Early Churn Prediction from Large Scale User-Product Interaction Time Series

User churn, characterized by customers ending their relationship with a business, has profound economic consequences across various Business-to-Customer scenarios. For numerous system-to-user actions, such as promotional discounts and retention campaigns, predicting potential churners stands as a primary objective. In volatile sectors like fantasy sports, unpredictable factors such as international sports events can influence even regular spending habits. Consequently, while transaction history and user-product interaction are valuable in predicting churn, they demand deep domain knowledge and intricate feature engineering. Additionally, feature development for churn prediction systems can be resource-intensive, particularly in production settings serving 200m+ users, where inference pipelines largely focus on feature engineering. This paper conducts an exhaustive study on predicting user churn using historical data. We aim to create a model forecasting customer churn likelihood, facilitating businesses in comprehending attrition trends and formulating effective retention plans. Our approach treats churn prediction as multivariate time series classification, demonstrating that combining user activity and deep neural networks yields remarkable results for churn prediction in complex business-to-customer contexts.Comment: 12 pages, 3 tables, 8 figures, Accepted in ICML

Deep learning reconstruction of sunspot vector magnetic fields for forecasting solar storms

Solar magnetic activity produces extreme solar flares and coronal mass ejections, which pose grave threats to electronic infrastructure and can significantly disrupt economic activity. It is therefore important to appreciate the triggers of explosive solar activity and develop reliable space-weather forecasting. Photospheric vector-magnetic-field data capture sunspot magnetic-field complexity and can therefore improve the quality of space-weather prediction. However, state-of-the-art vector-field observations are consistently only available from Solar Dynamics Observatory/Helioseismic and Magnetic Imager (SDO/HMI) since 2010, with most other current and past missions and observational facilities such as Global Oscillations Network Group (GONG) only recording line-of-sight (LOS) fields. Here, using an inception-based convolutional neural network, we reconstruct HMI sunspot vector-field features from LOS magnetograms of HMI as well as GONG with high fidelity (~ 90% correlation) and sustained flare-forecasting accuracy. We rebuild vector-field features during the 2003 Halloween storms, for which only LOS-field observations are available, and the CNN-estimated electric-current-helicity accurately captures the observed rotation of the associated sunspot prior to the extreme flares, showing a striking increase. Our study thus paves the way for reconstructing three solar cycles worth of vector-field data from past LOS measurements, which are of great utility in improving space-weather forecasting models and gaining new insights about solar activity.Comment: 19 Pages, 11 Figures, Accepted for publication in Ap

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

Time-dependent perturbation theory with a classical limit

We construct a quantum mechanical perturbation theory which uses the multiple time scale technique. Working with the time translation operator, we use a variant on the method of Bender and Bettencourt. Our perturbation theory smoothly crosses over to the classical result as h→0. It is seen that this technique has a nonperturbative element built into it

Vulnerabilities In Cognitive Radio Networks: A Survey

Cognitive radio networks are envisioned to drive the next generation wireless networks that can dynamically optimize spectrum use. However, the deployment of such networks is hindered by the vulnerabilities that these networks are exposed to. Securing communications while exploiting the flexibilities offered by cognitive radios still remains a daunting challenge. In this survey, we put forward the security concerns and the vulnerabilities that threaten to plague the deployment of cognitive radio networks. We classify various types of vulnerabilities and provide an overview of the research challenges. We also discuss the various techniques that have been devised and analyze the research developments accomplished in this area. Finally, we discuss the open research challenges that must be addressed if cognitive radio networks were to become a commercially viable technology. © 2013 Elsevier B.V. All rights reserved

Bare-carbon-ion-impact electron emission from adenine molecules: Differential and total cross-section measurements

Double-differential ionization cross sections (DDCS) for bare-carbon-ion-induced ionization of vapor-phase adenine molecules (C5H5N5) have been measured. The experiment has been performed using an electron spectroscopy technique. Electrons ejected from adenine were analyzed by a hemispherical electrostatic deflection analyzer over an energy range of 1-450eV for emission angles from 20 to 160. The single-differential cross section (SDCS) and total ionization cross section were also deduced. The experimental results have been compared with the continuum distorted wave-eikonal initial-state model calculation. We have observed a very good agreement between the theory and experiment. The angular distribution of the DDCS, SDCS and the asymmetry parameter for low-energy (Ee≤0.5 a.u.) electron display an oscillatory behavior which is in contrast to that observed in ion-atom collisions. A comparison is also made with available experimental cross-section results for uracil target colliding with the same velocity bare carbon ions and the scalability of ionization cross sections among these molecules is discussed.Fil: Bhattacharjee, Shamik. International Centre Of Theoretical Science. Tata Institute Of Fundamental Research; EspañaFil: Bagdia, Chandan. International Centre Of Theoretical Science. Tata Institute Of Fundamental Research; EspañaFil: Chowdhury, Madhusree Roy. International Centre Of Theoretical Science. Tata Institute Of Fundamental Research; EspañaFil: Mandal, Anuvab. International Centre Of Theoretical Science. Tata Institute Of Fundamental Research; EspañaFil: Monti, Juan Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Física de Rosario. Universidad Nacional de Rosario. Instituto de Física de Rosario; ArgentinaFil: Rivarola, Roberto Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Física de Rosario. Universidad Nacional de Rosario. Instituto de Física de Rosario; ArgentinaFil: Tribedi, Lokesh C.. International Centre Of Theoretical Science. Tata Institute Of Fundamental Research; Españ

The Combined Efficacy of Neural Mobilization with Transcutaneous Electrical Nerve Stimulation (TENS) Versus Neural Mobilization alone for the Management of Cervical Radiculopathy

Background: Cervical radiculopathy occurs annually in 85 out of 100,000 people. It is very disabling and interferes with the ADL of the patients. Many studies had shown the effectiveness of neural mobilization and TENS in reduction of pain and disability in patients with cervical Radiculopathy. But there are less documented studies that had shown the combined effect of neural mobilization and TENS and effectiveness of both over only neural mobilization in patients with cervical radiculopathy. Methods: 30 male and female subjects were assessed as cervical radiculopathy and selected for the study. This includes unilateral cervical radiculopathy. They were categorized randomly into two groups as group receiving neural mobilization and TENS (experimental group I) and group receiving only neural mobilization (experimental group II) with 15 patients in each group. Assessment was taken using VAS and NDI prior to treatment. Treatment was continued for 14 days and at the end of 14 days patients were reassessed using the same scales. Results: Group 1 receiving both the treatments had shown more significant reduction in pain and disability compared to Group 2 receiving only neural mobilization after 14 days of treatment. Conclusion: Both neural mobilization and TENS are effective in reduction of pain and disability in patients with cervical radiculopathy. And when compared, combined treatment is more effective than only neural mobilization

EFFICACY OF MODIFIED PROPRIOCEPTIVE NEUROMUSCULAR FACILITATION STRETCHING WITH CRYOTHERAPY OVER MANUAL PASSIVE STRETCHING WITH CRYOTHERAPY ON HAMSTRING FLEXIBILITY

Background: Healthy individuals, to ease and accomplish their activities of daily living they need flexible body without any tightness in the muscles, particularly those used for a definite function. Cooling soft tissues in a lengthened position after stretching has been shown to promote more lasting increases in soft tissue length and minimize post stretch muscle soreness. There are less documented studies which compared modified proprioceptive neuromuscular facilitation (PNF) stretch over passive manual stretch with cold application commonly after the interventions. Methods: Thirty high school going healthy students were divided into two groups- Group I received Passive Manual stretching (n=15) and Group II received modified PNF stretching (n=15) and both groups received cold application after the interventions for 10 minutes commonly for 5 days. ROM was taken on day 1, day 5 and day 7. Results: After day 7, Group II with Modified PNF stretching along with cold application showed a significant increase in range of motion tested with active knee extension test (AKET). Conclusion: Modified PNF stretching is considered to be the effective intervention in increasing and maintaining ROM in AKET over passive manual stretching with cold applications commonly after the interventions