bluuebunny/crossref_metadata_2025_split huggingface dataset:
The graded ring database for Fano 3-folds and the Bogomolov stability bound
Authors: Suzuki Kaori 
Published: May 2024

AbstractMy paper (Suzuki 2003) produced some computer routines in Magma (Bosma et al. J Symb Comp 24:235–265, 1997) for the numerical invariants of Fano 3-folds, and used them in particular to determine the maximum value $$f=19$$

f
=
19

of the Fano index. As a byproduct of the research, extensive data associated with all possible sets of singular points of Fano 3-folds with Fano indices greater than or equal to 2 was obtained. Collaborative research with Gavin Brown developed an improved version of the Magma program. The data discussed above was added to the Graded Ring Data Base (Brown et al. 2015) at the University of Kent. Subsequently, GRDB, now located to the University of Warwick, recently modified its interface to accommodate additional conditions, facilitating a more refined selection of Fano manifolds. In this context, we focus on the inequality known as the Bogomolov stability bound. We present a list of candidates for Fano 3-folds that do not satisfy these conditions and propose the conjecture that they do not exist.This result has been independently obtained in Liu and Liu (2023).
Zur Anwendung der Neufassung von § 64 StGB bei Jugendlichen und Heranwachsenden – rechts- und erfahrungswissenschaftliche Perspektiven
Authors: Schwarz Michael , Kaspar Johannes , Werner Raik , Groß Gregor , Stübner Susanne 
Published: May 2024

ZusammenfassungAm 01.10.2023 ist die Novellierung von § 64 des Strafgesetzbuches (StGB) in Kraft getreten. Der vorliegende Beitrag beschäftigt sich aus rechts- und erfahrungswissenschaftlicher Sicht mit den Besonderheiten der Anwendung bei straffälligen Jugendlichen und Heranwachsenden mit Substanzgebrauchsstörung. Auf Basis empirischer Befunde zu Jugenddelinquenz und Jugendmaßregelvollzug werden Problemfelder dargelegt, die sich infolge der Konturierung der Anordnungsvoraussetzungen von § 64 StGB ergeben könnten, sowie Anregungen zum diesbezüglichen Umgang gegeben.
Algebraic periods and minimal number of periodic points for smooth self-maps of $$\textbf{1}$$-connected $$\textbf{4}$$-manifolds with definite intersection forms
Authors: Duan Haibao , Graff Grzegorz , Jezierski Jerzy , Myszkowski Adrian 
Published: May 2024

AbstractLet M be a closed 1-connected smooth 4-manifolds, and let r be a non-negative integer. We study the problem of finding minimal number of r-periodic points in the smooth homotopy class of a given map $$f:M \rightarrow M$$

f
:
M
→
M

. This task is related to determining a topological invariant $$D^4_r[f]$$

D
r
4

[
f
]

, defined in Graff and Jezierski (Forum Math 21(3):491–509, 2009), expressed in terms of Lefschetz numbers of iterations and local fixed point indices of iterations. Previously, the invariant was computed for self-maps of some 3-manifolds. In this paper, we compute the invariants $$D^4_r[f]$$

D
r
4

[
f
]

for the self-maps of closed 1-connected smooth 4-manifolds with definite intersection forms (i.e., connected sums of complex projective planes). We also present some efficient algorithmic approach to investigate that problem
Volterra and Composition Inner Derivations on the Fock–Sobolev Spaces
Authors: Yang Xueyan , He Hua , Tong Cezhong , Arroussi Hicham 
Published: May 2024

AbstractOn the Fock–Sobolev spaces, we study the range of Volterra inner derivations and composition inner derivations. The Volterra inner derivation ranges in the ideal of compact operators if and only if the induced function g is a linear polynomial. The composition inner derivation ranges in the ideal of compact operators if and only if the induced function $$\varphi $$
φ
is either identity or a contractive linear self-mapping of $$\mathbb {C}$$
C
. Moreover, we describe the compact intertwining relations for composition operators and Volterra operators between different Fock–Sobolev spaces. In this paper, our results are complement and in a sense extend some aspects of Calkin’s result (Ann Math 42:839–873, 1941) to the algebras of bounded linear operators on Fock–Sobolev spaces.
Exploring the applicability of the experiment-based ANN and LSTM models for streamflow estimation
Authors: Akiner Muhammed Ernur , Kartal Veysi , Guzeler Anil Can , Karakoyun Erkan 
Published: May 2024

AbstractThe Yeşilırmak River Basin in northern Türkiye is crucial for the region’s water supply, agriculture, hydroelectric power generation, and clean drinking water. The primary goal of this study is to determine which modeling approach is most appropriate for various locations within the basin and how well meteorological data can predict river flow rates. Hydrological and meteorological forecasting both depend on the prediction of river flow rates. An artificial neural network (ANN), Univariate and Multivariate Long Short-Term Memory (LSTM) models have been utilized for streamflow forecasting. This research aims to determine the best model for several provinces in the basin area and give decision-makers a tool for reliable river flow rate estimates by combining LSTM and ANN models. According to research findings, the supervised multivariate LSTM model performed better than the unsupervised model in accuracy and precision. The sliding window methodology is suitable for estimating river flow based on meteorological datasets because it offers a primary method for reinterpreting time-series data in a supervised learning style. Compared to LSTM models, the ANN model that has been statistically optimized through experiments (DoE) design performs better in forecasting the river flow rate in the Yeşilırmak River basin (R2 = 0.98, RMSE = 0.18). The study’s findings provided prospective cognitive models for the strategic management of water resources by forecasting future data from flow monitoring stations.
Implications of Some Mass-Capacity Inequalities
Authors: Miao Pengzi 
Published: May 2024

AbstractApplying a family of mass-capacity related inequalities proved in Miao (Peking Math J 2023, https://doi.org/10.1007/s42543-023-00071-7), we obtain sufficient conditions that imply the nonnegativity as well as positive lower bounds of the mass, on a class of manifolds with nonnegative scalar curvature, with or without a singularity.
Impact of Artificial Weathering on Swimwear Fabric
Authors: Cüreklibatır Encan Berna 
Published: May 2024

AbstractLately, being physically active has become a priority of daily life. Despite that outdoor sports boost an individual’s mental and physical health, it also generates the problem of ultraviolet light exposure. Clothes provide the wearer protection from the sun, but they are also damaged while completing this task. Therefore, the impact of ultraviolet aging on swimwear fabric, which is the most exposed type of garment to the sunrays, was investigated in this study. Changes in breaking force, elongation at break, air permeability, fabric elasticity and stiffness, and dimensional characteristics were examined after 120 and 240 h of artificial weathering, together with scanning electron microscope (SEM) images and Fourier-Transform Infrared (FTIR) spectroscopy. The influence of seawater treatment was explored as well. The results presented that breaking force, elongation at break, fabric elasticity and stiffness, and air permeability were dramatically influenced by ultraviolet exposure. No chemical destruction was observed in FTIR spectra, while micro-damages were detected in SEM images. Furthermore, it was concluded that the main detrimental parameter was UV radiation, and the effect of seawater treatment was usually found to be minimal or not distinctive. Due to the limited number of research on the impact of UV aging on warp-knitted swimwear, this study is expected to contribute to the related literature.
Extracellular vesicle-mediated drug delivery in breast cancer theranostics
Authors: Abdul-Rahman Toufik , Roy Poulami , Herrera-Calderón Ranferi Eduardo , Khidri Feriha Fatima , Omotesho Quadri Ajibola , Rumide Tolulope Sharon , Fatima Mahek , Roy Sakshi , Wireko Andrew Awuah , Atallah Oday , Roy Subham , Amekpor Felix , Ghosh Shankhaneel , Agyigra Isaac Aksavdwa , Horbas Viktoriia , Teslyk Tetiana , Bumeister Valentyna , Papadakis Marios , Alexiou Athanasios 
Published: May 2024

AbstractBreast cancer (BC) continues to be a significant global challenge due to drug resistance and severe side effects. The increasing prevalence is alarming, requiring new therapeutic approaches to address these challenges. At this point, Extracellular vesicles (EVs), specifically small endosome-released nanometer-sized EVs (SEVs) or exosomes, have been explored by literature as potential theranostics. Therefore, this review aims to highlight the therapeutic potential of exosomes in BC, focusing on their advantages in drug delivery and their ability to mitigate metastasis. Following the review, we identified exosomes' potential in combination therapies, serving as miRNA carriers and contributing to improved anti-tumor effects. This is evident in clinical trials investigating exosomes in BC, which have shown their ability to boost chemotherapy efficacy by delivering drugs like paclitaxel (PTX) and doxorubicin (DOX). However, the translation of EVs into BC therapy is hindered by various challenges. These challenges include the heterogeneity of EVs, the selection of the appropriate parent cell, the loading procedures, and determining the optimal administration routes. Despite the promising therapeutic potential of EVs, these obstacles must be addressed to realize their benefits in BC treatment.
GAS5 regulated by FTO-mediated m6A modification suppresses cell proliferation via the IGF2BP2/QKI axis in breast cancer
Authors: Yan Yuzhao , Ma Jing , Chen Qingqiu , Zhang Ting , Fan Rui , Du Junze 
Published: May 2024

Abstract
Background
The lncRNA growth arrest-specific 5 (GAS5) is involved in regulating breast cancer progression. In this study, we aimed to elucidate the function and mechanism of GAS5 in breast cancer.

Methods
The expressions of GAS5, fat mass and obesity-associated protein (FTO), insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2), and Quaking (QKI) were assessed by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and western blot. The m6A modification level of GAS5 was detected using m6A immunoprecipitation assay (MeRIP). The interaction between IGF2BP2 and GAS5 or QKI was detected using RNA immunoprecipitation assay (RIP) and dual luciferase reporter assay. Cell proliferation was measured using the Cell Counting Kit-8 (CCK-8) assay. The biological functions of the FTO/GAS5/IGF2BP2/QKI axis was assessed using the tumor xenograft assay.

Results
LncRNA GAS5 expression decreased in breast cancer and was regulated by FTO-mediated m6A modification in an IGF2BP2-dependent manner, resulting in decreased GAS5 stability and expression. GAS5 recruited IGF2BP2 to target QKI and upregulated QKI expression in breast cancer cells. GAS5 suppressed breast cancer growth via IGF2BP2/QKI, and this inhibitory effect was modulated by FTO both in vitro and in vivo.

Conclusions
GAS5 regulated by FTO-mediated m6A modification represses the growth of breast cancer via the IGF2BP2/QKI pathway, suggesting that the FTO/GAS5/IGF2BP2/QKI pathway can be a potential target for breast cancer treatment.
The effect of electrical current on lubricant film thickness in boundary and mixed lubrication contacts measured with ultrasound
Authors: Cao-Romero-Gallegos Julio A. , Taghizadeh Saeid , Aguilar-Rosas Oscar A. , Dwyer-Joyce R. S. , Farfan-Cabrera Leonardo I. 
Published: May 2024

AbstractThis work explores experimentally the effects of DC electrical currents on lubricant film thickness alteration in lubricated sliding steel contacts in the boundary and mixed regime as measured by ultrasound. The experiments were performed in a two-electrode cell-based pin-on-disk tester instrumented with ultrasonic transducers. Unelectrified and electrified tribological tests were conducted on steel flat-on-flat contacts under various speeds and loads using both a mineral base oil and a gear oil. Film thickness, coefficient of friction (CoF), and electrical contact resistance (ECR) were measured during short experiments (30 s) in unelectrified and electrified (1.5 and 3 A) conditions. The results suggest that film thickness, CoF, and all ECR are altered by passing DC currents through the contact. In particular, film thickness increased and decreased, respectively, by applying electricity at the different speeds and loads tested. These alterations were majorly ascribed to oil viscosity decrease by local heat and surface oxidation caused by electrical discharge and break down at the interface.
Artificial intelligence multiprocessing scheme for pathology images based on transformer for nuclei segmentation
Authors: Gou Fangfang , Tang Xinrong , Liu Jun , Wu Jia 
Published: May 2024

AbstractMalignant tumors are a common cytopathologic disease. Pathological tissue examination is a key tool for diagnosing malignant tumors. Doctors need to manually analyze the images of pathological tissue sections, which is not only time-consuming but also highly subjective, easily leading to misdiagnosis. Most of the existing computer-aided diagnostic techniques focus too much on accuracy when processing pathological tissue images, and do not take into account the problems of insufficient resources in developing countries to meet the training of large models and the difficulty of obtaining medical annotation data. Based on this, this study proposes an artificial intelligence multiprocessing scheme (MSPInet) for digital pathology images of malignant tumors. We use techniques such as data expansion and noise reduction to enhance the dataset. Then we design a coarse segmentation method for cell nuclei of pathology images based on Transformer for Semantic Segmentation and further optimize the segmentation of tumor edges using conditional random fields. Finally, we improve the training strategy for knowledge distillation. As a medical assistive system, the method can quantify and convert complex pathology images into analyzable image information. Experimental results show that our method performs well in terms of segmentation accuracy and also has advantages in terms of time and space efficiency. This makes our technology available to developing countries that are not as well resourced, and equipped in terms of medical care. The teacher model and lightweight student model included in our method achieve 71.6% and 66.1% Intersection over Union (IoU) in cell segmentation respectively, outperforming Swin-unet and CSWin Transformer.
Situational diversity in video person re-identification: introducing MSA-BUPT dataset
Authors: Zhao Ruining , Liu Jiaxuan , Zhao Zhicheng , He Ziqi , Su Fei 
Published: May 2024

AbstractThanks to the success of deep learning over the past few years, the video person re-identification (ReID) algorithms have achieved high accuracy on multiple public benchmark datasets. However, the available video person ReID datasets cover a limited range of real-world scenarios, and they have several obvious limitations: limited camera viewing angles, tiny variations of the shooting scene, and even errors in manual labels. These disadvantages prevent video person ReID from being widely used in real-life scenarios. In this work, a new high-quality multi-situation video person ReID dataset, named MSA-BUPT, is built to promote the video person ReID task in large-scale urban surveillance. Specifically, MSA-BUPT contains 684 identities, 2,665 trajectories, and nearly 250,000 frames from 200-h videos across various complex scenarios. Person attribute annotations and unannotated video data are also provided for other research perspectives, such as cross-modality ReID, cross-domain ReID, and so on. Furthermore, two plug-and-play components are used to improve retrieval capabilities: a new scenario-based data augmentation method is proposed to alleviate the person misalignment problem; a re-ranking strategy based on person attribute is applied to make secondary adjustments to the content to the results of the model. The extensive experimental results show that the above methods improve the performance of some representative state-of-the-art models on the new dataset.
Multifunctional Integrated Organic–Inorganic-Metal Hybrid Aerogel for Excellent Thermal Insulation and Electromagnetic Shielding Performance
Authors: Niu Zhaoqi , Qu Fengjin , Chen Fang , Ma Xiaoyan , Chen Beixi , Wang Luyao , Xu Miao , Wang Shumeng , Jin Liang , Zhang Chengshuang , Hou Xiao 
Published: May 2024

AbstractVehicles operating in space need to withstand extreme thermal and electromagnetic environments in light of the burgeoning of space science and technology. It is imperatively desired to high insulation materials with lightweight and extensive mechanical properties. Herein, a boron–silica–tantalum ternary hybrid phenolic aerogel (BSiTa-PA) with exceptional thermal stability, extensive mechanical strength, low thermal conductivity (49.6 mW m−1 K−1), and heightened ablative resistance is prepared by an expeditious method. After extremely thermal erosion, the obtained carbon aerogel demonstrates noteworthy electromagnetic interference (EMI) shielding performance with an efficiency of 31.6 dB, accompanied by notable loading property with specific modulus of 272.8 kN·m kg−1. This novel design concept has laid the foundation for the development of insulation materials in more complex extreme environments.
Serving adults who have difficulty reading: challenges faced by U.S. adult education administrators
Authors: Pickard Amy 
Published: May 2024

AbstractRecent assessments suggest that 43 million adults in the United States have difficulty completing basic reading tasks. Although the federal Workforce Innovation and Opportunities Act (WIOA) prioritizes education for adults with the greatest needs, there is long-standing concern that federally-funded programs might not serve lower-performing students well. This study sought the perspectives of state administrators of WIOA-funded adult education to identify challenges in serving adults who have difficulty reading and areas for future research. Identifying challenges and creating a robust evidence base can center adults who have difficulty reading as important participants in the field of practice and support the creation of effective strategies for their inclusion and success in WIOA-funded programming.
Knowing the spectral directional emissivity of 316L and AlSi10Mg PBF-LB/M surfaces: gamechanger for quantitative in situ monitoring
Authors: Becker Tina , Stark Thomas , Arduini Mariacarla , Manara Jochen , Altenburg Simon J. 
Published: May 2024

AbstractFor a deep process understanding of the laser powder bed fusion process (PBF-LB/M), recording of the occurring surface temperatures is of utmost interest and would help to pave the way for reliable process monitoring and quality assurance. A notable number of approaches for in-process monitoring of the PBF-LB/M process focus on the monitoring of thermal process signatures. However, due to the elaborate calibration effort and the lack of knowledge about the occurring spectral directional emissivity $${{\varepsilon }^{\prime}}_{\lambda }$$

ε

′

λ

, only a few approaches attempt to measure real temperatures. In this study, to gain initial insights into $${{\varepsilon }^{\prime}}_{\lambda }$$

ε

′

λ

occurring in the PBF-LB/M process, measurements on PBF-LB/M specimens and metal powder specimens were performed for higher temperatures up to T = 1290 °C by means of the emissivity measurement apparatus (EMMA) of the Center for Applied Energy Research (CAE, Wuerzburg, Germany). Also, measurements at ambient temperatures were performed with a suitable measurement setup. Two different materials—stainless steel 316L and aluminum AlSi10Mg—were examined. The investigated wavelength λ ranges from the visible range ($${\lambda }_{VIS}$$

λ

VIS

= 0.40–0.75 µm) up to the infrared, λ = 20 µm. The influence of the following factors were investigated: azimuth angle φ, specimen temperature TS, surface texture as for PBF-LB/M surfaces with different scan angles α, and powder surfaces with different layer thicknesses $$t$$
t
.
β-Modification in heterogeneous polypropylene for laser-based powder bed fusion of polymers
Authors: Cholewa Simon , Forstner Thomas , Jaksch Andreas , Drummer Dietmar 
Published: May 2024

AbstractCurrently, polyamides serve as the primary material used in laser-based powder bed fusion of polymers (PBF-LB/P), which prevents the components from exhibiting the mechanical characteristics of traditional manufacturing techniques. As a result, highly ductile and chemical-resistant materials are needed to cover more potential application areas. The preferred material is polypropylene (PP) with various structures and settings. A common practice in conventional manufacturing processes is adjusting the morphology of the component, but studies examining this type of influence in PBF-LB/P are scarce. In addition to examining important PBF-LB/P process characteristics like thermal properties and powder flow behavior, this work first presents potential nucleation agents and then manufactures components to assess the impact of the structure. It was concluded that processing the material is possible despite significantly higher crystallization kinetics. A parameter study was conducted to evaluate the initial PBF-LB/P processability by building single and triple layers. These results led to the creation of mechanical specimens that showed the material system’s processability. For the first time, it was possible to process β-nucleated PP, which displays increased elongation at break for higher β-content.
AutoDetect: Novel Autoencoding Architecture for Counterfeit IC Detection
Authors: Bhure Chaitanya , Nicholas Geraldine Shirley , Ghosh Shajib , Asadi Navid , Saqib Fareena 
Published: May 2024

AbstractThe global electronic supply chain industry is a complex and interconnected network of companies, organizations, and individuals that collaborate to produce and distribute electronic devices and components. It plays a critical role in the global economy, as electronic devices have become an essential part of modern life. Electronic components and devices are produced and distributed across the world, with different regions and countries specializing in different aspects of the supply chain. This global nature of the electronic supply chain industry also poses challenges, particularly in terms of quality control and supply chain transparency involving counterfeit components owing to its interconnected nature. Counterfeiting of integrated circuits (ICs) and semiconductor devices is a significant challenge that poses threats to the safety and reliability of electronic devices, the global economy, intellectual property rights, and the overall sustainability of the electronic supply chain industry. To address this challenge, we propose a novel autoencoding architecture for counterfeit IC detection using a labeled database. The proposed architecture achieves an overall accuracy of 83% which is $$\approx$$
≈
20% more than the existing transfer learning approaches.