On Surprise, Change, and the Effect of Recent Outcomes

The leading models of human and animal learning rest on the assumption that individuals tend to select the alternatives that led to the best recent outcomes. The current research highlights three boundaries of this “recency” assumption. Analysis of the stock market and simple laboratory experiments suggests that positively surprising obtained payoffs, and negatively surprising forgone payoffs reduce the rate of repeating the previous choice. In addition, all previous trails outcomes, except the latest outcome (most recent), have similar effect on future choices. We show that these results, and other robust properties of decisions from experience, can be captured with a simple addition to the leading models: the assumption that surprise triggers change

Towards a User Privacy-Aware Mobile Gaming App Installation Prediction Model

Over the past decade, programmatic advertising has received a great deal of attention in the online advertising industry. A real-time bidding (RTB) system is rapidly becoming the most popular method to buy and sell online advertising impressions. Within the RTB system, demand-side platforms (DSP) aim to spend advertisers' campaign budgets efficiently while maximizing profit, seeking impressions that result in high user responses, such as clicks or installs. In the current study, we investigate the process of predicting a mobile gaming app installation from the point of view of a particular DSP, while paying attention to user privacy, and exploring the trade-off between privacy preservation and model performance. There are multiple levels of potential threats to user privacy, depending on the privacy leaks associated with the data-sharing process, such as data transformation or de-anonymization. To address these concerns, privacy-preserving techniques were proposed, such as cryptographic approaches, for training privacy-aware machine-learning models. However, the ability to train a mobile gaming app installation prediction model without using user-level data, can prevent these threats and protect the users' privacy, even though the model's ability to predict may be impaired. Additionally, current laws might force companies to declare that they are collecting data, and might even give the user the option to opt out of such data collection, which might threaten companies' business models in digital advertising, which are dependent on the collection and use of user-level data. We conclude that privacy-aware models might still preserve significant capabilities, enabling companies to make better decisions, dependent on the privacy-efficacy trade-off utility function of each case.Comment: 11 pages, 3 figure

Heat Shock Factor 1-dependent extracellular matrix remodeling mediates the transition from chronic intestinal inflammation to colon cancer

In the colon, long-term exposure to chronic inflammation drives colitis-associated colon cancer (CAC) in patients with inflammatory bowel disease. While the causal and clinical links are well established, molecular understanding of how chronic inflammation leads to the development of colon cancer is lacking. Here we deconstruct the evolving microenvironment of CAC by measuring proteomic changes and extracellular matrix (ECM) organization over time in a mouse model of CAC. We detect early changes in ECM structure and composition, and report a crucial role for the transcriptional regulator heat shock factor 1 (HSF1) in orchestrating these events. Loss of HSF1 abrogates ECM assembly by colon fibroblasts in cell-culture, prevents inflammation-induced ECM remodeling in mice and inhibits progression to CAC. Establishing relevance to human disease, we find high activation of stromal HSF1 in CAC patients, and detect the HSF1-dependent proteomic ECM signature in human colorectal cancer. Thus, HSF1-dependent ECM remodeling plays a crucial role in mediating inflammation-driven colon cancer.R35 GM118173 - NIGMS NIH HHS; U01 TR002625 - NCATS NIH HHS; P30 CA008748 - NCI NIH HHS; FC010144 - Cancer Research UK; FC010144 - Medical Research Council; FC010144 - Wellcome TrustPublished versio

Isolation of novel PSII-LHCII megacomplexes from pea plants characterized by a combination of proteomics and electron microscopy

This work was supported by the Italian Ministry of Education, University and Research, “Futuro in Ricerca 2013” program RBFR1334SB to CP

Quantitative MR Analysis of Changes in the Radius Bone Marrow in Osteoporosis

Purpose. This pilot study aimed to explore the feasibility of scanning the human distal radius bone marrow in vivo to detect osteoporosis-related changes using magnetic resonance and evaluate whether the radius may serve as an accessible probing site for osteoporosis. This may lead in the future to the use of affordable means such as low-field MRI scanners for the monitoring of disease progression. Methods. A clinical trial was performed using a 3T MR scanner, including 26 women assigned into three study groups: healthy-premenopausal (n = 7; mean age 48.6 ± 3.5 years), healthy-postmenopausal (n = 10; mean age 54.5 ± 5.6 years), and osteoporotic-postmenopausal (n = 9; mean age 61.3 ± 5.6 years). Marrow fat composition was evaluated using T2 maps, a two-compartment model of T1, and a Dixon pulse sequence. Results. The osteoporotic group exhibited higher fat content than the other two groups and lower T2 values than the healthy-premenopausal group. Conclusions. Osteoporosis-related changes in the composition of the distal radius bone marrow may be detected in vivo using MRI protocols. The scanning protocols chosen here can later be repeated using low-field MRI scanners, thus offering the potential for early detection and treatment monitoring, using an accessible, affordable means that may be applied in small clinics. This trial is registered with MOH_2018-05-23_002247, NCT03742362

A Choice Prediction Competition for Market Entry Games: An Introduction

A choice prediction competition is organized that focuses on decisions from experience in market entry games (http://sites.google.com/site/gpredcomp/ and http://www.mdpi.com/si/games/predict-behavior/). The competition is based on two experiments: An estimation experiment, and a competition experiment. The two experiments use the same methods and subject pool, and examine games randomly selected from the same distribution. The current introductory paper presents the results of the estimation experiment, and clarifies the descriptive value of several baseline models. The experimental results reveal the robustness of eight behavioral tendencies that were documented in previous studies of market entry games and individual decisions from experience. The best baseline model (I-SAW) assumes reliance on small samples of experiences, and strong inertia when the recent results are not surprising. The competition experiment will be run in May 2010 (after the completion of this introduction), but they will not be revealed until September. To participate in the competition, researchers are asked to E-mail the organizers models (implemented in computer programs) that read the incentive structure as input, and derive the predicted behavior as an output. The submitted models will be ranked based on their prediction error. The winners of the competition will be invited to publish a paper that describes their model

Early reoperation following pancreaticoduodenectomy: impact on morbidity, mortality, and long-term survival

Abstract Background Reoperation following PD is a surrogate marker for a complex post-operative course and may lead to devastating consequences. We evaluate the indications for early reoperation following PD and analyze its effect on short- and long-term outcome. Methods Four hundred and thirty-three patients that underwent PD between August 2006 and June 2016 were retrospectively analyzed. Results Forty-eight patients (11%; ROp group) underwent 60 reoperations within 60 days from PD. Forty-two patients underwent 1 reoperation, and 6 had up to 6 reoperations. The average time to first reoperation was 10.1 ± 13.4 days. The most common indications were anastomotic leaks (22 operations in 18 patients; 37.5% of ROp), followed by post-pancreatectomy hemorrhage (PPH) (14 reoperations in 12 patients; 25%), and wound complications in 10 (20.8%). Patients with cholangiocarcinoma had the highest reoperation rate (25%) followed by ductal adenocarcinoma (12.3%). Reoperation was associated with increased length of hospital stay and a high post-operative mortality of 18.7%, compared to 2.6% for the non-reoperated group. For those who survived the post-operative period, the overall and disease-free survival were not affected by reoperation. Conclusions Early reoperations following PD carries a dramatically increased mortality rate, but has no impact on long-term survival