Search

The study examines the temporal trend in the gender gap in working hours in the US economy and analyses the possible reasons underlying the gender gap. The study uses American Time Use data for the period 2003–2021. It estimates truncated and quantile regression models to estimate the gender gap. The gender gap is decomposed into two components capturing the effect of characteristics and coefficients. The study finds evidence that gender differential in working hours across gender is stable in the current millennium. The gap is particularly high in highly remunerative jobs involving extended working hours, reflecting a glass ceiling for women. Further, differences in characteristics contribute only a minor proportion of the gender gap, indicating the possible influence of social attitudes and norms, and discriminatory organisational practices. The study argues in favor of policies to transform institutions, organisational work culture, and social norms about work-home balance. Incentivising firms to continue with flexible work schedules and work-from-home policies, extending family support and childcare arrangements, regulating work hours, and substituting overtime with part-time jobs are other ways to reduce the gender gap in work hours.

ABSTRACTThe main contribution of this paper is inspired by the question “Can six-phase doubly-fed induction generator (6-Φ-DFIG) work in unhealthy (with one or more phases open-circuited) conditions or not?”. The conventional DFIG cannot work under open-phase conditions, while the novel 6-Φ-DFIG can operate with one or more phases open-circuited. This paper addresses the mathematical and simulation-based modelling of the novel 6-Φ-DFIG operation under open-phase faults. Moreover, the advantages of the novel 6-Φ-DFIG are also illustrated in this paper. Simulation results validate the mathematical modelling of the novel 6-Φ-DFIG due to an open phase for the post-fault conditions. To the best of the authors’ knowledge, the proposed novel 6-Φ-DFIG has never been modelled and simulated for open-phase conditions anywhere in the world.

Despite the call for ensuring universal access to affordable, reliable, sustainable and modern energy by 2030, the dependence of households on biomass fuel remains high. Studies reveal that empowering women leads to a shift to clean fuel. But are all dimensions of empowerment equally important in influencing the shift to clean fuel? This study employs data from the fifth round of the nationally-representative National Family Health Survey (2019–21) to undertake a comparative assessment of the impact of different channels of empowerment on the adoption of clean fuel. Propensity score matching, nearest neighbourhood matching and control function methods were used to analyse the data. Dose response models were used to test for the sensitivity of results to variations in cut-offs defining binary empowerment categories. Empowered women are more likely to adopt clean fuel, with channels like work, financial autonomy and, possibly, education driving the adoption of clean fuel. Contextual factors (vegetation, average number of wet days and last-mile connectivity) also impact the use of biomass. The income shock of the lockdown to contain COVID led to greater reliance on biomass. Policies encouraging employment, financial autonomy and education of women are necessary to reduce the dependence on biomass. Energy poverty can be reduced by offering financial support for second cylinders and refills.

In this work, a computational fluid dynamics (CFD)-assisted optimization study has been carried out, implementing geometric design modifications in a biomass cook stove (BCS) to achieve uniform air–fuel distribution. The work has been divided into two parts. The first part deals with the numerical investigations of fluid phase hydrodynamics and air–fuel homogeneous phase combustion. Simulations have been performed for a wide range of air velocities to predict the roles of primary and secondary airflow in improving the spatial airflow uniformity inside the BCS. The homogeneous combustion simulations show linear dependence of power and temperature on the air velocity and air-to-fuel ratio. The results indicate that the most optimized power output and temperature values are achieved when the grate is placed at a height of 25 mm, and the orifice plate with 15 holes of 10 mm each is located at a height of 105 mm from the bottom of the cook stove.

The onset of COVID-19 in 2020 led to the closure of educational institutions and a shift to online teaching in India. It provides a natural experiment setting in which to examine the formation of endogenous ties among students and analyses the path-dependent nature of such a process. Information on sources of academic assistance was collected from members of two groups of students enrolled in the postgraduate course of the Economics Department of an Indian University using Google forms. The information was analysed using standard measures employed in social network analysis, such as sociograms, centrality measures, and homophily index. We show that, contrary to expectations, inheriting ties can constrain actors from forming ties that optimize outcomes.JEL Codes:D85, I20

In this study, we have developed a novel model to include the spatial heterogeneity for the combustion of volatiles in the presence of oxygen inside a biomass cookstove (BCS). Three-dimensional computational fluid dynamic simulations of BCS were done to evaluate the dynamics of spatial heterogeneity incurred during biomass combustion. The proposed methodology prescribes the mass release rate of the fuel as a dynamic boundary condition that evolves as per the changing temperature in the void spaces of the packed bed. The temporally evolving mass release rate due to the change in temperatures of the void spaces is calculated iteratively and set as the inlet boundary condition on the particle surfaces using an empirical correlation. The validation studies showed that the time-averaged outlet temperatures predicted from the model are in good agreement with the experimentally obtained values.

In many countries information on expectations collected through consumer confidence surveys are used in macroeconomic policy formulation. Unfortunately, before doing so, the consistency of responses is often not taken into account, leading to biases creeping in and, in turn, affecting the consistency of the indices hence created. This paper describes how latent class analysis may be used to check the consistency of responses and ensure parsimony in the questionnaire. In particular, we examine how temporal changes may be incorporated into the model. Our methodology is illustrated using three rounds of Consumer Confidence Survey (CCS) conducted by Reserve Bank of India (RBI).

Background:The optimal treatment strategy for managing Acute Myeloid Leukemia (AML) and the use of reliable and predictive biomarkers to guide selection of cytotoxic chemotherapy regimens among patients with diverse genomic profiles remain unmet needs in the clinic. The combination of MEC [mitoxantrone (MIT), etoposide (VP16), and cytarabine (ARA-C)] is a commonly used regimen for relapsed or refractory AML patients. Unfortunately, many patients do not respond to MEC, and which of the three drug agents matters most for each individual patient is not known. Predictors of response are needed urgently.

Background:Genomic heterogeneity in leukemic blasts characterizes Acute Myeloid Leukemia (AML) patients and is associated to variable drug response. However, use of genomics to guide therapy has generally been restricted to a single-gene approach, which rarely has sufficient predictive power to be clinically useful. Comprehensive DNA sequencing and biosimulation of the Computational Omics Biology Model (CBM) provide the opportunity and means of predicting treatment outcome in advance of treatment.

Castro: Caris Life Sciences Inc.: Consultancy; Guardant Health Inc.: Speakers Bureau; Bugworks: Consultancy; Cellworks Group Inc.: Current Employment; Omicure Inc: Consultancy; Exact sciences Inc.: Consultancy. Howard: Servier: Consultancy; Cellworks Group Inc.: Consultancy; Sanofi: Consultancy, Other: Speaker fees. Kumar: Cellworks Group Inc.: Current Employment. Patil: Cellworks Group Inc.: Current Employment. Khandelwal: Cellworks Group Inc.: Current Employment. Watson: BioAi Health: Consultancy, Membership on an entity's Board of Directors or advisory committees; AlloVir: Consultancy, Membership on an entity's Board of Directors or advisory committees; CellMax Life: Consultancy, Other: Advisor; Cellworks Group Inc.: Consultancy, Other: Advisor. Kapoor: Cellworks Group Inc.: Current Employment. Kumari: Cellworks Group Inc.: Current Employment. Prasad: Cellworks Group Inc.: Current Employment. Gupta: Cellworks Group Inc.: Current Employment. Lunkad: Cellworks Group Inc.: Current Employment. Mitra: Cellworks Group Inc.: Current Employment. G: Cellworks Group Inc.: Current Employment. Kumar: Cellworks Group Inc.: Current Employment. Choudhury: Cellworks Group Inc.: Current Employment. Kulkarni: Cellworks Group Inc.: Current Employment. Choudhary: Cellworks Group Inc.: Current Employment. Prakash: Cellworks Group Inc.: Current Employment. Husain: Cellworks Group Inc.: Current Employment. Ghosh: Cellworks Group Inc.: Current Employment. Narvekar: Cellworks Group Inc.: Current Employment. Amara: Cellworks Group Inc.: Current Employment. Yuvavani: Cellworks Group Inc.: Current Employment. Patel: Cellworks Group Inc.: Current Employment. Macpherson: Cellworks Group Inc.: Current Employment. Marcucci: Novartis: Other: Speaker and advisory scientific board meetings; Abbvie: Other: Speaker and advisory scientific board meetings; Agios: Other: Speaker and advisory scientific board meetings.

Marcucci: Novartis: Other: Speaker and advisory scientific board meetings; Agios: Other: Speaker and advisory scientific board meetings; Abbvie: Other: Speaker and advisory scientific board meetings. Kumar: Cellworks Group Inc.: Current Employment. Castro: Cellworks Group Inc.: Current Employment; Omicure Inc: Consultancy; Caris Life Sciences Inc.: Consultancy; Exact sciences Inc.: Consultancy; Bugworks: Consultancy; Guardant Health Inc.: Speakers Bureau. Grover: Cellworks Group Inc.: Current Employment. Patil: Cellworks Group Inc.: Current Employment. Alam: Cellworks Group Inc.: Current Employment. Azam: Cellworks Group Inc.: Current Employment. Mohapatra: Cellworks Group Inc.: Current Employment. Tyagi: Cellworks Group Inc.: Current Employment. Kumari: Cellworks Group Inc.: Current Employment. Prasad: Cellworks Group Inc.: Current Employment. Nair: Cellworks Group Inc.: Current Employment. Lunkad: Cellworks Group Inc.: Current Employment. Joseph: Cellworks Group Inc.: Current Employment. G: Cellworks Group Inc.: Current Employment. Chauhan: Cellworks Group Inc.: Current Employment. Basu: Cellworks Group Inc.: Current Employment. Behura: Cellworks Group Inc.: Current Employment. Ghosh: Cellworks Group Inc.: Current Employment. Husain: Cellworks Group Inc.: Current Employment. Mandal: Cellworks Group Inc.: Current Employment. Raman: Cellworks Group Inc.: Current Employment. Patel: Cellworks Group Inc.: Current Employment. Mundkur: Cellworks Group Inc: Current Employment. Christie: Cellworks Group Inc.: Current Employment. Macpherson: Cellworks Group Inc.: Current Employment. Howard: Servier: Consultancy; Cellworks Group Inc.: Consultancy; Sanofi: Consultancy, Other: Speaker fees.

In recent years theoretical and empirical are focussing on occupational health hazards in industries that deal with gemstone, lime, etc. In this paper the focus is on one such industry – coal.We seek to examine the nature and magnitude of occupational diseases in coal-mining. The socio-economic and technological factors determining the incidence of occupational diseases on workers is also identified using a Tobit model. Finally, the implications of the findings of this paper for designing an optimal health care strategy have been stated.The work is based on a survey of three coal mines in the state of West Bengal, India.

In recent years attention has been increasingly drawn to environmental problems caused by industrial and consumption activities. While theoretical and empirical literature has focused on mainly externalities generated by such activities, the effects of production on the workers may also be significant. Such health hazards are prominent in labour-intensive industries like gem cutting, limestone and mining. In this paper the focus is on the coal industry. The nature of coal mining is such that one would expect that the workers engaged in the mining process suffer from various ailments. This paper seeks to examine the magnitude of the burden in terms of health care expenditure caused by such hazards. The authors also seek to identify the factors determining the health care expenditure on workers. The work is based on a survey of three coal mines (using three different types of extraction technologies) in the state of West Bengal, India.

Singh: Cellworks Research India Private Limited: Employment. Sauban:Cellworks Research India Private Limited: Employment. Husain:Cellworks Research India Private Limited: Employment. Kumar:Cellworks Research India Private Limited: Employment. Kumari:Cellworks Research India Private Limited: Employment. Tyagi:Cellworks Research India Private Limited: Employment. Abbasi:Cell Works Group Inc.: Employment. Vali:Cell Works Group Inc.: Employment. Ailawadhi:Pharmacyclics: Research Funding; Takeda: Consultancy; Celgene: Consultancy; Amgen: Consultancy; Janssen: Consultancy.

Background: Multiple myeloma (MM) is characterized by the invasion of malignant plasma cells into the bone marrow. While first line treatment options result in significant clinical benefit to patients, spatiotemporal clonal evolution results in disease relapse and mortality. Advances in genomics have armed clinicians with unprecedented insight into the molecular architecture of MM cells, however, the clinical benefit derived by genomics-guided intervention has been limited. We present a novel computational biology modelling (CBM) tool, which takes into account the combinedeffect of individual mutations, gene copy number abnormalities and large scale chromosomal changes in order to predict the salient molecular pathways utilized by the MM cell for survival. By reverse-engineering MM cell architecture in silico, the CBM tool is able to predict drug response and resistance mechanisms. Thus, our aim was to determine the accuracy of the CBM tool in predicting treatment response of relapsed/refractory MM patients for future management of their disease, in a more individualized manner.

Background: Multiple myeloma (MM) is an incurable and heterogeneous haematological malignancy in which immune suppression and complex biology affect the disease and its response to treatment. Several new treatments have been approved for MM in recent years providing numerous options for patients with relapsed/refractory disease. However, there is no validated method for selecting the best treatment combination for each patient, making patient management difficult. The ability to predict treatment response based on disease characteristics could improve clinically outcomes.

Vij: Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Jazz Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharma: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Jansson: Honoraria, Membership on an entity's Board of Directors or advisory committees. Singh:Cellworks Research India Private Limited: Employment. Sauban:Cellworks Research India Private Limited: Employment. Husain:Cellworks Research India Private Limited: Employment. Lakshminarayana:Cellworks Research India Private Limited: Employment. Talawdekar:Cellworks Research India Private Limited: Employment. Mitra:Cellworks Research India Private Limited: Employment. Abbasi:Cell Works Group Inc.: Employment. Vali:Cell Works Group Inc.: Employment.