Doherty, Jean-François · Bhattarai, Upendra · Ferreira, Sara · et al.
Abstract Almost every animal trait is strongly associated with parasitic infection or the potential exposure to parasites. Despite this importance, one of the greatest challenges that researchers still face is to accurately determine the status and severity of the endoparasitic infection without killing and dissecting the host. Thus, the precise detection of infection with minimal handling of the individual will improve experimental designs in live animal research. Here, we quantified extracellular DNA from two species of endoparasitic worm that grow within the host body cavity, hairworms (phylum Nematomorpha) and mermithids (phylum Nematoda), from the frass of their insect host, a cave wētā (Orthoptera: Rhaphidophoridae) and an earwig (Dermaptera: Forficulidae), respectively. Frass collection was done at two successive time periods, to test if parasitic growth correlated with relative DNA quantity in the frass. We developed and optimised two highly specific TaqMan assays, one for each parasite-specific DNA amplification. We were able to detect infection prevalence with 100 % accuracy in individuals identified as infected through post-study dissections. An additional infection in earwigs was detected with the TaqMan assay alone, likely because some worms were either too small or degraded to observe during dissection. No difference in DNA quantity was detected between sampling periods, although future protocols could be refined to support such a trend. This study demonstrates that a non-invasive and minimally stressful method can be used to detect endoparasitic infection with greater accuracy than dissection alone, helping improve protocols for live animal studies.
Ornelas, Francisco-Javier · de la Torre, Chris · Nweke, Chukwuebuka · et al.
The State of California has multiple sites with vertical arrays consisting of surface and downhole sensors, which are used to investigate shallow site response under earthquake excitations. Characterization of these sites typically includes a boring log and seismic velocity profiles (Vs and Vp). We augment the site characterization using microtremor Horizontal-to-Vertical-Spectral-Ratios (mHVSR), where the ground vibrations are caused for example by wind, ocean waves, and anthropogenic sources. This information is useful to identify potential site resonances, which in some cases may be associated with impedance contrasts at depths beyond the limits of the array, and the consistency of the geology when multiple mHVSR are evaluated at different locations relative to the vertical array. Collaborative research between the University of California, Los Angeles (UCLA), University of Southern California (USC), and the University of Canterbury in New Zealand has performed mHVSR at 16 vertical array sites in California. At each site, 4 tests were performed in 4 concentric circles of increasing diameter to better understand the spatial and azimuthal variation of mHVSR for each of the 16 sites. The HVSR curves developed using this dataset may be accessed in the United States Community Shear-Wave Velocity (VS) Profile Database (PDB) (https://uclageo.com/VPDB/). This work was supported by Pacific Gas and Electric Company, Viterbi School of Engineering, University of Southern California Faculty Award, United States Geological Survey (USGS) EHP G23AP00066-00 Award 2023-0106, New Zealand Earthquake Commission(EQC) and QuakeCoRE. The microtremor Horizontal-to-Vertical spectral ratio (mHVSR) method provides frequency-dependent ratios of Fourier amplitude spectra (FAS) for the horizontal to vertical components of a 3-component recording of ambient ground motions (typically velocities) from microtremors. This method can identify the frequencies associated with site resonances at sites with large impedance contrasts, and hence has potential to provide useful parameters for predicting seismic site response. The mHVSR method is applied by recording ground vibrations either from a temporarily-deployed seismometer, typically recording for a relatively short period of time (~1-2 hrs.), or from a permanently-installed broadband seismometer. It is also useful for studying the spatial, temporal, and azimuthal variation of ground vibrations at sites. The overall goals of our HVSR research are to develop a publicly accessible database of HVSR data for use in research, to develop effective protocols for analysis and interpretation of HVSR data, and to develop methods for predicting site response conditioned on HVSR data. The database has been established and is available in the United States Community Shear-Wave Velocity (VS) Profile Database (PDB) (https://uclageo.com/VPDB/); the work presented in this doi is contributing to that database.
Ornelas, Francisco-Javier · Stapleton, John · Brandenberg, Scott · et al.
The UCLA campus is situated near the Santa Monica Mountains in West Los Angeles (LA), just outside the LA Basin, which is a large sedimentary basin formed around the Cretaceous period. The geology of the campus itself consists of primarily younger alluvial deposits overlying bedrock, which formed around the late quaternary period. In an effort to better understand amplification of earthquake ground motions at the site, microtremor Horizontal-to-Vertical-Spectral-Ratios(mHVSR) surveys were performed. The information that these surveys provide can give us insight on site resonances which are anticipated to be significant due to large impedance contrasts. Moreover, we can better understand the geology when multiple surveys are evaluated at different areas around the site. The University of California, Los Angeles (UCLA) has performed mHVSR surveys at 14 sites on the campus, primarily in areas near ground motion recording stations. The HVSR curves developed using this dataset may be accessed in the United States Community Shear-Wave Velocity (VS) Profile Database (PDB) (https://vspdb.org) This work was supported by a donation from Pacific Gas and Electric. The microtremor Horizontal-to-Vertical spectral ratio (mHVSR) method provides frequency-dependent ratios of Fourier amplitude spectra (FAS) for the horizontal to vertical components of a 3-component recording of ambient ground motions (typically velocities) from microtremors. This method can identify the frequencies associated with site resonances at sites with large impedance contrasts, and hence has potential to provide useful parameters for predicting seismic site response. The mHVSR method is applied by recording ground vibrations either from a temporarily-deployed seismometer, typically recording for a relatively short period of time (~1-2 hrs.), or from a permanently-installed broadband seismometer. It is also useful for studying the spatial, temporal, and azimuthal variation of ground vibrations at sites. The overall goals of our HVSR research are to develop a publicly accessible database of HVSR data for use in research, to develop effective protocols for analysis and interpretation of HVSR data, and to develop methods for predicting site response conditioned on HVSR data. The database has been established and is available in the United States Community Shear-Wave Velocity (VS) Profile Database (PDB) (https://uclageo.com/VPDB/); the work presented in this doi is contributing to that database.
Replication package for 'The US Imbalance Residual: Decomposing What the Demographic Frame Doesn't Capture' by Brian Peters (2026). Documents that the US runs 5-9 percentage points of GDP below the income-conditioned demographic baseline across four orthogonal margins — current account, cyclically-adjusted fiscal balance, gross national savings, and investment-income balance — persistently from 2000 onwards. Tests two cross-country mechanism candidates: the inequality channel of Auclert et al. (2021), proxied by WDI top-10 income share (β(Z₁ × top10_share) = -0.049, p = 0.44), and the funded-vs-PAYG pension regime, proxied by pension spending/GDP (β(Z₁ × pension_spending_gdp) = +0.006, p = 0.93). Both are null. Four further mechanisms — reserve-currency status, financial-system depth, immigration-adjusted demography, and political-economy fiscal regime — are inherently descriptive on a sample of one and cannot be identified from cross-country variation. The post-COVID widening of the US current-account deficit (Δ = -1.83 pp/GDP, 2019→2024) is largely non-demographic (predicted Δ = -0.27 pp; residual Δ = -1.56 pp). Creditor asymmetry confirmed: aging × NFA on income balance for debtors = +0.43** vs creditors = -1.60***. Companion to Paper 36 (Sex Composition) as a credibility play on framework limits and extensions.
Chavez, Daniel Eduardo · Burchett, Molly R. · Murtha, Brian
The folder contains data for four studies. Studies 2a, 2b, and 2c, are scenario based experiments. The files to comply with JM's data transparency policy are included in this submission. Study 1 uses proprietary data covered by a Non-Disclosure Agreement with the collaborating firm. Therefore, we propose an alternative disclosure plan that is in keeping with the spirit of replicability while respecting the specific situation.
Historic company records. Created annually from Infogroup’s U.S. Business Database; a snapshot of the data is saved each December. Contains company name, mailing address, SIC and NAICS codes, employee size, sales volume, latitude/longitude, and many more variables about each company. Geo-coding started in 2003. Records from earlier versions of the database were roughly geo-coded based upon addresses within the current Infogroup Business Database, and not all records were able to be coded. DATA AVAILABLE FOR YEARS: 1997-2024
Thompson, Peter · Bjordal, Meg · Piczak, Morgan · et al.
Abstract Gaps in biodiversity protection occur in Canada due to limited jurisdiction of federal species-at-risk laws and the absence of dedicated legislation in many provinces, including British Columbia (B.C.). While lacking legal protection, B.C. maintains Red, Blue, and Yellow Lists of threatened, special-concern, and secure species, respectively, using a NatureServe ranking system. We compiled historical data on species status between 2008 and 2025 from the B.C. Conservation Data Centre. The province is currently home to 5,521 Yellow, 1,233 Blue, 493 Red-listed species, with a 25 % rise in species at risk (Blue and Red) since 2008 due largely to the addition of species. Changes in status over this time period were reported for 1,545 animal and 3,775 plant species. While there was an even split in uplistings (more imperiled) and downlistings (less imperiled) for animals, plant species more often shifted to a lower risk category. Analysing explanations for each change revealed that most were non-genuine (new information or methodology) rather than genuine (true changes in population size or threats), especially among downlistings. Genuine improvements in the status of species in B.C. have been exceedingly rare, indicating that current laws and regulations have been insufficient to recover species at risk within B.C.
Owens, Alasdair F. · Estrada, Erik · Hockings, Kimberley J. · et al.
Abstract Understanding the fundamental ecology of endangered species is essential for effective conservation, yet this remains challenging for elusive species inhabiting tropical forests. For the endangered Bornean white-bearded gibbon (Hylobates albibarbis), much of the available ecological information derives from peat swamp forests, while comparatively little is known from other forest types that make up a large part of its range. Passive acoustic monitoring provides an opportunity to address this gap, enabling the study of species’ vocal behaviour over larger spatial and temporal scales than previously possible. We deployed eight autonomous recording units across three forest types in Central Kalimantan, Indonesia, collecting 23,244 hours of acoustic data over 18 months. A pretrained deep learning detector was applied to identify great calls, performed by female gibbons as part of morning duets and used as a key indicator for comparing population density. We identified 83,956 great calls and examined how daily calling activity varied across habitats and in response to seasonal rainfall. Daily calling activity differed significantly among forest types, consistent with expected differences in gibbon population density. Significant temporal variation in calling behaviour was observed consistently across habitats. We documented negative short-term and positive long-term effects of rainfall on calling activity. Daily calling activity peaked 51-52 days following rainfall events, with effect sizes increasing with rainfall dose, suggesting that calling activity reflects a lagged phenological fruiting response to seasonal rainfall. Our findings highlight the importance of accounting for variable vocalisation rates in acoustic monitoring, particularly when evaluating the additive effects of anthropogenic disturbance and climate change on species behaviour and ecology. We emphasise the value of incorporating spatial data to strengthen ecological inferences from acoustic datasets, and demonstrate the power of deep learning for long-term monitoring of species’ vocal behaviour, providing deeper ecological understanding across increasingly broad spatiotemporal scales. Methods Eight autonomous recording units (ARUs) were deployed across three forest types (lowland heath, low pole, and mixed swamp) in the Mungku Baru Education and Research Forest, Central Kalimantan, Indonesia, from July 2018 to December 2019. The ARUs recorded each day continuously, saving audio as 1-hour waveform audio files (WAV). To ensure full coverage of morning gibbon duets, recordings between 04:00 and 10:00 were selected, and only days with no missing data were included, leaving 23,244 hours of audio. We then applied a pretrained deep learning automated detector, described in Owens et al. (2024), which identified 83,596 H. albibarbis great calls. These are listed in "detector_output.csv", along with associated spatiotemporal data. These detections were aggregated to estimate the number of great calls per day at each ARU (daily call rate), and whether or not a great call was detected on a given day at each ARU (daily call presence). Daily call rate and daily call presence are presented in "daily_data.csv", along with associated spatiotemporal data. To estimate daily rainfall accumulations for our study site we used the PERSIANN-CDR V3 dataset (Ashouri et al., 2015), downloaded via the CHRS data portal (Center for Hydrometeorology and Remote Sensing, University of California, Irvine). Daily rainfall data is presented in "daily_rainfall.csv". To assess detector performance, subsets of the detections were manually validated to test if precision and recall varied across conditions. Information regarding these subsets is presented in "precision_validation.csv" and "recall_validation.csv". All statistical analyses were conducted in R (R Core Team, 2023). The analysis pipeline for evaluating detector precision and recall can be reproduced using the provided script, "detector_validation.R". The analysis pipeline for assessing the timing of detected calls, and the effect of habitat and rainfall on great call rate and presence can be reproduced using the provided script, "call_analysis.R". Ashouri, H., Hsu, K.-L., Sorooshian, S., Braithwaite, D. K., Knapp, K. R., Cecil, L. D., Nelson, B. R., & Prat, O. P. (2015). PERSIANN-CDR: Daily precipitation climate data record from multisatellite observations for hydrological and climate studies. Bulletin of the American Meteorological Society, 96(1), 69–83. https://doi.org/10.1175/BAMS-D-13- 00068.1 Center for Hydrometeorology and Remote Sensing (CHRS). (n.d.). PERSIANN-CDR V3 Daily Precipitation Data [Data set]. University of California, Irvine. Retrieved April 1, 2026 from https://chrsdata.eng.uci.edu/ Owens, A. F., Hockings, K. J., Imron, M. A., Madhusudhana, S., Mariaty, Setia, T. M., Sharma, M., Maimunah, S., Van Veen, F. J. F., & Erb, W. M. (2024). Automated detection of Bornean white-bearded gibbon (Hylobates albibarbis) vocalizations using an open-source framework for deep learning. Journal of the Acoustical Society of America, 156(3), 1623–1632. https://doi.org/10.1121/10.0028268
I provide the replication data in the form of (social) media data for these two projects. Interview data cannot be shared due to confidentialty agreements in place.
Abstract Introduction Many newly qualified doctors struggle to cope with the challenging transition to internship, raising a concern over whether they are adequately prepared with the competencies they need for legitimate practice. This study aimed to explore the reality of the internship role, the types of competencies that form the basis of achievement in this context, and the perceived readiness of newly qualified doctors to demonstrate these competencies. Methods A qualitative study, using focused ethnography, was undertaken in a regional public hospital in Johannesburg. 15 first year internship doctors volunteered to take part. Data was gathered over a seven-week period through participant observation and shadowing and informal conversations. Semi-structured interviews were recorded with 13 of the participants to further explore emerging themes. The data were analysed using a reflective thematic analysis with additional analysis using the Legitimation Code Theory (LCT) specialisation dimension coding framework. Results Interns are the ‘engine room’ of the hospital, facing long hours and the responsibility for a high workload. Some interns cope well, while others become overwhelmed, negatively impacting their wellbeing. Competency in teamwork, organization, efficiency, and communication provides the basis for legitimate practice, all attributes not highly valued by the undergraduate curriculum. Discussion To thrive, newly qualified doctors need to demonstrate both confidence in their clinical knowledge and skills as well as the attributes that form the basis of achievement in internship. To achieve this we need holistic competency based medical education that meaningfully values the personal and social competencies that are critical for legitimate practice. Datafiles Title - Format - Description Observation 1-64 - Microsoft Word Files (x64) - Pseudonymised Field Notes Participant 1-13 - Microsoft Word Files (x13) - Pseudonymised Interview Transcripts
Abstract Introduction The transition from student to doctor represents a challenging shift in identity and responsibility that many graduates find difficult to manage. To understand better how to support the transition to practice we need an exploration of graduates' experiences that does not see the transition as a single moment, but a continuous learning process. This study aimed to explore how medical students negotiate legitimate participation and professional identity formation (PIF) through time as they transitioned to internship in South Africa. Methods We conducted longitudinal qualitative research using audio-diaries and semi-structured interviews to collect data from students over 7 months as they transitioned from medical school to several different health care institutions for internship. 22 students took part in entrance interviews, 20 collected audio-diaries and 17 took part in exit interviews. Data were analysed using a narrative analysis approach, using communities of practice (CoP) theory as a sensitising–analytic framework. Results We identified four dominant narrative plotlines in our data, revealing how legitimacy and PIF are constantly renegotiated through time. PIF faltered in medical school when students were excluded from hierarchical clinical teams, on graduation when they began to doubt their preparedness and in internship when participants were unable to demonstrate the competencies valued by CoPs within the demanding South African health care system. Professional identity was built when participants perceived themselves as being valued through their meaningful contributions to the shared enterprise of the CoP. Discussion We call for a change in our framing of preparedness from ‘preparedness for practice’ to ‘preparedness for transition’, shifting our conceptualisation of preparedness towards equipping students with the resources they need for a complex, contextual, ongoing process rather than a moment in time. This requires clinical learning environments that legitimise trainees as peripheral participants, where learning is orientated towards gaining experience, cultivating professional identity and supporting individuals in developing the confidence, adaptability and resilience that will allow them to thrive as they negotiate the ongoing transition from student to doctor. Data Files Title - Format - Description Participants 1-17 - Microsoft Word File (x17) - Pseudonymised Transcripts: Each transcript includes entrance interview, audio-diary entries and exit interview.
Abstract Despite demonstrating the required competencies to graduate, many newly qualified doctors find the transition to internship difficult. There is a concern over whether their preparation is aligned with the expectations of the role. This study aimed to gain a better understanding of the competencies needed for legitimate practice as junior doctors and explores their perceived preparedness for practice. A qualitative, descriptive study using focus groups was undertaken with first year internship doctors. Thirty-two junior doctors in their first year of internship took part in five focus groups. The data were analysed using a reflective thematic analysis approach with a subsequent analysis using the Legitima¬tion Code Theory (LCT) specialisation dimension coding framework to aid interpretation. Personal attributes including adaptability, organisation and proactivity form the basis of achievement in internship. While graduates felt ready in some ways, it was not in the ways that counted. Participants felt well prepared in terms of their clinical knowledge and skills, but legitimacy came from being able to take responsibility, communicate effectively and apply knowledge confidently and efficiently to all aspects of patient care, something that they did not feel ready to do. Using LCT has revealed a shift in the basis of achievement between medical school, where individual academic performance is rewarded, and intern¬ship, where personal and social competencies are legitimised. There is a clash between what graduates feel well prepared for and the expectations and demands of the internship role, resulting in a difficult and stressful transition from student to doctor. Data Files All documents described below are Microsoft Word files . Title - Description: Document 1 - Pseudonymised Transcript Focus Group 1 Document 2 - Pseudonymised Transcript Focus Group 2 Document 3 - Pseudonymised Transcript Focus Group 3 Document 4 - Pseudonymised Transcript Focus Group 4 Document 5 - Pseudonymised Transcript Focus Group 5
Abstract Purpose Many medical graduates are entering practice not ready in the ways that count. The prevailing explanation is a lack of opportunity for clinical experience, but this rationale is insufficient in resource constrained, high-volume clinical training contexts. What is legitimised will ultimately shape what is learned. This study aimed to explore what forms of knowledge, participation, and ways of being are legitimised within a medical curriculum in South Africa. Method We conducted explanatory, instrumental case study research using multiple sources of data from one medical school in South Africa. 21 Final-year medical students took part in four focus groups, 12 clinical training coordinators took part in semi-structured interviews and 20 documents conveying expectations to final-year medical students were collected from the online learning management system between March and August 2025. Data were analysed using thematic analysis, using Legitimation Code Theory (LCT) as a theoretical framework. Results Three key themes were identified: (1) medical school aspires to ready graduates with the holistic range of competencies required in practice (2) structural constraints privilege performance in assessments over participation and (3) both students and clinical teachers experience delegitimization in the clinical training environment. There is a misalignment between intended outcomes, where both knowledge and ways of being are valued, and an enacted and experienced legitimacy, where achievement is defined through performance in high-stakes assessments. This shift privileges ‘what you know’ while devaluing ‘who you are,’ resulting in the marginalisation of the competencies required for a successful transition to practice. Conclusion Clinical exposure is not enough to ensure students gain the experience they need to be prepared for practice, what is legitimised will determine whether intended learning takes place. Curriculum innovation and culture change aimed towards legitimising student participation and professional development can allow for the potential of clinical training environments to be realised. Data Files Title - Format - Description Focus Group 1-4 - Microsoft Word File (x4) - Pseudonymised Transcript Focus Groups 1-4 Participant 1-12 - Microsoft Word File (x12) - Pseudonymised Transcript Interviews 1-12 Document 1-13 - PDF (x13) - Anonymised LMS Document 1-13 Document 14-20 - Microsoft Word File (x7) - Anonymised LMS Document 14-20
Kollmann, Jelena · Hollaar, Malin H.L. · Servant-Miklos, Virginie F.C. · et al.
Dataset Description This dataset gives general information of the study and the codes used in coding the qualitative interviews. Background COVID-19 had an impact on youth health. To mitigate the impact of COVID-19 on youth health, resilience was essential. However, it is unclear how resilient different groups of youth were during COVID-19, and what helped them be resilient and what hindered them. Purpose This study aims to get insight into how pre-vocational secondary school and university students experienced resilience during the pandemic and what risk and protective factors could be targeted during crisis. Methods ● Data Collection - Type of data: qualitative data. - Dates collected: 2020-2022. - Method: secondary analysis on qualitative interviews. - Location: Rotterdam, the Netherlands. - Number of participants: 18. ● Participants There were two groups of students studied. The first group consisted of 8 participants who were pre-vocational secondary school students. Most of the pre-vocational students’ parents held low-income jobs. They were on average 16 years old (range 12-24). More than half had parents with a migrant background (63%), although most were born in the Netherlands, and less than half were female (38%). The second group were 10 university students. Most of these participants had parents with high-income jobs, the participants themselves often had side-jobs, and some lived alone and independently. They were on average 24 years old (range 21-29), and most were born in the Netherlands (80%). Half of the participants had parents with a migrant background or were born abroad (50%), and more than half were female (60%). ● Interview Procedure For the first dataset, interviews were conducted in person and online. The interviews were 30-45 minutes long. They were conducted in the language of choice of the pre-vocational students, which was mostly Dutch and for some English. Parents of the pre-vocational students signed an informed consent form, and verbal informed consent was asked of the pre-vocational students before the interviews commenced. The interview guide was semi-structured. Questions about high school and going to university were asked. For anonymity we used audio recordings only, then transcribed them using pseudonyms to identify the transcripts. Any names or places mentioned in the transcripts were edited or changed. No data saturation was sought, as the main aim of these interviews was to explore the experiences and perceptions of pre-vocational education students. No member check, i.e. checking the transcribed text with the interviewees, was performed due to the lockdown immediately after the interviews. For the second dataset, interviews were conducted online for approximately an hour per interview. The interview guide included the topics COVID-19, preventive behavior and lifestyle. Data saturation was reached around interview 7, after which three more interviews were conducted. A member check was done after transcription of the interviews for credibility of the data. For both datasets, questions have been posed open-endedly and neutrally to avoid bias as much as possible. Interviews were audio recorded and transcribed, and pseudonyms were used for anonymity. The reason why two different protocols are being described is the fact that these two datasets originated from two different studies. However, to get insight into the disruptions during the pandemic, cross-over discussions between the researchers resulted in a post-hoc decision to compare the datasets instead of keeping them as distinct studies. Comparability is ensured by using a social constructivist epistemology with a thematic analysis approach. This ensures that the same deductive themes are being used in both datasets with a focus on their perceived resilience, protective and risk factors. ● Ethics The participants gave consent for their data to be used for scientific purposes. Ethics approval has been obtained for this study from the department of Ethics of the Erasmus School of Social and Behavioural Sciences under reference number #ETH2324-0333. ● Anonymization Names of participants were anonymized, then the anonymized names were replaced by "Participant 1", "Participant 2" etc. for the scientific publication. ● Analysis All qualitative interviews were analyzed by means of a thematic analysis using Atlas.ti (v23). Author JK created a codebook based on the topics resilience, COVID-19, and health. This was used to code the interviews deductively with pre-existing codes. Moreover, open coding was used to further develop the codebook based on the participants’ answers, coding the interviews inductively as well. This was used, because the COVID-19 situation was a novel situation, which might have led to themes that could not be predetermined in the codebook. Before coding all the interviews in this way, two coders coded three interviews independently (JK and MH). After each interview was coded, an ICA (intercoder agreement) was calculated. This is a measure used to calculate how similarly the coders interpret and use the codes to ensure validity and reproducibility. A discussion of the coding process ensued until consensus was reached. After the third interview was coded by both authors, a satisfactory ICA was reached of 0.64 (for the first dataset) and 0.52 (for the second dataset). The range of an ICA can be between -1 and 1, so these ICAs provide substantial intercoder agreement for secondary data analyses as such. Author JK proceeded to code the rest of the interviews by using the deductive codes of the codebook and adding new inductive codes based on the interview responses. To further enhance reliability, the coding process was thoroughly discussed with the research team. The coded interviews were then analyzed per theme. The researchers looked at the components of resilience, namely sense of mastery, sense of relatedness and emotional reactivity. They also looked at codes describing changes due to COVID-19, mental and physical health, and protective and risk factors. These codes were studied per participant and captured in an Excel file to create an overview and see where possible patterns varied between participants’ background characteristics and between the two groups. Data Structure / Contents This repository contains the qualitative code tree used during the analysis of the interview data, as well as a README file describing the study design, data collection procedures, and analytic approach. Value of the Data for Potential Reuse The shared materials provide transparency regarding the qualitative analytic process and coding procedures used in this study. They may support methodological understanding, facilitate reproducibility of the analytic approach, and assist other researchers conducting qualitative interview research on related topics. Conclusion Resilience seemed to be more process- and context-dependent rather than education or age-dependent. Policy makers should focus on creating supportive environments and systems to foster youth resilience. ● Limitations One of the limitations of this study is that the interview guides included questions about different themes, as they were conducted in different studies. However, using a clear code book and consulting with researchers that were experienced in resilience and behavioral theories, we were still able to effectively code the interviews and extract the information that we needed for this study. Another limitation is that the interviews of the two datasets took place at different times during the pandemic. However, they still took place during the pandemic around lockdowns and with restrictions, which provided the sought-after insight into how youth experienced the pandemic and how resilient they were during this time.
Blue Chip Financial Forecasts: Monthly surveys of professional economists at leading investment banks, financial firms and consulting firms on the future direction of key U.S. interest rates and other macroeconomic indicators. Forecasts cover each of the next six quarters for each variable such as the Federal Funds Rate, Prime Rate, 3-month LIBOR, and Treasury Bills. Forecasts for interest rates and the Federal Reserve's Major Currency Index represent averages for the quarter, while forecasts for Real GDP, GDP Price Index and Consumer Price Index are seasonally-adjusted annual rates of change. DATA AVAILABLE FOR YEARS: 1982-2026:Mar.
This is a replication dataset for the manuscript titled: "Integrated surveillance in Kilifi reveals continued SARS-CoV-2 circulation and immune escape of emerging JN.1 sub-lineages post pandemic This study reveals continued circulation of SARS-CoV-2 in the Kenyan population in waves across the year peaking between November 2024 and February 2026 in Kilifi. We performed pseudovirus neutralization assays against locally circulating lineages LF.7 and MV.1 and global lineages XEC.4, LP.8.1 and XFG which was predominant between November 2024 and March 2026.
This dataset contains the replication code for "Slow Disaster, Immediate Accountability: Evidence from Uruguay's 2023 Water Crisis." The analysis examines whether citizens hold governments accountable for the management of a slow-onset hydrological drought using a difference-in-differences design and LAPOP AmericasBarometer survey data for Uruguay (2021–2023).
Alexander, Courtney · Falk, Justin · Blackwell, Siera · et al.
Background Complex Regional Pain Syndrome (CRPS), formerly known as Reflex Sympathetic Dystrophy (RSD), is a rare chronic pain condition characterized by hyperalgesia and allodynia following trauma or nerve injury (Taylor et al., 2021; Shim et al., 2019). Due to its complex presentation and unclear etiology, diagnosis and treatment remain challenging, with limited consensus on optimal management strategies. (Refer to attached Literature Review document) Purpose This study evaluates current diagnostic criteria and therapeutic interventions for CRPS, with a focus on the effectiveness of early, graded exercise and commonly used rehabilitation approaches in improving patient outcomes. Study design: Retrospective Observational Cohort Study Methods: A retrospective chart review was conducted using physical therapy evaluations, re-evaluations, and treatment notes from patients diagnosed with CRPS between 2020–2025. Data collected included demographics, symptom profiles, diagnostic codes, treatment interventions, and CPT units. Common interventions included therapeutic exercise, graded motor imagery, neuromuscular electrical stimulation (NMES), and mobility training. The study aimed to identify symptom patterns and evaluate patient responses to treatment strategies based on disability profiles. Analysis Methods: Microsoft Excel and JASP Statistical analysis was performed using descriptive statistics using Microsoft Excel and JASP software. Results 45 patient charts reviewed; 41 patients met inclusion criteria (≥2 visits). Males/ Females = 8/33 Mean age: 43.3 +/- years Mean duration of care: 198.6 +/- days Mean number of visits: 4 +/- visits Mean number of comorbid diagnoses: 3 Pain Outcomes Females reported higher pain levels than males at baseline (3.44 vs. 1.09) and post-treatment (2.38 vs. 0.78). Females demonstrated greater pain reduction during treatment (−0.93) compared to males (−0.22). Upper extremity CRPS presented with higher initial pain levels than lower extremity CRPS. Pain decreased following treatment across all CRPS diagnoses. Summary Patients arrived in significant pain; however, they experienced a large and statistically meaningful reduction during the session, and ended up at a much lower pain level. The re-evaluation pain scores appear consistent with end-of-session scores (no significant difference), suggesting the improvement holds at re-evaluation. (Refer to attached Poster) Conclusion Preliminary findings suggest that pain levels during physical therapy in patients with CRPS vary by biological sex and diagnosis. Females reported higher initial pain but demonstrated greater improvements during sessions. Patients with upper limb involvement also showed higher baseline pain and larger reductions compared to lower limb cases, indicating possible regional differences in treatment response. Pain decreased across all groups, supporting a multimodal rehabilitation approach (e.g., neuromuscular reeducation, desensitization, and therapeutic exercise). However, frequent symptom exacerbation highlights the need for individualized progression, patient education, and close symptom monitoring. Overall, results emphasize the importance of early, patient-centered, and function-focused physical therapy. Gradual progression and education may improve participation and outcomes, supporting conservative rehabilitation as an effective strategy for CRPS management. (Refer to Poster and Literature Review documents)
This dataset has been used for the study "Converting AI Capabilities into Sustainable Financial Performance: A Digital Entrepreneurship Capability Perspective in SaaS Startups". The study attempts to understand how digital entrepreneurship capability translates AI capabilities into sustainable financial performance in a hybrid SaaS and IT services startup. Adopting a qualitative case study methodology, the primary data for the study were collected through interviews, observations, and various organizational documents. The study argues that AI contributes to operational efficiency and data-driven decision-making. However, it significantly improves customer retention, recurring revenue stability, and financial resilience only if the company converts AI capabilities into digital innovation and scalable business opportunities. This dataset contains interview transcripts, coding, thematic analysis, and supporting evidence used to establish the relationship between AI capabilities, digital entrepreneurship capability, and sustainable financial performance.