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2022 ◽  
Vol 40 (3) ◽  
pp. 1-36
Jinyuan Fang ◽  
Shangsong Liang ◽  
Zaiqiao Meng ◽  
Maarten De Rijke

Network-based information has been widely explored and exploited in the information retrieval literature. Attributed networks, consisting of nodes, edges as well as attributes describing properties of nodes, are a basic type of network-based data, and are especially useful for many applications. Examples include user profiling in social networks and item recommendation in user-item purchase networks. Learning useful and expressive representations of entities in attributed networks can provide more effective building blocks to down-stream network-based tasks such as link prediction and attribute inference. Practically, input features of attributed networks are normalized as unit directional vectors. However, most network embedding techniques ignore the spherical nature of inputs and focus on learning representations in a Gaussian or Euclidean space, which, we hypothesize, might lead to less effective representations. To obtain more effective representations of attributed networks, we investigate the problem of mapping an attributed network with unit normalized directional features into a non-Gaussian and non-Euclidean space. Specifically, we propose a hyperspherical variational co-embedding for attributed networks (HCAN), which is based on generalized variational auto-encoders for heterogeneous data with multiple types of entities. HCAN jointly learns latent embeddings for both nodes and attributes in a unified hyperspherical space such that the affinities between nodes and attributes can be captured effectively. We argue that this is a crucial feature in many real-world applications of attributed networks. Previous Gaussian network embedding algorithms break the assumption of uninformative prior, which leads to unstable results and poor performance. In contrast, HCAN embeds nodes and attributes as von Mises-Fisher distributions, and allows one to capture the uncertainty of the inferred representations. Experimental results on eight datasets show that HCAN yields better performance in a number of applications compared with nine state-of-the-art baselines.

2022 ◽  
Vol 43 (2) ◽  
pp. 573-584
Fábio da Costa Málaga ◽  
Helloa Alaide Siqueira ◽  
Lucio Pereira Rauber ◽  
Mariana Groke Marques ◽  

In pig farming, measurements of production parameters play a fundamental role in the success of the activity. Minimal differences in fertility between breeders can lead to less reproductive efficiency and, less productivity. However, assessing the fertility of each male and the early identification of subfertile males is a difficult task to be performed. Thus, the aim of this study was to evaluate the use of in vitro and in vivo parameters in the identification of subfertile males of the Landrace breed, aiming to collaborate with genetic improvement programs, routine optimization in the Genetic Diffusion Units (GDUs) and the results of performance. In experiment 1, an approach to identify males with subfertility was evaluated based on retrospective data. For this, the results (averages of birth rates, number of total births and average percentages of female and male piglets per litter) were evaluated for a total of 996 matings and 847 parturitions. The inseminations came from ejaculates of 32 males, who had at least 19 females inseminated with homospermic doses in the concentration of 2.5 x 109 total sperm from the same male. As for the birth rate (BR), an average of 85.47% ± 6.05 was observed with a group of median males, seven males that stood out and one individual (M32) with a performance of 58.06% ± 9.0. For the total number of piglets born (PB) the average was 13.41 ± 0.56, with three males with better performance and one (M32) with very poor performance (8.62 ± 0.59). In experiment 2, it was verified whether evaluations of inseminating doses (ID) of semen in vitro (motility and sperm morphology) after 96 hours of storage had correlations with fertility in vivo, which can be used to identify subfertile males. The evaluations were performed on 30 ejaculates regarding the means of BR and PB, considering only those who had at least 7 females inseminated. There were no correlations between the motility assessments and semen morphological changes and the reproductive parameters evaluated. The results obtained in vivo, referring to BR and PB, demonstrated that it was possible to identify differences between males, the individual (M32) had the worst results for the percentages of BR and PB. It is concluded that there are males of high and low fertility and that only the in vitro analyzes carried out in this study are not enough to categorize them, however, the evaluation of retrospective data was efficient for this purpose.

Atmosphere ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 143
Hamed Hafizi ◽  
Ali Arda Sorman

Precipitation measurement with high spatial and temporal resolution over highly elevated and complex terrain in the eastern part of Turkey is an essential task to manage the water structures in an optimum manner. The objective of this study is to evaluate the consistency and hydrologic utility of 13 Gridded Precipitation Datasets (GPDs) (CPCv1, MSWEPv2.8, ERA5, CHIRPSv2.0, CHIRPv2.0, IMERGHHFv06, IMERGHHEv06, IMERGHHLv06, TMPA-3B42v7, TMPA-3B42RTv7, PERSIANN-CDR, PERSIANN-CCS, and PERSIANN) over a mountainous test basin (Karasu) at a daily time step. The Kling-Gupta Efficiency (KGE), including its three components (correlation, bias, and variability ratio), and the Nash-Sutcliffe Efficiency (NSE) are used for GPD evaluation. Moreover, the Hanssen-Kuiper (HK) score is considered to evaluate the detectability strength of selected GPDs for different precipitation events. Precipitation frequencies are evaluated considering the Probability Density Function (PDF). Daily precipitation data from 23 meteorological stations are provided as a reference for the period of 2015–2019. The TUW model is used for hydrological simulations regarding observed discharge located at the outlet of the basin. The model is calibrated in two ways, with observed precipitation only and by each GPD individually. Overall, CPCv1 shows the highest performance (median KGE; 0.46) over time and space. MSWEPv2.8 and CHIRPSv2.0 deliver the best performance among multi-source merging datasets, followed by CHIRPv2.0, whereas IMERGHHFv06, PERSIANN-CDR, and TMPA-3B42v7 show poor performance. IMERGHHLv06 is able to present the best performance (median KGE; 0.17) compared to other satellite-based GPDs (PERSIANN-CCS, PERSIANN, IMERGHHEv06, and TMPA-3B42RTv7). ERA5 performs well both in spatial and temporal validation compared to satellite-based GPDs, though it shows low performance in producing a streamflow simulation. Overall, all gridded precipitation datasets show better performance in generating streamflow when the model is calibrated by each GPD separately.

Ghobad Ramezani ◽  
Maryam Aalaa ◽  
Farzaneh Zahedi ◽  
Seyed Kamran Soltani Arabshahi ◽  
Davood Rasouli ◽  

The controversial role of ethics in clinical education and its ability to draw the attention of a large audience is inevitable. The issues and challenges of the COVID-19 pandemic have transformed the clinical education environment. This study was conducted to explore the challenges and ethical requirements of medical sciences education during the COVID-19 pandemic in 2020. The study was qualitative research and the instrument was a semi-structured interview. The participants included faculty members of the basic and clinical Sciences at Iran University of Medical Sciences. After 16 rounds of interviews, theoretical saturation was achieved. Qualitative data were analysed using conventional content analysis, which resulted in 81 preliminary codes and 28 sub-categories. Finally, two themes of "ethical challenges" and "ethical requirements", and 10 categories were achieved. The sub-categories were consisted of "being patient-centred", "social accountability of curriculums", "ethical challenges of the clinical environment", "the poor performance of the clinical faculty members and students", "being justice-centred", "raising awareness", "observing clinical research ethics", "preservation and promotion of mental health", "patient confidentiality", and "respect for individuals". We hope the ethical challenges in medical education that were created due to the emergence of Covid-19 can be reduced and eliminated by defining a framework for ethical requirements. 

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 679
Johannes Rossouw van der van der Merwe ◽  
Fabio Garzia ◽  
Alexander Rügamer ◽  
Santiago Urquijo ◽  
David Contreras Franco ◽  

The performance of GNSS receivers is significantly affected by interference signals. For this reason, several research groups have proposed methods to mitigate the effect of different kinds of jammers. One effective method for wide-band IM is the HDDM PB. It provides good performance to pulsed and frequency sparse interference. However, it and many other methods have poor performance against wide-band noise signals, which are not frequency-sparse. This article proposes to include AGC in the HDDM structure to attenuate the signal instead of removing it: the HDDM-AGC. It overcomes the wide-band noise limitation for IM at the cost of limiting mitigation capability to other signals. Previous studies with this approach were limited to only measuring the CN0 performance of tracking, but this article extends the analysis to include the impact of the HDDM-AGC algorithm on the PVT solution. It allows an end-to-end evaluation and impact assessment of mitigation to a GNSS receiver. This study compares two commercial receivers: one high-end and one low-cost, with and without HDDM IM against laboratory-generated interference signals. The results show that the HDDM-AGC provides a PVT availability and precision comparable to high-end commercial receivers with integrated mitigation for most interference types. For pulse interferences, its performance is superior. Further, it is shown that degradation is minimized against wide-band noise interferences. Regarding low-cost receivers, the PVT availability can be increased up to 40% by applying an external HDDM-AGC.

2022 ◽  
Vol 9 ◽  
Yangang Xue ◽  
Muhammad Mohsin ◽  
Farhad Taghizadeh-Hesary ◽  
Nadeem Iqbal

This study evaluates the role of information in the environmental performance index (EPI) in different energy-consuming sectors in Pakistan through a novel slack-based data envelopment analysis (DEA). The index combines energy consumption as the primary input and gross domestic product (GDP) as the desirable output and CO2 emissions as the undesirable output. Yale’s EPI measures the efficiency of the sectoral level environmental performance of primary energy consumption in the country. Performance analysis was conducted from 2009 to 2018. The sectors were assigned scores between one and zero, with zero indicating maximum decision-making unit (DMU) inefficiency and one indicating maximum DMU efficiency. Despite being in the top-performing sector, agriculture scored only 0.51 in 2018, and the electricity sector obtained 0.412. Results also show that even the best-performing sector operates below the efficiency level. The mining and quarrying sector ranked second by obtaining 0.623 EPI and 0.035 SBEPI. Results also show that much of the energy supply of Pakistan (60.17%) is focused on fossil fuels, supplemented by hydropower (33%), while nuclear, wind, biogas, and solar power account for 5.15%, 0.47%, 0.32%, and 0.03%, respectively. Nonetheless, the overall results for both measures remained reasonably consistent. According to the literature and the energy crisis and climate instability dilemma, the authors conclude that changes to a diverse green power network are a possibility and an imminent need. Similarly, the government should penalize companies with poor performance. Furthermore, to ensure the capacity development and stability of environmental management and associated actions in the country, providing access to knowledge and training to groom human resources and achieve the highest performance is crucial.

2022 ◽  
Vol 23 (1) ◽  
Yanyu Liang ◽  
Milton Pividori ◽  
Ani Manichaikul ◽  
Abraham A. Palmer ◽  
Nancy J. Cox ◽  

Abstract Background Polygenic risk scores (PRS) are valuable to translate the results of genome-wide association studies (GWAS) into clinical practice. To date, most GWAS have been based on individuals of European-ancestry leading to poor performance in populations of non-European ancestry. Results We introduce the polygenic transcriptome risk score (PTRS), which is based on predicted transcript levels (rather than SNPs), and explore the portability of PTRS across populations using UK Biobank data. Conclusions We show that PTRS has a significantly higher portability (Wilcoxon p=0.013) in the African-descent samples where the loss of performance is most acute with better performance than PRS when used in combination.

2022 ◽  
Vol 3 ◽  
Frode Moen ◽  
Marte Vatn ◽  
Maja Olsen ◽  
Jan Arvid Haugan ◽  
Vera Skalicka

The current study aimed to examine sleep characteristics of esport players and the stipulated effects of game performance on consecutive sleep characteristics using residual dynamic structural equation modeling (RDSEM). A sample of 27 Counterstrike players with a mean age of 18½ years participated in the current study. Sleep was detected over a period of 56 days with a Somnofy sleep monitor that utilizes an impulse radio ultra-wideband puls radar and Dopler technology, and weekly game performance was reported by the players. The results showed that esport players' sleep characteristics were in the lower levels of recommended guidelines and that sleep onset started later and sleep offset ended later in the morning compared with athletes from other traditional sports. The esport players displayed stable patterns in sleep onset, sleep offset, time in bed, sleep efficiency and non-REM respiration rates per minute (NREM RPM). On the between-person level, esport players with better game performance spent more time sleeping (r = 0.55) and scored lower on NREM RPM (r = −0.44). Unstandardized within-person cross-lagged paths showed that better game performance predicted subsequent earlier sleep offset. The within-level standardized estimates of the cross-lagged paths revealed that participants with better game performance spent subsequently more time in deep sleep (0.20), less time in light sleep (−0.14), less time in bed (−0.16), and displayed lower NREM RPM (−0.21), earlier sleep offset (−0.21), and onset (−0.09). The findings of better game performance being related to better sleep are discussed in terms of existing knowledge on how stress responses elicitated by poor performance might impact on non-REM respiration rates and sleep.

2022 ◽  
Stephane Raffard ◽  
Sophie Bayard ◽  
Margot Eisenblaetter ◽  
Philippe Tattard ◽  
Jerome Attal ◽  

Abstract Recent evidence suggests that schizophrenia patients are at high risk for severe COVID-19 and should be prioritized for vaccination. However, impaired decision-making capacities could negatively affect the uptake of COVID-19 vaccination in this population. Competence to consent to COVID-19 vaccination was assessed in 80 outpatients with schizophrenia. Using the MacArthur Competence Assessment Tool for Treatment, 56.3% of the sample were classified as having diminished mental capacity. Poor performance was associated with lower vaccination rates, poorer cognition and higher level of psychotic symptoms. Developing interventions for enhancing informed consent for vaccination is urgent within this population.

Paige Colley ◽  
Jamie A. Seabrook ◽  
Sarah J. Woodruff ◽  
Jason Gilliland

Purpose: Knowledge is fundamental to helping children make nutritional choices that support lifelong healthy behaviours. This study (i) investigates elementary school children’s knowledge about food and nutrition and (ii) identifies sociodemographic factors influencing children’s reported knowledge. Methods: In 2017–2019, a survey was administered to 2443 students (grades 5–8) at 60 schools across southwestern Ontario, Canada, and a parent survey was used to validate self-reported sociodemographics. Multiple regression was used to analyse children’s knowledge scores and related sociodemographic factors. A total knowledge score was calculated by summing correct responses derived from 46 individual questions in the student survey. Results: Mean total knowledge score was 29.2 out of a possible 46 points (63.5% correct). Students demonstrated some knowledge and awareness of strategies to encourage fruit and vegetable consumption, healthy food selection, nutrition, and food preparation skills, although knowledge of food guide recommendations and locally sourced produce were limited. Female sex, family income, and rurality were associated with higher knowledge scores. Conclusions: Results provide insight regarding strengths and gaps in elementary-school children’s food and nutrition knowledge. Poor performance of students on specific food guide-related questions suggests that the general guidance of the 2019 Canada’s Food Guide might be better understood by children and adolescents.

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