bluuebunny/crossref_metadata_2025 huggingface dataset:
Virtual network function reconfiguration in 5G networks: An optimization perspective
Authors: Biallach Hanane , Bouhtou Mustapha , Kumbria Kristina , Nace Dritan , Tomaszewski Artur
Published: February 2024

One of the major challenges in managing 5G networks is the reconfiguration of network slices. The task covers in particular reconfiguration and relocation of virtual network functions (VNFs) so as to match the service requirements of the slices and the availability of resources of the data centers. In this article, we study in deep the problem of optimal VNFs reconfiguration analyzing a number of its variants. We define two exact, compact integer linear programming formulations of the VNFs reconfiguration problem, and derive two approximate solution algorithms, one of them based on the column generation method. Numerical tests and comparisons illustrate the performance of the algorithms and the quality of the provided solutions.
Areas of work‐life, psychological capital and emotional intelligence on compassion fatigue and compassion satisfaction among nurses: A cross‐sectional study
Authors: Maillet Stéphanie , Read Emily A.
Published: February 2024

Aim

To examine the impact of six areas of work‐life, emotional intelligence and psychological capital on compassion fatigue and compassion satisfaction among Canadian Registered Nurses and licensed practical nurses.

Design

A cross‐sectional survey study.

Methods

A convenience sample of 296 Registered Nurses and 110 licensed practical nurses answered a self‐administered questionnaire measuring areas of work‐life, psychological capital, emotional intelligence, compassion satisfaction and compassion fatigue in September 2019. The association between variables were analysed with descriptive and correlational analyses, while the hypothesized models were tested using multiple regression analyses.

Results

This study identified several areas of work‐life and intrapersonal resources that impacted compassion satisfaction and compassion fatigue. Among Registered Nurses, compassion satisfaction was predicted by psychological capital, rewards, values and workload. Compassion fatigue was predicted by psychological capital, workload, control and community. Among licensed practical nurses, compassion satisfaction was predicted by psychological capital and emotional intelligence. Compassion fatigue was predicted by workload and psychological capital. Study results also revealed significant differences in Registered Nurses' and licensed practical nurses' perceptions of workload, rewards and fairness at work, and both compassion satisfaction and compassion fatigue. Registered Nurses perceived their workload to be more manageable and perceived greater rewards and greater fairness at work than licensed practical nurses. Compassion fatigue was higher for Registered Nurses than licensed practical nurses, while compassion satisfaction was higher for licensed practical nurses than Registered Nurses. Future studies should investigate the nature and span of these differences to suggest relevant strategies to mitigate compassion fatigue and promote compassion satisfaction for each of these nursing roles.

Conclusion

The results of this study underscore the need to create nursing work environments that foster a manageable workload and positive social relationships, where nurses have professional autonomy, decision‐making capacities and access to adequate resources to do their job effectively. The nursing work environment should also provide recognition of nurses' contributions and an alignment between personal and organizational values. Investments in the development and improvement of nurses' psychological capital and emotional intelligence should be prioritized since they are malleable and impactful intrapersonal resources on compassion satisfaction and compassion fatigue.

Reporting method

This study adhered to the STROBE guidelines.

Public contribution

A total of 406 nurses were involved in this study by answering a self‐administered study survey.
Associations Between Risk Perception and HPV Knowledge and Vaccine Uptake: Highlighting the LGBTQ+ Population
Authors: Ayo‐Ajibola Oluwatobiloba , Davis Ryan J. , Lin Matthew E. , West Jonathan D. , Kokot Niels C. , Chambers Tamara
Published: February 2024

Introduction

Gay and bisexual males and other LGBTQ+ communities are more frequently exposed to factors associated with an increased risk of human papillomavirus (HPV) acquisition. Vaccination is critical to protect against HPV+ head and neck cancer (HNC). We characterized the association of perceived level of risk of contraction with HPV knowledge, and vaccine decision‐making.

Study Design

Cross‐sectional cohort.

Setting

LGBTQ and general survey Reddit forums (control).

Methods

A survey was shared amongst the online forums. Descriptive statistics characterized the data. Multivariable logistic regression was used to understand factors associated with vaccination, self‐perceived high risk, and knowledge of HPV + HNC.

Results

Of 718 respondents, most were female (41.09%), Caucasian (59.89%), college‐educated (33.01%), and insured (77.15%) with a mean age of 30.75 years. Half were vaccinated (49.16%), with most unvaccinated endorsing interest (60.58%). Few dependents were vaccinated (25.91%), with interest in vaccination among parents of unvaccinated children (38.58%). Knowledge of HIV's association with HPV (62.95%), HPV causing HNC (55.57%), and the vaccine's efficacy against HNC (55.57%) was also moderate. Identifying female (P = .042), a self‐perceived high‐risk (P < .001), and having vaccinated children (P < .001) increased vaccination likelihood; transgender (P = .021), or lesbian or gay sexual identity (P < .001) decreased likelihood. Personal HNC diagnosis (P < .001), self‐vaccination (P < .001), having vaccinated children (P < .001), having anal sex (P = .001) or no knowledge of past HPV status (P < .001) increased likelihood of high self‐perceived risk.

Conclusion

Efforts to improve public education regarding the association between HPV and HNC and vaccination efficacy are required to better inform vaccine decision‐making among individuals at risk for HPV infection.
Association Between Modified Frailty Index and Postoperative Outcomes of Tracheostomies
Authors: Chinta Sree , Haleem Afash , Sibala Dhiraj R. , Kumar Keshav D. , Pendyala Navya , Aftab Owais M. , Choudhry Hannaan S. , Hegazin Michael , Eloy Jean Anderson
Published: February 2024

Objective

The 5‐item modified frailty index (mFI‐5) has been used to stratify patients based on the risk of postoperative complications in several surgical procedures but has not yet been done in tracheostomies. This study investigates the association between the mFI‐5 score and tracheostomy complications.

Study Design

Retrospective database review.

Setting

United States hospitals.

Methods

The National Surgical Quality Improvement Program database was queried for tracheostomy patients between 2005 and 2018. The mFI‐5 was calculated for each patient by assigning 1 point for each of the following comorbidities: diabetes mellitus, hypertension, congestive heart failure, chronic obstructive pulmonary disease, and functionally dependent health status. Univariate and multivariable analyses were conducted to determine associations between the mFI‐5 score and postoperative complications.

Results

A total of 4438 patients undergoing tracheostomies were queried and stratified into the following groups: mFI = 0 (N = 1741 [39.2%], mFI = 1 (N = 1720 [38.8%]), mFI = 2 (N = 726 [16.4%]), and mFI of 3 or higher (N = 251 [5.7%]). Univariate analysis showed that patients with higher mFI‐5 scores had a greater proportion of smoking, dyspnea, obesity, steroid use, emergency cases, complications, reoperations, and mortality (P < .001). Multivariable analyses found associations between mFI‐5 score and any complication (odds ratio [OR]: 1.49, 95% confidence interval [CI]: 1.03‐2.16, P = .035), mortality (OR: 2.32, 95% CI: 1.15‐4.68, P = .019), and any medical complication (OR: 2.75, 95% CI: 1.88‐4.02, P < .001).

Conclusion

This study suggests an association between the mFI‐5 score and postoperative complications in tracheostomies. mFI‐5 score can be used to stratify tracheostomy patients by operative risk.
Motivations behind wild animal consumption in social media in Mexico: A case study
Authors: Gutiérrez‐Ibarra Marielise , Jiménez Lara José Miguel , Amador‐Cruz Francisco , Camargo‐Rivera Evangelina , Ramírez‐Bravo O. Eric
Published: February 2024

Wildlife trade is a worldwide threat to biodiversity. It is a complex problem, and to deal with it, one must analyse its constituting factors, some of which are specific to certain geographic areas. Although Mexican laws have prohibited selling wild products, Mexico is still both a source and consumer of exotic wildlife; however, there is limited data on why people participate in this type of trade.

This paper aims to understand people's motivations for participating in the wildlife trade. 192 surveys on a population segment unrelated to it and 30 in‐depth interviews were performed to determine the patterns of wildlife trade in Mexico. Finally, we performed two in‐person interviews with collectors of large‐scale animals.

The outcomes demonstrated that Facebook was the social media showing more wildlife content. Most participants were aware of the diverse impacts of the animal trade, as well as, that offering, buying and having certain animals was a crime but were assuaged due to common knowledge that authorities do not investigate social media. Finally, based on the findings from the in‐person interviews, it was observed that the individuals engaged in heavy trafficking believed that their actions were altruistic in nature.

We concluded that the primary motivations for wildlife trade in Mexico were economic status and prestige within their social groups. In that order, our study is a pioneering attempt to determine motivations in Mexico, which could be a basis for future regional studies.

Read the free Plain Language Summary for this article on the Journal blog.
Synthesis and characterization of poly (acrylamide‐co‐acrylic acid)/chitosan (derived from fish scales) for controlled release of amoxicillin drug
Authors: Sahoo Deepti Rekha , Biswal Trinath
Published: February 2024

Chitosan (CS) can be extracted from waste fish scales through a series of chemical processes, including demineralization, deproteinization, and deacetylation. The biomaterial poly (acrylamide [AM]‐co‐acrylic acid [AA])/CS is a unique superabsorbent material synthesized through the free radical graft copolymerization method by using AM, AA, and CS powder. During synthesis, ammonium persulfate is used as an initiator, and N, N′‐methylene bisacrylamide is used as a cross‐linker. Scanning electron microscopy and Fourier transform infrared spectroscopy have been studied to know about the morphology and structure of the synthesized superabsorbent materials. The water absorbency of the material continuously increases from day 1 to day 30. The thermogravimetric analysis (TGA) and derivative thermogravimetry (DTG) of the superabsorbent material show adequate thermal stability. The X‐ray diffraction (XRD) analysis indicates that the synthesized biomaterial is virtually amorphous in nature. The percentage of biodegradability increases with time. The encapsulation efficiency of amoxicillin drugs is around 70%, which indicates that the biomaterial is highly efficient for drug release applications. The synthesized novel biomaterial is a low‐cost, eco‐friendly, and thermally stable hydrogel that can be effectively used in drug release applications.

Highlights

Chitosan (CS)‐based hydrogels are highly pH‐sensitive towards drug release.

The biodegradability and swelling behavior of the synthesized biomaterial were studied by adopting a suitable methodology.

The novel material formed was characterized by using Fourier transform infrared spectroscopy, TGA, and Scanning electron microscopy. The encapsulation efficiency, kinetic study, and controlled drug release behavior of the amoxicillin drug were studied in solutions of simulated gastric fluid and phosphate‐buffered saline.

The material developed in this study shows good performance in controlled drug delivery, and is therefore suitable for manufacturing medical devices used in drug delivery.
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

Light 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

Rationale

Isomerism 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).

Methods

The 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.

Results

The 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.

Conclusions

A 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

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

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

In 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

Phosphates 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

Design 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

Code 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

The 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.
Empowering Indoor Photovoltaics: Stable Lead‐Free Perovskites and Beyond
Authors: Farooq Umar , Wang Jin , Pan Zhenxiao , Li Zhengquan
Published: February 2024

Indoor photovoltaics (IPVs) have garnered significant attention in recent years due to their potential to empower small portable electronic devices and the Internet of Things. After silicon solar cells, it is now widely acknowledged that the dominant technology in the field of outdoor photovoltaics/IPVs is hybrid lead (Pb) halide perovskites. Despite the fascinating characteristics of hybrid Pb halide perovskites, the presence of toxic Pb is regarded as one of the major factors that prevent commercialization. Low‐toxic, Pb‐free, and stable perovskites are also being used in outdoor solar cells (ODSCs), but their efficiencies are low due to large bandgap (i.e., ≈2.0 eV). Recently, some of the stable, Pb‐free perovskite materials have drawn great interest due to their initial performance across various fields, including light‐emitting diodes, photodetectors, X‐rays, photocatalysis, ODSCs, and in IPVs. In this perspective, the current status and prospects for Pb‐free halide perovskites, chalcogen perovskites, silver bismuth halide (AaBbXa + 3b) family, and other chalcogen materials are summarized and being explored to speed up the progress of IPVs.
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

Glaucoma 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

Maximin 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

This 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

This 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

A 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

This 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

Despite 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

In 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

In 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

In 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.
Integrating Knowledge into Conversational Agents for Worker Upskilling
Authors: Alonso Rubén , Dessí Danilo , Meloni Antonello , Murgia Marco , Diego Reforgiato Recupero
Published: February 2024

The labor market is a key part of an economy. Several existing online platforms allow the upload of resumes and the search for a job. One of their limitations, however, is that obtaining the best opportunity can be hard because certain jobs need some experiences, abilities, and features that an applicant might not know. The recent diffusion and employment of conversational agents definitely have proven to benefit this kind of issue. For example, ChatGPT has shown impressive outcomes in different domains and for a variety of tasks. It has weaknesses, although, related to the veracity of the responses it generates, which might deceive the user interacting with it. The usage of external domain knowledge is the direction we suggest in this chapter. Several lexical databases and taxonomies have already been collected and designed by different organizations. We illustrate a list of such resources and provide a solution that integrates conversational agents with relevant information extracted from one of such resources showing the benefits and the impact that our proposal can generate.
Advancing Networked Production Through Decentralised Technical Intelligence
Authors: Walter Stefan , Mikkola Markku
Published: February 2024

In today’s competitive landscape, networked production plays a crucial role in enabling companies to create value and remain competitive. By integrating advanced logistics and supply chain processes, companies optimise resources through cooperation and dynamic arrangements. However, managing the emerging complexity requires a new and intelligent approach. Decentralised Technical Intelligence (DTI) is a response to this challenge. It refers to the distributed and autonomous intelligence embedded in interconnected systems, devices, and agents—involving both humans and machines. By combining the strengths of humans and artificial intelligence (AI), DTI creates a coordinated environment that enhances the overall system intelligence. This collaboration leads to greater autonomy and enables multiple DTI agents to operate independently within a decentralised network. To achieve advanced networked production with DTI, a roadmap will be established, encompassing building blocks that focus on transparency, cooperation, sustainability, seamless integration and intelligent network control. All building blocks are linked to a vision, value promise and development pathway. As networked production evolves, it gives rise to new business models and demands new skills and expertise. By following this roadmap, DTI unlocks its potential for advancement, creating value and fostering competitiveness.
XAI for Product Demand Planning: Models, Experiences, and Lessons Learnt
Authors: Lampathaki Fenareti , Bosani Enrica , Biliri Evmorfia , Ichtiaroglou Erifili , Louca Andreas , Syrrafos Dimitris , Calabresi Mattia , Sesana Michele , Antonello Veronica , Capaccioli Andrea
Published: February 2024

Today, Explainable AI is gaining more and more traction due to its inherent added value to allow all involved stakeholders to understand why/how a decision has been made by an AI system. In this context, the problem of Product Demand Forecasting as faced by Whirlpool has been elaborated and tackled through an Explainable AI approach. The Explainable AI solution has been designed and delivered in the H2020 XMANAI project and is presented in detail in this chapter. The core XMANAI Platform has been used by data scientists to experiment with the data and configure Explainable AI pipelines, while a dedicated manufacturing application is addressed to business users that need to view and gain insights into product demand forecasts. The overall Explainable AI approach has been evaluated by the end users in Whirlpool. This chapter presents experiences and lessons learnt from this evaluation.
Multisided Business Model for Platform Offering AI Services
Authors: Ejsmont Krzysztof , Gladysz Bartlomiej , Roczon Natalia , Bettoni Andrea , Barut Zeki Mert , Haber Rodolfo , Minisci Elena
Published: February 2024

The development of B2B platforms has led to the diffusion of business models (BMs) based on the concept of sharing economy. In recent years, multisided platform BMs have become an important way of creating and capturing value even though the phenomenon remains undertheorized (Zhao et al., Long Range Planning 53(4):101892, 2020). Multisided platforms (MSPs) are present in an increasing number of sectors due to the development of the Internet, digital technologies, and artificial intelligence (AI). The manufacturing sector has not been untouched by this trend; however, it still struggles to establish value drivers to support small- and medium-sized enterprises (SMEs) in the change. The objective of the proposed study is to present an ecosystem for the SME manufacturing sector, which will be based on the selected MSP offering AI services. An initial BM for the AI platform as a service will be design, and a revenue model will be proposed within it. The selected case allowed the use of a methodological approach (PDT – Platform Design Toolkit) to the design of an MSP business model based on a qualitative analysis of the dynamics governing the platform ecosystem. The originality of the research stems from the reliance on data obtained from the implementation of the KITT4SME project (H2020, GA 952119). The study results indicate that it is crucial to properly identify the needs of the platform’s stakeholders, and then precisely define the values and the mechanisms for exchanging them through MSP.
Digital-Twin-Enabled Framework for Training and Deploying AI Agents for Production Scheduling
Authors: Bakopoulos Emmanouil , Siatras Vasilis , Mavrothalassitis Panagiotis , Nikolakis Nikolaos , Alexopoulos Kosmas
Published: February 2024

Digital manufacturing tools aim to provide intelligent solutions that will help manufacturing industry adapt to the volatile work environment. Modern technologies such as artificial intelligence (AI) and digital twins (DT) are primarily exploited in a way to simulate and select efficient solutions from a broad range of alternative decisions. This work aims to couple DT and AI technologies in a framework where training, testing, and deployment of AI agents is made more efficient in production scheduling applications. A set of different AI agents were developed, utilizing key optimization technologies such as mathematical programming, deep learning, heuristic algorithms, and deep reinforcement learning are developed to address hard production schedule optimization problems. DT is the pilar technology, which is used to simulate accurately the production environment and allow the agents to reach higher efficiency. On top of that, Asset Administration Shell (AAS) technology, being the pilar components of Industry 4.0 (I4.0), was used for transferring data in a standardized format in order to provide interoperability within the multi-agent system (MAS) and compatibility with the rest of I4.0 ecosystem. The system validation was provided in the manufacturing system of the bicycle industry by improving the business performance.
Misrepresentation in Educational Media (1954–1999)
Authors: Gellman Mneesha
Published: February 2024

In this chapter, eight textbooks are analyzed from the years 1954 through 1999. From dissecting quotes, images, and maps within the textbooks, the textbook rhetoric is highly steeped in themes of White glory, White superiority, and White supremacy. There is excess justification on why White colonizers had to take over Native land, and very little mention on the plights of Mexican or Mexican American experiences in the 1800s Mexican-American War. Textbooks of this time were highly inaccurate and avoided the hard truths. Beginning in the 1980s, though, some of the analyzed textbooks started to improve by providing more accurate representations of the plights experienced by Native Americans, but the textbooks remain problem-ridden.
Kids These Days: Ethnographic Evidence on the Impact of Textbook Misrepresentation
Authors: Gellman Mneesha
Published: February 2024

To expand on the importance of culturally relevant curricula and textbooks, this chapter features the voices of students themselves, who attend various schools in far Northern California. Each have their own backgrounds and personal stories tied to their cultures, but much of their points are the same. They wish for things like teachers who understand their experiences and classroom activities and textbooks that include Native and other BIPOC experiences. Highlighting student voices and perspectives shows the dire need facing the US school system today when it comes to curricula being taught.
Digital Twin for Aerial-Ground Networks
Authors: Zhang Yan
Published: February 2024

With the widespread deployment of unmanned aerial vehicles (UAVs) in civil and military fields, researchers have turned their attention towards the emerging area of aerial-ground networks for computing-intensive applications, data-intensive applications, and network-intensive applications. However, the application of aerial-ground networks relies on dynamic perceptions and intelligent decision making, which are difficult to conceive of due to the heterogeneity of ground devices and the complexity of the aerial-ground environment. The convergence of digital twin (DT) and UAVs has great potential to tackle the challenge and improve the service quality and stability in applications such as rescue and search and communication relaying. This chapter first investigates the advantages, challenges, and key techniques of DTs for aerial-ground networks. In addition, we highlight the main issues of DT for UAV-assisted aerial-ground networks with two case studies, including cross-domain resource management and intelligent cooperation among devices.