bluuebunny/crossref_metadata_2025_split huggingface dataset:
A zinc porphyrin-amidine as a green carbon-based electron transport material for organic-light emitting diodes
Authors: Soultati Anastasia , Verykios Apostolis , Tsekouras Marios , Georgiopoulou Zoi , Vidali Veroniki , Pistolis Georgios , Davazoglou Dimitris , Coutsolelos Athanassios G. , Ogawa Marina , Skandamis Panagiotis N. , Argitis Panagiotis , Otsuki Joe , Vasilopoulou Maria 
Published: February 2024

AbstractCharge injection and transport interlayers based on artificial green carbon materials are imperative for a sustainable future of many classes of optoelectronic devices, including organic light-emitting diodes (OLEDs). Especially, porphyrin derivatives can act as efficient energy and charge funnels mimicking their successful photosynthetic function. Here, we report on the application of a novel green carbon material, in particular, a zinc porphyrin derivative bearing an amidine functional group (referred to as ZnP-amidine), as an electron transport material in fluorescent OLEDs based on a green-yellow co-polymer emitter. ZnP-amidine is processed from environmental friendly solvents without any annealing requirements thus being suitable for low-cost sustainable optoelectronics. It is applies as an ultra-thin interlayer between the aluminum cathode and the emissive layer to enable efficient electron transport and stable performance. This work paves the path towards low-cost green carbon materials inspired by natural processes for organic optoelectronics.
Formal Methods for Industrial Critical Systems
Authors: Groote Jan Friso , Huisman Marieke 
Published: February 2024

AbstractTo stimulate the development and application of formal methods in industry, we need to promote research and development for the improvement of formal methods and tools for industrial applications, and we need to exchange experiences of the industrial usage of these methods and tools. This special issue of Software Tools for Technology Transfer presents various tools and experience reports that are targeting the use of formal methods in industry. The papers in this special issue are extended versions of selected conference papers from the proceedings of the 27th International Conference on Formal Methods for Industrial Critical Systems (FMICS 2022).
Affordances and constraints of integrating esports into higher education from the perspectives of students and teachers: An ecological systems approach
Authors: Zhong Yuchun , Guo Kai , Chu Samuel Kai Wah 
Published: February 2024

AbstractThis study aimed to investigate the perceived affordances of incorporating esports into higher education using an ecological systems approach that examined the multiple factors shaping behaviours at the individual, interpersonal, and organisational levels. A total of 40 participants, comprising 32 students and 8 teachers, were invited to take part in semi-structured interviews. The data gathered from the interviews underwent qualitative analysis through the employment of thematic analysis methods. The results suggested that esports were perceived as having the potential to promote students’ skills development and foster an interactive learning culture. The study also identified constraints on esports integration at various levels, including student differences (i.e. in gaming interest, skills, attention, and physical capacity) and teachers’ insufficient knowledge (i.e. of esports and related pedagogy and content) at the individual level; concerns about the negative impacts of esports at the interpersonal level; and a lack of effective execution of university leadership at the organisational level. The results of this study offer valuable insights for education leaders into how to effectively exercise leadership in the context of esports. Specifically, the findings underscore the importance of developing professional development programmes for teachers to enhance their knowledge of the use of esports and related pedagogy and teaching content to improve the implementation of esports-based instruction.
Tokenized but remaining: how do international academics make sense of their decision to remain in Japanese universities?
Authors: Chen Lilan 
Published: February 2024

AbstractDespite challenging and uncertain circumstances and the perception of being tokenized symbols in Japanese universities, the majority of international academics are more inclined to remain in their affiliations. The study intends to elucidate how international academics make sense of their decision to remain in Japanese universities. The data are from a qualitative dataset examining the integration experiences of international academics in Japan. Following the philosophical foundations of purposive sampling in interpretative phenomenological analysis (IPA), which was applied as a methodological framework, the study recruited a total of 30 participants. The study reveals varied sensemaking strategies among the interviewees, characterized as survivors, pragmatists, and ambitionists. Survivors refer to those who were compelled to remain in their current affiliations often due to constraints related to their academic roles or age restrictions. Pragmatists prioritize the practical benefits of their positions or affiliations, deriving from professional aspects, sociocultural dimensions, and personal considerations. Ambitionist academics generally view experiences in their current affiliations as a stepping stone toward future professional opportunities elsewhere. The study suggests that insufficient dedication to recruiting and retaining international academics may pose potential long-term risks for Japanese higher education institutions (HEIs) in the global academic sphere, affecting their internationally competitive standing and resilience in an evolving academic landscape. The study provides theoretical and practical implications to researchers, university administrators, and policymakers.
Investigating the impact of vitrification on bovine ovarian tissue morphology, follicle survival, and transcriptomic signature
Authors: Deligiannis Spyridon P. , Kask Keiu , Modhukur Vijayachitra , Boskovic Nina , Ivask Marilin , Jaakma Ülle , Damdimopoulou Pauliina , Tuuri Timo , Velthut-Meikas Agne , Salumets Andres 
Published: February 2024

Abstract
Purpose
Ovarian tissue cryopreservation is vital for fertility preservation, yet its effect on ovarian tissue follicle survival and transcriptomic signature requires further investigation. This study delves into the effects of vitrification on tissue morphology, function, and transcriptomic changes, helping to find possibilities for vitrification protocol improvements.

Methods
Ovarian cortex from 19 bovine animals were used to conduct pre- and post-vitrification culture followed by histological assessment, immunohistochemistry, and TUNEL assay. Follicles’ functionality was assessed for viability and growth within the tissue and in isolated cultures. RNA-sequencing of ovarian tissue was used to explore the transcriptomic alterations caused by vitrification.

Results
Follicle density, cell proliferation, and DNA damage in ovarian stroma were unaffected by vitrification. However, vitrified cultured tissue exhibited reduced follicle density of primordial/primary and antral follicles, while freshly cultured tissue manifested reduction of antral follicles. Increased stromal cell proliferation and DNA damage occurred in both groups post-culture. Isolated follicles from vitrified tissue exhibited similar viability to fresh follicles until day 4, after which the survival dropped. RNA-sequencing revealed minor effects of vitrification on transcriptomic signatures, while culture induced significant gene expression changes in both groups. The altered expression of WNT and hormonal regulation pathway genes post-vitrification suggests the molecular targets for vitrification protocol refinement.

Conclusion
Vitrification minimally affects tissue morphology, follicle density, and transcriptomic signature post-thawing. However, culture revealed notable changes in vitrified tissue samples, including reduced follicle density, decreased isolated follicle survival, and alteration in WNT signalling and ovarian hormonal regulation pathways, highlighted them as possible limitations of the current vitrification protocol.
Control of the PVTOL with Strong Input Coupling
Authors: Lozano Rogelio , Eulopa-Hernandez Jhonatan F , Salazar-Cruz Sergio 
Published: February 2024

AbstractThis paper studies the modeling and control of a Planar Vertical Take-Off and Landing (PVTOL) with steerable thruster. A longitudinal model is obtained using Newton’s second law for the PVTOL which evolves in 3 degrees of freedom and has two control inputs. The aerial vehicle is driven by steerable propulsion controlling its evolution in the vertical plane through the thrust and torque control inputs, which drive the vehicle body and generate a rotation. The obtained model is nonlinear and is significantly different with respect to the well-known PVTOL. For this reason, different control algorithms are presented, and the closed-loop behavior is studied for each of them. The proposed control strategies perform a stationary flight at a desired altitude and control the position of the aerial vehicle. The performance of the proposed control algorithms is tested in numerical simulations.
Exploring User Perceptions of a Mobile App for Religious Practices
Authors: Laird Breanne , Van Tongeren Daryl R. , Hook Joshua N. , Do Bridgette , Hall Todd , Huberty Jennifer 
Published: February 2024

AbstractThe purpose of this study was to explore the usage patterns of USA subscribers of an online religious/spiritual application (i.e., app; Pray.com) and the associations of app usage with physical health, mental health, spiritual health, and well-being outcomes. A total of 1031 subscribers participated in the survey about their engagement with the Pray.com app. Most of the respondents had been using the app between one and two years, and more than half were high-frequency users. Although many individuals engaged with the app experienced spiritual growth, many also reported retrospective improvement in mental and physical health. This research serves as an initial examination of how religious-based apps may be associated with self-reported improvements in physical, mental, and spiritual health outcomes.
Study of phosphate sorption on rendzina soil by heterogeneous isotopic exchange: a biexponential kinetic model
Authors: Vörös János Z. , Kónya József , Nagy Noémi M. 
Published: February 2024

Abstract
Phosphate sorption on rendzina soil was studied by P-32 heterogeneous isotopic exchange under a steady-state. There are two types of sorbed phosphate, namely strongly and weakly bonded phosphate, the latter being able to exchange with phosphate (H232PO4−) ions in the soil solution. The experimental kinetic data was not fitted by the one exponential kinetic model. Starting from this observation, a new kinetic model is established by assuming two types of weakly bonded phosphate, which take part in the two parallel exchange processes. A biexponential kinetic equation is obtained, which fits the experimental data much better than the one exponential equation.

Graphical abstract
GREEN PATH: an expert system for space planning and design by the generation of human trajectories
Authors: Paolanti Marina , Manco Davide , Pietrini Rocco , Frontoni Emanuele 
Published: February 2024

AbstractPublic space is usually conceived as where people live, perceive, and interact with other people. The environment affects people in several different ways as well. The impact of environmental problems on humans is significant, affecting all human activities, including health and socio-economic development. Thus, there is a need to rethink how space is used. Dealing with the important needs raised by climate emergency, pandemic and digitization, the contributions of this paper consist in the creation of opportunities for developing generative approaches to space design and utilization. It is proposed GREEN PATH, an intelligent expert system for space planning. GREEN PATH uses human trajectories and deep learning methods to analyse and understand human behaviour for offering insights to layout designers. In particular, a Generative Adversarial Imitation Learning (GAIL) framework hybridised with classical reinforcement learning methods is proposed. An example of the classical reinforcement learning method used is continuous penalties, which allow us to model the shape of the trajectories and insert a bias, which is necessary for the generation, into the training. The structure of the framework and the formalisation of the problem to be solved allow for the evaluation of the results in terms of generation and prediction. The use case is a chosen retail domain that will serve as a demonstrator for optimising the layout environment and improving the shopping experience. Experiments were assessed on shoppers’ trajectories obtained from four different stores, considering two years.
Spectro Temporal Fusion with CLSTM-Autoencoder based approach for Anomalous Sound Detection
Authors: Chandrakala S. , Pidikiti Akhilandeswari , Sai Mahathi P. V. N. 
Published: February 2024

AbstractDeep learning models are proved efficient for complex learning tasks. Anomalous sound detection is one such complex task for which self-supervised deep architectures are emerging in recent days. Self-supervised deep models efficiently capture the underlying structure of data. Self-supervised anomalous sound detection attempts to distinguish between normal sounds and unidentified anomalous sounds. With the use of appropriate autoencoders, reconstruction error based decision making is effective for anomaly detection in domains such as computer vision. Auditory image (Spectrogram) based representation of sound signals are commonly used in sound event detection. We propose convolutional long short-term memory (CLSTM) Auto Encoder based approach for anomalous sound detection. In this approach, we explore fusion of spectral and temporal features to model characteristics of normal sounds with noises. The proposed approach is evaluated using MIMII dataset and the DCASE Challenge (2020) Task 2—Anomalous sound detection dataset. Experiments on proposed approach reveal significant improvement over the state-of-the-art approaches.
Exponential Stability of Stochastic Time-Delay Neural Networks with Random Delayed Impulses
Authors: Huang Yueli , Wu Ailong , Zhang Jin-E 
Published: February 2024

AbstractThe mean square exponential stability of stochastic time-delay neural networks (STDNNs) with random delayed impulses (RDIs) is addressed in this paper. Focusing on the variable delays in impulses, the notion of average random delay is adopted to consider these delays as a whole, and the stability criterion of STDNNs with RDIs is developed by using stochastic analysis idea and the Lyapunov method. Taking into account the impulsive effect, interference function and stabilization function of delayed impulses are explored independently. The results demonstrate that delayed impulses with random properties take a crucial role in dynamics of STDNNs, not only making stable STDNNs unstable, but also stabilizing unstable STDNNs. Our conclusions, specifically, allow for delays in both impulsive dynamics and continuous subsystems that surpass length of impulsive interval, which alleviates certain severe limitations, such as presence of upper bound for impulsive delays or requirement that impulsive delays can only exist between two impulsive events. Finally, feasibility of the theoretical results is verified through three simulation examples.
Synthetic Hard Negative Samples for Contrastive Learning
Authors: Dong Hengkui , Long Xianzhong , Li Yun 
Published: February 2024

AbstractContrastive learning has emerged as an essential approach in self-supervised visual representation learning. Its main goal is to maximize the similarities between augmented versions of the same image (positive pairs), while minimizing the similarities between different images (negative pairs). Recent studies have demonstrated that harder negative samples, i.e., those that are more challenging to differentiate from the anchor sample perform a more crucial function in contrastive learning. However, many existing contrastive learning methods ignore the role of hard negative samples. In order to provide harder negative samples for the network model more efficiently. This paper proposes a novel feature-level sample sampling method, namely sampling synthetic hard negative samples for contrastive learning (SSCL). Specifically, we generate more and harder negative samples by mixing them through linear combination and ensure their reliability by debiasing. Finally, we execute weighted sampling of these negative samples. Compared to state-of-the-art methods, our method can provide more high-quality negative samples. Experiments show that SSCL improves the classification performance on different image datasets and can be readily integrated into existing methods.
The Multifaceted Impact of Erasmus Programme on the School-to-Work Transition: A Matching Sensitivity Analysis
Authors: Croce Giuseppe , Ghignoni Emanuela 
Published: February 2024

AbstractThis study investigates the effects of studying abroad through the Erasmus Programme (EP), a European Union programme launched primarily to foster international mobility and cultural exchange of University students, on the school-to-work transition of university graduates. Since a satisfactory transition does not only mean finding a job, but also concerns the wage level and the quality of work, such as stability, working hours and risk of overeducation, we consider all these aspects in order to draw a comprehensive picture of the effect of the EP. We exploit a composite dataset, built on administrative and survey data, covering all graduates from the largest Italian university from 2011 to 2015, and replicate the analysis on a national sample of graduates to verify whether the results can be extended nationwide. Estimates are provided, based on a PSM procedure, of the effects of the EP on the probability of employment, including abroad, on the quality of jobs and on wage levels at different points in time after graduation. We also investigate whether less advantaged students benefit from the Erasmus experience, and provide insights about the role of the foreign languages skills. The results show that the participation in the EP improves employment prospects at least in the short term, as well as the quality of job, and has a positive long term effect on the participants' ability to find a job abroad. The wages of participants are persistently higher than those of non-participants. Less advantaged groups also benefit from the Erasmus experience.
Can ChatGPT be used to predict citation counts, readership, and social media interaction? An exploration among 2222 scientific abstracts
Authors: de Winter Joost 
Published: February 2024

AbstractThis study explores the potential of ChatGPT, a large language model, in scientometrics by assessing its ability to predict citation counts, Mendeley readers, and social media engagement. In this study, 2222 abstracts from PLOS ONE articles published during the initial months of 2022 were analyzed using ChatGPT-4, which used a set of 60 criteria to assess each abstract. Using a principal component analysis, three components were identified: Quality and Reliability, Accessibility and Understandability, and Novelty and Engagement. The Accessibility and Understandability of the abstracts correlated with higher Mendeley readership, while Novelty and Engagement and Accessibility and Understandability were linked to citation counts (Dimensions, Scopus, Google Scholar) and social media attention. Quality and Reliability showed minimal correlation with citation and altmetrics outcomes. Finally, it was found that the predictive correlations of ChatGPT-based assessments surpassed traditional readability metrics. The findings highlight the potential of large language models in scientometrics and possibly pave the way for AI-assisted peer review.
On the scalability of the speedup considering the overhead of consolidating virtual machines in servers for data centers
Authors: Juiz Carlos , Bermejo Belen 
Published: February 2024

AbstractVirtualization technologies are extensively utilized in data centers, particularly cloud computing. This facilitates data center management and diminishes the number of physical machines (servers) and, subsequently, their cooling requirements, leading to cost, space, and power consumption reductions. When applications in data centers are executing independent parallel transactions, but with similar performance requirements, the appropriate level of virtual machine consolidation on a server poses a fundamental challenge for capacity planning. This article introduces a method to evaluate the performance speedup achieved through virtualization on any server and the effects of virtualization and consolidation overheads on physical or virtual machine scalability. This research formalizes the speedup and overheads, using classical computer architecture statements. but at the same time proposes a new method to analyze these overhead amounts and types, showing the scalability and efficiency of different consolidations in the same server and its comparison against no consolidation. This work also proposes a new way to determine the optimal number of physical servers and the optimal number of consolidated virtual machines for a given transaction workload. The real experimentation was performed with different workload sizes, types of virtualizations and different servers. The method presented also facilitates the representation of linear scalability against the real degree of parallelism of either physical machines or consolidated virtual machines for a given transaction workload, as well as striking the right balance between speedup and energy in virtual server consolidation.
Effect of three different insect larvae on growth performance and antioxidant activity of thigh, breast, and liver tissues of chickens reared under mild heat stress
Authors: Stelios Vasilopoulos , Ilias Giannenas , Ioannis Panitsidis , Christos Athanassiou , Elias Papadopoulos , Paschalis Fortomaris 
Published: February 2024

AbstractThis study investigated the potential of insect-based diets to mitigate heat stress impact on broiler chickens, focusing on growth performance and antioxidant stability. Four dietary groups were examined, including a control and three treated groups with Tenebrio molitor (TM), Hermetia illucens (HI), and Zophobas morio (ZM) larvae, respectively, at a 5% replacement ratio. Temperature and relative humidity of the poultry house were monitored. Under heat stress conditions, the HI-fed group consistently exhibited the highest body weight, demonstrating their remarkable growth-promoting potential. TM-fed broilers also displayed commendable growth compared to the control. Insect larvae inclusion in the diet improved feed intake during early growth stages, indicating their positive influence on nutrient utilization. Regarding antioxidant stability, malondialdehyde (MDA) levels in the liver, an oxidative stress and lipid peroxidation marker, were significantly lower in the TM-fed group, suggesting reduced oxidative stress. While the specific insect-based diet did not significantly affect MDA levels in thigh and breast tissues, variations in the total phenolic content (TPC) were observed across tissues, with HI larvae significantly increasing it in the breast. However, the total antioxidant capacity (TAC) and 2,2-diphenyl-1-picrylhydrazyl (DPPH) levels did not differ significantly among dietary groups in the examined tissues. Results suggest that insect-based diets enhance broiler growth and potentially reduce oxidative stress, particularly in the liver. Dietary presence of bioactive compounds may contribute to these benefits. Further research is required to fully elucidate the mechanisms underlying these findings. Insect-based diets seem to offer promise as feed additives in addressing the multifaceted challenges of oxidative stress and enhancing broiler health and resilience under heat stress conditions.