bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of navigation apps on congestion and spread dynamics on a transportation network
Authors: Bagabaldo Alben Rome , Gan Qianxin , Bayen Alexandre M. , González Marta C. 
Published: June 2024

AbstractIn recent years, the widespread adoption of navigation apps by motorists has raised questions about their impact on local traffic patterns. Users increasingly rely on these apps to find better, real-time routes to minimize travel time. This study uses microscopic traffic simulations to examine the connection between navigation app use and traffic congestion. The research incorporates both static and dynamic routing to model user behavior. Dynamic routing represents motorists who actively adjust their routes based on app guidance during trips, while static routing models users who stick to known fastest paths. Key traffic metrics, including flow, density, speed, travel time, delay time, and queue lengths, are assessed to evaluate the outcomes. Additionally, we explore congestion propagation at various levels of navigation app adoption. To understand congestion dynamics, we apply a susceptible–infected–recovered (SIR) model, commonly used in disease spread studies. Our findings reveal that traffic system performance improves when 30–60% of users follow dynamic routing. The SIR model supports these findings, highlighting the most efficient congestion propagation-to-dissipation ratio when 40% of users adopt dynamic routing, as indicated by the lowest basic reproductive number. This research provides valuable insights into the intricate relationship between navigation apps and traffic congestion, with implications for transportation planning and management.
High Carbohydrate, Fat, and Protein Diets Have a Critical Role in Folliculogenesis and Oocyte Development in Rats
Authors: Gül Semir , Gül Mehmet , Otlu Barış , Erdemli Mehmet Erman , Gözükara Bağ Harika Gözde 
Published: June 2024

AbstractTo date, there is no comparative data on the effects of carbohydrates, fat, and proteins, which are macronutrients, on female reproductive functions. Therefore, in this study, we investigated the effects of diets enriched with carbohydrates, fats, and proteins on folliculogenesis and oocyte development in female rats. 21-day-old rats that were just weaned were divided into 4 groups: control, carbohydrate, fat, and protein. The control group was fed with standard chow and the carbohydrate, fat, and protein groups were fed diets enriched with 75% carbohydrate, 60% fat, and 50% protein for 11 weeks, respectively. It was found that high-fat and high-protein diets caused an increase in the estrous cycle length compared to carbohydrate group (p < 0.05). Graafian follicle number decreased in the protein group compared to the control (p < 0.05). However, the atretic follicle number was higher in the fat group compared to the control group (p < 0.05). In the carbohydrate group, Zp1 was found to be lower than the control and protein groups, Zp2 was found to be lower than the control, and Zp3 was found to be lower than the fat group (p < 0.05). While BMP15 was similar between groups (p > 0.05), GDF9 was lower in all diet groups compared to the control (p < 0.05). Foxo3a was lower in the protein group compared to carbohydrate and control (p < 0.05). GAS2 was found to be higher in the control group than the fat group, and higher in the carbohydrate group than the fat and protein groups (p < 0.05). FSH, LH, Progesterone, and E2 levels were higher in all three diet groups than in the control (p < 0.05). Also, significant differences were observed between the groups regarding adiponectin, resistin, and leptin levels. Taken together, high carbohydrate, fat, and protein intake are associated with impairment of the menstrual cycle, depletion of the developing follicle types, and altered expression of folliculogenesis-specific genes and hormones. Therefore, long-term macronutrient diets may result in shortened reproductive periods and reduced fertilization potential in females in the long run.
Infiltration and permeability of porous ceramics simulated by random networks
Authors: Mityushev Vladimir , Rylko Natalia , Dolata Anna Janina , Dyzia Maciej 
Published: June 2024

AbstractA network computational model for a 3D ceramic structure is developed. The model is applied to study the impact of geometric and material parameters of structure on the liquid metal flow through random porous ceramic medium in pressure infiltration processes. The characteristic geometric features of the ceramic structure favorable for liquid metal flow during the infiltration process are determined. The method of structural approximation and constructive homogenization are applied, and the discrete stationary Stokes equations on random graphs are considered. This approach gives a robust algorithm to determine the macroscopic permeability K of interpenetrating phases. The dependencies of K on the distribution of connections (windows) between the cells (inclusions) are derived. The numerical simulations demonstrate that the permeability K does not depend on the scaled distribution sizes of windows. This implies that K is proportional to the mean value of the window areas. The considered model takes into account a random complex structure of 3D ceramic. Hence, it complements the previous study on the local transport properties of tubes (windows) connecting the cells.
Pediatric Posterior Fossa Tumors Classification and Explanation-Driven with Explainable Artificial Intelligence Models
Authors: Ashry Eman Ragab , Maghraby Fahima A. , El-Latif Yasser M. Abd , Agag Mohamed 
Published: June 2024

AbstractThe use of deep learning for identifying defects in medical images has rapidly emerged as a significant area of interest across various medical diagnostic applications. The automated recognition of Posterior Fossa Tumors (PFT) in Magnetic Resonance Imaging (MRI) plays a vital role, as it furnishes essential data about irregular tissue, essential for treatment planning. Human examination has traditionally been the standard approach for identifying defects in brain MRI. This technique is unsuitable for a massive quantity of data. Therefore, automated PFT detection techniques are being established to minimize radiologist's time. In this paper, the posterior fossa tumor is detected and classified in brain MRI using Convolutional Neural Network (CNN) algorithms, and the model result and accuracy obtained from each algorithm are explained. A dataset collection made up of 3,00,000 images with an average of 500 patients from the Children's Cancer Hospital Egypt (CCHE) was used. The CNN algorithms investigated to classify the PFT were VGG19, VGG16, and ResNet50. Moreover, explanations for the behavior of networks were investigated using three different techniques: LIME, SHAP, and ICE. Overall, the results showed that the best model was VGG16 compared with other CNN-used models with accuracy rate values of 95.33%, 93.25%, and 87.4%, respectively.
Spectral Solutions of Specific Singular Differential Equations Using A Unified Spectral Galerkin-Collocation Algorithm
Authors: Ahmed H. M. , Abd-Elhameed W. M. 
Published: June 2024

Abstract
This paper presents a novel numerical approach to addressing three types of high-order singular boundary value problems. We introduce and consider three modified Chebyshev polynomials (CPs) of the third kind as proposed basis functions for these problems. We develop new derivative operational matrices for the three modified CPs of the third kind by deriving formulas for their first derivatives. Our approach follows a unified method for numerically handling singular differential equations (DEs). To transform these equations into algebraic systems suitable for numerical treatment, we employ the collocation method in combination with the introduced operational matrices of derivatives of the modified CPs of the third kind. We address the convergence examination for the three expansions in a unified manner. We present numerous numerical examples to demonstrate the accuracy and efficiency of our unified numerical approach.
Local Nanostructure in Multicomponent High-Entropy Materials
Authors: Cantor Brian 
Published: June 2024

AbstractMulticomponent phase space contains extended regions of random or near-random multicomponent solid-solution single phases, stabilised by a relatively large configurational entropy of mixing that can often (though not always) suppress compound formation between the different atomic species. The present paper shows that there are very extensive variations of local nanostructure, local atomic clusters and associated local lattice strains within multicomponent high-entropy solid-solution single phases such as the fcc Cantor alloys, bcc Senkov alloys and rock-salt-structured Rost mono-oxides, even when there is no short-range ordering, i.e. even when the solid solution is completely random or ideal. There are, for instance, many billions of different local nanostructures and different local atomic clusters in equiatomic five-component fully random solid-solution single-phase materials such as the original fcc Cantor alloy CrMnFeCoNi and the original bcc Senkov alloy VNbMoTaW, extending over distances of many microns, with associated fluctuating hydrostatic and shear lattice strains of several percent. The number and extent of the variations in local nanostructure, atomic clusters and lattice strains increase dramatically to even higher values with increasing number of components in the material. The present paper also shows that there are similar variations in local nanostructure, local atomic clusters and associated local lattice strains surrounding point defects such as vacancies, line defects such as dislocations and planar defects such as grain boundaries and external surfaces, influencing many important material properties such as diffusion, plastic flow, recrystallisation, grain growth and catalysis. The number and extent of the variations in local nanostructure, atomic clusters and lattice strains make it difficult to have too much confidence in structures and properties of multicomponent high-entropy materials calculated using ab initio and other atomistic computer modelling techniques, since these techniques are restricted to relatively small numbers of atoms and are unable to sample effectively the full range of local structures and properties.
Wired for society? From ego-logy to eco-logy
Authors: Kaufmann Laurence , Clément Fabrice 
Published: June 2024

Abstract
Somewhat questioning Elizabeth Spelke's attempt to account for infants’ social knowledge, our commentary argues that social cognition might be divided into several specialized systems. In addition to the core system dedicated to the intersubjective dimension of close relationships, infants could be prewired to process social relationships, such as dominance, characterized by their impersonal, normative dimension.
First language effects on incidental vocabulary learning through bimodal input
Authors:   The TwiLex Group
Published: June 2024

AbstractDespite accumulating evidence, accounts for the efficacy of reading-while-listening (RWL) in facilitating vocabulary learning are largely unexamined, hindering a thorough understanding of the reasons underlying the usefulness of such bimodal input. In this article, we report a close replication of Malone (2018), purposefully manipulating the participants’ native language background to shed light on whether the auditory component in RWL promotes spoken-written form mappings. One hundred and eighty-eight English learners from Austria, Belgium, Hong Kong, and Beijing read or read and listened to four stories containing target words for learning. They completed two surprise vocabulary tests and two assessments of working memory capacity. We only replicated a correlation between working memory capacity and the form recognition test reported in the initial study. Thanks to our manipulation, we discovered an important role of L1 background in the effectiveness of RWL for form recognition knowledge. We discuss the implications for RWL research.
Modeling the Propagation of Extremely Low Frequency Electromagnetic Emissions From the Power Lines to the Inner Magnetosphere in a Dipole Field
Authors: Xu Xiang , Zhou Chen , Wang Zhuangkai , Du Xiaohui 
Published: June 2024

AbstractDifferent from power line harmonic radiation (PLHR) events at high harmonics (∼kHz) in the ionosphere and inner magnetosphere, the wave dynamics of power line emission (PLE) (the fundamental frequency 50/60 Hz or PLHR at low harmonics) can be significantly affected by various ion species. In order to investigate the evolution of the wave properties of PLE from power lines to satellite altitudes in a dipole field, a numerical model is developed to perform full‐wave simulations, in which the lithosphere and atmosphere are characterized by electrical conductivity and the ionosphere (inner magnetosphere) is treated as collisional (collisionless) cold plasma consisting of electron, H+, He+, O+, and NO+. Our simulation results show that the spatial distribution and wave properties of PLE are determined by the magnetic latitudes of power lines and plasma densities. PLE from power lines at middle and high magnetic latitudes (|MLAT| > 40°) can propagate to high L shells as whistler waves; PLE from power lines at |MLAT| < 30° usually propagate at low L shells below local He+ cyclotron frequency as left‐handedly polarized or right‐handedly He+ band electromagnetic ion cyclotron (EMIC) waves. The amplitude of PLE is usually stronger with smaller electron density in the space plasma medium. With power lines at |MLAT| < 30°, the coupling efficiency between different right‐handedly polarized EMIC wave modes of PLE decreases significantly with electron density. Wave properties of PLE including Poynting vector direction, wave normal angle and wave polarization obtained from our simulation results are consistent with some of the recent observations using Van Allen Probes.
Intensification of Mid‐Latitude Cyclone by Aerosol‐Radiation Interaction Increases Transport of Canadian Wildfire Smoke to Northeastern US
Authors: Wang Zilin , Huang Xin , Xue Lian , Ding Ke , Lou Sijia , Zhu Anbao , Ding Aijun 
Published: June 2024

AbstractWildfires have long been regarded as one chief culprit in regional air pollution, and pose great impacts on climate change. Although climate forcing of wildfire smoke has been widely investigated, its influence on synoptic systems remains unclear. Based on measurement and modeling analysis, the impact of wildfire smoke on the development of a mid‐latitude cyclone was revealed for Canadian wildfires in early June of 2023. The radiative forcing induced by smoke at surface and in the atmosphere reached up to −150 and 100 W m−2, posing opposite tendencies of atmospheric stratification over the land and ocean. Such perturbations contributed to the enhancement and stagnation of the cyclone, which favored the transport of smoke from the fire‐intensive region, indicated by nearly 40% increment of PM2.5 mass flux. With escalating wildfire risk in the future, the inclusion of smoke aerosols' impacts on meteorology in weather forecast models is of great importance.
Quantitative phase imaging based on holography: trends and new perspectives
Authors: Huang Zhengzhong , Cao Liangcai 
Published: June 2024

AbstractIn 1948, Dennis Gabor proposed the concept of holography, providing a pioneering solution to a quantitative description of the optical wavefront. After 75 years of development, holographic imaging has become a powerful tool for optical wavefront measurement and quantitative phase imaging. The emergence of this technology has given fresh energy to physics, biology, and materials science. Digital holography (DH) possesses the quantitative advantages of wide-field, non-contact, precise, and dynamic measurement capability for complex-waves. DH has unique capabilities for the propagation of optical fields by measuring light scattering with phase information. It offers quantitative visualization of the refractive index and thickness distribution of weak absorption samples, which plays a vital role in the pathophysiology of various diseases and the characterization of various materials. It provides a possibility to bridge the gap between the imaging and scattering disciplines. The propagation of wavefront is described by the complex amplitude. The complex-value in the complex-domain is reconstructed from the intensity-value measurement by camera in the real-domain. Here, we regard the process of holographic recording and reconstruction as a transformation between complex-domain and real-domain, and discuss the mathematics and physical principles of reconstruction. We review the DH in underlying principles, technical approaches, and the breadth of applications. We conclude with emerging challenges and opportunities based on combining holographic imaging with other methodologies that expand the scope and utility of holographic imaging even further. The multidisciplinary nature brings technology and application experts together in label-free cell biology, analytical chemistry, clinical sciences, wavefront sensing, and semiconductor production.
Fully flexible implantable neural probes for electrophysiology recording and controlled neurochemical modulation
Authors: Malekoshoaraie Mohammad Hassan , Wu Bingchen , Krahe Daniela D. , Ahmed Zabir , Pupa Stephen , Jain Vishal , Cui Xinyan Tracy , Chamanzar Maysamreza 
Published: June 2024

AbstractTargeted delivery of neurochemicals and biomolecules for neuromodulation of brain activity is a powerful technique that, in addition to electrical recording and stimulation, enables a more thorough investigation of neural circuit dynamics. We have designed a novel, flexible, implantable neural probe capable of controlled, localized chemical stimulation and electrophysiology recording. The neural probe was implemented using planar micromachining processes on Parylene C, a mechanically flexible, biocompatible substrate. The probe shank features two large microelectrodes (chemical sites) for drug loading and sixteen small microelectrodes for electrophysiology recording to monitor neuronal response to drug release. To reduce the impedance while keeping the size of the microelectrodes small, poly(3,4-ethylenedioxythiophene) (PEDOT) was electrochemically coated on recording microelectrodes. In addition, PEDOT doped with mesoporous sulfonated silica nanoparticles (SNPs) was used on chemical sites to achieve controlled, electrically-actuated drug loading and releasing. Different neurotransmitters, including glutamate (Glu) and gamma-aminobutyric acid (GABA), were incorporated into the SNPs and electrically triggered to release repeatedly. An in vitro experiment was conducted to quantify the stimulated release profile by applying a sinusoidal voltage (0.5 V, 2 Hz). The flexible neural probe was implanted in the barrel cortex of the wild-type Sprague Dawley rats. As expected, due to their excitatory and inhibitory effects, Glu and GABA release caused a significant increase and decrease in neural activity, respectively, which was recorded by the recording microelectrodes. This novel flexible neural probe technology, combining on-demand chemical release and high-resolution electrophysiology recording, is an important addition to the neuroscience toolset used to dissect neural circuitry and investigate neural network connectivity.
Dramatic improvements in outcome following pancreatoduodenectomy for pancreatic and periampullary cancers
Authors: Xu Hui , Bretthauer Michael , Fang Fang , Ye Weimin , Yin Li , Adami Hans-Olov 
Published: June 2024

Abstract
Background
Pancreatoduodenectomy is the only cure for cancers of the pancreas and the periampullary region but has considerable operative complications and uncertain prognosis. Our goal was to analyse temporal improvements and provide contemporary population-based benchmarks for outcomes following pancreatoduodenectomy.

Methods
We empanelled a cohort comprising all patients in Sweden with pancreatic or periampullary cancer treated with pancreatoduodenectomy from 1964 to 2016 and achieved complete follow-up through 2016. We analysed postoperative deaths and disease-specific net survival.

Results
We analysed 5923 patients with cancer of the pancreas (3876), duodenum (444), bile duct (504), or duodenal papilla (963) who underwent classic (3332) or modified (1652) Whipple’s procedure or total pancreatectomy (803). Postoperative deaths declined from 17.2% in the 1960s to 1.6% in the contemporary time period (2010–2016). For all four cancer types, median, 1-year and 5-year survival improved substantially over time. Among patients operated between 2010 and 2016, 5-year survival was 29.0% (95% confidence interval (CI): 25.5, 33.0) for pancreatic cancer, 71.2% (95% CI: 62.9, 80.5) for duodenal cancer, 30.8% (95% CI: 23.0, 41.3) for bile duct cancer, and 62.7% (95% CI: 55.5, 70.8) for duodenal papilla cancer.

Conclusion
There is a continuous and substantial improvement in the benefit-harm ratio after pancreatoduodenectomy for cancer.
4-1BB-encoding CAR causes cell death via sequestration of the ubiquitin-modifying enzyme A20
Authors: Dou Zhangqi , Bonacci Thomas Raphael , Shou Peishun , Landoni Elisa , Woodcock Mark G. , Sun Chuang , Savoldo Barbara , Herring Laura E. , Emanuele Michael J. , Song Feifei , Baldwin Albert S. , Wan Yisong , Dotti Gianpietro , Zhou Xin 
Published: June 2024

AbstractCD28 and 4-1BB costimulatory endodomains included in chimeric antigen receptor (CAR) molecules play a critical role in promoting sustained antitumor activity of CAR-T cells. However, the molecular events associated with the ectopic and constitutive display of either CD28 or 4-1BB in CAR-T cells have been only partially explored. In the current study, we demonstrated that 4-1BB incorporated within the CAR leads to cell cluster formation and cell death in the forms of both apoptosis and necroptosis in the absence of CAR tonic signaling. Mechanistic studies illustrate that 4-1BB sequesters A20 to the cell membrane in a TRAF-dependent manner causing A20 functional deficiency that in turn leads to NF-κB hyperactivity, cell aggregation via ICAM-1 overexpression, and cell death including necroptosis via RIPK1/RIPK3/MLKL pathway. Genetic modulations obtained by either overexpressing A20 or releasing A20 from 4-1BB by deleting the TRAF-binding motifs of 4-1BB rescue cell cluster formation and cell death and enhance the antitumor ability of 4-1BB-costimulated CAR-T cells.
C-H-activated Csp2-Csp3 diastereoselective gridization enables ultraviolet-emitting stereo-molecular nanohydrocarbons with mulitple H···H interactions
Authors: Wei Ying , Zhong Chunxiao , Sun Yue , Ma Shuwei , Ni Mingjian , Wu Xiangping , Yan Yongxia , Yang Lei , Khodov Ilya A. , Ge Jiaoyang , Li Yang , Lin Dongqing , Wang Yongxia , Bao Qiujing , Zhang He , Wang Shasha , Song Juan , Lin Jinyi , Xie Linghai , Huang Wei 
Published: June 2024

AbstractGridization is an emerging molecular integration technology that enables the creation of multifunctional organic semiconductors through precise linkages. While Friedel-Crafts gridization of fluorenols is potent, direct linkage among fluorene molecules poses a challenge. Herein, we report an achiral Pd-PPh3-cataylized diastereoselective (>99:1 d.r.) gridization based on the C-H-activation of fluorene to give dimeric and trimeric windmill-type nanogrids (DWGs and TWGs). These non-conjugated stereo-nanogrids showcase intramolecular multiple H…H interactions with a low field shift to 8.51 ppm and circularly polarized luminescence with high luminescent dissymmetry factors (|gPL | = 0.012). Significantly, the nondoped organic light-emitting diodes (OLEDs) utilizing cis-trans-TWG1 emitter present an ultraviolet electroluminescent peak at ~386 nm (CIE: 0.17, 0.04) with a maximum external quantum efficiency of 4.17%, marking the highest record among nondoped ultraviolet OLEDs based on hydrocarbon compounds and the pioneering ultraviolet OLEDs based on macrocycles. These nanohydrocarbon offer potential nanoscafflolds for ultraviolet light-emitting optoelectronic applications.