bluuebunny/crossref_metadata_2025 huggingface dataset:
Laser-based powder bed fusion of niobium with different build-up rates
Authors: Griemsmann Tjorben , Abel Arvid , Hoff Christian , Hermsdorf Jörg , Weinmann Markus , Kaierle Stefan
Published: March 2021

Niobium is an important material for high temperature applications, in space, in superconductors or in chemical process constructions. Laser-based powder bed fusion of niobium (PBF-LB/M/Nb) offers new opportunities in design, though it is still an expensive technique. The build-up rate is an important factor for economical manufacturing using PBF-LB/M/Nb. It is largely influenced by variation of process parameters, affecting the heat flow during the manufacturing process. In this work, an empirical model for PBF-LB/M/Nb is developed. Based on this model, manufacturing parameter sets using different volume build-up rates are predicted and confirmed. They enable the manufacture of parts with homogeneous and crack-free microstructure with more than 99.9% relative density. Tensile and hardness tests of specimens, which were manufactured using different parameter sets, are performed to determine the effects of the build-up rate—and thus the heat flow during manufacturing—on different mechanical properties. The ultimate tensile strength and yield strength of as-manufactured specimens reach values up to 525 MPa and 324 MPa, respectively, while the elongation at break ranges between approximately 8 and 16%. The Vickers hardness of all specimens was in the range of 149 ± 8 HV0.1. In addition, the microstructure of the manufactured samples is investigated by means of light as well as scanning electron microscopy.
Does Overfilling Smooth Inflatable Saline-Filled Breast Implants Decrease the Deflation Rate? Experience with 4761 Augmentation Mammaplasty Patients
Authors: Eisenberg Ted
Published: March 2021

Background

Research suggests that overfilling saline inflatable breast implants may decrease their deflation rates. To date, there has been no large-scale study comparing breast implants filled within vs. beyond the manufacturer’s recommended fill volumes.

Methods

A retrospective comparative study was conducted for 4761 women who underwent aesthetic augmentation mammaplasty by the author. Patients were divided into two groups: Group 1 includes 2960 patients who had breast augmentation between 2002 and 2009 with implants filled within the manufacturer’s recommended fill volumes. Group 2 includes 1801 patients who had breast augmentation between 2011 and 2018. Their implants were overfilled with an average volume between 42 and 50 cc, or 10–13%, respectively.

All surgeries were performed with Mentor Style 1600 saline breast implants (smooth, round moderate profile) through an inframammary incision; implants were placed in the subpectoral (dual) plane. Also evaluated was the yearly increase in deflation rates.

Results

Group I had 119 deflations, representing a deflation rate of 4.02%. Group 2 had 33 deflations, providing a deflation rate of 1.83%. The author found a protective effect in overfilling the device (p < 0.00001 and Z-score of 4.17). Fold failure was the major reason for deflation in both groups.

The implants filled within the manufacturer’s recommended volume had a yearly increase in deflation rate of 0.41%, not 1% as is commonly reported. The overfilled implants did not have a yearly increase in deflation rate.

Conclusion

Overfilling Mentor Style 1600 saline breast implants (smooth, round moderate profile) 10–13% significantly reduced the deflation rate.

Level of Evidence III

This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266.
Using virtual 3D-models in surgical planning: workflow of an immersive virtual reality application in liver surgery
Authors: Boedecker Christian , Huettl Florentine , Saalfeld Patrick , Paschold Markus , Kneist Werner , Baumgart Janine , Preim Bernhard , Hansen Christian , Lang Hauke , Huber Tobias
Published: March 2021

Purpose

Three-dimensional (3D) surgical planning is widely accepted in liver surgery. Currently, the 3D reconstructions are usually presented as 3D PDF data on regular monitors. 3D-printed liver models are sometimes used for education and planning.

Methods

We developed an immersive virtual reality (VR) application that enables the presentation of preoperative 3D models. The 3D reconstructions are exported as STL files and easily imported into the application, which creates the virtual model automatically. The presentation is possible in “OpenVR”-ready VR headsets. To interact with the 3D liver model, VR controllers are used. Scaling is possible, as well as changing the opacity from invisible over transparent to fully opaque. In addition, the surgeon can draw potential resection lines on the surface of the liver. All these functions can be used in a single or multi-user mode.

Results

Five highly experienced HPB surgeons of our department evaluated the VR application after using it for the very first time and considered it helpful according to the “System Usability Scale” (SUS) with a score of 76.6%. Especially with the subitem “necessary learning effort,” it was shown that the application is easy to use.

Conclusion

We introduce an immersive, interactive presentation of medical volume data for preoperative 3D liver surgery planning. The application is easy to use and may have advantages over 3D PDF and 3D print in preoperative liver surgery planning. Prospective trials are needed to evaluate the optimal presentation mode of 3D liver models.
Endocannabinoid and dopaminergic system: the pas de deux underlying human motivation and behaviors
Authors: Laksmidewi A. A. A. Putri , Soejitno Andreas
Published: March 2021

Endocannabinoid system (ECS) has been identified ever since cannabinoid, an active substance of Cannabis, was known to interact with endogenous cannabinoid (endocannabinoid/eCB) receptors. It later turned out that eCB was more intricate than previously thought. It has a pervasive role and exerts a multitude of cellular signaling mechanisms, regulating various physiological neurotransmission pathways in the human brain, including the dopaminergic (DA) system. eCB roles toward DA system were robust, clearly delineated, and reproducible with respect to physiological as well as pathological neurochemical and neurobehavioral manifestations of DA system, particularly those involving the nigrostriatal and mesocorticolimbic pathways. The eCB–DA system regulates the basics in the Maslow’s pyramid of hierarchy of needs required for individual survival such as food and sexual activity for reproductive purpose to those of higher needs in the pyramid, including self-actualization behaviors leading to achievement and reward (e.g., academic- and/or work-related performance and achievements). It is, thus, interesting to specifically discuss the eCB–DA system, not only on the molecular level, but also its tremendous potential to be developed as a future therapeutic strategy for various neuropsychiatric problems, including obesity, drug addiction and withdrawal, pathological hypersexuality, or low motivation behaviors.
Restoring mechanism of mechanical properties of recycled polyethylene pellet moldings by a repelletizing treatment using a twin-screw extruder
Authors: Okubo H. , Yao S.
Published: March 2021

To develop material-recycling processes for used plastic products, it is necessary to design new material-recycling techniques to optimize the mechanical properties of the recycled plastics since the mechanical properties of recycled plastic products are normally deteriorated. In this study, we suggest one of the approaches that is a repelletizing treatment for improving the mechanical properties of recycled-polyethylene moldings using a twin-screw extruder. The results of the tensile test revealed the significant effect of the repelletizing treatment on the tensile performance of the recycled-polyethylene moldings. The tensile performance of the repelletized recycled-polyethylene moldings was significantly higher than that of the original recycled-polyethylene moldings under specific repelletizing conditions. The analysis of the polymeric structures revealed the significant effect of the repelletizing treatment on the secondary and higher-order structures such as the lamellar shape, aggregation of the crystal domains, amorphousness, and polyethylene chain conformation in the recycled-polyethylene moldings. The repelletizing treatment increased the tensile performances by optimizing the internal structure of the recycled-polyethylene moldings. The results confirmed the efficacy of the repelletizing treatment to optimize the mechanical performance of the recycled-polymer materials, thereby facilitating the reuse of waste plastics as value-added materials for various industrial applications.
On the stochastic vehicle routing problem with time windows, correlated travel times, and time dependency
Authors: Bomboi Federica , Buchheim Christoph , Pruente Jonas
Published: March 2021

Most state-of-the-art algorithms for the Vehicle Routing Problem, such as Branch-and-Price algorithms or meta heuristics, rely on a fast feasibility test for a given route. We devise the first approach to approximately check feasibility in the Stochastic Vehicle Routing Problem with time windows, where travel times are correlated and depend on the time of the day. Assuming jointly normally distributed travel times, we use a chance constraint approach to model feasibility, where two different application scenarios are considered, depending on whether missing a customer makes the rest of the route infeasible or not. The former case may arise, e.g., in drayage applications or in the pickup-and-delivery VRP. In addition, we present an adaptive sampling algorithm that is tailored for our setting and is much faster than standard sampling techniques. We use a case study for both scenarios, based on instances with realistic travel times, to illustrate that taking correlations and time dependencies into account significantly improves the quality of the solutions, i.e., the precision of the feasibility decision. In particular, the nonconsideration of correlations often leads to solutions containing infeasible routes.
Multiple b-values improve discrimination of cortical gray matter regions using diffusion MRI: an experimental validation with a data-driven approach
Authors: Ganepola Tara , Lee Yoojin , Alexander Daniel C. , Sereno Martin I. , Nagy Zoltan
Published: March 2021

Objective

To investigate whether varied or repeated b-values provide better diffusion MRI data for discriminating cortical areas with a data-driven approach.

Methods

Data were acquired from three volunteers at 1.5T with b-values of 800, 1400, 2000 s/mm2 along 64 diffusion-encoding directions. The diffusion signal was sampled from gray matter in seven regions of interest (ROIs). Rotational invariants of the local diffusion profile were extracted as features that characterize local tissue properties. Random forest classification experiments assessed whether classification accuracy improved when data with multiple b-values were used over repeated acquisition of the same (1400 s/mm2) b-value to compare all possible pairs of the seven ROIs. Three data sets from the Human Connectome Project were subjected to similar processing and analysis pipelines in eight ROIs.

Results

Three different b-values showed an average improvement in correct classification rates of 5.6% and 4.6%, respectively, in the local and HCP data over repeated measurements of the same b-value. The improvement in correct classification rate reached as high as 16% for individual binary classification experiments between two ROIs. Often using only two of the available three b-values were adequate to make such an improvement in classification rates.

Conclusion

Acquisitions with varying b-values are more suitable for discriminating cortical areas.
Role of environmental filtering and seed source availability in natural regeneration processes following large-scale disturbances in mountain forests
Authors: Szwagrzyk Jerzy , Gazda Anna , Zwijacz-Kozica Tomasz , Zięba Antoni , Ciesielska Barbara , Szewczyk Janusz , Foremnik Kacper , Muter Elżbieta , Bodziarczyk Jan
Published: March 2021

The relative importance of environmental factors and species pool in natural regeneration processes is still intensively disputed. Is environmental filtering especially important for species with higher requirements for temperature and soil fertility? Is the seed source limitation especially pronounced among tree species with lower dispersal abilities? Trees, seedlings and saplings measurements were conducted in 600 plots of 0.05 ha distributed in a regular grid in the Tatra Mountains (elevation range 817–1797 m a.s.l.). Boosted regression trees were used to analyse the relationships between the numbers of young trees, factors acting as environmental filters and the potential seed source availability. The most important factor affecting the distribution of young trees of most species was elevation; bedrock type was the second most important factor for Acer pseudoplatanus, while potential solar radiation was important for Sorbus aucuparia. The relationship between the presence of mature trees and abundance of young ones was strong in Fagus sylvatica, moderately strong in A. pseudoplatanus, and weak in Picea abies, Abies alba and S. aucuparia. The role of environmental factors in shaping the abundance of young trees varies strongly among species, while the seed source availability is very important for large-seeded trees.
A Random Walk on the Indecomposable Summands of Tensor Products of Modular Representations of SL2 $\left ({\mathbb {F}_p}\right )$
Authors: McDowell Eoghan
Published: March 2021

In this paper we introduce a novel family of Markov chains on the simple representations of SL2$\left ({\mathbb {F}_p}\right )$

F

p

in defining characteristic, defined by tensoring with a fixed simple module and choosing an indecomposable non-projective summand. We show these chains are reversible and find their connected components and their stationary distributions. We draw connections between the properties of the chain and the representation theory of SL2$\left ({\mathbb {F}_p}\right )$

F

p

, emphasising symmetries of the tensor product. We also provide an elementary proof of the decomposition of tensor products of simple SL2$\left ({\mathbb {F}_p}\right )$

F

p

-representations.
A branch & bound algorithm to determine optimal bivariate splits for oblique decision tree induction
Authors: Bollwein Ferdinand , Westphal Stephan
Published: March 2021

Univariate decision tree induction methods for multiclass classification problems such as CART, C4.5 and ID3 continue to be very popular in the context of machine learning due to their major benefit of being easy to interpret. However, as these trees only consider a single attribute per node, they often get quite large which lowers their explanatory value. Oblique decision tree building algorithms, which divide the feature space by multidimensional hyperplanes, often produce much smaller trees but the individual splits are hard to interpret. Moreover, the effort of finding optimal oblique splits is very high such that heuristics have to be applied to determine local optimal solutions. In this work, we introduce an effective branch and bound procedure to determine global optimal bivariate oblique splits for concave impurity measures. Decision trees based on these bivariate oblique splits remain fairly interpretable due to the restriction to two attributes per split. The resulting trees are significantly smaller and more accurate than their univariate counterparts due to their ability of adapting better to the underlying data and capturing interactions of attribute pairs. Moreover, our evaluation shows that our algorithm even outperforms algorithms based on heuristically obtained multivariate oblique splits despite the fact that we are focusing on two attributes only.
Inelastic displacement ratios for non-structural components in steel framed structures under forward-directivity near-fault strong-ground motion
Authors: Bravo-Haro M. A. , Virreira J. R. , Elghazouli A. Y.
Published: March 2021

This paper describes a detailed numerical investigation into the inelastic displacement ratios of non-structural components mounted within multi-storey steel framed buildings and subjected to ground motions with forward-directivity features which are typical of near-fault events. The study is carried out using detailed multi-degree-of-freedom models of 54 primary steel buildings with different structural characteristics. In conjunction with this, 80 secondary non-structural elements are modelled as single-degree-of-freedom systems and placed at every floor within the primary framed structures, then subsequently analysed through extensive dynamic analysis. The influence of ground motions with forward-directivity effects on the mean response of the inelastic displacement ratios of non-structural components are compared to the results obtained from a reference set of strong-ground motion records representing far-field events. It is shown that the mean demand under near-fault records can be over twice as large as that due to far-fault counterparts, particularly for non-structural components with periods of vibration lower than the fundamental period of the primary building. Based on the results, a prediction model for estimating the inelastic displacement ratios of non-structural components is calibrated for far-field records and near-fault records with directivity features. The model is valid for a wide range of secondary non-structural periods and primary building fundamental periods, as well as for various levels of inelasticity induced within the secondary non-structural elements.
Multi-label learning with missing and completely unobserved labels
Authors: Huang Jun , Xu Linchuan , Qian Kun , Wang Jing , Yamanishi Kenji
Published: March 2021

Multi-label learning deals with data examples which are associated with multiple class labels simultaneously. Despite the success of existing approaches to multi-label learning, there is still a problem neglected by researchers, i.e., not only are some of the values of observed labels missing, but also some of the labels are completely unobserved for the training data. We refer to the problem asmulti-label learning with missing and completely unobserved labels, and argue that it is necessary to discover these completely unobserved labels in order to mine useful knowledge and make a deeper understanding of what is behind the data. In this paper, we propose a new approach named MCUL to solve multi-label learning with Missing and Completely Unobserved Labels. We try to discover the unobserved labels of a multi-label data set with a clustering based regularization term and describe the semantic meanings of them based on the label-specific features learned by MCUL, and overcome the problem of missing labels by exploiting label correlations. The proposed method MCUL can predict both the observed and newly discovered labels simultaneously for unseen data examples. Experimental results validated over ten benchmark datasets demonstrate that the proposed method can outperform other state-of-the-art approaches on observed labels and obtain an acceptable performance on the new discovered labels as well.
Which Factors Influence Teacher Report of Adaptive Functioning in Autistic Children?
Authors: Moore Heather L. , Rogan Leanne , Taylor Lauren J. , Charman Tony , Le Couteur Ann , Green Jonathan , Grahame Victoria ,   the PACT-G Consortium, Aldred Catherine , Balabanovska Matea , Beach Hilary , Bennett Claire , Carruthers Sophie , Crook Imogen , Danvers Hannah , Dartnall Kate , Ellis Ceri , Emsley Richard , Foote Hannah , Graham Jessica , Howlin Patricia , Humphrey Neil , James Kirsty , Jamieson Sarah , Kappa Anna , Knight Anna , Leadbitter Kathy , Lowe Jo , Langhorne Sophie , Madeley Ruth , Maskell Deborah , Mitchell Olivia , McConachie Helen , Monteiro Francisca , Brooks Cat Papastavrou , Parr Jeremy , Pearson Amelia , Pickles Andrew , Rose Jessica , Slater Lisa , Slonims Vicky , Taylor Carol , Vosper Susanna , Wilson Helen
Published: March 2021

A wealth of parent-report research shows adaptive functioning difficulties in autistic children, with parent-report influenced by a number of child factors. Adaptive functioning in autistic children is known to vary across settings; however, no research has yet explored factors influencing education professional-report. This study investigated the rate and profile of impairment, and child factors influencing education professional-reported adaptive skills in 248 autistic children. Twelve children were < 3 years (min age for available normative data on the adaptive function measure), so were removed from the analyses. Results replicated parent-literature; adaptive skills were negatively associated with age and informant-reported autism severity, and positively associated with nonverbal ability and expressive language. Adaptive functioning is important for real-world outcomes, e.g. educational attainment, independence, and support needs. Improving our understanding of adaptive functioning in the education context may support opportunities for shared learning and enhance personalised support .
Developing microalgal oil production for an outdoor photobioreactor
Authors: Norsker Niels-Henrik , Cuaresma Maria , Uronen Pauliina , Barbosa Maria J. , Wijffels René
Published: March 2021

In this paper the preparations are described to develop a production of oil rich microalgal biomass under south European conditions. Ten microalgal species were compared in shake flasks in an incubator for potential for oil production. Potential oil production capacity was assayed as maximum total fatty acid (TFA) concentration and volumetric TFA productivity. TFA concentration ranged from 5 to 40% DW while TFA productivity rate ranged from 0 to 204 mg TFA L−1 day−1. To control the oil enrichment process in the outdoor microalgal batch culture, a quadratic equation was proposed, predicting the TFA concentration based on biomass inverse nitrogen quota. A concentrated substrate was developed to add to sea water, made from natural sea-salt and tap water.
Largest Family Without a Pair of Posets on Consecutive Levels of the Boolean Lattice
Authors: Katona Gyula O. H. , Xiao Jimeng
Published: March 2021

Suppose k ≥ 2 is an integer. Let Yk be the poset with elements x1,x2,y1,y2,…,yk− 1 such that y1 < y2 < ⋯ < yk− 1 < x1,x2 and let $Y_{k}^{\prime }$

Y

k

′

be the same poset but all relations reversed. We say that a family of subsets of [n] contains a copy of Yk on consecutive levels if it contains k + 1 subsets F1,F2,G1,G2,…,Gk− 1 such that G1 ⊂ G2 ⊂⋯ ⊂ Gk− 1 ⊂ F1,F2 and |F1| = |F2| = |Gk− 1| + 1 = |Gk− 2| + 2 = ⋯ = |G1| + k − 1. If both Yk and $Y^{\prime }_{k}$

Y

k

′

on consecutive levels are forbidden, the size of the largest such family is denoted by $\text {La}_{\mathrm {c}}\left (n, Y_{k}, Y^{\prime }_{k}\right )$

La

c

n
,

Y

k

,

Y

k

′

. In this paper, we will determine the exact value of $\text {La}_{\mathrm {c}}\left (n, Y_{k}, Y^{\prime }_{k}\right )$

La

c

n
,

Y

k

,

Y

k

′

.
How does tautomerization affect the excited-state dynamics of an amino acid-derivatized corrole?
Authors: Clark John A. , Orłowski Rafał , Derr James B. , Espinoza Eli M. , Gryko Daniel T. , Vullev Valentine I.
Published: March 2021

In the first two decades of the XXI century, corroles have emerged as an important class of porphyrinoids for photonics and biomedical photonics. In comparison with porphyrins, corroles have lower molecular symmetry and higher electron density, which leads to uniquely complementary properties. In macrocycles of free-base corroles, for example, three protons are distributed among four pyrrole nitrogens. It results in distinct tautomers that have different thermodynamic energies. Herein, we focus on the excited-state dynamics of a corrole modified with l-phenylalanine. The tautomerization in the singlet-excited state occurs in the timescales of about 10–100 picoseconds and exhibits substantial kinetic isotope effects. It, however, does not discernably affect nanosecond deactivation of the photoexcited corrole and its basic photophysics. Nevertheless, this excited-state tautomerization dynamics can strongly affect photoinduced processes with comparable or shorter timescales, considering the 100-meV energy differences between the tautomers in the excited state. The effects on the kinetics of charge transfer and energy transfer, initiated prior to reaching the equilibrium thermalization of the excited-state tautomer population, can be indeed substantial. Such considerations are crucially important in the design of systems for artificial photosynthesis and other forms of energy conversion and charge transduction.
A puzzle about laws and explanation
Authors: Jaag Siegfried
Published: March 2021

In this paper, we argue that the popular claim that laws of nature explain their instances (explanatory laws) creates a philosophical puzzle when it is combined with the widely held requirement that explanations need to be underpinned by ‘wordly’ relations (explanatory realism). We argue that a “direct solution” to the puzzle that accounts for bothexplanatory lawsandexplanatory realismrequires endorsing at least a radical metaphysics. Then, we examine the ramifications of a “skeptical solution”, i.e., dissolving it by giving up at least one of these two claims, and argue that adopting it is more favorable to Humean reductionists than to anti-reductionists about laws of nature.
Obstructive Sleep Apnea and Asthma: More Than Chance?
Authors: Pepito Donna L. , Mohammed Jamal M. , Hardin Kimberly A.
Published: March 2021

Purpose of Review

To discuss the current evidence regarding the association and mechanistic interaction between asthma and obstructive sleep apnea (OSA).

Recent Findings

The co-existence of OSA is highly prevalent in asthmatics and significantly associated with increased severity, decreased control, more frequent exacerbations, and hospitalizations despite medical management. Pre-existing asthma may also be a risk factor for new onset OSA. Rhinitis, obesity, and gastro-esophageal reflux are risk factors in both conditions. The obese asthmatic with OSA may present a unique phenotype. Positive airway pressure in severe asthma improves outcomes.

Pathophysiologic mechanisms and co-morbidities overlap between OSA and asthma, but the exact link has yet to be confirmed. Screening for OSA is recommended in those with severe asthma. Further investigations are needed to delineate the cellular processes with therapeutic targets. Similarly, prospective investigations are needed to evaluate the longitudinal relationship in pre-existing asthma and the development of OSA.
Dynamic friction energy dissipation and enhanced contrast in high frequency bimodal atomic force microscopy
Authors: Tan Xinfeng , Guo Dan , Luo Jianbin
Published: March 2021

Dynamic friction occurs not only between two contact objects sliding against each other, but also between two relative sliding surfaces several nanometres apart. Many emerging micro- and nano-mechanical systems that promise new applications in sensors or information technology may suffer or benefit from noncontact friction. Herein we demonstrate the distance-dependent friction energy dissipation between the tip and the heterogeneous polymers by the bimodal atomic force microscopy (AFM) method driving the second order flexural and the first order torsional vibration simultaneously. The pull-in problem caused by the attractive force is avoided, and the friction dissipation can be imaged near the surface. The friction dissipation coefficient concept is proposed and three different contact states are determined from phase and energy dissipation curves. Image contrast is enhanced in the intermediate setpoint region. The work offers an effective method for directly detecting the friction dissipation and high resolution images, which overcomes the disadvantages of existing methods such as contact mode AFM or other contact friction and wear measuring instruments.
Prenatal Diagnosis of Radial Ray Defect Associated with Fanconi Anemia: a Case Report
Authors: Bhatt Reema Kumar , Dwivedi Aradhana , Dua Ratna Puri , Singh L. B. , Kulshrestha Samarth
Published: March 2021

Fanconi anemia (FA) is a rare genetic disorder with multisystem involvement. Confirmatory genetic testing is possible by diagnostic clues on examination of the proband within the differential diagnosis. We describe a fetus with radial ray defect in a primigravida. Cytogenetic testing for breakages confirmed Fanconi anemia as the etiology. Molecular testing by next generation sequencing did not reveal a point change in any of the twenty-one genes known to be associated with FA. A confirmed fetal autopsy phenotype and the cytogenetic report allowed for the identification of a homozygous deletion of exon 4–6 in the FANCC gene on re-analysis of the molecular dataset. This case exemplifies the utility of a step wise approach to the diagnosis of prenatally diagnosed radial ray defects and the importance of genetic counseling and prenatal testing.
Generative adversarial network guided mutual learning based synchronization of cluster of neural networks
Authors: Sarkar Arindam
Published: March 2021

Neural synchronization is a technique for establishing the cryptographic key exchange protocol over a public channel. Two neural networks receive common inputs and exchange their outputs. In some steps, it leads to full synchronization by setting the discrete weights according to the specific rule of learning. This synchronized weight is used as a common secret session key. But there are seldom research is done to investigate the synchronization of a cluster of neural networks. In this paper, a Generative Adversarial Network (GAN)-based synchronization of a cluster of neural networks with three hidden layers is proposed for the development of the public-key exchange protocol. This paper highlights a variety of interesting improvements to traditional GAN architecture. Here GAN is used for Pseudo-Random Number Generators (PRNG) for neural synchronization. Each neural network is considered as a node of a binary tree framework. When bothi-th andj-th nodes of the binary tree are synchronized then one of these two nodes is elected as a leader. Now, this leader node will synchronize with the leader of the other branch. After completion of this process synchronized weight becomes the session key for the whole cluster. This proposed technique has several advantages like (1) There is no need to synchronize one neural network to every other in the cluster instead of that entire cluster can be able to share the same secret key by synchronizing between the elected leader nodes with only logarithmic synchronization steps. (2) This proposed technology provides GAN-based PRNG which is very sensitive to the initial seed value. (3) Three hidden layers leads to the complex internal architecture of the Tree Parity Machine (TPM). So, it will be difficult for the attacker to guess the internal architecture. (4) An increase in the weight range of the neural network increases the complexity of a successful attack exponentially but the effort to build the neural key decreases over the polynomial time. (5) The proposed technique also offers synchronization and authentication steps in parallel. It is difficult for the attacker to distinguish between synchronization and authentication steps. This proposed technique has been passed through different parametric tests. Simulations of the process show effectiveness in terms of cited results in the paper.
A new approach for automated measuring of the melt pool geometry in laser-powder bed fusion
Authors: Schmid Simon , Krabusch Johannes , Schromm Thomas , Jieqing Shi , Ziegelmeier Stefan , Grosse Christian Ulrich , Schleifenbaum Johannes Henrich
Published: March 2021

Additive manufacturing (AM) offers unique possibilities in comparison to conventional manufacturing processes. For example, complex parts can be manufactured without tools. For metals, the most commonly used AM process is laser-powder bed fusion (L-PBF). The L-PBF process is prone to process disturbances, hence maintaining a consistent part quality remains an important subject within current research. An established indicator for quantifying process changes is the dimension of melt pools, which depends on the energy input and the cooling conditions. The melt pool geometry is normally measured manually in cross sections of solidified welding seams. This paper introduces a new approach for the automated visual measuring of melt pools in cross-sections of parts manufactured by L-PBF. The melt pools are first segmented in the images and are then measured. Since the melt pools have a heterogeneous appearance, segmentation with common digital image processing is difficult, deep learning was applied in this project. With the presented approach, the melt pools can be measured over the whole cross section of the specimen. Furthermore, remelted melt pools, which are only partly visible, are evaluated. With this automated approach, a high number of melt pools in each cross-section can be measured, which allows the examination of trends over the build direction in a specimen and results in better statistics. Furthermore, deviations in the energy input can be estimated via the measured melt pool dimensions.
Association of Nonmedical Switches in Inhaled Respiratory Medications with Disruptions in Care: A Retrospective Prescription Claims Database Analysis
Authors: Gilbert Ileen , Aslam Mahmood Aanam , Devane Katie , Tan Laren
Published: March 2021

Introduction

There are limited data on the effects of forced medication switching for a nonmedical reason in patients with obstructive airway conditions. This study evaluated disruption in care resulting from a nonmedical medication switch for patients with asthma and/or chronic obstructive pulmonary disease who previously received the inhaled corticosteroid/long-acting β2-agonist budesonide/formoterol.

Methods

This retrospective pharmacy benefit prescription claims analysis evaluated Medicare Part D patients who filled a prescription for budesonide/formoterol as their last inhaled corticosteroid/long-acting β2-agonist in 2016 and were affected by a formulary block of budesonide/formoterol in 2017. Changes to respiratory maintenance therapy, length of gaps in care during which a patient was not in possession of a respiratory controller medication, acute medication use indicative of disease exacerbations, and medication adherence were assessed.

Results

A total of 42,553 patients were included in the analysis. Following the formulary block, 30,016 patients (71%) switched to another controller; 20,628 of these patients (69%) switched to a new inhaled corticosteroid/long-acting β2-agonist, 7081 (23%) stepped down to a monotherapy, and 2307 (8%) switched to a non-inhaled corticosteroid-containing controller. Despite the formulary block, 22,903 patients (54%) attempted to fill budesonide/formoterol as their first postblock controller, and 6624 patients (16%) attempted to return to budesonide/formoterol after switching to another controller. On average, patients experienced a gap in care of approximately 4 months without a controller medication. Also, 9674 (23%) did not fill any controller over the 1-year postblock period. Of those patients who experienced a gap in care, 14,926 (47%) filled a prescription indicative of a possible exacerbation during the gap period (i.e., oral corticosteroids for patients with asthma and oral corticosteroids and/or antibiotics for patients with chronic obstructive pulmonary disease).

Conclusions

The Medicare Part D formulary block was associated with disruption in the management of patients’ respiratory conditions and may have adversely impacted disease control.
COVID-19 Pandemic, Transparency, and “Polidemic” in the Republic of Korea
Authors: Kang Cheol , Lee Ilhak
Published: March 2021

This article examines the development of the Republic of Korea’s strategy to prevent the spread of COVID-19 with particular focus on ethical issues and the problem of politicization of public communication. Using prominent examples of stakeholders who have acted and expressed themselves in highly contradictory ways on the topic of the pandemic, we provide an analysis of how the public health policy discourse has entered into the realm of politicization and elaborate on the danger that this phenomenon poses in terms of rational debate and appropriate policy measures geared toward the public’s safety. Considering the role that the Republic of Korea have had in global media coverage of quarantine policies and epidemic prevention, we believe that our study makes a significant contribution to the literature because it provides a new perspective and insights into the forces at work within and around a prevention strategy that has both been lauded and seen as highly controversial.
VC: a method for estimating time-varying coefficients in linear models
Authors: Schlicht Ekkehart
Published: March 2021

This paper describes a moments estimator for a standard state-space model with coefficients generated by a random walk. The method calculates the conditional expectations of the coefficients, given the observations. A penalized least squares estimation is linked to the GLS (Aitken) estimates of the corresponding linear model with time-invariant parameters. The estimates are moments estimates. They do not require the disturbances to be Gaussian, but if they are, the estimates are asymptotically equivalent to maximum likelihood estimates. In contrast to Kalman filtering, no specification of an initial state or an initial covariance matrix is required. While the Kalman filter is one sided, the filter proposed here is two sided and therefore uses more of the available information for estimating intermediate states. Further, the proposed filter has a clear descriptive interpretation.
A uniqueness result for the Sine-Gordon breather
Authors: Mandel Rainer
Published: March 2021

In this note we prove that the sine-Gordon breather is the only quasimonochromatic breather in the context of nonlinear wave equations in $$\mathbb {R}^N$$

R

N

.
Estimating the potential impact of climate change on sunflower yield in the Konya province of Turkey
Authors: Gurkan Hudaverdi , Shelia Vakhtang , Bayraktar Nilgun , Ersoy Yildirim Y. , Yesilekin Nebi , Gunduz Arzu , Boote Kenneth , Porter Cheryl , Hoogenboom Gerrit
Published: March 2021

The impact of climate change on agricultural productivity is difficult to assess. However, determining the possible effects of climate change is an absolute necessity for planning by decision-makers. The aim of the study was the evaluation of the CSM-CROPGRO-Sunflower model of DSSAT4.7 and the assessment of impact of climate change on sunflower yield under future climate projections. For this purpose, a 2-year sunflower field experiment was conducted under semi-arid conditions in the Konya province of Turkey. Rainfed and irrigated treatments were used for model analysis. For the assessment of impact of climate change, three global climate models and two representative concentration pathways, i.e. 4.5 and 8.5 were selected. The evaluation of the model showed that the model was able to simulate yield reasonably well, with normalized root mean square error of 1.3% for the irrigated treatment and 17.7% for the rainfed treatment, a d-index of 0.98 and a modelling efficiency of 0.93 for the overall model performance. For the climate change scenarios, the model predicted that yield will decrease in a range of 2.9–39.6% under rainfed conditions and will increase in a range of 7.4–38.5% under irrigated conditions. Results suggest that temperature increases due to climate change will cause a shortening of plant growth cycles. Projection results also confirmed that increasing temperatures due to climate change will cause an increase in sunflower water requirements in the future. Thus, the results reveal the necessity to apply adequate water management strategies for adaptation to climate change for sunflower production.
The Political Economy of Famine: The Ukrainian Famine of 1933
Authors: Naumenko Natalya
Published: March 2021

The 1933 Ukrainian famine killed as many as 2.6 million people out of a population of 32 million. Historians offer three main explanations: weather, economic policies, genocide. This paper documents that (1) available data do not support weather as the main explanation: 1931 and 1932 weather predicts harvest roughly equal to the 1924–1929 average; weather explains up to 8.1 percent of excess deaths. (2) Policies (collectivization of agriculture and the lack of favored industries) significantly increased famine mortality; collectivization explains up to 52 percent of excess deaths. (3) There is some evidence that ethnic Ukrainians and Germans were discriminated against.
Long-pulse plasma source for SMOLA helical mirror
Authors: Ivanov Ivan A. , Ustyuzhanin V. O. , Sudnikov A. V. , Inzhevatkina A.
Published: March 2021

A plasma gun for forming a plasma stream in the open magnetic mirror trap with additional helicoidal field SMOLA is described. The plasma gun is an axisymmetric system with a planar circular hot cathode based on lanthanum hexaboride and a hollow copper anode. The two planar coils are located around the plasma source and create a magnetic field of up to 200 mT. The magnetic field forms the magnetron configuration of the discharge and provides a radial electric insulation. The source typically operates with a discharge current of up to 350 A in hydrogen. Plasma parameters in the SMOLA device are Ti ~ 5 eV, Te ~ 5–40 eV and ni ~ (0.1–1)  × 1019 m−3. Helium plasma can also be created. The plasma properties depend on the whole group of initial technical parameters: the cathode temperature, the feeding gas flow, the anode-cathode supply voltage and the magnitude of the cathode magnetic insulation.
Climate change refugia: landscape, stand and tree-scale microclimates in epiphyte community composition
Authors: Ellis Christopher J. , Eaton Sally
Published: March 2021

There is growing evidence that species and communities are responding to, and will continue to be affected by, climate change. For species at risk, vulnerability can be reduced by ensuring that their habitat is extensive, connected and provides opportunities for dispersal and/or gene flow, facilitating a biological response through migration or adaptation. For woodland epiphytes, vulnerability might also be reduced by ensuring sufficient habitat heterogeneity, so that microhabitats provide suitable local microclimates, even as the larger scale climate continues to change (i.e. microrefugia). This study used fuzzy set ordination to compare bryophyte and lichen epiphyte community composition to a large-scale gradient from an oceanic to a relatively more continental macroclimate. The residuals from this relationship identified microhabitats in which species composition reflected a climate that was more oceanic or more continental than would be expected given the prevailing macroclimate. Comparing these residuals to features that operate at different scales to create the microclimate (landscape, stand and tree-scale), it was possible to identify how one might engineer microrefugia into existing or new woodland, in order to reduce epiphyte vulnerability to climate change. Multimodel inference was used to identify the most important features for consideration, which included local effects such as height on the bole, angle of bole lean and bark water holding capacity, as well as tree species and tree age, and within the landscape, topographic wetness and physical exposure.
Self-reported and mother-rated personality traits at age 16 are associated with cognitive function measured concurrently and 30 years later
Authors: Sutin Angelina R. , Stephan Yannick , Luchetti Martina , Aschwanden Damaris , Sesker Amanda A. , O'Súilleabháin Páraic S. , Terracciano Antonio
Published: March 2021

Background

Models of personality and health suggest that personality contributes to health outcomes across adulthood. Personality traits, such as neuroticism and conscientiousness, have long-term predictive power for cognitive impairment in older adulthood, a critical health outcome. Less is known about whether personality measured earlier in life is also associated with cognition across adulthood prior to dementia.

Methods

Using data from the British Cohort Study 1970 (N = 4218; 58% female), the current research examined the relation between self-reported and mother-rated personality at age 16 and cognitive function concurrently at age 16 and cognitive function measured 30 years later at age 46, and whether these traits mediate the relation between childhood social class and midlife cognition.

Results

Self-reported and mother-rated conscientiousness at age 16 were each associated with every cognitive measure at age 16 and most measures at age 46. Self-reported openness was likewise associated with better cognitive performance on all tasks at age 16 and prospectively predicted age 46 performance (mothers did not rate openness). Mother-rated agreeableness, but not self-reported, was associated with better cognitive performance at both time points. Adolescent personality mediated the relation between childhood social class and midlife cognitive function.

Conclusions

The current study advances personality and cognition by showing that (1) adolescent personality predicts midlife cognition 30 years later, (2) both self-reports and mother-ratings are important sources of information on personality associated with midlife cognition, and (3) adolescent personality may be one pathway through which the early life socioeconomic environment is associated with midlife cognition.
Cognitive heterogeneity in first-episode psychosis and its relationship with premorbid developmental adjustment
Authors: Tan Eric J. , Rossell Susan L. , Subotnik Kenneth L. , Ventura Joseph , Nuechterlein Keith H.
Published: March 2021

Background

Patients with schizophrenia spectrum disorders have been increasingly recognised to form cognitive subgroups with differential levels of impairment. Using cluster analytical techniques, this study sought to identify cognitive clusters in a sample of first-episode psychosis (FEP) patients and examine clinical and developmental differences across the resultant groups.

Methods

In total, 105 FEP patients in the University of California Los Angeles Aftercare Research Program were assessed for cognition, symptoms and premorbid developmental adjustment. Hierarchical cluster analysis with Ward's method and squared Euclidean distance was conducted, confirmed by discriminant function analysis and optimised with k-means clustering. The stability of the solution was evaluated through split-sample (random, 80 and 70% samples) and alternate method (average linkage method) replication via Cohen's κ analysis. Controlling for multiple comparisons, one-way analysis of variances examined group differences in symptom severity and premorbid adjustment.

Results

Three groups were identified: severely impaired (n = 27), moderately impaired (n = 41) and relatively intact (n = 37). There were no significant differences in symptom severity across the groups. Significant differences were observed for scholastic performance at three different developmental stages: childhood, early adolescence and late adolescence, with the relatively intact group demonstrating significantly better scholastic performance at all three stages than both the moderately impaired and severely impaired groups (who did not significantly differ from each other).

Conclusions

The findings add to growing evidence that cognitive clusters in FEP mirror that of later-stage schizophrenia. They also suggest that premorbid scholastic performance may not just be a risk factor for developing schizophrenia, but is also related to cognitive impairment severity and potentially to prognosis.