BACKGROUND: Recent advances in genomics of viruses and cellular life forms have greatly stimulated interest in the origins and evolution of viruses and, for the first time, offer an opportunity for a data-driven exploration of the deepest roots of viruses. Here we briefly review the current views of virus evolution and propose a new, coherent scenario that appears to be best compatible with comparative-genomic data and is naturally linked to models of cellular evolution that, from independent considerations, seem to be the most parsimonious among the existing ones. RESULTS: Several genes coding for key proteins involved in viral replication and morphogenesis as well as the major capsid protein of icosahedral virions are shared by many groups of RNA and DNA viruses but are missing in cellular life forms. On the basis of this key observation and the data on extensive genetic exchange between diverse viruses, we propose the concept of the ancient virus world. The virus world is construed as a distinct contingent of viral genes that continuously retained its identity throughout the entire history of life. Under this concept, the principal lineages of viruses and related selfish agents emerged from the primordial pool of primitive genetic elements, the ancestors of both cellular and viral genes. Thus, notwithstanding the numerous gene exchanges and acquisitions attributed to later stages of evolution, most, if not all, modern viruses and other selfish agents are inferred to descend from elements that belonged to the primordial genetic pool. In this pool, RNA viruses would evolve first, followed by retroid elements, and DNA viruses. The Virus World concept is predicated on a model of early evolution whereby emergence of substantial genetic diversity antedates the advent of full-fledged cells, allowing for extensive gene mixing at this early stage of evolution. We outline a scenario of the origin of the main classes of viruses in conjunction with a specific model of precellular evolution under which the primordial gene pool dwelled in a network of inorganic compartments. Somewhat paradoxically, under this scenario, we surmise that selfish genetic elements ancestral to viruses evolved prior to typical cells, to become intracellular parasites once bacteria and archaea arrived at the scene. Selection against excessively aggressive parasites that would kill off the host ensembles of genetic elements would lead to early evolution of temperate virus-like agents and primitive defense mechanisms, possibly, based on the RNA interference principle. The emergence of the eukaryotic cell is construed as the second melting pot of virus evolution from which the major groups of eukaryotic viruses originated as a result of extensive recombination of genes from various bacteriophages, archaeal viruses, plasmids, and the evolving eukaryotic genomes. Again, this vision is predicated on a specific model of the emergence of eukaryotic cell under which archaeo-bacterial symbiosis was the starting point of eukaryogenesis, a scenario that appears to be best compatible with the data. CONCLUSION: The existence of several genes that are central to virus replication and structure, are shared by a broad variety of viruses but are missing from cellular genomes (virus hallmark genes) suggests the model of an ancient virus world, a flow of virus-specific genes that went uninterrupted from the precellular stage of life's evolution to this day. This concept is tightly linked to two key conjectures on evolution of cells: existence of a complex, precellular, compartmentalized but extensively mixing and recombining pool of genes, and origin of the eukaryotic cell by archaeo-bacterial fusion. The virus world concept and these models of major transitions in the evolution of cells provide complementary pieces of an emerging coherent picture of life's history. REVIEWERS: W. Ford Doolittle, J. Peter Gogarten, and Arcady Mushegian.
<h3>Abstract</h3> <b>Objectives:</b> To determine the attitude of general practitioners towards evidence based medicine and their related educational needs. <b>Design:</b> A questionnaire study of general practitioners. <b>Setting:</b> General practice in the former Wessex region, England. <b>Subjects:</b> Randomly selected sample of 25% of all general practitioners (452), of whom 302 replied. <b>Main outcome measures:</b> Respondents9 attitude towards evidence based medicine, ability to access and interpret evidence, perceived barriers to practising evidence based medicine, and best method of moving from opinion based to evidence based medicine. <b>Results:</b> Respondents mainly welcomed evidence based medicine and agreed that its practice improves patient care. They had a low level of awareness of extracting journals, review publications, and databases (only 40% knew of the <i>Cochrane Database of Systematic Reviews</i>), and, even if aware, many did not use them. In their surgeries 20% had access to bibliographic databases and 17% to the world wide web. Most had some understanding of the technical terms used. The major perceived barrier to practising evidence based medicine was lack of personal time. Respondents thought the most appropriate way to move towards evidence based general practice was by using evidence based guidelines or proposals developed by colleagues. <b>Conclusion:</b> Promoting and improving access to summaries of evidence, rather than teaching all general practitioners literature searching and critical appraisal, would be the more appropriate method of encouraging evidence based general practice. General practitioners who are skilled in accessing and interpreting evidence should be encouraged to develop local evidence based guidelines and advice. <h3>Key messages</h3> Despite considerable variation in 302 general practitioners9 attitudes to the promotion of evidence based medicine, most were welcoming and agreed that it improved patient care There was a low level of awareness of extracting journals, review publications, and databases relevant to evidence based medicine, and the major perceived barrier to its practice was lack of personal time In their surgery only 20% of general practitioners had access to Medline or other bibliographic databases and 17% had access to the world wide web Most had some understanding of the technical terms used in evidence based medicine, but less than a third felt able to explain to others the meaning of these terms Respondents thought that the best way to move from opinion based practice towards evidence based medicine was by using evidence based guidelines or protocols developed by colleagues
We compare the network of aggregated journal-journal citation relations provided by the Journal Citation Reports (JCR) 2012 of the Science and Social Science Citation Indexes (SCI and SSCI) with similar data based on Scopus 2012. First, global maps were developed for the two sets separately; sets of documents can then be compared using overlays to both maps. Using fuzzy-string matching and ISSN numbers, we were able to match 10,524 journal names between the two sets; that is, 96.4% of the 10,936 journals contained in JCR or 51.2% of the 20,554 journals covered by Scopus. Network analysis was then pursued on the set of journals shared between the two databases and the two sets of unique journals. Citations among the shared journals are more comprehensively covered in JCR than Scopus, so the network in JCR is denser and more connected than in Scopus. The ranking of shared journals in terms of indegree (that is, numbers of citing journals) or total citations is similar in both databases overall (Spearman's \r{ho} > 0.97), but some individual journals rank very differently. Journals that are unique to Scopus seem to be less important--they are citing shared journals rather than bein
Webology is an international peer-reviewed journal in English devoted to the field of the World Wide Web and serves as a forum for discussion and experimentation. It serves as a forum for new research in information dissemination and communication processes in general, and in the context of the World Wide Web in particular. This paper presents a Scientometric analysis of the Webology Journal. The paper analyses the pattern of growth of the research output published in the journal, pattern of authorship, author productivity, and subjects covered to the papers over the period (2013-2017). It is found that 62 papers were published during the period of study (2013-2017). The maximum numbers of articles were collaborative in nature. The subject concentration of the journal noted was Social Networking/Web 2.0/Library 2.0 and Scientometrics or Bibliometrics. Iranian researchers contributed the maximum number of articles (37.10%). The study applied standard formula and statistical tools to bring out the factual result.
Rankings of scholarly journals based on citation data are often met with skepticism by the scientific community. Part of the skepticism is due to disparity between the common perception of journals' prestige and their ranking based on citation counts. A more serious concern is the inappropriate use of journal rankings to evaluate the scientific influence of authors. This paper focuses on analysis of the table of cross-citations among a selection of Statistics journals. Data are collected from the Web of Science database published by Thomson Reuters. Our results suggest that modelling the exchange of citations between journals is useful to highlight the most prestigious journals, but also that journal citation data are characterized by considerable heterogeneity, which needs to be properly summarized. Inferential conclusions require care in order to avoid potential over-interpretation of insignificant differences between journal ratings. Comparison with published ratings of institutions from the UK's Research Assessment Exercise shows strong correlation at aggregate level between assessed research quality and journal citation `export scores' within the discipline of Statistics.
This study examines the social media uptake of scientific journals on two different platforms - X and WeChat - by comparing the adoption of X among journals indexed in the Science Citation Index-Expanded (SCIE) with the adoption of WeChat among journals indexed in the Chinese Science Citation Database (CSCD). The findings reveal substantial differences in platform adoption and user engagement, shaped by local contexts. While only 22.7% of SCIE journals maintain an X account, 84.4% of CSCD journals have a WeChat official account. Journals in Life Sciences & Biomedicine lead in uptake on both platforms, whereas those in Technology and Physical Sciences show high WeChat uptake but comparatively lower presence on X. User engagement on both platforms is dominated by low-effort interactions rather than more conversational behaviors. Correlation analyses indicate weak-to-moderate relationships between bibliometric indicators and social media metrics, confirming that online engagement reflects a distinct dimension of journal impact, whether on an international or a local platform. These findings underscore the need for broader social media metric frameworks that incorporate locally dom
Robot learning from interacting with the physical world is fundamentally bottlenecked by the cost of physical interaction. The two alternatives, supervised finetuning (SFT) from expert demonstrations and reinforcement learning (RL) in a software-based simulator, are limited by the amount of expert data available and the sim-to-real gap for manipulation. With the recent emergence of world models learned from real-world video-action data, we ask the question of whether training a policy in a world model can be more effective than supervised learning or software simulation in achieving better real-robot performance. We propose World-Gymnast, which performs RL finetuning of a vision-language-action (VLA) policy by rolling out the policy in an action-conditioned video world model and rewarding the rollouts with a vision-language model (VLM). On the Bridge robot setup, World-Gymnast outperforms SFT by as much as 18x and outperforms software simulator by as much as 2x. More importantly, World-Gymnast demonstrates intriguing capabilities of RL with a world model, including training on diverse language instructions and novel scenes from the world model, test-time training in a novel scene,
Interdisciplinary research is critical for innovation and addressing complex societal issues. We characterise the interdisciplinary knowledge structure of PubMed research articles in medicine as correlation networks of medical concepts and compare the interdisciplinarity of articles between high-ranking (impactful) and less high-ranking (less impactful) medical journals. We found that impactful medical journals tend to publish research that are less interdisciplinary than less impactful journals. Observing that they bridge distant knowledge clusters in the networks, we find that cancer-related research can be seen as one of the main drivers of interdisciplinarity in medical science. Using signed difference networks, we also investigate the clustering of deviations between high and low impact journal correlation networks. We generally find a mild tendency for strong link differences to be adjacent. Furthermore, we find topic clusters of deviations that shift over time. In contrast, topic clusters in the original networks are static over time and can be seen as the core knowledge structure in medicine. Overall, journals and policymakers should encourage initiatives to accommodate int
An exploratory, descriptive analysis is presented of the national orientation of scientific, scholarly journals as reflected in the affiliations of publishing or citing authors. It calculates for journals covered in Scopus an Index of National Orientation (INO), and analyses the distribution of INO values across disciplines and countries, and the correlation between INO values and journal impact factors. The study did not find solid evidence that journal impact factors are good measures of journal internationality in terms of the geographical distribution of publishing or citing authors, as the relationship between a journal's national orientation and its citation impact is found to be inverse U-shaped. In addition, journals publishing in English are not necessarily internationally oriented in terms of the affiliations of publishing or citing authors; in social sciences and humanities also USA has their nationally oriented literatures. The paper examines the extent to which nationally oriented journals entering Scopus in earlier years, have become in recent years more international. It is found that in the study set about 40 per cent of such journals does reveal traces of internati
Overlay journals are characterised by their articles being published on open access repositories, often already starting in their initial preprint form as a prerequisite for submission to the journal prior to initiating the peer-review process. In this study we aimed to identify currently active overlay journals and examine their characteristics. We utilised an explorative web search and contacted key service providers for additional information. The final sample consisted of 34 overlay journals. While the results show that new overlay journals have been actively established within recent years, the current presence of overlay journals remains diminutive compared to the overall number of open access journals. Most overlay journals publish articles in natural sciences, mathematics or computer sciences, and are commonly published by groups of academics rather than formal organisations. They may also rank highly within the traditional journal citation metrics. None of the investigated journals required fees from authors, which is likely related to the cost-effective aspects of the overlay publishing model. Both the growth in adoption of open access preprint repositories and researcher
What does Artificial Intelligence (AI) have to contribute to health care? And what should we be looking out for if we are worried about its risks? In this paper we offer a survey, and initial evaluation, of hopes and fears about the applications of artificial intelligence in medicine. AI clearly has enormous potential as a research tool, in genomics and public health especially, as well as a diagnostic aid. It's also highly likely to impact on the organisational and business practices of healthcare systems in ways that are perhaps under-appreciated. Enthusiasts for AI have held out the prospect that it will free physicians up to spend more time attending to what really matters to them and their patients. We will argue that this claim depends upon implausible assumptions about the institutional and economic imperatives operating in contemporary healthcare settings. We will also highlight important concerns about privacy, surveillance, and bias in big data, as well as the risks of over trust in machines, the challenges of transparency, the deskilling of healthcare practitioners, the way AI reframes healthcare, and the implications of AI for the distribution of power in healthcare ins
Using the Scopus dataset (1996-2007) a grand matrix of aggregated journal-journal citations was constructed. This matrix can be compared in terms of the network structures with the matrix contained in the Journal Citation Reports (JCR) of the Institute of Scientific Information (ISI). Since the Scopus database contains a larger number of journals and covers also the humanities, one would expect richer maps. However, the matrix is in this case sparser than in the case of the ISI data. This is due to (i) the larger number of journals covered by Scopus and (ii) the historical record of citations older than ten years contained in the ISI database. When the data is highly structured, as in the case of large journals, the maps are comparable, although one may have to vary a threshold (because of the differences in densities). In the case of interdisciplinary journals and journals in the social sciences and humanities, the new database does not add a lot to what is possible with the ISI databases.
Interdisciplinary research, a process of knowledge integration, is vital for scientific advancements. It remains unclear whether prestigious journals that are highly impactful lead in disseminating interdisciplinary knowledge. In this paper, by constructing topic-level correlation networks based on publications, we evaluated the interdisciplinarity of more and less prestigious journals in medicine. We found research from prestigious medical journals tends to be less interdisciplinary than research from other medical journals. We also established that cancer-related research is the main driver of interdisciplinarity in medical science. Our results indicate a weak tendency for differences in topic correlations between more and less prestigious journals to be co-located. Accordingly, we identified that interdisciplinarity in prestigious journals mainly differs from interdisciplinarity in other journals in areas such as infections, nervous system diseases and cancer. Overall, our results suggest that interdisciplinarity in science could benefit from prestigious journals easing rigid disciplinary boundaries.
We introduce HY-World 2.0, a multi-modal world model framework that advances our prior project HY-World 1.0. HY-World 2.0 accommodates diverse input modalities, including text prompts, single-view images, multi-view images, and videos, and produces 3D world representations. With text or single-view image inputs, the model performs world generation, synthesizing high-fidelity, navigable 3D Gaussian Splatting (3DGS) scenes. This is achieved through a four-stage method: a) Panorama Generation with HY-Pano 2.0, b) Trajectory Planning with WorldNav, c) World Expansion with WorldStereo 2.0, and d) World Composition with WorldMirror 2.0. Specifically, we introduce key innovations to enhance panorama fidelity, enable 3D scene understanding and planning, and upgrade WorldStereo, our keyframe-based view generation model with consistent memory. We also upgrade WorldMirror, a feed-forward model for universal 3D prediction, by refining model architecture and learning strategy, enabling world reconstruction from multi-view images or videos. Also, we introduce WorldLens, a high-performance 3DGS rendering platform featuring a flexible engine-agnostic architecture, automatic IBL lighting, efficient
Recent studies indicate that Generative Pre-trained Transformer 4 with Vision (GPT-4V) outperforms human physicians in medical challenge tasks. However, these evaluations primarily focused on the accuracy of multi-choice questions alone. Our study extends the current scope by conducting a comprehensive analysis of GPT-4V's rationales of image comprehension, recall of medical knowledge, and step-by-step multimodal reasoning when solving New England Journal of Medicine (NEJM) Image Challenges - an imaging quiz designed to test the knowledge and diagnostic capabilities of medical professionals. Evaluation results confirmed that GPT-4V performs comparatively to human physicians regarding multi-choice accuracy (81.6% vs. 77.8%). GPT-4V also performs well in cases where physicians incorrectly answer, with over 78% accuracy. However, we discovered that GPT-4V frequently presents flawed rationales in cases where it makes the correct final choices (35.5%), most prominent in image comprehension (27.2%). Regardless of GPT-4V's high accuracy in multi-choice questions, our findings emphasize the necessity for further in-depth evaluations of its rationales before integrating such multimodal AI m
A number of journal classification systems have been developed in bibliometrics since the launch of the Citation Indices by the Institute of Scientific Information (ISI) in the 1960s. These systems are used to normalize citation counts with respect to field-specific citation patterns. The best known system is the so-called "Web-of-Science Subject Categories" (WCs). In other systems papers are classified by algorithmic solutions. Using the Journal Citation Reports 2014 of the Science Citation Index and the Social Science Citation Index (n of journals = 11,149), we examine options for developing a new system based on journal classifications into subject categories using aggregated journal-journal citation data. Combining routines in VOSviewer and Pajek, a tree-like classification is developed. At each level one can generate a map of science for all the journals subsumed under a category. Nine major fields are distinguished at the top level. Further decomposition of the social sciences is pursued for the sake of example with a focus on journals in information science (LIS) and science studies (STS). The new classification system improves on alternative options by avoiding the problem
The academic journal zoning system is central to evaluating research talent, funding, and institutions. The CAS journal partition system, one of East Asia's most widely used tools, will cease operation in March 2026, creating a policy gap. Existing alternatives have major limitations: JCR depends on paid databases and excludes conferences; Scimago/CiteScore relies on Elsevier proprietary data; expert-based rankings such as CCF and CORE lack quantitative foundations and update slowly. This paper proposes the General Science Ranking (GSR), a multidimensional bibliometric framework built entirely on open-source data. GSR covers 500 computer science venues (397 journals and 103 conferences) and 500 medical journals using OpenAlex and Semantic Scholar. Scores combine four indicators: field-weighted citation impact (FWCI), two-year impact factor (IF2), five-year h-index (h5), and citation CAGR. For CS conferences lacking citation time-series data, IF2-approx was estimated from calibration on 1.41 million OpenAlex journal papers. Rankings adopt fixed quotas: Q1 (1-50), Q2 (51-100), Q3 (101-200), and Q4 (201+). All code and data are open source. In CS rankings, conferences and journals eac
World models predict state transitions in response to actions and are increasingly developed across diverse modalities. However, standard training objectives such as maximum likelihood estimation (MLE) often misalign with task-specific goals of world models, i.e., transition prediction metrics like accuracy or perceptual quality. In this paper, we present RLVR-World, a unified framework that leverages reinforcement learning with verifiable rewards (RLVR) to directly optimize world models for such metrics. Despite formulating world modeling as autoregressive prediction of tokenized sequences, RLVR-World evaluates metrics of decoded predictions as verifiable rewards. We demonstrate substantial performance gains on both language- and video-based world models across domains, including text games, web navigation, and robot manipulation. Our work indicates that, beyond recent advances in reasoning language models, RLVR offers a promising post-training paradigm for enhancing the utility of generative models more broadly. Code, datasets, models, and video samples are available at the project website: https://thuml.github.io/RLVR-World.
Virtual reality (VR) started about 50 years ago in a form we would recognize today [stereo head-mounted display (HMD), head tracking, computer graphics generated images] – although the hardware was completely different. In the 1980s and 1990s, VR emerged again based on a different generation of hardware (e.g., CRT displays rather than vector refresh, electromagnetic tracking instead of mechanical). This reached the attention of the public, and VR was hailed by many engineers, scientists, celebrities, and business people as the beginning of a new era, when VR would soon change the world for the better. Then, VR disappeared from public view and was rumored to be “dead.” In the intervening 25 years a huge amount of research has nevertheless been carried out across a vast range of applications – from medicine to business, from psychotherapy to industry, from sports to travel. Scientists, engineers, and people working in industry carried on with their research and applications using and exploring different forms of VR, not knowing that actually the topic had already passed away. \n \nThe purpose of this article is to survey a range of VR applications where there is some evidence for, or at least debate about, its utility, mainly based on publications in peer-reviewed journals. Of course not every type of application has been covered, nor every scientific paper (about 186,000 papers in Google Scholar): in particular, in this review we have not covered applications in psychological or medical rehabilitation. The objective is that the reader becomes aware of what has been accomplished in VR, where the evidence is weaker or stronger, and what can be done. We start in Section 1 with an outline of what VR is and the major conceptual framework used to understand what happens when people experience it – the concept of “presence.” In Section 2, we review some areas where VR has been used in science – mostly psychology and neuroscience, the area of scientific visualization, and some remarks about its use in education and surgical training. In Section 3, we discuss how VR has been used in sports and exercise. In Section 4, we survey applications in social psychology and related areas – how VR has been used to throw light on some social phenomena, and how it can be used to tackle experimentally areas that cannot be studied experimentally in real life. We conclude with how it has been used in the preservation of and access to cultural heritage. In Section 5, we present the domain of moral behavior, including an example of how it might be used to train professionals such as medical doctors when confronting serious dilemmas with patients. In Section 6, we consider how VR has been and might be used in various aspects of travel, collaboration, and industry. In Section 7, we consider mainly the use of VR in news presentation and also discuss different types of VR. In the concluding Section 8, we briefly consider new ideas that have recently emerged – an impossible task since during the short time we have written this page even newer ideas have emerged! And, we conclude with some general considerations and speculations. \n \nThroughout and wherever possible we have stressed novel applications and approaches and how the real power of VR is not necessarily to produce a faithful reproduction of “reality” but rather that it offers the possibility to step outside of the normal bounds of reality and realize goals in a totally new and unexpected way. We hope that our article will provoke readers to think as paradigm changers, and advance VR to realize different worlds that might have a positive impact on the lives of millions of people worldwide, and maybe even help a little in saving the planet.
BACKGROUND: Modern medicine often clashes with traditional medicine such as Chinese herbal medicine because of the little understanding of the underlying mechanisms of action of the herbs. In an effort to promote integration of both sides and to accelerate the drug discovery from herbal medicines, an efficient systems pharmacology platform that represents ideal information convergence of pharmacochemistry, ADME properties, drug-likeness, drug targets, associated diseases and interaction networks, are urgently needed. DESCRIPTION: The traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) was built based on the framework of systems pharmacology for herbal medicines. It consists of all the 499 Chinese herbs registered in the Chinese pharmacopoeia with 29,384 ingredients, 3,311 targets and 837 associated diseases. Twelve important ADME-related properties like human oral bioavailability, half-life, drug-likeness, Caco-2 permeability, blood-brain barrier and Lipinski's rule of five are provided for drug screening and evaluation. TCMSP also provides drug targets and diseases of each active compound, which can automatically establish the compound-target and target-disease networks that let users view and analyze the drug action mechanisms. It is designed to fuel the development of herbal medicines and to promote integration of modern medicine and traditional medicine for drug discovery and development. CONCLUSIONS: The particular strengths of TCMSP are the composition of the large number of herbal entries, and the ability to identify drug-target networks and drug-disease networks, which will help revealing the mechanisms of action of Chinese herbs, uncovering the nature of TCM theory and developing new herb-oriented drugs. TCMSP is freely available at http://sm.nwsuaf.edu.cn/lsp/tcmsp.php.