Bondage in freedom : colonial plantations in southern India, c. 1797-1947

Opposing views persist with regard to the emergence of plantations in southern India and the transfer of slave labour to these plantations: the abolition of slavery as an end in itself and, second, as a means to an end. In spite of the fact that slavery had been abolished by the mid-nineteenth century, workers on plantations found themselves no better off than slaves and bondsmen - so intensive and painful was the ill treatment meted out to them. The workers with their newly realised freedom from the feudal relations spared no means to revolt against the new Masters. Yet, a truly systemic transformation failed to materialise. The present paper attempts to unravel the constituents of changing forms of bondage and the coercive/disciplinary strategies adopted by the planters which in effect gave rise to a new labour regime. It also attempts to unravel the way in which the reborn ‘slaves’ unleashed their resistance at the capitalist work sites. JEL Classification: B25, N30, N50, N55 Key Words: slavery, plantations, colonial state, punishment, labour, outbursts

Beliefs and expertise in sequential decision making

This work explores a sequential decision making problem with agents having diverse expertise and mismatched beliefs. We consider an N-agent sequential binary hypothesis test in which each agent sequentially makes a decision based not only on a private observation, but also on previous agents’ decisions. In addition, the agents have their own beliefs instead of the true prior, and have varying expertise in terms of the noise variance in the private signal. We focus on the risk of the last-acting agent, where precedent agents are selfish. Thus, we call this advisor(s)-advisee sequential decision making. We first derive the optimal decision rule by recursive belief update and conclude, counterintuitively, that beliefs deviating from the true prior could be optimal in this setting. The impact of diverse noise levels (which means diverse expertise levels) in the two-agent case is also considered and the analytical properties of the optimal belief curves are given. These curves, for certain cases, resemble probability weighting functions from cumulative prospect theory, and so we also discuss the choice of Prelec weighting functions as an approximation for the optimal beliefs, and the possible psychophysical optimality of human beliefs. Next, we consider an advisor selection problem where in the advisee of a certain belief chooses an advisor from a set of candidates with varying beliefs. We characterize the decision region for choosing such an advisor and argue that an advisee with beliefs varying from the true prior often ends up selecting a suboptimal advisor, indicating the need for a social planner. We close with a discussion on the implications of the study toward designing artificial intelligence systems for augmenting human intelligence.https://arxiv.org/abs/1812.04419First author draf

Beliefs in Decision-Making Cascades

This work explores a social learning problem with agents having nonidentical noise variances and mismatched beliefs. We consider an $N$-agent binary hypothesis test in which each agent sequentially makes a decision based not only on a private observation, but also on preceding agents' decisions. In addition, the agents have their own beliefs instead of the true prior, and have nonidentical noise variances in the private signal. We focus on the Bayes risk of the last agent, where preceding agents are selfish. We first derive the optimal decision rule by recursive belief update and conclude, counterintuitively, that beliefs deviating from the true prior could be optimal in this setting. The effect of nonidentical noise levels in the two-agent case is also considered and analytical properties of the optimal belief curves are given. Next, we consider a predecessor selection problem wherein the subsequent agent of a certain belief chooses a predecessor from a set of candidates with varying beliefs. We characterize the decision region for choosing such a predecessor and argue that a subsequent agent with beliefs varying from the true prior often ends up selecting a suboptimal predecessor, indicating the need for a social planner. Lastly, we discuss an augmented intelligence design problem that uses a model of human behavior from cumulative prospect theory and investigate its near-optimality and suboptimality.Comment: final version, to appear in IEEE Transactions on Signal Processin

On the information theory of clustering, registration, and blockchains

Progress in data science depends on the collection and storage of large volumes of reliable data, efficient and consistent inference based on this data, and trusting such computations made by untrusted peers. Information theory provides the means to analyze statistical inference algorithms, inspires the design of statistically consistent learning algorithms, and informs the design of large-scale systems for information storage and sharing. In this thesis, we focus on the problems of reliability, universality, integrity, trust, and provenance in data storage, distributed computing, and information processing algorithms and develop technical solutions and mathematical insights using information-theoretic tools. In unsupervised information processing we consider the problems of data clustering and image registration. In particular, we evaluate the performance of the max mutual information method for image registration by studying its error exponent and prove its universal asymptotic optimality. We further extend this to design the max multiinformation method for universal multi-image registration and prove its universal asymptotic optimality. We then evaluate the non-asymptotic performance of image registration to understand the effects of the properties of the image transformations and the channel noise on the algorithms. In data clustering we study the problem of independence clustering of sources using multivariate information functionals. In particular, we define consistent image clustering algorithms using the cluster information, and define a new multivariate information functional called illum information that inspires other independence clustering methods. We also consider the problem of clustering objects based on labels provided by temporary and long-term workers in a crowdsourcing platform. Here we define budget-optimal universal clustering algorithms using distributional identicality and temporal dependence in the responses of workers. For the problem of reliable data storage, we consider the use of blockchain systems, and design secure distributed storage codes to reduce the cost of cold storage of blockchain ledgers. Additionally, we use dynamic zone allocation strategies to enhance the integrity and confidentiality of these systems, and frame optimization problems for designing codes applicable for cloud storage and data insurance. Finally, for the problem of establishing trust in computations over untrusting peer-to-peer networks, we develop a large-scale blockchain system by defining the validation protocols and compression scheme to facilitate an efficient audit of computations that can be shared in a trusted manner across peers over the immutable blockchain ledger. We evaluate the system over some simple synthetic computational experiments and highlights its capacity in identifying anomalous computations and enhancing computational integrity

Effect of Heat Stress on Milk Production and Composition in Murrah Buffaloes

Temperature humidity index (THI) is widely used to assess the effect of temperature and relative humidity on performance in animals. In summer the THI was between 74 - 89 with average value of 81.18. in winter months THI ranged between 49 -70 with the average of 60. The results showed a significant effect of heat stress on daily milk yield and milk composition. In the present study the daily milk yield decreases from 4.46 to 3.65kg, heat stress reduced milk yield by 18.2%. There was a significant effect of heat stress on milk composition. Heat stress significantly reduced milk fat content from 8.3% during the winter to 7.19% during the summer. Milk protein percentage significantly decreased as a result of summer heat stress (3.08 vs.2.9 %, respectively for the winter and summer). In the present study the SNF decreases from 9.08 to 9.05 %, heat stress reduced SNF % as the THI value went from > 74 to  83 in summer. Results showed that milk production is a function of THI. The negative slope of regression line indicates that milk production fat%, protein% and SNF% decreases as THI increases. This regression indicates that in general for each point increase in THI value. There was decrease in milk yield of 0.028kg per buffalo per day. Heat stress environments have been associated with depression in milk fat%, protein% and SNF%. There was decrease in milk fat of 0.046% per buffalo per day. There was also decrease in milk protein of 0.00014 % per buffalo per day. The decrease in milk SNF of 0.0047 % per buffalo per day

Effect of Year, Season and Parity on Milk Production Traits in Murrah Buffaloes

Effects of year, season and parity on total lactation milk yield (TLMY), 305 day milk yield (305d MY) and average fat percentage for Murrah buffaloes maintained at dairy farm under GADVASU, Ludhiana, Punjab, during 2004-2008 were evaluated. Averaged TLMY, 305d MY and Fat percentage were 2191.8± 93.7 kg, 2091.1±87.06 kg and 7.12±0.11%. TLMY was found to be significantly affected by season (P<0.05) but not by year and parity. The highest milk yield was obtained in animals calving in winter followed by rainy and summer. Milk yield of buffaloes in winter was significantly higher than that of animals in summer (P<0.05). The TLMY increased over the years with highest milk yield in the year 2006 (2345.1±99.32kg). There was no consistent increase or decrease with the advance in years there on which may be due to the environmental variation in different years. TLMY was found lower in first parity and highest in fifth parity thereof decreasing (P<0.05). Similar results were obtained for 305d MY, where only the season was found significant (P<0.05). The average fat percentage was significantly affected by year and season (p<0.05). Milk fat percentage of buffaloes calved in winter was significantly (P<0.05) higher than that of the animals calved in summer. Similarly the fat percentage varied significantly among the parities with no consistent increase over the advancement of the parities

Vocational Education and Training Reform in India: Business Needs in India and Lessons to be Learned from Germany. Working paper

India is among the countries with the lowest proportion of trained youth in the world. Even worse, vocational education in secondary schools has received very limited funding since the mid-1980s;nit has remained non-aspirational, of poor quality and involves little industry collaboration. The Vocational Education and Training (VET) system in Germany, in contrast, shows a much higher proportion of youth participation, more intense involvement of the private sector and is anchored in the law

Extracorporeal Cardiopulmonary Resuscitation

ECMO, or extracorporeal membrane oxygenation, is an advanced life support technique that provides cardiac and pulmonary support similar to cardiopulmonary bypass. ECPR (extracorporeal cardiopulmonary resuscitation) is the rapid deployment of VA-ECMO when conventional cardiopulmonary resuscitation fails to provide return of spontaneous circulation. Evidence in the literature is sparse, but with expanding reported applications, ECPR has shown promise to improve outcomes of cardiac arrest. ECPR is superior to conventional CPR for both survival and neurologic outcomes. ECPR has been successfully used to manage arrests secondary to cardiac and non-cardiac causes. Arrests secondary to primary cardiac causes have the best overall outcome. Other determinants of outcomes of ECPR include duration of low flow state and on-ECMO complications. A narrow list of ECPR contraindications exists, and includes severe neurologic injury and irreversible primary disease process. Various complications can occur with ECPR, and include mechanical, cardiovascular, pulmonary, hematologic, renal, and neurologic complications. Neurologic complications are the most serious, and significantly affect mortality or quality of life. ECPR is a nascent field, and substantial work remains to be done to optimize its application. Given the small number of patients at each institutional level, this is a field ripe for collaborative work and rewarding results