bluuebunny/crossref_metadata_2025_split huggingface dataset:
Plane-separated routing in ad-hoc networks
Authors: Ergenç Doğanalp , Onur Ertan 
Published: January 2022

AbstractControl and user (data) plane separation (CUPS) is a concept applied in various networking areas to scale network resources independently, increase the quality of service, and facilitate the autonomy of networks. In this study, we leverage this concept to design a plane-separated routing algorithm, CUPS-based hierarchical routing algorithm (CHRA), as an energy-efficient and low-latency end-to-end communication scheme for clustered ad-hoc networks. In CHRA, while cluster heads constitute the control plane to conduct network discovery and routing, ordinary nodes residing in the user plane forward packets according to the routing decisions taken by the control plane. Exploiting the CUPS, we avoid exhausting cluster heads by offloading packet-forwarding to ordinary nodes and improve the quality of service by utilizing alternative paths other than the backbone of cluster heads. Our simulation results show that CHRA offers a better quality of service in terms of end-to-end latency and data-to-all ratio, and promotes fairness in energy-consumption in both stationary and mobile scenarios.
Residual Stress Measurements in Extreme Environments for Hazardous, Layered Specimens
Authors: Benefiel B. C. , Larsen E. D. , Prime M. B. , Phillips A. M. , Davies K. B. , Castano D. , Cole J. I. 
Published: January 2022

Abstract
Background
In nuclear fuel plates of low-enriched U-10Mo (LEU) clad with aluminum by hot isostatic pressing (HIP), post-irradiation stresses arising during reactor shutdown are a major concern for safe reactor operations. Measurement of those residual stresses has not previously been possible because the high radioactivity of the plates requires handling only by remote manipulation in a hot cell.

Objective
The incremental slitting method for measuring through-thickness stress profiles was modified, and a system for automated, remote operation was built and tested.

Methods
Experimental modifications consisted of replacing electric-discharge machining (EDM) with a small end mill and strain-gauge measurements with cantilever displacement measurements. The inverse method used to calculate stresses was the pulse-regularization method modified to allow discontinuities across material interfaces. The new system was validated by comparing with conventional slitting on a depleted U-10Mo (DU) fuel plate.

Results
The new system was applied to two measurements each on six as-fabricated (pre-irradiation) LEU miniature fuel plates. Variations between the measurements at two locations in the same plate were strongly correlated with measured geometrical heterogeneity in the plate—a tilt in the fuel foil. Compressive stresses in the U-10Mo were shown to increase from 20 to 250 MPa as the ratio of aluminum thickness to U-10Mo thickness increased causing increased constraint during cooling. Faster cooling rates during processing also increased stress magnitudes.

Conclusions
The measurements trends agreed with data in the literature from similar plates made with DU, which further validates the method. Because other methods are impractical in a hot cell, the modified slitting method is now poised for the first measurements of post-irradiation stresses.
Dual-energy CT: minimal essentials for radiologists
Authors: Tatsugami Fuminari , Higaki Toru , Nakamura Yuko , Honda Yukiko , Awai Kazuo 
Published: January 2022

AbstractDual-energy CT, the object is scanned at two different energies, makes it possible to identify the characteristics of materials that cannot be evaluated on conventional single-energy CT images. This imaging method can be used to perform material decomposition based on differences in the material-attenuation coefficients at different energies. Dual-energy analyses can be classified as image data-based- and raw data-based analysis. The beam-hardening effect is lower with raw data-based analysis, resulting in more accurate dual-energy analysis. On virtual monochromatic images, the iodine contrast increases as the energy level decreases; this improves visualization of contrast-enhanced lesions. Also, the application of material decomposition, such as iodine- and edema images, increases the detectability of lesions due to diseases encountered in daily clinical practice. In this review, the minimal essentials of dual-energy CT scanning are presented and its usefulness in daily clinical practice is discussed.
Endogenous Levels of Alpha-Synuclein Modulate Seeding and Aggregation in Cultured Cells
Authors: Vasili Eftychia , Dominguez-Meijide Antonio , Flores-León Manuel , Al-Azzani Mohammed , Kanellidi Angeliki , Melki Ronald , Stefanis Leonidas , Outeiro Tiago Fleming 
Published: January 2022

AbstractParkinson’s disease is a progressive neurodegenerative disorder characterized by the accumulation of misfolded alpha-synuclein in intraneuronal inclusions known as Lewy bodies and Lewy neurites. Multiple studies strongly implicate the levels of alpha-synuclein as a major risk factor for the onset and progression of Parkinson’s disease. Alpha-synuclein pathology spreads progressively throughout interconnected brain regions but the precise molecular mechanisms underlying the seeding of alpha-synuclein aggregation are still unclear. Here, using stable cell lines expressing alpha-synuclein, we examined the correlation between endogenous alpha-synuclein levels and the seeding propensity by exogenous alpha-synuclein preformed fibrils. We applied biochemical approaches and imaging methods in stable cell lines expressing alpha-synuclein and in primary neurons to determine the impact of alpha-synuclein levels on seeding and aggregation. Our results indicate that the levels of alpha-synuclein define the pattern and severity of aggregation and the extent of p-alpha-synuclein deposition, likely explaining the selective vulnerability of different cell types in synucleinopathies. The elucidation of the cellular processes involved in the pathological aggregation of alpha-synuclein will enable the identification of novel targets and the development of therapeutic strategies for Parkinson’s disease and other synucleinopathies.
Hepatocellular carcinoma diagnosis using a novel electrochemiluminescence immunoassay targeting serum IgM-free AIM
Authors: Shimizu Tomo , Sawada Takashi , Asai Tomohide , Kanetsuki Yuka , Hirota Jiro , Moriguchi Michihisa , Nakajima Tomoaki , Miyazaki Toru , Okanoue Takeshi 
Published: January 2022

AbstractBackgroundRecent increases in the number of patients with non-alcoholic steatohepatitis (NASH) warrant the identification of biomarkers for early detection of hepatocellular carcinoma (HCC) associated with NASH (NASH-HCC). IgM-free apoptosis inhibitor of macrophage (AIM), which generally associates with IgM in blood and exerts its biological function by dissociation from IgM, may serve as an effective biomarker for NASH-HCC. Here, we established a fully automatic and high-throughput electrochemiluminescence immunoassay (ECLIA) to measure IgM-free AIM and investigated its efficacy in diagnosing NASH-HCC and viral HCC.MethodsIgM-free AIM levels were measured in 212 serum samples from patients with, or without, HCC related to NASH, hepatitis B virus, and hepatitis C virus, using ECLIA. We also developed an ECLIA for measuring both IgM-free and IgM-bound AIM and investigated the existing form of AIM in blood by size-exclusion chromatography.ResultsIgM-free AIM levels were significantly higher in the HCC group than in the non-HCC group, regardless of the associated pathogenesis. Moreover, the area under the receiver operating curve for IgM-free AIM was greater than that for conventional HCC biomarkers, alpha-fetoprotein or des-γ-carboxy prothrombin, regardless of the cancer stage. ECLIA counts of IgM-free AIM derived from samples fractionated by size-exclusion chromatography were significantly higher in patients with NASH-HCC than in healthy volunteers and in patients with non-alcoholic fatty liver and NASH.ConclusionsSerum IgM-free AIM may represent a universal HCC diagnostic marker superior to alpha-fetoprotein or des-γ-carboxy prothrombin. Our newly established ECLIA could contribute to further clinical studies on AIM and in vitro HCC diagnosis.
Capture the variation of acoustic impedance property in the Jaisalmer Formation due to structural deformation based on post-stack seismic inversion study: a case study from Jaisalmer sub-basin, India
Authors: Datta Gupta Saurabh , Sinha Sugata Kumar , Chahal Raman 
Published: January 2022

AbstractThe Rajasthan basin situates in the western part of India. The basin architecture comprises three significant sub-basins such as Barmer-Sanchor, Bikaner-Nagaur and Jaisalmer. Barmer-Sanchor and Bikaner-Nagaur sub-basins are intracratonic categories, whereas the Jaisalmer sub-basin comes under intracratonic nature. The current study was conducted in the Jaisalmer sub-basin. The study was conducted in two regions in the Jaisalmer sub-basin through a comparative quantitative interpretation study with the help of two vintages seismic surveys. Ghotaru and Bandha are two adjacent areas in the Jaisalmer sub-basin where Ghotaru has seen few hydrocarbon discoveries; however, no such discoveries are encountered in the Bandha area. The current study was concentrated on the Jaisalmer limestone formation in the Jurassic age. The sub-basin and its related study area have been structurally deformed due to various tectonic activities. Structural deformation was played a crucial role in changing the rock property of limestone facies. A post-stack seismic inversion was carried out to capture the rock property changes in the limestone reservoir based on P-impedance values. Development of high P-impedance was observed in the Ghotaru region compared to the Bandha region from this study. A frequency changes of the limestone lithofacies with structural components was also captured in this study. The high impedance limestone lithofacies is a probable hydrocarbon-bearing reservoir unit in the Jaisalmer Formation of the Ghotaru region.
Role of Radiologic Imaging in Otosclerosis
Authors: Manning Paul M. , Shroads Michael R. , Bykowski Julie , Mafee Mahmood F. 
Published: January 2022

AbstractPurpose of ReviewTo review the role of imaging in otosclerosis with an emphasis on pre- and post-operative imaging evaluation.Recent FindingsPre-operative CT imaging can help define the extent of bone involvement in otosclerosis and may help avoid surgical complications due to variant anatomy or unsuspected alternative causes of conductive hearing loss. In patients with recurrent hearing loss after surgery, CT imaging can clarify prosthesis position and re-assess anatomy.SummaryCT imaging complements otologic exam and audiometry findings in patients with suspected otosclerosis, for pre-operative planning, and post-operative assessment for patients with recurrent symptoms.
EBSD characterisation of grain size distribution and grain sub-structures for ferritic steel weld metals
Authors: Lehto Pauli , Remes Heikki 
Published: January 2022

AbstractMicrostructural characterisation of engineering materials is required for understanding the relationships between microstructure and mechanical properties. Conventionally grain size is measured from grain boundary maps obtained using optical or electron microscopy. This paper implements EBSD-based linear intercept measurement of spatial grain size variation for ferritic steel weld metals, making analysis flexible and robust. While grain size has been shown to correlate with the strength of the material according to the Hall–Petch relationship, similar grain sizes in weld metals with different phase volume fractions can have significantly different mechanical properties. Furthermore, the solidification of the weld pool induces the formation of grain sub-structures that can alter mechanical properties. The recently developed domain misorientation approach is used in this study to provide a more comprehensive characterisation of the grain sub-structures for ferritic steel weld metals. The studied weld metals consist of varying mixtures of primary ferrite, acicular ferrite, and bainite/martensite, with large differences observed in hardness, grain size, grain morphology, and dislocation cell size. For the studied weld metals, the average dislocation cell size varied between 0.68 and 1.41 µm, with bainitic/martensitic weld metals showing the smallest sub-structures and primary ferrite the largest. In contrast, the volume-weighted average grain size was largest for the bainitic/martensitic weld metal. Results indicate that a Hall–Petch-type relationship exists between hardness and average dislocation cell size and that it partially corrects the significantly different grain size—hardness relationship observed for ferritic and bainitic/martensitic weld metals. The methods and datasets are provided as open access.
Metal matrix nanocomposites in tribology: Manufacturing, performance, and mechanisms
Authors: Pan Shuaihang , Jin Kaiyuan , Wang Tianlu , Zhang Zhinan , Zheng Long , Umehara Noritsugu 
Published: January 2022

AbstractMetal matrix nanocomposites (MMNCs) become irreplaceable in tribology industries, due to their supreme mechanical properties and satisfactory tribological behavior. However, due to the dual complexity of MMNC systems and tribological process, the anti-friction and anti-wear mechanisms are unclear, and the subsequent tribological performance prediction and design of MMNCs are not easily possible: A critical up-to-date review is needed for MMNCs in tribology. This review systematically summarized the fabrication, manufacturing, and processing techniques for high-quality MMNC bulk and surface coating materials in tribology. Then, important factors determining the tribological performance (mainly anti-friction evaluation by the coefficient of friction (CoF) and anti-wear assessment with wear rate) in MMNCs have been investigated thoroughly, and the correlations have been analyzed to reveal their potential coupling/synergetic roles of tuning tribological behavior of MMNCs. Most importantly, this review combined the classical metal/alloy friction and wear theories and adapted them to give a (semi-)quantitative description of the detailed mechanisms of improved anti-friction and anti-wear performance in MMNCs. To guarantee the universal applications of these mechanisms, their links with the analyzed influencing factors (e.g., loading forces) and characteristic features like tribo-film have been clarified. This approach forms a solid basis for understanding, predicting, and engineering MMNCs’ tribological behavior, instead of pure phenomenology and experimental observation. Later, the pathway to achieve a broader application for MMNCs in tribo-related fields like smart materials, biomedical devices, energy storage, and electronics has been concisely discussed, with the focus on the potential development of modeling, experimental, and theoretical techniques in MMNCs’ tribological processes. In general, this review tries to elucidate the complex tribo-performances of MMNCs in a fundamentally universal yet straightforward way, and the discussion and summary in this review for the tribological performance in MMNCs could become a useful supplementary to and an insightful guidance for the current MMNC tribology study, research, and engineering innovations.
Fuzzy association rule mining approach to identify e-commerce product association considering sales amount
Authors: Dogan Onur , Kem Furkan Can , Oztaysi Basar 
Published: January 2022

AbstractOnline stores assist customers in buying the desired products online. Great competition in the e-commerce sector necessitates technology development. Many e-commerce systems not only present products but also offer similar products to increase online customer interest. Due to high product variety, analyzing products sold together similar to a recommendation system is a must. This study methodologically improves the traditional association rule mining (ARM) method by adding fuzzy set theory. Besides, it extends the ARM by considering not only items sold but also sales amounts. Fuzzy association rule mining (FARM) with the Apriori algorithm can catch the customers’ choice from historical transaction data. It discovers fuzzy association rules from an e-commerce company to display similar products to customers according to their needs in amount. The experimental result shows that the proposed FARM approach produces much information about e-commerce sales for decision-makers. Furthermore, the FARM method eliminates some traditional rules considering their sales amount and can produce some rules different from ARM.
Knowledge representation for explainable artificial intelligence
Authors: Borrego-Díaz Joaquín , Galán Páez Juan 
Published: January 2022

AbstractAlongside the particular need to explain the behavior of black box artificial intelligence (AI) systems, there is a general need to explain the behavior of any type of AI-based system (the explainable AI, XAI) or complex system that integrates this type of technology, due to the importance of its economic, political or industrial rights impact. The unstoppable development of AI-based applications in sensitive areas has led to what could be seen, from a formal and philosophical point of view, as some sort of crisis in the foundations, for which it is necessary both to provide models of the fundamentals of explainability as well as to discuss the advantages and disadvantages of different proposals. The need for foundations is also linked to the permanent challenge that the notion of explainability represents in Philosophy of Science. The paper aims to elaborate a general theoretical framework to discuss foundational characteristics of explaining, as well as how solutions (events) would be justified (explained). The approach, epistemological in nature, is based on the phenomenological-based approach to complex systems reconstruction (which encompasses complex AI-based systems). The formalized perspective is close to ideas from argumentation and induction (as learning). The soundness and limitations of the approach are addressed from Knowledge representation and reasoning paradigm and, in particular, from Computational Logic point of view. With regard to the latter, the proposal is intertwined with several related notions of explanation coming from the Philosophy of Science.
Semantic-guided autoencoder adversarial hashing for large-scale cross-modal retrieval
Authors: Li Mingyong , Li Qiqi , Ma Yan , Yang Degang 
Published: January 2022

AbstractWith the vigorous development of mobile Internet technology and the popularization of smart devices, while the amount of multimedia data has exploded, its forms have become more and more diversified. People’s demand for information is no longer satisfied with single-modal data retrieval, and cross-modal retrieval has become a research hotspot in recent years. Due to the strong feature learning ability of deep learning, cross-modal deep hashing has been extensively studied. However, the similarity of different modalities is difficult to measure directly because of the different distribution and representation of cross-modal. Therefore, it is urgent to eliminate the modal gap and improve retrieval accuracy. Some previous research work has introduced GANs in cross-modal hashing to reduce semantic differences between different modalities. However, most of the existing GAN-based cross-modal hashing methods have some issues such as network training is unstable and gradient disappears, which affect the elimination of modal differences. To solve this issue, this paper proposed a novel Semantic-guided Autoencoder Adversarial Hashing method for cross-modal retrieval (SAAH). First of all, two kinds of adversarial autoencoder networks, under the guidance of semantic multi-labels, maximize the semantic relevance of instances and maintain the immutability of cross-modal. Secondly, under the supervision of semantics, the adversarial module guides the feature learning process and maintains the modality relations. In addition, to maintain the inter-modal correlation of all similar pairs, this paper use two types of loss functions to maintain the similarity. To verify the effectiveness of our proposed method, sufficient experiments were conducted on three widely used cross-modal datasets (MIRFLICKR, NUS-WIDE and MS COCO), and compared with several representatives advanced cross-modal retrieval methods, SAAH achieved leading retrieval performance.
CARNet: Cascade attentive RefineNet for multi-lesion segmentation of diabetic retinopathy images
Authors: Guo Yanfei , Peng Yanjun 
Published: January 2022

AbstractDiabetic retinopathy is the leading cause of blindness in working population. Lesion segmentation from fundus images helps ophthalmologists accurately diagnose and grade of diabetic retinopathy. However, the task of lesion segmentation is full of challenges due to the complex structure, the various sizes and the interclass similarity with other fundus tissues. To address the issue, this paper proposes a cascade attentive RefineNet (CARNet) for automatic and accurate multi-lesion segmentation of diabetic retinopathy. It can make full use of the fine local details and coarse global information from the fundus image. CARNet is composed of global image encoder, local image encoder and attention refinement decoder. We take the whole image and the patch image as the dual input, and feed them to ResNet50 and ResNet101, respectively, for downsampling to extract lesion features. The high-level refinement decoder uses dual attention mechanism to integrate the same-level features in the two encoders with the output of the low-level attention refinement module for multiscale information fusion, which focus the model on the lesion area to generate accurate predictions. We evaluated the segmentation performance of the proposed CARNet on the IDRiD, E-ophtha and DDR data sets. Extensive comparison experiments and ablation studies on various data sets demonstrate the proposed framework outperforms the state-of-the-art approaches and has better accuracy and robustness. It not only overcomes the interference of similar tissues and noises to achieve accurate multi-lesion segmentation, but also preserves the contour details and shape features of small lesions without overloading GPU memory usage.
Intra-Site Structure of the Early Ahmarian Site of Al-Ansab 1, AH 1 (Jordan)
Authors: Schoenenberg Jonathan , Sauer Florian 
Published: January 2022

AbstractThe Early Ahmarian represents an Early Upper Palaeolithic cultural unit, which spans throughout the Levant to the Sinai Peninsula. At least 40 sites belong to this unit. Both open-air and cave sites provide different amounts of archaeological material at various spatial resolutions. The team of the Collaborative Research Centre 806 “Our Way to Europe” excavated the site of Al-Ansab 1, Wadi Sabra, since 2009. The site provides one of the largest lithic assemblages of the Early Ahmarian. Analysis of intra-site distributions and patterns has been conducted for a small number of sites, providing scarce information on the spatial makeup of Early Ahmarian occupation layers. The internal structure testifies to repeated settlement without task specialisation. While this has been described for the sites on the Sinai Peninsula, the situation has been unclear for locations placed in the escarpments of the Transjordanian Highlands. At Al-Ansab 1, we can observe the repeated, relatively ephemeral occupation of a specific location in the Wadi Sabra for the execution of various tasks such as processing of faunal elements and raw material exploitation. Our results correlate to a pattern of mobility observable at other Early Ahmarian sites such as Abu Noshra II. These sites are usually attributed to relatively small and highly mobile bands of hunter-gatherers. Analysing these patterns of intra-site and regional spatial behaviour in the context of environmental patterning highlights potential external drivers to the expression of human occupation at sites such as Al-Ansab 1, archaeological horizon 1.