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Advances in control techniques for vibrational quantum states in molecules present new challenges for modelling such systems, which could be amenable to quantum simulation methods. Here, by exploiting a natural mapping between vibrations in molecules and photons in waveguides, we demonstrate a reprogrammable photonic chip as a versatile simulation platform for a range of quantum dynamic behaviour in different molecules. We begin by simulating the time evolution of vibrational excitations in the harmonic approximation for several four-atom molecules, including H 2 CS, SO 3 , HNCO, HFHF, N 4 and P 4 . We then simulate coherent and dephased energy transport in the simplest model of the peptide bond in proteins— N -methylacetamide—and simulate thermal relaxation and the effect of anharmonicities in H 2 O. Finally, we use multi-photon statistics with a feedback control algorithm to iteratively identify quantum states that increase a particular dissociation pathway of NH 3 . These methods point to powerful new simulation tools for molecular quantum dynamics and the field of femtochemistry. By mapping vibrations in molecules to photons in waveguides, the vibrational quantum dynamics of various molecules are simulated using a photonic chip.

BackgroundAlmost 1/3 of incident pulmonary TB (PTB) cases in England start treatment >4 months after symptom onset.1 Leicester, a high incidence TB area (>40 cases/100,000 population) provides a centralised rapid access tuberculosis (RATB) pathway for suspected TB cases from primary and secondary care, facilitating urgent assessment. To expedite diagnosis, radiologists can assign urgent referral codes, such as the TB code, to streamline referrals to appropriate multidisciplinary teams.AimWe investigated the accuracy of radiology reports for diagnosing PTB and the impact of reporting codes and keywords on time to PTB notification in patients referred to the RATB service.MethodsWe assessed CXR reports of 1124 patients referred to the RATB service at University Hospitals of Leicester (Jan 2019–Dec 2023) for inclusion of TB or other urgent referral codes - lung cancer code (RAL), GPCTFU (GP CT follow-up), XRCCT (urgent CT follow-up) and TB keywords (TB*, tubercul*, mycobac*), and the intervals between CXR request, report and TB diagnosis.ResultsThere were 216 cases (19.2%) of PTB among the 1124 patients referred to RATB service. CXRs were performed promptly (median same-day), but median reporting times varied by requesting source - 2 days (A&E), 2 days (primary care), 6 days (inpatient), 11 days (outpatient) (p<0.001). Urgent codes or TB keywords were reported in 138 (63.9%) of the PTB cases. Interestingly, 22 PTB cases (10.2%) had reports containing TB keywords but no referral code assigned, and 41 cases (21.2%) had other abnormalities reported but no link to TB diagnosis was made. The diagnostic performance of different codes and TB keywords is noted in table 1. Inclusion of the RATB code or inclusion of TB keywords was associated with a significantly shorter median notification delay than non-coded cases (9 vs. 46.5 days (p<0.001)).Abstract M38 Table 1Effect of CXR coding and reporting of TB keywords on time to TB notification CXR CODING CATEGORIES IN PATIENT REFERRALS TO RATB Variable RATB coded RAL, GPCTFU or XRCCT urgent codes applied (RATB excluded) Non-urgent X-ray follow-up code (RATB and urgent codes excluded) Non-coded scans including TB keywords Non-coded scans with no TB keywords Number of CXRs in category (% total CXRs) 308(27.4) 103(9.2) 19(1.7) 79(7.0) 615(54.7) Number of PTB cases in the category (% of given category) 93(30.2) 23(22.3) 4(21.1) 22(27.8) 74(12.0) Sensitivity (%) [95% CI ] 43.1[36.4–49.9] 10.6[6.9–15.5] 1.9[0.5–4.7] 10.2[6.5–15.0] 34.3[28.0–41.0] Specificity (%) [95% CI ] 76.3[73.4–79.1] 91.2[89.2–93.0] 98.3[97.3–99.1] 93.7[91.9–95.2] 40.4[37.2–43.7] Median days from CXR report to PTB notification (IQR) 9(6–15) 29(11–45) 51.5(29–63) 10(5.5 – 24.5) 46.5(15–78) ConclusionAccurate reporting and inclusion of a TB code on CXR reports is a key driver of accelerated PTB diagnosis for RATB pathways. However, the code was applied to only a subset of cases, suggesting TB-related CXR changes lack specificity. These data provide a useful reference for evaluating AI-driven approaches to CXR reporting and coding for TB.Referencehttps://www.gov.uk/government/publications/tuberculosis-in-england-2023-report-data-up-to-end-of-2022/tb-treatment-and-outcomes-england-2022

People who are more avoidant of pathogens are more politically conservative, as are nations with greater parasite stress. In the current research, we test two prominent hypotheses that have been proposed as explanations for these relationships. The first, which is an intragroup account, holds that these relationships between pathogens and politics are based on motivations to adhere to local norms, which are sometimes shaped by cultural evolution to have pathogen-neutralizing properties. The second, which is an intergroup account, holds that these same relationships are based on motivations to avoid contact with outgroups, who might pose greater infectious disease threats than ingroup members. Results from a study surveying 11,501 participants across 30 nations are more consistent with the intragroup account than with the intergroup account. National parasite stress relates to traditionalism (an aspect of conservatism especially related to adherence to group norms) but not to social dominance orientation (SDO; an aspect of conservatism especially related to endorsements of intergroup barriers and negativity toward ethnic and racial outgroups). Further, individual differences in pathogen-avoidance motives (i.e., disgust sensitivity) relate more strongly to traditionalism than to SDO within the 30 nations.

With increasing worldwide demand for safe blood, there is much interest in generating red blood cells in vitro as an alternative clinical product. However, available methods for in vitro generation of red cells from adult and cord blood progenitors do not yet provide a sustainable supply, and current systems using pluripotent stem cells as progenitors do not generate viable red cells. We have taken an alternative approach, immortalizing early adult erythroblasts generating a stable line, which provides a continuous supply of red cells. The immortalized cells differentiate efficiently into mature, functional reticulocytes that can be isolated by filtration. Extensive characterization has not revealed any differences between these reticulocytes and in vitro -cultured adult reticulocytes functionally or at the molecular level, and importantly no aberrant protein expression. We demonstrate a feasible approach to the manufacture of red cells for clinical use from in vitro culture. The generation of a sustainable supply of erythroid progenitors is essential for the reliable production of an in vitro derived red blood cell clinical product. Here the authors immortalize early human erythroblasts to generate the first cell line capable of differentiation into functional adult reticulocytes.

This study examines the visibility, impact, and applications of bibliometric software tools in the peer-reviewed literature through a “Cited Reference Search” using the Web of Science (WOS) database. A total of 2882 citing research articles to eight bibliometric software tools were extracted from the WOS Core Collection between 2010 and 2021. These citing articles are analyzed by publication year, country, publication title, publisher, open access level, funding agency, and WOS category. Mentions of bibliometric software tools in Author Keywords and KeyWords Plus are also compared. The VOSviewer software is utilized to identify specific research areas by discipline from the keyword co-occurrences of the citing articles. The findings reveal that while bibliometric software tools are making a noteworthy impact and contribution to research, their visibility through referencing, Author Keywords, and KeyWords Plus is limited. This study serves as a clarion call to raise awareness and initiate discussions on the citing practices of software tools in scholarly publications.

Aims To visualize the trends and hotspots in the scientific research related to vascular cognitive impairment (VCI) quantitatively and qualitatively. Methods Cross‐sectional bibliometric analysis of publications that related to VCI was conducted. Publications were found by searching in the Web of Science Core Collection database (WoSCC) – Edition: Science Citation Index Expanded (SCI‐Expanded) from January 2000 to December 2021. Publication type was restricted to article and review in the English language. The downloaded data were screened and analyzed in January 2022. Results In total, 16,264 publications were identified, with a steady increase in annual publications. The United States was the leading country in VCI research regarding publication numbers and national influence. National Institute of Aging had the highest influence among all the institutes in the field of VCI. Philip Scheltens was the most active author. The top five active authors' publications focused on pathobiology, neuroimaging standards, risk factors, prevention, and the standard diagnosis of vascular dementia (VaD). A co‐cited publication clustering resulted in 19 main clusters, and the prevention, blood–brain barrier, cholesterol, cerebral amyloid angiopathy, and VaD were the top 5 clusters. Moreover, burst keywords detection revealed that the “small vessel disease” is the current hotspot in the field of VCI. Conclusions This bibliometric analysis mapped the overall research structure of VCI and analyzed the current research trends and hotspots for future studies orientation. Neuroimaging, risk factors detection, and pathobiology are the current trends in VCI research. Small vessel disease and its mechanisms are the current hotspots of VCI research. This bibliometric analysis mapped the overall research structure of VCI and analyzed the current research trends and hotspots for future studies orientation.

Knowledge evolution offers a road map for understanding knowledge creation, knowledge transfer, and performance in everyday work. Understanding the knowledge evolution of a research field is crucial for researchers, policymakers, and stakeholders. Further, paper keywords are considered efficient knowledge components to depict the knowledge structure of a research field by examining relationships between keywords. However, multiple relationships between keywords provided by papers are rarely used to explore knowledge evolution. Three relationships were applied: a direct co-occurrence relationship, indirect relationship by keyword pair citation, and same author trace, providing temporal and sequential knowledge evolution. The direct co-occurrence relationship is constructed by keyword co-occurrence pair and acts as the temporal structure of knowledge pairs. The indirect relationship is constructed by a keyword pair-based citation relationship, meaning the citation relationship between keyword co-occurrence pairs, acting as the sequential structure of knowledge pairs. Additionally, the same author trace represents an indirect relationship that a keyword pair provided by the same author in a different paper. Thus, knowledge evolution could be mined quantitatively from a different perspective. Therefore, we present an empirical study of the informetrics field with five evolution stages: knowledge generation, growth, obsolescence, transfer, and intergrowth. The results indicate that knowledge evolution is not a continuous trend but alternating growth and obsolescence. During evolution, knowledge pairs stimulate each other’s growth, and some knowledge pairs transfer to others, demonstrating a small step toward knowledge change. According to the indirect keyword relationship paired with the same author trace, creators and followers of knowledge evolution are different.

[This corrects the article DOI: 10.1371/journal.pone.0172778.].

Sentiment analysis, one of the research hotspots in the natural language processing field, has attracted the attention of researchers, and research papers on the field are increasingly published. Many literature reviews on sentiment analysis involving techniques, methods, and applications have been produced using different survey methodologies and tools, but there has not been a survey dedicated to the evolution of research methods and topics of sentiment analysis. There have also been few survey works leveraging keyword co-occurrence on sentiment analysis. Therefore, this study presents a survey of sentiment analysis focusing on the evolution of research methods and topics. It incorporates keyword co-occurrence analysis with a community detection algorithm. This survey not only compares and analyzes the connections between research methods and topics over the past two decades but also uncovers the hotspots and trends over time, thus providing guidance for researchers. Furthermore, this paper presents broad practical insights into the methods and topics of sentiment analysis, while also identifying technical directions, limitations, and future work.

Keywords: judgment of frequency, judgment of duration, dual path, common path, total time hypothesis, state trace analysis