cOAGB could provide a reliable alternative but needs to be substantiated in future long-term studies.
OGC SO15 - Utility of radiological re-staging following neo-adjuvant chemotherapy and its impact on oncological outcomes in resectable gastric adenocarcinoma
Authors: Ngo Vivien , D’Souza Joel , Alam Mushfique , Stephens Nathan , Pritchard Mark
Published: November 2024

Background

The current perioperative chemotherapy regimen that comprises the multimodal treatment strategy for gastric cancer consists of Fluorouracil, Leucovorin, Oxaliplatin, and Docetaxel. Despite improvement in outcomes at a population level, real-world data suggests that ≤40% of patients show a poor/no response to the neoadjuvant phase of treatment. Identification of these poor/non-responders may facilitate a re-evaluation of their treatment strategy and prevent potentially futile surgery. Radiological re-staging following neoadjuvant treatment is routinely performed despite its debatable accuracy and benefits. This study aimed to define the accuracy of radiological re-staging and its impact on survival following neoadjuvant treatment for resectable GC.

Method

Patients with resectable gastric cancer who completed 4 cycles of neoadjuvant FLOT and underwent resectional surgery with curative intent between 2018 and 2022 were retrospectively identified. All patients were clinically staged with gastroscopy, CT and staging laparoscopy. The index radiological/clinical stage at diagnosis was compared to the radiological re-staging following neoadjuvant treatment. Patient were re-staged with either a CT or PET-CT. Both were then compared with the final pathological stage to assess for correlation between the radiological and pathological stage. A survival analysis was then performed to evaluate the impact of radiological-pathological staging discrepancy on overall survival

Results

A total of 65 consecutive patients met the inclusion criteria of this study. On comparison of the index clinical stage with the radiological re-stage post-neoadjuvant treatment, 71% had concordant stages, 25% were downstaged, and 4% were upstaged. On comparison of the index clinical stage with the final pathological stage, 35% had concordant stages, 38% were upstaged and 27% were down staged (Cohen kappa = -0.224, 95% CI -0.390, -0.058). Discrepancy between clinical stage and radiological re-stage did not influence survival. However, discrepancy between clinical and pathological stage highlighted survival differences where upstaged patients had reduced survival (p = 0.018).

Conclusion

The accuracy of clinical staging compared to final pathological staging in the setting of aggressive tumour biology remains undefined. Radiological re-staging following neoadjuvant treatment proves to be an unreliable tool for assessing treatment response and does not predict long-term survival outcomes. These findings highlight the importance of accurate staging and the need for more precise methods of evaluating treatment response. This may enhance decision-making, individualise treatment regimens, and improve patient outcomes.
BN SO07 - Percutaneous cholecystostomy in patients with severe acute calculous cholecystitis. What next? An analysis of 102 cases
Authors: Ragatha Ram , Di Mauro Davide , Khalil Ibraheem , Jones Rebecca , Reece-Smith Alex , Wajed Saj
Published: November 2024

Background

Percutaneous cholecystostomy (PC) can be a life-saving treatment for patients presenting with fulminant acute calculous cholecystitis (ACC). In the case of those who make a good recovery and are fit for surgery, PC is often advocated. However, in those who are higher risk for surgery, there is currently no strong consensus regarding further management. The aim of this study was to evaluate the long-term outcomes of PC and interval LC versus PC alone in patients with ACC.

Method

We conducted a single-centre retrospective case-control evaluation of the outcomes of patients who have undergone a PC due to severe ACC, comparing those who have gone on to have an interval LC versus those who had PC only. The primary outcomes were the rate of readmissions with recurrent biliary disease and late mortality.

Results

While the rate of readmissions did not differ between groups (p= 0.583), in the surgical cohort most recurrent gallstone events occurred before LC. ASA score >2 and Tokyo grade 3 were significant positive predictors of all-cause mortality (95% CI 1.6 to 12.6, OR 4.5, p=0.004, and 95% CI 1.2 to 12.2, OR 3.8, p=0.027, respectively). Surgery was found to be a negative predictor of mortality (95% CI 0.04 to 0.5, OR 0.2, p=0.003).

Conclusion

Those who do not go on to have their gallbladder removed after PC, face significantly worse outcomes. Every effort should be made to optimise these patients to facilitate operative management.