bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Guide Toward Multi-scale and Quantitative Branching Analysis in the Mammary Gland
Authors: Hannezo Edouard , Scheele Colinda L. G. J. 
Published: January 2023

AbstractThe mammary gland consists of a bilayered epithelial structure with an extensively branched morphology. The majority of this epithelial tree is laid down during puberty, during which actively proliferating terminal end buds repeatedly elongate and bifurcate to form the basic structure of the ductal tree. Mammary ducts consist of a basal and luminal cell layer with a multitude of identified sub-lineages within both layers. The understanding of how these different cell lineages are cooperatively driving branching morphogenesis is a problem of crossing multiple scales, as this requires information on the macroscopic branched structure of the gland, as well as data on single-cell dynamics driving the morphogenic program. Here we describe a method to combine genetic lineage tracing with whole-gland branching analysis. Quantitative data on the global organ structure can be used to derive a model for mammary gland branching morphogenesis and provide a backbone on which the dynamics of individual cell lineages can be simulated and compared to lineage-tracing approaches. Eventually, these quantitative models and experiments allow to understand the couplings between the macroscopic shape of the mammary gland and the underlying single-cell dynamics driving branching morphogenesis.
Analysis of Vascular Morphogenesis in Zebrafish
Authors: Hubert Marvin , Herzog Wiebke 
Published: January 2023

AbstractAnalysis of cardiovascular development in zebrafish embryos has become a major driver of vascular research in recent years. Imaging-based analyses have allowed the discovery or verification of morphologically distinct processes and mechanisms of, e.g., endothelial cell migration, angiogenic sprouting, tip or stalk cell behavior, and vessel anastomosis. In this chapter, we describe the techniques and tools used for confocal imaging of zebrafish endothelial development in combination with general experimental approaches for molecular dissection of involved signaling pathways.
Robustness of Image-Based Malware Analysis
Authors: Tran Katrina , Di Troia Fabio , Stamp Mark 
Published: January 2023

AbstractIn previous work, “gist descriptor” features extracted from images have been used in malware classification problems and have shown promising results. In this research, we determine whether gist descriptors are robust with respect to malware obfuscation techniques, as compared to Convolutional Neural Networks (CNN) trained directly on malware images. Using the Python Image Library (PIL), we create images from malware executables and from malware that we obfuscate. We conduct experiments to compare classifying these images with a CNN as opposed to extracting the gist descriptor features from these images to use in classification. For the gist descriptors, we consider a variety of classification algorithms including k-nearest neighbors, random forest, support vector machine, and multi-layer perceptron. We find that gist descriptors are more robust than CNNs, with respect to the obfuscation techniques that we consider.
Twitter Bots’ Detection with Benford’s Law and Machine Learning
Authors: Bhosale Sanmesh , Di Troia Fabio 
Published: January 2023

AbstractOnline Social Networks (OSNs) have grown exponentially in terms of active users and have now become an influential factor in the formation of public opinions. For this reason, the use of bots and botnets for spreading misinformation on OSNs has become a widespread concern. Identifying bots and botnets on Twitter can require complex statistical methods to score a profile based on multiple features. Benford’s Law, or the Law of Anomalous Numbers, states that, in any naturally occurring sequence of numbers, the First Significant Leading Digit (FSLD) frequency follows a particular pattern such that they are unevenly distributed and reducing. This principle can be applied to the first-degree egocentric network of a Twitter profile to assess its conformity to such law and, thus, classify it as a bot profile or normal profile. This paper focuses on leveraging Benford’s Law in combination with various Machine Learning (ML) classifiers to identify bot profiles on Twitter. In addition, a comparison with other statistical methods is produced to confirm our classification results.
A Blockchain-Based Retribution Mechanism for Collaborative Intrusion Detection
Authors: Fan Wenjun , Kumar Shubham , Chang Sang-Yoon , Park Younghee 
Published: January 2023

AbstractCollaborative intrusion detection approach uses the shared detection signature between the collaborative participants to facilitate coordinated defense. In the context of collaborative intrusion detection system (CIDS), however, there is no research focusing on the efficiency of the shared detection signature. The inefficient detection signature costs not only the IDS resource but also the process of the peer-to-peer (P2P) network. In this paper, we therefore propose a blockchain-based retribution mechanism, which aims to incentivize the participants to contribute to verifying the efficiency of the detection signature in terms of certain distributed consensus. We implement a prototype using Ethereum blockchain, which instantiates a token-based retribution mechanism and a smart contract-enabled voting-based distributed consensus. We conduct a number of experiments built on the prototype, and the experimental results demonstrate the effectiveness of the proposed approach.
Impact of Location Spoofing Attacks on Performance Prediction in Mobile Networks
Authors: Kanuri Nikhil Sai , Chang Sang-Yoon , Park Younghee , Kim Jonghyun , Kim Jinoh 
Published: January 2023

AbstractPerformance prediction in wireless mobile networks is essential for diverse purposes in network management and operation. Particularly, the position of mobile devices is crucial to estimating the performance in the mobile communication setting. With its importance, this paper investigates mobile communication performance based on the coordinate information of mobile devices. We analyze a recent 5G data collection and examine the feasibility of location-based performance prediction. As location information is key to performance prediction, the basic assumption of making a relevant prediction is the correctness of the coordinate information of devices given. With its criticality, this paper also investigates the impact of position falsification on the ML-based performance predictor, which reveals the significant degradation of the prediction performance under such attacks, suggesting the need for effective defense mechanisms against location spoofing threats.
Four-fermion deformations of the massless Schwinger model and confinement
Authors: Cherman Aleksey , Jacobson Theodore , Shifman Mikhail , Ünsal Mithat , Vainshtein Arkady 
Published: January 2023

Abstract
We consider the massless charge-N Schwinger model and its deformation with two four-fermion operators. Without the deformations, this model exhibits chiral symmetry breaking without confinement. It is usually asserted that the massless Schwinger model is always deconfined and a string tension emerges only when a mass for the fermion field is turned on. We show that in the presence of these four-fermion operators, the massless theory can in fact confine. One of the four-fermion deformations is chirally neutral, and is a marginal deformation. The other operator can be relevant or irrelevant, and respects a ℤ2 subgroup of chiral symmetry for even N, hence forbidding a mass term. When it is relevant, even the exactly massless theory exhibits both confinement and spontaneous chiral symmetry breaking. The construction is analogous to QCD(adj) in 2d. While the theory without four-fermion deformations is deconfined, the theory with these deformations is generically in a confining phase. We study the model on ℝ2 using bosonization, and also analyze the mechanism of confinement on ℝ × S1, where we find that confinement is driven by fractional instantons.
A holographic inequality for N = 7 regions
Authors: Czech Bartłomiej , Wang Yunfei 
Published: January 2023

Abstract
In holographic duality, boundary states that have semiclassical bulk duals must obey inequalities, which bound their subsystems’ von Neumann entropies. Hitherto known inequalities constrain entropies of reduced states on up to N = 5 disjoint subsystems. Here we report one new such inequality, which involves N = 7 disjoint regions. Our work supports a recent conjecture on the structure of holographic inequalities, which predicted the existence and schematic form of the new inequality. We explain the logic and educated guesses by which we arrived at the inequality, and comment on the feasibility of employing similar tactics in a more exhaustive search.
A placenta-on-a-chip model to determine the regulation of FKBPL and galectin-3 in preeclampsia
Authors: Ghorbanpour Sahar Masoumeh , Richards Claire , Pienaar Dillan , Sesperez Kimberly , Aboulkheyr Es. Hamidreza , Nikolic Valentina N. , Karadzov Orlic Natasa , Mikovic Zeljko , Stefanovic Milan , Cakic Zoran , Alqudah Abdelrahim , Cole Louise , Gorrie Catherine , McGrath Kristine , Kavurma Mary M. , Ebrahimi Warkiani Majid , McClements Lana 
Published: January 2023

AbstractPreeclampsia is a pregnancy-specific cardiovascular disorder, involving significant maternal endothelial dysfunction. Although inappropriate placentation due to aberrant angiogenesis, inflammation and shallow trophoblast invasion are the root causes of preeclampsia, pathogenic mechanisms are poorly understood, particularly in early pregnancy. Here, we first confirm the abnormal expression of important vascular and inflammatory proteins, FK506-binding protein-like (FKBPL) and galectin-3 (Gal-3), in human plasma and placental tissues from women with preeclampsia and normotensive controls. We then employ a three-dimensional microfluidic placental model incorporating human umbilical vein endothelial cells (HUVECs) and a first trimester trophoblast cell line (ACH-3P) to investigate FKBPL and Gal-3 signaling in inflammatory conditions. In human samples, both circulating (n = 17 controls; n = 30 preeclampsia) and placental (n ≥ 6) FKBPL and Gal-3 levels were increased in preeclampsia compared to controls (plasma: FKBPL, p < 0.0001; Gal-3, p < 0.01; placenta: FKBPL, p < 0.05; Gal-3, p < 0.01), indicative of vascular dysfunction in preeclampsia. In our placenta-on-a-chip model, we show that endothelial cells are critical for trophoblast-mediated migration and that trophoblasts effectively remodel endothelial vascular networks. Inflammatory cytokine tumour necrosis factor-α (10 ng/mL) modulates both FKBPL and Gal-3 signaling in conjunction with trophoblast migration and impairs vascular network formation (p < 0.005). Our placenta-on-a-chip recapitulates aspects of inappropriate placental development and vascular dysfunction in preeclampsia.
Dentoskeletal effects of clear aligner vs twin block—a short-term study of functional appliances
Authors: Lombardo Elisabetta Cretella , Lione Roberta , Franchi Lorenzo , Gaffuri Francesca , Maspero Cinzia , Cozza Paola , Pavoni Chiara 
Published: January 2023

Abstract
Purpose
The twin block (TB) is one of the most widely used functional appliances for the correction of class II malocclusions. Align Technology (San Jose, CA, USA) developed the Invisalign® mandibular advancement (MA) that replicates the mechanism of action of a functional appliance. The aim of this study was to compare the changes produced by the TB versus those by MA.

Methods
The records of 56 class II patients treated with the TB (TB group: n = 35) or the MA (MA group: n = 21) were compared to a control sample of 15 untreated class II subjects (UC2).

Results
The TB and MA groups showed a significant reduction of the ANB angle, compared to the controls (TB group: −1.5°; MA group: −1.5°; UC2 group: +0.2°). For the Co-Gn values, the TB and MA groups showed significant differences when compared with the UC2 group with an increase of 8.4 mm in TB patients and of 8.3 mm in MA patients. The increase of the distance of Pg to the true vertical line (TVL) was the only measurement where significant differences between the three groups were found with a greater advancement of the soft tissue pogonion in the TB group compared with the MA group and the UC2 group (TB group: +3 mm; MA group: +0.9 mm; UC2 group: −1.6 mm). The angle between the palatal plane and mandibular plane revealed a more relevant reduction in the TB and MA groups. Both appliances were able to reduce overjet and vertical overbite values.

Conclusions
Treatment with the MA and TB appliances produced a significant elongation of the mandible with an improvement in sagittal relationship, overjet, and vertical overbite and with good control of the vertical relationship. TB subjects showed a greater advancement of the soft tissue chin.
Post-exposure Period as a key Factor to Assess Cadmium Toxicity: Lethal vs. Behavioral Responses
Authors: Alonso Álvaro 
Published: January 2023

AbstractThe exposure of animals to pollution in ecosystems is not always chronic. Toxicants can remain in aquatic ecosystems for a short-term. To improve the extrapolation of laboratory results to natural scenarios the inclusion of post-exposure periods is a relevant issue. The present study focuses on the assessment of cadmium toxicity on survival and behavior of the aquatic snail Potamopyrgus antipodarum (Tateidae, Mollusca) during exposure and post-exposure. Animals were exposed for 48 h to cadmium (0.05, 0.14, 0.44 and 1.34 mg Cd/L) and 168 h of post-exposure. During the post-exposure period an increase in mortality in all concentrations was observed. The effects observed during the post-exposure period on the LC50 and EC50 were significant. During the post-exposure, behavior showed a clear recovery in surviving animals exposed to 0.44 mg Cd/L. Animals exposed to 0.05 mg Cd/L did not show differences with control. Therefore, mortality after exposure should be included in the ecotoxicological bioassays for a more realistic estimation of the cadmium effects. To assess the degree of animal recovery after cadmium exposure, behaviour has been shown as an adequate parameter.
Artificial intelligence: a “promising technology”
Authors: Hirsch-Kreinsen Hartmut 
Published: January 2023

AbstractThis paper addresses the question of how the ups and downs in the development of artificial intelligence (AI) since its inception can be explained. It focuses on the development of artificial intelligence in Germany since the 1970s, and particularly on its current dynamics. An assumption is made that a mere reference to rapid advances in information technologies and the various methods and concepts of artificial intelligence in recent decades cannot adequately explain these dynamics, because from a social science perspective, this is an oversimplified, technology-centred explanation. Drawing on ideas from social scientific innovation research, the hypothesis is rather that artificial intelligence should be understood as a “promising technology”. Its various stages of development have always been driven by technological promises about its special powers and capabilities when applied to solving economic and societal challenges.
Stacking sequence optimisation of an aircraft wing skin
Authors: Ntourmas Georgios , Glock Florian , Deinert Sebastian , Daoud Fernass , Schuhmacher Gerd , Chronopoulos Dimitrios , Özcan Ender , Ninić Jelena 
Published: January 2023

AbstractThis paper demonstrates a stacking sequence optimisation process of a composite aircraft wing skin. A two-stage approach is employed to satisfy all sizing requirements of this industrial sized, medium altitude, long endurance drone. In the first stage of the optimisation, generic stacks are used to describe the thickness and stiffness properties of the structure while considering both structural requirements and discrete guidelines such as blending. In the second stage of the optimisation, mathematical programming is used to solve a Mixed Integer Linear Programming formulation of the stacking sequence optimisation. The proposed approach is suitable for real-world thick structures comprised of multiple patches. Different thickness discretisation strategies are examined for the retrieval of the discrete stacking sequences, with each one having a different influence on the satisfaction of all structural constraints across the various sub-components of the wing. The weight penalty introduced between the continuous and final discrete design of the proposed approach is negligible.
The Rayleigh–Bénard Problem for Compressible Fluid Flows
Authors: Feireisl Eduard , Świerczewska-Gwiazda Agnieszka 
Published: January 2023

AbstractWe consider the physically relevant fully compressible setting of the Rayleigh–Bénard problem of a fluid confined between two parallel plates, heated from the bottom, and subjected to gravitational force. Under suitable restrictions imposed on the constitutive relations we show that this open system is dissipative in the sense of Levinson, meaning there exists a bounded absorbing set for any global-in-time weak solution. In addition, global-in-time trajectories are asymptotically compact in suitable topologies and the system possesses a global compact trajectory attractor $$\mathcal {A}$$
A
. The standard technique of Krylov and Bogolyubov then yields the existence of an invariant measure—a stationary statistical solution sitting on $$\mathcal {A}$$
A
. In addition, the Birkhoff–Khinchin ergodic theorem provides convergence of ergodic averages of solutions belonging to $$\mathcal {A}$$
A
a.s. with respect to the invariant measure.
The contribution of high-resolution GC separations in plastic recycling research
Authors: Zanella Delphine , Romagnoli Monica , Malcangi Sofia , Beccaria Marco , Chenet Tatiana , De Luca Chiara , Testoni Fabio , Pasti Luisa , Visentini Ugo , Morini Giampiero , Cavazzini Alberto , Franchina Flavio A. 
Published: January 2023

AbstractOne convenient strategy to reduce environmental impact and pollution involves the reuse and revalorization of waste produced by modern society. Nowadays, global plastic production has reached 367 million tons per year and because of their durable nature, their recycling is fundamental for the achievement of the circular economy objective. In closing the loop of plastics, advanced recycling, i.e., the breakdown of plastics into their building blocks and their transformation into valuable secondary raw materials, is a promising management option for post-consumer plastic waste. The most valuable product from advanced recycling is a fluid hydrocarbon stream (or pyrolysis oil) which represents the feedstock for further refinement and processing into new plastics. In this context, gas chromatography is currently playing an important role since it is being used to study the pyrolysis oils, as well as any organic contaminants, and it can be considered a high-resolution separation technique, able to provide the molecular composition of such complex samples. This information significantly helps to tailor the pyrolysis process to produce high-quality feedstocks. In addition, the detection of contaminants (i.e., heteroatom-containing compounds) is crucial to avoid catalytic deterioration and to implement and design further purification processes. The current review highlights the importance of molecular characterization of waste stream products, and particularly the pyrolysis oils obtained from waste plastics. An overview of relevant applications published recently will be provided, and the potential of comprehensive two-dimensional gas chromatography, which represents the natural evolution of gas chromatography into a higher-resolution technique, will be underlined.
Is the Association of the Rare rs35667974 IFIH1 Gene Polymorphism With Autoimmune Diseases a Case of RNA Epigenetics?
Authors: Andreou Athena , Papakyriakou Athanasios , Zervou Maria I. , Goulielmos George N. , Eliopoulos Elias E. 
Published: January 2023

AbstractInterferon induced with helicase C domain-containing protein 1 (IFIH1) gene encodes a cytoplasmic RNA helicase otherwise known as melanoma differentiation-associated 5 (MDA5), a RIG-1-like RNA helicase that recognizes viral RNA and is involved in innate immunity through recognition of viral RNA. Upon binding to double-stranded (ds) RNA, MDA5 forms a filamentous assembly along the length of dsRNA and utilizes molecular signatures to discriminate self, versus non-self on the basis of dsRNA length and methylation. Its missense variant rs35667974 is protective for type 1 diabetes, psoriasis, and psoriatic arthritis, but is also found to be associated with an increased risk for ankylosing spondylitis, Crohn’s disease, and ulcerative colitis. To gain insight into the complex role of this variant we performed a structural analysis of MDA5 in complex with dsRNA using molecular dynamics simulations. Our data suggest that while the Ile923Val mutation of the rs35667974 variant does not affect binding to native dsRNA significantly, it displays a destabilizing effect in the presence of 2′-O uridine methylation. Thus, the presence of 2′-O-methylation at the dsRNA introduces a sensing signature that leads to selective reduction of the overall MDA catalytic activity. This study represents an evaluation of the role of the shared rs35667974 variant of autoimmune locus IFIH1, reported to lead to selectively reduced catalytic activity of the modified MDA5 phenotype and, as a consequence, reduced negative feedback on cytokine and chemokine signaling and selectively protection against autoimmunity.
Eye Tracking in Virtual Reality: a Broad Review of Applications and Challenges
Authors: Adhanom Isayas Berhe , MacNeilage Paul , Folmer Eelke 
Published: January 2023

AbstractEye tracking is becoming increasingly available in head-mounted virtual reality displays with various headsets with integrated eye trackers already commercially available. The applications of eye tracking in virtual reality are highly diversified and span multiple disciplines. As a result, the number of peer-reviewed publications that study eye tracking applications has surged in recent years. We performed a broad review to comprehensively search academic literature databases with the aim of assessing the extent of published research dealing with applications of eye tracking in virtual reality, and highlighting challenges, limitations and areas for future research.
Green construction for low-carbon cities: a review
Authors: Chen Lin , Huang Lepeng , Hua Jianmin , Chen Zhonghao , Wei Lilong , Osman Ahmed I. , Fawzy Samer , Rooney David W. , Dong Liang , Yap Pow-Seng 
Published: January 2023

AbstractThe construction industry is a major user of non-renewable energy and contributor to emission of greenhouse gases, thus requiring to achieve net-zero carbon emissions by 2050. Indeed, construction activities account for 36% of global energy consumption and 39% of global carbon dioxide emissions. Reducing carbon emissions requires adapted government policies, carbon emission analysis and calculation models, and sustainable materials. Here, we review green construction with focus on history, carbon emissions, policies, models, life cycle assessment, and sustainable materials such as biochar, bioplastic, agricultural waste, animal wool, fly ash and self-healing concrete. Analysis of carbon emissions over the building life cycle shows that the construction phase accounts for 20–50% of total carbon emissions. The average ratio of construction phase annual emissions to operation phase emissions is 0.62. We present national policy frameworks and technology roadmaps from the United States of America, Japan, China, and the European Union, highlighting plans to achieve carbon neutrality in the building sector.