bluuebunny/crossref_metadata_2025_split huggingface dataset:
High‐Energy Ball Milling Synthesize All‐Inorganic Lead‐Free Green Emitting Cs3MnBr5 Crystals
Authors: Xue Shiwei , Ding Huiling , Xia Zhenghao , Mao Hengbin , Zhao Sibo , Wang Hailong , Fan Bingbing , Shao Gang , Xu Hongliang , Lu Hongxia 
Published: February 2024

AbstractLight Emitting Diodes (LEDs) are the key to new generation displays. New semiconductor electron–hole recombination layer is the key to high‐performance LEDs. Although all‐inorganic quantum dot (QD) materials have the advantages of wide color gamut and narrow emission peaks, they face issues of toxicity of heavy metal ions and stability of QDs, the synthesis method is highly polluting and difficult to achieve industrial production. Thereby, lead‐free all‐inorganic phosphor with narrow FWHM needs to be explored. A new synthesis method is required to be investigated. All‐inorganic Mn2+ bromide (Cs3MnBr5) is easy to synthesize and has low toxicity and superior luminescent properties. However, most synthesis methods rely on liquid‐phase reaction systems and cannot achieve highly efficient synthesis. High‐energy ball milling is an efficient method and has enormous potential for industrial production. In this paper, this method is used to synthesize Cs3MnBr5, and then Cs/Mn ratio, ball milling time, and ligand usage are studied. Furthermore, a new phase transformation of all‐inorganic Mn2+ bromide is discovered, and the mechanism of high‐energy ball milling is interpreted combining with phase transformation process. This article brings a new method to synthesis of all‐inorganic Mn2+ bromide, explains the mechanism of ball milling, and expands the phase transformation of all‐inorganic Mn2+ bromide.
A strategy of combining energy‐resolved mass spectrometry and density functional theory for the recognition of forsythoside isomers
Authors: Lin Chuhui , Sun Yangkun , Kuang Jingjing , Zhang Hongyang , Yang Haoyu , Zhang Min , Hu Ping 
Published: February 2024

RationaleIsomerism is very common in nature, and the mass spectrometry (MS) behavior of isomers is highly similar, making their spectral analysis and identification difficult. Computational chemistry can effectively assist the study of MS spectra and molecule structures. Herein, three isomers of forsythoside (For‐A, For‐H, and For‐I) were successfully identified using energy‐resolved MS combined with density functional theory (DFT).MethodsThe MS scan spectra of the isomers were collected in electrospray ionization MS. The possible positive/negative ion adduct sites were investigated using the DFT method, and the molecular formation energy of each precursor ion was obtained. In the multireaction monitoring mode, the spectra of the common precursor ion → product ion pair of the three isomers were acquired under different collision energy, and the optimal collision energy (OCE) and maximum relative intensity (MRI) of each product ion were obtained. The energy of the broken chemical bond was calculated.ResultsThe experimental data showed that the product ions of [M + H]+ of the three isomers have the greatest differences in OCE and MRI and were the most suitable to distinguish the three isomers. The DFT data showed that there was a good positive correlation between the bond fragmentation energy calculated by the quasi‐molecular ion model and OCE. The results indicated that the energy of precursor ions and corresponding fragments could be correlated with their experimental spectra.ConclusionsA strategy of combining energy‐resolved MS and DFT was implemented on the recognition of forsythoside isomers, and this strategy was expected to be applied to the identification of more isomers.
Localised Erythema Nodosum Leprosum—A Rare Entity Managed with Thalidomide
Authors: Patel Chandni , De Barros Barbara , Walker Stephen L. 
Published: February 2024

Abstract
Leprosy is caused by Mycobacterium leprae. The condition primarily affects the skin and peripheral nerves. There are two types of leprosy reactions, Type 1 and Type 2 or erythema nodosum leprosum (ENL). ENL is a severe multi-system, immune-mediated complication of lepromatous leprosy. It is characterised by widespread painful cutaneous nodules, fever and peripheral oedema. This report discusses the unusual case of a 29-year-old woman who developed a localised form of ENL which required thalidomide to induce remission.
Overview of Popular Cosmeceuticals in Dermatology
Authors: Crous Chantalle , Pretorius Judey , Petzer Anél 
Published: February 2024

Abstract
The eternal pursuit to prevent ageing and maintain a youthful appearance has resulted in a rapidly expanding cosmeceutical industry. Cosmeceutical products, particularly of natural origin, are in high demand due to claims of efficacy for signs of ageing and other skin conditions. Consumers often include cosmeceutical products in their skin care regime as they are readily available, and a more affordable option compared to prescription products. However, many cosmeceutical ingredients lack clinical evidence regarding their efficacy and safety as these products are not regulated by the U.S. Food and Drug Administration. This review provides a brief overview of several popular cosmeceutical ingredients with regards to their potential indications, targets and mechanisms of action.
Crystal violet removal from aqueous media using Tragopogon dubius adsorbent
Authors: Yaghoub Krimi Seyed , Marofi Safar , Zare Mohamad Ali 
Published: February 2024

AbstractIn this study, Tragopogon dubius was used using a specific condition of adsorption to remove a cationic harmful dye (crystal violet : CV) in aqueous liquid media. Removing time, rate of adsorbent, pH of the media, initial concentration of the harmful dye, and absorbent particle size were studied to reach an optimum adsorption condition. Before and after the biosorption process of CV, the SEM micrographs and EDX spectra were obtained for Tragopogon dubius. The maximum removal efficiency of CV (90–93 %) has happened at pH=7.0, contact time of 120 min, adsorbent dose of 0.2 g/L (with particle size of 0.074 mm), temperature of 25 ○C, and pollutant rate of 50.0 mg/L. The adsorption rate of Tragopogon dubius was calculated using equilibrium models. It was also increased by water washing (30 min). The results showed that 50 % of the dye was absorbed when the adsorption time reached 50 min. Maximum adsorption (212.9 mg/g) occurred after 120 min of removing time. The results revealed the best accordance of the Tragopogon dubius adsorption with the Freundlich model (R2=0.96). A kinetic agreement was also observed between the dye adsorption and the Pseudo‐second order model. The negative value of ΔS° (−53.51 J/K mol) indicates that Tragopogon dubius removes CV during a relatively stable process with randomness in the system. The negative values of ΔG° at different temperatures indicate that the nature of CV adsorption was spontaneous.
N‐Containing Na2VTi(PO4)3/C for Aqueous Sodium‐Ion Batteries
Authors: Meng Qing Yu , Shao Jia Cheng , Dou Xin Rui , Chi Hong Zhong 
Published: February 2024

AbstractPhosphates featuring a 3D framework offer a promising alternative to aqueous sodium‐ion batteries, known for their safety, cost‐effectiveness, scalability, high power density, and tolerance to mishandling. Nevertheless, they often suffer from poor reversible capacity stemming from limited redox couples. Herein, N‐containing Na2VTi(PO4)3 is synthesized for aqueous sodium‐ion storage through multi‐electron redox reactions. It demonstrates a capacity of 155.2 mAh g−1 at 1 A g−1 (≈ 5.3 C) and delivers an ultrahigh specific energy of 55.9 Wh kg−1 in a symmetric aqueous sodium‐ion battery. The results from in situ X‐ray diffraction analysis, ex situ X‐ray photoelectron spectroscopy analysis, and first‐principle calculations provide insights into the local chemical environment of sodium ions, the mechanisms underlying capacity decay during cycling, and the dynamics of ion and electron transfer at various states of charge. This understanding will contribute to the advancement of electrode materials for aqueous sodium‐ion batteries.
Using Design Thinking to break social barriers: An experience report with former inmates
Authors: Dias Canedo Edna , Rodrigues Cançado Emille Catarine , Barbosa Mota Alana Paula , Nery Bandeira Ian , Teixeira Costa Pedro Henrique , Lima Fernanda , Amaral Luis , Bonifácio Rodrigo 
Published: February 2024

AbstractDesign Thinking techniques have been widely used in software requirements elicitation to understand the necessities of stakeholders and end‐users. However, there is a lack of evidence of their effectiveness when applied to guide the development process of a system targeting vulnerable populations. What are the implications of using Design Thinking techniques to elicit requirements in a community of former inmates—and what would be the benefits of and challenges in this deployment? In this paper, we report our experience of using Design Thinking for requirements elicitation of a mobile application customized for the former inmates of the Brazilian prison system and their families. We applied techniques such as Brainstorming, Stakeholder Mapping, Personas Creation, Rapid Ethnography, and Interviews to obtain relevant data and create several prototypes. These techniques contribute to the development of an uncommon application that aims to help the reintegration process of former inmates into society. Our results validate the initial hypothesis that such techniques, when applied to a sensitive context, assist product development that meets the end‐users' needs by creating a higher quality product. The main limitation of the research was the lack of access to low‐literacy end‐users and/or former inmates without previous experience using mobile devices.
GRRLN: Gated Recurrent Residual Learning Networks for code clone detection
Authors: Zhang Xiangping , Liu Jianxun , Shi Min 
Published: February 2024

AbstractCode clone detection is a critical problem in software development and maintenance domains. It aims to identify functionally identical or similar code fragments within an application. Existing works formulate the code clone detection task as a binary classification problem which predicts a code pair as a clone or not based on a pre‐defined threshold. In reality, there are various types of code clone subject to the degree of how a pair of code fragments are similar to each other. To investigate the effect of different code clone detection manners on the clone detection result, we propose Gated Recurrent Residual Learning Networks (GRRLN), a novel neural network model for code clone detection. To train GRRLN, we first represent each code fragment as a statement‐level tree sequence derived from the whole abstract syntax tree (AST). Then, a gated recurrent neural network with residual connections is adopted to fully extract the semantics of all individual statement trees together with their dependency relationships across the input statement sequence. Finally, the output representations of code fragments by GRRLN are used for similarity calculation and clone detection. We evaluate GRRLN using two real‐world datasets for code clone detection and clone type classification. Experiments show that GRRLN achieves promising and compelling results and meanwhile needs significantly less time and memory consumption compared with the state‐of‐the‐art methods.
MXene‐Integrated Solid‐Solid Phase Change Composites for Accelerating Solar‐Thermal Energy Storage and Electric Conversion
Authors: Usman Ali , Qin Mulin , Xiong Feng , Aftab Waseem , Shen Zhenghui , Bashir Akbar , Han Haiwei , Han Shenghui , Zou Ruqiang 
Published: February 2024

AbstractThe high thermal storage density of phase change materials (PCMs) has attracted considerable attention in solar energy applications. However, the practicality of PCMs is often limited by the problems of leakage, poor solar‐thermal conversion capability, and low thermal conductivity, resulting in low‐efficiency solar energy storage. In this work, a new system of MXene‐integrated solid‐solid PCMs is presented as a promising solution for a solar‐thermal energy storage and electric conversion system with high efficiency and energy density. The composite system's performance is enhanced by the intrinsic photo‐thermal behavior of MXene and the heterogeneous phase transformation properties of PCM molecular chains. The optimal composites system has an impressive solar thermal energy storage efficiency of up to 94.5%, with an improved energy storage capacity of 149.5 J g−1, even at a low MXene doping level of 5 wt.%. Additionally, the composite structure shows improved thermal conductivity and high thermal cycling stability. Furthermore, a proof‐of‐concept solar‐thermal‐electric conversion device is designed based on the optimized M‐SSPCMs and commercial thermoelectric generators, which exhibit excellent energy conversion efficiency. The results of this study highlight the potential of the developed PCM composites in high‐efficiency solar energy utilization for advanced photo‐thermal systems.
Deep learning models to predict primary open‐angle glaucoma
Authors: Zhou Ruiwen , Philip Miller J. , Gordon Mae , Kass Michael , Lin Mingquan , Peng Yifan , Li Fuhai , Feng Jiarui , Liu Lei 
Published: February 2024

SummaryGlaucoma is a major cause of blindness and vision impairment worldwide, and visual field (VF) tests are essential for monitoring the conversion of glaucoma. While previous studies have primarily focused on using VF data at a single time point for glaucoma prediction, there has been limited exploration of longitudinal trajectories. Additionally, many deep learning techniques treat the time‐to‐glaucoma prediction as a binary classification problem (glaucoma Yes/No), resulting in the misclassification of some censored subjects into the nonglaucoma category and decreased power. To tackle these challenges, we propose and implement several deep‐learning approaches that naturally incorporate temporal and spatial information from longitudinal VF data to predict time‐to‐glaucoma. When evaluated on the Ocular Hypertension Treatment Study (OHTS) dataset, our proposed convolutional neural network (CNN)‐long short‐term memory (LSTM) emerged as the top‐performing model among all those examined. The implementation code can be found online (https://github.com/rivenzhou/VF_prediction).
New bounds and search for maximin distance U‐type designs
Authors: Liu Sixu , Wang Yaping 
Published: February 2024

AbstractMaximin distance designs have attracted increasing attention in computer experiments owing to their appealing space‐filling properties. The quality of these designs is typically evaluated by comparing their separation distance with the associated upper bound. Nevertheless, deriving tight upper bounds for the separation distance of designs remains a challenging problem that has been infrequently addressed in the literature. In this study, we obtain a new upper bound for the separation distance of certain classes of five‐level U‐type designs. We also investigate the characteristics of maximin distance U‐type designs and show the optimality of some existing orthogonal designs. Based on these theoretical results, we develop an efficient algorithm for searching maximin distance U‐type designs. Numerical studies and comparisons are given to show the superior performance of the obtained designs.
Reducing the statistical error of generative adversarial networks using space‐filling sampling
Authors: Wang Sumin , Gao Yuyou , Zhou Yongdao , Pan Bin , Xu Xia , Li Tao 
Published: February 2024

AbstractThis paper introduces a novel approach to reducing statistical errors in generative models, with a specific focus on generative adversarial networks (GANs). Inspired by the error analysis of GANs, we find that statistical errors mainly arise from random sampling, leading to significant uncertainties in GANs. To address this issue, we propose a selective sampling mechanism called space‐filling sampling. Our method aims to increase the sampling probability in areas with insufficient data, thereby improving the learning performance of the generator. Theoretical analysis confirms the effectiveness of our approach in reducing statistical errors and accelerating convergence in GANs. This research represents a pioneering effort in targeting the reduction of statistical errors in GANs, and it demonstrates the potential for enhancing the training of other generative models.
Performance study of crack width calculation methods according to Eurocodes, fib model codes and the modified tension chord model
Authors: Terjesen Otto , Pinto Gianclaudio , Kanstad Terje , Tan Reignard 
Published: February 2024

AbstractThis article investigates the accuracy of various crack width prediction models and the newly proposed modified tension chord model (MTCM). A large number of experimental crack widths have been collected from the literature, including 203 specimens of reinforced concrete (RC) members subjected to bending and tension. The prediction models are described with upcoming new formulations and database validation. The modeling uncertainty is found by comparing the predicted crack widths against experimental data obtained using a log‐normal distribution. The results show that fib Model Code 2010 and MTCM provide the best crack width predictions of the collected databases; MTCM has the fewest mechanical simplifications of the investigated models and no empirical modifications for fitting towards experimental databases, in contrast to the approaches in Eurocode 2 and Model Code. However, the latter do predict the crack width to a reasonably good extent and are more suited for practical dimensioning than the MTCM. The findings in this article suggest that the MTCM should serve as a point of departure for further development of crack width calculation methods, and that it may have an extensive range of possible applications in the future.
The Jersey tornado and hailstorm of 1–2 November 2023
Authors: Knightley Paul , Horton Sarah , Clark Matthew , Winter Matthew 
Published: February 2024

AbstractA powerful tornado affected eastern parts of Jersey, Channel Islands, on the night of Wednesday 1 and Thursday 2 November 2023, associated with a supercell thunderstorm. As well as spawning the tornado, the parent thunderstorm also produced a severe hailstorm, with hailstones upwards of 5cm in diameter documented. A TORRO site investigation, assisted by staff from Jersey Met, concluded that the tornado produced a continuous damage path across the east of the island of around 8km in length, with a width of up to 500m. The tornado was assigned a provisional rating of T6 on the International Tornado Intensity Scale.
Emotional intelligence frameworks in leadership education
Authors: Haber‐Curran Paige , Williamson Erin 
Published: February 2024

AbstractThis article focuses on integrating topics of emotional intelligence in curricular and co‐curricular collegiate leadership education. The authors spotlight one institution's use of emotionally intelligent leadership as a framework across a variety of leadership programs, courses, and trainings. Critiques, considerations, and resources to inform leadership education efforts that focus on emotional intelligence are included.
From hero to humility: Critical approaches to teaching servant leadership
Authors: Madison Karryna , Fernando Judith , Robberts Jonathan , Eva Nathan 
Published: February 2024

AbstractDespite the growth of servant leadership research, current understandings of how to teach servant leadership are limited. Further, current approaches often reinforce heroic notions of servant leadership that do not adequately prepare learners to engage in leadership within their own lives. Against this backdrop, we integrate critical pedagogical approaches within servant leadership education. To do so, we outline several applications that focus on leader development, leadership development, and community leadership development as well as several critical considerations for educators.
Integrated intelligence of inverse multiquadric radial base neuro‐evolution for radiative MHD Prandtl–Eyring fluid flow model with convective heating
Authors: Butt Zeeshan Ikram , Ahmad Iftikhar , Shoaib Muhammad , Ilyas Hira , Kiani Adiqa Kausar , Raja Muhammad Asif Zahoor 
Published: February 2024

AbstractIn this communication, a new stochastic numerical paradigm is introduced for thorough scrutinization of the magnetohydrodynamic (MHD) boundary layer flow of Prandtl–Eyring fluidic model along a stretched sheet impact on thermal radiation as well as convective heating scenarios by exploiting the accurate approximation knacks of ANNs (artificial‐neural‐networks) modeling by using the inverse multiquadric (IMQ) function optimized/trained with well‐reputed global search with genetic algorithms (GAs) and local search efficacy of sequential quadratic programming (SQP), that is, ANNs‐IMQ‐GA‐SQP. The mathematical model of the Prandtl–Eyring fluid flow is portrayed in the form of PDEs and then converted in the form of a nonlinear system of ODEs by utilizing suitable similarity transformation to calculate/analyze the solution dynamics. The kinematic and thermodynamic properties of MHD Prandtl–Eyring fluid flow are examined/observed by varying the sundry physical parameters. The obtained intelligent computing designed solver‐based numerical results are consistently found in good agreement with reference results obtained through the Adams numerical technique. First and second‐order cumulant‐based statistical assessments are extensively exploited to endorse trustily the efficacy of ANNs‐IMQ‐GA‐SQP solver based on exhaustive simulations for the Prandtl–Eyring fluidic system.
Effect of Hall current, Soret number, and inclined magnetic field on entropy generation of mixed convection Jeffrey fluid flow through sloping channel under Navier‐slip condition
Authors: Mahla Ravi , Kaladhar Kolla 
Published: February 2024

AbstractIn this research article, the irreversibility of Jeffery fluid in mixed convective flow with inclined channel under the influence of Navier‐slip condition is analyzed. The effects of Hall current, Soret number, and an inclined magnetic field are taken into account. The spectral quasi‐linearization method (SQLM) is used to solve the governing equations after transforming them into a dimensionless form. The impacts of various parameters on velocity, temperature, and concentration are examined graphically. With the use of tabular data, variations in skin friction, the Nusselt number, and the Sherwood number are also discussed. Our findings indicate that entropy production increases with higher values of the magnetic parameter, Hall current, and inclination angle. Conversely, we have observed an opposing trend with an increased value of slip condition at the left plate and the Jeffrey fluid parameter.
Rural Dimension of the Employment Policies for NEETs. A Comparative Analysis of the Reinforced Youth Guarantee
Authors: Petrescu Claudia , Braziene Ruta , Prieto-Flores Òscar , Soler Mariano , Costantini Anastasia , Buligescu Bianca , Skuciene Daiva , Rocca Antonella , Pizzolante Federica , Koltai Luca , Smoter Mateusz , Danilowska Sylwia 
Published: February 2024

AbstractIn 2020, the European Commission relaunched the Youth Guarantee (YG) Programme, its flagship policy for youth unemployment since 2013. This action aims to renew the European Union efforts on promoting the employment of those below 30 years old in the aftermath of the COVID-19 pandemic. All EU member states adapted this EU directive to their national policies releasing their own national strategies. One of the novelties of this transnational policy initiative is its emphasis on targeting youth living in rural, remote, or disadvantaged areas. This book chapter analyzes how different EU countries are adapting this policy at the national level and how they integrate the rural dimension in the proposed measures. Commonalities and differences in approaches and types of actions to be implemented across countries will be discussed.