24 research outputs found
Surveys without Questions: A Reinforcement Learning Approach
The 'old world' instrument, survey, remains a tool of choice for firms to
obtain ratings of satisfaction and experience that customers realize while
interacting online with firms. While avenues for survey have evolved from
emails and links to pop-ups while browsing, the deficiencies persist. These
include - reliance on ratings of very few respondents to infer about all
customers' online interactions; failing to capture a customer's interactions
over time since the rating is a one-time snapshot; and inability to tie back
customers' ratings to specific interactions because ratings provided relate to
all interactions. To overcome these deficiencies we extract proxy ratings from
clickstream data, typically collected for every customer's online interactions,
by developing an approach based on Reinforcement Learning (RL). We introduce a
new way to interpret values generated by the value function of RL, as proxy
ratings. Our approach does not need any survey data for training. Yet, on
validation against actual survey data, proxy ratings yield reasonable
performance results. Additionally, we offer a new way to draw insights from
values of the value function, which allow associating specific interactions to
their proxy ratings. We introduce two new metrics to represent ratings - one,
customer-level and the other, aggregate-level for click actions across
customers. Both are defined around proportion of all pairwise, successive
actions that show increase in proxy ratings. This intuitive customer-level
metric enables gauging the dynamics of ratings over time and is a better
predictor of purchase than customer ratings from survey. The aggregate-level
metric allows pinpointing actions that help or hurt experience. In sum, proxy
ratings computed unobtrusively from clickstream, for every action, for each
customer, and for every session can offer interpretable and more insightful
alternative to surveys.Comment: The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19
Economics, Psychology, and Social Dynamics of Consumer Bidding in Auctions
With increasing numbers of consumers in auction marketplaces, we highlight some recent approaches that bring additional economic, social, and psychological factors to bear on existing economic theory to better understand and explain consumers' behavior in auctions. We also highlight specific research streams that could contribute towards enriching existing economic models of bidding behavior in emerging market mechanisms.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47034/1/11002_2005_Article_5901.pd
Subnational mapping of under-5 and neonatal mortality trends in India: the Global Burden of Disease Study 2000–17
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Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation
Combining Buy-In Penalties with Commissions at Auction Houses
Most auction sellers consign property to auction houses rather than holding the auction themselves. In addition to charging sellers a commission on property that sells in the auction, many auction houses also specify buy-in penalties in auction contracts. This is an amount the seller must pay the auction house if the property fails to sell at auction. An important managerial question for auction houses is whether and when buy-in penalties can increase revenues of the auction house, seller, or both, and what combinations of commission and buy-in penalty to use. We show that auctions which combine buy-in penalties with lower commissions Pareto-dominate auctions that use only commissions. This strategy motivates the seller to set a lower reserve, which creates a surplus in auction revenues that can go to one or both parties. This strategy is Pareto-dominant even if the auction house and the seller are uncertain about the number of bidders at the auction, or the auction house is uncertain about the seller's own valuation for the property, at the time the buy-in penalty, commission, and reserve are contractually set. We also discuss the incentive issues raised by this strategy.auctions, bidding, commissions, pricing, penalty
Dextran-Gated, Multifunctional Mesoporous Nanoparticle for Glucose-Responsive and Targeted Drug Delivery
Design of drug delivery nanocarrier
having targeted recognition followed by bioresponsive controlled release,
especially via glucose-responsive release, is a challenging issue.
Here, we report magnetic mesoporous silica (MMS)-based drug delivery
nanocarrier that can target specific cell and release drug via glucose-responsive
gate. The design involves synthesis of MMS functionalized with phenylboronic
acid and folate. After drug loading inside the pores of MMS, outside
of the pores are closed by dextran via binding with phenylboronic
acid. Dextran-gated pores are opened for drug release in the presence
of glucose that competes binding with phenylboronic acid. We found
that tolbutamide and camptothecin loaded MMS can target beta cells
and cancer cells, respectively, release drugs depending on bulk glucose
concentration and offers glucose concentration dependent cytotoxicity.
Developed functional MMS can be used for advanced drug delivery applications
for diabetes and cancers with more efficient therapy
β‑Cyclodextrin Functionalized Magnetic Mesoporous Silica Colloid for Cholesterol Separation
Although
cholesterol plays significant biochemical function in
the human body, excess of it leads to various disorders, and thus,
its control/separation is important in medical science and food industries.
However, efficient and selective separation of cholesterol is challenging
because cholesterol often exists in microheterogeneous or insoluble
forms in remote organ and exists with other chemicals/biochemicals.
Here, we have described a colloidal magnetic mesoporous silica (MMS)-based
approach for efficient separation of cholesterol in different forms.
MMS is functionalized with β-cyclodextrin for selective binding
with cholesterol via host–guest interaction. The colloidal
form of MMS offers effective interaction with cholesterol of any form,
and magnetic property of MMS offers easier separation of bound cholesterol.
Functionalized MMS is efficient in separating cholesterol crystals,
water-insoluble cholesterol, and the microheterogeneous form of cholesterol
from milk or a cellular environment. Developed material can be used
to remove cholesterol from a complex bioenvironment and extended for
large-scale cholesterol separation from food