Miracle-dz/UniFAR-FTUs huggingface dataset:
Good practice for guidance development – review of consensus methods

Introduction. The process of synthesizing scientific evidence and translating elaborate scientific research findings into recommendations for clinical practice is one of the most complex and significant initiatives in health care. In connection with the increasing number of recommendations, previously unformalised elements such as the process of consensus decision-making require developing a methodological approach. The use of consensus methods serves to reduce the impact of psychosocial factors in the formulation of recommendations and to increase the degree of process transparency. The aim of the publication is to present formal methods of achieving consensus used in the process of developing clinical practice guidelines. Materials and methods. The review focuses on results of reports analyzing the procedure and methods of developing clinical recommendations, with particular emphasis on the identification of consensus methods. Results. Many international and national organizations and institutions develop recommendations or adapt guidelines developed by others. They use both informal and formal instruments to deal with divergent expert opinions. The most popular formal methods of achieving consensus identified in the review are the Delphi method, the nominal group technique, the RAND/UCLA method, the consensus conference, and the combinations of individual approaches. Formal methods have been shown to lead to less biased and more reliable recommendations. Regardless of the method used, the guidelines should clearly define the quorum and document the process of agreeing a common standpoint on recommendations, guidelines and recommendations. Conclusions. Clinical guidelines have become an important tool influencing clinical practice. The participation of many experts representing the opinions and interests of different groups makes it necessary to apply a methodological and structured approach so that all participants have the opportunity to voice their opinion and to ensure process transparency, deal with misunderstandings and achieve a consensual position. The consensus methods allow to provide a wide range of stakeholders clinicians, policy makers, patients – with agreed rules of conduct in a given topic. The formal consensus methods and recommendations based on these methods combine scientific evidence with the practice and experience of experts.
SERPINs in Macrophage May Be Key Inflammation Regulator and Relevant to Poor Prognosis in Adamantinomatous Craniopharyngioma

Craniopharyngioma is one of the most prevalent sellar tumors in children. Though normally, gross resection might be reached, while the prognosis and outcome of the patient is much more worse than any other benign tumor. Inflammation in tumor is of essential in tumor growth and progression. We found that inflammation was relevant to patient outcome and macrophages in adamantinomatous craniopharyngioma were activated in an interesting pattern. We then evaluated immune microenvironment in adamantinomatous craniopharyngioma and intended to screen out potential functional molecules for therapeutic targets and predicting prognosis. The results showed that SERPINs family, especially SERPINE1 and SERPING1 were up-regulated in adamantinomatous craniopharyngioma and might be related to patient outcome in malignant tumor. At the same time, the immune environment of adamantinomatous craniopharyngioma was similar with glioma rather than other benign brain tumors. The study firstly proposes the view that ACP might share the same characteristics with malignant brain tumor, and meanwhile preliminarily demonstrates SERPINs, especially SERPINE1 might also play a critical role in ACP, just like other aggressive cancer.
Ethnoarchaeology of Introducing Agriculture and Social Continuity among Sedentarised Hunter–Gatherers: The Transition from the Jomon to the Yayoi Period

This study was conducted to elucidate the introduction of agriculture and social continuity from the Jomon to the Yayoi period, from an ethnoarchaeological perspective. The Yayoi period has been divided into two types: a broad spectrum economy that relied on many kinds of resources, such as rice, millet, and nuts, and a selective economy that specialised in rice and wild boar. However, it is not clear how the livelihoods shifted from the Jomon to the Yayoi period. In this study, ethnohistorical materials were examined first. Ethnohistorical reference materials gathered worldwide have revealed three relationships between hunter–gatherers and farmers: coexistence, fusion, and assimilation. Focusing on fusion, this study examined situations of hunting, gathering, and fishing, as inferred from ruins of the Late and Final Jomon period, and assessed their relationships with agriculture using ethnohistorical reference materials of the Early Edo period. There were not many social changes caused by the introduction of field farming; however, the introduction of paddy rice cultivation had different effects on society depending on the level of investment in obtaining water from streams and springs and creating irrigation features.
Short-term impact of visa waiver for Ukrainian citizens on economic migration to Poland

Ukrainian citizens can work in Poland based on a work permit or a registered employer’s declaration to entrust work to a foreigner. Based on the Regulation (EU) 2017/850 of the European Parliament and of the Council of 17 May 2017, they were exempted from the requirement to have a visa when crossing the external borders of the European Union. This regulation came into force on June 11, 2017 and applies to short-term stays of up to 90 days over a period of 180 days. According to some representatives of employers’ organizations, this resolution is unfavourable to Polish enterprises. It may lead to Ukrainian citizens choosing to look for a job in other European Union countries in which they can get higher compensation for their work than in Poland. The purpose of this article is to determine whether the visa waiver for Ukrainian citizens has influenced their decision of working in Poland within the 6 months of introducing the new regulations, i.e. from June to December 2017. The conducted research using
The Role of Family Involvement in Moderating The Relationship Between Company Characteristics and Dividend Policy in Indonesia

This study seeks out the relationship between the characteristics of companies and dividend policy, as well as the role of family involvement as a moderator of such relationships. This study utilized a purposive sampling method. We conducted the analysis by multiple linear regression and moderated regression analysis. The number of samples in this study is 192 observations in non-financial companies listed on the LQ45 index. The Result shows that profitability, size, and investment opportunities have a positive effect on dividend payout ratio. Meanwhile, financial leverage has a negative relationship with the dividend payout ratio. Family involvement weakens the positive influence of profitability on dividend policy but strengthens the positive effect of investment opportunities. Family involvement does not moderate the effect of size, and financial leverage on dividend policy.
Who Joins a Forum—And Who Does Not?—Evaluating Drivers of Forum Participation in Polycentric Governance Systems

: In polycentric governance systems, decisions that influence a given policy issue are often made across a series of forums: venues where actors meet to resolve collective action problems. Here, we examine who does and does not participate in forums, and the factors driving that participation. We analyze forum participation patterns of 307 actors involved in Swiss water governance, who could participate in water governance forums. We find that the majority of actors do not participate in any forums. Results from a Bayesian multilevel logistic regression model show that especially those concerned with a broader range of policy issues and those that have more organizational resources at their disposal are more likely to participate. To a lesser extent, this also holds for organizations that represent policy beliefs consistent with median beliefs in the system. A belief that increased cross-sectoral coordination is needed to promote more effective governance does not have a discernible impact on participation. These results question the integrative characteristics often attributed to forums in polycentric governance more generally. Abstract: In polycentric governance systems, decisions that influence a given policy issue are often made across a series of forums: venues where actors meet to resolve collective action problems. Here, we examine who does and does not participate in forums, and the factors driving that participation. We analyze forum participation patterns of 307 actors involved in Swiss water governance, who could participate in water governance forums. We find that the majority of actors do not participate in any forums. Results from a Bayesian multilevel logistic regression model show that especially those concerned with a broader range of policy issues and those that have more organizational resources at their disposal are more likely to participate. To a lesser extent, this also holds for organizations that represent policy beliefs consistent with median beliefs in the system. A belief that increased cross-sectoral coordination is needed to promote more effective governance does not have a discernible impact on participation. These results question the integrative characteristics often attributed to forums in polycentric governance more generally.
What Causes PM2.5 Pollution in China?
An Empirical Study from the Perspective of Social
and Economic Factors

Based on the Chinese provincial panel data collected from 2000 to 2014, the spatial correlation characteristics of PM2.5 pollution are measured by using the exploratory spatial data analysis method, and then the spatial Durbin model is used to analyze the social and economic causes of PM2.5 pollution. The results show that: (1) Both global and local spatial correlation characteristics of PM2.5 pollution in China show positive spatial correlation, and the local spatial correlation characteristic mainly includes the two cluster areas: high-high type and low-low type. (2) The high-high cluster areas of PM2.5 pollution are intensively distributed in the northern China plain and the Middle-Lower Yangtze plain while the low-low cluster areas are scattered throughout the Chinese northwest, southwest and northeast regions. (3) The increases of population density, industrialization level, economic development level and the number of motor vehicles will aggravate the degree of PM2.5 pollution, while the improvement of urbanization level and technological progress can alleviate the degree of PM2.5 pollution, but the role of environmental protection in lowering the degree of PM2.5 pollution has not yet been revealed. (4) The increases of energy consumption can exacerbate the degree of PM2.5 pollution in the local area, but its spatial spillover effects for the adjacent areas are not obvious.
Resting-state occipital alpha power is associated with treatment outcome in patients with chronic migraine.

ABSTRACT Preventive treatment is crucial for patients with chronic migraine (CM). This study explored the association between resting-state cortical oscillations and 3-month treatment outcome in patients with CM. Treatment-naïve patients with CM were recruited with their demographic data, psychosocial data, and headache profiles as well as the healthy controls (HCs). Resting-state cortical activities were recorded using an electroencephalogram and analysed using source-based and electrode-based spectral power method. The regions of interest were the bilateral primary somatosensory (S1) and visual (V1) cortices. After 3-month treatment with flunarizine, patients with CM were categorized into responders and nonresponders. Demographic, clinical, and electroencephalogram data from 72 patients with CM and 50 HCs were analysed. Elevated anxiety, depression, and stress were observed in patients with CM. Theta power in bilateral S1 and alpha and gamma powers in the right S1 increased in patients with CM. Nonresponders (n = 34) exhibited larger alpha powers in bilateral V1 than those in responders (n = 38). Alpha powers also exhibited significant correlations with changes of monthly headache days. Notably, in responders and nonresponders, occipital alpha powers did not differ at baseline and in the third month. In conclusion, patients with CM who were not responsive to preventive treatment were associated with augmented resting-state occipital alpha activity. Moreover, changes in migraine attack frequency were associated with baseline occipital alpha power. However, the prognostic feature of visual alpha oscillation seems to be inherent because it is not altered by flunarizine treatment. These findings may be useful for developing personalised migraine treatment plans.
Ground-based high-resolution remote sensing of sulphur hexafluoride (SF6) over Hefei, China: characterization, optical misalignment, influence, and variability.

It is a challenge to retrieve atmospheric sulphur hexafluoride (SF6) with high resolution solar spectra because it has only one single retrieval micro window and has interfered with many factors in the retrieval. Optical misalignment is one of the key factors that affect the accuracy of SF6 retrieval. In this study, we first present a long term time series of the SF6 total column over Hefei, China, between January 2017 and December 2020, retrieved by mid-infrared (MIR) solar spectra recorded by ground-based high-resolution Fourier transform infrared spectroscopy (FTIR). The sensitivities of the total column, root mean square of fitting residual (RMS), total error budgets, degrees of freedom for signal (DOFs), and vertical mixing ratio (VMR) profile with respect to different levels of optical misalignment for SF6 retrieval were assessed. The SF6 total column is sensitive to optical misalignment. In order to avoid inconsistencies in the total column due to optical misalignment, we use the true instrumental line shape (ILS) derived from regular low-pressure HBr cell measurements to retrieve the time series of SF6. The total column of SF6 over Hefei presents strong seasonal dependent features. The maximum monthly average value of (3.57 ± 0.21) × 1014 molecules*cm-2 in summer is (7.60 ± 3.50) × 1013 molecules*cm-2 (21.29 ± 9.80) % higher than the minimum monthly average value of (2.81 ± 0.14) × 1014 molecules*cm-2 in winter. The annual average SF6 total columns in 2017-2020 are (3.02 ± 0.17), (3.50 ± 0.18), (3.25 ± 0.18), and (3.08 ± 0.16) × 1014 molecules*cm-2, respectively, which are close to each other. It indicates that SF6 total column over Hefei is stable in the past four years. Our study can improve the current understanding for ground-based high-resolution remote sensing of SF6 and also contribute to generate new reliable remote sensing data in this sparsely monitored region for investigations of climate change, global warming, and air pollution.
Surrogate-Assisted Autoencoder-Embedded Evolutionary Optimization Algorithm to Solve High-Dimensional Expensive Problems

Surrogate-assisted evolutionary algorithms (EAs) have been intensively used to solve computationally expensive problems with some success. However, traditional EAs are not suitable to deal with high-dimensional expensive problems (HEPs) with high-dimensional search space even if their fitness evaluations are assisted by surrogate models. The recently proposed autoencoder-embedded evolutionary optimization (AEO) framework is highly appropriate to deal with high-dimensional problems. This work aims to incorporate surrogate models into it to further boost its performance, thus resulting in surrogate-assisted AEO (SAEO). It proposes a novel model management strategy that can guarantee reasonable amounts of re-evaluations; hence, the accuracy of surrogate models can be enhanced via being updated with new evaluated samples. Moreover, to ensure enough data samples before constructing surrogates, a problem-dimensionality-dependent activation condition is developed for incorporating surrogates into the SAEO framework. SAEO is tested on seven commonly used benchmark functions and compared with state-of-the-art algorithms for HEPs. The experimental results show that SAEO can further enhance the performance of AEO on most cases and SAEO performs significantly better than other algorithms. Therefore, SAEO has great potential to deal with HEPs.
Uma Abordagem Computacional em Ambientes Assistidos Baseada em Atividades Físicas e Biometeorologia

A importância de realizar atividades físicas para preservar a saúde pessoal é um conhecimento comum a toda sociedade humana. Uma pergunta a ser considerada seria: o desempenho, ao realizar essas atividades, é afetado pelo ecossistema que cerca as pessoas? Afetar o desempenho signiﬁca afetar o rendimento e, em contrapartida, implica afetar a eﬁciência na realização da atividade.Este trabalho de pesquisa apresenta uma proposta de uma aplicação que visa amparar proﬁssionais da área de educação física no acompanhamento de seus alunos, enquanto leva em consideração os elementos meteorológicos que os afetam. Outra contribuição diferencial foi a simulação desenvolvida visando uma melhor visualização do ambiente.
Social Frailty and Executive Function: Association with Geriatric Syndromes, Life Space and Quality of Life in Healthy Community-Dwelling Older Adults

Despite emerging evidence about the association between social frailty and cognitive impairment, little is known about the role of executive function in this interplay, and whether the coexistence of social frailty and cognitive impairment predisposes to adverse health outcomes in healthy community-dwelling older adults. We aim to examine independent associations between social frailty with the MMSE and FAB, and to determine if having both social frailty and cognitive impairment is associated with worse health outcomes than either or neither condition. We studied 229 cognitively intact and functionally independent community-dwelling older adults (mean age= 67.2±7.43). Outcome measures comprise physical activity; physical performance and frailty; geriatric syndromes; life space and quality of life. We compared Chinese Mini Mental State Examination (CMMSE) and Chinese Frontal Assessment Battery (FAB) scores across the socially non-frail, socially pre-frail and socially frail. Participants were further recategorized into three subgroups (neither, either or both) based on presence of social frailty and cognitive impairment. Cognitive impairment was defined as a score below the educational adjusted cut-offs in either CMMSE or FAB. We performed logistic regression adjusted for significant covariates and mood to examine association with outcomes across the three subgroups. Compared with CMMSE, Chinese FAB scores significantly decreased across the social frailty spectrum (p<0.001), suggesting strong association between executive function with social frailty. We derived three subgroups relative to relationship with socially frailty and executive dysfunction: (i) Neither, N=140(61.1%), (ii) Either, N=79(34.5%), and (iii) Both, N=10(4.4%). Compared with neither or either subgroups, having both social frailty and executive dysfunction was associated with anorexia (OR=4.79, 95% CI= 1.04–22.02), near falls and falls (OR= 5.23, 95% CI= 1.10–24.90), lower life-space mobility (odds ratio, OR=9.80, 95% CI=2.07–46.31) and poorer quality of life (OR= 13.2, 95% CI= 2.38–73.4). Our results explicated the association of executive dysfunction with social frailty, and their synergistic relationship independent of mood with geriatric syndromes, decreased life space and poorer quality of life. In light of the current COVID-19 pandemic, the association between social frailty and executive dysfunction merits further study as a possible target for early intervention in relatively healthy older adults.
Prediction of land surface temperature of major coastal cities of India using bidirectional LSTM neural networks

Surface Temperature (ST) is important in terms of surface energy and terrestrial water balances affecting urban ecosystems. In this study, to process the nonlinear changes of climatological variables by leveraging the distinct advantages of Long Short-Term Memory (LSTM) and Bidirectional Long Short-Term Memory (BiLSTM), we propose an LSTM-BiLSTM hybrid deep learning model which extracts multi-dimension features of inputs, i.e., backward (future to past) or forward (past to future) to predict ST. This study assessed the climatological variables, i.e., wind speed, wind direction, relative humidity, dew point temperature, and atmospheric pressure impact on ST using five major coastal cities of India: Chennai, Mangalore, Visakhapatnam, Cuddalore, and Cochin. The Recurrent Neural Networks (RNN) and hybrid LSTM-BiLSTM models have effectively predicted ST and outperformed the standalone Artificial Neural Networks (ANN), LSTM, and BiLSTM models. The RNN and LSTM-BiLSTM models have performed better in predicting ST for Mangalore (Nash-Sutcliffe efficiency (NSE)=0.91), followed by Cochin (NSE=0.89), Chennai (NSE=0.88), Cuddalore (NSE=0.88), and Vishakhapatnam (NSE=0.81). The hybrid data-driven modeling framework indicated that coupling the LSTM and BiLSTM models was proven effective in predicting the ST of coastal cities.
Predictive Model of ACC Speed to Enhance Engine Operating Conditions

The ACC feature when activated augments the engine performance in real-time. This article presents a novel methodology to predict the optimal adaptive cruise control set speed profile (ACCSSP) by considering all the effecting parameters. This paper investigates engine operating conditions (EOC) criteria to develop a predictive model of ACCSSP in real-time. We developed a deep learning (DL) model using the NARX method to predict engine operating point (EOP) mapping the vehicle-level vectors (VLV). We used real-world field data obtained from Cadillac test vehicles driven by activating the ACC feature for developing the DL model. We used a realistic set of assumptions to estimate the VLV for the future time steps for the range of allowable speed values and applied them at the input of the developed DL model to generate multiple sets of EOP’s. We imposed the defined EOC criteria on these EOPs, and the top three modes of speeds satisfying all the requirements are derived for each second. Thus three eligible speed values are estimated for each second, and an additional criterion is defined to generate a unique ACCSSP for future time steps. Performance comparison between predicted and constant ACCSSPs indicates that the predictive model outperforms constant ACCSSP.
Establishment of two nonnative parthenogenetic reptiles on Saba, Dutch Caribbean: Gymnophthalmus underwoodi and Indotyphlops braminus

Matthijs P. van den Burg1,2,*, Alwin Hylkema3,4, and Adolphe O. Debrot1,4 1Wageningen Marine Research, Wageningen University and Research, P.O. Box 57, 1780 AB Den Helder, the Netherlands. 2BioCoRe S. Coop Calle Villagarcía 6, 28010, Madrid, Spain. 3Coastal and Marine Systems, University of Applied Sciences Van Hall Larenstein, P.O. Box 1528, 8901 BV Leeuwarden, the Netherlands. 4Marine Animal Ecology group, Wageningen University and Research, P.O. Box 338, 6700 AH Wageningen, the Netherlands. *Corresponding author (thijs.burg@gmail.com)