Sam Harper

Abstract Background Establishing who is at risk from a novel rapidly arising cause of death, and why, requires a new approach to epidemiological research with very large datasets and timely data. Working on behalf of NHS England we therefore set out to deliver a secure and pseudonymised analytics platform inside the data centre of a major primary care electronic health records vendor establishing coverage across detailed primary care records for a substantial proportion of all patients in England. The following results are preliminary. Data sources Primary care electronic health records managed by the electronic health record vendor TPP, pseudonymously linked to patient-level data from the COVID-19 Patient Notification System (CPNS) for death of hospital inpatients with confirmed COVID-19, using the new OpenSAFELY platform. Population 17,425,445 adults. Time period 1st Feb 2020 to 25th April 2020. Primary outcome Death in hospital among people with confirmed COVID-19. Methods Cohort study analysed by Cox-regression to generate hazard ratios: age and sex adjusted, and multiply adjusted for co-variates selected prospectively on the basis of clinical interest and prior findings. Results There were 5683 deaths attributed to COVID-19. In summary after full adjustment, death from COVID-19 was strongly associated with: being male (hazard ratio 1.99, 95%CI 1.88-2.10); older age and deprivation (both with a strong gradient); uncontrolled diabetes (HR 2.36 95% CI 2.18-2.56); severe asthma (HR 1.25 CI 1.08-1.44); and various other prior medical conditions. Compared to people with ethnicity recorded as white, black people were at higher risk of death, with only partial attenuation in hazard ratios from the fully adjusted model (age-sex adjusted HR 2.17 95% CI 1.84-2.57; fully adjusted HR 1.71 95% CI 1.44-2.02); with similar findings for Asian people (age-sex adjusted HR 1.95 95% CI 1.73-2.18; fully adjusted HR 1.62 95% CI 1.431.82). Conclusions We have quantified a range of clinical risk factors for death from COVID-19, some of which were not previously well characterised, in the largest cohort study conducted by any country to date. People from Asian and black groups are at markedly increased risk of in-hospital death from COVID-19, and contrary to some prior speculation this is only partially attributable to pre-existing clinical risk factors or deprivation; further research into the drivers of this association is therefore urgently required. Deprivation is also a major risk factor with, again, little of the excess risk explained by co-morbidity or other risk factors. The findings for clinical risk factors are concordant with policies in the UK for protecting those at highest risk. Our OpenSAFELY platform is rapidly adding further NHS patients’ records; we will update and extend these results regularly.

<b>Objective</b> To examine the frequency of reporting of absolute and relative effect measures in health inequalities research. <b>Design</b> Structured review of selected general medical and public health journals. <b>Data sources</b> 344 articles published during 2009 in <i>American Journal of Epidemiology</i>, <i>American Journal of Public Health</i>, <i>BMJ</i>, <i>Epidemiology</i>, <i>International Journal of Epidemiology</i>, <i>JAMA</i>, <i>Journal of Epidemiology and Community Health</i>, <i>The Lancet</i>, <i>The New England Journal of Medicine</i>, and <i>Social Science and Medicine</i>. <b>Main outcome measures</b> Frequency and proportion of studies reporting absolute effect measures, relative effect measures, or both in abstract and full text; availability of absolute risks in studies reporting only relative effect measures. <b>Results</b> 40% (138/344) of articles reported a measure of effect in the abstract; among these, 88% (122/138) reported only a relative measure, 9% (13/138) reported only an absolute measure, and 2% (3/138) reported both. 75% (258/344) of all articles reported only relative measures in the full text; among these, 46% (119/258) contained no information on absolute baseline risks that would facilitate calculation of absolute effect measures. 18% (61/344) of all articles reported only absolute measures in the full text, and 7% (25/344) reported both absolute and relative measures. These results were consistent across journals, exposures, and outcomes. <b>Conclusions</b> Health inequalities are most commonly reported using only relative measures of effect, which may influence readers' judgments of the magnitude, direction, significance, and implications of reported health inequalities.

Abstract Social determinants of health (SDoH) play a critical role in patient outcomes, yet their documentation is often missing or incomplete in the structured data of electronic health records (EHRs). Large language models (LLMs) could enable high-throughput extraction of SDoH from the EHR to support research and clinical care. However, class imbalance and data limitations present challenges for this sparsely documented yet critical information. Here, we investigated the optimal methods for using LLMs to extract six SDoH categories from narrative text in the EHR: employment, housing, transportation, parental status, relationship, and social support. The best-performing models were fine-tuned Flan-T5 XL for any SDoH mentions (macro-F1 0.71), and Flan-T5 XXL for adverse SDoH mentions (macro-F1 0.70). Adding LLM-generated synthetic data to training varied across models and architecture, but improved the performance of smaller Flan-T5 models (delta F1 + 0.12 to +0.23). Our best-fine-tuned models outperformed zero- and few-shot performance of ChatGPT-family models in the zero- and few-shot setting, except GPT4 with 10-shot prompting for adverse SDoH. Fine-tuned models were less likely than ChatGPT to change their prediction when race/ethnicity and gender descriptors were added to the text, suggesting less algorithmic bias ( p &lt; 0.05). Our models identified 93.8% of patients with adverse SDoH, while ICD-10 codes captured 2.0%. These results demonstrate the potential of LLMs in improving real-world evidence on SDoH and assisting in identifying patients who could benefit from resource support.

Several studies have suggested strong associations between economic downturns and suicide mortality, but are at risk of bias due to unmeasured confounding. The rationale for our study was to provide more robust evidence by using a quasi-experimental design.We analysed 955,561 suicides occurring in the USA from 1980 to 2010 and used a broad index of economic activity in each US state to measure economic conditions. We used a quasi-experimental, fixed-effects design and we also assessed whether the effects were heterogeneous by demographic group and during periods of official recession.After accounting for secular trends, seasonality and unmeasured fixed characteristics of states, we found that an economic downturn similar in magnitude to the 2007 Great Recession increased suicide mortality by 0.14 deaths per 100,000 population [95% confidence interval (CI) 0.00, 0.28] or around 350 deaths. Effects were stronger for men (0.28, 95% CI 0.07, 0.49) than women and for those with less than 12 years of education (1.22 95% CI 0.83, 1.60) compared with more than 12 years of education. The overall effect did not differ for recessionary (0.11, 95% CI -0.02, 0.25) vs non-recessionary periods (0.15, 95% CI 0.01, 0.29). The main study limitation is the potential for misclassified death certificates and we cannot definitively rule out unmeasured confounding.We found limited evidence of a strong, population-wide detrimental effect of economic downturns on suicide mortality. The overall effect hides considerable heterogeneity by gender, socioeconomic position and time period.

The adoption of healthier behaviours has been hypothesised as a mechanism to explain empirical findings of population health improvements during some economic downturns.We estimated the effect of the local unemployment rate on health behaviours using pooled annual surveys from the 2003-2010 Behavioral Risk Factor Surveillance Surveys, as well as population-based telephone surveys of the US adult general population. Analyses were based on approximately 1 million respondents aged 25 years or older living in 90 Metropolitan Statistical Areas and Metropolitan Divisions (MMSAs). The primary exposure was the quarterly MMSA-specific unemployment rate. Outcomes included alcohol consumption, smoking status, attempts to quit smoking, body mass index, overweight/obesity and past-month physical activity or exercise.The average unemployment rate across MMSAs increased from a low of 4.5% in 2007 to a high of 9.3% in 2010. In multivariable models accounting for individual-level sociodemographic characteristics and MMSA and quarter fixed effects, a one percentage-point increase in the unemployment rate was associated with 0.15 (95% CI -0.31 to 0.01) fewer drinks consumed in the past month and a 0.14 (95% CI -0.28 to 0.00) percentage-point decrease in the prevalence of past-month heavy drinking; these effects were driven primarily by men. Changes in the unemployment rate were not consistently associated with other health behaviours. Although individual-level unemployment status was associated with higher levels of alcohol consumption, smoking and obesity, the MMSA-level effects of the recession were largely invariant across employment groups.Our results do not support the hypothesis that health behaviours mediate the effects of local-area economic conditions on mortality.

There is substantial debate concerning the impact of cannabis decriminalization and legalization on road safety outcomes.Seven databases were systematically searched: Embase, MEDLINE, and PsycINFO through Ovid as well as Web of Science Core Collection, SafetyLit, Criminal Justice Database (ProQuest), and Transport Research International Documentation (from inception to June 16, 2021). Eligible primary studies examined group-level cannabis decriminalization or legalization and a road safety outcome in any population.A total of 65 reports of 64 observational studies were eligible, including 39 that applied a quasi-experimental design. Studies examined recreational cannabis legalization (n=50), medical cannabis legalization (n=22), and cannabis decriminalization (n=5). All studies except 1 used data from the U.S. or Canada. Studies found mixed impacts of legalization on attitudes, beliefs, and self-reported driving under the influence. Medical legalization, recreational legalization, and decriminalization were associated with increases in positive cannabis tests among drivers. Few studies examined impacts on alcohol or other drug use, although findings suggested a decrease in positive alcohol tests among drivers associated with medical legalization. Medical legalization was associated with reductions in fatal motor-vehicle collisions, whereas recreational legalization was conversely associated with increases in fatal collisions.Increased cannabis positivity may reflect changes in cannabis use; however, it does not in itself indicate increased impaired driving. Subgroups impacted by medical and recreational legalization, respectively, likely explain opposing findings for fatal collisions. More research is needed concerning cannabis decriminalization; the impacts of decriminalization and legalization on nonfatal injuries, alcohol and other drugs; and the mechanisms by which legalization impacts road safety outcomes.

Few studies have evaluated the relationship between preterm birth (PTB) and maternal education over time. We sought to determine whether educational inequalities in PTB have increased in Québec, Canada.The authors analysed 2,124,909 singleton live births from 1981 to 2006, and computed the Relative Index of Inequality (RII) and Slope Index of Inequality (SII) with 95% CIs for the relationship between maternal education and extreme, very or moderate PTB (≤27, 28-31, and 32-36 completed weeks of gestation, respectively) for five periods (1981-1985, 1986-1990, 1991-1995, 1996-2000, 2001-2006), adjusting for maternal age, marital status, birthplace, language spoken at home, parity and infant sex.Average rates of extreme and moderate PTB increased over time but decreased for very PTB. A statistically significant increase in the RII over time was present for extreme and moderate PTB. The adjusted RII for extreme PTB increased from 1.58 (95% CI 1.24 to 2.01) in 1981-1985 to 3.11 (95% CI 2.54 to 3.81) in 2001-2006. For moderate PTB, the corresponding RIIs were 1.53 (95% CI 1.44 to 1.61) and 1.91 (95% CI 1.81 to 2.01). Absolute differences in the PTB proportion between the least and most educated mothers increased from 1981 to 2006 for extreme (adjusted SII 0.11% vs 0.28%) and moderate PTB (adjusted SII 1.67% vs 3.11%). Absolute differences in the proportion very PTB did not increase.Relative and absolute educational inequalities in extreme and moderate PTB have increased over time in Québec. Relative increases were largest for extreme PTB, and absolute increases were largest for moderate PTB.

The Compact Muon Solenoid (CMS) experiment has implemented a sophisticated two-level online selection system that achieves a rejection factor of nearly 105. During Run II, the LHC will increase its centre-of-mass energy up to 13 TeV and progressively reach an instantaneous luminosity of 2 × 1034 cm−2 s−1. In order to guarantee a successful and ambitious physics programme under this intense environment, the CMS Trigger and Data acquisition (DAQ) system has been upgraded. A novel concept for the L1 calorimeter trigger is introduced: the Time Multiplexed Trigger (TMT) . In this design, nine main processors receive each all of the calorimeter data from an entire event provided by 18 preprocessors. This design is not different from that of the CMS DAQ and HLT systems. The advantage of the TMT architecture is that a global view and full granularity of the calorimeters can be exploited by sophisticated algorithms. The goal is to maintain the current thresholds for calorimeter objects and improve the performance for their selection. The performance of these algorithms will be demonstrated, both in terms of efficiency and rate reduction. The callenging aspects of the pile-up mitigation and firmware design will be presented.

To be useful in a wider range of environments, especially environments that are not sanitized for their use, robots must be able to handle uncertainty in ground conditions. This requires a robot to incorporate new sensors and sources of information, and to be able to use this information to make decisions regarding navigation. When using autonomous mobile robots in unstructured and poorly defined environments, ground condition is of critical importance and is a common cause of failure, an example being the presence of ground water in the operating area. To evaluate a non-contact sensing method to mitigate this risk, Frequency Modulated Continuous Wave (FMCW) radar is integrated with an Unmanned Ground Vehicle (UGV), representing a novel application of FMCW to detect new measurands for Robotic Autonomous Systems (RAS) navigation, informing on ground integrity and adding to the state-of-the-art in sensing for optimized autonomous path planning. In this paper, FMCW is first evaluated in a desktop setting to determine water sensing capability. The FMCW is then fixed to a UGV, and the sensor system is successfully tested and validated in a representative environment containing regions with significant levels of ground water saturation. The successful integration of FMCW radar with autonomous environmental characterization and mapping has the potential to provide new measurands of terrain integrity data, such as the detection of water, snow, ice, oil or other contaminants on the operating surface that may otherwise jeopardize the operation of a UGV.

Social determinants of health (SDoH) have an important impact on patient outcomes but are incompletely collected from the electronic health records (EHR). This study researched the ability of large language models to extract SDoH from free text in EHRs, where they are most commonly documented, and explored the role of synthetic clinical text for improving the extraction of these scarcely documented, yet extremely valuable, clinical data. 800 patient notes were annotated for SDoH categories, and several transformer-based models were evaluated. The study also experimented with synthetic data generation and assessed for algorithmic bias. Our best-performing models were fine-tuned Flan-T5 XL (macro-F1 0.71) for any SDoH, and Flan-T5 XXL (macro-F1 0.70). The benefit of augmenting fine-tuning with synthetic data varied across model architecture and size, with smaller Flan-T5 models (base and large) showing the greatest improvements in performance (delta F1 +0.12 to +0.23). Model performance was similar on the in-hospital system dataset but worse on the MIMIC-III dataset. Our best-performing fine-tuned models outperformed zero- and few-shot performance of ChatGPT-family models for both tasks. These fine-tuned models were less likely than ChatGPT to change their prediction when race/ethnicity and gender descriptors were added to the text, suggesting less algorithmic bias (p<0.05). At the patient-level, our models identified 93.8% of patients with adverse SDoH, while ICD-10 codes captured 2.0%. Our method can effectively extracted SDoH information from clinic notes, performing better compare to GPT zero- and few-shot settings. These models could enhance real-world evidence on SDoH and aid in identifying patients needing social support.

Results from the completed Phase 1 Upgrade of the Compact Muon Solenoid (CMS) Level-1 Calorimeter Trigger are presented. The upgrade was performed in two stages, with the first running in 2015 for proton and heavy ion collisions and the final stage for 2016 data taking. The Level-1 trigger has been fully commissioned and has been used by CMS to collect over 43 fb−1 of data since the start of the Run II of the Large Hadron Collider (LHC). The new trigger has been designed to improve the performance at high luminosity and large number of simultaneous inelastic collisions per crossing (pile-up). For this purpose it uses a novel design, the Time Multiplexed Trigger (TMT), which enables the data from an event to be processed by a single trigger processor at full granularity over several bunch crossings. The TMT design is a modular design based on the μTCA standard. The trigger processors are instrumented with Xilinx Virtex-7 690 FPGAs and 10 Gbps optical links. The TMT architecture is flexible and the number of trigger processors can be expanded according to the physics needs of CMS. Sophisticated and innovative algorithms are now the core of the first decision layer of the experiment. The system has been able to adapt to the outstanding performance of the LHC, which ran with an instantaneous luminosity well above design. The performance of the system for single physics objects are presented along with the optimizations foreseen to maintain the thresholds for the harsher conditions expected during the LHC Run II and Run III periods.

We present a collection of signatures for physics beyond the standard model that need to be explored at the LHC. First, are presented various tools developed to measure new particle masses in scenarios where all decays include an unobservable particle. Second, various aspects of supersymmetric models are discussed. Third, some signatures of models of strong electroweak symmetry are discussed. In the fourth part, a special attention is devoted to high mass resonances, as the ones appearing in models with warped extra dimensions. Finally, prospects for models with a hidden sector/valley are presented. Our report, which includes brief experimental and theoretical reviews as well as original results, summarizes the activities of the "New Physics" working group for the "Physics at TeV Colliders" workshop (Les Houches, France, 8-26 June, 2009).

We present a collection of signatures for physics beyond the standard model that need to be explored at the LHC. First, are presented various tools developed to measure new particle masses in scenarios where all decays include an unobservable particle. Second, various aspects of supersymmetric models are discussed. Third, some signatures of models of strong electroweak symmetry are discussed. In the fourth part, a special attention is devoted to high mass resonances, as the ones appearing in models with warped extra dimensions. Finally, prospects for models with a hidden sector/valley are presented. Our report, which includes brief experimental and theoretical reviews as well as original results, summarizes the activities of the 'New Physics' working group for the 'Physics at TeV Colliders' workshop (Les Houches, France, 8-26 June, 2009).

The Compact Muon Solenoid (CMS) employs a sophisticated two-level online triggering system that has a rejection factor of up to 105. Since the beginning of Run II of LHC, the conditions that CMS operates in have become increasingly challenging. The centre-of-mass energy is now 13 TeV and the instantaneous luminosity currently peaks at 1.5 ×1034 cm−2s−1. In order to keep low physics thresholds and to trigger efficiently in such conditions, the CMS trigger system has been upgraded. A new trigger architecture, the Time Multiplexed Trigger (TMT) has been introduced which allows the full granularity of the calorimeters to be exploited at the first level of the online trigger. The new trigger has also benefited immensely from technological improvements in hardware. Sophisticated algorithms, developed to fully exploit the advantages provided by the new hardware architecture, have been implemented. The new trigger system started taking physics data in 2016 following a commissioning period in 2015, and since then has performed extremely well. The hardware and firmware developments, electron and photon algorithms together with their performance in challenging 2016 conditions is presented.

This OpenSAFELY report is a routine update of our peer-review paper published in the British Journal of General Practice on the Clinical coding of long COVID in English primary care: a federated analysis of 58 million patient records in situ using OpenSAFELY. It is a routine update of the analysis described in the paper. The data requires careful interpretation and there are a number of caveats. Please read the full detail about our methods and discussionis and the full analytical methods on this routine report are available on GitHub. OpenSAFELY is a new secure analytics platform for electronic patient records built on behalf of NHS England to deliver urgent academic and operational research during the pandemic. You can read more about OpenSAFELY on our website.

The chemical compatibility of wave length shifting fibers with several liquid scintillators has been investigated. Based on systematic characterization of the behavior of the BC-517 family, a time of life of 70–450 years was estimated for the polystyrene based wave length shifting fiber in BC-517P scintillator. Wavelength shifting (WLS) fibers irradiated continuously to a dose of 6.4 Mrads (at .377 Mrad/hr of 60Co) were observed to decrease from 100% to 5% transmission; however, after 100 hours of annealing, the transmission increased to 90%. GEANT3 simulations of a simplified calorimeter located behind a BaF2 electromagnetic calorimeter for the GEM detector at SSC showed that the constant term in the energy resolution will change from 1.8 to 2.9 in five years at 1034 luminosity for pseudorapidity η=3.

Adjusting for confounding is critical in observational studies that estimate the effect of an exposure on an outcome. Some methods for confounder selection, such as significance testing across exposure groups or including/excluding confounders based on whether they change the estimate of interest, can lead to bias by excluding important confounders and erroneously including factors affected by the exposure. Bias can be mitigated by careful selection of confounders a priori using prior knowledge supplemented with a causal diagram such as a Directed Acyclic Graph. We compared the prevalence of different approaches to confounder selection in recent obstetric and gynaecology studies. We reviewed all full-length original research articles from January 2022 through June 2022 in three leading obstetrics and gynecology journals (AJOG, BJOG, Obstetrics & Gynecology). We excluded experimental studies and studies that did not investigate the relationship between an exposure and a health outcome. We calculated the proportion of studies that selected all or some confounders using significance testing or a change-in-estimate approach, the proportion that reported selecting all confounders a priori, and the proportion that reported using a causal diagram. Of 252 studies, 158 met inclusion criteria. Fifty-three percent (84/158) of studies did not specify how they selected confounders. Twenty percent (32/158) used an outdated technique to select confounders—18% (29/158) used significance testing and 3% (4/158) used a change-in-estimate approach. Twenty-six percent (41/158) of studies reported selecting all confounders a priori, but only 4% (7/158) reported using a causal diagram and 2% (3/158) included their diagram. Outdated methods of confounder selection are common in recent obstetrics and gynecology studies, and many studies do not specify how confounders were selected. Investigators should emphasize prior knowledge when selecting confounders, justify the selection of confounders, and transparently report their modelling assumptions.

The CMS Level-1 calorimeter trigger is being upgraded in two stages to maintain performance as the LHC increases pile-up and instantaneous luminosity in its second run. In the first stage, improved algorithms including event-by-event pile-up corrections are used. New algorithms for heavy ion running have also been developed. In the second stage, higher granularity inputs and a time-multiplexed approach allow for improved position and energy resolution. Data processing in both stages of the upgrade is performed with new, Xilinx Virtex-7 based AMC cards.

We present a collection of signatures for physics beyond the standard model that need to be explored at the LHC. First, are presented various tools developed to measure new particle masses in scenarios where all decays include an unobservable particle. Second, various aspects of supersymmetric models are discussed. Third, some signatures of models of strong electroweak symmetry are discussed. In the fourth part, a special attention is devoted to high mass resonances, as the ones appearing in models with warped extra dimensions. Finally, prospects for models with a hidden sector/valley are presented. Our report, which includes brief experimental and theoretical reviews as well as original results, summarizes the activities of the New working group for the Physics at TeV Colliders workshop (Les Houches, France, 8-26 June, 2009).

We used data from a cluster-randomized trial in rural Rajasthan, India to evaluate the impact of providing access to a community-based daycare program on women’s economic outcomes two years later. The sample included 2858 mothers with age-eligible children. Providing access to daycare led 43% of households to utilize them. The intervention reduced time on childcare by 16.0 minutes/day (95%CI=-10.6, 42.5) and increased the probabilities that women were paid in cash and spent time during the prior day on paid work by 2.3 (95%CI=0.0, 4.5) and 2.6 (95%CI=0.9, 4.4) percentage points. Other indicators of labor force participation and income were unaffected.

Background: For policy questions where substantial empirical background information exists, conventional frequentist policy analysis is hard to justify. Bayesian analysis quantitatively incorporates prior knowledge, but is not often used in applied policy analysis. Methods: We combined 2000-2016 data from the Fatal Analysis Reporting System with priors based on past empirical studies and policy documents to study the impact of mandatory seat belt laws on traffic fatalities. We used a Bayesian data augmentation approach to combine information from prior studies with difference-in-differences analyses of recent law changes to provide updated evidence on the impact that upgrading to primary enforcement of seat belt laws has on fatalities. Results: After incorporating the evidence from past studies, we find limited evidence to support the hypothesis that recent policy upgrades affect fatality rates. We estimate that upgrading to primary enforcement reduced fatality rates by 0.37 deaths per billion vehicle miles traveled (95% posterior interval -0.90, 0.16), or a rate ratio of 0.96 (95% posterior interval 0.91, 1.02), and increased the proportion of decedents reported as wearing seat belts by 7 percentage points (95% posterior interval 5, 8), or a risk ratio of 1.18 (95% posterior interval 1.13, 1.24). Conclusion: Bayesian methods can provide credible estimates of future policy impacts, especially for policy questions that occur in dynamic environments, such as traffic safety.

The Compact Muon Solenoid (CMS) experiment is currently installing upgrades to their Calorimeter Trigger for LHC Run 2 to ensure that the trigger thresholds can stay low, and physics data collection will not be compromised. The electronics will be upgraded in two stages. Stage-1 for 2015 will upgrade some electronics and links from copper to optical in the existing calorimeter trigger so that the algorithms can be improved and we do not lose valuable data before stage-2 can be fully installed by 2016. Stage-2 will fully replace the calorimeter trigger at CMS with a micro-TCA and optical link system. It requires that the updates to the calorimeter back-ends, the source of the trigger primitives, be completed. The new system's boards will utilize Xilinx Virtex-7 FPGAs and have hundreds of high-speed links operating at up to 10 Gbps to maximize data throughput. The integration, commissioning, and installation of stage-1 in 2015 will be described, as well as the integration and parallel installation of the stage-2 in 2015, for a fully upgraded CMS calorimeter trigger in operation by 2016.

The status of CMS searches for new gauge bosons in the e+e−, eve and μ+μ− channels is reported on. A brief description of the Standard Model backgrounds and the techniques used to estimate them are given, together with the expected mass spectra for 100 pb−1 at s = 14 TeV. The mass spectra are interpreted to determine the luminosity required to discover a reference Z′ and W′ as a function of resonance mass for s = 10 TeV and 14 TeV.

Background: Research from high-income countries suggests that increasing the availability of daycare can improve economic outcomes for mothers, but similar research from low- and middle-income countries is lacking.Methods: We systematically searched databases of published and unpublished literature for studies that measured the impact of daycare provision on social, economic, and health outcomes in low- and middle-income countries without language or publication date restrictions. We synthesized the evidence using both narrative review and random effects meta-analysis.Results: We found 2073 studies and included 13 after applying our exclusion criteria. For a 30 percentage point increase in daycare utilization we estimate that maternal employment increased by 6 percentage points (95% confidence interval: 4 to 8), but we found considerable between-study heterogeneity and evidence of effect measure modification within studies. The impact on maternal earnings was mixed, and few studies assessed the impact of daycare on non-economic outcomes.Conclusions: We found moderate but heterogeneous evidence that interventions to increase access to formal daycare increase maternal labor force participation. Future studies would benefit from assessing the impact of daycare on non-economic outcomes and understanding the heterogeneity between studies.

Multi-robot systems face challenges in reducing human interventions as they are often deployed in dangerous environments. It is therefore necessary to include a methodology to assess robot failure rates to reduce the requirement for costly human intervention. A solution to this problem includes robots with the ability to work together to ensure mission resilience. To prevent this intervention, robots should be able to work together to ensure mission resilience. However, robotic platforms generally lack built-in interconnectivity with other platforms from different vendors. This work aims to tackle this issue by enabling the functionality through a bidirectional digital twin. The twin enables the human operator to transmit and receive information to and from the multi-robot fleet. This digital twin considers mission resilience and autonomous and human-led decision making to enable the resilience of a multi-robot fleet. This creates the cooperation, corroboration, and collaboration of diverse robots to leverage the capability of robots and support recovery of a failed robot.

Mobile robot autonomy has made significant advances in recent years, with navigation algorithms well developed and used commercially in certain well-defined environments, such as warehouses. The common link in usage scenarios is that the environments in which the robots are utilized have a high degree of certainty. Operating environments are often designed to be robot friendly, for example augmented reality markers are strategically placed and the ground is typically smooth, level, and clear of debris. For robots to be useful in a wider range of environments, especially environments that are not sanitized for their use, robots must be able to handle uncertainty. This requires a robot to incorporate new sensors and sources of information, and to be able to use this information to make decisions regarding navigation and the overall mission. When using autonomous mobile robots in unstructured and poorly defined environments, such as a natural disaster site or in a rural environment, ground condition is of critical importance and is a common cause of failure. Examples include loss of traction due to high levels of ground water, hidden cavities, or material boundary failures. To evaluate a non-contact sensing method to mitigate these risks, Frequency Modulated Continuous Wave (FMCW) radar is integrated with an Unmanned Ground Vehicle (UGV), representing a novel application of FMCW to detect new measurands for Robotic Autonomous Systems (RAS) navigation, informing on terrain integrity and adding to the state-of-the-art in sensing for optimized autonomous path planning. In this paper, the FMCW is first evaluated in a desktop setting to determine its performance in anticipated ground conditions. The FMCW is then fixed to a UGV and the sensor system is tested and validated in a representative environment containing regions with significant levels of ground water saturation.

Background: Cannabis use has been linked to impaired driving and fatal accidents. Prior evidence suggests the potential for population-wide effects of the annual cannabis celebration on April 20th ("4/20"), but evidence to date is limited.Methods: We used data from the Fatal Analysis Reporting System for the years 1975-2016 to estimate the impact of "4/20" on drivers involved in fatal traffic crashes occurring between 1620h and 2359h in the United States. We compared the effects of 4/20 to those for other major holidays, and evaluated whether the impact of "4/20" had changed in recent years. Results: Between 1992-2016 "4/20" was associated with an increase in the number of drivers involved in fatal crashes (Incidence rate ratio [IRR]: 1.12, 95% CI 0.97 to 1.28) relative to control days one week before and after, but not when compared with control days one and two weeks before and after (IRR 1.05, 95% CI 0.92 to 1.28) or all days of the year (IRR 0.98, 95% CI 0.88 to 1.10). Across all years we found little evidence to distinguish excess drivers involved in fatal crashes on 4/20 from routine daily variations. Conclusions: There is little evidence to suggest population-wide effects of the annual cannabis holiday on the number of drivers involved in fatal traffic crashes.

Numerous observational studies have shown that infants born after short interpregnancy intervals (the interval between birth and subsequent conception) are more likely to experience adverse perinatal outcomes than infants born following longer intervals. Yet it remains controversial whether the link between short interpregnancy interval and adverse outcomes is causal or is confounded by factors such as low socioeconomic position, inadequate access to health care, and unintended pregnancy. Sibling comparison studies, which use a woman as her own control by comparing exposure and outcome status of her different pregnancies (i.e., comparing sibling offspring), have gained popularity as a strategy to reduce confounding by these difficult-to-measure factors that are nevertheless relatively stable within women. A variant of this approach, used by Regan et al. (Am J Epidemiol. 2019;188(1):9–16) and reported in this issue of the Journal, is a maternally matched design based on a single interpregnancy interval per woman. Using real and simulated data, we highlight underappreciated shortcomings of these designs that could limit the validity of study findings. In particular, we illustrate how the single-interval variant appears to derive estimates from comparisons between different mothers, not within mothers. Future studies of optimal birth spacing using sibling comparison designs should examine in detail the potential consequences of these methodological limitations.

Observational studies are ambiguous, difficult, and necessary for epidemiology. Presently there are concerns that the evidence produced by most observational studies in epidemiology is not credible and contributes to research waste. I argue that observational epidemiology could be improved by focusing greater attention on: 1) defining questions that make clear whether the inferential goal is descriptive or causal; 2) greater utilization of quantitative bias analysis and alternative research designs that aim to decrease the strength of assumptions needed to estimate causal effects; and 3) promoting, experimenting, and perhaps institutionalizing reproducible research standards as well as replication studies to evaluate the fragility of study findings in epidemiology. Greater clarity, credibility, and transparency in observational epidemiology will help to provide reliable evidence that can serve as a basis for making decisions about clinical or population health interventions.

PurposeResearch suggests that the Great Recession of 2007–2009 led to nearly 5000 excess suicides in the United States. However, prior work has not accounted for seasonal patterning and unique suicide trends by age and gender.MethodsWe calculated monthly suicide rates from 1999 to 2013 for men and women aged 15 and above. Suicide rates before the Great Recession were used to predict the rate during and after the Great Recession. Death rates for each age-gender group were modeled using Poisson regression with robust variance, accounting for seasonal and nonlinear suicide trajectories.ResultsThere were 56,658 suicide deaths during the Great Recession. Age- and gender-specific suicide trends before the recession demonstrated clear seasonal and nonlinear trajectories. Our models predicted 57,140 expected suicide deaths, leading to 482 fewer observed than expected suicides (95% confidence interval −2079, 943).ConclusionsWe found little evidence to suggest that the Great Recession interrupted existing trajectories of suicide rates. Suicide rates were already increasing before the Great Recession for middle-aged men and women. Future studies estimating the impact of recessions on suicide should account for the diverse and unique suicide trajectories of different social groups.

Objectives: Mortality rates generally decline during economic recessions in high-income countries, however gaps remain in our understanding of the underlying mechanisms. This study estimates the impacts of increases in unemployment rates on both all-cause and cause-specific mortality across U.S. metropolitan regions during the Great Recession.Methods: We estimate the effects of economic conditions during the recent and severe recessionary period on mortality, including differences by age and gender subgroups, using fixed effects regression models. We identify a plausibly causal effect by isolating the impacts of within-metropolitan area changes in unemployment rates and controlling for common temporal trends. We aggregated vital statistics, population, and unemployment data at the area-month-year-age-gender-race level, yielding 527,040 observations across 366 metropolitan areas, 2005-2010.Results: We estimate that a one percentage point increase in the metropolitan area unemployment rate was associated with a decrease in all-cause mortality of 3.95 deaths per 100,000 person years (95%CI -6.80 to -1.10), or 0.5%. Estimated reductions in cardiovascular disease mortality contributed 60% of the overall effect and were more pronounced among women. Motor vehicle accident mortality declined with unemployment increases, especially for men and those under age 65, as did legal intervention and homicide mortality, particularly for men and adults ages 25-64. We find suggestive evidence that increases in metropolitan area unemployment increased accidental drug poisoning deaths for both men and women ages 25-64.Conclusions: Our finding that all-cause mortality increased during the Great Recession is consistent with previous studies. Some categories of cause-specific mortality, notably cardiovascular disease, also follow this pattern, and are more pronounced for certain gender and age groups. Our study also suggests that the recent recession contributed to the growth in deaths from overdoses of prescription drugs in working-age adults in metropolitan areas. Additional research investigating the mechanisms underlying the health consequences of macroeconomic conditions is warranted.

is realized in nature, gravity, is too weak to be observable in laboratory experiments carried out in high-energy particle physics and is not part of the Standard Model. Although the Standard Model has proven highly successful in correlating a huge amount of experimental results, a key ingredient is as yet untested: the origin of electroweak symmetry breaking. Currently, the only viable ansatz that is compatible with observation is the Higgs mechanism. It predicts the existence of a scalar particle, called the Higgs boson, and the couplings to the fundamental Standard Model particles, however not its mass. An upper limit on the mass of the Higgs boson of ~ 1 TeV can be inferred from unitarity arguments. One of the key tasks of particle physics in the next years will be to verify the existence of this particle. The introduction of an elementary scalar particle in a quantum field theory is highly problematic. The Higgs boson mass is subject to large quantum corrections, which makes it difficult to understand how its mass can be less than a TeV as required by theory. In addition, the Standard Model does not provide an answer to fundamental questions like the values of free parameters of the model, the pending integration of gravity or the evolution of the coupling constants of the fundamental forces at large energy regimes. Hence there are strong reasons to believe that the Standard Model is only a low-energy approximation to a more fundamental theory. One of the best studied candidates for an extension of the Standard Model is supersymmetry, which predicts the existence of a supersymmetric partner for each fundamental particle that differs only in spin. To allow different masses for Standard Model particles and their corresponding supersymmetric partners, supersymmetry must be broken. The mechanism behind supersymmetry breaking is currently unknown, however, various hypotheses exist. Supersymmetric models do not only solve the problem of the large quantum corrections to the Higgs boson mass, but they also allow the unification of the coupling constants at a common scale. In addition, certain supersymmetric models provide a suitable candidate for cold dark matter, which represents a large fraction of mass in our universe. Searches for supersymmetric particles have been performed by the four LEP experiments (ALEPH, DELPHI, L3, OPAL) up to the kinematic limit. Since no evidence for supersymmetric particles has been found, lower limits on their masses have been derived. The search for supersymmetry is now continuing at the Tevatron collider, located at the Fermi National Accelerator Laboratory in Batavia, Illinois. Two dedicated detector systems, CDF and D0, are installed at the Tevatron to analyze proton-antiproton collisions at a center-of-mass energy of 1.96 TeV. A particular promising discovery channel for supersymmetry within the Tevatron energy range is the trilepton channel. In this channel, the lighter supersymmetric partners of the Higgs and gauge bosons, the charginos and neutralinos, decay into final states with leptons or hadrons and missing energy. Using the leptonic final states, the signal can be separated from the large Standard Model background. Supersymmetry requires an extension of the Standard Model Higgs sector, leading to more than one neutral Higgs boson. Enhanced couplings result in sizable cross sections for Higgs boson production, and the decay into a tau pair becomes an important Higgs boson discovery channel. Within the present thesis, a search for new physics predicted by constrained supersymmetric models is performed in final states consisting of an electron and a tau using data collected with the D0 detector from April 2002 to July 2004. The first analysis searches for the associated production of the lightest chargino and the second lightest neutralino in final states with an electron, a hadronically decaying tau, an additional lepton and missing transverse energy: e + τb h + ℓ + ET. The second analysis searches for neutral supersymmetric Higgs bosons in the decay mode Φ → ττ → e + τh + ET. To improve the sensitivity, the results are interpreted in combination with other channels.

A global trend in increasing wind turbine size and distances from shore is emerging within the rapidly growing offshore wind farm market. In the UK, the offshore wind sector produced its highest amount of electricity in the UK in 2019, a 19.6% increase on the year before. Currently, the UK is set to increase production further, targeting a 74.7% increase of installed turbine capacity as reflected in recent Crown Estate leasing rounds. With such tremendous growth, the sector is now looking to Robotics and Artificial Intelligence (RAI) in order to tackle lifecycle service barriers as to support sustainable and profitable offshore wind energy production. Today, RAI applications are predominately being used to support short term objectives in operation and maintenance. However, moving forward, RAI has the potential to play a critical role throughout the full lifecycle of offshore wind infrastructure, from surveying, planning, design, logistics, operational support, training and decommissioning. This paper presents one of the first systematic reviews of RAI for the offshore renewable energy sector. The state-of-the-art in RAI is analyzed with respect to offshore energy requirements, from both industry and academia, in terms of current and future requirements. Our review also includes a detailed evaluation of investment, regulation and skills development required to support the adoption of RAI. The key trends identified through a detailed analysis of patent and academic publication databases provide insights to barriers such as certification of autonomous platforms for safety compliance and reliability, the need for digital architectures for scalability in autonomous fleets, adaptive mission planning for resilient resident operations and optimization of human machine interaction for trusted partnerships between people and autonomous assistants.

A global trend in increasing wind turbine size and distances from shore is emerging within the rapidly growing offshore wind farm market. In the UK, the offshore wind sector produced its highest amount of electricity in the UK in 2019, a 19.6% increase on the year before. Currently, the UK is set to increase production further, targeting a 74.7% increase of installed turbine capacity as reflected in recent Crown Estate leasing rounds. With such tremendous growth, the sector is now looking to Robotics and Artificial Intelligence (RAI) in order to tackle lifecycle service barriers as to support sustainable and profitable offshore wind energy production. Today, RAI applications are predominately being used to support short term objectives in operation and maintenance. However, moving forward, RAI has the potential to play a critical role throughout the full lifecycle of offshore wind infrastructure, from surveying, planning, design, logistics, operational support, training and decommissioning. This paper presents one of the first systematic reviews of RAI for the offshore renewable energy sector. The state-of-the-art in RAI is analyzed with respect to offshore energy requirements, from both industry and academia, in terms of current and future requirements. Our review also includes a detailed evaluation of investment, regulation and skills development required to support the adoption of RAI. The key trends identified through a detailed analysis of patent and academic publication databases provide insights to barriers such as certification of autonomous platforms for safety compliance and reliability, the need for digital architectures for scalability in autonomous fleets, adaptive mission planning for resilient resident operations and optimization of human machine interaction for trusted partnerships between people and autonomous assistants.

The chemical compatibility of wave length shifting fibers with several liquid scintillators has been investigated. Based on systematic characterization of the behavior of the BC-517 family, a time of life of 70{endash}450 years was estimated for the polystyrene based wave length shifting fiber in BC-517P scintillator. WLS (wavelength shifting) fibers irradiated continuously to a dose of 6.4 Mrads (at .377Mrad/hr of Co-60) were observed to decrease from 100% to 5% transmission; however, after 100 hours of annealing, the transmission increased to 90%. Geant simulations of a simplified calorimeter located behind a BaF2 electromagnetic calorimeter for the GEM detector at SSC showed that the constant term in the energy resolution will change from 1.8 to 2.9 in five years at 10{star}{star}34 luminosity for psuedorapidity eta=3.