bluuebunny/crossref_metadata_2025_split huggingface dataset:
An investigation of punching shear in flat slabs with spherical voids using the finite element method
Authors: Schimanowski Eric Renã Zavitzki , Campos Filho Américo , Lazzari Bruna Manica , Lazzari Paula Manica 
Published: November 2024

AbstractFlat slabs with voids allow for the reduction of the structure's self‐weight by removing concrete from regions of the cross‐section subjected to low stresses. However, the presence of voids impacts the behavior of these structures, especially under punching loads, and few studies have assessed the impact of different parameters on voided slabs. Thus, this study validated numerical modeling developed in the ANSYS software, using the finite element method, based on 17 experimental slabs from the literature. The numerical simulation indicated a good approximation of the deformation behavior of the structure, as well as a similar mode of failure. Once validated, the model evaluated different parameters in spherical voided slabs. The results showed significant impacts on the rupture load, ductility, or stiffness when varying the void's presence, position, diameter, concrete properties, slab thickness, flexural reinforcement ratio, and shear reinforcement. In voided slabs, the critical situation occurred when inserting the spheres in a region very close to the column, which reduced the rupture load by about half, when compared to a solid slab.
Data, Aesthetics, and Visualizations of Deep Time
Authors: Tamborini Marco 
Published: November 2024

AbstractThis chapter accomplishes a phenomenology of deep time visualizations. It examines the power and limits of a series of visual devices used in paleontology and geology to access, and eventually work with the earth’s deep past. First, I discuss how paleontologists visualize and sort data in the field; second, I examine the practices used to illustrate and validate knowledge about extinct animals; third, I explore what function visualizations play in supporting the transition between data collection and the possible explanation of global biological phenomena such as the estimation of diversity through geological time; fourth, I inquire into the role of the computer; and fifth, I discuss the recent intersection between paleontology and different kinds of new technologies such as augmented and visual reality and robotics, both to shed light on some aspects of the past and to generate new research questions. In conclusion, I reflect on the intersection between earth science visual cultures and knowledge production. In particular, I point out the function of knowledge circulation and in between scientists in the production of visual devices as well as the importance of aesthetics for cooperative research projects and knowledge production in the earth sciences.
Closing the gap in domain adaptation for semantic segmentation: a time-aware method
Authors: Serrat Joan , Gómez Jose Luis , López Antonio M. 
Published: November 2024

Abstract
Semantic segmentation models need a large number of images to be effectively trained but manual annotation of such images has a high cost. Active domain adaptation addresses this problem by pretraining the model with a synthetically generated dataset and then fine-tuning it with a few selected label annotations (the “budget”) on real images to account for the domain shift. Previous works annotate a percentage of either individual pixels or whole target images. We argue that the first is infeasible in practice, and the second spends part of the budget on classes that the pretrained model may have already learned well. We propose a method based on the annotation of regions computed by Segment Anything, a recently introduced foundation model for class-agnostic image segmentation. The key idea is to assign a ground truth label to each of a tiny subset of regions, those for which the model is more uncertain. In order to increase the number of annotated regions we propagate the ground truth labels to most similar regions according to a hierarchical clustering algorithm that uses the features learned by the pretrained model. Our method outperforms the state-of-the-art on the GTA5 to Cityscapes benchmark by using fewer annotations, almost closing the gap between the synthetically pre-trained model and that obtained with full supervision of the real images. Furthermore, we present competitive results for budgets less than 1% of samples and also for a larger and more challenging target dataset, Mapillary Vistas.
Oka tubes in holomorphic line bundles
Authors: Forstnerič Franc , Kusakabe Yuta 
Published: November 2024

AbstractLet (E, h) be a semipositive hermitian holomorphic line bundle on a compact complex manifold X with $$\dim X>1$$

dim
X
>
1

. Assume that for each point $$x\in X$$

x
∈
X

there exists a divisor $$D\in |E|$$

D
∈
|
E
|

in the complete linear system determined by E whose complement $$X\setminus D$$

X
\
D

is a Stein neighbourhood of x with the density property. Then, the disc bundle $$\Delta _h(E)=\{e\in E:|e|_h<1\}$$

Δ
h

(
E
)

=

{
e
∈
E
:
|
e
|

h

<
1
}

is an Oka manifold while $$D_h(E)=\{e\in E:|e|_h>1\}$$

D
h

(
E
)

=

{
e
∈
E
:
|
e
|

h

>
1
}

is a Kobayashi hyperbolic domain. In particular, the zero section of E admits a basis of Oka neighbourhoods $$\{|e|_h<c\}$$

{
|
e

|
h

<
c
}

with $$c>0$$

c
>
0

. We show that this holds if X is a rational homogeneous manifold of dimension $$>1$$

>
1

. This class of manifolds includes complex projective spaces, Grassmannians, and flag manifolds. This phenomenon contributes to the heuristic principle that Oka properties are related to metric positivity of complex manifolds.
Impact of intensity standardisation and ComBat batch size on clinical-radiomic prognostic models performance in a multi-centre study of patients with glioblastoma
Authors: Fatania Kavi , Frood Russell , Mistry Hitesh , Short Susan C. , O’Connor James , Scarsbrook Andrew F. , Currie Stuart 
Published: November 2024

Abstract
Purpose
To assess the effect of different intensity standardisation techniques (ISTs) and ComBat batch sizes on radiomics survival model performance and stability in a heterogenous, multi-centre cohort of patients with glioblastoma (GBM).

Methods
Multi-centre pre-operative MRI acquired between 2014 and 2020 in patients with IDH-wildtype unifocal WHO grade 4 GBM were retrospectively evaluated. WhiteStripe (WS), Nyul histogram matching (HM), and Z-score (ZS) ISTs were applied before radiomic feature (RF) extraction. RFs were realigned using ComBat and minimum batch size (MBS) of 5, 10, or 15 patients. Cox proportional hazards models for overall survival (OS) prediction were produced using five different selection strategies and the impact of IST and MBS was evaluated using bootstrapping. Calibration, discrimination, relative explained variation, and model fit were assessed. Instability was evaluated using 95% confidence intervals (95% CIs), feature selection frequency and calibration curves across the bootstrap resamples.

Results
One hundred ninety-five patients were included. Median OS = 13 (95% CI: 12–14) months. Twelve to fourteen unique MRI protocols were used per MRI sequence. HM and WS produced the highest relative increase in model discrimination, explained variation and model fit but IST choice did not greatly impact on stability, nor calibration. Larger ComBat batches improved discrimination, model fit, and explained variation but higher MBS (reduced sample size) reduced stability (across all performance metrics) and reduced calibration accuracy.

Conclusion
Heterogenous, real-world GBM data poses a challenge to the reproducibility of radiomics. ComBat generally improved model performance as MBS increased but reduced stability and calibration. HM and WS tended to improve model performance.

Key Points
QuestionComBat harmonisation of RFs and intensity standardisation of MRI have not been thoroughly evaluated in multicentre, heterogeneous GBM data.
Findings The addition of ComBat and ISTs can improve discrimination, relative model fit, and explained variance but degrades the calibration and stability of survival models.
Clinical relevanceRadiomics risk prediction models in real-world, multicentre contexts could be improved by ComBat and ISTs, however, this degrades calibration and prediction stability and this must be thoroughly investigated before patients can be accurately separated into different risk groups.
Scar endometriosis, a form of abdominal wall endometriosis–a neglected obstetrical complication?
Authors: Gruber T. M. , Lange K. , Ebeling G. S. , Henrich W. , Mechsner S. 
Published: November 2024

Abstract
Background
Scar endometriosis (EM) is defined by the presence of endometrial-like tissue outside the uterine cavity within the scar region after abdominal or pelvic surgery. It is a form of abdominal wall EM.
This systematic review addresses the question of whether women after cesarean delivery (CD) are more frequently affected by scar EM than women after other pelvic surgical procedures. The primary aim is to analyze the distribution of previous operations in patients with scar EM. Secondarily, symptoms, diagnosis, and treatment are described.

Methods
A systematic literature search in MEDLINE (Pubmed) was performed. Twelve studies were included.

Results
The terminology of scar EM is unspecific and the descriptions are, therefore, of limited comparability among authors. In 64–96%, patients with scar EM had a history of CD, followed by laparoscopy, laparotomy, and episiotomy. The main symptoms were pain, often cyclical, and the presence of local swelling. For diagnosis ultrasound, CT scan and MR imaging were used. All patients had undergone surgical resection and the diagnosis was confirmed.

Conclusion
Most often scar EM develops after CD. Diagnosis and treatment are often delayed. As an objective classifications system is missing, we propose a simple objective descriptive tool for abdominal wall EM.
Lower semicontinuity of monotone functionals in the mixed topology on $C_{b}$
Authors: Nendel Max 
Published: November 2024

AbstractThe main result of this paper characterises the continuity from below of monotone functionals on the space $C_{b}$

C
b

of bounded continuous functions on an arbitrary Polish space as lower semicontinuity in the mixed topology. In this particular situation, the mixed topology coincides with the Mackey topology for the dual pair $(C_{b},\mathrm{ca})$
(

C
b

,
ca
)
, where $\mathrm{ca}$
ca
denotes the space of all countably additive signed Borel measures of finite variation. Hence lower semicontinuity in the mixed topology is for convex monotone maps $C_{b}\to \mathbb{R}$

C
b

→
R
equivalent to a dual representation in terms of countably additive measures. Such representations are of fundamental importance in finance, e.g. in the context of risk measures and superhedging problems. Based on the main result, regularity properties of capacities and dual representations of Choquet integrals in terms of countably additive measures for 2-alternating capacities are studied. Moreover, a well-known characterisation of star-shaped risk measures on $L^{\infty }$

L
∞

is transferred to risk measures on $C_{b}$

C
b

. In a second step, the paper provides a characterisation of equicontinuity in the mixed topology for families of convex monotone maps. As a consequence, for every convex monotone map on $C_{b}$

C
b

taking values in a locally convex vector lattice, continuity in the mixed topology is equivalent to continuity on norm-bounded sets.
Electrodeposition of metals into nano/micropores of templates: a type of electrochemistry under confinement (review)
Authors: Bograchev D. A. , Kabanova T. B. , Davydov A. D. 
Published: November 2024

AbstractElectrodeposition of metals into nanopores of templates represents a crucial area of study within the field of confinement-controlled electrochemistry. This review addresses the templated synthesis of nanocomposites (nonmetallic hard templates with one-dimensional cylindrical nanopores filled with metal or semiconductor) and single nanowires and nanotubes obtained by template dissolution. The focus is on the influence of electrochemical conditions such as electrolyte composition, electrodeposition regimes, and template characteristics on the morphological and physical properties of the resulting nanostructures. Additionally, this review introduces the theoretical modeling of mass transfer in templated electrodeposition, which is critical for understanding and optimizing the pore-filling processes and the uniformity of nanostructure formation. The potential applications of these nanostructures in fields such as electronics, optoelectronics, and catalysis are also discussed, highlighting their significant implications for advancing nanotechnology and materials science.
Estimation of 3-D hydraulic conductivity fields from fictive grain-size distributions derived from 3-D geological modeling
Authors: Albarrán-Ordás Alberto , Zosseder Kai 
Published: November 2024

AbstractHydraulic conductivity (K) is a crucial parameter in hydrogeology but is highly heterogeneous and anisotropic due to variations in sediment texture, making its large-scale estimation challenging. Traditional laboratory and empirical methods based on grain-size distribution (GSD) analysis from limited data provide local K measurements, resulting in a poor representation of aquifer heterogeneity. In contrast, pumping tests estimate an integrated K value over a section of the aquifer within the cone of depression but still lack the spatial resolution needed to reveal detailed variations in K across larger aquifer extents. In this study, the Di models method was used to simulate local GSD in three-dimensional (3-D) detrital systems. The focus was to explore the potential to estimate K through simulated particle-size fractions derived from a 3-D geological model of the City of Munich. By employing log-cubic interpolation, a complete and accurate representation of the fictive GSD enabled the application of multiple empirical relationships for K estimation. The resulting 3-D K fields preserved the variability in K within each aquifer system. When averaged for each separate aquifer system across different lateral extents, i.e., 50–150 and 550 m, the predicted K values showed success rates of 44–47% with deviations of at least one order of magnitude in 15–19% of cases when compared to 364 K values derived from pumping-test data. The results highlight the ability of the approach to successfully estimate K while accounting for spatial heterogeneity, suggesting its potential for groundwater modeling, aquifer yield assessments and groundwater heat pump system design.
Quantifying low rank approximations of third order symmetric tensors
Authors: Hu Shenglong , Sun Defeng , Toh Kim-Chuan 
Published: November 2024

AbstractIn this paper, we present a method to certify the approximation quality of a low rank tensor to a given third order symmetric tensor. Under mild assumptions, best low rank approximation is attained if a control parameter is zero or quantified quasi-optimal low rank approximation is obtained if the control parameter is positive. This is based on a primal-dual method for computing a low rank approximation for a given tensor. The certification is derived from the global optimality of the primal and dual problems, and is characterized by easily checkable relations between the primal and the dual solutions together with another rank condition. The theory is verified theoretically for orthogonally decomposable tensors as well as numerically through examples in the general case.
Co-production of sustainability indicators in a vulnerable South American agricultural frontier
Authors: Piquer-Rodríguez María , Aragón Roxana , Pacheco Silvia , Malizia Sebastián , Zunino Hernán 
Published: November 2024

AbstractDeforestation linked to agricultural activities is a major sustainability concern. Planning towards sustainable agricultural landscapes in the (sub-)tropics requires indicators that capture the many aspects of social-ecological cost and benefit of agriculture. Agricultural production strategies are developed using the best available data and knowledge such as high-yield locations, distance to storage facilities, or certification bonuses. However, there is often a divide between sustainable production data generated by the scientific community and current data that are of interest to actors, such as those in the agribusiness sector. Here, we describe how the harmonization of crop production, conservation, and social data used by scientists and agribusiness is possible using a participatory exercise based on knowledge co-production (i.e., generation of knowledge in a collaborative way) of socio-economic and environmental indicators (such as agricultural production, logistics, or the location of indigenous communities). This was made available through an online decision support platform that facilitated the generation of sustainable entrepreneurial strategies. We tested this exercise for the social-environmentally vulnerable Argentine Chaco dry forest, subject to some of the highest rates of deforestation globally, mainly due to soybean production. The cooperation between participants of this exercise built a knowledge exchange network that was key for informing decision-makers and highlighted information gaps including agricultural productivity, accessibility of regions, and the vulnerability of rural communities. Our exercise may be applicable to other agricultural commodity frontiers and showcases the value of including actors’ priorities in the design of indicators to ensure their policy impact and to achieve food systems’ sustainability.
Occurrence of selected Covid-19 drugs in surface water resources: a review of their sources, pathways, receptors, fate, ecotoxicity, and possible interactions with heavy metals in aquatic ecosystems
Authors: Maremane S. R. , Belle G. N. , Oberholster P. J. , Omotola E. O. 
Published: November 2024

AbstractThe outbreak of the coronavirus disease 2019 (Covid-19) led to the high consumption of antibiotics such as azithromycin as well as corticosteroids such as prednisone, prednisolone, and dexamethasone used to treat the disease. Seemingly, the concentrations of these four Covid-19 drugs increased in wastewater effluents and surface water resources. This is due to the failure of traditional wastewater treatment facilities (WWTFs) to eliminate pharmaceuticals from wastewater. Therefore, the objective of the current research was to review the present state of literature on the occurrence of four Covid-19 drugs in water resources, the associated risks and toxicity, their fate, as well as the emergence of combined pollutants of Covid-19 drugs and heavy metals. From late 2019 to date, azithromycin was observed at concentrations of 935 ng/L, prednisone at 433 ng/L, prednisolone at 0.66 ng/L, and dexamethasone at 360 ng/L, respectively, in surface water resources. These concentrations had increased substantially in water resources and were all attributed to pollution by wastewater effluents and the rise in Covid-?19 infections. This phenomenon was also exacerbated by the observation of the pseudo-persistence of Covid-19 drugs, long half-life periods, as well as the excretion of Covid-19 drugs from the human body with about 30?90% of the parent drug. Nonetheless, the aquatic and human health toxicity and risks of Covid-19 drugs in water resources are unknown as the concentrations are deemed too low; thus, neglecting the possible long-term effects. Also, the accumulation of Covid-19 drugs in water resources presents the possible development of combined pollutants of Covid-19 drugs and heavy metals that are yet to be investigated. The risks and toxicity of the combined pollutants, including the fate of the Covid-19 drugs in water resources remains a research gap that undoubtably needs to be investigated.
A Helmholtz Energy Equation of State for Calculations of Thermodynamic Properties of trans-1,2-Difluoroethene [R-1132(E)]
Authors: Akasaka Ryo , Lemmon Eric W. 
Published: November 2024

AbstractThis work presents a fundamental equation of state for calculations of the thermodynamic properties of R-1132(E), which is a potential refrigerant for residential or mobile air conditioners. The equation of state has a functional form expressed explicitly in the Helmholtz energy with temperature and density as the independent variables, and the form is fitted to consistent experimental datasets, including the critical parameters, vapor pressure, saturated liquid and vapor densities, $$(p, \rho , T)$$

(
p
,
ρ
,
T
)

behavior, vapor-phase sound speed, and ideal gas isobaric heat capacity. The equation of state is valid between temperatures from 240 K and 400 K, with pressures up to 6.5 MPa. In this range, expected relative uncertainties at the 95 % confidence interval ($$k=2$$

k
=
2

) are 0.1 % for liquid densities, 0.4 % for vapor densities, and 0.1 % for vapor-phase sound speeds, except at the saturation states and in the critical region where larger deviations of up to 2 % are possible in densities due to higher experimental uncertainties. The uncertainty in calculated vapor pressures is 0.15 % above 275 K, which is larger at lower temperatures due to their small values. Various plots of derived properties from the equation of state show that the equation exhibits qualitatively correct behavior over wide ranges of temperature and pressure.
Pointlessness of average period of production: A critique of Lewin and Cachanosky
Authors: Rapka Przemysław 
Published: November 2024

AbstractPeter Lewin and Nicolas Cachanosky seek to rehabilitate the concept of the average period of production (APP) introduced into Austrian capital theory by Böhm-Bawerk (1930). In their works, they argue that the financial concepts of Macauley’s Duration and Modified Duration are appropriate measures of the average period of production. For this reason, the most relevant aspects of the Austrian Business Cycle Theory (ABCT), i.e. the lengthening and shortening of the production structure, can be captured by them. In fact, the introduction of this concept into ABCT is pointless, since it only shows the sensitivity of the economy to changes in interest rates. Meanwhile, it does not help us understand a number of other phenomena that can be observed over the business cycle. By focusing on APP as represented by duration and modified duration, we are only referring to how the average value of all investments in the economy changes under the influence of a change in interest rates, ignoring other important phenomena that take place over the course of the business cycle.
Digitally extended knowledge
Authors: Kallestrup Jesper 
Published: November 2024

Abstract
The hypothesis of extended cognition says that cognitive processes and mental states extend to include extra-organismic parts of the external world, provided certain conditions on cognitive integration are satisfied. Moreover, if knowledge is assumed to be a mental state, knowledge is, by a similar line of reasoning, equally extended. However, extended knowledge presents an additional challenge to do with cognitive bloat, given that knowledge is widely regarded as a distinctive cognitive achievement. This paper explores the idea that different types of software systems, rather than specific external devices, may serve to extend knowledge beyond our bodily boundaries, and if so whether this new hypothesis of digitally extended knowledge leads to any untoward expansion of knowledge.