Benchmarking the performance of density functional theory based Green’s function formalism utilizing different self-energy models in calculating electronic transmission through molecular systems

Electronic transmission through a metal-molecule-metal system is calculated by employing a Green’s function formalism in the scattering based scheme. Self-energy models representing the bulk and the potential bias are used to describe electron transport through the molecular system. Different self-energies can be defined by varying the partition between device and bulk regions of the metal-molecule-metal model system. In addition, the self-energies are calculated with different representations of the bulk through its Green’s function. In this work, the dependence of the calculated transmission on varying the self-energy subspaces is benchmarked. The calculated transmission is monitored with respect to the different choices defining the self-energy model. In this report, we focus on one-dimensional model systems with electronic structures calculated at the density functional level of theory.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87873/2/204717_1.pd

Bias effects on the electronic spectrum of a molecular bridge

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98651/1/JChemPhys_134_054708.pd

Academic Performance and Behavioral Patterns

Identifying the factors that influence academic performance is an essential part of educational research. Previous studies have documented the importance of personality traits, class attendance, and social network structure. Because most of these analyses were based on a single behavioral aspect and/or small sample sizes, there is currently no quantification of the interplay of these factors. Here, we study the academic performance among a cohort of 538 undergraduate students forming a single, densely connected social network. Our work is based on data collected using smartphones, which the students used as their primary phones for two years. The availability of multi-channel data from a single population allows us to directly compare the explanatory power of individual and social characteristics. We find that the most informative indicators of performance are based on social ties and that network indicators result in better model performance than individual characteristics (including both personality and class attendance). We confirm earlier findings that class attendance is the most important predictor among individual characteristics. Finally, our results suggest the presence of strong homophily and/or peer effects among university students

Resonant Electron Dynamics in Open Nano Scale Systems: A Time-Dependent Non- Equilibrium Green Function Approach.

Research in nanometer length scale electronics is motivated by both a desire to understand the physics of such small systems and the technological advantages of implementing ever smaller more efficient devices. Ongoing experimental research is focused on characterizing the temporal response of nano-electronics to both weak and strong time-dependent classical driving fields. Theoretical models and methods are also being developed and implemented to explain these experiments. In particular, the weak classical driving field scenario offers the opportunity to efficiently model the response of the manifold of states to the driving field. This two variable (state energy and time) problem is the focus of this dissertation. A two-variable non-equilibrium Green function (NEGF) based time-dependent perturbation theory (TDPT) is developed and applied to small model two and four state systems. This formalism is used to study the dynamic interplay between a source drain bias and a resonant laser excitation that induces coherences and transfers population between states and out of the device. A unique effect in which laser induced population inversion between states brings about a reversal of current direction (absolute negative conductance) is reported. Finally, a one variable constant constant potential theory (CPT), is derived and compared to Landauer theory for simple systems.Ph.D.PhysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/64694/1/aprociuk_1.pd

Addressing Inequalities in Long Covid Healthcare: A Mixed-Methods Study on Building Inclusive Services

\ua9 2025 The Author(s). Health Expectations published by John Wiley & Sons Ltd. BACKGROUND: Long Covid (LC) significantly impacts health, economic and social activities. Women, deprived, learning disability, homeless and some minority ethnic populations have high prevalence rates but low access to support, indicating health inequities in LC care. AIM: To identify health inequities in LC care and inclusion strategies that align with the priorities of people with LC. DESIGN AND SETTING: Mixed-methods study employing qualitative data from people with LC, professional experts, LC clinic staff and primary care data from North West (NW) London GPs. METHOD: Qualitative interviews with 23 people with LC and 18 professional experts explored the experience of diagnosis and support for people from disadvantaged groups. Framework analysis identified themes that informed the subsequent collection of clinic and primary care data. Staff from 10 LC clinics across England provided survey and qualitative data describing their initiatives to identify and reduce inequalities. Descriptive quantitative analysis of NW London adult primary care records (n = 6078), linked to hospital use across England, explored LC diagnosis and care pathways for diverse groups of people with LC. RESULTS: Study participants from disadvantaged groups reported delays in formal diagnosis and specialist referrals being initated and had low trust in healthcare services. They described difficulties in obtaining information, advice and support as barriers to access specialist referrals. LC clinics confirmed the under-referral of those from the most disadvantaged groups compared to the general population. Primary care data confirmed under-referral of people with LC to specialist clinics; however, incomplete data across the LC clinical pathway prevented an analysis of equity in referral patterns between population groups. Clinics used various strategies to improve access and increase the flow of disadvantaged groups from primary care to LC services. Interventions included data collection to identify underserved groups, targeting outreach to primary care and community providers, adapting clinic provision and developing care pathways involving multidisciplinary teams (MDTs), primary and secondary care practitioners and third sector organisations. These activities were not widespread, however, and were particular to a few clinics. CONCLUSION: Strategies to improve access to LC healthcare provide a starting point to explore inclusive care pathways for people with LC from disadvantaged social groups. Future research should focus on the effectiveness of initiatives to increase access to specialist LC provision among disadvantaged groups and establish greater trust in healthcare providers. PRIORITIES OF PEOPLE WITH LC FOR HEALTHCARE PRACTICE: This study highlights the need for health system practitioners to identify under-represented groups and target inclusion initiatives at these populations in sensitive and appropriate ways. Improved diagnosis and support for such populations would be helped by training health and social care practitioners to recognise and accept the accounts of people with LC about their symptoms. Protocols that support consistent practice in referrals for specialist care are also needed. People with LC from disadvantaged groups often lack access to evidence-based sources of advice and information. Practitioners should provide information on LC while individuals are waiting to receive specialist care and should advocate for support from employers, including work modifications. PATIENT AND PUBLIC CONTRIBUTION: People with lived experience of LC were involved in the study as members of the research team and LOCOMOTION Patient Advisory Group (PAG). The PAG was involved in the wider study design, including the initial grant application, attending proposal planning meetings and helping to develop the research aim, objectives and questions. During the course of the study, the PAG met quarterly with each other and at least monthly with other research team members to review progress and feed into data collection and analysis processes. PAG members also attended a Quality Improvement Collaborative meeting involving academics and LC practitioners, which discussed initial findings from data analysis of qualitative interviews on LC inequalities. Through these meetings, the group supported and oversaw the study as a whole in terms of how data was collected, recruitment of participants, involvement in data analysis and interpretation, as well as providing more specific advice to all the individual workstreams within the study. A PPI facilitator within the study team provided training and support to PAG members in these areas and was available to respond to other needs expressed by the group. PAG members have also been involved in organising and contributing to a wide range of study dissemination events. PAG involvement throughout the study has ensured that the research is aligned with the key research priorities of people diagnosed with LC as well as those with LC symptoms but no formal diagnosis. PAG members were recruited through and linked to the LC clinics involved in the study and have helped disseminate study findings to local clinical practice, the lay public and other LC centres with which they are involved. S.E. is a PAG member from a minority ethnic background and a co-author on the paper. She has been involved in overseeing and supporting data collection and interpretation relating to inequalities affecting people with LC and has contributed to the preparation of this manuscript from an early draft to production of the final version

Addressing Inequalities in Long Covid Healthcare: A Mixed‐Methods Study on Building Inclusive Services

Background: Long Covid (LC) significantly impacts health, economic and social activities. Women, deprived, learning disability, homeless and some minority ethnic populations have high prevalence rates but low access to support, indicating health inequities in LC care. Aim: To identify health inequities in LC care and inclusion strategies that align with the priorities of people with LC. Design and Setting: Mixed‐methods study employing qualitative data from people with LC, professional experts, LC clinic staff and primary care data from North West (NW) London GPs. Method: Qualitative interviews with 23 people with LC and 18 professional experts explored the experience of diagnosis and support for people from disadvantaged groups. Framework analysis identified themes that informed the subsequent collection of clinic and primary care data. Staff from 10 LC clinics across England provided survey and qualitative data describing their initiatives to identify and reduce inequalities. Descriptive quantitative analysis of NW London adult primary care records (n = 6078), linked to hospital use across England, explored LC diagnosis and care pathways for diverse groups of people with LC. Results: Study participants from disadvantaged groups reported delays in formal diagnosis and specialist referrals being initated and had low trust in healthcare services. They described difficulties in obtaining information, advice and support as barriers to access specialist referrals. LC clinics confirmed the under‐referral of those from the most disadvantaged groups compared to the general population. Primary care data confirmed under‐referral of people with LC to specialist clinics; however, incomplete data across the LC clinical pathway prevented an analysis of equity in referral patterns between population groups. Clinics used various strategies to improve access and increase the flow of disadvantaged groups from primary care to LC services. Interventions included data collection to identify underserved groups, targeting outreach to primary care and community providers, adapting clinic provision and developing care pathways involving multidisciplinary teams (MDTs), primary and secondary care practitioners and third sector organisations. These activities were not widespread, however, and were particular to a few clinics. Conclusion: Strategies to improve access to LC healthcare provide a starting point to explore inclusive care pathways for people with LC from disadvantaged social groups. Future research should focus on the effectiveness of initiatives to increase access to specialist LC provision among disadvantaged groups and establish greater trust in healthcare providers. Priorities of People With LC for Healthcare Practice: This study highlights the need for health system practitioners to identify under‐represented groups and target inclusion initiatives at these populations in sensitive and appropriate ways. Improved diagnosis and support for such populations would be helped by training health and social care practitioners to recognise and accept the accounts of people with LC about their symptoms. Protocols that support consistent practice in referrals for specialist care are also needed. People with LC from disadvantaged groups often lack access to evidence‐based sources of advice and information. Practitioners should provide information on LC while individuals are waiting to receive specialist care and should advocate for support from employers, including work modifications. Patient and Public Contribution: People with lived experience of LC were involved in the study as members of the research team and LOCOMOTION Patient Advisory Group (PAG). The PAG was involved in the wider study design, including the initial grant application, attending proposal planning meetings and helping to develop the research aim, objectives and questions. During the course of the study, the PAG met quarterly with each other and at least monthly with other research team members to review progress and feed into data collection and analysis processes. PAG members also attended a Quality Improvement Collaborative meeting involving academics and LC practitioners, which discussed initial findings from data analysis of qualitative interviews on LC inequalities. Through these meetings, the group supported and oversaw the study as a whole in terms of how data was collected, recruitment of participants, involvement in data analysis and interpretation, as well as providing more specific advice to all the individual workstreams within the study. A PPI facilitator within the study team provided training and support to PAG members in these areas and was available to respond to other needs expressed by the group. PAG members have also been involved in organising and contributing to a wide range of study dissemination events. PAG involvement throughout the study has ensured that the research is aligned with the key research priorities of people diagnosed with LC as well as those with LC symptoms but no formal diagnosis. PAG members were recruited through and linked to the LC clinics involved in the study and have helped disseminate study findings to local clinical practice, the lay public and other LC centres with which they are involved. S.E. is a PAG member from a minority ethnic background and a co‐author on the paper. She has been involved in overseeing and supporting data collection and interpretation relating to inequalities affecting people with LC and has contributed to the preparation of this manuscript from an early draft to production of the final version

Remote COVID-19 Assessment in Primary Care (RECAP) risk prediction tool: derivation and real-world validation studies

This article relates to a research study that included patients or members of the workforce as study participants from GP practices in Nottingham and Nottinghamshire.Background: Accurate assessment of COVID-19 severity in the community is essential for patient care and requires COVID-19-specific risk prediction scores adequately validated in a community setting. Following a qualitative phase to identify signs, symptoms, and risk factors, we aimed to develop and validate two COVID-19-specific risk prediction scores. Remote COVID-19 Assessment in Primary Care-General Practice score (RECAP-GP; without peripheral oxygen saturation [SpO2]) and RECAP-oxygen saturation score (RECAP-O2; with SpO2). Methods: RECAP was a prospective cohort study that used multivariable logistic regression. Data on signs and symptoms (predictors) of disease were collected from community-based patients with suspected COVID-19 via primary care electronic health records and linked with secondary data on hospital admission (outcome) within 28 days of symptom onset. Data sources for RECAP-GP were Oxford-Royal College of General Practitioners Research and Surveillance Centre (RCGP-RSC) primary care practices (development set), northwest London primary care practices (validation set), and the NHS COVID-19 Clinical Assessment Service (CCAS; validation set). The data source for RECAP-O2 was the Doctaly Assist platform (development set and validation set in subsequent sample). The two probabilistic risk prediction models were built by backwards elimination using the development sets and validated by application to the validation datasets. Estimated sample size per model, including the development and validation sets was 2880 people. Findings: Data were available from 8311 individuals. Observations, such as SpO2, were mostly missing in the northwest London, RCGP-RSC, and CCAS data; however, SpO2 was available for 1364 (70·0%) of 1948 patients who used Doctaly. In the final predictive models, RECAP-GP (n=1863) included sex (male and female), age (years), degree of breathlessness (three point scale), temperature symptoms (two point scale), and presence of hypertension (yes or no); the area under the curve was 0·80 (95% CI 0·76-0·85) and on validation the negative predictive value of a low risk designation was 99% (95% CI 98·1-99·2; 1435 of 1453). RECAP-O2 included age (years), degree of breathlessness (two point scale), fatigue (two point scale), and SpO2 at rest (as a percentage); the area under the curve was 0·84 (0·78-0·90) and on validation the negative predictive value of low risk designation was 99% (95% CI 98·9-99·7; 1176 of 1183). Interpretation: Both RECAP models are valid tools to assess COVID-19 patients in the community. RECAP-GP can be used initially, without need for observations, to identify patients who require monitoring. If the patient is monitored and SpO2 is available, RECAP-O2 is useful to assess the need for treatment escalation

Modeling transient aspects of coherence-driven electron transport

Non-equilibrium Green's function formalism (NEGF) by employing time-dependent (TD) perturbation theory is used to solve the electronic equations of motion of model systems under potential biasing conditions. The time propagation is performed in the full frequency domain of the two time variables representation. We analyze transient aspects of the resulting conductance under effects of applied direct-current and alternating current potentials. The coherence induced response dependence on different aspects of the applied perturbation is resolved in time and analyzed using calculated TD distributions of the current operator.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85419/1/jpconf10_220_012008.pd

Bone Marrow Transplantation for Feline Mucopolysaccharidosis I

Severe mucopolysaccharidosis type I (MPS I) is a fatal neuropathic lysosomal storage disorder with significant skeletal involvement. Treatment involves bone marrow transplantation (BMT), and although effective, is suboptimal, due to treatment sequelae and residual disease. Improved approaches will need to be tested in animal models and compared to BMT. Herein we report on bone marrow transplantation to treat feline mucopolysaccharidosis I (MPS I). Five MPS I stably engrafted kittens, transplanted with unfractionated bone marrow (6.3 × 107–1.1 × 109 nucleated bone marrow cells per kilogram) were monitored for 13–37 months post-engraftment. The tissue total glycosaminoglycan (GAG) content was reduced to normal levels in liver, spleen, kidney, heart muscle, lung, and thyroid. Aorta GAG content was between normal and affected levels. Treated cats had a significant decrease in the brain GAG levels relative to untreated MPS I cats and a paradoxical decrease relative to normal cats. The α-l-iduronidase (IDUA) activity in the livers and spleens of transplanted MPS I cats approached heterozygote levels. In kidney cortex, aorta, heart muscle, and cerebrum, there were decreases in GAG without significant increases in detectable IDUA activity. Treated animals had improved mobility and decreased radiographic signs of disease. However, significant pathology remained, especially in the cervical spine. Corneal clouding appeared improved in some animals. Immunohistochemical and biochemical analysis documented decreased central nervous system ganglioside storage. This large animal MPS I study will serve as a benchmark of future therapies designed to improve on BMT