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Demand-side behavioural change interventions promote a reduction in car use, and shift to low carbon transport modes, thereby addressing economic, health and GHG emissions-related costs associated with car-dependent lifestyles. However, the relative effectiveness of such interventions in initiating transport behaviour change has not been evaluated systematically. Here, we conduct a systematic review and meta-analysis to evaluate the evidence on behavioural interventions in changing transport-related behavioural patterns. Relying on 37 literature reviews and 41 additional new studies, we identify more than 450 cases of behavioural interventions. Our analysis reveals that behavioural measures are effective in increasing the percentage growth of public transit and active transport mode use as well as decreasing car use at the personal level. However, their effectiveness in shifting commuters away from cars to more sustainable modes of transport at the aggregate level is limited. Our findings suggest that behavioural interventions have a role to play in reducing the health, economic and environmental costs of car-centric transportation systems. We find that, under the best-case scenario, behavioural interventions can contribute up to a 5% per cent reduction of global GHG emissions from urban transport, or about 150Mt CO2/yr, a notable but limited potential compared to the reductions necessary to meet sectoral goals. Critical analysis of studies in our review indicates that interdisciplinary researchers interested in these issues should take a more strategic and rigorous approach—better study designs, more representative samples, and consideration of infrastructure effects—to determine which interventions are most effective in tackling multi-faceted urban transport issues.

This paper examines the role that the two lead authors’ personal connections played in the research methodology and data collection for the Partition Stories project—a mixed-methods approach to rev...

Despite the importance of evaluating all mitigation options to inform policy decisions addressing climate change, a comprehensive analysis of household-scale interventions and their emissions reduction potential is missing. Here, we address this gap for interventions aimed at changing individual households’ use of existing equipment, such as monetary incentives or feedback. We have performed a machine learning-assisted systematic review and meta-analysis to comparatively assess the effectiveness of these interventions in reducing energy demand in residential buildings. We extracted 360 individual effect sizes from 122 studies representing trials in 25 countries. Our meta-regression confirms that both monetary and non-monetary interventions reduce the energy consumption of households, but monetary incentives, of the sizes reported in the literature, tend to show on average a more pronounced effect. Deploying the right combinations of interventions increases the overall effectiveness. We have estimated a global carbon emissions reduction potential of 0.35 GtCO2 yr−1, although deploying the most effective packages of interventions could result in greater reduction. While modest, this potential should be viewed in conjunction with the need for de-risking mitigation pathways with energy-demand reductions. Behavioural interventions can reduce energy consumption and hence carbon emissions among households. Khanna et al. compare the effectiveness of different types of monetary and non-monetary household interventions using a machine learning-assisted meta-analysis, and examine the situations where each is most useful.

Like the United States, both China and India have long grappled and continue to grapple with whether and how to create a meritocratic society in terms of educational, professional, and political opportunities. Though the notion of “merit” is contextually defined, the challenges of making meritocracy, of ensuring that persons with merit are rewarded, display striking similarities across time and space. Arguments for meritocracy are typically rooted in either ethical or efficiency reasoning. Both latent and engineered obstacles can undermine efforts to make meritocracy. The beneficiaries of privilege often reframe efforts to challenge their privilege as inherently unmeritocratic. But the experiences of making meritocracy in other contexts can provide important lessons for how these challenges can be addressed successfully, even if the final goal of a truly meritocratic society remains elusive.

America is not exceptional in the opportunities afforded by the making of meritocracy, or in the angst that it invokes. Similar sentiments have arisen in China and India, repeatedly, from ancient to contemporary times. It behooves us to learn from these societal experiments. This afterword reminds the reader that relative advantages, acquired through fair means or luck, are very persistent, and attempts to reset the proverbial table equally are incomplete and often backfire, intentions notwithstanding. Yet, optimistically, it is also possible to find seemingly immutable inequalities turning out to be quite mutable under targeted policy action. Future scholarship could usefully address many areas, including the use of technology to augment meritocracy in a practical sense while being sensitive to any notion of inadvertent techno-utopianism, including and especially for the blue-collar masses who are all but invisible in most of the discourses around meritocracy, in a poignant reminder of the point of this volume.

The interpretation of human genetic variation is one of the greatest challenges of modern genetics. New approaches are urgently needed to prioritize variants, especially those that are rare or lack a definitive clinical interpretation. We examined 10,136,597 human missense genetic variants from GnomAD, ClinVar and UniProt. We were able to perform large-scale atom-based mapping and phenotype interpretation of 3,960,015 of these variants onto 18,874 experimental and 84,818 in house predicted three-dimensional coordinates of the human proteome. We demonstrate that 14% of amino acid substitutions from the GnomAD database that could be structurally analysed are predicted to affect protein structure (n = 568,548, of which 566,439 rare or extremely rare) and may, therefore, have a yet unknown disease-causing effect. The same is true for 19.0% (n = 6266) of variants of unknown clinical significance or conflicting interpretation reported in the ClinVar database. The results of the structural analysis are available in the dedicated web catalogue Missense3D-DB (http://missense3d.bc.ic.ac.uk/). For each of the 4 M variants, the results of the structural analysis are presented in a friendly concise format that can be included in clinical genetic reports. A detailed report of the structural analysis is also available for the non-experts in structural biology. Population frequency and predictions from SIFT and PolyPhen are included for a more comprehensive variant interpretation. This is the first large-scale atom-based structural interpretation of human genetic variation and offers geneticists and the biomedical community a new approach to genetic variant interpretation.

This article examines the evolution of Indian pharmaceutical manufacturer Cipla toward producing drugs that met the quality standards of European and U.S. regulators. It employs new research in both Cipla's corporate archives and a wide range of oral histories. The article argues that, along with a long-standing corporate culture of self-reliance rooted in nationalism starting from the company's inception in 1935, major factors in Cipla's strategy from the 1960s through the early 2000s included the early adoption and continued use of quality-control technology, along with efforts to create global goodwill for affordable high-quality generic drugs during the HIV/AIDS epidemic of the early 2000s.

We exploit plausibly exogenous variation in the staggered entry of new managers into India’s 42 public R&D labs between 1994 and 2006 to study how alignment between the CEO and middle-level managers affects research productivity. We show that the introduction of new lab managers aligned with the national R&D reforms raised patenting and multinational licensing revenues by 58% and 75%, respectively, and scientist research productivity, including: a 16%, 10%, 11%, and 22% increase in h-indices, number of coauthors, publications, and citations per scientist, respectively. Using natural language processing techniques on the set of research abstracts produced among these scientists, we also find that overall mood and sentiment increased by 8.5% following the first managerial change. (JEL L22, L23, O32, O33)

We demonstrate how a novel synthesis of three methods — (1) unsupervised topic modeling of text data to generate new measures of textual variance, (2) sentiment analysis of text data, and (3) supervised ML coding of facial images with a cutting-edge convolutional neural network algorithm — can shed light on questions related to CEO oral communication. With videos and corresponding transcripts of interviews with emerging market CEOs, we employ this synthesis of methods to discover five distinct communication styles that incorporate both verbal and nonverbal aspects of communication. Our data are comprised of interviews that represent unedited expressions and content, making them especially suitable as data sources for the measurement of an individual’s communication style. We then perform a proof-of-concept analysis, correlating CEO communication styles to M&A outcomes, highlighting the value of combining text and videographic data to define styles. We also discuss the benefits of using our methods versus current research methods.

Internationalizing firms often find developing host-country resources challenging as they simultaneously attempt to replicate the resources that worked well in the home country and adapt them to fit the context of the host country. On the basis of a longitudinal study of the expansion of India-domiciled Narayana Health (NH), a tertiary healthcare provider, to the contextually distinct Cayman Islands, we propose a recombination-based internationalization model that allows us to offer a new conception of this replication–adaptation tradeoff. Recombination entails creating anew in the host country by drawing from, adapting, and integrating diverse resources developed earlier in heterogeneous settings in the home country. We theoretically explore the mechanisms underlying such recombination processes in organizational settings.

SummaryInfection with SARS-CoV-2 has a wide range of clinical presentations, from asymptomatic to life-threatening. Old age is the strongest factor associated with increased COVID19-related mortality, followed by sex and pre-existing conditions. The importance of genetic and immunological factors on COVID19 outcome is also starting to emerge, as demonstrated by population studies and the discovery of damaging variants in genes controlling type I IFN immunity and of autoantibodies that neutralize type I IFNs. The human protein transmembrane protease serine type 2 (TMPRSS2) plays a key role in SARS-CoV-2 infection, as it is required to activate the virus’ spike protein, facilitating entry into target cells. We focused on the only common TMPRSS2 non-synonymous variant predicted to be damaging (rs12329760), which has a minor allele frequency of ∼25% in the population. In a large population of SARS-CoV-2 positive patients, we show that this variant is associated with a reduced likelihood of developing severe COVID19 (OR 0.87, 95%CI:0.79-0.97, p=0.01). This association was stronger in homozygous individuals when compared to the general population (OR 0.65, 95%CI:0.50-0.84, p=1.3×10−3). We demonstrate in vitro that this variant, which causes the amino acid substitution valine to methionine, impacts the catalytic activity of TMPRSS2 and is less able to support SARS-CoV-2 spike-mediated entry into cells.TMPRSS2 rs12329760 is a common variant associated with a significantly decreased risk of severe COVID19. Further studies are needed to assess the expression of the TMPRSS2 across different age groups. Moreover, our results identify TMPRSS2 as a promising drug target, with a potential role for camostat mesilate, a drug approved for the treatment of chronic pancreatitis and postoperative reflux esophagitis, in the treatment of COVID19. Clinical trials are needed to confirm this.

UNSTRUCTURED In the wake of the COVID-19 pandemic, digital health tools have been deployed by governments around the world to advance clinical and population health objectives. Few interventions have been successful or have achieved sustainability or scale. In India, government agencies are proposing sweeping changes to India’s digital health architecture. Underpinning these initiatives is the assumption that mobile health solutions will find near universal acceptance and uptake, though the observed reticence of clinicians to use electronic health records suggests otherwise. In this practice article, we describe our experience with implementing a digital surveillance tool at a large mass gathering, attended by nearly 30 million people. Deployed with limited resources and in a dynamic chaotic setting, the adherence to human-centered design principles resulted in near universal adoption and high end-user satisfaction. Through this use case, we share generalizable lessons in the importance of contextual relevance, stakeholder participation, customizability, and rapid iteration, while designing digital health tools for individuals or populations.

Can accelerators and investors pick the most promising startup ideas no matter their provenance? We investigate this question using unique data from a global accelerator in which judges across international regions are randomly assigned to evaluate startups headquartered across the globe. Our analysis of this natural experiment shows that judges are less likely to recommend startups headquartered outside their home region by 4 percentage points. Additional information about a startup does not appear to attenuate this bias. Back-of-the-envelope calculations suggest that this discount leads judges to pass over 1 in 10 high-potential startups. Our results reveal that judges are able to discern high from low quality startups regardless of their origin, but they systematically discount foreign ideas relative to local ones.

BACKGROUND: The human protein transmembrane protease serine type 2 (TMPRSS2) plays a key role in SARS-CoV-2 infection, as it is required to activate the virus' spike protein, facilitating entry into target cells. We hypothesized that naturally-occurring TMPRSS2 human genetic variants affecting the structure and function of the TMPRSS2 protein may modulate the severity of SARS-CoV-2 infection.METHODS: We focused on the only common TMPRSS2 non-synonymous variant predicted to be damaging (rs12329760 C>T, p.V160M), which has a minor allele frequency ranging from 0.14 in Ashkenazi Jewish to 0.38 in East Asians. We analysed the association between the rs12329760 and COVID-19 severity in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units recruited as part of the GenOMICC (Genetics Of Mortality In Critical Care) study. Logistic regression analyses were adjusted for sex, age and deprivation index. For in vitro studies, HEK293 cells were co-transfected with ACE2 and either TMPRSS2 wild type or mutant (TMPRSS2 V160M). A SARS-CoV-2 pseudovirus entry assay was used to investigate the ability of TMPRSS2 V160M to promote viral entry. RESULTS: We show that the T allele of rs12329760 is associated with a reduced likelihood of developing severe COVID-19 (OR 0.87, 95%CI:0.79-0.97, p = 0.01). This association was stronger in homozygous individuals when compared to the general population (OR 0.65, 95%CI:0.50-0.84, p = 1.3 × 10 -3). We demonstrate in vitro that this variant, which causes the amino acid substitution valine to methionine, affects the catalytic activity of TMPRSS2 and is less able to support SARS-CoV-2 spike-mediated entry into cells. CONCLUSION: TMPRSS2 rs12329760 is a common variant associated with a significantly decreased risk of severe COVID-19. Further studies are needed to assess the expression of TMPRSS2 across different age groups. Moreover, our results identify TMPRSS2 as a promising drug target, with a potential role for camostat mesilate, a drug approved for the treatment of chronic pancreatitis and postoperative reflux esophagitis, in the treatment of COVID-19. Clinical trials are needed to confirm this.

Despite the importance of evaluating all mitigation options so as to inform policy decisions addressing climate change, a systematic analysis of household-scale interventions to reduce carbon emissions is missing. Here, we address this gap through a state-of-the-art machine-learning assisted meta-analysis to comparatively assess the effectiveness of a range of monetary and behavioral interventions in energy demand of residential buildings. We identify 122 studies and extract 360 effect sizes representing trials on 1.2 million households in 25 countries. We find that all the studied interventions reduce energy consumption of households. Our meta-regression evidences that monetary incentives are on an average more effective than behavioral interventions, but deploying the right combinations of interventions together can increase overall effectiveness. We estimate global cumulative emissions reduction of 8.64 Gt CO2 by 2040, though deploying the most effective packages and interventions could result in greater reduction. While modest, this potential should be viewed in conjunction with the need for de-risking mitigation with energy demand reductions and realizing substantial co-benefits.

New generators located far from consumption centers require transmission infrastructure and increase network losses. The primary objective of this paper is to study signals that affect the location of generation investment. Such signals result from the electricity market itself and from additional regulatory instruments. We cluster them into five groups: locational electricity markets, deep grid connection charges, grid usage charges, capacity mechanisms, and renewable energy support schemes. We review the use of instruments in twelve major power systems and discuss relevant properties, including a quantitative estimate of their strength. We find that most systems use multiple instruments in parallel, and none of the identified instruments prevails. The signals vary between locations by up to 20 EUR per MWh. Such a difference is significant when compared to the levelized costs of combined cycle plants of 64-72 EUR per MWh in Europe.

Mobile health (mHealth) and related digital health interventions in the past decade have not always scaled globally as anticipated earlier despite large investments by governments and philanthropic foundations. The implementation of digital health tools has suffered from 2 limitations: (1) the interventions commonly ignore the “law of amplification” that states that technology is most likely to succeed when it seeks to augment and not alter human behavior; and (2) end-user needs and clinical gaps are often poorly understood while designing solutions, contributing to a substantial decrease in usage, referred to as the “law of attrition” in eHealth. The COVID-19 pandemic has addressed the first of the 2 problems—technology solutions, such as telemedicine, that were struggling to find traction are now closely aligned with health-seeking behavior. The second problem (poorly designed solutions) persists, as demonstrated by a plethora of poorly designed epidemic prediction tools and digital contact-tracing apps, which were deployed at scale, around the world, with little validation. The pandemic has accelerated the Indian state’s desire to build the nation’s digital health ecosystem. We call for the inclusion of regulatory sandboxes, as successfully done in the fintech sector, to provide a real-world testing environment for mHealth solutions before deploying them at scale.

UNSTRUCTURED Mobile health (mHealth) and related digital health interventions in the past decade have not always scaled globally as anticipated earlier despite large investments by governments and philanthropic foundations. The implementation of digital health tools has suffered from 2 limitations: (1) the interventions commonly ignore the “law of amplification” that states that technology is most likely to succeed when it seeks to augment and not alter human behavior; and (2) end-user needs and clinical gaps are often poorly understood while designing solutions, contributing to a substantial decrease in usage, referred to as the “law of attrition” in eHealth. The COVID-19 pandemic has addressed the first of the 2 problems—technology solutions, such as telemedicine, that were struggling to find traction are now closely aligned with health-seeking behavior. The second problem (poorly designed solutions) persists, as demonstrated by a plethora of poorly designed epidemic prediction tools and digital contact-tracing apps, which were deployed at scale, around the world, with little validation. The pandemic has accelerated the Indian state’s desire to build the nation’s digital health ecosystem. We call for the inclusion of regulatory sandboxes, as successfully done in the fintech sector, to provide a real-world testing environment for mHealth solutions before deploying them at scale.

SARS-CoV-2 is a novel virus causing mainly respiratory, but also gastrointestinal symptoms. Elucidating the molecular processes underlying SARS-CoV-2 infection, and how the genetic background of an individual is responsible for the variability in clinical presentation and severity of COVID-19 is essential in understanding this disease.Cell infection by the SARS-CoV-2 virus requires binding of its Spike (S) protein to the ACE2 cell surface protein and priming of the S by the serine protease TMPRSS2. One may expect that genetic variants leading to a defective TMPRSS2 protein can affect SARS-CoV-2 ability to infect cells. We used a range of bioinformatics methods to estimate the prevalence and pathogenicity of TMPRSS2 genetic variants in the human population, and assess whether TMPRSS2 and ACE2 are co-expressed in the intestine, similarly to what is observed in lungs.We generated a 3D structural model of the TMPRSS2 extracellular domain using the prediction server Phyre and studied 378 naturally-occurring TMPRSS2 variants reported in the GnomAD database. One common variant, p.V160M (rs12329760), is predicted damaging by both SIFT and PolyPhen2 and has a MAF of 0.25. Valine 160 is a highly conserved residue within the SRCS domain. The SRCS is found in proteins involved in host defence, such as CD5 and CD6, but its role in TMPRSS2 remains unknown. 84 rare variants (53 missense and 31 leading to a prematurely truncated protein, cumulative minor allele frequency (MAF) 7.34×10−4) cause structural destabilization and possibly protein misfolding, and are also predicted damaging by SIFT and PolyPhen2 prediction tools. Moreover, we extracted gene expression data from the human protein atlas and showed that both ACE2 and TMPRSS2 are expressed in the small intestine, duodenum and colon, as well as the kidneys and gallbladder.The implications of our study are that: i. TMPRSS2 variants, in particular p.V160M with a MAF of 0.25, should be investigated as a possible marker of disease severity and prognosis in COVID-19 and ii. in vitro validation of the co-expression of TMPRSS2 and ACE2 in gastro-intestinal is warranted.

During the COVID-19 crisis, millions of migrants around the world face food insecurity This could force migrants to travel during the pandemic, exposing them t

We propose to examine how ideas are evaluated when innovators are diverse and the implications on organizational and individual-level outcomes. This question is timely because managers from more or...

Structural and thermodynamic properties as well as diffusion coefficients of binary fluid mixtures with asymmetry in mass, size, charge and their combinations have been studied using classical molecular dynamics simulations. The fluid mixture is modelled as spherical particles interacting via the Weeks–Chandler–Andersen and Coulomb potential. The diameter, charge and mass of the fluid particles are in the range 6–60 A, 1–10e and 1—500 amu, respectively. Systematic variations in pair-correlation functions, thermodynamic properties as well as the self-diffusion coefficient are found with the size, charge and mass ratio of the particles. The self-diffusion coefficient for systems having more than one type of asymmetry is calculated and expressed in terms of diffusion coefficients of systems with only one type of asymmetry.

Cardiovascular disease is the leading case of mortality from non-communicable diseases (NCD) in India. The government's National Programme for Prevention and Control of Cancer, Diabetes, Cardiovascular Diseases and Stroke seeks to increase capacity building, screening, referral and management of NCDs across India, and includes community-based outreach and screening programmes. The government in India routinely provides basic care at religious mass gatherings. However, in 2015, at the Kumbh Mela in Nashik and Trimbakeshwar, the state government extended its services to include a hypertension screening programme. We examine here the value and implications of such opportunistic screening at mass gatherings. At the Kumbh, 5760 persons voluntarily opted for hypertension screening, and received a single blood pressure measurement. In all, 1783 (33.6%) screened positive, of whom, 1580 were previously unaware of their diagnosis. Of the 303 that had previously known hypertension, 240 (79%) were prescribed medications, and 160 were compliant (that is, 52.8% under treatment). Fifty-five (18%) had normal blood pressure readings (BP under control). The data also demonstrated higher prevalence (39%) of hypertension among tobacco users compared to non-users (28%) (P

Research summary: Emerging markets are characterized by underdeveloped institutions and frequent environmental shifts. Yet, they also contain many firms that have survived over generations. How are firms in weak institutional environments able to persist over time? Motivated by 69 interviews with leaders of emerging market firms with histories spanning generations, we combine induction and deduction to propose reputation as a meta-resource that allows firms to activate their conventional resources. We conceptualize reputation as consisting of prominence, perceived quality, and resilience, and develop a process model that illustrates the mechanisms that allow reputation to facilitate survival in ways that persist over time. Building on research in strategy and business history, we thus shed light on an underappreciated strategic construct (reputation) in an undertheorized setting (emerging markets) over an unusual period (the historical long run). Managerial summary: Why are some firms able to persistently survive in challenging, uncertain, and underdeveloped business environments? To explore this question, we analyze in-depth interviews with leaders of emerging market firms that have survived over decades and even centuries. We find that firm reputation is a key strategic driver, and propose new ideas about the ways through which reputation facilitates survival. We elaborate how a favorable reputation allows a firm to more fully utilize its existing resources by decreasing uncertainty. We also propose that reputation has offensive and defensive properties that make it valuable to firms during both positive and negative economic cycles. Finally, we discuss why a reputation-based source of competitive advantage is hard to imitate, and outline three general approaches for building reputation. Copyright © 2017 John Wiley & Sons, Ltd.

This paper examines the role that the two lead authors’ personal connections played in the research methodology and data collection for the Partition Stories Project - a mixed methods approach to revisiting the much-studied historical trauma of the Partition of British India in 1947. The Project collected survivors’ oral histories, a data type that is a mainstay of qualitative research, and subjected their narrative data to statistical analysis to detect aggregated trends. In this paper, the authors discuss the process of straddling the dichotomies of insider/outsider and qualitative/quantitative, address the “myth of informed objectivity”, and the need for hybrid research structures with the intent to innovate in humanities projects such as this. In presenting key learnings from the project, this paper highlights the tensions that the authors faced between positivist and interpretivist methods of inquiry, between “insider” and “outsider” categories of positionality, and in the quantification of qualitative oral history data. The paper concludes with an illustrative example from one of the lead authors’ past research experiences to suggest that the tensions of this project are general in occurrence and global in applicability, beyond the specifics of the Partition case study explored here.

AimsTo explore the level of supervision between training and non-training posts at LSCFT.Background•Supervision is defined as ‘provision of guidance and feedback on matters of personal, professional and educational development in the context of a trainees' experience of providing safe and appropriate patient care’.•Along with the trainees, doctors working in non-training posts such as staff grade, specialty doctors, trust grade doctors (TJD)and MTI (Medical training initiative) doctors form an integral part of patient care in the NHS.Method•A mixed method approach was adopted with both qualitative and quantitative data collected simultaneously in the form of an online questionnaire.•An anonymous online questionnaire was sent to junior doctors currently in training and non-training posts at LSCFT in 2019 using Meridian software.Result1- Quantitative Data: - Participants included were doctors in training post such as Foundation Doctors (5), Psychiatry Core Trainees (6), GP STs (2) and doctors in non-training post such as TJD (4), Specialty Doctors (2) and MTI doctors (4). Based on the Meridian score, 84% of doctors were satisfied with the supervision. It was found that 72% of doctors received weekly supervisions, 10% monthly (1 TJD, 1 Foundation trainee) and16% bi-monthly (1 MTI, 1 SAS, 2 CTs). The data suggested that there was no difference in the frequency of supervisions between training and non-training posts at LSCFT.2- Qualitative Data: - The feedback was common as there was no major difference between training and non-training doctors. •Positives – WPBAs, discussion on reflections, management of complex cases and medication, personal issues affecting work.•Negatives – Limited discussion on QI, Audit, Research and Psychotherapy.- More specific help, need more support at times.Conclusion1.To prepare a checklist of contents to be discussed during supervision.2.To prepare a timeline chart of supervision.3.Preparing a ‘menu’ of QI projects that junior doctors can sign up to at the start of each post.4.To formulate training packages available to support junior doctors with QI/Audits.