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Visual sunspot observations form the longest scientific record of solar activity, spanning over four centuries. Long term solar studies are crucial to predict the future evolution of the solar cycles and at improving our understanding of the solar influence on Earth climate change.As an important step for the ongoing sunspot number recalibration throughout the entire solar physics community, (Lefevre et al., 2018), SN Version 2 was released in July, 2015 (Clette et al., 2016), which helped in shedding new light to long-term solar variations and instabilities of the 11-year solar cycle. However, uncertainties remain and errors in past historical data need to be further revised using the data at our disposal for a robust long-term series.In 1843, Professor Rudolf Wolf who coined the term “Sunspot Number”, founded a journal called the "Mittheilungen der Naturforschenden Gesellschaft in Berne" where he published yearbooks with all of his findings, including sunspot observations as far back as Galileo (Wolf, 1861). The journal was maintained from 1848 (Wolf, 1848) until his death (Wolf and Wolfer, 1894). The Sunspot records collected by him from his European colleagues and his auxiliary observers are all tabulated in this journal. The Royal Observatory of Belgium (https://www.astro.oma.be/en/), particularly the WDC-SILSO, conducted a mission between 2017 and 2019 to digitize all the data contained in the published Mittheilungen.In this study we exploit this database along with other available recounts of various observers to identify scale discrepancies or inhomogeneities that happened along the Sunspot number series over time. We also introduce statistical techniques to implement confidence bands or errors on daily Sunspot Numbers, an information that existing versions lack. The long-term aim is a complete reconstruction of the Sunspot Number series from the available raw data instead of a recalibration.

A combined morphological and molecular genetic study of the European species within the /Rhombisporum clade of the genus Entoloma reveals a high species diversity. This group comprises typical grassland species with pronounced and well-differentiated cheilocystidia, and a wide range of spore shapes varying from rhomboid to five-angled. To fix the concept of the classical species E. rhombisporum, a neotype is designated. Nine species are described as new to science based on the result of nrDNA ITS phylogeny with additional gap coding, and morphological characterization: E. caulocystidiatum, E. lunare, E. pararhombisporum, E. pentagonale, E. perrhombisporum, E. rhombiibericum, E. rhombisporoides, E. sororpratulense, and E. subcuboideum. The ITS sequences of the holotypes of previously described species belonging to the /Rhombisporum clade, viz., E. laurisilvae and E. pratulense have also been generated and are published here for the first time. Since many of the above-mentioned species have been misidentified as E. cocles, it seemed opportune to also study this species and to designate a neotype to fix its current concept. A key including European species is presented. As most of the species are potentially important indicators for threatened grassland communities, the 130 ITS barcodes newly generated for this study may be useful as a reference in conservation and metabarcoding projects.

Background Evidence-informed deliberative processes (EDPs) were recently introduced to guide health technology assessment (HTA) agencies to improve their processes towards more legitimate decision-making. The EDP framework provides guidance that covers the HTA process, ie, contextual factors, installation of an appraisal committee, selecting health technologies and criteria, assessment, appraisal, and communication and appeal. The aims of this study were to identify the level of use of EDPs by HTA agencies, identify their needs for guidance, and to learn about best practices. Methods A questionnaire for an online survey was developed based on the EDP framework, consisting of elements that reflect each part of the framework. The survey was sent to members of the International Network of Agencies for Health Technology Assessment (INAHTA). Two weeks following the invitation, a reminder was sent. The data collection took place between September-December 2018. Results Contact persons from 27 member agencies filled out the survey (response rate: 54%), of which 25 completed all questions. We found that contextual factors to support HTA development and the critical elements regarding conducting and reporting on HTA are overall in place. Respondents indicated that guidance was needed for specific elements related to selecting technologies and criteria, appraisal, and communication and appeal. With regard to best practices, the Canadian Agency for Drugs and Technologies and the National Institute for Health and Care Excellence (NICE, UK) were most often mentioned. Conclusion This is the first survey among HTA agencies regarding the use of EDPs and provides useful information for further developing a practical guide for HTA agencies around the globe. The results could support HTA agencies in improving their processes towards more legitimate decision-making, as they could serve as a baseline measurement for future monitoring and evaluation.

Objective Recent years have witnessed an increased interest in the use of multicriteria decision analysis (MCDA) to support health technology assessment (HTA) agencies for setting healthcare priorities. However, its implementation to date has been criticized for being “entirely mechanistic,” ignoring opportunity costs, and not following best practice guidelines. This article provides guidance on the use of MCDA in this context. Methods The present study was based on a systematic review and consensus development. We developed a typology of MCDA studies and good implementation practice. We reviewed 36 studies over the period 1990 to 2018 on their compliance with good practice and developed recommendations. We reached consensus among authors over the course of several review rounds. Results We identified 3 MCDA study types: qualitative MCDA, quantitative MCDA, and MCDA with decision rules. The types perform differently in terms of quality, consistency, and transparency of recommendations on healthcare priorities. We advise HTA agencies to always include a deliberative component. Agencies should, at a minimum, undertake qualitative MCDA. The use of quantitative MCDA has additional benefits but also poses design challenges. MCDA with decision rules, used by HTA agencies in The Netherlands and the United Kingdom and typically referred to as structured deliberation, has the potential to further improve the formulation of recommendations but has not yet been subjected to broad experimentation and evaluation. Conclusion MCDA holds large potential to support HTA agencies in setting healthcare priorities, but its implementation needs to be improved.

Background Countries around the world are increasingly rethinking the design of their health benefit packages to achieve universal health coverage and health technology assessment (HTA) bodies support governments in these decisions. Coverage decision-making is an intrinsically complex and value-laden political process, but value frameworks currently employed by HTA bodies do not sufficiently account for this complex reality. Methods Several years ago, evidence-informed deliberative processes (EDPs) were developed to address this issue. An EDP is a practical and stepwise approach for HTA bodies to enhance legitimate health benefit package design based on deliberation between stakeholders to identify, reflect and learn about the meaning and importance of values, and to interpret available evidence on these values. We further developed the conceptual framework and initial 2019 guidance based on academic knowledge exchange, analysing practices of HTA bodies, surveying HTA bodies and experts around the globe, and implementation of EDPs in several countries around the world.Results EDPs stem from the general concept of legitimacy, which is translated into four elements – stakeholder involvement ideally operationalised through stakeholder participation with deliberation; evidence-informed evaluation; transparency; and appeal. The 2021 practical guidance distinguishes six practical steps of a HTA process and provides recommendations on how these elements can be implemented in each of these steps. Conclusion There is an increased attention for legitimacy, deliberative processes for HTA and health benefit package design, but the development of theories and methods for such processes remain behind. The added value of EDPs lies in the operationalisation of the general concept of legitimacy into practical guidance for HTA bodies.

Background: Countries around the world are using health technology assessment (HTA) for health benefit package design. Evidence-informed deliberative processes (EDPs) are a practical and stepwise approach to enhance legitimate health benefit package design based on deliberation between stakeholders to identify, reflect and learn about the meaning and importance of values, informed by evidence on these values. This paper reports on the development of practical guidance on EDPs, while the conceptual framework of EDPs is described in a companion paper. Methods: The first guide on EDPs (2019) is further developed based on academic knowledge exchange, surveying 27 HTA bodies and 66 experts around the globe, and the implementation of EDPs in several countries. We present the revised steps of EDPs and how selected HTA bodies (in Australia, Brazil, Canada, France, Germany, Scotland, Thailand and the United Kingdom) organize key issues of legitimacy in their processes. This is based on a review of literature via PubMed and HTA bodies’ websites. Results: HTA bodies around the globe vary considerable in how they address legitimacy (stakeholder involvement ideally through participation with deliberation; evidence-informed evaluation; transparency; and appeal) in their processes. While there is increased attention for improving legitimacy in decision-making processes, we found that the selected HTA bodies are still lacking or just starting to develop activities in this area. We provide recommendations on how HTA bodies can improve on this. Conclusion: The design and implementation of EDPs is in its infancy. We call for a systematic analysis of experiences of a variety of countries, from which general principles on EDPs might subsequently be inferred.

Health Technology Assessment (HTA) uses explicit methods to determine the value of a health technology. This typically results in several claims regarding the effects that are expected to follow from the use of a health technology in a particular context. These claims seem to capture conclusions based solely on facts, but they often combine empirical information with normative presuppositions. Claims that have this character reflect (implicit) value judgments and have been labelled mixed claims. Not recognizing these normative components of such claims risks value inattention and value imposition, presenting results as self-evident and not in need of any moral justification. As proposed by Anna Alexandrova, to avoid these risks of value inattention and imposition we need rules to deal with mixed claims. According to her, when producing and evaluating mixed claims we need to unearth the invoked value presuppositions and check whether these presuppositions are invariant to disagreements. By applying these rules, the robustness of mixed claims can be checked: it can be evaluated whether their truth value is independent from the way in which their components, involving normative presuppositions, are conceptualized. This paper aims to illustrate the role of mixed claims in HTA, and expand upon the work by Alexandrova, by analyzing claims and recommendations presented in an HTA report on the introduction of Non-Invasive Prenatal Testing (NIPT) in The Netherlands. Our results show that the report contains mixed claims, and that a normative analysis of these claims can help to clarify the normativity of HTA and evaluate the robustness of claims on alleged effects of a health technology.

We compare the pricing ability of popular asset pricing models for the cross-section of U.S. equities on a large, liquid, but mostly segmented equity market of Chinese A-shares. The q-factor model performs well among factor models developed for the U.S. equity market, but is outperformed by a modified Fama-French six-factor model and by a four-factor asset pricing model adapted to the Chinese A-shares market. A data-driven method to detect the preferred asset pricing model results in the same four factors, plus three additional ones. However, these three additional factors do not reduce the pricing errors to a set of test assets. When taking transaction costs into account, the ranking of asset pricing models changes. The preferred model from both the direct and data-driven model comparison methods now consists of a three-factor model comprising the market, size, and an earnings-based value factor.

This paper sheds light on the similarities and differences with respect to the presence of anomalies in the China A-share market and other markets. To this end, we examine the existence of 32 anomalies in the China A-share market over the period 2000–2019. We find that value, risk, and trading anomalies carry over to China A-shares. Evidence for anomalies in the size, quality, and past return categories is substantially weaker, with the exception of a strong residual momentum and reversal effect. We document that most anomalies cannot be explained by industry composition, and are present among large, mid, and small capitalization stocks. We are the first to examine the existence of residual reversal, return seasonalities, and connected firm momentum for the China A-share market. We find strong out-of-sample evidence for the former two, but not the latter. Specific characteristics of the China A-share market, such as short-sale restrictions, the prevalence of state-owned enterprises, and the effect of stock market reforms, are examined in more detail. These features do not seem to be important drivers of our empirical findings.

In sparse high-dimensional data, the selection of a model can lead to an overestimation of the number of nonzero variables. Indeed, the use of an \(\ell _1\) norm constraint while minimising the sum of squared residuals tempers the effects of false positives, thus they are more likely to be included in the model. On the other hand, an \(\ell _0\) regularisation is a non-convex problem and finding its solution is a combinatorial challenge which becomes unfeasible for more than 50 variables. To overcome this situation, one can perform selection via an \(\ell _1\) penalisation but estimate the selected components without shrinkage. This leads to an additional bias in the optimisation of an information criterion over the model size. Used as a stopping rule, this IC must be modified to take into account the deviation of the estimation with and without shrinkage. By looking into the difference between the prediction error and the expected Mallows’s Cp, previous work has analysed a correction for the optimisation bias and an expression can be found for a signal-plus-noise model given some assumptions. A focus on structured models, in particular, grouped variables, shows similar results, though the bias is noticeably reduced.

Background: Some studies in the Netherlands have gauged public views on principles for health care priority setting, but they fall short of comprehensively explaining the public disapproval of several recent reimbursement decisions. Objective: To obtain insight into citizens’ preferences and identify the criteria they would propose for decisions pertaining to the benefits package of basic health insurance. Methods: Twenty-four Dutch citizens were selected for participation in a Citizen Forum, which involved 3 weekends. Deliberations took place in small groups and in plenary, guided by 2 moderators, on the basis of 8 preselected case studies, which participants later compared and prioritized under the premise that not all treatments can or need to be reimbursed. Participants received opportunities to inform themselves through written brochures and live interactions with 3 experts. Results: The Citizen Forum identified 16 criteria for inclusion or exclusion of treatments in the benefits package; they relate to the condition (2 criteria), treatment (11 criteria), and individual characteristics of those affected by the condition (3 criteria). In most case studies, it was a combination of criteria that determined whether or not participants favored inclusion of the treatment under consideration in the benefits package. Participants differed in their opinion about the relative importance of criteria, and they had difficulty in operationalizing and trading off criteria to provide a recommendation. Conclusions: Informed citizens are prepared to make and, to a certain extent, capable of making reasoned choices about the reimbursement of health services. They realize that choices are both necessary and possible. Broad public support and understanding for making tough choices regarding the benefits package of basic health insurance is not automatic: it requires an investment.

The estimation of a density function with an unknown number of singularities or discontinuities is a typical example of a multiscale problem, with data observed at nonequispaced locations. The data are analyzed through a multiscale local polynomial transform (MLPT), which can be seen as a slightly overcomplete, non-dyadic alternative for a wavelet transform, equipped with the benefits from a local polynomial smoothing procedure. In particular, the multiscale transform adopts a sequence of kernel bandwidths in the local polynomial smoothing as resolution level-dependent, user-controlled scales. The MLPT analysis leads to a reformulation of the problem as a variable selection in a sparse, high-dimensional regression model with exponentially distributed responses. The variable selection is realized by the optimization of the l1-regularized maximum likelihood, where the regularization parameter acts as a threshold. Fine-tuning of the threshold requires the optimization of an information criterion such as AIC. This paper develops discussions on results in [9].

Objective International guidelines recommend countries to expand antiretroviral therapy (ART) to all HIV-infected individuals and establish local-level priorities in relation to other treatment, prevention and mitigation interventions through fair processes. However, no practical guidance is provided for such priority-setting processes. Evidence-informed deliberative processes (EDPs) fill this gap and combine stakeholder deliberation to incorporate relevant social values with rational decision-making informed by evidence on these values. This study reports on the first-time implementation and evaluation of an EDP in HIV control, organised to support the AIDS Commission in West Java province, Indonesia, in the development of its strategic plan for 2014–2018. Methods Under the responsibility of the provincial AIDS Commission, an EDP was implemented to select priority interventions using six steps: (i) situational analysis; (ii) formation of a multistakeholder Consultation Panel; (iii) selection of criteria; (iv) identification and assessment of interventions’ performance; (v) deliberation; and (vi) selection of funding and implementing institutions. An independent researcher conducted in-depth interviews (n = 21) with panel members to evaluate the process. Results The Consultation Panel included 23 stakeholders. They identified 50 interventions and these were evaluated against four criteria: impact on the epidemic, stigma reduction, cost-effectiveness and universal coverage. After a deliberative discussion, the Consultation Panel prioritised a combination of several treatment, prevention and mitigation interventions. Conclusion The EDP improved both stakeholder involvement and the evidence base for the strategic planning process. EDPs fill an important gap which international guidelines and current tools for strategic planning in HIV control leave unaddressed.

Background: A deliberative Citizen Forum ‘Choices in healthcare’ was held in the Netherlands to obtain insight into the criteria informed citizens would propose for the public reimbursement of healthcare. During 3 weekends, 24 citizens participated in evidence-informed deliberation on the basis of 8 case studies. The aim of this study was to assess how the opinions of 8 participants in the deliberative Citizens Forum changed and if so, why participants themselves believe their opinions have changed, whether participation influenced their perceived reasonableness of other participants in the forum and whether it influenced their opinions about involvement of citizens in decision-making. Methods: Semi-structured interviews were held with 8 participants before and after their participation in the Citizen Forum. Using the method of reconstructing interpretive frames opinions about the public reimbursement of healthcare were reconstructed. Results: Participants’ opinions changed over time; they became more aware of the complexity of decision-making and came to accept that there are limits to the available resources and accept cost as a criterion for reimbursement decisionmaking. Participants report that exchanging arguments and personal experiences with other participants made them change their initial opinions. Participants ascribed increases in the perceived reasonableness of other participants’ opinions to feelings of group-bonding and becoming more familiar with each other’s personal circumstances. Participants further believe that citizens represent an additional opinion to that of other stakeholders and believe their opinions should be considered in relation to those of other stakeholders, given they are provided with opportunities for critical discussion. Conclusion: Organized deliberation should allow for the exchange of arguments and the sharing of personal experiences which is linked to learning. On the one hand this is reflected in the uptake of new arguments and on the other hand in the revision, specification or expansion of personal argumentation. Providing opportunities for critical deliberation is key to prevent citizens from adhering to initial emotional reactions that remain unchallenged and which may no longer be supported after deliberation.

Contains fulltext : 208833.pdf (Publisher’s version ) (Open Access)

The multiscale local polynomial transform, developped in this paper, combines the benefits from local polynomial smoothing with sparse multiscale decompositions. The contribution of the paper is twofold. First, it focusses on the bandwidths used throughout the transform. These bandwidths operate as user controlled scales in a multiscale analysis, which is explained to be of particular interest in the case of nonequispaced data. The paper presents both a likelihood based optimal bandwidth selection and a fast, heuristic approach. The second contribution of the paper is the combination of local polynomial smoothing with orthogonal prefilters, similar to Daubechies' wavelet filters, but defined on irregularly spaced covariate values.

Contains fulltext : 168069.pdf (Publisher’s version ) (Open Access) Priority setting of health interventions is generally considered as a valuable approach to support low- and middle-income countries (LMICs) in their strive for universal health coverage (UHC). However, present initiatives on priority setting are mainly geared towards the development of more cost-effectiveness information, and this evidence does not sufficiently support countries to make optimal choices. The reason is that priority setting is in reality a value-laden political process in which multiple criteria beyond cost-effectiveness are important, and stakeholders often justifiably disagree about the relative importance of these criteria. Here, we propose the use of 'evidence-informed deliberative processes' as an approach that does explicitly recognise priority setting as a political process and an intrinsically complex task. In these processes, deliberation between stakeholders is crucial to identify, reflect and learn about the meaning and importance of values, informed by evidence on these values. Such processes then result in the use of a broader range of explicit criteria that can be seen as the product of both international learning ('core' criteria, which include eg, cost-effectiveness, priority to the worse off, and financial protection) and learning among local stakeholders ('contextual' criteria). We believe that, with these evidence-informed deliberative processes in place, priority setting can provide a more meaningful contribution to achieving UHC.

AimLung cancer screening reduces mortality. We aim to validate the performance of Lung EpiCheck, a six-marker panel methylation-based plasma test, in the detection of lung cancer in European and Chinese samples.MethodsA case–control European training set (n=102 lung cancer cases, n=265 controls) was used to define the panel and algorithm. Two cut-offs were selected, low cut-off (LCO) for high sensitivity and high cut-off (HCO) for high specificity. The performance was validated in case–control European and Chinese validation sets (cases/controls 179/137 and 30/15, respectively).ResultsThe European and Chinese validation sets achieved AUCs of 0.882 and 0.899, respectively. The sensitivities/specificities with LCO were 87.2%/64.2% and 76.7%/93.3%, and with HCO they were 74.3%/90.5% and 56.7%/100.0%, respectively. Stage I nonsmall cell lung cancer (NSCLC) sensitivity in European and Chinese samples with LCO was 78.4% and 70.0% and with HCO was 62.2% and 30.0%, respectively. Small cell lung cancer (SCLC) was represented only in the European set and sensitivities with LCO and HCO were 100.0% and 93.3%, respectively. In multivariable analyses of the European validation set, the assay's ability to predict lung cancer was independent of established risk factors (age, smoking, COPD), and overall AUC was 0.942.ConclusionsLung EpiCheck demonstrated strong performance in lung cancer prediction in case–control European and Chinese samples, detecting high proportions of early-stage NSCLC and SCLC and significantly improving predictive accuracy when added to established risk factors. Prospective studies are required to confirm these findings. Utilising such a simple and inexpensive blood test has the potential to improve compliance and broaden access to screening for at-risk populations.

Accountable decision-makers are required to legitimize their priority setting decisions in health to members of society. In this perspective we stress the point that fair, legitimate processes should reflect efforts of authorities to treat all stakeholders as moral equals in terms of providing all people with well-justified, reasonable reasons to endorse the decisions. We argue there is a special moral concern for being accountable to those who are potentially adversely affected by decisions. Health authorities need to operationalize this requirement into real world action. In this perspective, we operationalize five key steps in doing so, in terms of (i) proactively identifying potentially adversely affected stakeholders; (ii) comprehensively including them in the decision-making process; (iii) ensuring meaningful participation; (iv) communication of recommendations or decisions; and (v) the organization of evaluation and appeal mechanisms. Health authorities are advised to use a checklist in the form of 29 reflective questions, aligned with these five key steps, to assist them in the practical organization of legitimate priority setting in healthcare.

This paper investigates two types of results that support the use of Generalized Cross Validation (GCV) for variable selection under the assumption of sparsity. The first type of result is based on the well established links between GCV on one hand and Mallows’s C p and Stein Unbiased Risk Estimator (SURE) on the other hand. The result states that GCV performs as well as C p or SURE in a regularized or penalized least squares problem as an estimator of the prediction error for the penalty in the neighborhood of its optimal value. This result can be seen as a refinement of an earlier result in GCV for soft thresholding of wavelet coefficients. The second novel result concentrates on the behavior of GCV for penalties near zero. Good behavior near zero is of crucial importance to ensure successful minimization of GCV as a function of the regularization parameter. Understanding the behavior near zero is important in the extension of GCV from l 1 towards l 0 regularized least squares, i.e., for variable selection without shrinkage, or hard thresholding. Several possible implementations of GCV are compared with each other and with SURE and C p . These simulations illustrate the importance of the fact that GCV has an implicit and robust estimator of the observational variance.

Optical remote sensing in complex waters is challenging because the optically active constituents may vary independently and have a combined and interacting influence on the remote sensing signal. Additionally, the remote sensing signal is influenced by noise and spectral contamination by confounding factors, resulting in ill-posedness and ill-conditionedness in the inversion of the model. There is a need for inversion methods that are less sensitive to these changing or shifting spectral features. We proposeWaveIN, a wavelet-enhanced inversion method, specifically designed for complex waters. It integrates wavelettransformed high-spectral resolution reflectance spectra in a multiscale analysis tool. Wavelets are less sensitive to a bias in the spectra and can avoid the changing or shifting spectral features by selecting specific wavelet scales. This paper applied WaveIN to simulated reflectance spectra for the Scheldt River. We tested different scenarios, where we added specificnoise or confounding factors, specifically uncorrelated noise, contamination due to spectral mixing, a different sun zenith angle, and specific inherent optical property (SIOP) variation.WaveIN improved the constituent estimation in case of the reference scenario, contamination due to spectral mixing, and a different sun zenith angle. WaveIN could reduce, but not overcome, the influence of variation in SIOPs. Furthermore, it is sensitive to wavelet edge effects. In addition, it still requires in situ data for the wavelet scale selection. Future research should therefore improve the wavelet scale selection. Index Terms--Chlorophyll-a, continuous wavelet transforms, dissolved organic matter, hyperspectral remote sensing, multiscale, optically complex waters, suspended matter.

Summary points The ever-growing HIV treatment programs in sub-Saharan Africa (SSA) present local policy makers with complex decision dilemmas, as international guidelines emphasize the need for expanded access to antiretroviral therapy (ART), yet funding has flatlined. We argue that the current evidence base for prioritizing ART scale-up strategies results in recommendations that are theoretically optimal but practically infeasible to implement. Cost-effectiveness analyses (CEAs) of scaling up ART in SSA should be made more responsive to the needs of policy makers by taking into account the local health system. We provide suggestions for a better integration of health system constraints into CEA by integrating supply- and demand-side constraints in mathematical models and improving the dialogue between researchers and policy makers.

Time and the Ancestors: Aztec and Mixtec Ritual Art combines iconographical analysis with archaeological, historical and ethnographic studies and offers new interpretations of enigmatic masterpieces from ancient Mexico, focusing specifically on the symbols and values of the religious heritage of indigenous peoples.

Contains fulltext : 173677.pdf (Publisher’s version ) (Open Access) Embedding health technology assessment (HTA) in a fair process has great potential to capture societal values relevant to public reimbursement decisions on health technologies. However, the development of such processes for priority setting has largely been theoretical. In this paper, we provide further practical lead ways on how these processes can be implemented. We first present the misconception about the relation between facts and values that is since long misleading the conduct of HTA and underlies the current assessment-appraisal split. We then argue that HTA should instead be explicitly organized as an ongoing evidence-informed deliberative process, that facilitates learning among stakeholders. This has important consequences for whose values to consider, how to deal with vested interests, how to consider all values in the decision-making process, and how to communicate decisions. This is in stark contrast to how HTA processes are implemented now. It is time to set the stage for HTA as learning.