bluuebunny/crossref_metadata_2025_split huggingface dataset:
Complementary relation between quantum entanglement and entropic uncertainty
Authors: Cao Yun , Wang Dong , Fan Xiao-Gang , Ming Fei , Wang Zhang-Yin , Ye Liu 
Published: December 2020

Abstract
Quantum entanglement is regarded as one of the core concepts, which is used to describe the non-classical correlation between subsystems, and entropic uncertainty relation plays a vital role in quantum precision measurement. It is well known that entanglement of formation can be expressed by von Neumann entropy of subsystems for arbitrary pure states. An interesting question is naturally raised: is there any intrinsic correlation between the entropic uncertainty relation and quantum entanglement? Or if the relation can be applied to estimate the entanglement. In this work, we focus on exploring the complementary relation between quantum entanglement and the entropic uncertainty relation. The results show that there exists an inequality relation between both of them for an arbitrary two-qubit system, and specifically the larger uncertainty will induce the weaker entanglement of the probed system, and vice versa. Besides, we use randomly generated states as illustrations to verify our results. Therefore, we claim that our observations might offer and support the validity of using the entropy uncertainty relation to estimate quantum entanglement.
A neurophysiological approach to spatial filter selection for adaptive brain–computer interfaces
Authors: Bennett James D , John Sam E , Grayden David B , Burkitt Anthony N 
Published: December 2020

Abstract

Objective. The common spatial patterns (CSP) algorithm is an effective method to extract discriminatory features from electroencephalography (EEG) to be used by a brain–computer interface (BCI). However, informed selection of CSP filters typically requires oversight from a BCI expert to accept or reject filters based on the neurophysiological plausibility of their activation patterns. Our goal was to identify, analyze and automatically classify prototypical CSP patterns to enhance the prediction of motor imagery states in a BCI. Approach. A data-driven approach that used four publicly available EEG datasets was adopted. Cluster analysis revealed recurring, visually similar CSP patterns and a convolutional neural network was developed to distinguish between established CSP pattern classes. Furthermore, adaptive spatial filtering schemes that utilize the categorization of CSP patterns were proposed and evaluated. Main results. Classes of common neurophysiologically probable and improbable CSP patterns were established. Analysis of the relationship between these categories of CSP patterns and classification performance revealed discarding neurophysiologically improbable filters can decrease decoder performance. Further analysis revealed that the spatial orientation of EEG modulations can evolve over time, and that the features extracted from the original CSP filters can become inseparable. Importantly, it was shown through a novel adaptive CSP technique that adaptation in response to these emerging patterns can restore feature separability. Significance. These findings highlight the importance of considering and reporting on spatial filter activation patterns in both online and offline studies. They also emphasize to researchers in the field the importance of spatial filter adaptation in BCI decoder design, particularly for online studies with a focus on training users to develop stable and suitable brain patterns.
Maize yield loss risk under droughts in observations and crop models in the United States
Authors: Leng Guoyong 
Published: December 2020

Abstract
The negative drought impacts on crop yield are well recognized in the literature, but are evaluated mainly in a deterministic manner. Considering the randomness feature of droughts and the compounding effects of other factors, we hypothesize that droughts effects on yields are probabilistic especially for assessment in large geographical regions. Taking US maize yield as an example, we found that a moderate, severe, extreme and exceptional drought event (based on the standardized precipitation evapotranspiration index) would lead to a yield loss risk (i.e. the probability of yield reduction lower than expected value) of 64.3%, 69.9%, 73.6%, and 78.1%, respectively, with hotspots identified in Central and Southeastern US. Irrigation has reduced yield loss risk by 10%–27%, with the benefit magnitude depending on the drought intensity. Evaluations of eight process crop models indicate that they can well reproduce observed drought risks for the country as a whole, but show difficult in capturing the spatial distribution patterns. The results highlight the diverse risk pattern in response to a drought event of specific intensity, and emphasize the need for better representation of drought effects in process models at local scales. The analysis framework developed in this study is novel in that it allows for an event-based assessment of drought effects in a risk manner in both observations and process crop models. Such information is valuable not only for robust decision-makings but also for the insurance sector, which typically require the risk information rather than a single value of outcome especially given the uncertainty of drought effects.
Dual index properties of photonic crystal and its application in subwavelength focusing
Authors: Liang Bingming , Ji Jing , Tang Dawei , Huang Yan , Huang Xiao 
Published: December 2020

Abstract
Based on the two-dimensional dielectric wedge-shaped photonic crystal, we studied the existence of two kinds of equivalent refractive indexes (negative refractive index is −1, positive refractive index is 1.897) in the photonic crystal by means of fast Fourier transform (FFT), as well as its influence on the optical propagation characteristics was discussed. By adjusting the wedge angle of the photonic crystal to eliminate the influence of positive refraction beam on the imaging, the sub wavelength focusing with half-width less than half of a wavelength can be realized. The numerical results show that the Full Width Half Maximum (FWHM) of the image point can reach a minimum of

0.41
λ

when the wedge angle of the photonic crystal is 73°.
On the frequency spectra of the electrostatic upper hybrid wave and linear Landau damping in a weakly magnetized relativistic electron plasma
Authors: Noureen S , Abbas Gohar , Sarfraz M , James L 
Published: December 2020

Abstract
On the basis of Vlasov-Kinetic model and using Maxwell-Juttner distribution function, dispersion relation of electrostatic wave in a collisionless homogeneous relativistic electron plasma is derived. The analysis of the oscillation spectra is carried out in a weak magnetic field limit

ω
−

kv

th

≥ Ω. Approximate analytic expression for the weakly damped mode is obtained in the subluminal limiting range. It is shown that the relativistic weakly damped mode can be estimated analytically in the range where the wave phase velocity v

φ
becomes greater than relativistic thermal velocity of the electron but less than speed of light. Results in the non-relativistic and the ultrarelativistic cases are also discussed.
Atomic permutationally invariant polynomials for fitting molecular force fields
Authors: Allen Alice E A , Dusson Geneviève , Ortner Christoph , Csányi Gábor 
Published: December 2020

Abstract
We introduce and explore an approach for constructing force fields for small molecules, which combines intuitive low body order empirical force field terms with the concepts of data driven statistical fits of recent machine learned potentials. We bring these two key ideas together to bridge the gap between established empirical force fields that have a high degree of transferability on the one hand, and the machine learned potentials that are systematically improvable and can converge to very high accuracy, on the other. Our framework extends the atomic permutationally invariant polynomials (aPIP) developed for elemental materials in (2019 Mach. Learn.: Sci. Technol.
1 015004) to molecular systems. The body order decomposition allows us to keep the dimensionality of each term low, while the use of an iterative fitting scheme as well as regularisation procedures improve the extrapolation outside the training set. We investigate aPIP force fields with up to generalised 4-body terms, and examine the performance on a set of small organic molecules. We achieve a high level of accuracy when fitting individual molecules, comparable to those of the many-body machine learned force fields. Fitted to a combined training set of short linear alkanes, the accuracy of the aPIP force field still significantly exceeds what can be expected from classical empirical force fields, while retaining reasonable transferability to both configurations far from the training set and to new molecules.
Human versus Computer Partner in the Paired Oral Discussion Test
Authors: Ockey Gary J , Chukharev-Hudilainen Evgeny 
Published: December 2020

Abstract
A challenge of large-scale oral communication assessments is to feasibly assess a broad construct that includes interactional competence. One possible approach in addressing this challenge is to use a spoken dialog system (SDS), with the computer acting as a peer to elicit a ratable speech sample. With this aim, an SDS was built and four trained human raters assessed the discourse elicited from 40 test takers that completed a paired oral task with both a human and a computer partner. The test takers were evaluated based on the analytic operational oral communication rating scales which included interactional competence, fluency, pronunciation, and grammar/vocabulary. Repeated-measures ANOVA indicated that fluency, pronunciation, and grammar and vocabulary were scored similarly across the two conditions, while interactional competence was scored substantially higher in the human partner condition. A g-study indicated that the computer partner was more reliable in assessing interactional competence, and rater questionnaire and interview data suggested the computer provided a more standardized assessment. Conversely, raters generally favored the human partner, in part because of its perceived authenticity and naturalness.
Key Anatomical Clarifications for the Marginal Mandibular Branch of the Facial Nerve: Clinical Significance for the Plastic Surgeon
Authors: Marolt Clayton , Freed Blair , Coker Charles , Steele Robert , Johnson Kenneth , Arellanes Russell , Gordon Victoria , Wright Barth , Stephens Robert , Surek Christopher C 
Published: December 2020

Abstract

Background
The marginal mandibular branch (MMBr) of the facial nerve is the least likely to recover from injury due to infrequent anastomosis with other branches. The MMBr has been described as coursing superior to the inferior border of the mandible. However, studies have reported variations in its location in embalmed and fresh specimens. It has been postulated that the embalming process may effect its anatomic position.

Objectives
The aim of this study was to re-evalulate the location of the MMBr relative to the inferior border of the mandible in both fresh and embalmed cadavers, and investigate variation in its position with sex, side of the face, and age.

Methods
Superficial fascial planes were dissected to reveal the MMBr and its anatomic relations. Distance between the most inferior branch of the MMBr and the antegonial notch were measured bilaterally. The most inferior position of the MMBr between the antegonial notch and gonion was measured. Fresh heads were used as a comparison, with an additional measurement taken of the distance between the MMBr and the gonial angle.

Results
The MMBr was located inferior to the border of the mandible (90.3%) more often than above (9.6%). No significant differences were found between fresh and embalmed cadavers, sex, side of body, or age (P &gt; 0.05). No significant difference was found between intact cadavers and fresh heads (P &gt; 0.05).

Conclusions
This study confirms and describes reliable landmarks for safety zones for the MMBr during plastic and reconstructive surgery of the lower face and upper neck. These data add reliability to studies that have investigated nerve locations in embalmed cadavers.
Patient Representation and Diversity in Plastic Surgery Social Media
Authors: Tirrell Abigail R , Bekeny Jenna C , Baker Stephen B , Song David H , Fan Kenneth L 
Published: December 2020

Abstract

Background
Plastic surgeons increasingly use social media as a means for patient engagement, trainee education, and research dissemination. Appropriate patient diversity on these platforms is critical to promote interaction with all patients and ensure adequate training of plastic surgeons to work with diverse populations.

Objectives
This study aimed to assess patient representation, particularly of racial and ethnic groups, among plastic surgery Instagram accounts.

Methods
Nine Instagram accounts of plastic surgery journals and professional organizations were analyzed for posts containing patient images between April 2015 and June 2020. Each unique patient image was assessed for demographic factors. Skin tone was analyzed as a proxy for racial diversity, with Fitzpatrick scale scores of 1 to 3 indicating white and 4 to 6 indicating nonwhite. Univariate analysis was performed to determine differences in representation.

Results
A total of 6719 posts from 5 journal and 4 professional organization accounts were found to contain 2547 unique patient images. Overall, 88.14% of patient images had white skin tone, whereas only 11.86% displayed nonwhite skin tone. Cosmetic procedure patient images had a higher frequency of white skin tone than reconstruction images (89.93% vs 81.98%, P &lt; 0.001). When compared with US Census data and the ASPS Annual Report data on race of patients undergoing plastic surgery, our data revealed significant underrepresentation of patients of color on social media (P &lt; 0.001).

Conclusions
This study highlights the underrepresentation of patients of color within social media imagery. Equitable representation of patients on social media is important to decrease patient barriers to healthcare and improve physician training to engage with diverse populations.
DSTG: deconvoluting spatial transcriptomics data through graph-based artificial intelligence
Authors: Song Qianqian , Su Jing 
Published: December 2020

AbstractRecent development of spatial transcriptomics (ST) is capable of associating spatial information at different spots in the tissue section with RNA abundance of cells within each spot, which is particularly important to understand tissue cytoarchitectures and functions. However, for such ST data, since a spot is usually larger than an individual cell, gene expressions measured at each spot are from a mixture of cells with heterogenous cell types. Therefore, ST data at each spot needs to be disentangled so as to reveal the cell compositions at that spatial spot. In this study, we propose a novel method, named deconvoluting spatial transcriptomics data through graph-based convolutional networks (DSTG), to accurately deconvolute the observed gene expressions at each spot and recover its cell constitutions, thus achieving high-level segmentation and revealing spatial architecture of cellular heterogeneity within tissues. DSTG not only demonstrates superior performance on synthetic spatial data generated from different protocols, but also effectively identifies spatial compositions of cells in mouse cortex layer, hippocampus slice and pancreatic tumor tissues. In conclusion, DSTG accurately uncovers the cell states and subpopulations based on spatial localization. DSTG is available as a ready-to-use open source software (https://github.com/Su-informatics-lab/DSTG) for precise interrogation of spatial organizations and functions in tissues.
Neuroanatomical basis of the nerve growth factor ovulation–induction pathway in llamas†
Authors: Carrasco Rodrigo A , Singh Jaswant , Ratto Marcelo H , Adams Gregg P 
Published: December 2020

AbstractThe objective of the study was to characterize the anatomical framework and sites of action of the nerve growth factor (NGF)-mediated ovulation-inducing system of llamas. The expression patterns of NGF and its receptors in the hypothalamus of llamas (n = 5) were examined using single and double immunohistochemistry/immunofluorescence. We also compare the expression pattern of the P75 receptor in the hypothalamus of llama and a spontaneous ovulator species (sheep, n = 5). Both NGF receptors (TrkA and P75) were highly expressed in the medial septum and diagonal band of Broca, and populations of TrkA cells were observed in the periventricular and dorsal hypothalamus. Unexpectedly, we found NGF immunoreactive cell bodies with widespread distribution in the hypothalamus but not in areas endowed with NGF receptors. The organum vasculosum of the lamina terminalis (OVLT) and the median eminence displayed immunoreactivity for P75. Double immunofluorescence using vimentin, a marker of tanycytes, confirmed that tanycytes were immunoreactive to P75 in the median eminence and in the OVLT. Additionally, tanycytes were in close association with GnRH and kisspeptin in the arcuate nucleus and median eminence of llamas. The choroid plexus of llamas contained TrkA and NGF immunoreactivity but no P75 immunoreactivity. Results of the present study demonstrate sites of action of NGF in the llama hypothalamus, providing support for the hypothesis of a central effect of NGF in the ovulation-inducing mechanism in llamas.
Boost in Test–Retest Reliability in Resting State fMRI with Predictive Modeling
Authors: Taxali Aman , Angstadt Mike , Rutherford Saige , Sripada Chandra 
Published: December 2020

Abstract
Recent studies found low test–retest reliability in functional magnetic resonance imaging (fMRI), raising serious concerns among researchers, but these studies mostly focused on the reliability of individual fMRI features (e.g., individual connections in resting state connectivity maps). Meanwhile, neuroimaging researchers increasingly employ multivariate predictive models that aggregate information across a large number of features to predict outcomes of interest, but the test–retest reliability of predicted outcomes of these models has not previously been systematically studied. Here we apply 10 predictive modeling methods to resting state connectivity maps from the Human Connectome Project dataset to predict 61 outcome variables. Compared with mean reliability of individual resting state connections, we find mean reliability of the predicted outcomes of predictive models is substantially higher for all 10 modeling methods assessed. Moreover, improvement was consistently observed across all scanning and processing choices (i.e., scan lengths, censoring thresholds, volume- vs. surface-based processing). For the most reliable methods, the reliability of predicted outcomes was mostly, though not exclusively, in the “good” range (above 0.60). Finally, we identified three mechanisms that help to explain why predicted outcomes of predictive models have higher reliability than individual imaging features. We conclude that researchers can potentially achieve higher test–retest reliability by making greater use of predictive models.
Motor Planning Modulates Neural Activity Patterns in Early Human Auditory Cortex
Authors: Gale Daniel J , Areshenkoff Corson N , Honda Claire , Johnsrude Ingrid S , Flanagan J Randall , Gallivan Jason P 
Published: December 2020

Abstract
It is well established that movement planning recruits motor-related cortical brain areas in preparation for the forthcoming action. Given that an integral component to the control of action is the processing of sensory information throughout movement, we predicted that movement planning might also modulate early sensory cortical areas, readying them for sensory processing during the unfolding action. To test this hypothesis, we performed 2 human functional magnetic resonance imaging studies involving separate delayed movement tasks and focused on premovement neural activity in early auditory cortex, given the area’s direct connections to the motor system and evidence that it is modulated by motor cortex during movement in rodents. We show that effector-specific information (i.e., movements of the left vs. right hand in Experiment 1 and movements of the hand vs. eye in Experiment 2) can be decoded, well before movement, from neural activity in early auditory cortex. We find that this motor-related information is encoded in a separate subregion of auditory cortex than sensory-related information and is present even when movements are cued visually instead of auditorily. These findings suggest that action planning, in addition to preparing the motor system for movement, involves selectively modulating primary sensory areas based on the intended action.
Neural Correlates of Interpersonal Space Permeability and Flexibility in Autism Spectrum Disorder
Authors: Massaccesi Claudia , Groessing Alexander , Rosenberger Lisa A , Hartmann Helena , Candini Michela , di Pellegrino Giuseppe , Frassinetti Francesca , Silani Giorgia 
Published: December 2020

Abstract
Previous research indicates that the size of interpersonal space at which the other is perceived as intrusive (permeability) and the ability to adapt interpersonal distance based on contextual factors (flexibility) are altered in Autism Spectrum Disorder (ASD). However, the neurophysiological basis of these alterations remains poorly understood. To fill this gap, we used fMRI and assessed interpersonal space preferences of individuals with ASD before and after engaging in cooperative and non-cooperative social interactions. Compared to matched controls, ASDs showed lower comfort in response to an approaching confederate, indicating preference for larger interpersonal space in autism (altered permeability). This preference was accompanied by reduced activity in bilateral dorsal intraparietal sulcus (dIPS) and left fusiform face area (FFA), regions previously shown to be involved in interpersonal space regulation. Furthermore, we observed differences in effective connectivity among dIPS, FFA, and amygdala in ASDs compared to controls, depending on the level of experienced comfort. No differences between groups were observed in interpersonal space regulation after an experienced social interaction (flexibility). Taken together, the present findings suggest that a dysregulation of the activity and connectivity of brain areas involved in interpersonal space processing may contribute to avoidance of physical proximity and social impairments in ASD.