bluuebunny/crossref_metadata_2025 huggingface dataset:
A Method for Computing Conceptual Distances between Medical Recommendations: Experiments in Modeling Medical Disagreement
Authors: Hematialam Hossein , Garbayo Luciana , Gopalakrishnan Seethalakshmi , Zadrozny Wlodek W.
Published: February 2021

Using natural language processing tools, we investigate the semantic differences in medical guidelines for three decision problems: breast cancer screening, lower back pain and hypertension management. The recommendation differences may cause undue variability in patient treatments and outcomes. Therefore, having a better understanding of their causes can contribute to a discussion on possible remedies. We show that these differences in recommendations are highly correlated with the knowledge brought to the problem by different medical societies, as reflected in the conceptual vocabularies used by the different groups of authors. While this article is a case study using three sets of guidelines, the proposed methodology is broadly applicable. Technically, our method combines word embeddings and a novel graph-based similarity model for comparing collections of documents. For our main case study, we use the CDC summaries of the recommendations (very short documents) and full (long) texts of guidelines represented as bags of concepts. For the other case studies, we compare the full text of guidelines with their abstracts and tables, summarizing the differences between recommendations. The proposed approach is evaluated using different language models and different distance measures. In all the experiments, the results are highly statistically significant. We discuss the significance of the results, their possible extensions, and connections to other domains of knowledge. We conclude that automated methods, although not perfect, can be applicable to conceptual comparisons of different medical guidelines and can enable their analysis at scale.
Improving Distant Supervised Relation Extraction with Noise Detection Strategy
Authors: Meng Xiaoyan , Jiang Tonghai , Zhou Xi , Ma Bo , Wang Yi , Zhao Fan
Published: February 2021

Distant supervised relation extraction (DSRE) is widely used to extract novel relational facts from plain text, so as to improve the knowledge graph. However, distant supervision inevitably suffers from the noisy labeling problem that will severely damage the performance of relation extraction. Currently, most DSRE methods are mainly focused on reducing the weights of noisy sentences, ignoring the bag-level noise where all sentences in a bag are wrongly labeled. In this paper, we present a novel noise detection-based relation extraction approach (NDRE) to automatically detect noisy labels with entity information and dynamically correct them, which can alleviate both instance-level and bag-level noisy problems. By this means, we can extend the dataset from the Web tables without introducing more noise. In this approach, to embed the semantics of sentences from corpus and web tables, we firstly propose a powerful sentence coder that employs an internal multi-head self-attention mechanism between the piecewise max-pooling convolutional neural network. Second, we adopt a noise detection strategy, which is expected to dynamically detect and correct the original noisy label according to the similarity between sentence representation and entity-aware embeddings. Then, we aggregate the information from corpus and web tables to make the final relation prediction. Experimental results on a public benchmark dataset demonstrate that our proposed approach achieves significant improvements over the state-of-the-art baselines and can effectively reduce the noisy labeling problem.
Microfluidic Platform for Examination of Effect of Chewing Xylitol Gum on Salivary pH, O2, and CO2
Authors: Podunavac Ivana , Hinić Stevan , Kojić Sanja , Jelenčiakova Nina , Radonić Vasa , Petrović Bojan , Stojanović Goran M.
Published: February 2021

Miniaturization of different measurement processes and a scaled-down approach open the possibility for rapid measurements with the small amounts of samples and reagents into a compact platform with integrated sensors and different measuring components. In this paper, we report a microfluidic approach for measurements of salivary pH, dissolved O2, and CO2 during chewing xylitol gum. The study was done with the samples of 30 healthy volunteers who were chewing a xylitol gum, and the measurements were performed in the microfluidic (MF) chip with integrated commercial PreSens sensors. Xylitol exhibited a significant effect on the pH of saliva in terms of its initial drop, which was the most significant between the 5th and 10th minutes. The effect of xylitol on the amount of oxygen and carbon dioxide in saliva cannot be confirmed. The employed microfluidic platform was shown to be applicable and effective in the analysis of salivary biomarkers relevant to caries development.
Good Practices in the Use of Augmented Reality for the Dissemination of Architectural Heritage of Rural Areas
Authors: Merchán M. J. , Merchán P. , Pérez E.
Published: February 2021

When it concerns dissemination, the relationship between cultural heritage and technology has not always been easy. On the one hand, the emotions involved in knowing, enjoying, and feeling a real heritage remain should not be eclipsed by the technological experience. On the other hand, technology cannot be relegated to the point where its use is so superficial as to make it irrelevant. Hence, in the search of good practices in the dissemination of cultural heritage, it is essential that interdisciplinary work teams, composed of humanists and technicians, design new experiences that try to achieve a balance between what must be shown and the way in which it is done. This paper aims to show the potential of augmented reality (AR) for the dissemination of cultural heritage, since it allows the perceiving of real remains while offering virtual reconstructions and complementary information, sounds, images, etc. A bibliometric analysis focusing on its use for the preservation of the memory of vernacular architecture is made. Then, from the understanding and interpretation of the ideas exposed in literature, a decalogue of good practices in the use of AR for architectural heritage is established considering the holistic perspectives that any dissemination initiative must have. These initiatives can attract people to rural areas and contribute to the improvement of their social and economic situation. As an example, a proof of concept of an AR experience is presented at the end of the paper.
Improving Monte Carlo Tree Search with Artificial Neural Networks without Heuristics
Authors: Cotarelo Alba , García-Díaz Vicente , Núñez-Valdez Edward Rolando , González García Cristian , Gómez Alberto , Chun-Wei Lin Jerry
Published: February 2021

Monte Carlo Tree Search is one of the main search methods studied presently. It has demonstrated its efficiency in the resolution of many games such as Go or Settlers of Catan and other different problems. There are several optimizations of Monte Carlo, but most of them need heuristics or some domain language at some point, making very difficult its application to other problems. We propose a general and optimized implementation of Monte Carlo Tree Search using neural networks without extra knowledge of the problem. As an example of our proposal, we made use of the Dots and Boxes game. We tested it against other Monte Carlo system which implements specific knowledge for this problem. Our approach improves accuracy, reaching a winning rate of 81% over previous research but the generalization penalizes performance.
Estimation of Saprolite Thickness Needed to Remove E. coli from Wastewater
Authors: Vepraskas Michael J. , Amoozegar Aziz , Gardner Terrence
Published: February 2021

Saprolite, weathered bedrock, is being used to dispose of domestic sewage through septic system drainfields, but the thickness of saprolite needed to remove biological contaminants is unknown for most saprolites. This study developed and tested a simple method for estimating the thickness of saprolite needed below septic drainlines to filter E. coli from wastewater using estimates of the volume of pores that are smaller than the length of the coliform (≤10 μm). Particle size distribution (texture) and water retention data were obtained for 12 different saprolites from the Piedmont and Mountain regions of North Carolina (N.C.). Saprolite textures ranged from clay loam to coarse sand. The volume of pores with diameters ≤10 μm were determined by water retention measurements for each saprolite. The data were used in an equation to estimate the saprolite thickness needed to filter E. coli. The estimated saprolite thicknesses ranged from 36 cm in the clay loam to 113 cm for the coarse sand. The average thickness across all samples was 58 cm. Saprolite thickness estimates increased as silt percentage decreased and as sand percentage and in situ saturated hydraulic conductivity increased. Silt percentage may be most useful for estimating appropriate saprolite thicknesses in the field.
How to Correctly Detect Face-Masks for COVID-19 from Visual Information?
Authors: Batagelj Borut , Peer Peter , Štruc Vitomir , Dobrišek Simon
Published: February 2021

The new Coronavirus disease (COVID-19) has seriously affected the world. By the end of November 2020, the global number of new coronavirus cases had already exceeded 60 million and the number of deaths 1,410,378 according to information from the World Health Organization (WHO). To limit the spread of the disease, mandatory face-mask rules are now becoming common in public settings around the world. Additionally, many public service providers require customers to wear face-masks in accordance with predefined rules (e.g., covering both mouth and nose) when using public services. These developments inspired research into automatic (computer-vision-based) techniques for face-mask detection that can help monitor public behavior and contribute towards constraining the COVID-19 pandemic. Although existing research in this area resulted in efficient techniques for face-mask detection, these usually operate under the assumption that modern face detectors provide perfect detection performance (even for masked faces) and that the main goal of the techniques is to detect the presence of face-masks only. In this study, we revisit these common assumptions and explore the following research questions: (i) How well do existing face detectors perform with masked-face images? (ii) Is it possible to detect a proper (regulation-compliant) placement of facial masks? and iii) How useful are existing face-mask detection techniques for monitoring applications during the COVID-19 pandemic? To answer these and related questions we conduct a comprehensive experimental evaluation of several recent face detectors for their performance with masked-face images. Furthermore, we investigate the usefulness of multiple off-the-shelf deep-learning models for recognizing correct face-mask placement. Finally, we design a complete pipeline for recognizing whether face-masks are worn correctly or not and compare the performance of the pipeline with standard face-mask detection models from the literature. To facilitate the study, we compile a large dataset of facial images from the publicly available MAFA and Wider Face datasets and annotate it with compliant and non-compliant labels. The annotation dataset, called Face-Mask-Label Dataset (FMLD), is made publicly available to the research community.
A Methodology for Utilizing Vector Space to Improve the Performance of a Dog Face Identification Model
Authors: Yoon Bohan , So Hyeonji , Rhee Jongtae
Published: February 2021

Recent improvements in the performance of the human face recognition model have led to the development of relevant products and services. However, research in the similar field of animal face identification has remained relatively limited due to the greater diversity and complexity in shape and the lack of relevant data for animal faces such as dogs. In the face identification model using triplet loss, the length of the embedding vector is normalized by adding an L2-normalization (L2-norm) layer for using cosine-similarity-based learning. As a result, object identification depends only on the angle, and the distribution of the embedding vector is limited to the surface of a sphere with a radius of 1. This study proposes training the model from which the L2-norm layer is removed by using the triplet loss to utilize a wide vector space beyond the surface of a sphere with a radius of 1, for which a novel loss function and its two-stage learning method. The proposed method classifies the embedding vector within a space rather than on the surface, and the model’s performance is also increased. The accuracy, one-shot identification performance, and distribution of the embedding vectors are compared between the existing learning method and the proposed learning method for verification. The verification was conducted using an open-set. The resulting accuracy of 97.33% for the proposed learning method is approximately 4% greater than that of the existing learning method.
Configuration Design of an Upper Limb Rehabilitation Robot with a Generalized Shoulder Joint
Authors: Yan Hao , Wang Hongbo , Chen Peng , Niu Jianye , Ning Yuansheng , Li Shuangshuang , Wang Xusheng
Published: February 2021

For stroke patients with upper limb motor dysfunction, rehabilitation training with the help of rehabilitation robots is a social development trend. Existing upper limb rehabilitation robots have difficulty fully fitting the complex motion of the human shoulder joint and have poor human–robot compatibility. In this paper, based on the anatomical structure of the human upper limb, an equivalent mechanism model of the human upper limb is established. The configuration synthesis of the upper limb rehabilitation mechanism was carried out, a variety of shoulder joint man–machine closed-chain Θs and shoulder elbow human–machine closed-chain Θse configuration combinations were synthesized, and the configuration model with compatibility and reduced moment conduction attenuation was selected from them. Two configurations, 2Pa1P3Ra and 5Ra1P, are proposed for the generalized shoulder joint mechanism of the robot. The closed-chain kinematic models of the two configurations are established, and the velocity Jacobian matrix is obtained. Motion performance analysis, condition reciprocal analysis and operability ellipsoid analysis of different configuration design schemes were carried out in different operation planes. The results show that in the normal upper limb posture of the human body, the 5Ra1P configuration of the shoulder joint has better kinematic performance. Finally, on this basis, an upper limb rehabilitation robot prototype with good human–computer compatibility is developed, and its moving space was verified.
An Intrusion Resistant SCADA Framework Based on Quantum and Post-Quantum Scheme
Authors: Ghosh Sagarika , Zaman Marzia , Sakauye Gary , Sampalli Srinivas
Published: February 2021

The rapid emergence of quantum computing threatens current Supervisory Control and Data Acquisition (SCADA) security standards, mainly, American Gas Association (AGA)-12. Therefore, researchers are developing various security schemes based on either quantum or post-quantum algorithms. However, the efficiency of quantum algorithms impacts the security of the post-quantum digital signature scheme. We propose an intrusion resistant algorithm exploiting and applying quantum principles in the post-quantum signature algorithm. We use the Bennett 1992 (B92) protocol, a quantum key distribution scheme, to obtain the cipher, and the practical Stateless Hash-based Signatures (SPHINCS)-256 protocol to obtain a post-quantum signature. However, instead of Chacha-12, a well-known cryptographically secure pseudo-random number generator, we apply a quantum random number generator to obtain a truly random Hash to Obtain Random Subset (HORS) signature with Tree (HORST) secret key used in SPHINCS-256. We have implemented the design in Python with the Quantum Information Toolkit. We have validated the proposed algorithm using the Probabilistic Model Checking for Performance and Reliability Analysis (PRISM) and Scyther tools. Moreover, the National Institute of Standards and Technology (NIST) statistical tests show that the proposed algorithm key pairs have randomness of 98% and RSA and ECDSA are below 96%.
Ischemic Stroke Prediction by Exploring Sleep Related Features
Authors: Xie Jia , Wang Zhu , Yu Zhiwen , Guo Bin , Zhou Xingshe
Published: February 2021

Ischemic stroke is one of the typical chronic diseases caused by the degeneration of the neural system, which usually leads to great damages to human beings and reduces life quality significantly. Thereby, it is crucial to extract useful predictors from physiological signals, and further diagnose or predict ischemic stroke when there are no apparent symptoms. Specifically, in this study, we put forward a novel prediction method by exploring sleep related features. First, to characterize the pattern of ischemic stroke accurately, we extract a set of effective features from several aspects, including clinical features, fine-grained sleep structure-related features and electroencephalogram-related features. Second, a two-step prediction model is designed, which combines commonly used classifiers and a data filter model together to optimize the prediction result. We evaluate the framework using a real polysomnogram dataset that contains 20 stroke patients and 159 healthy individuals. Experimental results demonstrate that the proposed model can predict stroke events effectively, and the Precision, Recall, Precision Recall Curve and Area Under the Curve are 63%, 85%, 0.773 and 0.919, respectively.
Source Apportionment and Toxic Potency of Polycyclic Aromatic Hydrocarbons (PAHs) in the Air of Harbin, a Cold City in Northern China
Authors: Liu Haitao , Li Bo , Qi Hong , Ma Lixin , Xu Jianzhong , Wang Minling , Ma Wenwen , Tian Chongguo
Published: February 2021

A total of 68 PUF samples were collected seasonally from 17 sampling sites in Harbin, China from May 2016 to April 2017 for analyzing 15 congeners of gaseous polycyclic aromatic hydrocarbons (Σ15PAHs). An improved non-negative matrix (NMF) model and a positive matrix factorization (PMF) model were used to apportion the sources of PAHs. The carcinogenic risk due to exposure to PAHs was estimated by the toxicity equivalent of BaP (BaPeq). The results showed that the average concentration of Σ15PAHs was 68.3 ± 22.3 ng/m3, and the proportions of 3-ring, 4-ring, 5-ring, and 6-ring PAHs were 64.4%, 32.6%, 2.10%, and 0.89%, respectively. Among the six typical functional areas in Harbin, the Σ15PAHs concentrations were 98.1 ± 76.7 ng/m3, 91.2 ± 76.2 ng/m3, 71.4 ± 75.6 ng/m3, 67.9 ± 65.6 ng/m3, 42.6 ± 34.7 ng/m3, and 38.5 ± 38.0 ng/m3 in the wastewater treatment plant, industrial zone, business district, residential area, school, and suburb, respectively. During the sampling period, the highest concentration of Σ15PAHs was in winter. The improved NMF model and PMF model apportioned the PAHs into three sources including coal combustion, biomass burning, and vehicle exhaust. The contributions of coal combustion, biomass burning, and vehicle exhausts were 34.6 ± 3.22%, 48.6 ± 4.03%, and 16.8 ± 5.06%, respectively. Biomass burning was the largest contributor of Σ15PAHs concentrations in winter and coal combustion contributed significantly to the concentrations in summer. The average ΣBaPeq concentration was 0.54 ± 0.23 ng/m3 during the sampling period, high concentrations occurred in the cold season and low levels presented in the warm period. Vehicle exhaust was the largest contributor to the ΣBaPeq concentration of PAHs in Harbin.
Effects of Recent Climate Change on Maize Yield in Southwest Ecuador
Authors: Lopez Gina , Gaiser Thomas , Ewert Frank , Srivastava Amit
Published: February 2021

In recent years, evidence of recent climate change has been identified in South America, affecting agricultural production negatively. In response to this, our study employs a crop modelling approach to estimate the effects of recent climate change on maize yield in four provinces of Ecuador. One of them belongs to a semi-arid area. The trend analysis of maximum temperature, minimum temperature, precipitation, wind speed, and solar radiation was done for 36 years (from 1984 to 2019) using the Mann–Kendall test. Furthermore, we simulated (using the LINTUL5 model) the counterfactual maize yield under current crop management in the same time-span. During the crop growing period, results show an increasing trend in the temperature in all the four studied provinces. Los Rios and Manabi showed a decreasing trend in radiation, whereas the semi-arid Loja depicted a decreasing precipitation trend. Regarding the effects of climate change on maize yield, the semi-arid province Loja showed a more significant negative impact, followed by Manabi. The yield losses were roughly 40 kg ha−1 and 10 kg ha−1 per year, respectively, when 250 kg N ha−1 is applied. The simulation results showed no effect in Guayas and Los Rios. The length of the crop growing period was significantly different in the period before and after 2002 in all provinces. In conclusion, the recent climate change impact on maize yield differs spatially and is more significant in the semi-arid regions.
Assessment of Trends and Uncertainties in the Atmospheric Boundary Layer Height Estimated Using Radiosounding Observations over Europe
Authors: Madonna Fabio , Summa Donato , Di Girolamo Paolo , Marra Fabrizio , Wang Yuanzu , Rosoldi Marco
Published: February 2021

Trends in atmospheric boundary layer height may represent an indication of climate changes. The related modified interaction between the surface and free atmosphere affects both thermodynamics variables and dilution of chemical constituents. Boundary layer is also a major player in various feedback mechanisms of interest for climate models. This paper investigates trends in the nocturnal and convective boundary layer height at mid-latitudes in Europe using radiosounding profiles from the Integrated Global Radiosounding Archive (IGRA). Atmospheric data from the European Centre for Medium-Range Weather Forecasts (ECMWF) ReAnalysis v5 (ERA5) and from the GCOS Reference Upper-Air Network (GRUAN) Lindenberg station are used as intercomparison datasets for the study of structural and parametric uncertainties in the trend analysis. Trends are calculated after the removal of the lag-1 autocorrelation term for each time series. The study confirms the large differences reported in literature between the boundary layer height estimates obtained with the two different algorithms used for IGRA and ERA5 data: ERA5 shows a density distribution with median values of 350 m and 1150 m for the night and the daytime data, respectively, while the corresponding IGRA median values are of 1150 m and 1750 m. An overall good agreement between the estimated trends is found for nighttime data, while daytime ERA5 boundary layer height estimates over Europe are characterized by a lower spatial homogeneity than IGRA. Parametric uncertainties due to missing data in both the time and space domain are also investigated: the former is not exceeding 1.5 m, while the latter are within 10 m during night and 17 m during the day. Recommendations on dataset filtering based on time series completeness are provided. Finally, the comparison between the Lindenberg data as processed at high-resolution by GRUAN and as provided to IGRA at a lower resolution, shows the significant impact of using high-resolution data in the determination of the boundary layer height, with differences from about 200 m to 450 m for both night and day, as well as a large deviation in the estimated trend.
High-Resolution Analysis of Wind Flow Behavior on Ship Stacks Configuration: A Portuguese Case Study
Authors: Correia Luís P. , Rafael Sandra , Sorte Sandra , Rodrigues Vera , Borrego Carlos , Monteiro Alexandra
Published: February 2021

Atmospheric emissions related to harbor-related activities can significantly contribute to air pollution of coastal urban areas and so, could have implications to the citizens’ health that live in those areas. Of great concern is the local impact of the emissions that are generated while ships are at berth, since not all types of ships switch off the main engines. This paper intends to investigate the influence of the stack configuration for generic cargo ships on the exhaust smoke dispersion, using the Port of Leixões as a case study and a series of wind tunnel experiments with support of Particle Image Velocimetry (PIV) technique. For that, different configurations of the stack of a cargo ship (in terms of height, geometry and diameter) were simulated under the typical wind conditions of the study area. The PIV results indicate negligible differences between the medium and long stack height, with the short stack height presenting a strong impact on the flow field around the stack. For the short stack height, the flow field is not only disturbed by the stack, but also by the cargo ship bridge, with both obstacles promoting disturbances on the flow field and creating a large wake turbulence effect, which is important for the downwash phenomena. Regarding the effects linked with two distinct geometries (straight or curved), the results show that the straight chimney led to higher perturbation of wind field when compared with the curved geometry. The curved stack presents an increase of vorticity, indicating the generation of more turbulent structures. The PIV results also confirmed that higher wind velocity at the inlet conducts to higher vorticity levels, as well as a higher number of Kelvin–Helmholtz structures. For distinct wind conditions the PIV measurements point out different patterns, indicating the northern wind direction as the most favorable condition for the exposure of dock workers to pollutants. Overall, the results showed that a ship stack with a curved end, medium length and smaller diameter has the capability to promote the behaviors in the flow that are coherent with increased pollutant dispersion.
IoT Technologies for Livestock Management: A Review of Present Status, Opportunities, and Future Trends
Authors: Akhigbe Bernard Ijesunor , Munir Kamran , Akinade Olugbenga , Akanbi Lukman , Oyedele Lukumon O.
Published: February 2021

The world population currently stands at about 7 billion amidst an expected increase in 2030 from 9.4 billion to around 10 billion in 2050. This burgeoning population has continued to influence the upward demand for animal food. Moreover, the management of finite resources such as land, the need to reduce livestock contribution to greenhouse gases, and the need to manage inherent complex, highly contextual, and repetitive day-to-day livestock management (LsM) routines are some examples of challenges to overcome in livestock production. The Internet of Things (IoT)’s usefulness in other vertical industries (OVI) shows that its role will be significant in LsM. This work uses the systematic review methodology of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to guide a review of existing literature on IoT in OVI. The goal is to identify the IoT’s ecosystem, architecture, and its technicalities—present status, opportunities, and expected future trends—regarding its role in LsM. Among identified IoT roles in LsM, the authors found that data will be its main contributor. The traditional approach of reactive data processing will give way to the proactive approach of augmented analytics to provide insights about animal processes. This will undoubtedly free LsM from the drudgery of repetitive tasks with opportunities for improved productivity.
The Potential Relevance of the Microbiome to Hair Physiology and Regeneration: The Emerging Role of Metagenomics
Authors: Constantinou Andria , Kanti Varvara , Polak-Witka Katarzyna , Blume-Peytavi Ulrike , Spyrou George M. , Vogt Annika
Published: February 2021

Human skin and hair follicles are recognized sites of microbial colonization. These microbiota help regulate host immune mechanisms via an interplay between microbes and immune cells, influencing homeostasis and inflammation. Bacteria affect immune responses by controlling the local inflammatory milieu, the breakdown of which can result in chronic inflammatory disorders. Follicular microbiome shifts described in some inflammatory cutaneous diseases suggest a link between their development or perpetuation and dysbiosis. Though the hair follicle infundibulum is an area of intense immunological interactions, bulb and bulge regions represent immune-privileged niches. Immune privilege maintenance seems essential for hair growth and regeneration, as collapse and inflammation characterize inflammatory hair disorders like alopecia areata and primary cicatricial alopecia. Current research largely focuses on immunological aberrations. However, studies suggest that external stimuli and interactions across the follicular epithelium can have profound effects on the local immune system, homeostasis, and cycling. Herein, we review hair follicle bacterial colonization, its possible effects on the underlying tissue, and links to the pathogenesis of alopecia, beyond the pure investigation of specific species abundance. As skin microbiology enters the metagenomics era, multi-dimensional approaches will enable a new level of investigations on the effects of microorganisms and metabolism on host tissue.
NeuroDante: Poetry Mentally Engages More Experts but Moves More Non-Experts, and for Both the Cerebral Approach Tendency Goes Hand in Hand with the Cerebral Effort
Authors: Cartocci Giulia , Rossi Dario , Modica Enrica , Maglione Anton Giulio , Martinez Levy Ana C. , Cherubino Patrizia , Canettieri Paolo , Combi Mariella , Rea Roberto , Gatti Luca , Babiloni Fabio
Published: February 2021

Neuroaesthetics, the science studying the biological underpinnings of aesthetic experience, recently extended its area of investigation to literary art; this was the humus where neurocognitive poetics blossomed. Divina Commedia represents one of the most important, famous and studied poems worldwide. Poetry stimuli are characterized by elements (meter and rhyme) promoting the processing fluency, a core aspect of neuroaesthetics theories. In addition, given the evidence of different neurophysiological reactions between experts and non-experts in response to artistic stimuli, the aim of the present study was to investigate, in poetry, a different neurophysiological cognitive and emotional reaction between Literature (L) and Non-Literature (NL) students. A further aim was to investigate whether neurophysiological underpinnings would support explanation of behavioral data. Investigation methods employed: self-report assessments (recognition, appreciation, content recall) and neurophysiological indexes (approach/withdrawal (AW), cerebral effort (CE) and galvanic skin response (GSR)). The main behavioral results, according to fluency theories in aesthetics, suggested in the NL but not in the L group that the appreciation/liking went hand by hand with the self-declared recognition and with the content recall. The main neurophysiological results were: (i) higher galvanic skin response in NL, whilst higher CE values in L; (ii) a positive correlation between AW and CE indexes in both groups. The present results extended previous evidence relative to figurative art also to auditory poetry stimuli, suggesting an emotional attenuation “expertise-specific” showed by experts, but increased cognitive processing in response to the stimuli.
Is Right Angular Gyrus Involved in the Metric Component of the Mental Body Representation in Touch and Vision? A tDCS Study
Authors: Spitoni Grazia Fernanda , Pireddu Giorgio , Zanellati Valerio , Dionisi Beatrice , Galati Gaspare , Pizzamiglio Luigi
Published: February 2021

Several studies have found in the sense of touch a good sensory modality by which to study body representation. Here, we address the “metric component of body representation”, a specific function developed to process the discrimination of tactile distances on the body. The literature suggests the involvement of the right angular gyrus (rAG) in processing the tactile metricity on the body. The question of this study is the following: is the rAG also responsible for the visual metric component of body representation? We used tDCS (anodal and sham) in 20 subjects who were administered an on-body distance discrimination task with both tactile and visual stimuli. They were also asked to perform the same task in a near-body condition. The results allow us to confirm the role of rAG in the estimation of tactile distances. Further, we also showed that rAG might be involved in the discrimination of distances on the body not only in tactile but also in visual modality. Finally, based on the significant effects of anodal stimulation even in a near-body visual discrimination task, we proposed a higher-order function of the AG in terms of a supramodal comparator of quantities.
The Influence of Diabetes on Multisensory Integration and Mobility in Aging
Authors: Mahoney Jeannette R. , Verghese Joe , George Claudene
Published: February 2021

(1) Background: one out of every four adults over the age of 65 are living with diabetes, and this alarming rate continues to increase with age. Diabetes in older adults is associated with many adverse health outcomes, including sensory and motor impairments. The objective of this exploratory study was to determine whether diabetes influences the interplay between multisensory integration processes and mobility in aging. (2) Methods: in this cross-sectional observational study, we recruited 339 non-demented older adults (76.59 ± 6.21 years; 52% female, 18% with diabetes). Participants completed a simple reaction time test in response to visual, somatosensory, and combined visual-somatosensory stimulation. Magnitude of visual-somatosensory integration was computed and served as the independent variable. (3) Results: logistic regression revealed that presence of diabetes was inversely associated with the magnitude of visual-somatosensory integration (β = −3.21; p < 0.01). Further, mediation models revealed that presence of diabetes negatively influenced the relationship of visual–somatosensory integration magnitude with balance (95% CI −0.16, −0.01) and gait (95% CI −0.09, −0.01). Participants with diabetes and taking insulin (n = 14) failed to integrate sensory information entirely; (4) conclusions: taken together, results from this exploration provide compelling evidence to support the adverse effect of diabetes on both multisensory and motor functioning in older adults.
Analysis of HIC and Hydrostatic Pressure in the Human Head during NOCSAE Tests of American Football Helmets
Authors: Dymek Mateusz , Ptak Mariusz , Ratajczak Monika , Fernandes Fábio A. O. , Kwiatkowski Artur , Wilhelm Johannes
Published: February 2021

Brain damage is a serious economic and social burden. Contact sports such as American football, are one of the most common sources of concussions. The biomechanical response of the head–helmet system caused by dynamic loading plays a major role. The literature has focused on measuring the resultant kinematics that act on the head and helmet during tackles. However, few studies have focused on helmet validation tests, supported by recent findings and emerging numerical approaches. The future of helmet standards could benefit from insights at the level of injury mechanisms, using numerical tools to assess the helmets. Therefore, in this work, a numerical approach is employed to investigate the influence of intracranial pressure (ICP) on brain pathophysiology during and after helmeted impacts, which are common in American football. The helmeted impacts were performed at several impact locations according to the NOCSAE standard (configurations A, AP, B, C, D, F, R, UT). In order to evaluate the ICP levels, the αHEAD finite element head and brain model was combined with a Hybrid III-neck structure and then coupled with an American football helmet to simulate the NOCSAE impacts. In addition, the ICP level was analyzed together with the resulting HIC value, since the latter is commonly used, in this application and others, as the injury criterion. The obtained results indicate that ICP values exceed the common threshold of head injury criteria and do not correlate with HIC values. Thus, this work raises concern about applying the HIC to predict brain injury in American football direct head impacts, since it does not correlate with ICP predicted with the FE head model.
Regional Gray Matter Volume Changes in Parkinson’s Disease with Orthostatic Hypotension
Authors: Kim Jung Bin , Kim Hayom , Lee Chan-Nyung , Park Kun-Woo , Kim Byung-Jo
Published: February 2021

Neurodegenerative change in the central nervous system has been suggested as one of the pathophysiological mechanisms of autonomic nervous system dysfunction in Parkinson’s disease (PD). We analyzed gray matter (GM) volume changes and clinical parameters in patients with PD to investigate any involvement in the brain structures responsible for autonomic control in patients with PD having orthostatic hypotension (OH). Voxel-based morphometry was applied to compare regional GM volumes between PD patients with and without OH. Multivariate logistic regression analysis using a hierarchical model was carried out to identify clinical factors independently contributing to the regional GM volume changes in PD patients with OH. The Sobel test was used to analyze mediation effects between the independent contributing factors to the GM volume changes. PD patients with OH had more severe autonomic dysfunction and reduction in volume in the right inferior temporal cortex than those without OH. The right inferior temporal volume was positively correlated with the Qualitative Scoring MMSE Pentagon Test (QSPT) score, reflecting visuospatial/visuoperceptual function, and negatively correlated with the Composite Autonomic Severity Score (CASS). The CASS and QSPT scores were found to be factors independently contributing to regional volume changes in the right inferior temporal cortex. The QSPT score was identified as a mediator in which regional GM volume predicts the CASS. Our findings suggest that a decrease in the visuospatial/visuoperceptual process may be involved in the presentation of autonomic nervous system dysfunction in PD patients.
One Year Trajectory of Caregiver Burden in Parkinson’s Disease and Analysis of Gender-Specific Aspects
Authors: Klietz Martin , von Eichel Hannah , Schnur Theresa , Staege Selma , Höglinger Günter U. , Wegner Florian , Stiel Stephanie
Published: February 2021

Parkinson’s disease (PD) is a slowly progressive neurodegenerative movement disorder that leads to impairments in activities of daily living. In addition to reducing patients’ quality of life, this disease also affects caregivers’ well-being. Until recently, caregiver burden was mainly assessed by generic questionnaires, which do not take the characteristics of the chronic disease into consideration. In the case of PD, this issue has been addressed by the introduction of the “Parkinson’s disease caregiver burden” questionnaire (PDCB). Data on longitudinal trajectories of caregiver burden are still missing in the literature. In this study, we assessed the one-year trajectory of caregiver burden by the PDCB as a disease-specific questionnaire. Further, gender-specific aspects of caregiver burden were analyzed by applying a caregiver task questionnaire. PDCB total score (n = 84 patients and caregivers) did not significantly change from baseline (30.4) to one year at follow-up (31.5). No significant difference was detected between female and male caregivers in global burden and-specific caregiver tasks. Our data showed only a mild increase of caregiver burden in the timeframe of one year. Gender-specific differences do not seem to impact-specific caregiver tasks in the presented study population.
Motivated Interpretations of Deceptive Information
Authors: Vainapel Sigal , Shani Yaniv , Shalvi Shaul
Published: February 2021

We examine whether people seek information that might help them make sense of others’ dishonest behavior. Participants were told that a hypothetical partner (either a friend or a stranger) had engaged in a task in which the partner could lie to boost their earnings at the expense of the participant’s earnings. Participants were less likely to search for information that can justify potential dishonest behavior conducted by a friend than by a stranger (Experiment 1). When participants knew for certain that their partners had lied to them, they were less likely to assume that that the lie was justified when told that the partner was a friend rather than a stranger (Experiment 2). The results imply that people are more likely to search for information that may reduce the severity of possible dishonest behavior when a stranger, rather than a friend, is responsible for the behavior.
Preliminary Analysis of the Use of Construction Waste to Replace Conventional Aggregates in Concrete
Authors: Silva Fernando A. N. , Delgado João M. P. Q. , Azevedo António C. , Lima António G. B. , Vieira Castorina S.
Published: February 2021

This work aims to study the influence of using construction and demolition waste in the replacement of coarse and fine aggregate to produce recycled aggregate concrete (RAC). A moderate compressive strength concrete made with usual fine and coarse aggregate was used as a benchmark material. Compressive and split tensile tests were performed using 120 cylindrical concrete specimens with 150 mm diameter and 300 mm length. Four-point flexural tests in reinforced beams made with conventional concrete and RAC were performed. The results obtained showed that the use of recycled fine aggregates, in both percentages of substitution investigated—50% and 100%—did not generate any deleterious influence on the values of compressive strength and split tensile strength of the RACs produced. Tin fact, the mechanical strengths of RACs produced with recycled fine aggregate were equal or higher than those from the reference concrete. The same behavior was not observed, however, when the recycled coarse aggregate was used. For this case, decreases in concrete mechanical strengths were observed, especially in compressive strength, with values around 35% lower when compared to the reference concrete. Tensile mechanical tests results confirmed the excellent behavior of all RACs made with replacement of usual fine aggregates by recycled. Bending tests performed in reinforced RAC beams had as objective to evaluate the deformation profile of the beams. The obtained results showed that RAC beams with full replacement of usual fine aggregate by the recycled aggregates have presented little changes in the global behavior, an aspect that encourages its use.
Inhibition of PI3K Isoform p110γ Increases Both Anti-Tumor and Immunosuppressive Responses to Aggressive Murine Head and Neck Squamous Cell Carcinoma with Low Immunogenicity
Authors: Anderson Kelvin , Ryan Nathan , Alkhimovitch Anastasia , Siddiqui Arham , Oghumu Steve
Published: February 2021

HNSCC is the sixth most common cancer, with around 650,000 new cases yearly. Gain of function mutations in the PI3K pathway are common in HNSCC, and inhibition of the PI3K p110γ subunit has shown promise in HNSCC treatment. However, given that PI3K p110γ plays an important role in myeloid and lymphoid immune cell function, it is essential to understand how PI3K p110γ inhibition affects the anti-tumor immune response independent of tumor cells. To elucidate PI3K p110γ function in HNSCC, we employed an orthotopic mouse model using poorly immunogenic and aggressive cell line MOC2 on Pik3cg−/− mice. We observed that wild-type and Pik3cg−/− mice displayed similar rates of HNSCC tumor growth and metastasis after 20 days following tumor injection. T-cell infiltration and intrinsic T-cell responses to MOC2 oral tumors were comparable between wild-type and Pik3cg−/− mice. Interestingly, the immune response of tumor-bearing Pik3cg−/− mice was marked by increased anti-tumor cytotoxic molecules (IFN-γ, IL-17)) by T-cells and immune checkpoint marker (PD-L1, PD-1) expression by myeloid cells and T-cells compared to tumor-bearing wild-type mice. Taken together, our findings demonstrate that inhibition of PI3K p110γ modulates tumor-associated immune cells, which likely potentiates HNSCC treatment when used in combination with selective checkpoint inhibitors.
Multi-Omics Data Analysis of Gene Expressions and Alterations, Cancer-Associated Fibroblast and Immune Infiltrations, Reveals the Onco-Immune Prognostic Relevance of STAT3/CDK2/4/6 in Human Malignancies
Authors: Lawal Bashir , Lin Li-Ching , Lee Jih-Chin , Chen Jia-Hong , Bekaii-Saab Tanios , Wu Alexander , Ho Ching-Liang
Published: February 2021

Signal transducer and activator of transcription 3 (STAT3)/Cyclin-dependent kinases are multifunctional proteins that play an important implicative role in cancer initiations, progression, drug resistance, and metastasis, and has been extensively explored in cancer therapy. However, the genetic alterations of STAT3/CDK2/4/6 and its role in predicting immune infiltration and immunotherapeutic response are yet to be well exploited. In this study, we use in silico methods to analyze differential expression, prognostic value, genetic and epigenetic alterations, association with tumor-infiltrating immune cells, and cancer-associated fibroblast (CAF) infiltrations of STAT3/CDK2/4/6 in multiple cancer types. Our results revealed that the expression of STAT3/CDK2/4/6 was altered in various cancers and is associated with poor overall and disease-free survival of the cohorts. Moreover, genetic alterations in STAT3/CDK2/4/6 co-occurred with a number of other genetic alterations and are associated with poorer prognoses of the cohorts. The protein-protein interaction (PPI) network analysis suggests CDK2/4/6/STAT3 may directly interact with factors that promote tumorigenesis and immune response. We found that STAT3/CDK2/4/6 expressions were associated with infiltrations of CAF and the various immune cells in multiple cancers and it’s associated with poor response to immunotherapy. Collectively, our study suggested that STAT3/CDK2/4/6 are important onco-immune signatures that play central roles in tumor immune invasion, poor prognoses and, immune therapy response. Findings from the present study may therefore be clinically useful in prognosis assessment and follow-up management of immunotherapy.
Pharmacological Activation of p53 during Human Monocyte to Macrophage Differentiation Attenuates Their Pro-Inflammatory Activation by TLR4, TLR7 and TLR8 Agonists
Authors: Namgaladze Dmitry , Brüne Bernhard
Published: February 2021

The transcription factor p53 has well-recognized roles in regulating cell cycle, DNA damage repair, cell death, and metabolism. It is an important tumor suppressor and pharmacological activation of p53 by interrupting its interaction with the ubiquitin E3 ligase mouse double minute 2 homolog (MDM2) is actively explored for anti-tumor therapies. In immune cells, p53 modulates inflammatory responses, but the impact of p53 on macrophages remains incompletely understood. In this study, we used the MDM2 antagonist idasanutlin (RG7388) to investigate the responses of primary human macrophages to pharmacological p53 activation. Idasanutlin induced a robust p53-dependent transcriptional signature in macrophages, including several pro-apoptotic genes. However, idasanutlin did not generally sensitize macrophages to apoptosis, except for an enhanced response to a Fas-stimulating antibody. In fully differentiated macrophages, idasanutlin did not affect pro-inflammatory gene expression induced by toll-like receptor 4 (TLR4), TLR3, and TLR7/8 agonists, but inhibited interleukin-4-induced macrophage polarization. However, when present during monocyte to macrophage differentiation, idasanutlin attenuated inflammatory responses towards activation of TLR4 and TLR7/8 by low doses of lipopolysaccharide or resiquimod (R848). This was accompanied by a reduced expression of CD14, TLR7, and TLR8 in macrophages differentiated in the presence of idasanutlin. Our data suggest anti-inflammatory effects of pharmacological p53 activation in differentiating human macrophages.