bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Progress in Molecular Transport and Therapeutic Development in Human Blood–Brain Barrier Models in Neurological Disorders
Authors: Korszun-Karbowniczak Joanna , Krysiak Zuzanna Joanna , Saluk Joanna , Niemcewicz Marcin , Zdanowski Robert 
Published: April 2024

AbstractThe blood–brain barrier (BBB) is responsible for maintaining homeostasis within the central nervous system (CNS). Depending on its permeability, certain substances can penetrate the brain, while others are restricted in their passage. Therefore, the knowledge about BBB structure and function is essential for understanding physiological and pathological brain processes. Consequently, the functional models can serve as a key to help reveal this unknown. There are many in vitro models available to study molecular mechanisms that occur in the barrier. Brain endothelial cells grown in culture are commonly used to modeling the BBB. Current BBB platforms include: monolayer platforms, transwell, matrigel, spheroidal, and tissue-on-chip models. In this paper, the BBB structure, molecular characteristic, as well as its dysfunctions as a consequence of aging, neurodegeneration, or under hypoxia and neurotoxic conditions are presented. Furthermore, the current modelling strategies that can be used to study BBB for the purpose of further drugs development that may reach CNS are also described.
Cepair: an AI-powered and fog-based predictive CEP system for air quality monitoring
Authors: Şimsek Mehmet Ulvi , Kök İbrahim , Özdemir Suat 
Published: April 2024

AbstractAir pollution is one of the influential problems threatening the environment and human health today. Therefore, it is critical to develop predictive systems for proactive decisions in solving this problem. Since the prediction of air pollution depends on several complicated factors such as the accuracy of meteorology reports, air pollution accumulation, traffic flow, and industrial emissions, the contribution of historical or real-time predictions to the solution of the problem is limited. To address the existing limitations, we propose a novel AI-powered and Fog-based predictive complex event processing system (CepAIr) for the prediction of future air pollution rates. CepAIr predicts the future air quality of pollutant gases using RNN, LSTM, CNN, and SVR models. Then, it sends the prediction results to decision-makers in an understandable format, enabling them to take proactive actions. Finally, we evaluate the performance of the CepAIr with SVR and DL models. Additionally, we examine CepAIr in terms of end-to-end network delay and measure its impact on the network. The extensive simulation results demonstrate that the CepAIr predicts future pollutant gas concentrations with DL models (especially with CNN) with a high success rate while guaranteeing minimum end-to-end network delay.
Securing internet of things using machine and deep learning methods: a survey
Authors: Ghaffari Ali , Jelodari Nasim , pouralish Samira , derakhshanfard Nahide , Arasteh Bahman 
Published: April 2024

AbstractThe Internet of Things (IoT) is a vast network of devices with sensors or actuators connected through wired or wireless networks. It has a transformative effect on integrating technology into people’s daily lives. IoT covers essential areas such as smart cities, smart homes, and health-based industries. However, security and privacy challenges arise with the rapid growth of IoT devices and applications. Vulnerabilities such as node spoofing, unauthorized access to data, and cyberattacks such as denial of service (DoS), eavesdropping, and intrusion detection have emerged as significant concerns. Recently, machine learning (ML) and deep learning (DL) methods have significantly progressed and are robust solutions to address these security issues in IoT devices. This paper comprehensively reviews IoT security research focusing on ML/DL approaches. It also categorizes recent studies on security issues based on ML/DL solutions and highlights their opportunities, advantages, and limitations. These insights provide potential directions for future research challenges.
Fast decoding of lifted interleaved linearized Reed–Solomon codes for multishot network coding
Authors: Bartz Hannes , Puchinger Sven 
Published: April 2024

AbstractMartínez-Peñas and Kschischang (IEEE Trans. Inf. Theory 65(8):4785–4803, 2019) proposed lifted linearized Reed–Solomon codes as suitable codes for error control in multishot network coding. We show how to construct and decode lifted interleaved linearized Reed–Solomon (LILRS) codes. Compared to the construction by Martínez-Peñas–Kschischang, interleaving allows to increase the decoding region significantly and decreases the overhead due to the lifting (i.e., increases the code rate), at the cost of an increased packet size. We propose two decoding schemes for LILRS that are both capable of correcting insertions and deletions beyond half the minimum distance of the code by either allowing a list or a small decoding failure probability. We propose a probabilistic unique Loidreau–Overbeck-like decoder for LILRS codes and an efficient interpolation-based decoding scheme that can be either used as a list decoder (with exponential worst-case list size) or as a probabilistic unique decoder. We derive upper bounds on the decoding failure probability of the probabilistic-unique decoders which show that the decoding failure probability is very small for most channel realizations up to the maximal decoding radius. The tightness of the bounds is verified by Monte Carlo simulations.
Plant invasion alters movement behaviour in endangered butterflies but not their morphology or genetic variability
Authors: Kajzer-Bonk Joanna , Śliwińska Ewa B. , Malik Kamila 
Published: April 2024

AbstractInvasions of alien plants often result in biodiversity loss and may impact the biology of native species. However, the effects of biological invasions on the behavioural responses of native species have rarely been investigated. We studied how the alteration of habitat due to the invasion of alien goldenrod (Solidago spp) affects a native butterfly, the scarce large blue Phengaris teleius, which is a flagship species for grassland biodiversity conservation. To better understand immediate responses in flight behaviour (daily movements, resting, and dispersal) to a new habitat, we performed observations of experimentally translocated butterflies of two origins (invaded vs. non-invaded habitats) to four different environments: invaded habitat, non-invaded habitat, invaded matrix, non-invaded matrix. Moreover, we tested whether the level of invasion may be related to the variation in morphological traits associated with flight (wing size, body mass) and genetic variability. Flight behaviour was affected by the high goldenrod cover and the sex of the butterflies, regardless of the butterflies’ origin. In the habitat and matrix invaded by goldenrod, the butterflies tended to display dispersal behaviour more often compared to the non-invaded ones. Flight distances were longest in the matrix with goldenrod and resting time was longest in habitats invaded by goldenrod. Analysis of morphological traits as well as eight microsatellite loci did not reveal significant differences in morphology or genetic variation among the populations studied.
Discovering Psychological Well-Being: A Bibliometric Review
Authors: Yiğit Busra , Çakmak Bünyamin Yasin 
Published: April 2024

AbstractPsychological well-being is among the concepts that have attracted significant attention from researchers in the fields of social life, work life, and health in recent years. We conducted bibliometric mapping and content analysis to reveal current trends in the concept and contribute to the literature. Using VOSviewer, Citespace, Bibliometrix and MS Office Excel programs, we analysed 16,885 academic studies published in the Web of Science database between 1980 and 2022. The research results show a continuous increase in publications and citations, with a notable surge observed after 2016. The United States accounts for over a third of the publications. Furthermore, the International Journal of Environment Research and Public Health and Frontiers in Psychology stand out as the most productive journals, whereas Carol D. Ryff is the most prolific and cited author in the field. When the footprints of the keywords over the past 10 years are interpreted, some notable trends are identified. Initially, research themes mainly revolved around children, dementia, and social support. However, with the COVID-19 pandemic emerging as a new thematic focus and the disruption of the person-job and person-environment order due to the repercussions of lockdowns, the emphasis has shifted from the theme of social support to mindfulness, loneliness, and support. Notably, motivation and rehabilitation have emerged as significant focal points, with increased attention on social isolation and healthcare workers in recent publications.
SampleHST-X: A Point and Collective Anomaly-Aware Trace Sampling Pipeline with Approximate Half Space Trees
Authors: Gias Alim Ul , Gao Yicheng , Sheldon Matthew , Perusquía José A. , O’Brien Owen , Casale Giuliano 
Published: April 2024

AbstractThe storage requirement for distributed tracing can be reduced significantly by sampling only the anomalous or interesting traces that occur rarely at runtime. In this paper, we introduce an unsupervised sampling pipeline for distributed tracing that ensures high sampling accuracy while reducing the storage requirement. The proposed method, SampleHST-X, extends our recent work SampleHST. It operates based on a budget which limits the percentage of traces to be sampled while adjusting the storage quota of normal and anomalous traces depending on the size of this budget. The sampling process relies on accurately defining clusters of normal and anomalous traces by leveraging the distribution of mass scores, which characterize the probability of observing different traces, obtained from a forest of Half Space Trees (HST). In our experiments, using traces from a cloud data center, SampleHST yields 2.3$$\times$$×to 9.5$$\times$$×better sampling performance. SampleHST-X further extends the SampleHST approach by incorporating a novel class of Half Space Trees, namely Approximate HST, that uses approximate counters to update the mass scores. These counters significantly reduces the space requirement for HST while the sampling performance remains similar. In addition to this extension, SampleHST-X includes a Family of Graph Spectral Distances (FGSD) based trace characterization component, which, in addition to point anomalies, enables it to sample traces with collective anomalies. For such traces, we observe that the SampleHST-X approach can yield 1.2$$\times$$×to 19$$\times$$×better sampling performance.
The Role of the Law in Critical Theory: An Engagement with Hardt and Negri’s Commonwealth
Authors: Xifaras Mikhaïl 
Published: April 2024

AbstractThis paper discusses the role of Law and Legal Thinking in Critical Theory with specific reference to the arguments that Michael Hardt and Antonio Negri offer in their book Commonwealth. The core idea is that Critical Theory is no less radical, but much more concrete, when it is performing not only an external, but also an internal critique of the Law. It shows that the role of the law in critical theory emerges as a problem when the latter claims that ‘there is no outside’ and that ‘the legal base of the system structures our lives.’ It then discusses optimistic and pessimistic strategies to overcome the problem, and argue for a demanding strategy which consist in articulating the external and the internal critique of the law. To make this point, the paper goes back to the epistemic context in which critical attitudes are deployed (the ‘Conflict of the Faculties’), describes the four theoretical moves constitutive of the historical moment in which, at the end of the 18th Century, modern law as we know it was conceived of and founded; and sketches the key moments of the history of the internal critique of the law. It then illustrates the demanding strategy with examples taken from the field of Intellectual Property, and concludes that the Law is malleable and open enough to allow the thinking and practicing of radical alternatives from within the legal system and also that alternatives spoken in the language of the law are no less radical, but certainly, more concrete than others.
A Cyclic Random Motion in $$\mathbb {R}^3$$ Driven by Geometric Counting Processes
Authors: Iuliano Antonella , Verasani Gabriella 
Published: April 2024

AbstractWe consider the random motion of a particle that moves with constant velocity in $$\mathbb {R}^3$$

R

3

. The particle can move along four different directions that are attained cyclically. It follows that the support of the stochastic process describing the particle’s position at a fixed time is a tetrahedron. We assume that the sequence of sojourn times along each direction follows a Geometric Counting Process (GCP). When the initial condition is fixed, we obtain the explicit form of the probability law of the process, for the particle’s position. We also investigate the limiting behavior of the related probability density when the intensities of the four GCPs tend to infinity. Furthermore, we show that the process does not admit a stationary density. Finally, we introduce the first-passage-time problem for the first component of the process through a constant positive boundary providing the bases for future developments.
Clinical Characteristics and Pathogen Spectrum of Male Genital Fungal Infections in Nanchang Area, South China
Authors: Jin Yun , Gao Yangmin , Luo Yunpeng , Tao XiaoHua , Jiang Qing , Fan Xinyi , Xu Rui , Qian Hua , Li Xiaoguang , Zhou Zhijun 
Published: April 2024

AbstractThe cutaneous fungal infections in male genitalia are relatively rare, and often present with various atypical clinical symptoms. It was mainly reported in a small number of case reports, while data with large number of patients were rarely reported. In this study, we reported 79 male patients with cutaneous fungal infections on scrotum or penis. The fungal infections were confirmed by microscopic examination directly and fungus culture. Clinical characteristics and predisposing factors were also collected. Of these 79 patients, 72 has lesions on scrotum, 5 on penis and 2 on both scrotum and penis. Trichophyton (T.) rubrum is the most common pathogen, found in 50 (67.6%) patients, which presented diverse clinical manifestation such as majorly erythematous, dry diffused scaly lesions without a clear border, slightly powdery and scutular scalings. Candida (C.) albicans is the secondly common pathogen, found in 21 (28.4%) patients, which also presented diverse lesions such as erythematous with dry whitish scaly lesions and erythematous erosion. The predisposing factors mainly included concomitant fungal infections on sites other than genitalia, especially inguinal region (tinea cruris), application of corticosteroid and high moisture. In conclusion, cutaneous fungal infections in male genitalia could be caused by different fungi, showed atypical or mild clinical appearances in most cases and might be a fungus reservoir, emphasizing the necessity to timely perform the fungi examinations and corresponding therapy.
Plant-derived bioactive compounds as key players in the modulation of immune-related conditions
Authors: Vieira Sara F. , Reis Rui L. , Ferreira Helena , Neves Nuno M. 
Published: April 2024

Abstract
The immune system is a complex and fundamental network for organism protection. A minimal unbalance in the host defense system homeostasis can originate severe repercussions in human health. Fundamentally, immune-related diseases can arise from its compromise (immunodeficiency diseases), overactivation against itself (autoimmune diseases) or harmless substances (allergies), and failure of eliminating the harmful agent (chronic inflammation). The notable advances and achievements in the immune system diseases pathophysiology have been allowing for a dramatic improvement of the available treatments. Nevertheless, they present some drawbacks, including the inappropriate benefit/risk ratio. Therefore, there is a strong and urgent need to develop effective therapeutic strategies. Nature is a valuable source of bioactive compounds that can be explored for the development of new drugs. Particularly, plants produce a broad spectrum of secondary metabolites that can be potential prototypes for innovative therapeutic agents. This review describes the immune system and the inflammatory response and examines the current knowledge of eight plants traditionally used as immunomodulatory medicines (Boswellia serrata, Echinacea purpurea, Laurus nobilis, Lavandula angustifolia, Olea europaea, Salvia officinalis, Salvia rosmarinus, and Taraxacum officinale). Moreover, the issues responsible for possible biologic readout inconsistencies (plant species, age, selected organ, developmental stage, growth conditions, geographical location, drying methods, storage conditions, solvent of extraction, and extraction method) will also be discussed. Furthermore, a detailed list of the chemical composition and the immunomodulatory mechanism of action of the bioactive compounds of the selected plant extracts are presented. This review also includes future perspectives and proposes potential new avenues for further investigation.
A computer vision system for apple fruit sizing by means of low-cost depth camera and neural network application
Authors: Bortolotti G. , Piani M. , Gullino M. , Mengoli D. , Franceschini C. , Grappadelli L. Corelli , Manfrini L. 
Published: April 2024

AbstractFruit size is crucial for growers as it influences consumer willingness to buy and the price of the fruit. Fruit size and growth along the seasons are two parameters that can lead to more precise orchard management favoring production sustainability. In this study, a Python-based computer vision system (CVS) for sizing apples directly on the tree was developed to ease fruit sizing tasks. The system is made of a consumer-grade depth camera and was tested at two distances among 17 timings throughout the season, in a Fuji apple orchard. The CVS exploited a specifically trained YOLOv5 detection algorithm, a circle detection algorithm, and a trigonometric approach based on depth information to size the fruits. Comparisons with standard-trained YOLOv5 models and with spherical objects were carried out. The algorithm showed good fruit detection and circle detection performance, with a sizing rate of 92%. Good correlations (r > 0.8) between estimated and actual fruit size were found. The sizing performance showed an overall mean error (mE) and RMSE of + 5.7 mm (9%) and 10 mm (15%). The best results of mE were always found at 1.0 m, compared to 1.5 m. Key factors for the presented methodology were: the fruit detectors customization; the HoughCircle parameters adaptability to object size, camera distance, and color; and the issue of field natural illumination. The study also highlighted the uncertainty of human operators in the reference data collection (5–6%) and the effect of random subsampling on the statistical analysis of fruit size estimation. Despite the high error values, the CVS shows potential for fruit sizing at the orchard scale. Future research will focus on improving and testing the CVS on a large scale, as well as investigating other image analysis methods and the ability to estimate fruit growth.
The Importance of Contrary Forces in Education: On the Notion of Conflict in Tagore’s Religion of Man
Authors: Pouwels Jan G. 
Published: April 2024

AbstractDealing with conflicts seems to be a great challenge in society today. But not only in society. Higher education displays an air of resoluteness with certainty and security that disguises the conflicts and the fear of conflicts in a substantial number of subjects. If not in a state of denial, higher education avoids taking up conflicts over issues, for learning. The detailed investigation of Tagore’s pedagogical writings, with a focus on the importance of conflicts in education, reveals a genuine embrace of conflicts for education. Conflicts are natural and necessary for the development and change of both the individual and society and the start of a ‘creative imagination’ to solve the problems we face in life. Contradictions in conflicts are not incompatible incongruities that are irreconcilable and mutually exclusive, but to the contrary, in need of each other. Contradictions do not represent different worlds but are substantial parts of one world: together they form a unity. Conflicting forces are necessary to create harmony. Creativity, imagination, love, art, and critical encounters are key elements in Tagore’s practical education aimed at finding similarities among people instead of emphasizing differences. Relations between people over the Identity of people. In other words, we need conflicts to become creative and imaginative human beings. The paper continues discussing conceptual and practical issues that seem necessary to get the teaching of conflicts in education off the ground. On the conceptual level, in particular our dealing with uncertainty and fear, the valuation of conflict and the need for uncertainty-researching education. On a practical level, I propose a certain teaching model, a supportive curriculum, a way of choosing genuine conflicts for education and finally, I argue for specific support and education of teachers, acknowledging the vital role teachers play in delivering the education that we need.
A flexible Bayesian tool for CoDa mixed models: logistic-normal distribution with Dirichlet covariance
Authors: Martínez-Minaya Joaquín , Rue Haavard 
Published: April 2024

AbstractCompositional Data Analysis (CoDa) has gained popularity in recent years. This type of data consists of values from disjoint categories that sum up to a constant. Both Dirichlet regression and logistic-normal regression have become popular as CoDa analysis methods. However, fitting this kind of multivariate models presents challenges, especially when structured random effects are included in the model, such as temporal or spatial effects. To overcome these challenges, we propose the logistic-normal Dirichlet Model (LNDM). We seamlessly incorporate this approach into the R-INLA package, facilitating model fitting and model prediction within the framework of Latent Gaussian Models. Moreover, we explore metrics like Deviance Information Criteria, Watanabe Akaike information criterion, and cross-validation measure conditional predictive ordinate for model selection in R-INLA for CoDa. Illustrating LNDM through two simulated examples and with an ecological case study on Arabidopsis thaliana in the Iberian Peninsula, we underscore its potential as an effective tool for managing CoDa and large CoDa databases.
Reconstruction pattern of the cell wall in Fagopyrum protoplast-derived hybrid cells
Authors: Sala-Cholewa Katarzyna , Milewska-Hendel Anna , Pérez-Pérez Reneé , Grzebelus Ewa , Betekhtin Alexander 
Published: April 2024

AbstractThe cell wall rebuilding is one of the first stage of protoplast development that enables further mitotic divisions and differentiation. Therefore, this work focuses on the comparison of the cell wall regeneration in the parental protoplasts of Fagopyrum tataricum, F. esculentum and the F. tataricum (+) F. esculentum hybrids, which are promising materials in terms of future breeding and research programmes. It is worth emphasizing that the preparation of buckwheat hybrids using electrofusion was described for the first time. The results indicate that cell wall rebuilding exhibited a common mechanism for parent protoplasts and the heterokaryon as all analysed cell wall components recognising arabinogalactan proteins (JIM13, JIM16), extensin (JIM20), xyloglucan (LM25) and pectins (LM20, LM5, LM6) were detected during the process of wall regeneration. However, there were certainly differences in the spatio-temporal appearance or disappearance of individual epitopes during the 72 h of the cell culture, which have been discussed in the paper.