Adversarial Unsupervised Representation Learning for Activity Time-Series

Sufficient physical activity and restful sleep play a major role in the prevention and cure of many chronic conditions. Being able to proactively screen and monitor such chronic conditions would be a big step forward for overall health. The rapid increase in the popularity of wearable devices provides a significant new source, making it possible to track the user's lifestyle real-time. In this paper, we propose a novel unsupervised representation learning technique called activity2vec that learns and "summarizes" the discrete-valued activity time-series. It learns the representations with three components: (i) the co-occurrence and magnitude of the activity levels in a time-segment, (ii) neighboring context of the time-segment, and (iii) promoting subject-invariance with adversarial training. We evaluate our method on four disorder prediction tasks using linear classifiers. Empirical evaluation demonstrates that our proposed method scales and performs better than many strong baselines. The adversarial regime helps improve the generalizability of our representations by promoting subject invariant features. We also show that using the representations at the level of a day works the best since human activity is structured in terms of daily routinesComment: Accepted at AAAI'19. arXiv admin note: text overlap with arXiv:1712.0952

Embarrassingly Simple MixUp for Time-series

Labeling time series data is an expensive task because of domain expertise and dynamic nature of the data. Hence, we often have to deal with limited labeled data settings. Data augmentation techniques have been successfully deployed in domains like computer vision to exploit the use of existing labeled data. We adapt one of the most commonly used technique called MixUp, in the time series domain. Our proposed, MixUp++ and LatentMixUp++, use simple modifications to perform interpolation in raw time series and classification model's latent space, respectively. We also extend these methods with semi-supervised learning to exploit unlabeled data. We observe significant improvements of 1\% - 15\% on time series classification on two public datasets, for both low labeled data as well as high labeled data regimes, with LatentMixUp++

Filling out the missing gaps: Time Series Imputation with Semi-Supervised Learning

Missing data in time series is a challenging issue affecting time series analysis. Missing data occurs due to problems like data drops or sensor malfunctioning. Imputation methods are used to fill in these values, with quality of imputation having a significant impact on downstream tasks like classification. In this work, we propose a semi-supervised imputation method, ST-Impute, that uses both unlabeled data along with downstream task's labeled data. ST-Impute is based on sparse self-attention and trains on tasks that mimic the imputation process. Our results indicate that the proposed method outperforms the existing supervised and unsupervised time series imputation methods measured on the imputation quality as well as on the downstream tasks ingesting imputed time series

Using Clinical Notes with Time Series Data for ICU Management

Monitoring patients in ICU is a challenging and high-cost task. Hence, predicting the condition of patients during their ICU stay can help provide better acute care and plan the hospital's resources. There has been continuous progress in machine learning research for ICU management, and most of this work has focused on using time series signals recorded by ICU instruments. In our work, we show that adding clinical notes as another modality improves the performance of the model for three benchmark tasks: in-hospital mortality prediction, modeling decompensation, and length of stay forecasting that play an important role in ICU management. While the time-series data is measured at regular intervals, doctor notes are charted at irregular times, making it challenging to model them together. We propose a method to model them jointly, achieving considerable improvement across benchmark tasks over baseline time-series model. Our implementation can be found at \url{https://github.com/kaggarwal/ClinicalNotesICU}.Comment: Accepted at EMNLP 201

Molecular Detection Method Developed to Track the Koinobiont Larval Parasitoid Apanteles opuntiarum (Hymenoptera: Braconidae) Imported from Argentina to Control Cactoblastis cactorum (Lepidoptera: Pyralidae)

Apanteles opuntiarum Martínez & Berta (Hymenoptera: Braconidae) is a native natural enemy of the cactus moth, Cactoblastis cactorum Berg (Lepidoptera: Pyralidae) in Argentina, where the 2 species are believed to have co-evolved. Cactoblastis cactorum is an established invasive pest in the US that is rapidly spreading throughout the southeast. Apanteles opuntiarum was imported from Argentina, and reared at the Division of Plant Industry containment facility in Gainesville, Florida, for study as a possible biocontrol agent for release in the US to control C. cactorum. A DNA barcode was developed to enable the identification of the reared parasitoid population. The mitochondrial cytochrome oxidase I (COI) gene of the A. opuntiarum reared in Florida containment was found to be identical to its Argentine founders, but distinctly different from the COI sequences of all other reported Apanteles species in the NCBI (National Center for Biotechnology Information) GenBank. Additionally, the AoF1 and AoR1 primer pair developed in this study specifically amplified the COI gene of A. opuntiarum, but did not amplify the COI gene of the host C. cactorum. Therefore, the COI gene fragment identified in this study has the potential to be used as a DNA barcode specific to A. opuntiarum that can aid in tracking and identifying this parasitoid inside hosts.Apanteles opuntiarum Martínez & Berta (Hymenoptera: Braconidae) es un enemigo natural de la polilla de la tuna Cactoblastis cactorum Berg (Lepidoptera: Pyralidae) en Argentina, su rango nativo, donde han co-evolucionado. Cactoblastis cactorum es una especie invasora establecida en Estados Unidos, que se está dispersando rápidamente hacia el sudeste de este país. Apanteles opuntiarum fue importado desde Argentina y es criado en la cuarentena de Gainesville, Florida (Division of Plant Industry), donde está siendo evaluado como posible agente de control de C. cactorum, para ser liberado en Estados Unidos. Se desarrolló un código de barras de ADN para permitir la identificación de la población de parasitoides criada. Se encontró que el gen de la citocromo oxidasa mitocondrial I (COI) de los A. opuntiarum criados en Florida fue idéntico al de sus fundadores argentinos, y claramente diferente de las secuencias de COI de todas las demás especies de Apanteles reportados en el GenBank del NCBI (Centro Nacional de información sobre biotecnología). Además, el par “primer” AoF1 y AoR1 desarrollado en este estudio amplificó específicamente el gen COI de A. opuntiarum, y no amplificó el gen de la COI del hospedador C. cactorum. Por lo tanto, el fragmento del gen COI identificado en este estudio tiene el potencial para ser utilizados como un código de barras de ADN específico para A. opuntiarum que puede ayudar en el seguimiento y la identificación de este parasitoide dentro de los hospedadoresFil: Srivastava, Mrittunjai. Florida Department of Agriculture and Consumer Services; Estados UnidosFil: Srivastava, Pratibha. Florida Department of Agriculture and Consumer Services; Estados UnidosFil: Karan, Ratna. Florida Department of Agriculture and Consumer Services; Estados UnidosFil: Jeyaprakash, Ayyamperumal. Florida Department of Agriculture and Consumer Services; Estados UnidosFil: Whilby, Leroy. Florida Department of Agriculture and Consumer Services; Estados UnidosFil: Rohrig, Eric. Florida Department of Agriculture and Consumer Services; Estados UnidosFil: Howe, Amy C.. Florida Department of Agriculture and Consumer Services; Estados UnidosFil: Hight, Stephen D.. United States Department of Agriculture. Agriculture Research Service; Estados UnidosFil: Varone, Laura. Fundación para el Estudio de Especies Invasivas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

A study of the neuroprotective role of Punica granatum and rosuvastatin in scopolamine induced cognitive deficit in rats

Background: The present work has been planned to find out the effect of Punica granatum and Rosuvastatin on learning and memory in Scopolamine induced cognitive deficits in rats. Scopolamine being an anticholinergic agent is used fervently in experimental models for memory deficits and has been widely implicated for the screening of cognitive dysfunction. Punica granatum (Pomegranate) has shown to suppress tumor neuronal cells, hence it can be a potential agent in providing neuroprotection for preventing the development and progression of AD. There are conflicting reports indicating the role of statins as a neuroprotective agent. This contradiction led us to investigate the effect of the role of Rosuvastatin on memory. The test agents were further compared to the standard treatment group acetylcholinesterase inhibitor i.e. Donepezil.Methods: Male wistar rats 150-200gms were divided into 4 groups of 6 rats each. Amnesia was induced by scopolamine 3mg/kg ip at day 5 in all the groups. Group1 (amnesic control) given distilled water; group 2(standard treatment i.e. Donepezil 0.5mg/kg orally); group 3(Rosuvastatin group10mg/kg orally); group 4 (Punica granatum juice 500mg/kg orally) The methods for validating cognition deficits were behavioural tests like Cook’s pole response and Passive Avoidance response.Results: It was evident from our research that the Punica granatum juice and Rosuvastatin effectively antagonized the scopolamine induced cognitive impairment in the paradigms studied. The neuroprotective effect of Punica granatum juice was better as compared to the Rosuvastatin group and the effects of the former were comparable with the standard treatment i.e. Donepezil group.Conclusions: Punica granatum has a remarkable protective role in memory function, learning, cognition and behavior in Scopolamine induced amnesia model of Alzheimer’s disease which was better than Rosuvastatin treatment

Microbial beta glucosidase enzymes: recent advances in biomass conversation for biofuels application

The biomass to biofuels production process is green, sustainable, and an advanced technique to resolve the current environmental issues generated from fossil fuels. The production of biofuels from biomass is an enzyme mediated process, wherein β-glucosidase (BGL) enzymes play a key role in biomass hydrolysis by producing monomeric sugars from cellulose-based oligosaccharides. However, the production and availability of these enzymes realize their major role to increase the overall production cost of biomass to biofuels production technology. Therefore, the present review is focused on evaluating the production and efficiency of β-glucosidase enzymes in the bioconversion of cellulosic biomass for biofuel production at an industrial scale, providing its mechanism and classification. The application of BGL enzymes in the biomass conversion process has been discussed along with the recent developments and existing issues. Moreover, the production and development of microbial BGL enzymes have been explained in detail, along with the recent advancements made in the field. Finally, current hurdles and future suggestions have been provided for the future developments. This review is likely to set a benchmark in the area of cost effective BGL enzyme production, specifically in the biorefinery area

Multifactorial Model and Treatment Approaches of Refractory Hypotension in a Patient Who Took an ACE Inhibitor the Day of Surgery

In the field of anesthesiology, there is wide debate on discontinuing angiotensin-converting enzyme inhibitor (ACEI) and angiotensin receptor blocker (ARB) therapy the day of noncardiac surgery. Although there have been many studies attributing perioperative hypotension to same-day ACEI and ARB use, there are many additional variables that play a role in perioperative hypotension. Additionally, restoring blood pressure in these patients presents a unique challenge to anesthesiologists. A case report is presented in which a patient took her ACEI the day of surgery and developed refractory hypotension during surgery. The evidence of ACEI use on the day of surgery and development of hypotension is reviewed, and additional variables that contributed to this hypotensive episode are discussed. Lastly, current challenges in restoring blood pressure are presented, and a basic model on treatment approaches for refractory hypotension in the setting of perioperative ACEI use is proposed