5-endo-trig Radical Cyclizations:  A New Means to the Stereoselective Synthesis of Cyclopentanes and Diquinanes

Cross-electrophile coupling (XEC), defined by us as the cross-coupling of two different σ-electrophiles that is driven by catalyst reduction, has seen rapid progression in recent years. As such, this review aims to summarize the field from its beginnings up until mid-2023 and to provide comprehensive coverage on synthetic methods and current state of mechanistic understanding. Chapters are split by type of bond formed, which include C(sp3)–C(sp3), C(sp2)–C(sp2), C(sp2)–C(sp3), and C(sp2)–C(sp) bond formation. Additional chapters include alkene difunctionalization, alkyne difunctionalization, and formation of carbon-heteroatom bonds. Each chapter is generally organized with an initial summary of mechanisms followed by detailed figures and notes on methodological developments and ending with application notes in synthesis. While XEC is becoming an increasingly utilized approach in synthesis, its early stage of development means that optimal catalysts, ligands, additives, and reductants are still in flux. This review has collected data on these and various other aspects of the reactions to capture the state of the field. Finally, the data collected on the papers in this review is offered as Supporting Information for readers.

This dataset is associated with the paper 'Artificial Personality and Disfluency' by Mirjam Wester, Matthew Aylett, Marcus Tomalin and Rasmus Dall published at Interspeech 2015, Dresden. The focus of this paper is artificial voices with different personalities. Previous studies have shown links between an individual's use of disfluencies in their speech and their perceived personality. Here, filled pauses (uh and um) and discourse markers (like, you know, I mean) have been included in synthetic speech as a way of creating an artificial voice with different personalities. We discuss the automatic insertion of filled pauses and discourse markers (i.e., fillers) into otherwise fluent texts. The automatic system is compared to a ground truth of human ``acted' filler insertion. Perceived personality (as defined by the big five personality dimensions) of the synthetic speech is assessed by means of a standardised questionnaire. Synthesis without fillers is compared to synthesis with either spontaneous or synthetic fillers. Our findings explore how the inclusion of disfluencies influences the way in which subjects rate the perceived personality of an artificial voice.

This dataset contain ventilation ages calculated using the transit time distribution (TTD) method (e.g., Waugh et al., 2004) on the GLODAPv2 data synthesis product (Olsen et al., 2016). Ventilation age is defined as the time elapsed since a water parcel was last in contact with the atmosphere. Our calculated ages are estimated from measured concentrations of the transient tracers sulphur hexafluoride (SF6), and the chlorofluorocarbons (CFCs) CFC-11 and CFC-12. For these TTD calculations we have assumed full (100%) saturation of the transient tracers when subducted, which will generate a bias toward older ages in especially dense water formation regions since it is known that the saturation there is frequently lower than 100%. We assume that the solution to the Greens function is an Inverse Gaussian (IG) function. Furthermore, we have assumed a balance between advection and mixing, i.e., unity ratio between the width and the mean age of the TTDs. This assumption is typically adopted in the global ocean (e.g., Waugh et al., 2006), although there is regional variability (e.g., Stöven and Tanhua, 2014; Rajasakaren et al., 2019). Thus, some care should be taken when utilising the calculated ages in certain regions. The main reason for the published dataset is to give a user-friendly product that can be applied in ocean studies where ventilation ages are of interest, both to give an appreciation of typical ages and gradients in the ocean, and to be adopted in studies calculating biogeochemical rates. A recent example of the latter is the updated calcium carbonate dissolution study by Sulpis et al. (2021), which used these data. All included data are listed and specified in the dataset description below, and most of them are identical to the values found in GLODAPv2 (Key et al., 2015; Olsen et al., 2016). The novel addition in this dataset are the ventilation ages. The files contain both the TTD-based mean ages that are calculated as described above, and, calculated tracer ages, which assumes no mixing and are simply derived by matching the observed tracer concentration to the atmospheric history. For the atmospheric history we used (Walker et al. (2000) and Bullister (2015)), updated to 2016 by extrapolating with the same atmospheric evolution rate as the year before. The dataset consists of files covering four regions, following the GLODAPv2 data synthesis product: the Arctic Mediterranean (ARC), The Atlantic Ocean (ATL), the Indian Ocean (IND), and the Pacific Ocean (PAC). The data are provided both in comma separated (.csv) format and in Matlab® format (.mat).

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Palmer Station (PAL) contains wind speed (mean) measurements in metersPerSecond units and were aggregated to a yearly timescale.

A palladium-catalyzed C–H bond functionalization of acrylamides was developed to build up stereoselectively trifluoromethylated 1,3-butadienes. Using a tertiary amide as a directing group, olefins were selectively functionalized with 2-bromo-3,3,3-trifluoropropene to access these important fluorinated compounds. The methodology was extended to the construction of pentafluoroethyl-substituted 1,3-dienes. Mechanistic studies supported by density functional theory calculations suggested a redox neutral mechanism for this transformation.

The objective was to identify innovative strategies that may increase recruitment and/or retention of groups less represented in chronic disease clinical research. A systematic review was conducted. Inclusion criteria were: (a) NIH-defined racial and ethnic minority groups and clinical research; (b) evidence-based, clinical research recruitment and/or retention strategies involving the leading causes of mortality and morbidity in the United States; (c) conducted in the United States; and (d) qualitative design. Data exploring the strategies were extracted and thematically analyzed. Twenty-seven studies were included. Studies focused on cancer (70%), recruitment (93%), and perspectives from clinicians (63%). The most referenced strategies were education (44%), communication (48%), and community-based participatory research (63%). Critical themes include empowerment, transparency, trust, and sustainability. Strategies must prioritize the community and be implemented sustainably, where cultural humility and community-based participatory research are foundational. Methods We adhered to and adapted the Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ) guidelines, Enhancing the Quality and Transparency of Health Research (EQUATOR) guidelines, and The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist to report this completed systematic review and meta-synthesis. Eligibility criteria Briefly, we included studies with qualitative or mixed methods research designs, were conducted in the U.S., published in English or Spanish in a peer-reviewed journal between 2009 and 2024, and that demonstrated evidence-based recruitment and/or retention strategies for clinical research focused on the leading causes of morbidity and mortality in the U.S. as determined by the Centers for Disease Control and Prevention (CDC). Studies spanning ten years from 2009 were initially selected; this was later updated to include fifteen years from 2009 to reflect the increasing significance and importance of this work during this period. Eligible studies targeted ethnic and racial minorities defined by the NIH. Studies included all ages and used the NIH definition of clinical research. Information sources and search strategy The literature search strategy was developed in collaboration with the review team and trained biomedical librarians (NT and AL) at the National Institutes of Health (NIH). The search strategy was created using a combination of text words and the controlled vocabulary terms in the following databases: (PubMed (MeSH) Medical Subject Headings, Embase - EMTREE, and CINAHL subject headings. The search was refined using an iterative process and finalized by the review team members and librarians. For each search strategy, the search terms included these text words and controlled vocabulary when available: underrepresented, minority, racial and ethnic groups, clinical research, and disparities. The following databases were searched: PubMed (National Library of Medicine), Embase (Elsevier), CINAHL Plus (Cumulative Index to Nursing and Allied Health Literature - EBSCOhost), and Web of Science Core Collection (Clarivate Analytics). The following limits were applied using the filters available in each database. The search was limited to human studies only and was limited to studies conducted in the United States. The final search strategy can be found in the S2 Appendix. Selection process Covidence systematic review software (Veritas Health Innovation, Melbourne, Australia; www.covidence.org) imported studies and automatically excluded duplicates. All stages of the screening, data extraction, and quality assessment were independently conducted by members of the review team (CJP, JMG, AK, MW, LA, and JGG). The review team was composed of six members. The review team first screened titles and abstracts to identify studies that met the inclusion criteria. Next, the full texts of studies included during the title and abstract were screened using the same eligibility criteria. Each article was screened by two reviewers and conflicts between reviewers were resolved by consensus discussion with the review team. Data collection process & data items Data from each included study were collected by two reviewers using Covidence. The following outcomes of interest were extracted: focus on recruitment, retention, or both; and a description of the evidence-based strategies. We extracted data on study characteristics, including year of publication and condition of interest, including subtype for cancer. Additionally, we extracted characteristics including race and ethnicity, sex assigned at birth if applicable, geography (urban or rural), and role in clinical research (e.g., participant, clinician (i.e., medical or research staff), community leader, etc.). Study risk of bias assessment For the quality assessment, we evaluated the following domains: (a) role of the researcher; (b) sampling method; (c) data collection method; and (d) analysis method, which were identified as all criteria met or criteria partially met. We followed the adapted guidelines and conceptual domains of the Critical Appraisal Skills Programme (CASP) quality assessment tool to assess the quality of studies. Two reviewers assessed the risk of bias for each included study and resolved disagreements by consensus discussion with the review team. Synthesis methods A thematic synthesis was operationalized for the data analysis, where we analyzed the findings and developed inductive and deductive codes using qualitative synthesis methodologies and established guidelines. The thematic synthesis utilized an iterative process grounded in qualitative thematic analysis methodologies. We initially developed a deductive coding scheme, focusing on direct meaning and content that highlighted evidence-based strategies and direct quotations from study participants. The team discussed and created the codebook, and then each code was defined. Discrepancies or additional deductive codes were added and discussed by the team for consensus. Each study was coded independently by reviewers. Inductive codes were later added to describe high-level interpretation and themes. Both deductive and inductive codes existed in our codebook using this iterative process. Further analysis was conducted where strategies and themes were summarized into a conceptual model emphasizing key elements for the recruitment and retention of racial and ethnic groups historically underrepresented in clinical research.

The human auditory system extracts meaning from the environment by transforming acoustic input signals into semantic categories. Specific acoustic features give rise to distinct categorical percepts, such as speech or music, and to spatially distinct preferential responses in the auditory cortex. These responses contain category-relevant information, yet their representational level and role within the acoustic-to-semantic transformation process remain unclear. We combined neuroimaging, a deep neural network, a brain-based sound synthesis, and psychophysics to identify the sound features that are internally represented in the speech- and music-selective human auditory cortex and test their functional role in sound categorization. We found that the synthetized sounds exhibit unnatural features distinct from those normally associated with speech and music, yet they elicit categorical cortical and behavioral responses resembling those of natural speech and music. Our findings provide new insights into the fundamental sound features underlying speech and music categorization in the human auditory cortex.

seed desiccation response 1 means desiccation-tolerant, 0 means desiccation-sensitive, blanks mean lack of information.

growth form 1 means woody, and 0 means herbaceous.

fruit type 1 means fleshy, 0 means dry, blanks mean lack of information.

nondormant 1 means nondormant, 0 means dormant, blanks mean lack of information.

physical dormant 1 means physical dormant, 0 means non physical dormant, blanks mean lack of information.

other dormant 1 means other dormant (include physiological dormancy, morphological dormancy and morphophysiological dormancy), 0 means nondormant or physical dormant, blanks mean lack of information.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities.

Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office.

The following dataset from Sevilleta (SEV) contains wind speed (mean) measurements in metersPerSecond units and were aggregated to a monthly timescale.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Palmer Station (PAL) contains air temperature (mean maximum ) measurements in celsius units and were aggregated to a monthly timescale.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities.

Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office.

The following dataset from Grassland Soil and Water Research Laboratory (GSW) contains wind speed (mean) measurements in metersPerSecond units and were aggregated to a monthly timescale.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities.

Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office.

The following dataset from Virginia Coast Reserve (VCR) contains wind speed (mean) measurements in metersPerSecond units and were aggregated to a yearly timescale.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities.

Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office.

The following dataset from Hubbard Brook (HBR) contains wind speed (mean) measurements in metersPerSecond units and were aggregated to a yearly timescale.

Zeolites are a diverse class of crystalline microporous materials of, mainly, aluminosilicate chemical composition. Organic structure-directing agents (OSDAs) are generally utilized in zeolite synthesis to drive the outcome to a specific zeolite phase. In addition to OSDA, the presence and content of aluminum in the gel play a role in driving the synthesis under specific conditions. The structure-directing role of aluminum as well as fluoride in zeolite synthesis was explored through the analysis of three recently synthesized aluminosilicate zeolites, PST-21 (PWO), PST-22 (PWW), and ERS-7 (ESV), using a force field simulation approach. An updated and recently proposed method based on the calculation of “synthesis energy” is used to predict the stability of zeolites at pure-silica and aluminosilicate gel compositions, also able to include fluoride anions as well as OSDAs, and hence largely general. The results are not only demonstrating that the calculated structures with lowest “synthesis energy” correspond to those experimentally obtained under “standard” (meaning HF/SDA = 1) synthesis conditions but also that new structures obtained under the recently introduced “excess fluoride approach” are those which follow with energy slightly larger than the lowest, as calculated from the list of competing zeolites. With this method, we were able to rationalize the structure-directing effect of aluminum, in the presence of fluoride and OSDAs, in the synthesis of zeolites.

The development of models that accurately predict the formation of eutectic mixtures (EMs, including the well-known deep eutectic solvents) and their viscosity is imperative to save time in synthesizing new solvents. We developed reliable machine-learning-based classifiers able to discern between eutectic and noneutectic (non-EM) mixtures and regressors able to predict the viscosity of an EM. A new experimental data set of 219 EMs, 384 non-EMs, and 1450 viscosity points at different temperatures and water contents is provided and used to challenge several models, defined both by an algorithm and by descriptors. The top-performing EM/non-EM classifier yields an accuracy of 92%, and the best regressor achieves viscosity predictions with a mean absolute error of 2.2 mPa·s; the extrapolation capabilities of the latter were assessed on additional measurements at temperatures and water contents outside the range of the training data set, revealing good accuracy at low viscosities. The SHapley Additive exPlanations (SHAP) algorithm was employed in several models as an eXplainable Artificial Intelligence (XAI) technique to quantify input feature contributions to the model output. These results represent a significant step forward in developing robust and highly accurate models for determining eutectic mixtures and their viscosity.

The LGM Tropical Terrestrial Data Synthesis (Farrera et al., 1999) contains quantitative reconstructions of mean temperature of the coldest month (MTCO) and mean annual ground temperature (MAT), and qualitative reconstructions of plant-available moisture (PAM) and runoff (equivalent to precipitation minus evaptranspiration, P-E) from radiocarbon-dated terrestrial sites between 32° N and 33° S with records for the last glacial maximum (defined as 18,000±1000 yr B.P. on the radiocarbon time scale, equivalent to 21,000 yr B.P. on the calendar time scale). The data set was explicitly compiled to provide an evaluation data set for LGM simulations. The dataset combines multiple indicators of quantitative changes in land surface temperature (pollen and plant macrofossil records of mean temperature of the coldest month = MTCO, and noble gas and speleothem records of mean annual temperature = MAT) and qualitative indicators of moisture balance parameters (pollen and plant macrofossil records of PAM and lake status records of P-E). The use of multiple indicators allows the consistency of the temperature and moisture balance reconstructions to be evaluated. The original publication lists all tropical sites with climate estimates - many of these sites were unsuitable for making quantitative reconstructions or were extremely poorly dated, and so do not appear on the maps. The complete list of sites is available on request.

 The LGM Tropical Terrestrial Data Synthesis has records for 85 sites with
 records of PAM, 42 sites with records of P-E, 64 sites with record for
 temperature at the site elevation, and 34 sites with records of temperature
 reduced to sea level.

A new method for the synthesis of multiarylanthracenes was developed by means of the RuH2(CO)(PPh3)3-catalyzed arylation of anthraquinone with arylboronates. This method consists of short and straightforward sequences starting with an easily accessible anthraquinone and is applicable to the syntheses of various multiarylanthracenes including those bearing twisted backbones.

An ensemble of forecasts generated by different model simulations provides rich information for meteorologists about impending weather such as precipitating clouds. One major form of forecasts presents cloud images created by multiple ensemble members. Common features identified from these images are often used as the consensus prediction of the entire ensemble, while the variation among the images indicates forecast uncertainty. However, the large number of images and the possibly tremendous extent of dissimilarity between them pose cognitive challenges for decision making. In this article, we develop novel methods for summarizing an ensemble of forecasts represented by cloud images and call them collectively the Geometry-Sensitive Ensemble Mean (GEM) toolkit. Conventional pixel-wise or feature-based averaging either loses interesting geometry information or focuses narrowly on some pre-chosen characteristics of the clouds to be forecasted. In GEM, we represent a cloud simulation by a Gaussian mixture model, which captures cloud shapes effectively without making special assumptions. Furthermore, using a state-of-the-art optimization algorithm, we compute the Wasserstein barycenter for a set of distributional entities, which can be considered as the consensus mean or centroid under the Wasserstein metric. Experimental results on two sets of ensemble simulated images are provided. Supplemental materials for the article are available online.

IntroductionFoundational to a well-functioning health system is a strong routine health information system (RHIS) that informs decisions and actions at all levels of the health system. In the context of decentralization across low- and middle-income countries, RHIS has the promise of supporting sub-national health staff to take data-informed actions to improve health system performance. However, there is wide variation in how “RHIS data use” is defined and measured in the literature, impeding the development and evaluation of interventions that effectively promote RHIS data use.MethodsAn integrative review methodology was used to: (1) synthesize the state of the literature on how RHIS data use in low- and middle-income countries is conceptualized and measured; (2) propose a refined RHIS data use framework and develop a common definition for RHIS data use; and (3) propose improved approaches to measure RHIS data use. Four electronic databases were searched for peer-reviewed articles published between 2009 and 2021 investigating RHIS data use.ResultsA total of 45 articles, including 24 articles measuring RHIS data use, met the inclusion criteria. Less than half of included articles (42%) explicitly defined RHIS data use. There were differences across the literature whether RHIS data tasks such as data analysis preceded or were a part of RHIS data use; there was broad consensus that data-informed decisions and actions were essential steps within the RHIS data use process. Based on the synthesis, the Performance of Routine Information System Management (PRISM) framework was refined to specify the steps of the RHIS data use process.ConclusionConceptualizing RHIS data use as a process that includes data-informed actions emphasizes the importance of actions in improving health system performance. Future studies and implementation strategies should be designed with consideration for the different support needs for each step of the RHIS data use process.