bluuebunny/crossref_metadata_2025 huggingface dataset:
Commercial Aspects, Safety Regulations, Environmental and Health Impacts, and Recycling Strategies of Supercapacitors
Authors: Thakur Anukul K. , Majumder Mandira , Patole Archana S. , Patole Shashikant P.
Published: December 2023

Supercapacitors have great potential for applications in electric and hybrid vehicles, wind farms, and low-power equipment due to their large specific power density and long-term cyclic stability. Waste supercapacitors are required to be recycled for making their use sustainable from the waste electronic equipment perspective. This chapter describes a recycling approach for end-of-life supercapacitors based on shredding and mild thermal treatment. Further, the safety regulations for supercapacitors with respect to the operating conditions like temperature, potential window, self-discharge, leakage current, etc., are discussed. We further include discussion about the impact of supercapacitor applications on human health. We also include a brief analysis about the ethical issues as well as the social impacts of supercapacitor applications. This chapter summarizes the various aspects of the implementation of supercapacitors and their recycling prospects.
Simultaneous and site-specific profiling of heterogeneity and turnover in protein S-acylation by intact S-acylated peptide analysis with a cleavable bioorthogonal tag
Authors: Wu Roujun , Ji Guanghui , Chen Weiyu , Zhang Lei , Fang Caiyun , Lu Haojie
Published: December 2023

A novel method for the analysis of S-acylproteome by site-specifically profiling dynamicity and acyl chain heterogeneity in protein S-acylation by analyzing intact S-acylated peptides.
Re-injection off-axis integrated cavity output spectroscopy for the simultaneous detection of N2O, H2O and CO with a mid-infrared QCL laser
Authors: Yang Xi , Zhang Zhirong , Xia Hua , Sun Pengshuai , Pang Tao , Wu Bian , Liu Xu , Guo Qiang
Published: December 2023

A novel re-injection off-axis integrating cavity system is developed for simultaneously measuring N2O, H2O and CO in the atmosphere.
The chemical logic of enzymatic lignin degradation
Authors: Bugg Timothy D. H.
Published: December 2023

The article discusses mechanisms used by enzymes that attack the aromatic polymer lignin found in plant biomass.
Reducing delamination of an electron-transporting polymer from a metal oxide for electrochemical applications
Authors: Mohapatra Aiswarya Abhisek , Yual Waleed Kuar , Zhang Yadong , Samoylov Anton Aleksandrovich , Thurston Jonathan , Davis Casey M. , McCarthy Declan P. , Printz Adam D. , Toney Michael F. , Ratcliff Erin L. , Armstrong Neal R. , Greenaway Ann L. , Barlow Stephen , Marder Seth R.
Published: December 2023

An azide-modified phosphonic acid can be used to covalently tether polymers to indium tin oxide, preventing delamination and dissolution.
Oxygen evolution reaction (OER) active sites in BiVO4 studied using density functional theory and XPS experiments
Authors: Zhang Qingyan , Liu Guowei , Liu Taifeng
Published: December 2023

Stable VO4 structures lead to strong surface reconstruction and make the V sites on the top surface unsuitable for OER.
A closer look at amyloid ligands, and what they tell us about protein aggregates
Authors: Chisholm Timothy S. , Hunter Christopher A.
Published: December 2023

A database of over 2000 different ligands that bind amyloid fibrils (Aβ, tau, or αSyn) has been compiled and used to investigate the factors that influence binding affinity and selectivity.
Unveiling practical considerations for reliable and standardized SERS measurements: lessons from a comprehensive review of oblique angle deposition-fabricated silver nanorod array substrates
Authors: Zhao Yiping , Kumar Amit , Yang Yanjun
Published: December 2023

Uncover the SERS secrets for silver nanorod substrates: to illustrate insights of growth, mechanisms, optimization, quality, storage, measurement, device, and manufacturing; address practical issues; and unlock potential for different applications.
Unravelling the 6sp ← 6s absorption spectra of Bi(iii) complexes
Authors: Harriswangler Charlene , Lucio-Martínez Fátima , Rodríguez-Rodríguez Aurora , Esteban-Gómez David , Platas-Iglesias Carlos
Published: December 2023

The position of the absorption maximum in the electronic spectra of small Bi(iii) complexes depends mainly on the covalent character of the Bi(iii)-donor bonds, rather than on differences in spin–orbit coupling.
Differential microthermometry enables high-throughput calorimetry
Authors: Kazemi Amin , Zargartalebi Mohammad , Sinton David
Published: December 2023

Thermal balance between the sample and reference channels (ΔT = 0) enables rapid and accurate specific heat capacity measurement.
Lactose utilisation to furan carboxylates: a unique source for platform molecules
Authors: Install Joseph , Zupanc Anže , Nikunen Mikko , Jänis Janne , Repo Timo
Published: December 2023

Conversion of lactose side-stream from the dairy industry into highly valuable furan carboxylates with excellent efficiency, through mucic acid as an intermediate, a potential source for PEF production (created with https://Biorender.com).
Particle generated spectral interferences in single particle ICP-MS: a roadblock to accurate nanometrology
Authors: Goodman Aaron J. , Kanapilly Sandra , Bednar Anthony J. , Ranville James F.
Published: December 2023

Ion clouds from ablated nanoparticles form spectral interferences in a manner similar to their dissolved counterparts. This study investigates the formation of such interferences, and presents strategies for their mitigation.
Recent insights on the use of modified Zn-based catalysts in eCO2RR
Authors: Wang Hao , Deng Nanping , Li Xinyi , Chen Yiyang , Tian Ying , Cheng Bowen , Kang Weimin
Published: December 2023

In this paper, we discuss the advantages of various Zn-based catalysts and introduce the relevant mechanisms. Our own views on the future application prospects of Zn-based catalysts in eCO2RR are also put forward.
It’s in My DNA: Genes That Code for Personalities
Authors: Ferrington Yasmin
Published: December 2023

The Biochemical Society identifies and celebrates outstanding science communication talent in the molecular biosciences with its annual Science Communication Prize. Yasmin Ferrington, from Coventry University, won the first prize in the written category for students in higher education. Yasmin’s piece is titled ‘It’s in My DNA: Genes That Code for Personalities’.
A Data‐Driven Artificial Neural Network Approach to Software Project Risk Assessment
Authors: Alatawi Mohammed Naif , Alyahyan Saleh , Hussain Shariq , Alshammari Abdullah , Aldaeej Abdullah A. , Alali Ibrahim Khalil , Alwageed Hathal Salamah
Published: December 2023

In the realm of software project management, predicting and mitigating risks are pivotal for successful project execution. Traditional risk assessment methods have limitations in handling complex and dynamic software projects. This study presents a novel approach that leverages artificial neural networks (ANNs) to enhance risk prediction accuracy. We utilize historical project data, encompassing project complexity, financial factors, performance metrics, schedule adherence, and user‐related variables, to train the ANN model. Our approach involves optimizing the ANN architecture, with various configurations tested to identify the most effective setup. We compare the performance of mean squared error (MSE) and mean absolute error (MAE) as error functions and find that MAE yields superior results. Furthermore, we demonstrate the effectiveness of our model through comprehensive risk assessment. We predict both the overall project risk and individual risk factors, providing project managers with a valuable tool for risk mitigation. Validation results confirm the robustness of our approach when applied to previously unseen data. The achieved accuracy of 97.12% (or 99.12% with uncertainty consideration) underscores the potential of ANNs in risk management. This research contributes to the software project management field by offering an innovative and highly accurate risk assessment model. It empowers project managers to make informed decisions and proactively address potential risks, ultimately enhancing project success.
Spatial feature embedding for robust visual object tracking
Authors: Liu Kang , Liu Long , Yang Shangqi , Fu Zhihao
Published: December 2023

Recently, the offline‐trained Siamese pipeline has drawn wide attention due to its outstanding tracking performance. However, the existing Siamese trackers utilise offline training to extract ‘universal’ features, which is insufficient to effectively distinguish between the target and fluctuating interference in embedding the information of the two branches, leading to inaccurate classification and localisation. In addition, the Siamese trackers employ a pre‐defined scale for cropping the search candidate region based on the previous frame's result, which might easily introduce redundant background noise (clutter, similar objects etc.), affecting the tracker's robustness. To solve these problems, the authors propose two novel sub‐network spatial employed to spatial feature embedding for robust object tracking. Specifically, the proposed spatial remapping (SRM) network enhances the feature discrepancy between target and distractor categories by online remapping, and improves the discriminant ability of the tracker on the embedding space. The MAML is used to optimise the SRM network to ensure its adaptability to complex tracking scenarios. Moreover, a temporal information proposal‐guided (TPG) network that utilises a GRU model to dynamically predict the search scale based on temporal motion states to reduce potential background interference is introduced. The proposed two network is integrated into two popular trackers, namely SiamFC++ and TransT, which achieve superior performance on six challenging benchmarks, including OTB100, VOT2019, UAV123, GOT10K, TrackingNet and LaSOT, TrackingNet and LaSOT denoting them as SiamSRMC and SiamSRMT, respectively. Moreover, the proposed trackers obtain competitive tracking performance compared with the state‐of‐the‐art trackers in the attribute of background clutter and similar object, validating the effectiveness of our method.
A parallel input parallel output current fed front end DC‐DC converter‐based solid state transformer utilised in grid connected mode PV applications
Authors: Kumar Nitesh , Agarwal Pramod
Published: December 2023

The presented work operated a PIPO Current fed front end converter‐based solid‐state transformer (SST) for maximum power point tracking (MPPT) and voltage boost operation in medium power range PV applications. The proposed system employed the perturb and observe (P&O)‐based MPPT technique and upheld the ZVS and ZCS operations of all primary side switches and secondary side rectifier diodes, respectively. The proposed system introduced a new fundamental extractor titled ‘Pre‐filter double fundamental signal extractor (DFSE) based multi‐layered DFSE (p‐DFSE‐MDFSE)’ and utilised it in the grid controller for synchronisation and harmonics mitigation operation. The primary goal was to achieve a compact size, reduced weight and cheaper magnetic component‐based front‐end converter of SST on the PV array side and a fast, secure and trustworthy mitigation control of current harmonics on the utility grid side. The proposed system was inspected on the OPAL‐RT (RT‐LABv2021.3.2.307) platform for various grid anomalies, and its conduct was found to be well within the IEEE 519 norms.
Multiband circularly polarised CubeSat antenna operating in S, C, X, Ku, K, and Ka bands
Authors: Elkady Hesham M. , Abdullah Haythem H. , Darwish Saad M.
Published: December 2023

A novel design of a high‐frequency multiband with a circular polarisation antenna based on a four‐patch antenna system consolidated with an Archimedean spiral antenna for CubeSat applications. The geometry and size are compatible with the CubeSat standard structure dimensions of 10 × 10 cm2. The antenna consists of a spiral antenna in the middle of four patch antennas surrounding it; the first antenna structure consists of two sets of two orthogonal identical patch antennas with a 90° phase shift to cover the band from 1.55 to 1.94 GHz at L‐band, 2, 2.1, and 2.3 GHz at S‐band, the second antenna is an Archimedean spiral antenna to cover all C‐bands, all X‐bands, all Ku‐bands, all K‐bands, and from 26 to 29 GHz at Ka‐band. The measured results show that the reflection coefficients (S11) and (S22) achieve < −10 dB and the axial ratio achieves <3 dB, with a reference impedance of 50 Ω. The simulated and the measured results give a better agreement.
Biopolymer‐based nanoparticles as promising candidate for inducing apoptosis in liver cancer cells
Authors: Hoseinzadeh Mahsa , Mokhtari Mohammad Javad , Kafilzadeh Farshid , Mohammadnejad Javad , Taheri Yaghoob
Published: December 2023

Liver cancer is one of the most common causes of death all around the globe. On the other hand, conventional modalities, such as chemotherapy and surgery, have not been effectively suppressed cancer incidence due to some deficiencies. As a result, a novel folic acid (FA)‐decorated poly lactic‐co‐glycolic acid (PLGA)‐Alginate (Alg) nanocarrier was efficiently developed for active doxorubicin (Dox) delivery to human HepG2 liver cancer cells. The in vitro assays, including cell viability assay (MTT (3‐(4,5‐dimethylthiazol‐2‐yl)‐2,5‐diphenyltetrazolium bromide) test), apoptosis, cell cycle arrest, and cellular uptake, were applied to evaluate the cancer cell growth suppression and apoptosis‐inducing ability of the nanocarrier. More than 85% cytotoxicity was attained after 24 h of treatment with 400‐nM concentration of FA‐PLGA‐Dox‐Alg. More than 21% and 61% apoptosis were observed after 24 h of treatment with 100‐nM concentrations of FA‐PLGA‐Dox‐Alg in apoptosis and cell cycle arrest assays. The cellular uptake of the FA‐PLGA‐Alg nanocarrier was about 30% higher than that of the PLGA‐Alg carrier which indicated the cancer cell targeting ability of the FA‐PLGA‐Alg sample. These results have indicated the potential capability of FA‐PLGA‐Dox‐Alg in the inhibition of liver cancer cells.
Quantum intelligence in medicine: Empowering thyroid disease prediction through advanced machine learning
Authors: Sha Mohemmed
Published: December 2023

The medical information system is rich in datasets, but no intelligent systems can easily analyse the disease. Recently, ML (Machine Learning)‐based algorithms have acted as a handy diagnostic tool to identify whether a person is affected by thyroid or not. However, they produced classification with low accuracy and led to misclassification. Hence, the proposed system combines quantum computing with ML techniques to enhance computational power and precision. The system employs modified QPSO (Quantum Particle Swarm Optimisation) for feature selection since its searching performance is better than that of conventional PSO for selecting the optimum global position of the particle, thus selecting the relevant feature. Whereas, the QSVM (Quantum Support Vector Machine) is implemented for more accurate classification than classical SVM, as it tends to capture complex patterns in data produced due to high dimensional feature space applied by quantum kernel functions. This combination of modified QPSO and QSVM tends to increase the performance accuracy significantly. The efficiency of the proposed model is measured based on derivative parameters, such as F‐1‐score, recall, precision and accuracy, with corresponding confusion matrix and ROC. Further, the classification is compared with other traditional approaches to predict the accuracy of the proposed model with traditional methods.
Long baseline bistatic radar imaging of tumbling space objects for enhancing space domain awareness
Authors: Serrano Alexander , Kobsa Alexander , Uysal Faruk , Cerutti‐Maori Delphine , Ghio Selenia , Kintz Andrew , Morrison Robert L. , Welch Sarah , van Dorp Philip , Hogan Gregory , Garrington Simon , Bassa Cees , Saunders Chris , Martorella Marco , Caro Cuenca Miguel , Lowe Isaac
Published: December 2023

Long baseline bistatic radar systems herald enhanced sensitivity and metric accuracy for space objects in geosynchronous orbits and beyond. Radio telescopes are ideal participants in such a system; in particular, they often feature large apertures with low‐noise temperatures and have stable, synchronised clocks. Pairing radio telescopes with high‐power radars creates new methodologies for Space Domain Awareness. This paper describes long baseline bistatic measurements using the Millstone Hill Radar in the USA, the Tracking and Imaging Radar in Germany, multiple receivers of the enhanced multi‐element remotely linked interferometer network array in the United Kingdom, and the Westerbork Synthesis Radio Telescope in the Netherlands. The authors, a Research Task Group formed by the NATO Science and Technology Organisation Sensors and Electronic Technology Panel (SET‐293), performed novel bistatic and monostatic radar imaging experiments with real on‐orbit tumbling rocket bodies. These experiments on tumbling objects at near‐geosynchronous orbits highlight successful demonstrations of advanced bistatic Doppler characterisation across diverse imaging geometries. Specialised Doppler processing on tumbling targets, such as the Doppler superpulse algorithm, enables high‐fidelity rotation period estimation and determination of minimum target size.
Adaptation and mitigation management of drought, wildfire, and climate change toward the development of natural tourism in Jatirejo District, Mojokerto Regency, Indonesia
Authors: Santoso Eko Budi , Zulkarnain Muhammad Ifaldy Amrila , Kamila Azura Calista Shafa , Dyaksa Gde Abhicanika Pranata , Vera Shinta Novia , Ashari Annisa Fadhilah
Published: December 2023

Global climate change, drought, and the threat of wildfires become major challenges in tourism development. Jatirejo District has a unique natural landscape and is stated as an Environmental Strategic Area in the form of Raden Soerjo Forest Park, which is frequently hit by drought, wildfire, and climate change. This study aims to identify those disasters that threaten natural tourism, see how far the gap with ideal conditions and formulate adaptation and mitigation strategies. The methods used in this research are spatial analysis to identify the disaster risks and qualitative method by gap analysis to formulate the strategies. The findings show that wildfires in 2019 at R. Soerjo Forest Park had a coverage area of 64.7 hectares. Moreover, 59% of the total area has been identified as a very high-risk index of wildfire and drought. There is also a significant increase in temperature by 0.7oC-1oC. This study shows the large gap between the severity of the disaster and the ideal conditions according to the guidelines. The potential of tourism destinations, as well as the threat of disasters, shows the need for adaptation and mitigation strategies for tourism development which contain three phases, specifically prevention and preparation, response, and recovery.
A Comparative Study on Photovoltaic using Fuzzy Logic and perturbation and observation
Authors: Ballouti Abdelkarim , Chouiekh Mohamed , Zakriti Alia , El Mourabit Youness
Published: December 2023

The global shift to renewable energy, especially solar energy, is critical to reducing our dependence on fossil fuels and solving environmental problems. This study directly compares two methods for solar optimization in photovoltaic systems: perturbation and observation (P&O) and fuzzy logic controller (FLC). We evaluated their performance in different lighting conditions, with the FLC offering stability but slightly slower response times, while the P&O offering real-world reliability, albeit with minimal fluctuations. Our results highlight the significant impact of light intensity on power output. We recommend using P&O for quick tuning and FLC for consistent performance. These insights help decision-makers select the most appropriate methods to maximize photovoltaic efficiency, thereby contributing to sustainable energy solutions.
Measurement of radon gas concentration and effective dose in water from the Midelt region of Morocco, Using nuclear track detectors (LR-115)
Authors: Khadour Said , Sedra M.B. , Elboukili Abderrahman
Published: December 2023

The article's objective is to evaluate the concentration of radon in different water samples, with levels ranging from 0.31 Bq/L to2.24 Bq/L, the annual effective dose ranged from 2.09 to 8.83 (mSv/y). Radon (222Rn), a radioactive gas originating from the decay of 238U in the 226Ra decay series, is commonly found in rocks, soil, natural gas, and groundwater. Exposure to radon in both air and water can lead to human radiation exposure, potentially increasing the risk of specific types of cancer. The primary goal of this study is to measure radon levels in water samples from various locations in Morocco, specifically in the Midelt province and Daraa-Tafilalt region (located at 32° 40' 48″ North, 4° 44' 24″ West), using Solid State Nuclear Track Detectors of LR-115 type, It's important to mention that all the analyzed water samples recorded annual effective doses that fall within the global average recommended levels for ingestion exposure dose values set by the United Nations Scientific Committee on the Effects of Atomic Radiation. Based on these findings, there appear to be no radiation risks associated with radon gas in the study area.
A Smart Water Management System for Detecting Household Water Wastage
Authors: Gichuhi Janice , Khakata Esther , Kofi Isaac
Published: December 2023

Water scarcity in Kenya is a significant issue that cannot be overlooked. Despite numerous efforts by Water Service Providers to deliver water services to Kenyan residents, the high demand for accessible water across the country remains unmet. In addition, the service provider’s ability to meet this demand is further impeded by various obstacles including inadequate control over water usage, insufficient resources to manage and conserve water, and the dilapidated water infrastructure within the nation. While attempts have been made to try and address these concerns, they’ve been largely manual and expensive hence lacking the potential for scalability. Globally, water resources continue to decline rapidly due to the impact of climate change and water overuse, therefore action must be taken to conserve this resource. This study investigates the development of a smart water management system using water flow sensors connected directly to the water appliances that integrate with the existing water system, Node MCU microcontrollers and a cloud-based application. The solution focuses on monitoring household water usage frequency to inform users of their consumption and alert them via mobile notifications of potential water leaks to reduce wastage. Management and control of household water consumption is a positive contribution towards water conservation efforts.
Optimal Artificial Neural Network using Particle Swarm Optimization
Authors: Alam M. N. , Sallem Amin , Pereira Pedro , Bachir Benhala , Masmoudi Nouri
Published: December 2023

Artificial neuron networks (ANNs) are widely used for data analyticS in broad areas of engineering applications and commercial services. The ANN has one to two hidden layers. In advanced ANN, multiple-layer ANN is used where the network extracts different features until it can recognize what it is looking for through deep learning approaches. Usually, a backpropagation algorithm is used to train the network and fix weights and biases associated with each network neuron. This paper proposes a particle swarm optimization (PSO) based algorithm for training ANN for better performance and accuracy. Two types of ANN models and their training using PSO have been developed. The performance of the developed models has been analyzed on a standard dataset. Also, the effectiveness and suitability of the developed approach have been demonstrated through statistics of the obtained results.
Medium term load forecasting using fuzzy logic approach: A case study of Taroudannt province
Authors: Stitou Hicham , Atillah Mohamed Amine , Boudaoud Abdelghani , Mounaim Aqil
Published: December 2023

Increasing energy efficiency and reliability of power grids is becoming an essential part of grid energy management. Accurately predicting load demand is one of the most important responsibilities of any power utility.

This paper focuses on medium term load forecasting for the Moroccan province of Taroudannt using historical monthly load data for five years (2018-2022), temperature and wind speed. This study is the first of its kind in Morocco, particularly within the province of Taroudannt. The main objective is to contribute to the improvement of energy efficiency in the Souss Massa region. To forecast consumed energy, the fuzzy logic approach is used. Three different models are developed, considering three defuzzification methods, namely Centroid, Bisector and smallest of maximum (SOM). The model is tested using data from the year 2022. The simulation results show that the SOM prediction values are less precise, with a mean error of 13 %. In contrast, the other two methods generate the more reasonable and satisfactory values which are closer to the actual load, with the mean absolute percentage error (MAPE) less than 8.5 %. The result obtained demonstrate that the proposed model is capable of accurately forecasting future load for Taroudannt province.
A first-principles study of the unsynthesized Indium halide perovskites RbInX3 (X= F, Cl, Br, I) for photovoltaic and photocatalytic applications
Authors: El Akkel Mihade , Achqraoui Mounia , Ez-Zahraouy Hamid
Published: December 2023

Due to their relevant properties, lead-free halide perovskites have attracted wide attention in the scientific community. This study investigates the structural, mechanical, electronic, optical, and photocatalytic properties of the Indium-based halide perovskites RbInX3 (X= F, Cl, Br, I) based on the density functional theory (DFT) using the WIEN2k package. The results show that RbInI3 exhibits a metallic behavior, while RbInBr3, RbInCl3, and RbInF3 exhibit semiconducting behavior with bandgap energies of 0.67, 1.43, and 2.45 eV, respectively. The high optical absorption and corresponding band gap energies make them good candidates for photovoltaic applications. In addition, the RbInF3 compound exhibits good photocatalytic performance since it satisfies the thermodynamic requirements needed to trigger the water-splitting reaction. This study also allows us to analyze the influence of halogen substitution on the properties of the compound RbInX3. Moreover, it will open the way to the experimental community as it is the first to study the properties of these perovskites.
Multi-Defender Strategic Filtering Against Multi Agent Cyber Epidemics on Multi-Environment Model for Smart Grid Protection
Authors: Bitirgen Kübra , Başaran Filik Ümmühan
Published: December 2023

The growing cyber space with the developments in cyber network technologies in smart grid (SG) systems has necessitated questioning the reliability of networks and taking precautions against possible cyber threats. For this reason, defensive strategies and approaches against cyber attacks must be improved to sustain secure information flow of the network connections used in electricity generation, transmission, distribution, and consumption. This paper proposes a multi-agent multi environment deep reinforcement learning (MM-DRL) based defender response against cyber epidemics consisting coordinated cyber-attacks (multi-CAs) in the same time frame scheme to sustain security for SG networks. In this regard, the PMU-connected 123-bus system is integrated as a Markov game. MM-DRL approach is implemented for subenvironments of a typical SG system. Multi-CAs game aims to coordinate PMU signals across intersections to improve the network efficiency of a SG. DRL has been applied to data control recently and demonstrated promising performance where each data signal is regarded as an agent. Conversely, multi-CAs are self-renewing emerging causative agent of electricity theft, network disturbances, and data manipulation in SG systems characterized with wide characteristic diversity and rapid evolution. The game results show that the presented request response algorithm is able to minimize system attack damage and maintain protection duties when compared to a benchmark without request response. In addition, the performance of the MM-DRL approach compared to other developed methods is examined.
Perspectives psychanalytiques sur l’art de l’acteur. Travail de l’acteur et construction du personnage
Authors: Ionescu Elena , Maïdi Houari
Published: December 2023

Dans ce travail, nous nous proposons d’étudier le processus de construction du personnage par le comédien. Nous essayons d’identifier, par la mise en évidence des mécanismes psychiques impliqués dans ce processus, si cette construction n’est autre chose qu’une modalité de symbolisation d’une expérience vécue par le comédien, et qui est restée non-intégrée dans sa subjectivité. Aussi, nous cherchons à montrer la liaison entre le travail créatif du comédien et son fonctionnement psychique dans l’après-coup de ce travail.

Pour développer cette étude, nous faisons appel à la littérature psychanalytique en utilisant principalement les auteurs comme Freud, Ferenczi, Winnicott, M. Klein, E. Jones, Hanna Segal, Roussillon pour leur conception sur l’art et sur la symbolisation.

Lors de son travail de construction du personnage, l’artiste se met dans une condition de vulnérabilité extrême. Il met en mouvement un processus dont il n’est pas le maître absolu. Ce qui exige de lui une forme de passivation, de se laisser posséder par son propre produit artistique. La dimension masochiste de l’acteur est visée. Sa disponibilité de revivre l’angoisse face à l’inconnu, lui donne la possibilité de se rapprocher de cette expérience, à peine aperçue, de raconter quelque chose sur elle, à lui donner une place, à l’inscrire dans le temps. Le choix du medium, les moyens techniques que l’artiste va utiliser dans le processus créatif, sont spécifiques à chaque type d’art et mobiliseront des contenus inconscients différents et des modalités particulières pour les traiter. En parlant de l’acteur, nous devons prendre en considération le fait que son instrument principal de représentation, la matière première de son produit artistique, est son propre corps. Ainsi, sont enclenchés des processus inconscients particuliers, comme la sublimation ou la symbolisation, que nous avons cherché à explorer.
Earnings management of acquiring and non-acquiring companies: the key role of ownership structure and national corporate governance in GCC
Authors: Alghemary Mahmoud , Polovina Nereida , Al-Najjar Basil
Published: December 2023

We are mainly interested in the impact of acquisition, ownership structure, and national governance quality on accrual earnings management (AEM) in the GCC listed companies’ context. Our sample is composed of 3210 firm-year observations for the period from 2007 to 2017. We employ panel data models in investigating the determinants of AEM for acquiring and non-acquiring firms. The findings reveal that acquiring firms involve more in earnings management than non-acquiring firms and that acquiring firms involve in AEM through income increasing rather than income decreasing. Institutional and state ownership are found to be an efficient tool in restraining companies’ engagement in earnings management whereas foreign ownership is shown to have no impact. National governance quality is found to be an efficient mechanism to reduce the companies’ engagement in earnings management. The study has both organizational and policy implications. In the organizational context, the GCC listed companies could benefit from attracting institutional and state owners to mitigate earnings management and therefore enhance firm performance. In the legislative context, policy makers are encouraged to concentrate on developing national governance systems to mitigate AEM.
Considering a superposition of classical reference frames
Authors: Tammaro Elliott , Angle H. , Mbadu E.
Published: December 2023

A ubiquitous feature of quantum mechanical theories is the existence of states of superposition. This is expected to be no different for a quantum gravity theory. Guided by this consideration and others we consider a framework in which classical reference frames may be in superposition relative to one another. Mirroring standard quantum mechanics we introduce a complex-valued wavefunctional, which takes as input the transformations between the coordinates, Ψ[x(x′)], with the interpretation that an interaction between the reference frames may select a particular transformation with probability distribution given by the Born rule — P[x(x′)] = probability distribution functional ≡ |Ψ[x(x′)]|2. The cases of two and three reference frames in superposition are considered explicitly. It is shown that the set of transformations is closed. A rule for transforming wavefunctions from one system to another system in superposition is proposed and consistency with the Schrodinger equation is demonstrated.
Energy spectrum analysis on a red blood cell model
Authors: Yamamoto Tetsuya , Watanabe Hiroshi
Published: December 2023

It is important to understand the dynamics of red blood cells (RBCs) in blood flow. This requires the formulation of coarse-grained RBC models that reproduce the hydrodynamic properties of blood accurately. One of the models that successfully reproduces the rheology and morphology of blood has been proposed by Fedosov et al. [Comput. Methods Appl. Mech. Eng. 199, 1937–1948 (2010)]. The proposed RBC model contains several parameters whose values are determined by either various experiments or physical requirements. In this study, we developed a new method of determining parameter values precisely from the fluctuations of the RBC membrane. Specifically, we studied the relationship between the spectra of the fluctuations and model parameters. Characteristic peaks were observed in the spectra, whose peak frequencies were dependent on the parameter values. In addition, we investigated the spectra of the radius of gyration. We identified the peaks originating from the spring potential and the volume-conserving potential appearing in the spectra. These results lead to the precise experimental determination of the parameters used in the RBC model.
Thermal conductivity-based hydrogen in argon detector (HAD): Design, development of instrumentation, and performance evaluation
Authors: Lakshmigandhan I. , Premalatha S. , Prabhu E. , Ravindranath Nair Afijith , Gunasekaran G. , Jayaraman V.
Published: December 2023

The Hydrogen in Argon Detectors (HADs) working on the principle of thermal conductivity difference between argon (reference) and argon + H2 (sample) in the cover gas of a sodium-cooled fast breeder reactor using the Wheatstone bridge circuit. The output of HAD is very sensitive to the gas flow rate and to the variation in ambient temperature. The RMSnoise of current was brought within ±1 µA by a constant current source across the bridge. The temperature correction factor fed in the processor brought down the RMSnoise in the HAD signal within ±2.4 mV than the uncorrected one having RMSnoise of ±230 mV. The filtered noise of HAD facilitates enhancing the detection limit of HAD down to 30 ppm (3σ) of hydrogen in argon.
Measuring three-dimensional bubble dynamics for hydrogen production via water electrolysis
Authors: Mei Xiaohan , Yuan Shu , Zhao Congfan , Yan Xiaohui , Zhao ChangYing , Wang Qian
Published: December 2023

The commercialization of mass hydrogen production via water electrolysis is presently limited by low operational current densities. The optimal performance of electrolysis cells is significantly influenced by the substantial formation and residence of bubbles at high current densities. Thus, it is crucial to design electrodes with the ability for rapid bubble discharge to ensure appropriate bubble management. However, the quantitative volumetric measurements required to determine the bubble discharge ability of an electrode are not yet sufficiently accurate. This paper describes a quantitative volumetric method that combines a stereoscopic shadowgraph imaging system with particle tracking velocimetry (PTV) to measure the three-dimensional position, size, and velocity of micrometer-sized bubbles. The proposed method successfully captures hydrogen bubbles larger than 30 μm bubbles in an alkaline water electrolyzer. Considering the different luminance patterns of small bubbles (r ≤ 4 pixels) and large bubbles (r > 4 pixels) in the current imaging system, a bubble-size adaptive detection algorithm is established based on the cascade correlation method to obtain the two-dimensional centroid coordinates and radius of the observed bubbles. The bubble size information is also introduced into a two-view PTV algorithm for retrieving the Lagrangian trajectory of each bubble. Both the bubble detection and PTV algorithms are validated using synthetic datasets. Once the bubble trajectories are resolved successfully, the three-dimensional bubble velocity is obtained, and the actual bubble sizes are further corrected using the depth information. Analysis of the trajectory and velocity components indicates the existence of lateral bubble motion, reflecting interactions among bubbles. The rise velocity is positively correlated with the bubble radius in two regions, respectively, and the deviation from the theoretical value reveals the influence of non-buoyancy factors. The proposed technique provides effective diagnostics of the three-dimensional dynamic characteristics of micrometer-sized bubbles and can be used to evaluate and design bubble management systems for various electrochemical energy conversion devices.
Design, optimization, and characterization of an XY nanopositioning stage with multi-level spatial flexure hinges for high-precision large-stroke motion guidance
Authors: Shi Zhichao , Li Xiaoquan , Zhu Zhiwei
Published: December 2023

Establishing a novel design and accurate analytical models for XY nanopositioning stages based on voice coil motor (VCM) actuators is critical to achieving an optimal working performance. To overcome the existing design challenges of 2-degree-of-freedom guiding mechanisms, a four-layer structure composed of L-shaped spatial double parallelogram flexure mechanisms was proposed for the magnetic stage, which exhibits light weight and inhibits parasitic and decoupled motions. The guiding mechanisms were modeled by the compliance matrix method. Thereafter, by combining an electromagnetic model for the VCMs with the equivalent magnetic network method, an electromagnetic–mechanical coupling optimization method with multiple constraints was proposed for the stage to achieve a millimeter-range motion with a maximized natural frequency. The mechanical and electromagnetic performances were then verified by finite element analysis software. The optimized prototype was tested with a stroke of ±3.41 and ±3.08 mm for X axis and Y axis, respectively, a closed-loop resolution of 100 nm for X axis and 150 nm for Y axis, and a resonant frequency of 11.75 Hz for both axes. The tracking of a 0.1 Hz spiral of Archimedes achieved a maximum tracking error of 2.9%.
Orbital dependent complications for close vs well-separated electrons in diradicals
Authors: Hooshmand Zahra , Bravo Flores Jose Gustavo , Pederson Mark R.
Published: December 2023

We investigate two limits in open-shell diradical systems: O3, in which the interesting orbitals are in close proximity to one another, and (C21H13)2, where there is a significant spatial separation between the two orbitals. In accord with earlier calculations, we find that standard density-functional approximations do not predict the open-shell character for the former case but uniformly predict the open-shell character for the latter case. We trace the qualitatively incorrect behavior in O3 predicted by these standard density functional approximations to self-interaction error and use the Fermi–Löwdin-orbital-self-interaction-corrected formalism to determine accurate triplet, closed-shell singlet, and open-shell broken-spin-symmetry electronic configurations. Analysis of the resulting many-electron overlap matrices allows us to unambiguously show that the broken-spin-symmetry configurations do not participate in the representation of the Ms = 0 triplet states and allows us to reliably extract the singlet–triplet splitting in O3 by analyzing the energy as a function of Fermi-orbital-descriptor permutations. The results of these analyses predict the percentage of open-shell character in O3, which agrees well with conventional wavefunction-based methods. While these techniques are expected to be required in cases near the Coulson–Fischer point, we find that they will be less necessary in diradical systems with well-separated electrons, such as (C21H13)2. Results based on energies from self-interaction-corrected generalized gradient, local density, and Hartree–Fock approximations and experimental results are in generally good agreement for O3. These results help form the basis for deriving extended Heisenberg-like Hamiltonians that are needed for descriptions of molecular magnets when there are competing low-energy electronic configurations.
Post-disruption reconnection event driven by a runaway current
Authors: Singh L. , Borgogno D. , Subba F. , Grasso D.
Published: December 2023

The role of a runaway current in a post-disruption plasma is investigated through numerical simulations in an asymmetric magnetic reconnection event. We first reproduce the known linear results on the growth rate, the rotation frequency, and the formation of a microlayer smaller than the resistive one as found in Liu et al. [Physics of Plasmas 27, 092507 (2020)] and then focus on the nonlinear regime where are our main findings. We find that while the resistive layer controls the transition of the island from the linear to the nonlinear stage, the microlayer width controls the transition of the runaway current from the linear to the nonlinear phase. This latter transition is accompanied by a redistribution of runaways according to a spiral-like structure within the island. The same structure is also found in the thermal electron distribution when the electron inertia effects into the Ohm's law are taken into account. Finally, nonlinear simulations show that the island rotation frequency tends toward zero when the saturation is reached.
Calibration in machine learning uncertainty quantification: Beyond consistency to target adaptivity
Authors: Pernot Pascal
Published: December 2023

Reliable uncertainty quantification (UQ) in machine learning (ML) regression tasks is becoming the focus of many studies in materials and chemical science. It is now well understood that average calibration is insufficient, and most studies implement additional methods for testing the conditional calibration with respect to uncertainty, i.e., consistency. Consistency is assessed mostly by so-called reliability diagrams. There exists, however, another way beyond average calibration, which is conditional calibration with respect to input features, i.e., adaptivity. In practice, adaptivity is the main concern of the final users of the ML-UQ method, seeking the reliability of predictions and uncertainties for any point in the feature space. This article aims to show that consistency and adaptivity are complementary validation targets and that good consistency does not imply good adaptivity. An integrated validation framework is proposed and illustrated with a representative example.
Development of x-ray beam wavefront sensors for Advanced Photon Source upgrade
Authors: Frith Matthew G. , Highland Matthew J. , Qiao Zhi , Rebuffi Luca , Assoufid Lahsen , Shi Xianbo
Published: December 2023

Next-generation synchrotron radiation facilities, such as the Advanced Photon Source Upgrade (APS-U), bring significant advancements in scientific research capabilities, necessitating advanced diagnostic tools. Central to these diagnostics are x-ray wavefront sensors, crucial for preserving beam properties, including brightness, coherence, and stability. This paper presents two novel wavefront sensor prototypes developed at the APS using the coded-mask-based technique. The first is a compact design tailored for specific conditions and adaptability to diverse beamline configurations. The second, an adjustable zoom version, offers flexibility to accommodate a wide range of beam conditions. Both prototypes underwent rigorous testing at the APS 28-ID-B beamline and demonstrated their effectiveness in both absolute wavefront sensing and relative metrology modes. These results highlight their promise in beamline diagnostics, potentially enabling applications such as beamline auto-alignment and real-time wavefront manipulation.
Mean-field coherent Ising machines with artificial Zeeman terms
Authors: Mastiyage Don Sudeera Hasaranga Gunathilaka , Inui Yoshitaka , Kako Satoshi , Yamamoto Yoshihisa , Aonishi Toru
Published: December 2023

Coherent Ising Machine (CIM) is a network of optical parametric oscillators that solve combinatorial optimization problems by finding the ground state of an Ising Hamiltonian. In CIMs, a problem arises when attempting to realize the Zeeman term because of the mismatch in size between interaction and Zeeman terms due to the variable amplitude of the optical parametric oscillator pulses corresponding to spins. There have been three approaches proposed so far to address this problem for CIM, including the absolute mean amplitude method, the auxiliary spin method, and the chaotic amplitude control (CAC) method. This paper focuses on the efficient implementation of Zeeman terms within the mean-field CIM model, which is a physics-inspired heuristic solver without quantum noise. With the mean-field model, computation is easier than with more physically accurate models, which makes it suitable for implementation in field programmable gate arrays and large-scale simulations. First, we examined the performance of the mean-field CIM model for realizing the Zeeman term with the CAC method, as well as their performance when compared to a more physically accurate model. Next, we compared the CAC method to other Zeeman term realization techniques on the mean-field model and a more physically accurate model. In both models, the CAC method outperformed the other methods while retaining similar performance.
Tightly coupled arrays with time-domain beam scan for the radiation of high-power ultrawideband electromagnetic pulses
Authors: Wang Shao-fei , Zhu Cheng-ru , Tang Wen-yue , Zhang Pu-qing , Xie Yan-zhao
Published: December 2023

In this paper, a kind of tightly coupled array (TCA) with time-domain beam scan is developed for the radiation of high-power ultrawideband (UWB) electromagnetic pulses, and the peak-power pattern is proposed to characterize the directivity. First, the active voltage standing wave ratio (AVSWR) bandwidth of the TCA is optimized, which is the precondition for the beam scan. It indicates that the lower-cutoff frequency (LCF) is inversely proportional to the total length of the whole array; an increase in the distance between the array and the ground plane could remarkably reduce the LCF; and an increase in the element number can also decrease the LCF because of the increase in length, but more elements would make the center elements difficult to match in the low-frequency range, so there is a limitation on the number of elements for a certain LCF. Based on these results, a six-element linear array is designed. Then, the definition of the peak-power pattern is proposed to characterize the directivity of the UWB pulsed antenna. Finally, the optimized six-element array is developed, and the measured working band is 276 MHz–6.4 GHz (AVSWR < 3). The effective potential gain is 1.76, and it improves by 51.7% with a reduction in the aperture area by 68.4% compared with the previous TCA, which means that the aperture efficiency is remarkably improved. The half-power beam width of the developed TCA with the scan angle of 0° is 45°. The time-domain beam scan could be performed with time-delay feeding lines, and the maximum scan angle is over ±30° in the E-plane. The developed TCA can be applied for the generation of high-power electromagnetic environments for the study of intentional electromagnetic interference.