bluuebunny/crossref_metadata_2025 huggingface dataset:
Positive Youth Development Attributes and Parenting as Protective Factors Against Adolescent Social Networking Addiction in Hong Kong
Authors: Yu Lu , Shek Daniel Tan Lei
Published: March 2021

This study examined the predictive effects of 15 positive youth development (PYD) attributes and parenting behavior on adolescent social networking addiction (SNA) in a representative sample of Hong Kong students. In total, 1,896 Hong Kong Secondary 1 students from 20 randomly selected schools (age = 13.19 ± 0.52 years) completed the Bergen Social Media Addiction Scale (BSMAS), the Chinese Positive Youth Development Scale, and the Chinese Parenting Behavior Scale. Of the participants, 11.4% could be classified as being addicted to Social Networking Sites (SNSs). Regression analyses showed that students' emotional competence (β = −0.09; p < 0.01), behavioral competence (β = −0.12; p < 0.001), beliefs in the future (β = −0.10; p < 0.01), and spirituality (β = −0.08; p < 0.01) were negatively associated with SNA, while social competence (β = 0.07; p < 0.05) and positive identity (β = 0.13; p < 0.001) were positively related to SNA. Paternal and maternal responsiveness showed indirect effects on students' SNA through the full mediation of PYD attributes. Specific PYD attributes and positive parenting behavior may serve as important protective factors against the development of SNA among Hong Kong adolescents.
Fenretinide Improves Intestinal Barrier Function and Mitigates Alcohol Liver Disease
Authors: Tang Xiao-Han , Melis Marta , Mai Karen , Gudas Lorraine J. , Trasino Steven E.
Published: March 2021

Alcohol liver disease (ALD) is a major cause of liver-related mortality globally, yet there remains an unmet demand for approved ALD drugs. The pathogenesis of ALD involves perturbations to the intestinal barrier and subsequent translocation of bacterial endotoxin that, acting through toll-like receptor 4 (TLR4), promotes hepatic inflammation and progression of ALD. In the present study we investigated the ability of fenretinide (Fen) [N-(4-hydroxyphenyl) retinamide], a synthetic retinoid with known anti-cancer and anti-inflammatory properties, to modulate intestinal permeability and clinical hallmarks of ALD in a mouse model of chronic ethanol (EtOH) exposure. Our results show that EtOH-treated mice had reductions in mRNA and protein expression of intestinal tight junction proteins, including claudin one and occludin, and increases in intestinal permeability and endotoxemia compared to pair-fed mice. Also, EtOH-treated mice had marked increases in hepatic steatosis, liver injury, and expression of pro-inflammatory mediators, including TNF-α, and TLR4-positive macrophages, Kupffer cells, and hepatocytes in the intestines and liver, respectively. In contrast, EtOH + Fen-treated mice were resistant to the effects of EtOH on promoting intestinal permeability and had higher intestinal protein levels of claudin one and occludin. Also, EtOH + Fen-treated mice had significantly lower plasma levels of endotoxin, and reductions in expression of TNF-α and TLR4 positive macrophages, Kupffer cells, and hepatocytes in the intestine and liver. Lastly, we found that EtOH + Fen-treated mice exhibited major reductions in hepatic triglycerides, steatosis, and liver injury compared to EtOH-treated mice. Our findings are the first to demonstrate that Fen possesses anti-ALD properties, potentially through modulation of the intestinal barrier function, endotoxemia, and TLR4-mediated inflammation. These data warrant further pre-clinical investigations of Fen as a potential anti-ALD drug.
Sequence2Script: A Web-Based Tool for Translation of Pharmacogenetic Data Into Evidence-Based Prescribing Recommendations
Authors: Bousman Chad A. , Wu Patrick , Aitchison Katherine J. , Cheng Tony
Published: March 2021

Pharmacogenomic (PGx) testing has emerged as an effective strategy for informing drug selection and dosing. This has led to an increase in the use of PGx testing in the clinic and has catalyzed the emergence of a burgeoning commercial PGx testing industry. However, not all PGx tests are equivalent in their approach to translating testing results into prescribing recommendations, due to an absence of regulatory standards. As such, those generating and using PGx data require tools for ensuring the prescribing recommendations they are provided align with current peer-reviewed PGx-based prescribing guidelines developed by expert groups or approved product labels. Herein, we present Sequence2Script (sequence2script.com), a simple, free, and transparent web-based tool to assist in the efficient translation of PGx testing results into evidence-based prescribing recommendations. The tool was designed with a wide-range of user groups (e.g., healthcare providers, laboratory staff, researchers) in mind. The tool supports 97 gene-drug pairs with evidence-based prescribing guidelines, allows users to adjust recommendations for concomitant inhibitors and inducers, and generates a clinical report summarizing the patient’s genotype, inferred phenotype, phenoconverted phenotype (if applicable), and corresponding prescribing recommendations. In this paper, we describe each of the tool’s features, provide use case examples, and discuss limitations of and future development plans for the tool. Although we recognize that Sequecnce2Script may not meet the needs of every user, the hope is that this novel tool will facilitate more standardized use of PGx testing results and reduce barriers to implementing these results into practice.
Equitable Domination in Vague Graphs With Application in Medical Sciences
Authors: Rao Yongsheng , Kosari Saeed , Shao Zehui , Qiang Xiaoli , Akhoundi Maryam , Zhang Xiao
Published: March 2021

Considering all physical, biological, and social systems, fuzzy graph (FG) models serve the elemental processes of all natural and artificial structures. As the indeterminate information is an essential real-life problem, which is mostly uncertain, modeling the problems based on FGs is highly demanding for an expert. Vague graphs (VGs) can manage the uncertainty relevant to the inconsistent and indeterminate information of all real-world problems, in which FGs possibly will not succeed in bringing about satisfactory results. In addition, VGs are a very useful tool to examine many issues such as networking, social systems, geometry, biology, clustering, medical science, and traffic plan. The previous definition restrictions in FGs have made us present new definitions in VGs. A wide range of applications has been attributed to the domination in graph theory for several fields such as facility location problems, school bus routing, modeling biological networks, and coding theory. Concepts from domination also exist in problems involving finding the set of representatives, in monitoring communication and electrical networks, and in land surveying (e.g., minimizing the number of places a surveyor must stand in order to take the height measurement for an entire region). Hence, in this article, we introduce different concepts of dominating, equitable dominating, total equitable dominating, weak (strong) equitable dominating, equitable independent, and perfect dominating sets in VGs and also investigate their properties by some examples. Finally, we present an application in medical sciences to show the importance of domination in VGs.
Clinical Interpretation of Cardiopulmonary Exercise Testing: Current Pitfalls and Limitations
Authors: Neder J. Alberto , Phillips Devin B. , Marillier Mathieu , Bernard Anne-Catherine , Berton Danilo C. , O’Donnell Denis E.
Published: March 2021

Several shortcomings on cardiopulmonary exercise testing (CPET) interpretation have shed a negative light on the test as a clinically useful tool. For instance, the reader should recognize patterns of dysfunction based on clusters of variables rather than relying on rigid interpretative algorithms. Correct display of key graphical data is of foremost relevance: prolixity and redundancy should be avoided. Submaximal dyspnea ratings should be plotted as a function of work rate (WR) and ventilatory demand. Increased work of breathing and/or obesity may normalize peak oxygen uptake (V̇O2) despite a low peak WR. Among the determinants of V̇O2, only heart rate is measured during non-invasive CPET. It follows that in the absence of findings suggestive of severe impairment in O2delivery, the boundaries between inactivity and early cardiovascular disease are blurred in individual subjects. A preserved breathing reserve should not be viewed as evidence that “the lungs” are not limiting the subject. In this context, measurements of dynamic inspiratory capacity are key to uncover abnormalities germane to exertional dyspnea. A low end-tidal partial pressure for carbon dioxide may indicate either increased “wasted” ventilation or alveolar hyperventilation; thus, direct measurements of arterial (or arterialized) PO2might be warranted. Differentiating a chaotic breathing pattern from the normal breath-by-breath noise might be complex if the plotted data are not adequately smoothed. A sober recognition of these limitations, associated with an interpretation report free from technicalities and convoluted terminology, is crucial to enhance the credibility of CPET in the eyes of the practicing physician.
COVID-19 and Smoking: What Evidence Needs Our Attention?
Authors: Xie Jianghua , Zhong Rui , Wang Wei , Chen Ouying , Zou Yanhui
Published: March 2021

The current COVID-19 pandemic has caused severe morbidity and mortality worldwide. Although relevant studies show that the smoking rate of COVID-19 patients is relatively low, the current smoking status of people with COVID-19 cannot be accurately measured for reasons. Thus, it is difficult to assess the relationship between smoking and COVID-19. Smoking can increase the risk of severe COVID-19 symptoms and aggravate the condition of patients with COVID-19. Nicotine upregulates the expression of ACE2, which can also increase susceptibility to COVID-19, aggravatiing the disease. Although nicotine has certain anti-inflammatory effects, there is no evidence that it is related to COVID-19 treatment; therefore, smoking cannot be considered a preventative measure. Furthermore, smokers gathering and sharing tobacco may promote the spread of viruses. Despite the COVID-19 epidemic, the findings suggested that COVID-19 has not encouraged smokers to quit. Additionally, there is evidence that isolation at home has contributed to increased smoking behavior and increased quantities. Therefore, it is recommended that governments increase smoking cessation messaging as part of public health measures to contain the COVID-19 pandemic. This review analyzes the existing research on smoking’s impact on COVID-19 so that governments and medical institutions can develop evidence-based smoking-related prevention and control measures for COVID-19.
Significance of Atrial and Brain Natriuretic Peptide Measurements in Fetuses With Heart Failure
Authors: Miyoshi Takekazu , Hosoda Hiroshi , Minamino Naoto
Published: March 2021

Fetal heart failure is mainly caused by congenital heart defect and arrhythmia. It is difficult to appropriately diagnose the severity of fetal heart failure simply by ultrasonography because the development of a fetal heart in fetoplacental circulation and how well the fetal myocardium can adapt to postnatal cardiopulmonary circulation are challenging to assess. In adult cardiology, natriuretic peptides (NPs) are the most useful biomarker of heart failure; however, studies investigating NP levels in the fetuses and amniotic fluid are quite limited. Furthermore, little is known about their production and metabolism. This review summarized the most relevant findings on NP levels in the umbilical cord blood and amniotic fluid. The findings can then extend their use as a diagnostic biomarker of heart failure in fetuses with congenital heart defect and/or arrhythmia.
Sex-Specific Differences in the Physiological and Biochemical Performance of Arbuscular Mycorrhizal Fungi-Inoculated Mulberry Clones Under Salinity Stress
Authors: Wang Yan-Hong , Zhang Nai-Li , Wang Min-Qiang , He Xiao-Bin , Lv Zhi-Qiang , Wei Jia , Su Xiu , Wu Ai-Ping , Li Yan
Published: March 2021

Arbuscular mycorrhizal fungi (AMF) are often considered bioameliorators. AMF can promote plant growth under various stressful conditions; however, differences between male and female clones in mycorrhizal strategies that protect plants from the detrimental effects of salinity are not well studied. In this study, we aimed to examine the interactive effects of salinity and AMF on the growth, photosynthetic traits, nutrient uptake, and biochemical responses of Morus alba males and females. In a factorial setup, male and female M. alba clones were subjected to three salinity regimes (0, 50, and 200 mM NaCl) and planted in soil with or without Funneliformis mosseae inoculation. The results showed that NaCl alone conferred negative effects on the growth, salinity tolerance, photosynthetic performance, and shoot and root ionic ratios (K+/Na+, Ca2+/Na+, and Mg2+/Na+) in both sexes; in contrast, mycorrhizal inoculation mitigated the detrimental effects of salinity. Furthermore, the mycorrhizal effects were closely correlated with Mn2+, proline, and N concentrations. Females benefited more from AMF inoculation as shown by the enhancements in their biomass accumulation, and N, proline, K+, Mg2+, Fe2+, Zn2+, and Mn2+ concentrations than males with mycorrhizal inoculation under saline conditions. In comparison, male plants inoculated with AMF showed improvements in biomass allocated to the roots, P, and peroxidase concentrations under saline conditions. These sex-specific differences suggest that male and female mulberry clones adopted different mycorrhizal strategies when growing under saline conditions. Overall, our results provide insight into the sex-specific difference in the performance of AMF-associated mulberry clones, suggesting that female mulberry could be more suitable for vegetation remediation than the male one, due to its higher salinity tolerance.
Plant Protein O-Arabinosylation
Authors: Petersen Bent Larsen , MacAlister Cora A. , Ulvskov Peter
Published: March 2021

A wide range of proteins with diverse functions in development, defense, and stress responses areO-arabinosylated at hydroxyprolines (Hyps) within distinct amino acid motifs of continuous stretches of Hyps, as found in the structural cell wall extensins, or at non-continuous Hyps as, for example, found in small peptide hormones and a variety of plasma membrane proteins involved in signaling. PlantO-glycosylation relies on hydroxylation of Prolines to Hyps in the protein backbone, mediated by prolyl-4-hydroxylase (P4H) which is followed byO-glycosylation of the Hyp C4-OH group by either galactosyltransferases (GalTs) or arabinofuranosyltranferases (ArafTs) yielding either Hyp-galactosylation or Hyp-arabinosylation. A subset of the P4H enzymes with putative preference to hydroxylation of continuous prolines and presumably all ArafT enzymes needed for synthesis of the substituted arabinose chains of one to four arabinose units, have been identified and functionally characterized. Truncated root-hair phenotype is one common denominator of mutants of Hyp formation and Hyp-arabinosylation glycogenes, which act on diverse groups ofO-glycosylated proteins, e.g., the small peptide hormones and cell wall extensins. Dissection of different substrate derived effects may not be regularly feasible and thus complicate translation from genotype to phenotype. Recently, lack of proper arabinosylation on arabinosylated proteins has been shown to influence their transport/fate in the secretory pathway, hinting to an additional layer of functionality ofO-arabinosylation. Here, we provide an update on the prevalence and types ofO-arabinosylated proteins and the enzymatic machinery responsible for their modifications.
Multiplexed CRISPR/Cas9-Mediated Knockout of Laccase Genes in Salvia miltiorrhiza Revealed Their Roles in Growth, Development, and Metabolism
Authors: Zhou Zheng , Li Qing , Xiao Liang , Wang Yun , Feng Jingxian , Bu Qitao , Xiao Ying , Hao Kai , Guo Meili , Chen Wansheng , Zhang Lei
Published: March 2021

Laccases are multicopper-containing glycoproteins related to monolignol oxidation and polymerization. These properties indicate that laccases may be involved in the formation of important medicinal phenolic acid compounds in Salvia miltiorrhiza such as salvianolic acid B (SAB), which is used for cardiovascular disease treatment. To date, 29 laccases have been found in S. miltiorrhiza (SmLACs), and some of which (SmLAC7 and SmLAC20) have been reported to influence the synthesis of phenolic acids. Because of the functional redundancy of laccase genes, their roles in S. miltiorrhiza are poorly understood. In this study, the CRISPR/Cas9 system was used for targeting conserved domains to knockout multiple genes of laccase family in S. miltiorrhiza. The expressions of target laccase genes as well as the phenolic acid biosynthesis key genes decrease dramatically in editing lines. Additionally, the growth and development of hairy roots was significantly retarded in the gene-edited lines. The cross-sections examination of laccase mutant hairy roots showed that the root development was abnormal and the xylem cells in the edited lines became larger and looser than those in the wild type. Additionally, the accumulation of RA as well as SAB was decreased, and the lignin content was nearly undetectable. It suggested that SmLACs play key roles in development and lignin formation in the root of S. miltiorrhiza and they are necessary for phenolic acids biosynthesis.
The Psychological Pathway to Suicide Attempts: A Strategy of Control Without Awareness
Authors: Macintyre Vanessa G. , Mansell Warren , Pratt Daniel , Tai Sara J.
Published: March 2021

Objectives

This paper aims to identify potential areas for refinement in existing theoretical models of suicide, and introduce a new integrative theoretical framework for understanding suicide, that could inform such refinements.

Methods

Literature on existing theoretical models of suicide and how they contribute to understanding psychological processes involved in suicide was evaluated in a narrative review. This involved identifying psychological processes associated with suicide. Current understanding of these processes is discussed, and suggestions for integration of the existing literature are offered.

Results

Existing approaches to understanding suicide have advanced the current knowledge of suicide in various ways. They have guided valuable research in the following areas: motivations for suicide and the psychological distress which influences suicide attempts; ambivalence about suicide; suicidal individuals’ focus of attention; and ways in which individuals who contemplate suicide differ from individuals who attempt suicide. We outline a new theoretical framework as a means to integrating all of these concepts into the three principles of control, conflict, and awareness. Within this framework, suicide is regarded as occurring due to a long standing conflict between an individual’s personal goals, culminating in an episode of acute loss of control. The new framework posits that the individual then strives to regain control through the means of suicide because of a narrowed awareness of consequences of their actions on other valued goals. This psychological mechanism of limited awareness is posited to be the common pathway by which individuals make a suicide attempt, regardless of which risk factors are present.

Conclusion

This article introduces a theoretical framework that generates several hypotheses for future research, and focuses on psychological processes occurring during immediate crisis. One of the key hypotheses resulting from our predictions on how individuals progress from contemplating to attempting suicide will be tested in an ongoing program of research: Individuals who attempt suicide have a significantly reduced awareness of consequences of suicide, which would negatively impact on their important life goals, values, principles, or ideals, compared to individuals who contemplate suicide. Therapy guided by the new framework may be more flexible, immediate, and client-focused than other therapies for suicidal individuals.
Mobile Technology Use and Its Association With Executive Functioning in Healthy Young Adults: A Systematic Review
Authors: Warsaw Rachel E. , Jones Andrew , Rose Abigail K. , Newton-Fenner Alice , Alshukri Sophie , Gage Suzanne H.
Published: March 2021

Introduction: Screen-based and mobile technology has grown at an unprecedented rate. However, little is understood about whether increased screen-use affects executive functioning (EF), the range of mental processes that aid goal attainment and facilitate the selection of appropriate behaviors. To examine this, a systematic review was conducted.

Method: This systematic review is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. A comprehensive literature search was conducted using Web of Science, MEDLINE, PsycINFO and Scopus databases to identify articles published between 2007 and March 2020, examining the use of mobile technologies on aspects of EF in healthy adults aged 18–35 years. In total 6079 articles were screened by title, and 39 screened by full text. Eight eligible papers were identified for inclusion. Our methods were pre-registered on the PROSPERO international prospective register of systematic reviews.

Results: A total of 438 participants were included across the eight studies. Five of the eight studies examined more than one EF. Five studies measured inhibition, and four studies measured decision-making. Smartphone use was negatively associated with inhibition and decision-making. Working memory performance was found to be improved by increased time engaging in video games and by refraining from smartphone use prior to bedtime. Quality assessments indicated high risk of methodological biases across the studies and a low quality of evidence for determining the relationship between technology use and executive functioning.

Conclusions: This review highlights the scarcity of the literature in this area. It presents a call for rigorous and objective research to further our understanding of the impact of mobile technology on different aspects of executive function.
A Systematic Review of Factors Affecting Mental Health and Well-Being of Asylum Seekers and Refugees in Germany
Authors: Hajak Vivien L. , Sardana Srishti , Verdeli Helen , Grimm Simone
Published: March 2021

Background: Since the onset of the 2015 European refugee crisis, ~4. 46 million people have sought asylum in the European Union, with Germany logging the largest share of all asylum applications. In addition to the severe adversities before and during flight, the process of settling into a new environment involves stressors that affect psychological well-being and mental health. The aim of this systematic review was to examine contextual factors during post-migration that influence the mental health and well-being of asylum seekers and refugees (ASRs) in Germany.

Methods: Following PRISMA guidelines, a systematic review was conducted across multiple databases for English and German studies published between 2015 and 2020 with index keywords.

Results: From a total of 303 articles, 156 duplicates were removed and, after title review, another 87 were excluded for not meeting the inclusion criteria. After assessing the abstracts of the remaining 60 articles, 39 were excluded. Full texts of 21 articles were assessed for eligibility and after excluding 8 articles, 13 articles were included in the review. The results demonstrate high rates of psychological distress among ASRs in Germany and the significant influence of contextual factors on their mental health and psychological well-being. The risk factors for poor mental health include an uncertain asylum status, living in shared asylum accommodations, separation from the nuclear family, lack of German language skills, integration issues and discrimination, while employment is a protective factor.

Conclusion: Asylum seekers and refugees have high prevalence rates of psychological distress directly influenced by contextual factors in Germany. Based on these findings, policy makers are strongly recommended to apply preventive strategies to reduce mental health problems of ASRs in Germany.
Association Between Aspirin Use and Decreased Risk of Pneumonia in Patients With Cardio-Cerebra-Vascular Ischemic Disease: A Population-Based Cohort Study
Authors: Chen Ying-Cheng , Chen Yin-Yang , Yeh Han Wei , Yeh Tung-Ying , Huang Jing-Yang , Liao Pei-Lun , Yeh Liang-Tsai , Yang Shun-Fa , Chou Ming-Chih , Yeh Chao-Bin
Published: March 2021

This study evaluated the association between long-term low-dose aspirin use and decreased risk of pneumonia in patients with cardio-cerebra-vascular ischemic diseases (CCVDs). This retrospective cohort study used records from Taiwan's National Health Insurance Research Database of claims made between 1997 and 2013. After propensity score matching (PSM), patients who took a low dose of aspirin for more than 90 days within 1 year of diagnosis with CCVDs were identified as the exposure group (n = 15,784). A matched total of 15,784 individuals without aspirin use were selected for the non-aspirin group. The main outcome was the development of pneumonia after the index date. Multivariable Cox regression analysis and Kaplan–Meier survival analysis were performed to estimate the adjusted hazard ratio (aHR) and cumulative probability of pneumonia. The result after PSM indicated a lower hazard ratio for pneumonia in aspirin users (aHR = 0.890, 95% confidence interval = 0.837–0.945). Therefore, patients with CCVDs who took aspirin had a lower risk of developing pneumonia than those who did not. In conclusion, this population-based cohort study demonstrated that long-term low-dose aspirin use is associated with a slightly decreased risk of pneumonia in patients with CCVDs.
An Attempt to Boost Posterior Population Expansion Using Fast Machine Learning Algorithms
Authors: Juda Przemysław , Renard Philippe
Published: March 2021

In hydrogeology, inverse techniques have become indispensable to characterize subsurface parameters and their uncertainty. When modeling heterogeneous, geologically realistic discrete model spaces, such as categorical fields, Monte Carlo methods are needed to properly sample the solution space. Inversion algorithms use a forward operator, such as a numerical groundwater solver. The forward operator often represents the bottleneck for the high computational cost of the Monte Carlo sampling schemes. Even if efficient sampling methods (for example Posterior Population Expansion, PoPEx) have been developed, they need significant computing resources. It is therefore desirable to speed up such methods. As only a few models generated by the sampler have a significant likelihood, we propose to predict the significance of generated models by means of machine learning. Only models labeled as significant are passed to the forward solver, otherwise, they are rejected. This work compares the performance of AdaBoost, Random Forest, and convolutional neural network as classifiers integrated with the PoPEx framework. During initial iterations of the algorithm, the forward solver is always executed and subsurface models along with the likelihoods are stored. Then, the machine learning schemes are trained on the available data. We demonstrate the technique using a simulation of a tracer test in a fluvial aquifer. The geology is modeled by the multiple-point statistical approach, the field contains four geological facies, with associated permeability, porosity, and specific storage values. MODFLOW is used for groundwater flow and transport simulation. The solution of the inverse problem is used to estimate the 10 days protection zone around the pumping well. The estimated speed-ups with Random Forest and AdaBoost were higher than with the convolutional neural network. To validate the approach, computing times of inversion without and with machine learning schemes were computed and the error against the reference solution was calculated. For the same mean error, accelerated PoPEx achieved a speed-up rate of up to 2 with respect to the standard PoPEx.
Robotic Telemedicine for Mental Health: A Multimodal Approach to Improve Human-Robot Engagement
Authors: Lima Maria R. , Wairagkar Maitreyee , Natarajan Nirupama , Vaitheswaran Sridhar , Vaidyanathan Ravi
Published: March 2021

COVID-19 has severely impacted mental health in vulnerable demographics, in particular older adults, who face unprecedented isolation. Consequences, while globally severe, are acutely pronounced in low- and middle-income countries (LMICs) confronting pronounced gaps in resources and clinician accessibility. Social robots are well-recognized for their potential to support mental health, yet user compliance (i.e., trust) demands seamless affective human-robot interactions; natural ‘human-like’ conversations are required in simple, inexpensive, deployable platforms. We present the design, development, and pilot testing of a multimodal robotic framework fusing verbal (contextual speech) and nonverbal (facial expressions) social cues, aimed to improve engagement in human-robot interaction and ultimately facilitate mental health telemedicine during and beyond the COVID-19 pandemic. We report the design optimization of a hybrid face robot, which combines digital facial expressions based on mathematical affect space mapping with static 3D facial features. We further introduce a contextual virtual assistant with integrated cloud-based AI coupled to the robot’s facial representation of emotions, such that the robot adapts its emotional response to users’ speech in real-time. Experiments with healthy participants demonstrate emotion recognition exceeding 90% for happy, tired, sad, angry, surprised and stern/disgusted robotic emotions. When separated, stern and disgusted are occasionally transposed (70%+ accuracy overall) but are easily distinguishable from other emotions. A qualitative user experience analysis indicates overall enthusiastic and engaging reception to human-robot multimodal interaction with the new framework. The robot has been modified to enable clinical telemedicine for cognitive engagement with older adults and people with dementia (PwD) in LMICs. The mechanically simple and low-cost social robot has been deployed in pilot tests to support older individuals and PwD at the Schizophrenia Research Foundation (SCARF) in Chennai, India. A procedure for deployment addressing challenges in cultural acceptance, end-user acclimatization and resource allocation is further introduced. Results indicate strong promise to stimulate human-robot psychosocial interaction through the hybrid-face robotic system. Future work is targeting deployment for telemedicine to mitigate the mental health impact of COVID-19 on older adults and PwD in both LMICs and higher income regions.
Changing Between Virtual Reality and Real-World Adversely Affects Memory Recall Accuracy
Authors: Lamers Maarten H. , Lanen Maik
Published: March 2021

Context-dependency effects on memory exist, whereby people’s context influences their ability to accurately recall items from memory. This effect was not previously studied when considering virtual reality as an environmental context. We show that adverse effects on recall of memorized items exist when changing between virtual and real environments. The effect was not present when memorizing and recall were both done in VR; it appears to be caused by the change of environmental context. This previously unknown effect may impact how we use VR for memorization tasks, particularly when accurate recall of memorized information in a real environment is important. In a memory-recall experiment (n= 51) participants that underwent a context change involving VR after memorizing performed significantly worse on 24-h later item recall than those who did not change context (17% lower accuracy,p< 0.001). In particular memorizing in VR as opposed to a real environment lowers accuracy of recall in a real environment (24% lower,p= 0.001).
Influence of the COVID-19 Pandemic on Mood and Training in Australian Community Tennis Players
Authors: Turner Mitchell , Beranek Philipp , Rogers Shane L. , Nosaka Kazunori , Girard Olivier , Cruickshank Travis
Published: March 2021

The COVID-19 outbreak has led to the implementation of strict restrictions in Australia, which have severely impacted sporting activities. Tennis is played by 6.2% of the population within the Oceania region, and is a valuable sport for maintaining social, mental, and physical health. Current literature indicates the COVID-19 pandemic has negatively affected the mental health of Australian residents. The aim of this study was to investigate changes in training and match play due to the outbreak, and its effects on emotional well-being of Australian senior tennis players. Additionally, explore any differences between middle aged (41–60 years) and senior (61 years and over) Australian tennis players. An online survey was used to assess training and match play habits, as well as ascertain the emotional well-being of tennis players. The survey was active from 24th April 2020 until 6th June 2020. Participants were adult (41+ years) tennis players from Australia. Wilcoxon signed rank tests were performed to check for differences in training hours and tennis matches played. Mann–WhitneyUtests were used to assess the difference in Brief Emotional Experience Scale (BEES) scores, employment status as well as the training hours and tennis matches played between the two age groups. A Kendall's Tau B correlation test was performed to assess the associations of training, match play and demographic characteristics with BEES scores. Kruskal–Wallis tests assessed differences in BEES scores between participants of differing match play formats, tennis experience and cessation of tennis training time periods. There were 245 respondents who met our inclusion criteria. Tennis training hours along with the tennis matches played significantly decreased during COVID-19 compared to pre-COVID-19, 85.09 and 88.48%, respectively. No significant (p> 0.05) differences were observed between age groups for any of the training modality hours, nor was there any significant difference in number of tennis matches played. The participants average BEES score was 0.99 ± 1.27, indicating that respondents had a positive emotional well-being during the COVID-19 pandemic. The emotional well-being of the senior group was significantly (P= 0.002) higher than the middle aged group. Together, our results show that training and tennis match play decreased during the COVID-19 pandemic, however the emotional well-being of senior tennis players in Australia appeared to not be negatively affected.
The Influence of Training Load on Hematological Athlete Biological Passport Variables in Elite Cyclists
Authors: Astolfi Tiffany , Crettaz von Roten Fabienne , Kayser Bengt , Saugy Martial , Faiss Raphael
Published: March 2021

The hematological module of the Athlete Biological Passport (ABP) is used in elite sport for antidoping purposes. Its aim is to better target athletes for testing and to indirectly detect blood doping. The ABP allows to monitor hematological variations in athletes using selected primary blood biomarkers [hemoglobin concentration (Hb) and reticulocyte percentage (Ret%)] with an adaptive Bayesian model to set individual upper and lower limits. If values fall outside the individual limits, an athlete may be further targeted and ultimately sanctioned. Since (Hb) varies with plasma volume (PV) fluctuations, possibly caused by training load changes, we investigated the putative influence of acute and chronic training load changes on the ABP variables. Monthly blood samples were collected over one year in 10 male elite cyclists (25.6 ± 3.4 years, 181 ± 4 cm, 71.3 ± 4.9 kg, 6.7 ± 0.8 W.kg−1 5-min maximal power output) to calculate individual ABP profiles and monitor hematological variables. Total hemoglobin mass (Hbmass) and PV were additionally measured by carbon monoxide rebreathing. Acute and chronic training loads–respectively 5 and 42 days before sampling–were calculated considering duration and intensity (training stress score, TSSTM). (Hb) averaged 14.2 ± 0.0 (mean ± SD) g.dL−1 (range: 13.3–15.5 g·dl−1) over the study with significant changes over time (P = 0.004). Hbmass was 1030 ± 87 g (range: 842–1116 g) with no significant variations over time (P = 0.118), whereas PV was 4309 ± 350 mL (range: 3,688–4,751 mL) with a time-effect observed over the study time (P = 0.014). Higher acute–but not chronic—training loads were associated with significantly decreased (Hb) (P <0.001). Although individual hematological variations were observed, all ABP variables remained within the individually calculated limits. Our results support that acute training load variations significantly affect (Hb), likely due to short-term PV fluctuations, underlining the importance of considering training load when interpreting individual ABP variations for anti-doping purposes.
An Automatic Participant Detection Framework for Event Tracking on Twitter
Authors: Mamo Nicholas , Azzopardi Joel , Layfield Colin
Published: March 2021

Topic Detection and Tracking (TDT) on Twitter emulates human identifying developments in events from a stream of tweets, but while event participants are important for humans to understand what happens during events, machines have no knowledge of them. Our evaluation on football matches and basketball games shows that identifying event participants from tweets is a difficult problem exacerbated by Twitter’s noise and bias. As a result, traditional Named Entity Recognition (NER) approaches struggle to identify participants from the pre-event Twitter stream. To overcome these challenges, we describe Automatic Participant Detection (APD) to detect an event’s participants before the event starts and improve the machine understanding of events. We propose a six-step framework to identify participants and present our implementation, which combines information from Twitter’s pre-event stream and Wikipedia. In spite of the difficulties associated with Twitter and NER in the challenging context of events, our approach manages to restrict noise and consistently detects the majority of the participants. By empowering machines with some of the knowledge that humans have about events, APD lays the foundation not just for improved TDT systems, but also for a future where machines can model and mine events for themselves.
The Effect of Antecedence on Empirical Model Forecasts of Crop Yield from Observations of Canopy Properties
Authors: Florence Anna , Revill Andrew , Hoad Stephen , Rees Robert , Williams Mathew
Published: March 2021

Identification of yield deficits early in the growing season for cereal crops (e.g., Triticum aestivum) could help to identify more precise agronomic strategies for intervention to manage production. We investigated how effective crop canopy properties, including leaf area index (LAI), leaf chlorophyll content, and canopy height, are as predictors of winter wheat yield over various lead times. Models were calibrated and validated on fertiliser trials over two years in fields in the UK. Correlations of LAI and plant height with yield were stronger than for yield and chlorophyll content. Yield prediction models calibrated in one year and tested on another suggested that LAI and height provided the most robust outcomes. Linear models had equal or smaller validation errors than machine learning. The information content of data for yield prediction degraded strongly with time before harvest, and in application to years not included in the calibration. Thus, impact of soil and weather variation between years on crop phenotypes was critical in changing the interactions between crop variables and yield (i.e., slopes and intercepts of regression models) and was a key contributor to predictive error. These results show that canopy property data provide valuable information on crop status for yield assessment, but with important limitations.
Effect of Bacterial Manure on the Properties of Complex Soil and Growth of Ryegrass
Authors: Zhang Ningning , Yan Jiakun , Liu Puling
Published: March 2021

To cope with the growing population, there is a growing demand for more land to be rendered cultivable. A complex soil created by applying soft rocks into sandy soil can be cultivated. However, the strong water-retaining ability and extreme poverty in nutrients of this complex soil has a negative effect on plant growth. To solve this problem, a complex of microbes and bacterial manure (BM) was added to the complex soil. The soil column culture test was used to detect the influence of BM application on soil bulk-density and infiltration parameters, and a pot experiment was conducted to evaluate its effect on the physical and chemical properties of soil, and ryegrass growth. The addition of 0.15% of BM to the complex soil decreased soil bulk-density, and increased the wetting front migration distance and soil hydraulic conductivity. The BM application also increased soil enzyme activities, which increased the available nitrogen and phosphorus content. As a result, BM increased the ryegrass root and shoot biomass. Overall, this study indicates that BM could be used as an eco-friendly sandy soil conditioner for improving the quality of complex soils, thereby, sustaining agricultural production in arid and semi-arid regions.
Black Rot Disease Decreases Young Brassica oleracea Plants’ Biomass but Has No Effect in Adult Plants
Authors: Vega-Álvarez Carmen , Francisco Marta , Soengas Pilar
Published: March 2021

Black rot disease, caused by the bacterium Xanthomonas campestris pv. campestris (Pammel) Dowson (Xcc), causes important yield losses in Brassica oleracea L. crops worldwide. In temperate areas, yield losses are mostly due to the discarding of those plants showing chlorotic and necrotic lesions, since they may be unmarketable. However, the biomass loss caused by the diversion of resources from the primary to the secondary defense metabolism could also affect the final crop yield. In this work, we have focused on studying the impact of Xcc race 1 invasion on the biomass production of young and adult B. oleracea plants. The results have shown that Xcc infection reduces biomass and photosynthesis in the aerial parts of seedlings and modifies their water percentage in a time-dependent manner. When adult plants were inoculated in the field, no effect was detected on the leaves or the biomass of marketable products. This was probably due to a better immune response when compared to seedlings. Since the first developmental stages of B. oleracea crops are especially vulnerable to Xcc, plant disease control should be increased in order to avoid yield losses of marketable products at the adult stage.
Identification of Rhizospheric Microorganisms That Manages Root Knot Nematode and Improve Oil Yield in Sweet Basil (Ocimum basilicum L.)
Authors: Tiwari Sudeep , Pandey Rakesh , Gross Avner
Published: March 2021

Sweet basil (Ocimum basilicum), a highly valuable medicinal crop, is extremely susceptible to Meloidogyne incognita infestation, leading to severe losses in yield and chemo-pharmaceutical quality. Currently, chemical nematicides are the only effective option for the disease management. However, high toxicity to non-target organisms and adverse impact on soil health motivated the look for ecofriendly alternatives. Here, bioinoculants (Bacillus megatarium (“BM”), B. subtilis (“BS”)) were isolated from the rhizosphere of various medicinal and aromatic plants growing in Lucknow region, India. Their biocontrol effects were studied in O. basilicum plants that were invaded by M. incognita either in single or in consortium with Trichoderma harzianum (“TH”) and their efficiency compared to chemical nematicide (carbofuran) and a microbial reference strain (Pseudomonas fluorescens). The results show that all bioinoculants enhanced the growth and oil yield production and increased the nutrient content of O. basilicum by significantly reducing M. incognita infestation by 46 to 72%. Among the strains, a consortium of BM and TH was the most potent treatment. The efficiency of these bioinoculants was not restricted to sterile soil condition but remained high also in natural soil conditions, indicating that enriching soils with rhizospheric microbes can be an effective alternative to chemical nematicides.
Implications of the EFSA Scientific Opinion on Site Directed Nucleases 1 and 2 for Risk Assessment of Genome-Edited Plants in the EU
Authors: Rostoks Nils
Published: March 2021

Genome editing is a set of techniques for introducing targeted changes in genomes. It may be achieved by enzymes collectively called site-directed nucleases (SDN). Site-specificity of SDNs is provided either by the DNA binding domain of the protein molecule itself or by RNA molecule(s) that direct SDN to a specific site in the genome. In contrast to transgenesis resulting in the insertion of exogenous DNA, genome editing only affects specific endogenous sequences. Therefore, multiple jurisdictions around the world have exempted certain types of genome-edited organisms from national biosafety regulations completely, or on a case-by-case basis. In the EU, however, the ruling of the Court of Justice on the scope of mutagenesis exemption case C-528/16 indicated that the genome-edited organisms are subject to the GMO Directive, but the practical implications for stakeholders wishing to develop and authorize genome-edited products in the EU remain unclear. European Food Safety Authority in response to a request by European Commission has produced a scientific opinion on plants developed by SDN-1, SDN-2, and oligonucleotide-directed mutagenesis (ODM) genome editing techniques. In this review, I will (1) provide a conceptual background on GMO risk assessment in the EU; (2) will introduce the main conclusions of the EFSA opinion, and (3) will outline the potential impact on the risk assessment of genome-edited plants.