bluuebunny/crossref_metadata_2025 huggingface dataset:
Anandamide Exerts a Differential Effect on Human Placenta Before and After the Onset of Labor
Authors: Accialini Paula , Abán Cyntia , Etcheverry Tomás , Negri Malbrán Mercedes , Leguizamón Gustavo , Herlax Vanesa , Maté Sabina , Farina Mariana
Published: May 2021

The onset of labor involves the action of multiple factors and recent reports have postulated the endocannabinoid system as a new regulator of this process. Our objective was to study the role of anandamide, one of the main endocannabinoids, on the regulation of placental molecules that contribute to the onset of labor at term. Placental samples were obtained from patients with laboring vaginal deliveries and from non-laboring elective cesarean sections. Vaginal delivery placentas produced higher prostaglandins levels than cesarean section samples. Besides, no differences were observed in NOS basal activity between groups. Incubation of vaginal delivery placentas with anandamide increased prostaglandins concentration and decreased NOS activity. Antagonism of type-1cannabinoid receptor (CB1) did not alter the effect observed on NOS activity. Conversely, incubation of cesarean section placentas with anandamide reduced prostaglandins levels and enhanced NOS activity, the latter involving the participation of CB1. Furthermore, we observed a differential expression of the main components of the endocannabinoid system between placental samples, being the change in CB1 localization the most relevant finding. Our results suggest that anandamide acts as a modulator of the signals that regulate labor, exerting differential actions depending on CB1 localization in laboring or non-laboring term placentas.
Aerobic and Anaerobic Speed Predicts 800-m Running Performance in Young Recreational Runners
Authors: Støren Øyvind , Helgerud Jan , Johansen Jan-Michael , Gjerløw Lars-Erik , Aamlid Aanund , Støa Eva Maria
Published: May 2021

The main aim was to investigate the impact of maximal aerobic speed (MAS), maximal anaerobic speed (MANS), and time to exhaustion (TTE) at 130% MAS, on 800-m running time performance (800TT). A second aim was to investigate the impact of anaerobic speed reserve (ASR), i.e., the relative difference between MAS and MANS, on TTE. A total of 22 healthy students classified as recreational runners participated in a cross-sectional study. They were tested for maximal oxygen consumption (VO2max), oxygen cost of running (CR), time performance at 100 m (100TT), time performance at 800 m (800TT), and TTE. MAS was calculated as VO2max × CR–1, and MANS was calculated as 100TT velocity. Both MAS and MANS correlated individually with 800TT (r = –0.74 and –0.67, respectively, p < 0.01), and the product of MAS and MANS correlated strongly (r = –0.82, p < 0.01) with 800TT. TTE did not correlate with 800TT. Both ASR and % MANS correlated strongly with TTE (r = 0.90 and –0.90, respectively, p < 0.01). These results showed that 800TT was first and foremost dependent on MAS and MANS, and with no impact from TTE. It seemed that TTE was merely a product of each runner’s individual ASR. We suggest a simplified model of testing and training for 800TT, namely, by focusing on VO2max, CR, and short sprint velocity, i.e., MAS and MANS.
Dissection of the Genetic Basis of Yield-Related Traits in the Chinese Peanut Mini-Core Collection Through Genome-Wide Association Studies
Authors: Zhou Xiaojing , Guo Jianbin , Pandey Manish K. , Varshney Rajeev K. , Huang Li , Luo Huaiyong , Liu Nian , Chen Weigang , Lei Yong , Liao Boshou , Jiang Huifang
Published: May 2021

Peanut is an important legume crop worldwide. To uncover the genetic basis of yield features and assist breeding in the future, we conducted genome-wide association studies (GWAS) for six yield-related traits of the Chinese peanut mini-core collection. The seed (pod) size and weight of the population were investigated under four different environments, and these traits showed highly positive correlations in pairwise combinations. We sequenced the Chinese peanut mini-core collection using genotyping-by-sequencing approach and identified 105,814 high-quality single-nucleotide polymorphisms (SNPs). The population structure analysis showed essentially subspecies patterns in groups and obvious geographical distribution patterns in subgroups. A total of 79 significantly associated loci (P < 4.73 × 10–7) were detected for the six yield-related traits through GWAS. Of these, 31 associations were consistently detected in multiple environments, and 15 loci were commonly detected to be associated with multiple traits. Two major loci located on chromosomal pseudomolecules A06 and A02 showed pleiotropic effects on yield-related traits, explaining ∼20% phenotypic variations across environments. The two genomic regions were found 46 putative candidate genes based on gene annotation and expression profile. The diagnostic marker for the yield-related traits from non-synonymous SNP (Aradu-A06-107901527) was successfully validated, achieving a high correlation between nucleotide polymorphism and phenotypic variation. This study provided insights into the genetic basis of yield-related traits in peanut and verified one diagnostic marker to facilitate marker-assisted selection for developing high-yield peanut varieties.
PSDX: A Comprehensive Multi-Omics Association Database of Populus trichocarpa With a Focus on the Secondary Growth in Response to Stresses
Authors: Wang Huiyuan , Liu Sheng , Dai Xiufang , Yang Yongkang , Luo Yunjun , Gao Yubang , Liu Xuqing , Wei Wentao , Wang Huihui , Xu Xi , Reddy Anireddy S. N. , Jaiswal Pankaj , Li Wei , Liu Bo , Gu Lianfeng
Published: May 2021

Populus trichocarpa (P. trichocarpa) is a model tree for the investigation of wood formation. In recent years, researchers have generated a large number of high-throughput sequencing data in P. trichocarpa. However, no comprehensive database that provides multi-omics associations for the investigation of secondary growth in response to diverse stresses has been reported. Therefore, we developed a public repository that presents comprehensive measurements of gene expression and post-transcriptional regulation by integrating 144 RNA-Seq, 33 ChIP-seq, and six single-molecule real-time (SMRT) isoform sequencing (Iso-seq) libraries prepared from tissues subjected to different stresses. All the samples from different studies were analyzed to obtain gene expression, co-expression network, and differentially expressed genes (DEG) using unified parameters, which allowed comparison of results from different studies and treatments. In addition to gene expression, we also identified and deposited pre-processed data about alternative splicing (AS), alternative polyadenylation (APA) and alternative transcription initiation (ATI). The post-transcriptional regulation, differential expression, and co-expression network datasets were integrated into a new P. trichocarpa Stem Differentiating Xylem (PSDX) database (http://forestry.fafu.edu.cn/db/SDX), which further highlights gene families of RNA-binding proteins and stress-related genes. The PSDX also provides tools for data query, visualization, a genome browser, and the BLAST option for sequence-based query. Much of the data is also available for bulk download. The availability of PSDX contributes to the research related to the secondary growth in response to stresses in P. trichocarpa, which will provide new insights that can be useful for the improvement of stress tolerance in woody plants.
Plant Biostimulants: New Insights Into the Biological Control of Verticillium Wilt of Olive
Authors: López-Moral Ana , Agustí-Brisach Carlos , Trapero Antonio
Published: May 2021

Verticillium wilt of olive (Olea europaea subsp. europaea L.) (VWO), caused by the hemibiotrophic soil-borne fungus Verticillium dahliae Kleb., is considered the major limiting factor of this crop in Mediterranean-type climate regions of the world. The absence of effective chemical treatments makes the control of the disease difficult. In this way, the use of biostimulants and host plant defense inducers seems to be one of the most promising biological and eco-friendly alternatives to traditional control measures. Thus, the main goal of this study was to evaluate the effect of 32 products, including amino acids, micronutrients, microorganisms, substances of natural origin, copper complex-based products, and organic and inorganic salts against the disease under controlled conditions. To this end, their effects on mycelial growth and microsclerotia (MS) inhibition of V. dahliae were evaluated by means of dual cultures or by sensitivity tests in vitro as well as on disease progression in planta. Wide ranging responses to the pathogen and disease reduction levels were observed among all the products tested, suggesting multiple modes of action. Copper-based products were among the most effective for mycelial growth and MS inhibition, whereas they did not show an important effect on the reduction of disease severity in planta. Phoma sp. and Aureobasidium pullulans were the most effective in disease reduction in planta with foliar application. On the other hand, two phosphite salts, one with copper and the other with potassium, were the most effective in disease reduction in planta when they were applied by irrigation, followed by A. pullulans and Bacillus amyloliquefaciens. This study will be useful to select the best candidates for future studies, contributing significantly to new insights into the current challenge of the biological control of VWO.
Stress-Related Growth in Adolescents Returning to School After COVID-19 School Closure
Authors: Waters Lea , Allen Kelly-Ann , Arslan Gökmen
Published: May 2021

The move to remote learning during COVID-19 has impacted billions of students. While research shows that school closure, and the pandemic more generally, has led to student distress, the possibility that these disruptions can also prompt growth in is a worthwhile question to investigate. The current study examined stress-related growth (SRG) in a sample of students returning to campus after a period of COVID-19 remote learning (n= 404, age = 13–18). The degree to which well-being skills were taught at school (i.e., positive education) before the COVID-19 outbreak and student levels of SRG upon returning to campus was testedviastructural equation modeling. Positive reappraisal, emotional processing, and strengths use in students were examined as mediators. The model provided a good fit [χ2= 5.37,df= 3,p= 0.146, RMSEA = 0.044 (90% CI = 0.00–0.10), SRMR = 0.012, CFI = 99, TLI = 0.99] with 56% of the variance in SRG explained. Positive education explained 15% of the variance in cognitive reappraisal, 7% in emotional processing, and 16% in student strengths use during remote learning. The results are discussed using a positive education paradigm with implications for teaching well-being skills at school to foster growth through adversity and assist in times of crisis.
“Transparency” of Textbook Activities as Perceived by Chinese Middle School English Teachers With Different Professional Experience
Authors: Xu Hao
Published: May 2021

Transparency of textbook activities, i.e., the degree of easiness for teachers to process and comprehend them, needs to be researched in terms of both materials design and materials use. This article reports on a study that investigates the impact of teachers’ professional experience and transparency of textbook activities (due to materials design) on teachers’ actual perception of the transparency of materials. The study adopted a mixed-methods design and collected quantitative data via a five-point scale survey from 115 secondary school teachers as well as interview data from 15 informants. Data analysis reveals that both teachers’ professional experience and transparency of textbook activities affect the degree of easiness teachers perceived as they understand and interpret the activities for pedagogical purposes. However, discrepancy exists between transparency in materials design and transparency in teachers’ perception. Lack of pedagogical knowledge about the relationship between teaching objectives, steps, and assessment and strong existing cognitive schemata developed from the stereotype of processing a familar set of teaching materials might hamper teachers’ perception of transparency.
The Psychometric Properties of the Resilience Scale (RS-14) in Lithuanian Adolescents
Authors: Zelviene Paulina , Jovarauskaite Lina , Truskauskaite-Kuneviciene Inga
Published: May 2021

In the current study, we provided the evidence of satisfactory validity of the RS-14 scale in the Lithuanian adolescents’ sample (N = 1299; Mage = 14.24; SDage = 1.26), based on its internal structure, and relations to other variables. The results of the study indicated an acceptable model fit for a single-factor structure of the scale with a high internal consistency (McDonald’s omega = 0.89). We also confirmed the scalar measurement invariance across groups of adolescents in terms of their age (i.e., early and middle adolescence) and mental health profile as well as partial scalar gender invariance. Adolescents characterized by high levels of socio-emotional problems reported lower levels of resilience, in comparison to adolescents that reported low levels of socio-emotional problems. However, the data indicated that adolescents from emotional problems and behavioral problems groups cannot be differentiated with the RS-14 scale.
Development and Validity of the Nurse Presenteeism Questionnaire
Authors: Shan Geyan , Wang Shengnan , Feng Kai , Wang Wei , Guo Shujie , Li Yongxin
Published: May 2021

This study aimed to develop and test the reliability and validity of a multi-item nurses’ presenteeism behaviour questionnaire. Study 1 administered the Nurse Presenteeism Questionnaire (NPQ) to 250 Chinese nurses. Study 2, surveyed 650 nurses with the NPQ, the Sickness Presenteeism Questionnaire, the Stanford Presenteeism Scale, the General Health Questionnaire, and the Emotional Exhaustion Scale using convenience sampling. After item analysis, the subjects were randomly divided into two groups to verify the questionnaire structure. Study 1 revealed the nurses’ core symptoms when they go to work with illness, and the NPQ with 11 items was developed. Study 2’s item analysis revealed that 11 NPQ items had good discrimination (t = 22.67∼36.11, p < 0.01) and high homogeneity. Besides, the scale had good reliability (Cronbach’s = 0.93) and external criterion validity (r = 0.24∼0.84, p < 0.01). Thus, the NPQ can be used to measure presenteeism behaviour in nursing.
Prefrontal Functional Connectivity During the Verbal Fluency Task in Patients With Major Depressive Disorder: A Functional Near-Infrared Spectroscopy Study
Authors: Dong Suh-Yeon , Choi JongKwan , Park Yeonsoo , Baik Seung Yeon , Jung Minjee , Kim Yourim , Lee Seung-Hwan
Published: May 2021

Deviations in activation patterns and functional connectivity have been observed in patients with major depressive disorder (MDD) with prefrontal hemodynamics of patients compared with healthy individuals. The graph-theoretical approach provides useful network metrics for evaluating functional connectivity. The evaluation of functional connectivity during a cognitive task can be used to explain the neurocognitive mechanism underlying the cognitive impairments caused by depression. Overall, 31 patients with MDD and 43 healthy individuals completed a verbal fluency task (VFT) while wearing a head-mounted functional near-infrared spectroscopy (fNIRS) devices. Hemodynamics and functional connectivity across eight prefrontal subregions in the two groups were analyzed and compared. We observed a reduction in prefrontal activation and weaker overall and interhemispheric subregion-wise correlations in the patient group compared with corresponding values in the control group. Moreover, efficiency, the network measure related to the effectiveness of information transfer, showed a significant between-group difference [t (71.64) = 3.66, corrected p < 0.001] along with a strong negative correlation with depression severity (rho = −0.30, p = 0.009). The patterns of prefrontal functional connectivity differed significantly between the patient and control groups during the VFT. Network measures can quantitatively characterize the reduction in functional connectivity caused by depression. The efficiency of the functional network may play an important role in the understanding of depressive symptoms.
Changes in Psychopathology and Mental Health Resilience
Authors: Onchev Georgi
Published: May 2021

Accelerated culture transition and contemporary post-truth mass cognitive distortions contribute to cognitive insecurity and substitution of facts with opinions. In this paper the impact of these changes on normal psyche and on psychopathological manifestations and mental health care is described. The consequences include drop of mental resilience, pathomorphosis of some clinical pictures, blurring of diagnostic boundaries, mimicry of psychopathology, and overdiagnosis. Their repercussions on mental health care and professional integrity are discussed, and particularly the need for shift of mental health care focus from protection to resilience is disputed.
Resilience Predicts Self-Stigma and Stigma Resistance in Stabilized Patients With Bipolar I Disorder
Authors: Post Fabienne , Buchta Melanie , Kemmler Georg , Pardeller Silvia , Frajo-Apor Beatrice , Hofer Alex
Published: May 2021

The identification of factors that prevent self-stigma and on the other hand promote stigma resistance are of importance in the long-term management of bipolar disorder. Accordingly, the aim of the current study was to investigate the association of factors deemed relevant in this context, i.e., resilience, premorbid functioning, and residual mood symptoms, with self-stigma/stigma resistance. Sixty patients diagnosed with bipolar I disorder were recruited from a specialized outpatient clinic. Self-stigma and stigma resistance were measured by the Internalized Stigma of Mental Illness (ISMI) Scale. The presence and severity of symptoms were assessed by the Montgomery-Asberg Depression Rating Scale (MADRS) and the Young Mania Rating Scale (YMRS). Resilience and premorbid functioning were measured by the Resilience Scale (RS-25) and the Premorbid Adjustment Scale (PAS), respectively. Resilience correlated negatively with self-stigma and positively with stigma resistance and was a predictor for self-stigma/stigma resistance in multiple linear regression analysis. Residual depressive symptoms correlated positively with self-stigma and negatively with stigma resistance. There were no significant correlations between sociodemographic variables, premorbid functioning as well as residual manic symptoms and self-stigma/stigma resistance. The findings of this study implicate that resilience may be considered as an important component of self-stigma reduction interventions.
One-Year Update on Salivary Diagnostic of COVID-19
Authors: Caixeta Douglas Carvalho , Oliveira Stephanie Wutke , Cardoso-Sousa Leia , Cunha Thulio Marquez , Goulart Luiz Ricardo , Martins Mario Machado , Marin Lina Maria , Jardim Ana Carolina Gomes , Siqueira Walter Luiz , Sabino-Silva Robinson
Published: May 2021

Background: Coronavirus disease 2019 (COVID-19) is a global health problem, which is challenging healthcare worldwide. In this critical review, we discussed the advantages and limitations in the implementation of salivary diagnostic platforms of COVID-19. The diagnostic test of COVID-19 by invasive nasopharyngeal collection is uncomfortable for patients and requires specialized training of healthcare professionals in order to obtain an appropriate collection of samples. Additionally, these professionals are in close contact with infected patients or suspected cases of COVID-19, leading to an increased contamination risk for frontline healthcare workers. Although there is a colossal demand for novel diagnostic platforms with non-invasive and self-collection samples of COVID-19, the implementation of the salivary platforms has not been implemented for extensive scale testing. Up to date, several cross-section and clinical trial studies published in the last 12 months support the potential of detecting SARS-CoV-2 RNA in saliva as a biomarker for COVID-19, providing a self-collection, non-invasive, safe, and comfortable procedure. Therefore, the salivary diagnosis is suitable to protect healthcare professionals and other frontline workers and may encourage patients to get tested due to its advantages over the current invasive methods. The detection of SARS-CoV-2 in saliva was substantial also in patients with a negative nasopharyngeal swab, indicating the presence of false negative results. Furthermore, we expect that salivary diagnostic devices for COVID-19 will continue to be used with austerity without excluding traditional gold standard specimens to detect SARS-CoV-2.
Rapid Evidence Assessment of Mental Health Outcomes of Pandemics for Health Care Workers: Implications for the Covid-19 Pandemic
Authors: Waring Sara , Giles Susan
Published: May 2021

Background: Little is known about the long-term mental health (MH) impact of the Covid-19 pandemic on health care workers (HCWs). However, synthesizing knowledge from past pandemics can help to anticipate this, along with identifying interventions required, when, and target populations most in need. This paper provides a balanced evaluation of what is currently known about short- and long-term MH impacts of pandemics on HCWs and effect of methodological limitations on knowledge claims.

Method: A rapid evidence assessment (REA) was conducted on 41 studies published in the past two decades that examined MH outcomes for HCWs in relation to pandemics.

Results: Findings of literary synthesis highlight common MH outcomes across pandemics, including increased stress, distress, burnout, and anxiety in the short-term, and post-traumatic stress and depression in the long-term. Findings also show the key role that organizations and public health bodies play in promoting adaptive coping and reducing health worries and the emotional and psychological distress caused by this. Evidence highlights particular groups at risk of developing MH issues (contact with patients that are infected, having children), and time points where risk may increase (initial response phase, when quarantined). However, inconsistencies in measures, analysis, and reporting all create limitations for pooling data.

Conclusions: Findings can be used by researchers to provide a knowledge framework to inform future research that will assist HCWs in responding to pandemics, and by policy makers and service planners to provide an evidence-led brief about direction and evidence base for related policy initiatives, interventions or service programmes.
The Impact of COVID-19 Interventions on Influenza and Mycobacterium Tuberculosis Infection
Authors: Geng Yiman , Li Gang , Zhang Leiliang
Published: May 2021

A series of public health interventions have been implemented to prevent the transmission of SARS-CoV-2 in China. However, the effect of non-pharmaceutical interventions to COVID-19 on the incidence of the influenza virus and Mycobacterium tuberculosis infections is not clear. In current study, we analyzed surveillance data on influenza and Mycobacterium tuberculosis from Henan Provincial People’s Hospital in Zhengzhou, Henan province, China from 2019 to 2020. The monthly positive test rate for influenza and Mycobacterium tuberculosis to estimate transmissibility changes was calculated. The positive detection rate of influenza A declined significantly during the implementation of inventions in 2020, from a total positive rate of 17.69% in 2019 to 5.77% in 2020. Similarly, a 2.15% reduction in positive detective rate was seen for influenza B, from a total positive rate of 5.15% in 2019 to 3% in 2020. The positive rate curve of Mycobacterium tuberculosis measured by x-pert in 2020 remained above the curve in 2019 from March to June, and August, showing the rising trend under these precautions. Our study suggests that non-pharmaceutical public health interventions likely reduced influenza transmission significantly and have less effect on Mycobacterium tuberculosis transmission in 2020.
Neuronal Sequence Models for Bayesian Online Inference
Authors: Frölich Sascha , Marković Dimitrije , Kiebel Stefan J.
Published: May 2021

Various imaging and electrophysiological studies in a number of different species and brain regions have revealed that neuronal dynamics associated with diverse behavioral patterns and cognitive tasks take on a sequence-like structure, even when encoding stationary concepts. These neuronal sequences are characterized by robust and reproducible spatiotemporal activation patterns. This suggests that the role of neuronal sequences may be much more fundamental for brain function than is commonly believed. Furthermore, the idea that the brain is not simply a passive observer but an active predictor of its sensory input, is supported by an enormous amount of evidence in fields as diverse as human ethology and physiology, besides neuroscience. Hence, a central aspect of this review is to illustrate how neuronal sequences can be understood as critical for probabilistic predictive information processing, and what dynamical principles can be used as generators of neuronal sequences. Moreover, since different lines of evidence from neuroscience and computational modeling suggest that the brain is organized in a functional hierarchy of time scales, we will also review how models based on sequence-generating principles can be embedded in such a hierarchy, to form a generative model for recognition and prediction of sensory input. We shortly introduce the Bayesian brain hypothesis as a prominent mathematical description of how online, i.e., fast, recognition, and predictions may be computed by the brain. Finally, we briefly discuss some recent advances in machine learning, where spatiotemporally structured methods (akin to neuronal sequences) and hierarchical networks have independently been developed for a wide range of tasks. We conclude that the investigation of specific dynamical and structural principles of sequential brain activity not only helps us understand how the brain processes information and generates predictions, but also informs us about neuroscientific principles potentially useful for designing more efficient artificial neuronal networks for machine learning tasks.
An Explainable Multimodal Neural Network Architecture for Predicting Epilepsy Comorbidities Based on Administrative Claims Data
Authors: Linden Thomas , De Jong Johann , Lu Chao , Kiri Victor , Haeffs Kathrin , Fröhlich Holger
Published: May 2021

Epilepsy is a complex brain disorder characterized by repetitive seizure events. Epilepsy patients often suffer from various and severe physical and psychological comorbidities (e.g., anxiety, migraine, and stroke). While general comorbidity prevalences and incidences can be estimated from epidemiological data, such an approach does not take into account that actual patient-specific risks can depend on various individual factors, including medication. This motivates to develop a machine learning approach for predicting risks of future comorbidities for individual epilepsy patients. In this work, we use inpatient and outpatient administrative health claims data of around 19,500 U.S. epilepsy patients. We suggest a dedicated multimodal neural network architecture (Deep personalized LOngitudinal convolutional RIsk model—DeepLORI) to predict the time-dependent risk of six common comorbidities of epilepsy patients. We demonstrate superior performance of DeepLORI in a comparison with several existing methods. Moreover, we show that DeepLORI-based predictions can be interpreted on the level of individual patients. Using a game theoretic approach, we identify relevant features in DeepLORI models and demonstrate that model predictions are explainable in light of existing knowledge about the disease. Finally, we validate the model on independent data from around 97,000 patients, showing good generalization and stable prediction performance over time.
Systematic Review and Meta-Analysis of Virtual Reality in Mental Healthcare: Effects of Full Body Illusions on Body Image Disturbance
Authors: Turbyne Collin , Goedhart Abe , de Koning Pelle , Schirmbeck Frederike , Denys Damiaan
Published: May 2021

Background: Body image (BI) disturbances have been identified in both clinical and non-clinical populations. Virtual reality (VR) has recently been used as a tool for modulating BI disturbances through the use of eliciting a full body illusion (FBI). This meta-analysis is the first to collate evidence on the effectiveness of an FBI to reduce BI disturbances in both clinical and non-clinical populations.

Methods: We performed a literature search in MEDLINE (PubMed), EMBASE, PsychINFO, and Web of Science with the keywords and synonyms for “virtual reality” and “body image” to identify published studies until September 2020. We included studies that (1) created an FBI with a modified body shape or size and (2) reported BI disturbance outcomes both before and directly after the FBI. FBI was defined as a head-mounted display (HMD)-based simulation of embodying a virtual body from an egocentric perspective in an immersive 3D computer-generated environment.

Results: Of the 398 identified unique studies, 13 were included after reading full-texts. Four of these studies were eligible for a meta-analysis on BI distortion inducing a small virtual body FBI in healthy females. Significant post-intervention results were found for estimations of shoulder width, hip width, and abdomen width, with the largest reductions in size being the estimation of shoulder circumference (SMD = −1.3; 95% CI: −2.2 to −0.4; p = 0.004) and hip circumference (SMD = −1.0; 95% CI: −1.6 to −0.4; p = 0.004). Mixed results were found in non-aggregated studies from large virtual body FBIs in terms of both estimated body size and BI dissatisfaction and in small virtual body FBI in terms of BI dissatisfaction.

Conclusions: The findings presented in this paper suggest that the participants' BIs were able to conform to both an increased as well as a reduced virtual body size. However, because of the paucity of research in this field, the extent of the clinical utility of FBIs still remains unclear. In light of these limitations, we provide implications for future research about the clinical utility of FBIs for modulating BI-related outcomes.
The Disparate Approaches of General Practitioners to the Pharmaceuticalisation of Cardiovascular Disease Prevention
Authors: Douglass Tom , Calnan Michael
Published: May 2021

In the context of current clinical practice guidance, this paper will analyse the role of GPs in decision-making about the primary prevention of cardiovascular disease (CVD) using the concept of pharmaceuticalisation. Drawing on thematic analysis of semi-structured interviews with 20 GPs, the paper argues that the way GPs approach CVD pharmaceuticalisation is shaped by their understandings of and use of guidelines (and the knowledge they embody), existing treatment perspectives and the moral qualities of preventative treatment, and professional evaluations of ‘relevant’ information. The analysis indicates that there exist disparate and distinct approaches to and understandings of CVD pharmaceuticalisation amongst GPs. Depending on how knowledge, treatment perspectives and values variously combine, GPs sit somewhere on a spectrum of how pharmaceuticalised they are in terms of the approaches to and understandings of the prevention of CVD.
Prevalence of Antimicrobial Resistance and Characteristics of Escherichia coli Isolates From Fecal and Manure Pit Samples on Dairy Farms in the Province of Québec, Canada
Authors: Massé Jonathan , Lardé Hélène , Fairbrother John M. , Roy Jean-Philippe , Francoz David , Dufour Simon , Archambault Marie
Published: May 2021

Antimicrobial resistance (AMR) is an important burden for public health and veterinary medicine. For Québec (Canada) dairy farms, the prevalence of AMR is mostly described using passive surveillance, which may be misleading. In addition, the presence of extended spectrum β-lactamase (ESBL)/AmpC producing Escherichia coli is unknown. This observational cross-sectional study used random dairy farms (n = 101) to investigate AMR and extended spectrum β-lactamase (ESBL)/AmpC producing Escherichia coli. Twenty antimicrobials were tested on E. coli isolates (n = 593) recovered from fecal samples (n = 599) from calves, cows, and the manure pit. Isolates were mostly susceptible (3% AMR or less) to the highest priority critically important antimicrobials in humans. The highest levels of AMR were to tetracycline (26%), sulfisozaxole (23%) and streptomycin (19%). The resistance genes responsible for these resistances were, respectively: tet(A), tet(B), sul1, sul2, sul3, aph(3”)-Ib (strA), aph(6)-Id (strB), aadA1, aadA2, and aadA5. ESBL analysis revealed two predominant phenotypes: AmpC (51%) and ESBL (46%) where blaCMY−2 and blaCTX−M(blaCTX−M−1, blaCTX−M−15, and blaCTX−M−55) were the genes responsible for these phenotypes, respectively. During this study, 85% of farms had at least one ESBL/AmpC producing E. coli. Isolates from calves were more frequently resistant than those from cows or manure pits. Although prevalence of AMR was low for critically important antimicrobials, there was a high prevalence of ESBL/AmpC-producing E. coli on Quebec dairy farms, particularly in calves. Those data will help determine a baseline for AMR to evaluate impact of initiatives aimed at reducing AMR.
Stadiony świata, żądło i o błysk szprychy. Profesjonalizmy sportowe na materiale rejestrowanym przez Wielki słownik języka polskiego PAN.
Authors: Niepytalska-Osiecka Anna
Published: May 2021

This paper discusses the issue of the language elements coming from sport
professiolects which have been recorded by the Polish Academy of Sciences
Great Dictionary of Polish (WSJP PAN) and labelled as sport. pot. (sport coll.). The
author ponders on the reasons why the sport elements which were restricted to
professional communication until a point in time are now entering the resource
of a larger group of Polish language users and general dictionaries of Polish.
Keywords: language of sport – lexicography – professiolect – sociolect
– professionalism
Sensing, Actuation, and Control of the SmartX Prototype Morphing Wing in the Wind Tunnel
Authors: Nazeer Nakash , Wang Xuerui , Groves Roger M.
Published: May 2021

This paper presents a study on trailing edge deflection estimation for the SmartX camber morphing wing demonstrator. This demonstrator integrates the technologies of smart sensing, smart actuation and smart controls using a six module distributed morphing concept. The morphing sequence is brought about by two actuators present at both ends of each of the morphing modules. The deflection estimation is carried out by interrogating optical fibers that are bonded on to the wing’s inner surface. A novel application is demonstrated using this method that utilizes the least amount of sensors for load monitoring purposes. The fiber optic sensor data is used to measure the deflections of the modules in the wind tunnel using a multi-modal fiber optic sensing approach and is compared to the deflections estimated by the actuators. Each module is probed by single-mode optical fibers that contain just four grating sensors and consider both bending and torsional deformations. The fiber optic method in this work combines the principles of hybrid interferometry and FBG spectral sensing. The analysis involves an initial calibration procedure outside the wind tunnel followed by experimental testing in the wind tunnel. This method is shown to experimentally achieve an accuracy of 2.8 mm deflection with an error of 9%. The error sources, including actuator dynamics, random errors, and nonlinear mechanical backlash, are identified and discussed.
Evaluation of CH4 Emission in Two Paddy Field Areas, Khonkaen and Ayutthaya, in Thailand
Authors: Sukdanont Pongsathorn , Arunrat Noppol , Amkha Suphachai , Hatano Ryusuke
Published: May 2021

It is well known that submerged soils emit high levels of methane (CH4) due to oxygen deprivation and free iron oxide causing a quick reduction. However, there are other soil properties that control the reduction processes in soil, especially the amount of soil organic carbon (SOC). This study aimed to investigate the major factors controlling CH4 production potential (CH4PP) in Thai paddy fields. Two provinces, Ayutthaya, a clay soil region, and Khonkaen, a sandy soil region, were selected to represent a wide range of soil textures. Soil characteristic analysis pre- and post-incubation, and weekly gas detection in an incubation experiment over two months, was conducted. Stepwise multiple regression analysis was employed to analyze major soil factors controlling CH4PP. For the regional prediction of CH4PP, a map dataset of Ayutthaya and Khonkaen by the Land Development Department, Thailand, and a soil texture map (with intersected point data using the soil property map in ArcGIS) by OpenLandMap, were used. CH4PP was correlated with 1:10 pH, Fe2+, and water-soluble organic carbon (WSOC) measured after incubation. Although CH4PP showed no significant correlation with any soil properties measured before incubation, CH4PP was correlated with SOC, 1:10 electrical conductivity (EC), exchangeable ammonium (ExNH4), and sand content. It was thought that SOC and ExNH4 were related to organic matter decomposition, 1:10 EC was related to SO42− reduction and sand content was related to free oxides. Predicted regional CH4PP was similar in Ayutthaya and Khonkaen, although SOC, ExNH4 and 1:10 EC was higher, and sand content was lower in Ayutthaya than in Khonkaen. In both regions, the distribution of CH4PP corresponded to SOC, and CH4PP was lower with lower sand content and higher 1:10 EC. In clayey Ayutthaya, higher CH4PP was observed in the area with higher ExNH4. This indicates that soil properties other than soil texture and SOC influence CH4PP in the paddy fields in Thailand.
Assessment of Macro-, Micro-, Trace, and Ultratrace Element Concentration in Green-Legged Partridge Hens’ Eggs from a Free-Range System
Authors: Trziszka Tadeusz , Dobrzański Zbigniew , Chojnacka Katarzyna , Bubel Anna , Beń Halina , Korczyński Mariusz , Konkol Damian , Tronina Wojciech
Published: May 2021

The goal of this research was to determine the concentration of macro-, micro-, trace, and ultratrace elements in egg albumen and yolk of Green-Legged Partridge (GLP) hens (Polish native breed) maintained in a free-range system. The hens received two feed mixtures (FM), which differed in mineral content (Gr-1 and Gr-2). Analyses of 57 chemical elements were performed using inductively coupled plasma spectroscopy by ICP-OES and ICP-MS techniques. FM from Gr-2 were characterized by a significantly (p < 0.05 or 0.01) higher concentration of macro- and microelements (Al, Ba, Ca, K, P, S, Si) than that from Gr-1. Among the trace and ultratrace elements there were significantly higher levels of Co, Cr, Li, Nb, Ni, Pb, Ru, Sn, and Zr, and significantly lower levels of Cs, Pd, and Te in Gr-2 compared with Gr-1. Egg albumen from hens from the Gr-2 group contained a significantly higher Ba concentration. In the case of trace and ultratrace elements, significantly greater Au, Co, Cr, Mo, Nb, Ru, and Se, and less As were recorded in the albumen from Gr-2. No significant differences were observed in the concentrations of macro- and microelements in the egg yolk. Among the examined trace and ultratrace elements, substantial differences were observed in the level of Co, Cr, Ni, Se, Sn, and Y (more in Gr-2), and Au, Hf, Hg, Nb, Nd, and Rb (less in Gr-2). Only in the case of Co and Cr concentrations in the feed (Gr-2) was a significant increase found in the albumen and yolk. Gr-2 also showed a significantly greater concentration of Ba, Nb, and Ru in the albumen, and Ni and Sn in the yolk.
Automatic and Reliable Leaf Disease Detection Using Deep Learning Techniques
Authors: Chowdhury Muhammad E. H. , Rahman Tawsifur , Khandakar Amith , Ayari Mohamed Arselene , Khan Aftab Ullah , Khan Muhammad Salman , Al-Emadi Nasser , Reaz Mamun Bin Ibne , Islam Mohammad Tariqul , Ali Sawal Hamid Md
Published: May 2021

Plants are a major source of food for the world population. Plant diseases contribute to production loss, which can be tackled with continuous monitoring. Manual plant disease monitoring is both laborious and error-prone. Early detection of plant diseases using computer vision and artificial intelligence (AI) can help to reduce the adverse effects of diseases and also overcome the shortcomings of continuous human monitoring. In this work, we propose the use of a deep learning architecture based on a recent convolutional neural network called EfficientNet on 18,161 plain and segmented tomato leaf images to classify tomato diseases. The performance of two segmentation models i.e., U-net and Modified U-net, for the segmentation of leaves is reported. The comparative performance of the models for binary classification (healthy and unhealthy leaves), six-class classification (healthy and various groups of diseased leaves), and ten-class classification (healthy and various types of unhealthy leaves) are also reported. The modified U-net segmentation model showed accuracy, IoU, and Dice score of 98.66%, 98.5%, and 98.73%, respectively, for the segmentation of leaf images. EfficientNet-B7 showed superior performance for the binary classification and six-class classification using segmented images with an accuracy of 99.95% and 99.12%, respectively. Finally, EfficientNet-B4 achieved an accuracy of 99.89% for ten-class classification using segmented images. It can be concluded that all the architectures performed better in classifying the diseases when trained with deeper networks on segmented images. The performance of each of the experimental studies reported in this work outperforms the existing literature.
Effects of Manure and Chemical Fertilizer on Bacterial Community Structure and Soil Enzyme Activities in North China
Authors: Liu Zhiping , Xie Wenyan , Yang Zhenxing , Huang Xuefang , Zhou Huaiping
Published: May 2021

The application of organic fertilizer affects soil microbes and enzyme activities. In this study, we explored the effects of various long-term different fertilization treatments (manure, M; chemical fertilizer, NP; manure + chemical fertilizer, MNP; and no fertilizer, CK) on bacterial community structure and soil sucrase, urease, and alkaline phosphatase activities in Shaping, Hequ, China. High-throughput sequencing was used to amplify the third to the fourth hypervariable region of the 16S ribosomal RNA for analysis of the bacterial community structure. Enzyme activities were determined by colorimetry. Soil treated with MNP had the highest bacterial Abundance-based Coverage Estimator index and enzyme activities. The principal coordinates analysis results showed significant differences among the various fertilization treatments (p < 0.001). Proteobacteria, Actinobacteria, Acidobacteria, Gemmatimonadetes, and Chloroflexi were consistently dominant in all soil samples. The redundancy analysis and Monte Carlo permutation tests showed that the soil bacterial communities were significantly correlated with alkali-hydrolyzable nitrogen, organic matter, urease, and alkaline phosphatase. Our results reveal the fundamentally different effects that organic and inorganic fertilizers have on soil bacterial communities and their functions.
Multi-Sensor Approach for Tropical Soil Fertility Analysis: Comparison of Individual and Combined Performance of VNIR, XRF, and LIBS Spectroscopies
Authors: Tavares Tiago Rodrigues , Molin José Paulo , Nunes Lidiane Cristina , Wei Marcelo Chan Fu , Krug Francisco José , de Carvalho Hudson Wallace Pereira , Mouazen Abdul Mounem
Published: May 2021

Rapid, cost-effective, and environmentally friendly analysis of key soil fertility attributes requires an ideal combination of sensors. The individual and combined performance of visible and near infrared (VNIR) diffuse reflectance spectroscopy, X-ray fluorescence spectroscopy (XRF), and laser-induced breakdown spectroscopy (LIBS) was assessed for predicting clay, organic matter (OM), cation exchange capacity (CEC), pH, base saturation (V), and extractable (ex-) nutrients in tropical soils. A set of 102 samples, collected from two agricultural fields, with broad ranges of fertility attributes were selected. Two contrasting data fusion approaches have been applied for modeling: (i) merging spectral data of different sensors followed by partial least squares regression (PLS), known as fusion before prediction; and (ii) applying the Granger and Ramanathan (GR) averaging approach, known as fusion after prediction. Results showed VNIR as individual technique to be the best for the prediction of clay and OM content (2.61 ≤ residual prediction deviation (RPD) ≤ 3.37), while the chemical attributes CEC, V, ex-P, ex-K, ex-Ca, and ex-Mg were better predicted (1.82 ≤ RPD ≤ 4.82) by elemental analysis techniques (i.e., XRF and LIBS). Only pH cannot be predicted regardless the technique. The attributes OM, V, and ex-P were best predicted using single-sensor approaches, while the attributes clay, CEC, pH, ex-K, ex-Ca, and ex-Mg were overall best predicted using multi-sensor approaches. Regarding the performance of the multi-sensor approaches, ex-K, ex-Ca, and ex-Mg, were best predicted (RPD of 4.98, 5.30, and 4.11 for ex-K, ex-Ca and ex-Mg, respectively) using two-sensor fusion approach (VNIR + XRF for ex-K and XRF + LIBS for ex-Ca and ex-Mg), while clay, CEC and pH were best predicted (RPD of 4.02, 2.63, and 1.32 for clay, CEC, and pH, respectively) with the three-sensor fusion approach (VNIR + XRF + LIBS). Therefore, the best combination of sensors for predicting key fertility attributes proved to be attribute-specific, which is a drawback of the data fusion approach. The present work is pioneering in highlighting benefits and limitations of the in tandem application of VNIR, XRF, and LIBS spectroscopies for fertility analysis in tropical soils.
Three Manual Noncommercial Methods to Prepare Equine Platelet-Rich Plasma
Authors: Segabinazzi Lorenzo G. T. M. , Podico Giorgia , Rosser Michael F. , Nanjappa Som G. , Alvarenga Marco A. , Canisso Igor F.
Published: May 2021

In light of PRP’s increasing popularity in veterinary practice, this study aimed to compare three manual methods to prepare and cool equine PRP. The blood of 18 clinically healthy mares was collected via venipuncture in a blood transfusion bag (method 1), blood tubes (method 2), and a syringe (method 3). In method 1, samples were double centrifuged; method 2 involved one centrifugation, and in method 3 the syringe was kept in an upright position to sediment for 4 h. After processing with three methods, PRP and platelet-poor plasma (PPP) were extracted and assessed for red (RBC) and white blood cell counts (WBC), platelet counts, and viability. In a subset of mares (n = 6), samples were processed with the three methods, and PRP was evaluated at 6 and 24 h postcooling at 5 °C. Method 1 resulted in the highest and method 3 in the lowest platelet concentration (p < 0.05), and the latter also had greater contamination with WBC than the others (p < 0.001). Platelet viability was similar across treatments (p > 0.05). Cooling for 24 h did not affect platelet counts in all methods (p > 0.05); however, platelet viability was reduced after cooling PRP produced by method 3 (p = 0.04), and agglutination increased over time in all methods (p < 0.001). The three methods increased (1.8–5.6-fold) platelet concentration in PRP compared to whole blood without compromising platelet viability. In conclusion, all three methods concentrated platelets and while cooling affected their viability. It remains unknown whether the different methods and cooling would affect PRP’s clinical efficacy.