Model-agnostic Fits for Understanding Information Seeking Patterns in Humans

In decision making tasks under uncertainty, humans display characteristic biases in seeking, integrating, and acting upon information relevant to the task. Here, we reexamine data from previous carefully designed experiments, collected at scale, that measured and catalogued these biases in aggregate form. We design deep learning models that replicate these biases in aggregate, while also capturing individual variation in behavior. A key finding of our work is that paucity of data collected from each individual subject can be overcome by sampling large numbers of subjects from the population, while still capturing individual differences. In addition, we can predict human behavior with high accuracy without making any assumptions about task goals, reward structure, or individual biases, thus providing a model-agnostic fit to human behavior in the task. Such an approach can sidestep potential limitations in modeler-specified inductive biases, and has implications for computational modeling of human cognitive function in general, and of human-AI interfaces in particular.Comment: 8 pages, 9 figures. AAAI 202

Resources and Evaluations for Multi-Distribution Dense Information Retrieval

We introduce and define the novel problem of multi-distribution information retrieval (IR) where given a query, systems need to retrieve passages from within multiple collections, each drawn from a different distribution. Some of these collections and distributions might not be available at training time. To evaluate methods for multi-distribution retrieval, we design three benchmarks for this task from existing single-distribution datasets, namely, a dataset based on question answering and two based on entity matching. We propose simple methods for this task which allocate the fixed retrieval budget (top-k passages) strategically across domains to prevent the known domains from consuming most of the budget. We show that our methods lead to an average of 3.8+ and up to 8.0 points improvements in Recall@100 across the datasets and that improvements are consistent when fine-tuning different base retrieval models. Our benchmarks are made publicly available.Comment: REML @ SIGIR 2023; 9 pages, 8 figure

Nephrocutaneous fistula due to textiloma with in the pelvicalyceal system

Textiloma or gossypiboma is an embarrassing surgical scenario. Nephrocutaneous fistula is itself a rare complication after renal surgeries, but due to textiloma, it is rarest of the rare. In this case, 30-year-old lady presented with the complaints of chronic seropurulent discharge from a wound on her right lumbar region. On exploration it was found to be a retained surgical sponge in pelvicalyceal system, which was there for last seven years

Nutritional Studies and Antioxidant Profile of Pickled Oyster Mushrooms of North East India

Mushroom is a very popular food that is consumed around the globe yet it finds very limited acceptance in India, that too mainly among the elite. Non-availability of mushrooms around the year and its highly perishable nature makes it an expensive commodity for the common people to afford. Hence pickling may be viewed as a method to increase the shelf life of oyster mushrooms from 4-7 days under refrigerated condition to at least up to 12 months at room temperature. Hence a recipe for pickling of mushrooms using Indian spices was formulated so as to suit the Indian palate. The proximate analysis, calorific value, mineral and fatty acid profile along with antioxidant profile of the mushroom pickle was elucidated. Sensory parameters and shelf life and stability determining data like pH, titratable acidity and microbiological profile of the pickle was also performed. Finally it was observed that the mushroom pickle formulation has a shelf life of at least 12 months at room temperature with an overall acceptability (OAA) score above ‘very good’ mark

Cadmium induces lung inflammation independent of lung cell proliferation: a molecular approach

<p>Abstract</p> <p>Background</p> <p>Cadmium is one of the inflammation-related xenobiotics and has been regarded as a potent carcinogen. The relationship between inflammation and cell proliferation due to chronic infection has been studied, but the mechanism is not fully clear. Though the mode of cadmium toxicity is well characterized in animal cells, still it requires some further investigations. Previously we reported that cadmium induces immune cell death in Swiss albino mice. In the present study we showed that instead of inducing cell death mechanism, cadmium in low concentration triggers proliferation in mice lung cell and our results reveals that prior to the induction of proliferation it causes severe inflammation.</p> <p>Methods</p> <p>Swiss albino mice were treated with different concentrations of cadmium to determine the LD50. Mice were subdivided (5 mice each) according to the exposure period (15, 30, 45, 60 days) and were given sub lethal dose (5 mg/Kg body weight) of cadmium chloride and ibuprofen (50 mg/Kg body weight, recommended dose) once in a week. SEM and histology were performed as evidence of changes in cellular morphology. Inflammation was measured by the expression of Cox-2 and MMPs. Expression of proinflammatory cytokines (Cox-2, IL-6), signaling and cell cycle regulatory molecules (STAT3, Akt, CyclinD1) were measured by western blot, ELISA and immunoprecipitation. Mutagenecity was evidenced by comet assay. Cell proliferation was determined by cell count, cell cycle and DNA analysis.</p> <p>Results</p> <p>Prolonged exposure of low concentration of cadmium resulted in up regulation of proinflammatory cytokines and cell cycle regulatory molecules. Though NSAIDs like Ibuprofen reduces the expression of inflammatory cytokines, but it did not show any inhibitory effect on cadmium adopted lung cell proliferation.</p> <p>Conclusion</p> <p>Our results prove that cadmium causes both inflammation and cell proliferation when applied in a low dose but proliferative changes occur independent of inflammation.</p