bluuebunny/crossref_metadata_2025_split huggingface dataset:
Automatic configuration of the reference point method for fully automated multi‐objective treatment planning applied to oropharyngeal cancer
Authors: van Haveren Rens , Heijmen Ben J. M. , Breedveld Sebastiaan 
Published: February 2020

PurposeIn automated treatment planning, configuration of the underlying algorithm to generate high‐quality plans for all patients of a particular tumor type can be a major challenge. Often, a time‐consuming trial‐and‐error tuning procedure is required. The purpose of this paper is to automatically configure an automated treatment planning algorithm for oropharyngeal cancer patients.MethodsRecently, we proposed a new procedure to automatically configure the reference point method (RPM), a fast automatic multi‐objective treatment planning algorithm. With a well‐tuned configuration, the RPM generates a single Pareto optimal treatment plan with clinically favorable trade‐offs for each patient. The automatic configuration of the RPM requires a set of computed tomography (CT) scans with corresponding dose distributions for training. Previously, we demonstrated for prostate cancer planning with 12 objectives that training with only 9 patients resulted in high‐quality configurations. This paper further develops and explores the new automatic RPM configuration procedure for head and neck cancer planning with 22 objectives. Investigations were performed with planning CT scans of 105 previously treated unilateral or bilateral oropharyngeal cancer patients together with corresponding Pareto optimal treatment plans. These plans were generated with our clinically applied two‐phase ε‐constraint method (Erasmus‐iCycle) for automated multi‐objective treatment planning, ensuring consistent high quality and Pareto optimality of all plans. Clinically relevant, nonconvex criteria, such as dose‐volume parameters and NTCPs, were included to steer the RPM configuration.ResultsTraining sets with 20–50 patients were investigated. Even with 20 training plans, high‐quality configurations of the RPM were feasible. Automated plan generation with the automatically configured RPM resulted in Pareto optimal plans with overall similar or better quality than that of the Pareto optimal database plans.ConclusionsAutomatic configuration of the RPM for automated treatment planning is feasible and drastically reduces the time and workload required when compared to manual tuning of an automated treatment planning algorithm.
Electron spin relaxation time of Ni(II) ion in hexapyrazole zinc(II) dinitrate at 300 K
Authors: K Amrutha , Kathirvelu Velavan 
Published: February 2020

AbstractUnderstanding the electron spin relaxation properties of paramagnetic species is a fundamental requirement to use them as a probe to measure distances between sites in biomolecules by electron paramagnetic resonance (EPR) spectroscopy. Even though Ni(II) ion is an essential trace element for many species, relaxation properties are not well understood. Herein, the polycrystalline sample of Ni(II) ion magnetically diluted in Zn(Pyrazole)6(NO3)2 (Ni/ZPN) has been studied in detail by EPR spectroscopy to explore the electron spin relaxation time. Progressive continuous‐wave (CW) EPR power saturation study on Ni/ZPN at 300 K yielded 907 mW as the P1/2 value. The cavity constant (KQ) has been calculated using tempol in PVA‐BA glass matrix and the product of electron spin‐lattice relaxation time (T1) and spin–spin relaxation time (T2) for Ni/ZPN at 300 K has been reported for the first time.
Deletion of the mouse X‐linked Prame gene causes germ cell reduction in spermatogenesis
Authors: Lu Chen , Yang Mingyao , Rossi Randall M. , Wang Aihua , Feitosa Weber B. , Diaz Francisco J. , Liu Wan‐Sheng 
Published: February 2020

AbstractPreferentially expressed antigen in melanoma (PRAME) is cancer/testis antigen and a transcriptional repressor, inhibiting the signaling of retinoic acid through the retinoic acid receptor (RAR) for promoting cell proliferation and preventing cell apoptosis in cancer cells. The role of PRAME in testis and germline is unknown. We report here the generation and characterization of an X‐linked Prame conditional knockout (cKO) mouse. Although fertile, the testis size (p < .01) and sperm count (p < .05) of the Prame cKO mice were significantly reduced by 12% at 4 months of age compared with the Prame floxed mice. Histological, immunofluorescence with germ cell‐specific markers and terminal deoxynucleotidyl transferase dUTP nick end labeling analyses of testis cross‐sections at postnatal day 7 (P7), P14, P21, P35, P120, and P365 indicated a significant increase in apoptotic germ cells at P7 and P14 and an increase in abnormal seminiferous tubules at P21 and P35. Germ cells were gradually lost resulting in two different phenotypes in the Prame cKO testes: Sertoli‐cell‐only for some of the affected tubules in young mice (at P35) and germ cell arrest at spermatogonia stage for other affected tubules in mature mice. Both phenotypes were a consequence of disruption in RAR signaling pathway by the depletion of Prame at a different time point during the first and subsequent rounds of spermatogenesis. The results suggest that Prame plays a minor, but important role in spermatogenesis and different paralogs in the Prame gene family may be functionally and partially redundant.
Stochastic production capacity: A bane or a boon for quick response supply chains?
Authors: Zhang Juzhi , Choi Tsan‐Ming , Cheng T. C. E. 
Published: February 2020

AbstractThe quick response (QR) system that can cope with demand volatility by shortening lead time has been well studied in the literature. Much of the existing literature assumes implicitly or explicitly that the manufacturers under QR can always meet the demand because the production capacity is always sufficient. However, when the order comes with a short lead time under QR, availability of the manufacturer's production capacity is not guaranteed. This motivates us to explore QR in supply chains with stochastic production capacity. Specifically, we study QR in a two‐echelon supply chain with Bayesian demand information updating. We consider the situation where the manufacturer's production capacity under QR is uncertain. We first explore how stochastic production capacity affects supply chain decisions and QR implementation. We then incorporate the manufacturer's ability to expand capacity into the model. We explore how the manufacturer determines the optimal capacity expansion decision, and the value of such an ability to the supply chain and its agents. Finally, we extend the model to the two‐stage two‐ordering case and derive the optimal ordering policy by dynamic programming. We compare the single‐ordering and two‐ordering cases to generate additional managerial insights about how ordering flexibility affects QR when production capacity is stochastic. We also explore the transparent supply chain and find that our main results still hold.
Content placement in 5G‐enabled edge/core data center networks resilient to link cut attacks
Authors: Natalino Carlos , de Sousa Amaro , Wosinska Lena , Furdek Marija 
Published: February 2020

AbstractHigh throughput, resilience, and low latency requirements drive the development of 5G‐enabled content delivery networks (CDNs) which combine core data centers (cDCs) with edge data centers (eDCs) that cache the most popular content closer to the end users for traffic load and latency reduction. Deployed over the existing optical network infrastructure, CDNs are vulnerable to link cut attacks aimed at disrupting the overlay services. Planning a CDN to balance the stringent service requirements and increase resilience to attacks in a cost‐efficient way entails solving the content placement problem (CPP) across the cDCs and eDCs. This article proposes a framework for finding Pareto‐optimal solutions with minimal user‐to‐content distance and maximal robustness to targeted link cuts, under a defined budget. We formulate two optimization problems as integer linear programming (ILP) models. The first, denoted as K‐best CPP with minimal distance (K‐CPP‐minD), identifies the eDC/cDC placement solutions with minimal user‐to‐content distance. The second performs critical link set detection to evaluate the resilience of the K‐CPP‐minD solutions to targeted fiber cuts. Extensive simulations verify that the eDC/cDC selection obtained by our models improves network resilience to link cut attacks without adversely affecting the user‐to‐content distances or the core network traffic mitigation benefits.
Processing and wear response study of glass‐polyester composites with waste marble dust as particulate filler
Authors: Nayak Sandip K. , Satapathy Alok , Mantry Sisir 
Published: February 2020

AbstractProper management of any waste lies in using its potential in the development of some value added products. In line with this, the present research has explored the use of marble dust, an industrial/construction waste as a secondary filler in the glass‐polyester material system to prepare wear‐resistant hybrid composites. Such hybrid composites are fabricated through a simple hand layup route. The composites are characterized in regard to their density and porosity. Mechanical properties, such as tensile and flexural strength, are evaluated under controlled laboratory conditions. Dry sliding wear trials are conducted under different test conditions using a pin‐on‐disc test rig as per ASTM G 99‐05 following Taguchi's L25 orthogonal array. Significant control factors influencing the specific wear rates (SWRs) are identified and an optimal factor setting based on minimum wear is found out. Scanning electron microscopy of the worn composite surfaces is done to ascertain the possible wear mechanisms. Analysis revealed that the incorporation of filler helps in reducing the wear rate of the composites. Thus, the wear resistance of glass‐polyester composites is improved significantly by the incorporation of marble dust. Furthermore, a prediction model based on artificial neural networks is developed to estimate the SWR within and beyond the experimental domain.
Refined protocol for δ13C analysis of calcite and dolomite in carbonate mixture samples
Authors: Du Yong , Song Huyue 
Published: February 2020

RationaleThe carbon isotope composition of carbonates is widely used in petrology and paleoenvironments as a proxy for carbon sources and environmental parameters during mineral formation or late diagenesis. However, most carbonate minerals in nature are complicated mixtures (i.e., coexisting calcite and dolomite). Precise separation of individual signals in mixed carbonate minerals is essential to obtain information regarding these indexes because of the diverse isotopic behavior of different minerals.MethodsThe conditions for pretreating calcite–dolomite mixtures to determine each of their δ13C values were optimized with a series of experiments varying the purging and reaction conditions using an isotope ratio mass spectrometer equipped with an online GasBench II interface. Sequential phosphoric acid reactions of pure calcite and dolomite were performed to measure the characteristics of single minerals under different temperatures and reaction times. Artificial mixtures with varied proportions of calcite and dolomite were used to verify the precision of the proposed method.ResultsThe optimized pretreatment conditions for δ13C analysis of calcite in the mixture involved purging the sample bottle using helium and then reacting it with 99% H3PO4 for 100 min in a cold water bath at 2°C. The optimized pretreatment conditions for δ13C analysis of dolomite in the mixture involved purging the sample bottle using helium gas after δ13Ccal measurement and reacting it with H3PO4 on a heating plate for 10 h at 45°C.ConclusionsThis study introduced a workflow with ultimate precision for the selective δ13C measurements of calcite–dolomite mixtures combining a GasBench II with a continuous flow isotope ratio mass spectrometer.
Field of experts optimization‐based noisy image retrieval
Authors: Guo Junqi , Shen Guicheng , Sun Yichen , Zhao Jin , Wu Hao , Zhu Zhilin 
Published: February 2020

SummaryThe value of image retrieval has become more and more prominent in the era of big data. However, large numbers of images are missed from current method since the image retrieval precision largely depends on the high quality of images. By common methodology, when the quality of images decreases a little, the accuracy of retrieval would decrease significantly. In particular, it is difficult to retrieve noisy images effectively by conventional approach. Yet large number of the noisy images could not be ignored at the age of data explosion. Aiming at the problem above, we proposed noisy image retrieval model based on field of experts (FoE) optimization. High‐quality learning images could be selected by sparse coding, which is based on similarity calculation model, and the multioption filter combination model enhances the power of FoE model. We set up a database containing a large numbers of noisy images. Over this database, adequate groups of experiments are conducted. The verification of the method concluded its effectiveness and superiority.
Effect of add‐on administration of kamikihito with donepezil monotherapy in a patient with Alzheimer's disease
Authors: Ishida Kazuyuki 
Published: February 2020

ABSTRACTCaseA 69‐year‐old male presented with a two‐year history of memory decline. Results of his cognitive function tests suggested cognitive impairment and brain magnetic resonance imaging showed cortical atrophy, predominantly in the temporal lobes. Based on these findings, he was diagnosed with Alzheimer's disease.OutcomeAlthough treatment with donepezil was commenced, the patient's cognitive function deteriorated in the year after initiation. However, his cognitive impairment improved in the year after add‐on administration of kamikihito, a traditional Japanese herbal medicine, with donepezil monotherapy.ConclusionCombination therapy with donepezil and kamikihito seems to be beneficial and worth considering for patients who are secondarily non‐responsive to donepezil monotherapy.
Path integration in a three-dimensional world: the case of desert ants
Authors: Ronacher Bernhard 
Published: February 2020

AbstractDesert ants use path integration to return from foraging excursions on a shortcut way to their nests. Intriguingly, when walking over hills, the ants incorporate the ground distance, the paths’ projection to the horizontal plane, into their path integrator. This review discusses howCataglyphismay solve this computational feat. To infer ground distance, ants must incorporate the inclination of path segments into the assessment of distance. Hair fields between various joints have been eliminated as likely sensors for slope measurement, without affecting slope detection; nor do postural adaptations or changes in gait provide the relevant information. Changes in the sky’s polarization pattern due to different head inclinations on slopes were ruled out as cues. Thus, the mechanisms by which ants may measure slopes still await clarification. Remarkably, the precision of slope measurement is roughly constant up to a 45° inclination, but breaks down at 60°. An encounter of sloped path segments during a foraging trip induces a general acceptance of slopes, however, slopes are not associated with specific values of the home vector. All current evidence suggests thatCataglyphisdoes not compute a vector in 3-D: path integration seems to operate exclusively in the horizontal plane.
Overloaded! Critical revision and a new conceptual approach for snow indicators in ski tourism
Authors: Abegg B. , Morin S. , Demiroglu O. C. , François H. , Rothleitner M. , Strasser U. 
Published: February 2020

AbstractIndicators are widely used in climate variability and climate change assessments to simplify the tracking of complex processes and phenomena in the state of the environment. Apart from the climatic criteria, the snow indicators in ski tourism have been increasingly extended with elements that relate to the technical, operational, and commercial aspects of ski tourism. These non-natural influencing factors have gained in importance in comparison with the natural environmental conditions but are more difficult to comprehend in time and space, resulting in limited explanatory power of the related indicators when applied for larger/longer scale assessments. We review the existing indicator approaches to derive quantitative measures for the snow conditions in ski areas, to formulate the criteria that the indicators should fulfill, and to provide a list of indicators with their technical specifications which can be used in snow condition assessments for ski tourism. For the use of these indicators, a three-step procedure consisting of definition, application, and interpretation is suggested. We also provide recommendations for the design of indicator-based assessments of climate change effects on ski tourism. Thereby, we highlight the importance of extensive stakeholder involvement to allow for real-world relevance of the achieved results.
Multiparametric radiomics methods for breast cancer tissue characterization using radiological imaging
Authors: Parekh Vishwa S. , Jacobs Michael A. 
Published: February 2020

Abstract
Background and purpose
Multiparametric radiological imaging is vital for detection, characterization, and diagnosis of many different diseases. Radiomics provide quantitative metrics from radiological imaging that may infer potential biological meaning of the underlying tissue. However, current methods are limited to regions of interest extracted from a single imaging parameter or modality, which limits the amount of information available within the data. This limitation can directly affect the integration and applicable scope of radiomics into different clinical settings, since single image radiomics are not capable of capturing the true underlying tissue characteristics in the multiparametric radiological imaging space. To that end, we developed a multiparametric imaging radiomic (mpRad) framework for extraction of first and second order radiomic features from multiparametric radiological datasets.

Methods
We developed five different radiomic techniques that extract different aspects of the inter-voxel and inter-parametric relationships within the high-dimensional multiparametric magnetic resonance imaging breast datasets. Our patient cohort consisted of 138 breast patients, where, 97 patients had malignant lesions and 41 patients had benign lesions. Sensitivity, specificity, receiver operating characteristic (ROC) and areas under the curve (AUC) analysis were performed to assess diagnostic performance of the mpRad parameters. Statistical significance was set at p < 0.05.

Results
The mpRad features successfully classified malignant from benign breast lesions with excellent sensitivity and specificity of 82.5% and 80.5%, respectively, with Area Under the receiver operating characteristic Curve (AUC) of 0.87 (0.81–0.93). mpRad provided a 9–28% increase in AUC metrics over single radiomic parameters.

Conclusions
We have introduced the mpRad framework that extends radiomic analysis from single images to multiparametric datasets for better characterization of the underlying tissue biology.
Learning Mathematics Problem Solving through Test Practice: a Randomized Field Experiment on a Global Scale
Authors: Avvisati Francesco , Borgonovi Francesca 
Published: February 2020

AbstractWe measure the effect of a single test practice on 15-year-old students’ ability to solve mathematics problems using large, representative samples of the schooled population in 32 countries. We exploit three unique features of the 2012 administration of the Programme for International Student Assessment (PISA), a large-scale, low-stakes international assessment. During the 2012 PISA administration, participating students were asked to sit two separate tests consisting of problem-solving tasks. Both tests included questions that covered the same internationally recognized and validated framework for mathematics assessment. Students were randomly assigned in the first, 2-h-long test to one of three test versions containing varying amounts of mathematics, reading, and science problems. We found that the amount of mathematics problems in the first test had a small positive effect on mean mathematics performance on the second test, but no effect on general reasoning and problem-solving ability. Subject-specific effects of test practice on subsequent test performance were found over both short lags (same day) and medium lags (1–7 days). The learning gains ascribed to mathematics problem-solving practice were larger for boys than for girls.
On the Tension Between Physics and Mathematics
Authors: Rédei Miklós 
Published: February 2020

AbstractBecause of the complex interdependence of physics and mathematics their relation is not free of tensions. The paper looks at how the tension has been perceived and articulated by some physicists, mathematicians and mathematical physicists. Some sources of the tension are identified and it is claimed that the tension is both natural and fruitful for both physics and mathematics. An attempt is made to explain why mathematical precision is typically not welcome in physics.
A Closeness- and Priority-Based Logical Study of Social Network Creation
Authors: Smets Sonja , Velázquez-Quesada Fernando R. 
Published: February 2020

AbstractThis paper is part of an on-going programme on the study of the logical aspects of social network formation. It recalls the so-calledsocial networkmodel, discussing the properties of a notion ofclosenessbetween agents (in terms of the number of traits they have in common); then introduces anextended social networkmodel in which different agents might assign different values to different traits, discussing the properties of the notion ofweighted closenessthat arises. These notions are used to define social network creation operations by means of athresholdstrategy. The paper studies the properties of the social networks the updates create, providing sound and complete axiom systems for formal languages describing these updates’ effects.
Quantitative trait loci analysis of potato tuber greening
Authors: Plich Jarosław , Zimnoch-Guzowska Ewa , Tatarowska Beata , Śliwka Jadwiga 
Published: February 2020

AbstractA conversion of amyloplasts into chloroplasts in the potato tuber after light exposure is known as tuber greening and is one of the major causes of tuber loss. We report here the first mapping of the factors affecting tuber greening in potato. We used an F1 mapping population of diploid potatoes and DArTseq™ markers to construct a genetic map. The individuals of the mapping population, parents and standards were phenotyped for two tuber greening parameters: external tuber greening and internal greening depth on 0–5 scales in three years 2015, 2016 and 2018. The results were used for the analysis of Quantitative Trait Loci (QTLs) by an interval QTL mapping. Two most important QTLs were covering large regions of chromosomes VII and X and had the strongest effect on both greening parameters in data sets obtained in particular years and in the mean data set. Variance observed in the mean tuber greening could be ascribed in 16.9% to the QTL on chromosome VII and in 23.4% to the QTL on chromosome X. The QTL on chromosome VII explained 13.1%, while the QTL on chromosome X explained up to 17.7% of the variance in the mean tuber greening depth. Additional, minor QTLs were year- and/or trait-specific. The QTLs on chromosomes VII and X determine big parts of the observed tuber greening variation and should be investigated further in order to identify the genes underlying their effects but also should be taken into account when selecting non-greening potato lines in the breeding process.