bluuebunny/crossref_metadata_2025 huggingface dataset:
RETRACTED ARTICLE: Confidence level based complex polytopic fuzzy Einstein aggregation operators and their application to decision-making process
Authors: Rahman Khaista , Khishe Mohammad
Published: July 2024

A complex Polytopic fuzzy set (CPoFS) extends a Polytopic fuzzy set (PoFS) by handling vagueness with degrees that range from real numbers to complex numbers within the unit disc. This extension allows for a more nuanced representation of uncertainty. In this research, we develop Complex Polytopic Fuzzy Sets (CPoFS) and establish basic operational laws of CPoFS. Leveraging these laws, we introduce new operators under a confidence level, including the confidence complex Polytopic fuzzy Einstein weighted geometric aggregation (CCPoFEWGA) operator, the confidence complex Polytopic fuzzy Einstein ordered weighted geometric aggregation (CCPoFEOWGA) operator, the confidence complex Polytopic fuzzy Einstein hybrid geometric aggregation (CCPoFEHGA) operator, the induced confidence complex Polytopic fuzzy Einstein ordered weighted geometric aggregation (I-CCPoFEOWGA) operator and the induced confidence complex Polytopic fuzzy Einstein hybrid geometric aggregation (I-CCPoFEHGA) operator, enhancing decision-making precision in uncertain environments. We also investigate key properties of these operators, including monotonicity, boundedness, and idempotency. With these operators, we create an algorithm designed to solve multiattribute decision-making problems in a Polytopic fuzzy environment. To demonstrate the effectiveness of our proposed method, we apply it to a numerical example and compare its flexibility with existing methods. This comparison will underscore the advantages and enhancements of our approach, showing its efficiency in managing complex decision-making scenarios. Through this, we aim to demonstrate how our method provides superior performance and adaptability across different situations.
Temporally extended successor feature neural episodic control
Authors: Zhu Xianchao
Published: July 2024

One of the long-term goals of reinforcement learning is to build intelligent agents capable of rapidly learning and flexibly transferring skills, similar to humans and animals. In this paper, we introduce an episodic control framework based on the temporal expansion of subsequent features to achieve these goals, which we refer to as Temporally Extended Successor Feature Neural Episodic Control (TESFNEC). This method has shown impressive results in significantly improving sample efficiency and elegantly reusing previously learned strategies. Crucially, this model enhances agent training by incorporating episodic memory, significantly reducing the number of iterations required to learn the optimal policy. Furthermore, we adopt the temporal expansion of successor features a technique to capture the expected state transition dynamics of actions. This form of temporal abstraction does not entail learning a top-down hierarchy of task structures but focuses on the bottom-up combination of actions and action repetitions. Thus, our approach directly considers the temporal scope of sequences of temporally extended actions without requiring predefined or domain-specific options. Experimental results in the two-dimensional object collection environment demonstrate that the method proposed in this paper optimizes learning policies faster than baseline reinforcement learning approaches, leading to higher average returns.
Identification of key biomarkers for early warning of diabetic retinopathy using BP neural network algorithm and hierarchical clustering analysis
Authors: Li Peiyu , Wang Hui , Tian Guo , Fan Zhihui
Published: July 2024

Diabetic retinopathy is one of the most common microangiopathy in diabetes, essentially caused by abnormal blood glucose metabolism resulting from insufficient insulin secretion or reduced insulin activity. Epidemiological survey results show that about one third of diabetes patients have signs of diabetic retinopathy, and another third may suffer from serious retinopathy that threatens vision. However, the pathogenesis of diabetic retinopathy is still unclear, and there is no systematic method to detect the onset of the disease and effectively predict its occurrence. In this study, we used medical detection data from diabetic retinopathy patients to determine key biomarkers that induce disease onset through back propagation neural network algorithm and hierarchical clustering analysis, ultimately obtaining early warning signals of the disease. The key markers that induce diabetic retinopathy have been detected, which can also be used to explore the induction mechanism of disease occurrence and deliver strong warning signal before disease occurrence. We found that multiple clinical indicators that form key markers, such as glycated hemoglobin, serum uric acid, alanine aminotransferase are closely related to the occurrence of the disease. They respectively induced disease from the aspects of the individual lipid metabolism, cell oxidation reduction, bone metabolism and bone resorption and cell function of blood coagulation. The key markers that induce diabetic retinopathy complications do not act independently, but form a complete module to coordinate and work together before the onset of the disease, and transmit a strong warning signal. The key markers detected by this algorithm are more sensitive and effective in the early warning of disease. Hence, a new method related to key markers is proposed for the study of diabetic microvascular lesions. In clinical prediction and diagnosis, doctors can use key markers to give early warning of individual diseases and make early intervention.
A retrospective cross-sectional study of risk factors for communicable disease diagnoses among refugees in mainland Greek camps, 2016–2017
Authors: Scales Sarah Elizabeth , Park Jee Won , Nixon Rebecca , Guha-Sapir Debarati , Horney Jennifer A.
Published: July 2024

Communicable disease risk is high in refugee camps and reception centers. To better understand the risks for communicable disease diagnoses among refugees and asylum seekers, this study assesses individual- and camp-level risk factors among individuals utilizing Médecins du Monde clinics in four large refugee camps—Elliniko, Malakasa, Koutsochero, and Raidestos—on mainland Greece between July 2016 and May 2017. Descriptive statistics are reported for the demographic characteristics of the study population and for communicable disease burdens within the four camps—Elliniko, Malakasa, Raidestos, and Koutsochero. A hierarchical generalized linear model was used to assess risk factors for communicable disease diagnoses while accounting for individual-level clustering. This study shows marginal patterns in risk factors for communicable disease. Males had marginally higher risk of communicable disease diagnosis than females (OR = 1.12; 95% CI 0.97—1.29), and increased age was more protective against communicable disease for females (OR = 0.957; 95% CI 0.953—0.961) than for males (OR = 0.963; 95% CI 0.959—0.967). Communicable disease risk was significantly different between camps, with Elliniko (OR = 1.58; 95% CI 1.40–1.79) and Malakasa (OR = 1.43; 95% CI 1.25–1.63) having higher odds of communicable disease than Raidestos. The demographic and epidemiologic profiles of displaced populations differ across settings, and epidemiologic baselines for displaced populations are fundamental to evidence-informed provision of humanitarian aid. Further, while influences and risks for negative health outcomes in complex emergencies are broadly, the causal mechanisms that underpin these relationships are not as well understood. Both practitioners and researchers should engage with further research to elucidate the mechanisms through which these risks operate among displaced populations, including multilevel analyses.
SIGNIFICANCE deep learning based platform to fight illicit trafficking of Cultural Heritage goods
Authors: Malinverni Eva Savina , Abate Dante , Agapiou Antonia , Stefano Francesco Di , Felicetti Andrea , Paolanti Marina , Pierdicca Roberto , Zingaretti Primo
Published: July 2024

The illicit traffic of cultural goods remains a persistent global challenge, despite the proliferation of comprehensive legislative frameworks developed to address and prevent cultural property crimes. Online platforms, especially social media and e-commerce, have facilitated illegal trade and pose significant challenges for law enforcement agencies. To address this issue, the European project SIGNIFICANCE was born, with the aim of combating illicit traffic of Cultural Heritage (CH) goods. This paper presents the outcomes of the project, introducing a user-friendly platform that employs Artificial Intelligence (AI) and Deep learning (DL) to prevent and combat illicit activities. The platform enables authorities to identify, track, and block illegal activities in the online domain, thereby aiding successful prosecutions of criminal networks. Moreover, it incorporates an ontology-based approach, providing comprehensive information on the cultural significance, provenance, and legal status of identified artefacts. This enables users to access valuable contextual information during the scraping and classification phases, facilitating informed decision-making and targeted actions. To accomplish these objectives, computationally intensive tasks are executed on the HPC CyClone infrastructure, optimizing computing resources, time, and cost efficiency. Notably, the infrastructure supports algorithm modelling and training, as well as web, dark web and social media scraping and data classification. Preliminary results indicate a 10–15% increase in the identification of illicit artifacts, demonstrating the platform’s effectiveness in enhancing law enforcement capabilities.
The predictive value of GLIM criteria on clinical outcomes and responses to nutritional support in patients with neurocritical illnesses
Authors: Liu Peiqi , Tian Huimin , Gao Lan , Zhong Tangsheng , Wang Yujiao , Chen Li
Published: July 2024

Neurocritically ill patients frequently exhibit coma, gastroparesis, and intense catabolism, leading to an increased risk of malnutrition. The Global Leadership Initiative on Malnutrition (GLIM) criteria for the diagnosis of malnutrition was created to achieve a consistent malnutrition diagnosis across diverse populations. This study aimed to validate the concurrent and predictive validity of GLIM criteria in patients with neurocritical illnesses. A total of 135 participants were followed from admission to the neurocritical unit (NCU) until discharge. Comparing GLIM criteria to the Subjective Global Assessment (SGA), sensitivity was 0.95 and specificity was 0.69. Predictive validity of GLIM criteria was assessed using a composite adverse clinical outcome, comprising mortality and various major complications. Adjusted hazard ratios for moderate and severe malnutrition were 2.86 (95% CI 1.45–5.67) and 3.88 (95% CI 1.51–9.94), respectively. Changes in indicators of nutritional status, including skeletal muscle mass and abdominal fat mass, within 7 days of admission were obtained for 61 participants to validate the predictive capability of the GLIM criteria for the patients’ response of standardized nutritional support. The GLIM criteria have a statistically significant predictive validity on changes in rectus femoris muscle thickness and midarm muscle circumference. In conclusion, the GLIM criteria demonstrate high sensitivity for diagnosing malnutrition in neurocritically ill patients and exhibit good predictive validity.
Nickel ferrite decorated noble metal containing nitrogen-doped carbon nanotubes as potential magnetic separable catalyst for dinitrotoluene hydrogenation
Authors: Hajdu Viktória , Sikora Emőke , Muránszky Gábor , Kristály Ferenc , Kaleta Zoltán , Nagy Miklós , Viskolcz Béla , Fiser Béla , Vanyorek László
Published: July 2024

The 2,4-toluenediamine (TDA) is one of the most important chemicals in the polyurethane industry, produced by the catalytic hydrogenation of 2,4-dinitrotoluene (DNT). The development of novel catalysts that can be easily recovered from the reaction mixture is of paramount importance. In our work, a NiFe2O4/N-BCNT supported magnetic catalyst was prepared by a modified coprecipitation method. The catalyst support alone also showed activity in the synthesis of TDA. Platinum nanoparticles were deposited on the catalyst support surface by a fast, relatively simple, and efficient sonochemical method, resulting in a readily applicable catalytically active system. The prepared catalyst exhibited high activity in hydrogenation tests, which was proved by the exceptionally high DNT conversion (100% for 120 min at 333 K) and TDA yield (99%). Furthermore, the magnetic catalyst can be easily recovered from the reaction medium by the action of an external magnetic field, which can greatly reduce catalyst loss during separation.
Employing a magnetic chitosan/molybdenum disulfide nanocomposite for efficiently removing polycyclic aromatic hydrocarbons from milk samples
Authors: Rezagholizade-shirvan Alieh , Mohammadi Mansoureh , Mazaheri Yeganeh , Fallahizadeh Saeid , Ghorbani Haniyeh , Shokri Samira , Shariatifar Nabi , Darroudi Majid , Shamloo Ehsan
Published: July 2024

This study aimed to develop a highly efficient nanocomposite composed of magnetic chitosan/molybdenum disulfide (CS/MoS2/Fe3O4) for the removal of three polycyclic aromatic hydrocarbons (PAHs)—pyrene, anthracene, and phenanthrene. Novelty was introduced through the innovative synthesis procedure and the utilization of magnetic properties for enhanced adsorption capabilities. Additionally, the greenness of chitosan as a sorbent component was emphasized, highlighting its biodegradability and low environmental impact compared to traditional sorbents. Factors influencing PAH adsorption, such as nanocomposite dosage, initial PAH concentration, pH, and contact time, were systematically investigated and optimized. The results revealed that optimal removal efficiencies were attained at an initial PAH concentration of 150 mg/L, a sorbent dose of 0.045 g, pH 6.0, and a contact time of 150 min. The pseudo-second-order kinetic model exhibited superior fitting to the experimental data, indicating an equilibrium time of approximately 150 min. Moreover, the equilibrium adsorption process followed the Freundlich isotherm model, with kf and n values exceeding 7.91 mg/g and 1.20, respectively. Remarkably, the maximum absorption capacities for phenanthrene, anthracene, and pyrene on the sorbent were determined as 217 mg/g, 204 mg/g, and 222 mg/g, respectively. These findings underscore the significant potential of the CS/MoS2/Fe3O4 nanocomposite for efficiently removing PAHs from milk and other dairy products, thereby contributing to improved food safety and public health.
Power spectral density-based resting-state EEG classification of first-episode psychosis
Authors: Redwan Sadi Md. , Uddin Md Palash , Ulhaq Anwaar , Sharif Muhammad Imran , Krishnamoorthy Govind
Published: July 2024

Historically, the analysis of stimulus-dependent time–frequency patterns has been the cornerstone of most electroencephalography (EEG) studies. The abnormal oscillations in high-frequency waves associated with psychotic disorders during sensory and cognitive tasks have been studied many times. However, any significant dissimilarity in the resting-state low-frequency bands is yet to be established. Spectral analysis of the alpha and delta band waves shows the effectiveness of stimulus-independent EEG in identifying the abnormal activity patterns of pathological brains. A generalized model incorporating multiple frequency bands should be more efficient in associating potential EEG biomarkers with first-episode psychosis (FEP), leading to an accurate diagnosis. We explore multiple machine-learning methods, including random-forest, support vector machine, and Gaussian process classifier (GPC), to demonstrate the practicality of resting-state power spectral density (PSD) to distinguish patients of FEP from healthy controls. A comprehensive discussion of our preprocessing methods for PSD analysis and a detailed comparison of different models are included in this paper. The GPC model outperforms the other models with a specificity of 95.78% to show that PSD can be used as an effective feature extraction technique for analyzing and classifying resting-state EEG signals of psychiatric disorders.
Evaluation of the effects of temperature and centrifugation time on elimination of uncured resin from 3D-printed dental aligners
Authors: Kim Ji-Eun , Mangal Utkarsh , Yu Jae-Hun , Kim Gi-Tae , Kim Hoon , Seo Ji-Young , Cha Jung-Yul , Lee Kee-Joon , Kwon Jae-Sung , Choi Sung-Hwan
Published: July 2024

The study investigated the effects of temperature and centrifugation time on the efficacy of removing uncured resin from 3D-printed clear aligners. Using a photo-polymerizable polyurethane resin (Tera Harz TC-85, Graphy Inc., Seoul, Korea), aligners were printed and subjected to cleaning processes using isopropyl alcohol (IPA) or centrifugation (g-force 27.95g) at room temperature (RT, 23 °C) and high temperature (HT, 55 °C) for 2, 4, and 6 min. The control group received no treatment (NT). Cleaning efficiency was assessed through rheological analysis, weight measurement, transparency evaluation, SEM imaging, 3D geometry evaluation, stress relaxation, and cell viability tests. Results showed increased temperature and longer centrifugation times significantly reduced aligner viscosity, weight (P < 0.05), and transmittance. IPA-cleaned aligners exhibited significantly lower transparency and rougher surfaces in SEM images. All groups met ISO biocompatibility standards in cytotoxicity tests. The NT group had higher root mean square (RMS) values, indicating greater deviation from the original design. Stress relaxation tests revealed over 95% recovery in all groups after 60 min. The findings suggest that a 2-min HT centrifugation process effectively removes uncured resin without significantly impacting the aligners’ physical and optical properties, making it a clinically viable option.
Effect of true triaxial principal stress unloading rate on strain energy density of sandstone
Authors: Liu Zhixi , Zhao Guangming , Meng Xiangrui , Gu Qingheng
Published: July 2024

Deep rock are often in a true triaxial stress state. Studying the impacts of varying unloading speeds on their strain energy (SE) density is highly significant for predicting rock stability. Through true triaxial unloading principal stress experiments and true triaxial stress equilibrium unloading experiments on sandstone, this paper proposes a method to compute the SE density in a true triaxial compressive unloading principal stress test. This method aims to analyze the SE variation in rocks under the action of true triaxial unloading principal stresses. Acoustic emission is used to verify the correctness of the SE density calculation method in this paper. This study found that: (1) Unloading in one principal stress direction causes the SE density to rise in the other principal stress directions. This rise in SE, depending on its reversibility, can be categorized into elastic and dissipated SE. (2)When unloading principal stresses, the released elastic SE density in the unloading direction is influence by the stress path and rate. (3) The higher the unloading speed will leads to greater increases in the input SE density, elastic SE density, and dissipative SE density in the other principal stress directions. (4) The dissipated SE generated under true triaxial compression by unloading the principal stress is positively correlated with the damage to the rock; with an increase in unloading rate, there is a corresponding increase in the formation of cracks after unloading. (5) Utilizing the stress balance unloading test, we propose a calculation method for SE density in true triaxial unloading principal stress tests.
Fluorescence lifetime multiplexing with fluorogen activating protein FAST variants
Authors: Bogdanova Yulia A. , Solovyev Ilya D. , Baleeva Nadezhda S. , Myasnyanko Ivan N. , Gorshkova Anastasia A. , Gorbachev Dmitriy A. , Gilvanov Aidar R. , Goncharuk Sergey A. , Goncharuk Marina V. , Mineev Konstantin S. , Arseniev Alexander S. , Bogdanov Alexey M. , Savitsky Alexander P. , Baranov Mikhail S.
Published: July 2024

In this paper, we propose a fluorescence-lifetime imaging microscopy (FLIM) multiplexing system based on the fluorogen-activating protein FAST. This genetically encoded fluorescent labeling platform employs FAST mutants that activate the same fluorogen but provide different fluorescence lifetimes for each specific protein-dye pair. All the proposed probes with varying lifetimes possess nearly identical and the smallest-in-class size, along with quite similar steady-state optical properties. In live mammalian cells, we target these chemogenetic tags to two intracellular structures simultaneously, where their fluorescence signals are clearly distinguished by FLIM. Due to the unique structure of certain fluorogens under study, their complexes with FAST mutants display a monophasic fluorescence decay, which may facilitate enhanced multiplexing efficiency by reducing signal cross-talks and providing optimal prerequisites for signal separation upon co-localized and/or spatially overlapped labeling.
Accuracy of ultrasound, magnetic resonance imaging and intraoperative frozen section in the diagnosis of ovarian tumours: data from a London tertiary centre
Authors: Mitchell Sian , Gleeson Joseph , Tiwari Mansi , Bailey Frances , Gaughran Jonathan , Mehra Gautam , Muallem Mustafa Zelal , Sayasneh Ahmad
Published: July 2024

Background

Ovarian cancer has the worst prognosis among all gynaecological cancers. The pre-operative and intraoperative diagnosis of ovarian tumours is imperative to ensure the right operation is performed and to improve patients’ outcomes.

Methodology

A retrospective review of cases with a confirmed histological diagnosis of ovarian cases was undertaken from January 2017 to December 2021. Comparison was undertaken between this final diagnosis and the pre-operative ultrasound, MRI and frozen section (FS) to assess diagnostic accuracy of each. In the ultrasound cases, the level of the examiner was collected. Statistical analysis was performed using Stata MP v17.0 software (USA, 2023).

Results

In total, 156 ovarian masses were examined by FS. In the histopathological examination, 123/156 of these tumours were epithelial tumours. Pre-operative US subjective impression was made in 63/156 cases and preoperative MRI subjective impression was made in 129/156 cases. For benign, borderline and malignant tumours, FS demonstrated a sensitivity of 90.8% (95%CI:81.9–96.2), 86.8% (95%CI:71.9–95.6) and 97.6% (95%CI:87.4–99.9) respectively. Ultrasound’s sensitivities were 95.2% (95%CI:76.2–99.9), 20% (95%:4.33–48.1), 57.1% (95%CI:28.9–82.3) and MRI’s sensitivities were 100% (95%CI:80.5–100), 31.5% (95%CI:19.5–45.6) and 63.2% (95%CI:46–78.2) respectively.

Conclusions

FS remains an accurate tool for diagnosing ovarian malignancy. However, across both imaging modalities and FS, the diagnosis of borderline ovarian tumours remains challenging.
Revolutionizing energy storage: exploring the nanoscale frontier of all-solid-state batteries
Authors: Anil Kumar Yedluri , Roy Nipa , Ramachandran Tholkappiyan , Assiri Mohammed A. , Srinivasa Rao Sunkara , Moniruzzaman Md , Joo Sang Woo
Published: July 2024

All-solid-state batteries offer secure energy storage. Nanomaterials boost performance, but challenges include reducing electrolyte size while maintaining conductivity. This review highlights recent advances in electrode-electrolyte interfaces.
Exo- or endo-1H-pyrazole metal coordination modulated by the polyamine chain length in [1 + 1] condensation azamacrocycles. Binuclear complexes with remarkable SOD activity
Authors: Bonastre-Sabater Irene , Lopera Alberto , Martínez-Camarena Álvaro , Blasco Salvador , Doménech-Carbó Antonio , Jiménez Hermas R. , Verdejo Begoña , García-España Enrique , Clares M. Paz
Published: July 2024

Increasing the polyamine chain length changes the binding mode of pyrazole from exo to endo in Cu2+ complexes of pyrazolacyclophanes, leading to outstanding SOD activity.
Metal coordination governs the antimicrobial efficacy of calcitermin derivatives
Authors: Leveraro Silvia , Garstka Kinga , Śliwka Paulina , Janek Tomasz , Rowińska-Żyrek Magdalena , Remelli Maurizio , Bellotti Denise
Published: July 2024

The characterization of Zn(ii) and Cu(ii) complexes withad hocdesigned peptides provides new insights into the antimicrobial activity of calcitermin.
Multilayer stacked ultra-wideband perfect solar absorber and thermal emitter based on SiO2-InAs-TiN nanofilm structure
Authors: Chen Peng , Song Qianju , Ma Can , Yi Zao , Bian Liang , Cheng Shubo , Hao Zhiqiang , Sun Tangyou , Wu Pinghui , Zeng Qingdong
Published: July 2024

We propose an ultra-wideband perfect solar absorber that achieves high efficiency in the range of 280 nm–3000 nm.
Hemicelluloses from bioresidues and their applications in the food industry – towards an advanced bioeconomy and a sustainable global value chain of chemicals and materials
Authors: Mathura Sarah R. , Landázuri Andrea C. , Mathura Farrah , Andrade Sosa Ana Gabriela , Orejuela-Escobar Lourdes M.
Published: July 2024

A major concern in the food industry is the use of non-renewable, petroleum-based materials and its detrimental impact on the environment.
Improving the in vivo stability and sensor lifetime with new blend membranes on CGM sensors
Authors: Zuo Yinxiu , Lei Lanjie , Huang Ke , Hao Qing , Zhao Chao , Liu Hong
Published: July 2024

PDMS/HT outer membrane-coated CGM sensors can extend the in vivo lifetime to 28 days.
Ultra-sensitive detection of PFASs using surface enhanced Raman scattering and machine learning: a promising approach for environmental analysis
Authors: Rothstein Joshua C. , Cui Jiaheng , Yang Yanjun , Chen Xianyan , Zhao Yiping
Published: July 2024

SERS combined with machine learning was employed using AgNR substrates. The method demonstrates high sensitivity and specificity in detecting and differentiating PFASs in water or methanol samples.
Conjugated small molecules based on alkylsilyl-modified triphenylamine: promising hole transport materials in perovskite photovoltaics
Authors: Martynov Ilya V. , Zhivchikova Aleksandra N. , Tereshchenko Mikhail D. , Kuznetsov Ilya E. , Baryshev Stepan , Volkov Valentyn S. , Tepliakova Marina , Akkuratov Alexander V. , Arsenin Aleksey V.
Published: July 2024

Our research presents novel TPA-based hole-transport materials with triisopropylsilyl side chains, which possess good alignment of HOMO energy level with MAPbI3 increasing VOC of perovskite solar cells up to 1.1 V.
Performance Assessment of GaAs Pocket‐Doped Dual‐Material Gate‐Oxide‐Stack DG‐TFET at Device and Circuit Level
Authors: Singh Km. Sucheta , Kumar Satyendra , Chaturvedi Saurabh , Tyagi Kapil Dev , Tyagi Vaibhav Bhushan
Published: July 2024

This study explores the impact of integrating a gallium arsenide (GaAs) pocket at the source and drain in a dual‐material gate‐oxide‐stack double‐gate tunnel field‐effect transistor (DMGOSDG‐TFET). The performance of this DMGOSDG‐TFET, employing work‐function engineering and gate‐oxide‐stack techniques, is compared with a GaAs pocket‐doped DMGOSDG‐TFET. Using the Silvaco Technology Computer‐Aided Design tool, the comparison covers DC characteristics, analog/RF behavior, and circuit‐level assessments. The research introduces an optimized heterostructure pocket‐doped DMGOSDG‐TFET to enhance DC characteristics, analog/RF performance, and DC/transient analysis. This novel architecture effectively suppresses ambipolarity, making it more suitable for current conduction. The incorporation of work‐function engineering and a gate‐oxide‐stack approach enhances the device’s current driving capability, while the use of a highly doped GaAs pocket at the source and drain virtually eliminates ambipolar current conduction. Simulation results indicate that the proposed heterostructure device exhibits a high ON‐current and switching ratio. For analog/RF applications, the optimized heterostructure device outperforms conventional DMGOSDG‐TFET, offering higher cutoff frequency, transconductance, and other analog/RF parameters. Circuit‐level performance is assessed using HSPICE, with a focus on the implementation of a resistive‐load inverter for both proposed and conventional device topologies through DC and transient evaluations.
An optimization scheme for vehicular edge computing based on Lyapunov function and deep reinforcement learning
Authors: Zhu Lin , Tan Long , Li Bingxian , Tian Huizi
Published: July 2024

Traditional vehicular edge computing research usually ignores the mobility of vehicles, the dynamic variability of the vehicular edge environment, the large amount of real‐time data required for vehicular edge computing, the limited resources of edge servers, and collaboration issues. In response to these challenges, this article proposes a vehicular edge computing optimization scheme based on the Lyapunov function and Deep Reinforcement Learning. In this solution, this article uses Digital Twin technology (DT) to simulate the vehicular edge environment. The edge server DT is used to simulate the vehicular edge environment under the edge server, and the base station DT is used to simulate the entire vehicular edge system environment. Based on the real‐time data obtained from DT simulation, this paper defines the Lyapunov function to simplify the migration cost of vehicle tasks between servers into a multi‐objective dynamic optimization problem. It solves the problem by applying the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm. Experimental results show that compared with other algorithms, this scheme can effectively optimize the allocation and collaboration of vehicular edge computing resources and reduce the delay and energy consumption caused by vehicle task processing.
Energy‐efficient adaptive dependent task scheduling in cooperative vehicle‐infrastructure system
Authors: Su Beipo , Dai Liang , Ju Yongfeng
Published: July 2024

In the cooperative vehicle‐infrastructure system (CVIS), due to its computation limitation, vehicles are difficult to handle computing‐intensive delay‐sensitive tasks, so offload tasks to roadside unit (RSU) become popular. Due to the complexity of vehicles’ tasks and tasks generated by different vehicles have different delay constraints, minimize energy consumption of RSUs under task dependence and delay constraints is challenging. This paper defines the task priority queuing criterion for the task priority division problem, proposes a task scheduling strategy for energy‐packet queue length tradeoff (TSET) in CVIS under RSUs distributed task scheduling problem and establishes the vehicle speed state model, task model, data queue model, task computing model and energy consumption model. After Lyapunov optimization theory transformed the optimization model, a knapsack problem was described. The simulation results verify that TSET reduces the average energy consumption of roadside units and ensures the stability of the data queue under task dependence and deadline conditions.
Transient frequency response test and measurement error prediction of DCTV based on adaptive inertial weight improved ACO
Authors: Yang Yutao , Zhai Shaolei , Tang Hansong , Duan Genyue , Deng Liwu
Published: July 2024

A temporary frequency response test and measurement error prediction method of direct current voltage transformer (DCTV) based on artificial intelligence (AI) is proposed. Firstly, the frequency characteristic of direct current (DC) side voltage of DCTV is analyzed. On this basis, a DCTV transient Frequency Response testing method based on transient alternating current (AC) & DC superposition was developed. Then, the method of voltage sudden change and phase correction is used to achieve transient process DCTV response time testing. Finally, the ant colony optimization (ACO) algorithm was improved by combining an adaptive inertia weight improvement strategy, achieving accurate prediction of the Measurement Error of DCTV. The proposed AI based DCTV transient Frequency Response testing and Measurement Error prediction method were compared and analyzed with the other three methods through simulation experiments. Compared to the other three comparison methods, the maximum transformation error in the evaluation indicators of mean squared error (MSE), root mean squared error (RMSE), and mean absolute error (MAE) decreased by 0.006, 0.0119, and 0.0085, respectively, while the maximum phase error decreased by 0.2794, 0.3004, and 0.2823, respectively.
Comparing extragalactic megahertz-peaked spectrum and gigahertz-peaked spectrum sources
Authors: Ballieux F. J. , Callingham J. R. , Röttgering H. J. A. , Slob M. M.
Published: July 2024

Recent sensitive wide-field radio surveys, such as the LOFAR Two-metre Sky Survey (LoTSS), the LOFAR LBA Sky Survey (LoLSS), and the Very Large Array Sky Survey (VLASS), enable the selection of statistically large samples of peaked spectrum (PS) sources. PS sources are radio sources that have a peak in their radio continuum spectrum and are observed to be compact. They are often considered to be the precursors to large radio galaxies. We present a sample of 8032 gigahertz-peaked spectrum (GPS) sources with spectral turnovers near 1400 MHz, and a sample of 506 megahertz-peaked spectrum (MPS) sources with turnovers near 144 MHz. Our GPS sample is over five times larger than any previously known sample of PS sources. These large sample sizes allow us to make a robust comparison between GPS sources and MPS sources, such that we can investigate the differences between these types of sources, and study their lifetimes. The shape of the source counts of both samples match that of the general radio-loud active galactic nuclei (AGN) samples, scaled down by a factor 44 ± 2 for the MPS sample, and a factor 28 ± 1 for the GPS sample. Assuming no cosmological evolution, these offsets imply that both MPS and GPS sources have a shorter duration than general radio-loud AGN, with MPS sources having an ≈1.6 times shorter lifespan than GPS sources. The shorter duration of MPS sources relative to GPS sources can be explained by the transition between GPS and MPS sources coinciding with the jet breakout phase of PS sources, such that GPS sources traverse through the surrounding medium at a lower speed than MPS sources. Such evolution has been observed in simulations of PS source evolution.
The radio properties of z > 3.5 quasars: Are most high-redshift radio-loud active galactic nuclei obscured?
Authors: Capetti Alessandro , Balmaverde Barbara
Published: July 2024

We explore the radio properties of powerful (rest-frame luminosity ≳1028 W Hz−1 at 500 MHz) high-redshift (z ≳ 3.5) quasars. The aim of this study is to gain a better understanding of radio-loud sources at the epoch when they reach the highest space density. We selected 29 radio-loud quasars at low radio frequencies (76 MHz). Their radio spectra, covering the range from 76 MHz to 5 GHz, are generally well reproduced by a single power law. We created samples that were matched in radio luminosity at lower redshift (from z ∼ 1.3 to z ∼ 2.8) to investigate any spectral evolution. We find that the fraction of flat-spectrum radio quasars (FSRQs) strongly increases with redshift (from ∼8% at z = 1.2 to ∼45% at z >  3.5). This effect is also observed in quasars with lower luminosities (down to ∼1027 W Hz−1). The increase in the fraction of FSRQs with redshift corresponds to a decrease in the steep- spectrum radio quasars. This result can be explained when we assume that the beaming factor and the slope of the luminosity function do not change with redshift, if high-redshift radio-loud sources can be recognized as quasars only when they are seen at a small viewing angle (≲25°), while most of them, about 90%, are obscured in the UV and optical bands. We also found a trend for the size of radio sources to decrease with increasing redshift. Because projection effects are insufficient to cause this trend, we suggest that the large amount of gas causing the nuclear obscuration also hampers the growth of the more distant sources.
Separating source-intrinsic and Lorentz invariance violation induced delays in the very high-energy emission of blazar flares
Authors: Levy C. , Sol H. , Bolmont J.
Published: July 2024

Aims.The aim of the present study is to explore how to disentangle energy-dependent time delays due to a possible Lorentz invariance violation (LIV) at Planck scale from intrinsic delays expected in standard blazar flares.

Methods.We first characterised the intrinsic time delays in BL Lacs and flat-spectrum radio quasars in standard one-zone time-dependent synchrotron self-Compton or external Compton models, during flares produced by particle acceleration and cooling processes. We simulated families of flares with both intrinsic and external LIV-induced energy-dependent delays. Discrimination between intrinsic and LIV delays is then investigated in two different ways. A technique based on Euclidean distance calculation between delays obtained in the synchrotron and in the inverse-Compton spectral bumps is used to assess their degree of correlation. A complementary study is performed using spectral hardness versus intensity diagrams in both energy ranges.

Results.We show that the presence of non-negligible LIV effects, which essentially act only at very high energy (VHE), can drastically reduce the strong correlation expected between the X-ray and the VHE gamma-ray emission in leptonic scenarios. The LIV phenomenon can then be hinted at measuring the Euclidean distancedEfrom simultaneous X-ray and gamma-ray flare monitoring. Large values of minimum distancedE, minwould directly indicate the influence of non-intrinsic time delays possibly due to LIV in SSC flares. LIV effects can also significantly modify the VHE hysteresis patterns in hardness-intensity diagrams and even change their direction of rotation compared to the X-ray behaviour. Both observables could be used to discriminate between LIV and intrinsic delays, provided high-quality flare observations are available.
Fast supermassive black hole growth in the SPT2349–56 protocluster at z = 4.3
Authors: Vito F. , Brandt W. N. , Comastri A. , Gilli R. , Ivison R. J. , Lanzuisi G. , Lehmer B. D. , Lopez I. E. , Tozzi P. , Vignali C.
Published: July 2024

Context. Large-scale environment is one of the main physical drivers of galaxy evolution. The densest regions at high redshifts (i.e. z > 2 protoclusters) are gas-rich regions characterised by high star formation activity. The same physical properties that enhance star formation in protoclusters are also thought to boost the growth of supermassive black holes (SMBHs), most likely in heavily obscured conditions.

Aims. We aim to test this scenario by probing the active galactic nucleus (AGN) content of SPT2349–56: a massive, gas-rich, and highly star-forming protocluster core at z = 4.3 discovered as an overdensity of dusty star-forming galaxies (DSFGs). We compare our results with data on the field environment and other protoclusters.

Methods. We observed SPT2349–56 with Chandra (200 ks) and searched for X-ray emission from the known galaxy members. We also performed a spectral energy distribution fitting procedure to derive the physical properties of the discovered AGNs.

Results. In the X-ray band, we detected two protocluster members: C1 and C6, corresponding to an AGN fraction among DSFGs in the structure of ≈10%. This value is consistent with other protoclusters at z  =  2 − 4, but higher than the AGN incidence among DSFGs in the field environment. Both AGNs are heavily obscured sources, hosted in star-forming galaxies with ≈3 × 1010 M⊙ stellar masses. We estimate that the intergalactic medium in the host galaxies contributes to a significant fraction (or even entirely) to the nuclear obscuration. In particular, C1 is a highly luminous (LX = 2 × 1045 erg s−1) and Compton-thick (NH = 2 × 1024 cm−2) AGN, likely powered by a MBH > 6 × 108 M⊙ SMBH, assuming Eddington-limited accretion. Its high accretion rate suggests that it is in the phase of efficient growth that is generally required to explain the presence of extremely massive SMBHs in the centres of local galaxy clusters. Considering SPT2349–56 and DRC, a similar protocuster at z = 4, and under different assumptions on their volumes, we find that gas-rich protocluster cores at z ≈ 4 enhance the triggering of luminous (logLX/erg s−1 = 45 − 46) AGNs by three to five orders of magnitude with respect to the predictions from the AGN X-ray luminosity function at a similar redshift in the field environment. We note that this result is not solely driven by the overdensity of the galaxy population in the structures.

Conclusions. Our results indicate that gas-rich protoclusters at high redshift boost the growth of SMBHs, which will likely impact the subsequent evolution of the structures. Therefore, they stand as key science targets to obtain a complete understanding of the relation between the environment and galaxy evolution. Dedicated investigations of similar protoclusters are required to definitively confirm this conclusion with a higher statistical significance.
Medusa SDMT testing at the Onsøy Geo-Test Site, Norway
Authors: Monaco Paola , Chiaradonna Anna , Marchetti Diego , Amoroso Sara , L’Heureux Jean-Sebastien , Le Thi Minh Hue
Published: July 2024

The Medusa SDMT is the last-generation, fully automated version of the seismic dilatometer (SDMT). An extensive in situ testing campaign with the Medusa SDMT was carried out in June 2022 in different soil types at four well-known benchmark test sites in Norway, part of the Geo-Test Sites (NGTS) research infrastructure managed by the Norwegian Geotechnical Institute. The experimental campaign was conducted as part of the Transnational Access project – JELLYFISh funded by H2020-GEOLAB. This paper presents a preliminary assessment of significant results obtained by Medusa SDMT at the Onsoy test site, a soft marine clay. The data is compared to available in situ and laboratory data previously published at the Onsøy test site. The results show that the Medusa SDMT data are consistent with traditional (pneumatic) SDMT results. Furthermore, the parameters obtained from the interpretation of Medusa SDMT data, in particular the overconsolidation ratio OCR, the coefficient of earth pressure at rest K0, and the undrained shear strength su agree generally well with the corresponding parameters obtained in past investigations from other in situ and laboratory tests.
Numerical simulation of soil structure damage upon sampling
Authors: Monforte Lluís , Arroyo Marcos , Gens Antonio
Published: July 2024

Sampling disturbance is a perennial problem of geotechnical site investigation. The structure of soft soils is particularly fragile and prone to disturbance during sampling. The extent by which different sampling procedures modify soil structure has been generally assessed on an empirical basis, observing the outcomes of tests performed on specimens obtained with different sampling technologies. That kind of experiment is slow, costly and laborious. In this communication we present a procedure to perform similar experiments “in silico”, by simulating the sampling procedure, examining the effect of tube sampling on the initial soil structure, obtaining sub specimens from the simulated core and testing them afterwards in simulated triaxial undrained compression and in the oedometer. The simulations are based on G-PFEM, a code developed for soil-structure interaction at large strains. The numerical experiments clarify the origin of sampling related property variability.
An evaluation of non-linear undrained behaviour in the moderate strain range for fine-grained soils
Authors: Beesley Mair , Ibraim Erdin , Vardanega Paul J.
Published: July 2024

To select appropriate stress-strain parameters for serviceability limit state calculations, an understanding is needed of the likely variation of stress-strain behaviour within the model displacement mechanism. One approach that may be utilised to investigate variations in stress-strain behaviour is by employing a simple non-linear model (with a small number of physically significant parameters) that simulates experimental measurements of soil stress-strain with reasonable precision. By testing the sensitivity of the model parameters to changes in physical properties that can be expected to be related to them the reliability of different models can be established. Recently, empirical analysis of the published triaxial test database RFG/TXCU-278 identified a significant positive correlation between50andOCRfor four test modes (CIUC, CIUE, CKUC and CKUE). In this paper, a new experimental dataset from a programme of reconstituted soil tests on Kaolin and Bothkennar Clay is used to investigate the validity of a simple non-linear model.
Influence of particle crushing on the critical state line of rockfill materials
Authors: Ventini Roberta , Lirer Stefania , Flora Alessandro , Mancuso Claudio
Published: July 2024

The mechanical behaviour of rockfill materials is strongly affected by particle breakage, which causes a continuous variation of the grain size distribution (GSD) until a stationary condition. Although the evolution of grain crushing caused among others by the initial grading, the relative density and stress level has been extensively studied, the relationship describing the influence of the current GSD on other soil properties such as the critical state line is not uniquely defined. In this study, a series of triaxial compression tests with various stress paths under monotonic loading were performed on a rockfill to examine the effect of particle breakage on the position of the critical state lines (CSLs) in the compression plane. Specimens were prepared with the same initial grading and relative density to investigate the evolution of the GSD as a result of grain breakage determined by different stress paths applied in a large triaxial apparatus. In addition, a recently proposed simplified procedure is employed to capture the evolution of the CSLs of the tested crushable rockfill as a function of a breakage parameter related to the breakage index Bg. Experimental results obtained for the tested rockfill demonstrate that the abovementioned procedure is capable to predict the position of the CSL linked to the GSD reached at the end of the triaxial test, also when the critical state condition, defined as the ultimate condition in which shearing could continue indefinitely without changes in volume or effective stresses, is not reached.
Micromechanical observation of kinematics of sheared circular discs
Authors: Ali Usman , Kikumoto Mamoru , Cui Ying , Ciantia Matteo , Previtali Marco
Published: July 2024

Particle rolling is an essential microscopic mechanism that governs macroscopic behavior. This study conducts biaxial shearing tests on bi-dispersed circular discs at different confining pressures. A novel 2D image analysis technique is employed to measure the rolling of all the particles. It is observed that most of the particles exhibit significant rolling during shearing. Rollings are normally distributed in clockwise and counterclockwise directions, and the net rolling of the granular assembly is almost zero. Generally, the rolling of a particle is accompanied by its neighboring particle’s opposite rolling in a similar magnitude. In some cases, a group of particles is observed to exhibit rolling in the same direction, accompanied by another opposite rolling group in the neighboring regions. Particles inside the shear band tend to show significant rolling. The rolling rate is prominent at the beginning of the shearing and gradually decreases towards the end. Small particles exhibit significantly higher rotations, while larger particles are relatively resistant to rolling. Small particles work as ball bearings between two big particles, reducing the shear strength of the granular materials. The experimental data obtained in this study can be used to perform detailed validation of numerical models to simulate realistic granular behavior such as DEM.