bluuebunny/crossref_metadata_2025_split huggingface dataset:
Breaking the data barrier: a review of deep learning techniques for democratizing AI with small datasets
Authors: Rather Ishfaq Hussain , Kumar Sushil , Gandomi Amir H. 
Published: August 2024

AbstractJustifiably, while big data is the primary interest of research and public discourse, it is essential to acknowledge that small data remains prevalent. The same technological and societal forces that generate big datasets also produce a more significant number of small datasets. Contrary to the notion that more data is inherently superior, real-world constraints such as budget limitations and increased analytical complexity present critical challenges. Quality versus quantity trade-offs necessitate strategic decision-making, where small data often leads to quicker, more accurate, and cost-effective insights. Concentrating AI research, particularly in deep learning (DL), on big datasets exacerbates AI inequality, as tech giants such as Meta, Amazon, Apple, Netflix and Google (MAANG) can easily lead AI research due to their access to vast datasets, creating a barrier for small and mid-sized enterprises that lack similar access. This article addresses this imbalance by exploring DL techniques optimized for small datasets, offering a comprehensive review of historic and state-of-the-art DL models developed specifically for small datasets. This study aims to highlight the feasibility and benefits of these approaches, promoting a more inclusive and equitable AI landscape. Through a PRISMA-based literature search, 175+ relevant articles are identified and subsequently analysed based on various attributes, such as publisher, country, utilization of small dataset technique, dataset size, and performance. This article also delves into current DL models and highlights open research problems, offering recommendations for future investigations. Additionally, the article highlights the importance of developing DL models that effectively utilize small datasets, particularly in domains where data acquisition is difficult and expensive.
Interplay between neutrino kicks and hydrodynamic kicks of neutron stars and black holes
Authors: Janka Hans-Thomas , Kresse Daniel 
Published: August 2024

AbstractNeutron stars (NSs) are observed with high space velocities and elliptical orbits in binaries. The magnitude of these effects points to natal kicks that originate from asymmetries during the supernova (SN) explosions. Using a growing set of long-time 3D SN simulations with the Prometheus-Vertex code, we explore the interplay of NS kicks that are induced by asymmetric neutrino emission and by asymmetric mass ejection. Anisotropic neutrino emission can arise from a large-amplitude dipolar convection asymmetry inside the proto-NS (PNS) termed LESA (Lepton-number Emission Self-sustained Asymmetry) and from aspherical accretion downflows around the PNS, which can lead to anisotropic neutrino emission (absorption/scattering) with a neutrino-induced NS kick roughly opposite to (aligned with) the kick by asymmetric mass ejection. In massive progenitors, hydrodynamic kicks can reach up to more than 1300 km s−1, whereas our calculated neutrino kicks reach (55–140) km s−1 (estimated upper bounds of (170–265) km s−1) and only ∼(10–50) km s−1, if LESA is the main cause of asymmetric neutrino emission. Therefore, hydrodynamic NS kicks dominate in explosions of high-mass progenitors, whereas LESA-induced neutrino kicks dominate for NSs born in low-energy SNe of the lowest-mass progenitors, when these explode nearly spherically. Our models suggest that the Crab pulsar with its velocity of ∼160 km s−1, if born in the low-energy explosion of a low-mass, single-star progenitor, should have received a hydrodynamic kick in a considerably asymmetric explosion. Black holes, if formed by the collapse of short-lived PNSs and solely kicked by anisotropic neutrino emission, obtain velocities of only some km s−1.
Thermal performance of native and invasive crab species: investigating the invasion potential of Hemigrapsus takanoi in southern European Carcinus maenas’ habitats
Authors: Rato L. D. , Simões T. , Novais S. C. , Damasceno J. M. , Van der Meer J. , Thieltges D. W. , Marques J. C. , Lemos M. F. L. 
Published: August 2024

AbstractInvasive species’ plasticity and latitudinal spread have become an increasing matter of concern in rapidly changing climate. The brush-clawed shore crab (Hemigrapsus takanoi), native along northwestern Pacific shores, has established dense populations in northern European coasts. Detrimental effects in natura have been reported, such as displacement of native species and competition for shelter, rasing concerns regarding shellfish early life stages and food webs-posing a threat to wild stocks’ recruitment and aquaculture. The species has not yet been observed in southern European countries (e.g., Portugal), where niche habitats such as harbours, mudflats, and lagoons reach higher temperatures than the invaded northern range. The aims of this study were to determine H. takanoi potential to acclimate to a southern thermal range, assess thermal performance, and identify potential competitive advantages over the native shore crab Carcinus maenas. This was accomplished through individual exposure to one of three treatments, resembling a southern European thermal range (17 °C, 21 °C, or 25 °C), for 30 days. H. takanoi thrived in temperatures as high as 25 °C, a realistic thermal scenario in Óbidos Lagoon (the biggest Portuguese lagoon)—while the native shore crab C. maenas underperformed at that treatment, showing lower survival, growth, and feed intake than H. takanoi. These results suggest that H. takanoi may be able to colonise southern and warmer European locations and have higher plasticity than the native species already inhabiting areas close to its upper thermal limits. Under global warming scenarios, inferences of further latitudinal spread and increased invaded range may also be taken to the invaded northern European habitats.
Influence of tumour grade on disease survival in male breast cancer patients: a systematic review
Authors: Kinsey-Trotman Stephen , Nguyen Alain , Edwards Suzanne , Swalling Adam , Dasari Pallave , Walsh David , Ingman Wendy V. 
Published: August 2024

Abstract
Purpose
Histological grading of tumours is a well-established biomarker used to guide treatment in female breast cancer. However, its significance in male breast cancer remains unclear. This systematic review investigates the prognostic significance of tumour grade in relation to breast cancer-specific survival (BCSS) in male breast cancer patients undergoing surgery.

Methods
MEDLINE, PUBMED Central and EMBASE databases were searched to identify randomised trials and observational studies related to male breast neoplasms, tumour grading, recurrence, and survival.

Results
A total of fifteen observational type studies were included in the review. A significant association between tumour grade and BCSS was reported in a majority of studies. This association was most evident with regard to high-grade (grade III) compared to low grade (grade I) tumours, with a significant relationship in 4 out of 4 studies. For intermediate-grade II tumours an association was demonstrated in a minority of studies.

Conclusions
This study confirms an association between high-grade male breast cancers and poorer disease-specific survival, however, the significance of intermediate-grade tumours remains unclear. Further research is required to investigate the biology of male breast cancer in relation to histological grade and optimally define intermediate-grade disease.
Social Impact Assessment of Corporate Social Responsibility Initiatives: Evaluating the Social Return on Investment of an Inclusion Offer
Authors: Scelles Nicolas , Inoue Yuhei , Perkin Seth Joseph , Valenti Maurizio 
Published: August 2024

AbstractThis study addresses the growing interest in the social impact assessment of corporate social responsibility (CSR) initiatives. Using the benefit (value) transfer approach, this study seeks to demonstrate how the social return on investment (SROI) of a CSR inclusion initiative promoting disability sport participation can be assessed. Literature on CSR inclusion initiatives, social impact measurement, disability sport participation and disability interventions/organizations was reviewed and compared. This helped identify the stakeholders and social outcomes to include, and the assumptions for the financial proxies and beneficiary percentages. Based on data provided by the Rugby Football League in England, an application to Inclusion Rugby League— a CSR inclusion initiative promoting disability sport participation—was then conducted. The SROI of Inclusion Rugby League is 3.39:1—a social return of £3.39 for £1 invested. Our research quantifies the positive social impact of a CSR inclusion initiative in monetary terms, providing insights for assessing SROI. This study informs future research on the social impact assessment of CSR initiatives, offering valuable guidance for organizations and their managers in making a case for further investments in CSR. Moreover, it encourages potential funders to engage in CSR initiatives.
Visual pigment chromophore usage in Nicaraguan Midas cichlids: phenotypic plasticity and genetic assimilation of cyp27c1 expression
Authors: Bertinetti César , Meyer Axel , Torres-Dowdall Julián 
Published: August 2024

AbstractThe wide-ranging photic conditions found across aquatic habitats may act as selective pressures that potentially drive the rapid evolution and diversity of the visual system in teleost fish. Teleost fish fine-tune their visual sensitivities by regulating the two components of visual pigments, the opsin protein and the chromophore. Compared with opsin protein variation, chromophore usage across photic habitats has received little attention. The Nicaraguan Midas cichlid species complex, Amphilophus cf citrinellus [Günther 1864], has independently colonized seven isolated crater lakes with different photic conditions, resulting in several recent adaptive radiations. Here, we investigate variation in cyp27c1, the main enzyme modulating chromophore exchange. We measured cyp27c1 expression in photic environments in the wild, its genetic component in laboratory-reared fish, and its response to different light conditions during development. We found that photic environments significantly predict variation in cyp27c1 expression in wild populations and that this variation seems to be genetically assimilated in two populations. Furthermore, light-induced cyp27c1 expression exhibited genotype-by-environment interactions in our manipulative experiments. Overall, within-lake variation in cyp27c1 expression was higher and inversely related to variation in opsin gene expression along the photic gradient, emphasizing the key role of cyp27c1 in the visual ecology of cichlid fish.
Gut Microbiota and Autism Spectrum Disorder: A Neuroinflammatory Mediated Mechanism of Pathogenesis?
Authors: Zarimeidani Fatemeh , Rahmati Rahem , Mostafavi Mehrnaz , Darvishi Mohammad , Khodadadi Sanaz , Mohammadi Mahya , Shamlou Farid , Bakhtiyari Salar , Alipourfard Iraj 
Published: August 2024

AbstractAutism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairments in social communication and behavior, frequently accompanied by restricted and repetitive patterns of interests or activities. The gut microbiota has been implicated in the etiology of ASD due to its impact on the bidirectional communication pathway known as the gut-brain axis. However, the precise involvement of the gut microbiota in the causation of ASD is unclear. This study critically examines recent evidence to rationalize a probable mechanism in which gut microbiota symbiosis can induce neuroinflammation through intermediator cytokines and metabolites. To develop ASD, loss of the integrity of the intestinal barrier, activation of microglia, and dysregulation of neurotransmitters are caused by neural inflammatory factors. It has emphasized the potential role of neuroinflammatory intermediates linked to gut microbiota alterations in individuals with ASD. Specifically, cytokines like brain-derived neurotrophic factor, calprotectin, eotaxin, and some metabolites and microRNAs have been considered etiological biomarkers. We have also overviewed how probiotic trials may be used as a therapeutic strategy in ASD to reestablish a healthy balance in the gut microbiota. Evidence indicates neuroinflammation induced by dysregulated gut microbiota in ASD, yet there is little clarity based on analysis of the circulating immune profile. It deems the repair of microbiota load would lower inflammatory chaos in the GI tract, correct neuroinflammatory mediators, and modulate the neurotransmitters to attenuate autism. The interaction between the gut and the brain, along with alterations in microbiota and neuroinflammatory biomarkers, serves as a foundational background for understanding the etiology, diagnosis, prognosis, and treatment of autism spectrum disorder.
Graphical Abstract
Towards Resource-Efficient DDoS Detection in IoT: Leveraging Feature Engineering of System and Network Usage Metrics
Authors: Gavric Nikola , Prasad Bhandari Guru , Shalaginov Andrii 
Published: August 2024

AbstractThe Internet of Things (IoT) is omnipresent, exposing a large number of devices that often lack security controls to the public Internet. In the modern world, many everyday processes depend on these devices, and their service outage could lead to catastrophic consequences. There are many Deep Packet Inspection (DPI) based intrusion detection systems (IDS). However, their linear computational complexity induced by the event-driven nature poses a power-demanding obstacle in resource-constrained IoT environments. In this paper, we shift away from the traditional IDS as we introduce a novel and lightweight framework, relying on a time-driven algorithm to detect Distributed Denial of Service (DDoS) attacks by employing Machine Learning (ML) algorithms leveraging the newly engineered features containing system and network utilization information. These features are periodically generated, and there are only ten of them, resulting in a low and constant algorithmic complexity. Moreover, we leverage IoT-specific patterns to detect malicious traffic as we argue that each Denial of Service (DoS) attack leaves a unique fingerprint in the proposed set of features. We construct a dataset by launching some of the most prevalent DoS attacks against an IoT device, and we demonstrate the effectiveness of our approach with high accuracy. The results show that standalone IoT devices can detect and classify DoS and, therefore, arguably, DDoS attacks against them at a low computational cost with a deterministic delay.
Sustainable urban planning to control flood exposure in the coastal zones of China
Authors: Wu Yijing , Li Jingwei , Wu Haoyuan , Duan Yongqiang , Shen Hanru , Du Shiqiang 
Published: August 2024

Abstract
Context
Sustainable development in coastal zones faces escalating flood risk in the context of climate change and urbanization, and the rapid urban growth in flood zones has been one of the key drivers. Therefore, understanding the Urban Exposure to Flooding (UEF) and its future scenarios is important in coastal zones.

Objectives
The objectives of this study were: (1) to assess the future dynamics of UEFs in China's coastal zones, and (2) to identify a sustainable way of urban planning in controlling the growth of UEFs.

Methods
Future UEFs in coastal China were assessed during 2020–2050 by combining urban expansion model, scenario analysis, and flood exposure assessment. Alternative scenarios were considered of shared socioeconomic pathways (SSPs), representative concentration pathways (RCPs), strategies of urban planning.

Results
The results show that the 1000-year flood UEFs along coastal China was expected to grow under SSP2-RCP4.5 from 9,879 km2 in 2020 to 13,424 (12,997–13,981) km2 in 2050, representing an increment of 35.88% (31.56%–41.52%). Alternatively, the strategy of sustainable development planning could reduce the newly added UEF by 16.98% (15.63%–18.67%) in a 1000-year flood scenario.

Conclusions
The findings proved that the ways of urban growth matters in terms of affecting food exposure and risk and flood risk should be incorporated into urban planning for a sustainable landscape. The study could offer methodology and support for sustainable development strategies in reducing future urban flood risk.
ConcatNeXt: An automated blood cell classification with a new deep convolutional neural network
Authors: Erten Mehmet , Barua Prabal Datta , Dogan Sengul , Tuncer Turker , Tan Ru-San , Acharya U. R. 
Published: August 2024

AbstractExamining peripheral blood smears is valuable in clinical settings, yet manual identification of blood cells proves time-consuming. To address this, an automated blood cell image classification system is crucial. Our objective is to develop a precise automated model for detecting various blood cell types, leveraging a novel deep learning architecture.We harnessed a publicly available dataset of 17,092 blood cell images categorized into eight classes. Our innovation lies in ConcatNeXt, a new convolutional neural network. In the spirit of Geoffrey Hinton's approach, we adapted ConvNeXt by substituting the Gaussian error linear unit with a rectified linear unit and layer normalization with batch normalization. We introduced depth concatenation blocks to fuse information effectively and incorporated a patchify layer.Integrating ConcatNeXt with nested patch-based deep feature engineering, featuring downstream iterative neighborhood component analysis and support vector machine-based functions, establishes a comprehensive approach. ConcatNeXt achieved notable validation and test accuracies of 97.43% and 97.77%, respectively. The ConcatNeXt-based feature engineering model further elevated accuracy to 98.73%. Gradient-weighted class activation maps were employed to provide interpretability, offering valuable insights into model decision-making.Our proposed ConcatNeXt and nested patch-based deep feature engineering models excel in blood cell image classification, showcasing remarkable classification performances. These innovations mark significant strides in computer vision-based blood cell analysis.
Characterization of a Fatty Acid Amide Hydrolase (FAAH) in Hirudo Verbana
Authors: Kabeiseman Emily , Paulsen Riley T. , Burrell Brian D. 
Published: August 2024

AbstractThe endocannabinoid system plays a critical role in modulating both peripheral and central nervous system function. Despite being present throughout the animal kingdom, there has been relatively little investigation of the endocannabinoid system beyond traditional animal models. In this study, we report on the identification and characterization of a putative fatty acid amide hydrolase (FAAH) in the medicinal leech, Hirudo verbana. FAAH is the primary enzyme responsible for metabolizing the endocannabinoid signaling molecule arachidonoyl ethanolamide (anandamide or AEA) and therefore plays a critical role in regulating AEA levels in the nervous system. mRNA encoding Hirudo FAAH (HirFAAH) is expressed in the leech central nervous system (CNS) and sequence analysis suggests that this is an orthologue of FAAH-2 observed in vertebrates. Functionally, HirFAAH has serine hydrolase activity based on activity-based protein profiling (ABPP) studies using the fluorophosphonate probe TAMRA-FP. HirFAAH also hydrolyzes arachidonyl 7-amino, 4-methyl coumarin amide (AAMCA), a substrate specific to FAAH. Hydrolase activity during both the ABPP and AAMCA assays was eliminated by a mutation at a conserved catalytic serine. Activity was also blocked by the known FAAH inhibitor, URB597. Treatment of Hirudo ganglia with URB597 potentiated synapses made by the pressure-sensitive mechanosensory neuron (P cell), mimicking the effects of exogenously applied AEA. The Hirudo CNS has been a useful system in which to study properties of endocannabinoid modulation of nociception relevant to vertebrates. Therefore, this characterization of HirFAAH is an important contribution to comparative studies of the endocannabinoid system.
Bibliometrics beyond citations: introducing mention extraction and analysis
Authors: Petrovich Eugenio , Verhaegh Sander , Bös Gregor , Cristalli Claudia , Dewulf Fons , van Gemert Ties , IJdens Nina 
Published: August 2024

AbstractStandard citation-based bibliometric tools have severe limitations when they are applied to periods in the history of science and the humanities before the advent of now-current citation practices. This paper presents an alternative method involving the extracting and analysis of mentions to map and analyze links between scholars and texts in periods that fall outside the scope of citation-based studies. Focusing on one specific discipline in one particular period and language area—Anglophone philosophy between 1890 and 1979—we describe a procedure to create a mention index by identifying, extracting, and disambiguating mentions in academic publications. Our mention index includes 1,095,765 mention links, extracted from 22,977 articles published in 12 journals. We successfully link 93% of these mentions to specific philosophers, with an estimated precision of 82% to 91%. Moreover, we integrate the mention index into a database named EDHIPHY, which includes data and metadata from multiple sources and enables multidimensional mention analyses. In the final part of the paper, we present four case studies conducted by domain experts, demonstrating the use and the potential of both EDHIPHY and mention analyses more generally.
Cross-Scale Phase Relationship of the Ca II K Index with Solar Wind Parameters: A Space Climate Focus
Authors: Reda Raffaele , Giovannelli Luca , Alberti Tommaso 
Published: August 2024

AbstractThe solar wind, representing one of the most impacting phenomena in the circum-terrestrial space, constitutes one of the several manifestations of the magnetic activity of the Sun. With the aim of shedding light on the scales beyond the rotational period of the Sun (i.e., Space Climate scales), this study investigates the phase relationship of a solar activity physical proxy, the Ca II K index, with solar wind properties measured near the Earth, over the whole space era (last five solar cycles). Using a powerful tool such as the Hilbert–Huang transform, we investigate the dependence of their phase coherence on the obtained time scale components. Phase coherence at the same time scales is found between all the components and is also preserved between adjacent components with time scales ≳ 2 yrs. Finally, given the availability of the intrinsic modes of oscillation, we explore how the relationship of Ca II K index with solar wind parameters depends on the time scale considered. According to our results, we hypothesize the presence of a bifurcation in the phase-space Ca II K index vs. solar wind speed (dynamic pressure), where the time scale seems to act as a bifurcation parameter. This concept may be pivotal for unraveling the complex interplay between solar activity and solar wind, bearing implications from the prediction and the interpretation point of view in Space Climate studies.