bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Effect of Different Flaw Data to Machine Learning Powered Ultrasonic Inspection
Authors: Koskinen Tuomas , Virkkunen Iikka , Siljama Oskar , Jessen-Juhler Oskari 
Published: February 2021

AbstractPrevious research (Li et al., Understanding the disharmony between dropout and batch normalization by variance shift. CoRR abs/1801.05134 (2018).http://arxiv.org/abs/1801.05134arXiv:1801.05134) has shown the plausibility of using a modern deep convolutional neural network to detect flaws from phased-array ultrasonic data. This brings the repeatability and effectiveness of automated systems to complex ultrasonic signal evaluation, previously done exclusively by human inspectors. The major breakthrough was to use virtual flaws to generate ample flaw data for the teaching of the algorithm. This enabled the use of raw ultrasonic scan data for detection and to leverage some of the approaches used in machine learning for image recognition. Unlike traditional image recognition, training data for ultrasonic inspection is scarce. While virtual flaws allow us to broaden the data considerably, original flaws with proper flaw-size distribution are still required. This is of course the same for training human inspectors. The training of human inspectors is usually done with easily manufacturable flaws such as side-drilled holes and EDM notches. While the difference between these easily manufactured artificial flaws and real flaws is obvious, human inspectors still manage to train with them and perform well in real inspection scenarios. In the present work, we use a modern, deep convolutional neural network to detect flaws from phased-array ultrasonic data and compare the results achieved from different training data obtained from various artificial flaws. The model demonstrated good generalization capability toward flaw sizes larger than the original training data, and the effect of the minimum flaw size in the data set affects the$$a_{90/95}$$a90/95value. This work also demonstrates how different artificial flaws, solidification cracks, EDM notch and simple simulated flaws generalize differently.
Building Social Cohesion Through Intergroup Contact: Evaluation of a Large-Scale Intervention to Improve Intergroup Relations Among Adolescents
Authors: Reimer Nils Karl , Love Angelika , Wölfer Ralf , Hewstone Miles 
Published: February 2021

AbstractPast research has found intergroup contact to be a promising intervention to reduce prejudice and has identified adolescence as the developmental period during which intergroup contact is most effective. Few studies, however, have tested whether contact-based interventions can be scaled up to improve intergroup relations at a large scale. The present research evaluated whether and when the National Citizen Service, a large-scale contact-based intervention reaching one in six 15- to 17-year-olds in England and Northern Ireland, builds social cohesion among adolescents from different ethnic backgrounds. In a diverse sample of adolescents (N = 2099; Mage = 16.37, age range: 15–17 years; 58% female), this study used a pretest–posttest design with a double pretest to assess the intervention’s effectiveness. Controlling for test–retest effects, this study found evidence that the intervention decreased intergroup anxiety and increased outgroup perspective-taking—but not that it affected intergroup attitudes, intergroup trust, or perceptions of relative (dis-)advantage. These (small) effects were greater for adolescents who had experienced less positive contact before participating and who talked more about group differences while participating. These findings suggest that the intervention might not immediately improve intergroup relations—but that it has the potential to prepare adolescents, especially those with less positive contact experiences before the intervention, for more positive intergroup interactions in the future.
Application of single-cell sequencing technologies in pancreatic cancer
Authors: Mannarapu Mastan , Dariya Begum , Bandapalli Obul Reddy 
Published: February 2021

AbstractPancreatic cancer (PC) is the third lethal disease for cancer-related mortalities globally. This is mainly because of the aggressive nature and heterogeneity of the disease that is diagnosed only in their advanced stages. Thus, it is challenging for researchers and clinicians to study the molecular mechanism involved in the development of this aggressive disease. The single-cell sequencing technology enables researchers to study each and every individual cell in a single tumor. It can be used to detect genome, transcriptome, and multi-omics of single cells. The current single-cell sequencing technology is now becoming an important tool for the biological analysis of cells, to find evolutionary relationship between multiple cells and unmask the heterogeneity present in the tumor cells. Moreover, its sensitivity nature is found progressive enabling to detect rare cancer cells, circulating tumor cells, metastatic cells, and analyze the intratumor heterogeneity. Furthermore, these single-cell sequencing technologies also promoted personalized treatment strategies and next-generation sequencing to predict the disease. In this review, we have focused on the applications of single-cell sequencing technology in identifying cancer-associated cells like cancer-associated fibroblast via detecting circulating tumor cells. We also included advanced technologies involved in single-cell sequencing and their advantages. The future research indeed brings the single-cell sequencing into the clinical arena and thus could be beneficial for diagnosis and therapy of PC patients.
A hybridization of SKH and RKFCM clustering optimization algorithm for efficient moving object exploration
Authors: Mahalingam T. 
Published: February 2021

AbstractObject detection is a really crucial application of image processing. It is of essential value for object active surveillance and various other applications. Hence, the object detection has been extensively investigated. Refined Kernel fuzzy c-means system still carries a couple of downsides, for instance, to reduce the convergence level, obtaining stuck in the regional area minima and problem to initiation level of sensitiveness. To conquer the over problems, the following suggested strategy for stud krill herd Clustering Optimization Algorithm. This paper stands for an optimizing approach to global optimizing utilizing a unique variation of KH (Krill Herd). This approach is termed as Stud Krill Herd (SKH).The stud krill herd Clustering Optimization procedure utilizes to find the optimal centroid. At first, the background and foreground area partition is finished by hybridization of refined kernel fuzzy c means algorithm (RKFCM) with stud krill herd Clustering Optimization procedure. The suggested new strategy is scholarly and furthermore dynamic clustering system for dividing the moving object. This research study performs recommended a reliable object detection making use of hybridization of stud krill herd Clustering optimizing and RKFCM. Moving object tracing is done via the blob detection which happens under the tracing phase. The assessment phase has characteristic abstraction and categorization. High and appearance-based and quality based attributes are mined from fine-tuned frames whichever attended to classification. Considering that categorization we are developing usage of J48 (C4.5) i.e., decision tree based classification. The effectiveness of the advised method is analyzed through prior approaches k-NN and MLP in regard to accuracy, f-measure, ROC and recall.
Data integration by two-sensors in a LEAP-based Virtual Glove for human-system interaction
Authors: Placidi Giuseppe , Avola Danilo , Cinque Luigi , Polsinelli Matteo , Theodoridou Eleni , Tavares João Manuel R. S. 
Published: February 2021

AbstractVirtual Glove (VG) is a low-cost computer vision system that utilizes two orthogonal LEAP motion sensors to provide detailed 4D hand tracking in real–time. VG can find many applications in the field of human-system interaction, such as remote control of machines or tele-rehabilitation. An innovative and efficient data-integration strategy, based on the velocity calculation, for selecting data from one of the LEAPs at each time, is proposed for VG. The position of each joint of the hand model, when obscured to a LEAP, is guessed and tends to flicker. Since VG uses two LEAP sensors, two spatial representations are available each moment for each joint: the method consists of the selection of the one with the lower velocity at each time instant. Choosing the smoother trajectory leads to VG stabilization and precision optimization, reduces occlusions (parts of the hand or handling objects obscuring other hand parts) and/or, when both sensors are seeing the same joint, reduces the number of outliers produced by hardware instabilities. The strategy is experimentally evaluated, in terms of reduction of outliers with respect to a previously used data selection strategy on VG, and results are reported and discussed. In the future, an objective test set has to be imagined, designed, and realized, also with the help of an external precise positioning equipment, to allow also quantitative and objective evaluation of the gain in precision and, maybe, of the intrinsic limitations of the proposed strategy. Moreover, advanced Artificial Intelligence-based (AI-based) real-time data integration strategies, specific for VG, will be designed and tested on the resulting dataset.
Doubly derivatized poly(lactide)–albumin nanoparticles as blood vessel-targeted transport device for magnetic resonance imaging (MRI)
Authors: Pashkunova-Martic Irena , Kremser Christian , Talasz Heribert , Mistlberger Klaudia , Bechter-Hugl Beate , Pfaller Kristian , Baurecht Dieter , Debbage Paul , Jaschke Werner , Helbich Thomas H. , Keppler Bernhard 
Published: February 2021

AbstractMolecular imaging using magnetic resonance imaging (MRI) is expected to play a crucial future role in oncological diagnosis and in monitoring of therapeutic progress. Targeted nanoparticle contrast media (CM) with high relaxivities are required in order to obtain adequate signal-to-noise ratios as well as visualization of a desired pathologic area of the human body. The aims of this study were to synthesize and define certain physicochemical and enhancement properties of new doubly derivatized polylactic acid–bovine serum albumin (PLA-BSA) nanoparticles (NPs) modified by the covalent coupling of glutaraldehyde as a crosslinking agent. An additional functionalization with endothelial cells (ECs) targeting groups (tomato lectins; LEA) and signal-emitting moieties (DTPA-Gd) enables its use as a macromolecular, biodegradable contrast agent for MRI. The NPs were characterized by different spectroscopies, size exclusion chromatography, and scanning and transmission electron microscopy. In a human vein model, the dynamics of the nanoparticle interactions with the vein wall were examined in MRI, with correlative imaging in electron microscopy. In vitro studies were conducted to show endothelial binding and persistent enhancement at the apical EC surface. NPs with a diameter between 55 and 75 nm, able to carry simultaneous signal emitting, and targeting motifs on a single construct were successfully prepared. A high Gd payload and endothelial binding to blood vessel walls were observed. The binding affinity and specificity of LEA was preserved, and a strong enhancement at the endothelium was achieved. The stabilized core–shell structure of PLA-NP might allow for further encapsulation of lipophilic drugs or for attachment of other targeting molecules, such as antibodies.
Graphical abstract
Event-triggering $${H}_{\infty }$$-based observer combined with NN for simultaneous estimation of vehicle sideslip and roll angles with network-induced delays
Authors: Boada Maria Jesus L. , Boada Beatriz L. , Zhang Hui 
Published: February 2021

AbstractNowadays, vehicles are being fitted with systems that improve their maneuverability, stability, and comfort in order to reduce the number of accidents. Improving these aspects is of particular interest thanks to the incorporation of autonomous vehicles onto the roads. The knowledge of vehicle sideslip and roll angles, which are among the main causes of road accidents, is necessary for a proper design of a lateral stability and roll-over controller system. The problem is that these two variables cannot be measured directly through sensors installed in current series production vehicles due to their high costs. For this reason, their estimation is fundamental. In addition, there is a time delay in the relaying of information between the different vehicle systems, such as, sensors, actuators and controllers, among others. This paper presents the design of an $${H}_{\infty }$$

H
∞

-based observer that simultaneously estimates both the sideslip angle and the roll angle of a vehicle for a networked control system, with networked transmission delay based on an event-triggered communication scheme combined with neural networks (NN). To deal with the vehicle nonlinearities, NN and linear-parameter-varying techniques are considered alongside uncertainties in parameters. Both simulation and experimental results are carried out to prove the performance of observer design.
Investigating modes of being in the world: an introduction to Phenomenologically grounded qualitative research
Authors: Køster Allan , Fernandez Anthony Vincent 
Published: February 2021

AbstractIn this article, we develop a new approach to integrating philosophical phenomenology with qualitative research. The approach uses phenomenology’s concepts, namely existentials, rather than methods such as the epoché or reductions. We here introduce the approach to both philosophers and qualitative researchers, as we believe that these studies are best conducted through interdisciplinary collaboration. In section 1, we review the debate over phenomenology’s role in qualitative research and argue that qualitative theorists have not taken full advantage of what philosophical phenomenology has to offer, thus motivating the need for new approaches. In section 2, we introduce our alternative approach, which we call Phenomenologically Grounded Qualitative Research (PGQR). Drawing parallels with phenomenology’s applications in the cognitive sciences, we explain how phenomenological grounding can be used to conceptually front-load a qualitative study, establishing an explicit focus on one or more structures of human existence, or of our being in the world. In section 3, we illustrate this approach with an example of a qualitative study carried out by one of the authors: a study of the existential impact of early parental bereavement. In section 4, we clarify the kind of knowledge that phenomenologically grounded studies generate and how it may be integrated with existing approaches.
Current status and impending progress for cassava structural genomics
Authors: Lyons Jessica B. , Bredeson Jessen V. , Mansfeld Ben N. , Bauchet Guillaume Jean , Berry Jeffrey , Boyher Adam , Mueller Lukas A. , Rokhsar Daniel S. , Bart Rebecca S. 
Published: February 2021

Key message
We demystify recent advances in genome assemblies for the heterozygous staple crop cassava (Manihot esculenta), and highlight key cassava genomic resources.

Abstract
Cassava, Manihot esculenta Crantz, is a crop of societal and agricultural importance in tropical regions around the world. Genomics provides a platform for accelerated improvement of cassava’s nutritional and agronomic traits, as well as for illuminating aspects of cassava’s history including its path towards domestication. The highly heterozygous nature of the cassava genome is widely recognized. However, the full extent and context of this heterozygosity has been difficult to reveal because of technological limitations within genome sequencing. Only recently, with several new long-read sequencing technologies coming online, has the genomics community been able to tackle some similarly difficult genomes. In light of these recent advances, we provide this review to document the current status of the cassava genome and genomic resources and provide a perspective on what to look forward to in the coming years.
A mixed methods approach to the social assessment of transport infrastructure projects
Authors: Lucas Karen , Philips Ian , Verlinghieri Ersilia 
Published: February 2021

AbstractIn this paper, we propose a mixed methods quantitative and qualitative approach to capture fully the measurable and less tangible social impacts of transport projects on local people and communities. The approach was used to assess the potential social impacts of a strategic road by-pass project case study in a deprived region of Wales in the UK. The project specifically aimed to stimulate local economic growth and regeneration in the local areas it serves. In a ‘before and after’ case study, we combined fine-grained, GIS-based spatial analysis of secondary datasets with qualitative participative exercises with the local residents of the five communities living adjacent to the road, and interviews with professional local stakeholders. This mixed methods approach significantly enhanced understanding of both the social benefits and disbenefits of the road project. It helped to reveal local concerns that would not otherwise have been apparent from secondary dataset analysis alone. The qualitative studies were also successful in bringing to the table new ‘hard to reach’ voices that had not been heard through the formal consultation and public engagement process. The study revealed that the social benefits accruing to local people from the project could have been significantly enhanced, whilst a number of its locally occurring negative social impacts could have been avoided had social assessment been employed earlier in the decision processes concerning its routing and design. Recommendations to improve the practice and uptake of social assessments at the option appraisal, project design mitigation and post evaluation stages of transport projects are included in the paper.
Estimating persistence for irregularly spaced historical data
Authors: Franses Philip Hans 
Published: February 2021

AbstractThis paper introduces to the literature on Economic History a measure of persistence which is particularly useful when the data are irregularly spaced. An illustration to ten historical unevenly spaced data series for Holland of 1738 to 1779 shows the merits of the methodology. It is found that the weight of slave-based contribution in that period has grown with a deterministic trend pattern.
Another generalization of Euler’s arithmetic function and Menon’s identity
Authors: Tóth László 
Published: February 2021

AbstractWe define the k-dimensional generalized Euler function $$\varphi _k(n)$$

φ
k

(
n
)

as the number of ordered k-tuples $$(a_1,\ldots ,a_k)\in {\mathbb {N}}^k$$

(

a
1

,
…
,

a
k

)

∈

N

k

such that $$1\le a_1,\ldots ,a_k\le n$$

1
≤

a
1

,
…
,

a
k

≤
n

and both the product $$a_1\cdots a_k$$

a
1

⋯

a
k

and the sum $$a_1+\cdots +a_k$$

a
1

+
⋯
+

a
k

are prime to n. We investigate some of the properties of the function $$\varphi _k(n)$$

φ
k

(
n
)

, and obtain a corresponding Menon-type identity.
Mapping the intellectual structure of GIS-T field (2008–2019): a dynamic co-word analysis
Authors: Hosseini Seyedmohammadreza , Baziyad Hamed , Norouzi Rasoul , Jabbedari Khiabani Sheida , Gidófalvi Győző , Albadvi Amir , Alimohammadi Abbas , Seyedabrishami Seyedehsan 
Published: February 2021

AbstractUsing geographic information systems (GIS) widely for dealing with transportation problems (is well-known as GIS-T), has made it nessasary for researchers to discover the current state-of-the-art and predict the trends of future research. This paper aims to contribute to a better understanding of GIS-T research area from a longitudinal perspective, over the period 2008–2019. A co-word analysis was used to illustrate all the underlying subfields of GIS-T based on published papers in the Web of Science (WoS) database service. The main knowledge areas representing the intellectual structure of GIS-T including (a) sustainability, (b) health, (c) planning and management, and (d) methods and tools, were detected. Finally, in order to illustrate the structure and development of the identified clusters, two-dimensional maps and strategic diagrams for each period were drawn. This study is the first attempt to employ a text mining method so as to detect the conceptual structure of GIS-T research area from a complex and interdisciplinary literature.
Mars Mineralogical Spectrometer (MMS) on the Tianwen-1 Mission
Authors: He Zhiping , Xu Rui , Li Chunlai , Yuan Liyin , Liu Chengyu , Lv Gang , Jin Jian , Xie Jianan , Kong Chuifeng , Li Feifei , Chen Xiaowen , Wang Rong , Xu Sheng , Pan Wei , Wu Jincai , Li Changkun , Wang Tianhong , Jin Haijun , Chen Hourui , Qiu Jun , Wang Jianyu 
Published: February 2021

AbstractThe Mars Mineralogical Spectrometer (MMS) is a hyperspectral imager onboard the Mars orbiter of Tianwen-1, China’s first Mars exploration mission. MMS consists of 4 subassemblies: an Optical Sensor Unit (OSU), an Electronics Unit (EU), a Calibration Unit (CU), and a Thermal Control Accessories (TCA). With a 0.5 mrad IFOV and a 416-sample cell array for nadir observation, MMS can map the spectral and spatial information of the Martian surface through push-broom scanning, and it can transmit scientific data by hyperspectral mode or multispectral imaging mode through spatial and spectral combination. MMS can perform multi-sample hyperspectral imaging at full spectral resolution (0.379–1.076 μm with 2.73 nm/band, 1.033–3.425 μm at 7.5 nm/band, both spectral ranges at 2.1 km/pixel at 265 km). For the wavelength region of interest, the multispectral mapping mode provides additional options, a subset of 72 bands that are binned to minimum pixel footprints of 265 m/pixel. The major objective of the MMS is to analyze the compositions and distributions of the minerals on Martian surface, in order to characterize its evolution.
A Review of Indoor Localization Techniques and Wireless Technologies
Authors: Obeidat Huthaifa , Shuaieb Wafa , Obeidat Omar , Abd-Alhameed Raed 
Published: February 2021

AbstractThis paper introduces a review article on indoor localization techniques and technologies. The paper starts with current localization systems and summarizes comparisons between these systems in terms of accuracy, cost, advantages, and disadvantages. Also, the paper presents different detection techniques and compare them in terms of accuracy and cost. Finally, localization methods and algorithms, including angle of arrival (AOA), time of arrival (TOA), and recived signal strength (RSS) are introduced. The study contains concepts, requirements, and specifications for each category of methods presents pros and cons for investigated methods, and conducts comparisons between them.