bluuebunny/crossref_metadata_2025 huggingface dataset:
Modeling of Viscoelasticity of Thermoplastic Polymers Employed in the Hot Embossing Process
Authors: Rabhi F. , Cheng G. , Barriere T.
Published: August 2024

The manufacturing of micro-scale components requires mastery of shaping processes ranging from micromechanics to electronic microfabrication. The hot embossing (HE) process is widely developed in various fields, since it allows to emboss complex structures at the micro/nanoscale such as optical sensors, diffractive lenses, microfluidic channels, and so on. The development of micro-structured parts via this process requires an in-depth analysis of the surface quality obtained and the mold filling rate. It is essential to analyze the influence of polymer properties to optimize the final mold filling to reduce cycle time and obtain defect-free replicated components. In this research, compression tests were carried out with poly(methyl methacrylate) (PMMA) and polycarbonate (PC), at different forming temperatures to determine their behavior law properties. Numerical simulation of the polymer forming processing was carried out by using Abaqus finite element software, taking into account the mechanical properties of both polymers and the characteristics of microchannels. The aim was to analyze the effect of the elastic–viscoplastic properties of the materials on the mold filling rate at different temperatures. Numerical simulation of the HE process with PMMA shows that the mold cavity is completely filled with elastic-viscoplastic behaviors, and the filling rate increases as a function of mold displacement. On the other hand, for PC, the embossed temperature has an influence on the filling ratio of the mold.
Numerical Analysis of Damage and Failure in Anisotropic Sheet Metals During Biaxial Loading
Authors: Brünig Michael , Koirala Sanjeev , Gerke Steffen
Published: August 2024

In the paper, the influence of stress state and loading direction with respect to the principal axes of anisotropy on damage and fracture behavior of the anisotropic aluminum alloy EN AW-2017A is discussed. The focus is on numerical calculations on the micro-level considering void-containing representative volume elements revealing information on damage mechanisms. Using experimental data taken from uniaxial and biaxial tests, material parameters are identified. Based on numerical studies on the micro-scale with differently loaded void-containing cubes, it is shown that the stress state, the load ratio and the loading direction with respect to the principal axes of anisotropy have an influence on evolution of damage processes on the micro-scale and on the corresponding damage strains.
Numerical and Experimental Investigation of Multi-axial Forging of AA6082 Alloy
Authors: Prabhakar Srijan , Kumar D. Ravi , Aravindan S.
Published: August 2024

Multi-axial forging is a useful technique for producing ultrafine-grained structures in bulk materials by means of severe plastic deformation. The workpiece is subjected to a specific plastic strain in the multi-axial forging process by repeatedly upsetting along all three axes by rotating the sample by 90° between the two passes; this leads to the accumulation of a large plastic strain in the material. The shape of the product does not change, as equal compressive strain is applied in all directions. Severe plastic deformation methods such as multi-axial forging can be used for producing lightweight high-strength Al alloys with ultrafine-grained structures. In this study, as-cast AA6082 has been multiaxially forged with a true strain of 0.1 in each direction, leading to a total effective strain of 0.3 in each cycle. The strain inhomogeneity from center to the surface has been predicted by a finite element simulation of the multi-axial forging with a Voce hardening model, and it has been correlated with an experimentally determined hardness variation. The peak loads in all of the passes have also been compared.
Evaluation of Forming Factors for Titanium Gr. 2 Alloy Sheets with Multistage SPIF Process
Authors: Mulay Amrut , Sameer Vadher
Published: August 2024

In the vast prospects for automation, incremental sheet forming (ISF) is a reliable sector on which the industry may focus in the future. Due to spring back, poor surface finish, and production time, ISF has yet to apply in broad prospects in mainstream high-value manufacturing sectors. ISF performance is affected by process factors such as vertical step depth, feed rate, spindle speed, forming angle, tool path, intermetallic friction, and bending forces. One of the variants of ISF processes is Single Point Incremental Forming (SPIF). The formability of the SPIF process increases by incorporating certain intermediary phases known as Multistage Incremental Sheet Forming (MSPIF). The strain hardening effect that emerged in the distorted sheet alters its deformability. The integration of intermediate results into some new process parameters to address in this work includes the number of stages, angle interval between the stages, and tool diameter. The present research focuses on the influence of process parameters on section thickness, equivalent plastic strain, and spring back. A simulation study of various process parameters of multistage forming and their effects on multistage incremental forming performance were evaluated.
Spindle black holes and theories of class $$ \mathcal{F} $$
Authors: Hristov Kiril , Suh Minwoo
Published: August 2024

Abstract

We construct solutions in the form of AdS2 × Σ, where Σ denotes a spindle geometry, within a particular 4d $$ \mathcal{N} $$
N
= 2 gauged supergravity with vector multiplets and a charged hypermultiplet stemming from a consistent truncation of 6d matter coupled F(4) gauged supergravity on a Riemann surface. We also compute the Bekenstein-Hawking entropy for the presumed asymptotically AdS4 black hole solutions, providing a dual prediction for the spindle index of 3d superconformal field theories falling under the class $$ \mathcal{F} $$
F
. Notably, the gravitational block description of the solutions accurately replicates the entropy and the values of scalar fields at the two orbifold points of the spindle, validating our findings.
When left and right disagree: entropy and von Neumann algebras in quantum gravity with general AlAdS boundary conditions
Authors: Marolf Donald , Zhang Daiming
Published: August 2024

Abstract

Euclidean path integrals for UV-completions of d-dimensional bulk quantum gravity were recently studied in [1] by assuming that they satisfy axioms of finiteness, reality, continuity, reflection-positivity, and factorization. Sectors $$ {\mathcal{H}}_{\mathcal{B}} $$

H
B

of the resulting Hilbert space were then defined for any (d − 2)-dimensional surface $$ \mathcal{B} $$
B
, where $$ \mathcal{B} $$
B
may be thought of as the boundary ∂Σ of a bulk Cauchy surface in a corresponding Lorentzian description, and where $$ \mathcal{B} $$
B
includes the specification of appropriate boundary conditions for bulk fields. Cases where $$ \mathcal{B} $$
B
was the disjoint union B ⊔ B of two identical (d − 2)-dimensional surfaces B were studied in detail and, after the inclusion of finite-dimensional ‘hidden sectors,’ were shown to provide a Hilbert space interpretation of the associated Ryu-Takayanagi entropy. The analysis was performed by constructing type-I von Neumann algebras $$ {\mathcal{A}}_L^B $$

A
L
B

, $$ {\mathcal{A}}_R^B $$

A
R
B

that act respectively at the left and right copy of B in B ⊔ B.

Below, we consider the case of general $$ \mathcal{B} $$
B
, and in particular for $$ \mathcal{B} $$
B
= BL ⊔ BR with BL, BR distinct. For any BR, we find that the von Neumann algebra at BL acting on the off-diagonal Hilbert space sector $$ {\mathcal{H}}_{B_L\bigsqcup {B}_R} $$

H

B
L

⊔

B
R

is a central projection of the corresponding type-I von Neumann algebra on the ‘diagonal’ Hilbert space $$ {\mathcal{H}}_{B_L\bigsqcup {B}_L} $$

H

B
L

⊔

B
L

. As a result, the von Neumann algebras $$ {\mathcal{A}}_L^{B_L} $$

A
L

B
L

, $$ {\mathcal{A}}_R^{B_L} $$

A
R

B
L

defined in [1] using the diagonal Hilbert space $$ {\mathcal{H}}_{B_L\bigsqcup {B}_L} $$

H

B
L

⊔

B
L

turn out to coincide precisely with the analogous algebras defined using the full Hilbert space of the theory (including all sectors $$ {\mathcal{H}}_{\mathcal{B}} $$

H
B

). A second implication is that, for any $$ {\mathcal{H}}_{B_L\bigsqcup {B}_R} $$

H

B
L

⊔

B
R

, including the same hidden sectors as in the diagonal case again provides a Hilbert space interpretation of the Ryu-Takayanagi entropy. We also show the above central projections to satisfy consistency conditions that lead to a universal central algebra relevant to all choices of BL and BR.
Tissue Distribution and Toxicological Risk Assessment of Mercury and Other Elements in Northern Populations of Wolverine (Gulo gulo)
Authors: Chételat John , Jung Thomas S. , Awan Malik , Baryluk Steven , Harrower William , Kukka Piia M. , McClelland Christine , Mowat Garth , Pelletier Nicolas , Rodford Christine , Stimmelmayr Raphaela
Published: August 2024

Wolverines are facultative scavengers that feed near the top of terrestrial food chains. We characterized concentrations of mercury and other trace elements in tissues of wolverine from a broad geographic area, representing much of their contemporary distribution in northwestern North America. We obtained tissues from 504 wolverines, from which mercury was measured on muscle (n = 448), kidney (n = 222), liver (n = 148), hair (n = 130), and brain (n = 52). In addition, methylmercury, seven trace elements (arsenic, cadmium, chromium, cobalt, lead, nickel, selenium), and arsenic compounds were measured on a subset of samples. Concentrations of mercury and other trace elements varied between tissues and were generally highest in kidney compared to brain, liver and muscle. Mercury was predominately as methylmercury in brain and muscle, but largely as inorganic mercury in liver and kidney. Mercury concentrations of hair were moderately correlated with those of internal tissues (Pearson r = 0.51–0.75, p ≤ 0.004), making hair a good non-lethal indicator of broad spatial or temporal differences in mercury exposure to wolverine. Arsenobetaine was the dominant arsenic compound identified in tissues, and arsenite, arsenocholine and dimethylarsinic acid were also detected. A preliminary risk assessment suggested the cadmium, lead, mercury, and selenium concentrations in our sample of wolverines were not likely to pose a risk of overt toxicological effects. This study generated a comprehensive dataset on mercury and other trace elements in wolverine, which will support future contaminants study of this northern terrestrial carnivore.
Does the development environment cause the pace of life to change in a rainforest lizard?
Authors: Buchholz Kali M. , Goulet Celine T. , de Jong Madeleine , Hart Wesley , Llewelyn John , Phillips Ben L. , Chapple David G.
Published: August 2024

Life history theory emphasizes that finite resources result in allocation trade-offs among the competing interests of self-maintenance, growth, reproduction, and survival. Environmental conditions, particularly during development, can influence these life history trade-offs, leading to the coupling of physiological and behavioural traits with life history strategies. Thus, populations may vary in the pattern of trait covariation, clustering along a fast-slow continuum, termed the extended pace-of-life syndrome (POLS) theory. We aimed to test how variation in ecological conditions influence life history trade-offs and their association with behaviour and physiology by comparing captive bred and wild-collected southern rainforest sunskink (Lampropholis similis). The captive bred skinks were the offspring of the wild-caught skinks, and all tests were conducted in the laboratory. We found that the groups differed, on average, in growth rate, body condition, thermal preferences, sprint performance, and activity. Counter to our expectation, wild-caught skinks exhibited a faster pace of life relative to captive-bred skinks despite experiencing more challenging environmental conditions. Furthermore, life history trade-offs were not detected, nor were traits correlated to form the syndrome. Studies are needed to identify the proximate mechanisms causing life history trade-offs and how they lead to the coupling, or decoupling, of physiological and behavioural traits. Such information will provide vital insight into how ecological forces drive the evolution of traits.
Development of the basic architecture of neocortical circuitry in the human fetus as revealed by the coupling spatiotemporal pattern of synaptogenesis along with microstructure and macroscale in vivo MR imaging
Authors: Kostović Ivica
Published: August 2024

In humans, a quantifiable number of cortical synapses appears early in fetal life. In this paper, we present a bridge across different scales of resolution and the distribution of synapses across the transient cytoarchitectonic compartments: marginal zone (MZ), cortical plate (CP), subplate (SP), and in vivo MR images. The tissue of somatosensory cortex (7–26 postconceptional weeks (PCW)) was prepared for electron microscopy, and classified synapses with a determined subpial depth were used for creating histograms matched to the histological sections immunoreacted for synaptic markers and aligned to in vivo MR images (1.5 T) of corresponding fetal ages (maternal indication). Two time periods and laminar patterns of synaptogenesis were identified: an early and midfetal two-compartmental distribution (MZ and SP) and a late fetal three-compartmental distribution (CP synaptogenesis). During both periods, a voluminous, synapse-rich SP was visualized on the in vivo MR. Another novel finding concerns the phase of secondary expansion of the SP (13 PCW), where a quantifiable number of synapses appears in the upper SP. This lamina shows a T2 intermediate signal intensity below the low signal CP. In conclusion, the early fetal appearance of synapses shows early differentiation of putative genetic mechanisms underlying the synthesis, transport and assembly of synaptic proteins. “Pioneering” synapses are likely to play a morphogenetic role in constructing of fundamental circuitry architecture due to interaction between neurons. They underlie spontaneous, evoked, and resting state activity prior to ex utero experience. Synapses can also mediate genetic and environmental triggers, adversely altering the development of cortical circuitry and leading to neurodevelopmental disorders.
Explainable multi-layer COSFIRE filters robust to corruptions and boundary attack with application to retina and palmprint biometrics
Authors: Apap Adrian , Bhole Amey , Fernández-Robles Laura , Castejón-Limas Manuel , Azzopardi George
Published: August 2024

We propose a novel and versatile computational approach, based on hierarchical COSFIRE filters, that addresses the challenge of explainable retina and palmprint recognition for automatic person identification. Unlike traditional systems that treat these biometrics separately, our method offers a unified solution, leveraging COSFIRE filters’ trainable nature for enhanced selectivity and robustness, while exhibiting explainability and resilience to decision-based black-box adversarial attack and partial matching. COSFIRE filters are trainable, in that their selectivity can be determined with a one-shot learning step. In practice, we configure a COSFIRE filter that is selective for the mutual spatial arrangement of a set of automatically selected keypoints of each retina or palmprint reference image. A query image is then processed by all COSFIRE filters and it is classified with the reference image that was used to configure the COSFIRE filter that gives the strongest similarity score. Our approach, tested on the VARIA and RIDB retina datasets and the IITD palmprint dataset, achieved state-of-the-art results, including perfect classification for retina datasets and a 97.54% accuracy for the palmprint dataset. It proved robust in partial matching tests, achieving over 94% accuracy with 80% image visibility and over 97% with 90% visibility, demonstrating effectiveness with incomplete biometric data. Furthermore, while effectively resisting a decision-based black-box adversarial attack and impervious to imperceptible adversarial images, it is only susceptible to highly perceptible adversarial images with severe noise, which pose minimal concern as they can be easily detected through histogram analysis in preprocessing. In principle, the proposed learning-free hierarchical COSFIRE filters are applicable to any application that requires the identification of certain spatial arrangements of moderately complex features, such as bifurcations and crossovers. Moreover, the selectivity of COSFIRE filters is highly intuitive; and therefore, they provide an explainable solution.
Continuous glycemic monitoring in managing diabetes in adult patients with wolfram syndrome
Authors: Zmysłowska Agnieszka , Grzybowska-Adamowicz Julia , Michalak Arkadiusz , Wykrota Julia , Szadkowska Agnieszka , Młynarski Wojciech , Fendler Wojciech
Published: August 2024

Aims

In this study we evaluated the use of Continuous Glucose Monitoring system in adults with insulin-dependent diabetes in the course of Wolfram syndrome (WFS) in comparison to patients with type 1 diabetes (T1D).

Methods

Individuals with WFS (N = 10) used continuous glucose monitoring for 14 days and were compared with 30 patients with T1D matched using propensity score for age and diabetes duration. Glycemic variability was calculated with Glyculator 3.0.

Results

We revealed significant differences in glycemic indices between adults with Wolfram syndrome-related diabetes and matched comparison group. Patients with Wolfram syndrome presented lower mean glucose in 24-h and nighttime records [24h: 141.1 ± 30.4mg/dl (N = 10) vs 164.9 ± 31.3mg/dl (N = 30), p = 0.0427; nighttime: 136.7 ± 39.6mg/dl vs 166.2 ± 32.1mg/dl (N = 30), p = 0.0442]. Moreover, they showed lower standard deviation of sensor glucose over all periods [24h: 50.3 ± 9.2mg/dl (N = 10) vs 67.7 ± 18.7 mg/dl (N = 30), p = 0.0075; daytime: 50.8 ± 8.7mg/dl (N = 10) vs 67.4 ± 18.0mg/dl (N = 30), p = 0.0082; nighttime: 45.1 ± 14.9mg/dl (N = 10) vs 65.8 ± 23.2mg/dl (n = 30), p = 0.0119] and coefficient of variation at night [33.3 ± 5.8% (N = 10) vs 40.5 ± 8.8% (N = 30), p = 0.0210]. Additionally, WFS patients displayed lower time in high-range hyperglycemia (> 250mg/dl) across all parts of day [24h: 4.6 ± 3.8% (N = 10) vs 13.4 ± 10.5% (N = 30), p = 0.0004; daytime: 4.7 ± 3.9% (N = 10) vs 13.8 ± 11.2% (N = 30), p = 0.0005; nighttime: 4.2 ± 5.5% (N = 10) vs 12.1 ± 10.3% (N = 30), p = 0.0272].

Conclusions

Adult patients with Wolfram syndrome show lower mean blood glucose, less extreme hyperglycemia, and lower glycemic variability in comparison to patients with type 1 diabetes.
A systematic survey of fuzzy deep learning for uncertain medical data
Authors: Zheng Yuanhang , Xu Zeshui , Wu Tong , Yi Zhang
Published: August 2024

Intelligent medical industry is in a rapid stage of development around the world, followed by are the expanding market size and basic theories of intelligent medical diagnosis and decision-making. Deep learning models have achieved good practical results in medical domain. However, traditional deep learning is almost calculated and developed by crisp values, while imprecise, uncertain, and vague medical data is common in the process of diagnosis and treatment. It is important and significant to review the contributions of fuzzy deep learning for uncertain medical data, because fuzzy deep learning that originated from fuzzy sets, can effectively deal with uncertain and inaccurate information, providing new viewpoints for alleviating the presence of noise, artifact or high dimensional unstructured information in uncertain medical data. Therefore, taking focus on the intersection of both different fuzzy deep learning models and several types of uncertain medical data, the paper first constructs four types of frameworks of fuzzy deep learning models used for uncertain medical data, and investigates the status from three aspects: fuzzy deep learning models, uncertain medical data and application scenarios. Then the performance evaluation metrics of fuzzy deep learning models are analyzed in details. This work has some original points: (1) four types of frameworks of applying fuzzy deep learning models for uncertain medical data are first proposed. (2) Seven fuzzy deep learning models, five types of uncertain medical data, and five application scenarios are reviewed in details, respectively. (3) The advantages, challenges, and future research directions of fuzzy deep learning for uncertain medical data are critically analyzed, providing valuable suggestions for further deep research.
Experimental validation of the neutron flux suppression in samples with high manganese content in instrumental neutron activation analysis
Authors: Schramm Lukas-Morris , Nemetz Markus , Renz Franz , Feng Bin , Steinhauser Georg
Published: August 2024

Instrumental neutron activation analysis (INAA) relies on constant neutron flux densities throughout the activated samples. Although this concept is true for most typical samples, occasionally, the presence of highly neutron absorbing nuclides in the sample may cause a neutron flux density suppression which would ultimately lead to distorted results in the INAA. Here, we have investigated artificial samples with a high manganese (Mn) content. By adding aqueous gold solution, we introduced a liquid in-situ neutron flux monitor into the sample. An Mn content ≤ 50% shows little effect to the internal neutron flux density, however, the flux can be suppressed by ca. 20% when the Mn content reaches 63.2%.
Why some countries but not others? Urbanisation, GDP and endemic disease predict global SARS-CoV-2 excess mortality patterns
Authors: Fountain-Jones Nicholas M. , Charleston Michael , Flies Emily J. , Carver Scott , Yates Luke A.
Published: August 2024

Context

The global impact of the SARS-CoV-2 pandemic has been uneven, with some regions experiencing significant excess mortality while others have been relatively unaffected. Yet factors which predict this variation remain enigmatic, particularly at large spatial scales.

Objectives

We aimed to uncover the key drivers of excess mortality across countries and regions to help understand the factors contributing to the varied impacts of the pandemic worldwide.

Methods

We used spatially explicit Bayesian models that integrate environmental, socio-demographic and endemic disease data at the country level to provide robust global estimates of excess SARS-CoV-2 mortality (P-scores) for the years 2020 and 2021.

Results

We find that urbanization, gross domestic product (GDP) and spatial patterns are strong predictors of excess mortality, with countries characterized by low GDP but high urbanization experiencing the highest levels of excess mortality. Intriguingly, we also observed that the prevalence of malaria and human immunodeficiency virus (HIV) are associated with country-level SARS-CoV-2 excess mortality in Africa and the Western Pacific, whereby countries with low HIV prevalence but high malaria prevalence tend to have lower levels of excess mortality. While these associations are correlative in nature at the macro-scale, they emphasize that patterns of endemic disease and socio-demographic factors are needed to understand the global dynamics of SARS-CoV-2.

Conclusions

Our study identifies factors associated with variation in excess mortality across countries, providing insights into why some were more impacted by the pandemic than others. By understanding these predictors, we can better inform global outbreak management strategies, such as targeting medical resources to highly urban countries with low GDP and high HIV prevalence to reduce mortality during future outbreaks.
A generic approach for reproducible model distillation
Authors: Zhou Yunzhe , Xu Peiru , Hooker Giles
Published: August 2024

Model distillation has been a popular method for producing interpretable machine learning. It uses an interpretable “student” model to mimic the predictions made by the black box “teacher” model. However, when the student model is sensitive to the variability of the data sets used for training even when keeping the teacher fixed, the corresponded interpretation is not reliable. Existing strategies stabilize model distillation by checking whether a large enough sample of pseudo-data is generated to reliably reproduce student models, but methods to do so have so far been developed separately for each specific class of student model. In this paper, we develop a generic approach for stable model distillation based on central limit theorem for the estimated fidelity of the student to the teacher. We start with a collection of candidate student models and search for candidates that reasonably agree with the teacher. Then we construct a multiple testing framework to select a sample size such that the consistent student model would be selected under different pseudo samples. We demonstrate the application of our proposed approach on three commonly used intelligible models: decision trees, falling rule lists and symbolic regression. Finally, we conduct simulation experiments on Mammographic Mass and Breast Cancer datasets and illustrate the testing procedure throughout a theoretical analysis with Markov process. The code is publicly available at https://github.com/yunzhe-zhou/GenericDistillation.
Impact of dietary regime on the metabolomic profile of bovine buttermilk and whole milk powder
Authors: Connolly Claire , Timlin Mark , Hogan Sean A. , Murphy Eoin G. , O’Callaghan Tom F. , Brodkorb André , Hennessy Deirdre , Fitzpartick Ellen , O’Donavan Michael , McCarthy Kieran , Murphy John P. , Yin Xiaofei , Brennan Lorraine
Published: August 2024

Introduction

Bovine milk contains a rich matrix of nutrients such as carbohydrates, fat, protein and various vitamins and minerals, the composition of which is altered by factors including dietary regime.

Objectives

The objective of this research was to investigate the impact of dietary regime on the metabolite composition of bovine whole milk powder and buttermilk.

Methods

Bovine whole milk powder and buttermilk samples were obtained from spring-calving cows, consuming one of three diets. Group 1 grazed outdoors on perennial ryegrass which was supplemented with 5% concentrates; group 2 were maintained indoors and consumed a total mixed ration diet; and group 3 consumed a partial mixed ration diet consisting of perennial ryegrass during the day and total mixed ration maintained indoors at night.

Results

Metabolomic analysis of the whole milk powder (N = 27) and buttermilk (N = 29) samples was preformed using liquid chromatography-tandem mass spectrometry, with 504 and 134 metabolites identified in the samples respectively. In whole milk powder samples, a total of 174 metabolites from various compound classes were significantly different across dietary regimes (FDR adjusted p-value ≤ 0.05), including triglycerides, of which 66% had their highest levels in pasture-fed samples. Triglycerides with highest levels in pasture-fed samples were predominantly polyunsaturated with high total carbon number. Regarding buttermilk samples, metabolites significantly different across dietary regimes included phospholipids, sphingomyelins and an acylcarnitine.

Conclusion

In conclusion the results reveal a significant impact of a pasture-fed dietary regime on the metabolite composition of bovine dairy products, with a particular impact on lipid compound classes.
Relaxation and Noise-Driven Oscillations in a Model of Mitotic Spindle Dynamics
Authors: Hargreaves Dionn , Woolner Sarah , Jensen Oliver E.
Published: August 2024

During cell division, the mitotic spindle moves dynamically through the cell to position the chromosomes and determine the ultimate spatial position of the two daughter cells. These movements have been attributed to the action of cortical force generators which pull on the astral microtubules to position the spindle, as well as pushing events by these same microtubules against the cell cortex and plasma membrane. Attachment and detachment of cortical force generators working antagonistically against centring forces of microtubules have been modelled previously (Grill et al. in Phys Rev Lett 94:108104, 2005) via stochastic simulations and mean-field Fokker–Planck equations (describing random motion of force generators) to predict oscillations of a spindle pole in one spatial dimension. Using systematic asymptotic methods, we reduce the Fokker–Planck system to a set of ordinary differential equations (ODEs), consistent with a set proposed by Grill et al., which can provide accurate predictions of the conditions for the Fokker–Planck system to exhibit oscillations. In the limit of small restoring forces, we derive an algebraic prediction of the amplitude of spindle-pole oscillations and demonstrate the relaxation structure of nonlinear oscillations. We also show how noise-induced oscillations can arise in stochastic simulations for conditions in which the mean-field Fokker–Planck system predicts stability, but for which the period can be estimated directly by the ODE model and the amplitude by a related stochastic differential equation that incorporates random binding kinetics.
Soil resilience assessment using soil profile descriptions and Analytic Hierarchy Process in Mediterranean mountains considering diverse fire occurrences
Authors: Rodrigo-Comino Jesús
Published: August 2024

Wildfires are complex natural phenomena that exert significant impacts on landscapes, societies, and economies. Understanding the concept of resilience is crucial in mitigating its possible negative impacts, as it involves preparing for, responding to, and recovering from wildfires. This research aims to demonstrate the utility of in situ soil profile description in assessing land use resilience using an Analytic Hierarchy Process (AHP) through an expert panel survey. The study examines a catchment located in the Balearic Islands, considering two fire occurrences (once and twice), comparing abandoned agricultural terraces and natural hillslopes. The results demonstrated that the priority ranking of variables to assess soil profile resilience against wildfires, determined by a panel of 10 experts, identified horizon depth (25.1%), slope inclination (21.5%), and hydrological connectivity (16.6%) as the most crucial factors. Other variables, such as number and size of roots, structure of pedal soil material, size class structure, and rock fragments, also contributed to resilience but to a lesser extent, with scores ranging from 5.7% to 9.6%. Analyzing the priorities established by the experts using AHP, the results showed that the least resilient soil horizon was H1 of the control hillslope, especially under high and low connectivity processes, which aligned with the loss of superficial soil horizons after one and two wildfires. Hillslopes showed greater changes in resilience after occurring wildfires compared to terraces, with the most significant alterations occurring after the second wildfire event. This study addresses a significant knowledge gap in the field by highlighting the interconnectedness of wildfires, resilience, and land use, providing insights into land management strategies for wildfire-prone regions.
Innovative utilization of olive mill wastewater phenolics extracted by lecithin: spray-dried powders in cake formulations
Authors: Karadag Ayse , Cakmakoglu Selma Kayacan , Bekiroglu Hatice , Karasu Salih , Ozer Hayrettin , Sagdic Osman , Yildirim Rusen Metin
Published: August 2024

In the present study, the olive mill wastewater (OMW) phenolics were extracted with soy lecithin using the cloud point extraction method, and this enriched lecithin (OMW-L) was converted into spray-dried powders using maltodextrin (MD) and whey protein concentrate to be utilized as a dry food ingredient in a cake premix. The inlet temperature of 170 °C and a 3 mL/min feed flow rate yielded the highest powder yield (70.88 ± 2.12%) with a moisture content of 3.78 ± 0.03% when the mass ratio of lecithin to MD was 1:3 (w:w). The hydroxytyrosol and tyrosol contents of the powder were 42.60 ± 4.51 mg/100 g and 15.48 ± 2.50 mg/100 g, respectively. Vanillic acid, caffeic acid, 3-hydroxybenzoic acid, catechin, and rutin were also identified in the powders. The spray-dried OMW-L powder with a higher loading of polyphenols was then used in a cake premix, replacing 1% and 3% of wheat flour. This substitution significantly reduced the K value of the cake batter, as determined by rheological analyses. The addition of spray-dried OMW-L powder to the cake samples, particularly at higher concentrations (3%), influenced both crust and crumb color, causing changes in L*, a*, and b* values. The hardness values of the cake samples did not alter when blank or OMW-enriched lecithin powders were added; rather, the hardness value was influenced by the powder content. Overall, this research offers a different perspective on the use of OMW phenolics in food applications, especially in ready-to-use blends, and demonstrates the effects of the obtained spray-dried lecithin powders on batter rheology and cake characteristics.

Graphical abstract
Bridging human expertise and machine learning in production management: a case study on ML-based decision support systems to prevent missing parts at assembly
Authors: Sauer Carl René , Burggräf Peter , Steinberg Fabian
Published: August 2024

In the field of production management, decision support systems (DSS) equipped with machine learning (ML) have significantly advanced production planning and control within manufacturing companies. These systems are crucial, particularly in the machinery industry, for predicting shortages such as missing parts at the start of assembly. However, current ML-based DSS typically focus solely on predicting occurring problems or suggesting options for simplified scenarios, often missing the critical integration of human operators in the decision-making loop. This study introduces an advanced DSS that integrates ML to predict a missing part for the assembly start and to automatically provide a clear indication of the causes behind predicted shortages. This is achieved by employing shapley additive explanations (SHAP) to the respective ML-based prediction model. Thus, this analysis enables production controllers to initiate both proactive and/or reactive actions by detailed insights into the system’s predictions, and fostering a more dynamic interaction providing between human decision-makers and automated systems. This integration reduces the reliance on time-consuming manual analyses and enhances transparency in decision-making processes. The efficacy of the integrated approach is demonstrated by a case study conducted at a German machinery manufacturer, specialized in low-volume, high-variety production. The findings of this case study confirm that the DSS is efficacious in supporting complex decision-making processes, making it a valuable tool for modern production environments.
Advances in Digital Health for Gastrointestinal Nutrition
Authors: Kim Sowon , Zhang Yi , Mauldin Kasuen , Limketkai Berkeley N.
Published: August 2024

Purpose of Review

Advances in computing have led to an explosion in digital health. This review discusses potential applications of digital technologies, their implications for patient care, and future directions at the intersection between nutrition and gastrointestinal (GI) conditions.

Recent Findings

We present an array of digital technologies, including mobile applications, wearable devices, biosensors, artificial intelligence (AI), and telehealth, that have uses for GI nutrition. While having practical value, many are still limited to the early phases of development or have not yet been proven to provide clinical benefit.

Digital health technologies offer unprecedented insight into the individual’s health and lifestyle. AI technologies, coupled with the wealth of data collected, offer a path toward precision nutrition. Balanced against the incredible potential and promise of digital health, we should also recognize its limitations, particularly risks involving patient privacy and AI bias, when implementing these tools. Much more research is needed for creating, refining, and validating these technologies for GI nutrition before they can be more widely adopted in clinical practice.
Victim’s identification and social categorization: first- and second-order effects on altruistic behavior
Authors: Regasa Wubeshet , Galmarini Umberto , Porro Giuseppe
Published: August 2024

We explore in laboratory how donations to a charity can be influenced by the identifiability and the social categorization of the recipients. We find that donors give more, on average, to unidentified than to identified beneficiaries, since the latter are more likely to receive small donations than the former. Average donations are the same for in- and out-group beneficiaries; however, an in-group recipient is more likely to receive a top donation than an out-group one, whereas the latter is more likely than the former to receive an intermediate donation. Both first- and second-order effects are associated to the Dynamic Identity Fusion Index elicited from participants toward the ‘Multicultural World’.
Mobility and the use of littoral resources in the Late Mesolithic of Northern Spain: the case of La Chora cave (Voto, Cantabria, N Spain)
Authors: León-Cristóbal Alejandro , García-Escárzaga Asier , Fano Miguel Ángel , Arniz-Mateos Rosa , Quesada José Manuel , Abril-Orzaiz Jon , Gutiérrez-Zugasti Igor
Published: August 2024

Littoral resources have been consumed by humans since at least the Middle Palaeolithic. Examples of the use of molluscs have been documented along the shores of Europe during that period but it was not until many millennia later that European hunter-fisher-gatherer societies exploited those resources intensively—see the case of Nerja cave during the Younger Dryas. This economic activity caused the accumulation of shells at archaeological sites during the Mesolithic, resulting in the formation of the so-called shell middens, a very common type of deposit along the Atlantic seaboard of Europe. Despite the large number of research projects that have studied the exploitation of coastal environments and the way of life of Mesolithic populations, questions such as the relationship between human mobility and mollusc exploitation patterns still remain. The archaeomalacological study of the shell midden in La Chora cave (Cantabria, Spain) confirms that people foraged for shellfish at several places along the coast, mainly in the estuary of the River Asón. The main difference between La Chora and other Mesolithic sites is its longer shellfish collection radius as the inhabitants travelled over 10 km to the open coast to collect shellfish. This study has expanded the available data about the subsistence strategies of Mesolithic groups in a little-studied area and improved our knowledge of mobility patterns among Mesolithic societies in the northern Iberian Peninsula.
Development of 3D-iNET ORION: a novel, pre-clinical, three-dimensional in vitro cell model for modeling human metastatic neuroendocrine tumor of the pancreas
Authors: Strnadel Jan , Valasek Mark A. , Lin Grace Y. , Lin Huahui , Tipps Ann M. Ponsford , Woo Sang Myung , Fujimura Ken , Wang Huawei , Choi Sunkyu , Bui Jack , Hermosillo Christopher , Jepsen Kristen , Navarro Michael R. , Kelber Jonathan A. , Klemke Richard L. , Bouvet Michael
Published: August 2024

Neuroendocrine tumors (NETs) of the pancreas are rare neoplasms that present complex challenges to diagnosis and treatment due to their indolent course. The incidence of pancreatic neuroendocrine tumors has increased significantly over the past two decades. A limited number of pancreatic neuroendocrine cell lines are currently available for the research. Here, we present 3D-iNET ORION, a novel 3-dimensional (spheroid) cell line, isolated from human pancreatic neuroendocrine tumor liver metastasis. Three-dimensionally grown (3D) cancer cell lines have gained interest over the past years as 3D cancer cell lines better recapitulate the in vivo structure of tumors, and are more suitable for in vitro and in vivo experiments. 3D-iNET ORION cancer cell line showed high potential to form tumorspheres when embedded in Matrigel matrix and expresses synaptophysin and EpCAM. Electron microscopy analysis of cancer cell line proved the presence of dense neurosecretory granules. When xenografted into athymic mice, 3D-iNET ORION cells produce slow-growing tumors, positive for chromogranin and synaptophysin. Human Core Exome Panel Analysis has shown that 3DiNET ORION cell line retains the genetic aberration profile detected in the original tumor. In conclusion, our newly developed neuroendocrine cancer cell line can be considered as a new research tool for in vitro and in vivo experiments.
Galois representations in arithmetic geometry
Authors: Lombardo Davide
Published: August 2024

We survey some recent recent results whose proofs depend in an essential way on the study of Galois representations. We discuss in particular the scarcity of rational points on ramified covers of abelian varieties, the problem of algorithmically computing endomorphism rings of abelian varieties over number fields, and a version of Kummer theory for commutative algebraic groups.
Clinical impact of restless legs syndrome in patients with migraine: a 12-year, single-center, longitudinal study
Authors: Suzuki Keisuke , Suzuki Shiho , Haruyama Yasuo , Fujita Hiroaki , Hirata Koichi
Published: August 2024

Although many studies have indicated a significant association between migraine and restless legs syndrome (RLS), few long-term longitudinal studies have examined RLS in patients with migraine. We conducted a single-center, 12-year, longitudinal study of migraine patients and assessed whether RLS was present in 2010, 2017, or 2022 to evaluate its associations with clinical factors. Headache-related disability was assessed using the Migraine Disability Assessment (MIDAS). Sleep quality, daytime sleepiness, and depressive symptoms were assessed using the Pittsburgh Sleep Quality Index (PSQI), the Epworth Sleepiness Scale (ESS) and the Beck Depression Inventory-II (BDI-II), respectively. Of the 262 patients included at baseline (2010), 101 were available after 7 years (2017), and 74 were available after 12 years (2022). The RLS incidence rates were 13.7%, 20.8%, and 24.3% in 2010, 2017, and 2022, respectively. The RLS severity score did not significantly differ among the three time points. The persistent RLS group, defined as those who were positive for RLS at the last evaluation in addition to the first and/or second evaluations, had significantly higher MIDAS, BDI-II, PSQI and ESS scores than did the never RLS group, defined as those who did not exhibit RLS at any of the three time points. Our 12-year longitudinal study revealed significant impacts of RLS on the burden of patients with migraine.
The China trade shock and the gender wage gap in India: A district-level analysis
Authors: Saha Kajari
Published: August 2024

This study provides new evidence on the debate surrounding international trade and the gender wage gap in a developing country context. It asks whether increased competition from trade has any causal effect on the district-level gender wage gap in India. Changes in competition from trade are measured using changes in imports from China, owing to the dramatic rise in Chinese imports into India in recent years. To isolate the supply-driven component of Chinese imports and establish causality, I use Chinese import growth in other low and lower-middle-income countries as an instrument for Chinese import growth in India. Results indicate a positive and statistically significant impact of an increase in Chinese imports on the gender wage gap over time. In addition to the economy-wide sample of workers, this effect holds true for the sub-samples of casual laborers and rural sector workers where the majority of women workers in India are concentrated. Unlike previous studies using industry-level data, the district-level focus of this study allows us to capture micro-level effects, as well as the net effects of trade in the surrounding district.
Discovery of a potential bladder cancer inhibitor CHNQD-01281 by regulating EGFR and promoting infiltration of cytotoxic T cells
Authors: Liu Jian-Yu , Jiang Yao-Yao , Li Peng-Jie , Yao Bo , Song Yi-Jing , Gao Ji-Xiu , Said Gulab , Gao Yang , Lai Jun-Yu , Shao Chang-Lun
Published: August 2024

As one of the common malignancies that threaten human life, bladder cancer occurs frequently with a high mortality rate in the world, due to its invasion, recurrence and drug resistance. Natural products from marine microorganisms are becoming the hotspots in discovery of new candidate drug entities, especially in the area of cancer. Brefeldin A (BFA) is a natural Arf-GEFs inhibitor, but due to the low aqueous solubility, strong toxicity, and poor bioavailability, it is urgent to conduct structural optimization research. Herein, a new BFA pyridine acrylate derivative CHNQD-01281 with improved solubility was prepared and found to exert moderate to strong antiproliferative activity on a variety of human cancer cell lines. It was noteworthy that CHNQD-01281 was most sensitive to two bladder cancer cell lines T24 and J82 (IC50 = 0.079 and 0.081 μmol/L) with high selectivity index (SI = 14.68 and 14.32), suggesting a superior safety to BFA. In vivo studies revealed that CHNQD-01281 remarkably suppressed tumor growth in a T24 nude mice xenograft model (TGI = 52.63%) and prolonged the survival time (ILS = 68.16%) in an MB49 allogeneic mouse model via inducing infiltration of cytotoxic T cells. Further mechanism exploration indicated that CHNQD-01281 regulated both EGFR/PI3K/AKT and EGFR/ERK pathways and mediated the chemotactic effect of chemokines on immune effector cells. Overall, CHNQD-01281 may serve as a potential therapeutic agent for bladder cancer through multiple mechanisms.
Materials selection and fashion design: strengthening reflections on fibre’s nature in fibres and textiles selection
Authors: Mazzitelli Melissa , Papile Flavia , Del Curto Barbara
Published: August 2024

Textile ecosystems are complex productive realities, in the eye of the cyclone when it comes sustainability-related analysis. Being characterised by very complex value-chains and interconnection of productive actors, textiles production and use represent one of the most crucial challenges for the circular and sustainable transition. Their deployment is esteemed to be in growing for the next years, therefore reflections on how to improve product and materials circularity in this sector is of increasing interest in research and industrial practice. In this contribution, authors will try to map the material properties that can influence textiles application in the fashion sector, focusing on the coupling of material selection activity and application of design strategies to anticipate at best the reflections upon textiles use and recirculation. Results of this activity are then shown and discussed to question the applicability of the reported data into a fashion design activity, to promote awareness and critical reflections upon materials use while designing new fashion goods.