Efficacy of Feedforward and LSTM Neural Networks at Predicting and Gap Filling Coastal Ocean Timeseries: Oxygen, Nutrients, and Temperature

Ocean data timeseries are vital for a diverse range of stakeholders (ranging from government, to industry, to academia) to underpin research, support decision making, and identify environmental change. However, continuous monitoring and observation of ocean variables is difficult and expensive. Moreover, since oceans are vast, observations are typically sparse in spatial and temporal resolution. In addition, the hostile ocean environment creates challenges for collecting and maintaining data sets, such as instrument malfunctions and servicing, often resulting in temporal gaps of varying lengths. Neural networks (NN) have proven effective in many diverse big data applications, but few oceanographic applications have been tested using modern frameworks and architectures. Therefore, here we demonstrate a “proof of concept” neural network application using a popular “off-the-shelf” framework called “TensorFlow” to predict subsurface ocean variables including dissolved oxygen and nutrient (nitrate, phosphate, and silicate) concentrations, and temperature timeseries and show how these models can be used successfully for gap filling data products. We achieved a final prediction accuracy of over 96% for oxygen and temperature, and mean squared errors (MSE) of 2.63, 0.0099, and 0.78, for nitrates, phosphates, and silicates, respectively. The temperature gap-filling was done with an innovative contextual Long Short-Term Memory (LSTM) NN that uses data before and after the gap as separate feature variables. We also demonstrate the application of a novel dropout based approach to approximate the Bayesian uncertainty of these temperature predictions. This Bayesian uncertainty is represented in the form of 100 monte carlo dropout estimates of the two longest gaps in the temperature timeseries from a model with 25% dropout in the input and recurrent LSTM connections. Throughout the study, we present the NN training process including the tuning of the large number of NN hyperparameters which could pose as a barrier to uptake among researchers and other oceanographic data users. Our models can be scaled up and applied operationally to provide consistent, gap-free data to all data users, thus encouraging data uptake for data-based decision making

Firm-specific intangible assets and subsidiary profitability: the moderating role of distance, ownership strategy and subsidiary experience

How does distance attenuate the value of MNC parent intangible assets on affiliate profitability? Beyond the basic assumption of internalization theory about the positive relationship between parent intangibles and foreign affiliate performance, we test how this relationship, is contingent on ownership strategy, subsidiary experience, and is moderated by the distance between home and host economies, in terms of differences in technological capacity, intellectual property regimes, economic development, language and geography. Based on newly-available accounting data on intangible assets, we test hypotheses on a sample of over 2000 multinationals and 5000 of their overseas affiliates in 45 home and host economies

Male breast cancer: is the scenario changing

<p>Abstract</p> <p>Background</p> <p>The overall incidence of male breast cancer is around 1% of all breast cancers and is on the rise. In this review we aim to present various aspects of male breast cancer with particular emphasis on incidence, risk factors, patho-physiology, treatment, prognostic factors, and outcome.</p> <p>Methods</p> <p>Information on all aspects of male breast cancer was gathered from available relevant literature on male breast cancer from the MEDLINE database over the past 32 years from 1975 to 2007. Various reported studies were scrutinized for emerging evidence. Incidence data were also obtained from the IARC, Cancer Mondial database.</p> <p>Conclusion</p> <p>There is a scenario of rising incidence, particularly in urban US, Canada and UK. Even though more data on risk factors is emerging about this disease, more multi-institutional efforts to pool data with large randomized trials to show treatment and survival benefits are needed to support the existing vast emerging knowledge about the disease.</p

Theoretical frameworks for the study of structuring processes in group decision support systems

Most theoretical perspectives used to explain the use and effects of communication and decision support technologies assume someform of technological a&amp;rminism. lnwnsisten&amp;s in the research jindings have prompted theorists to reject the assumptions of technological determinism in favor of an emergent perspective. To date, only adaptive structuration theo y CAST) offers the promise of satisfying two requirements for exphnation based on an emergent perspective: recursivify and unique effects. The current article reviews the application of AST to the study of a relatively recent technology in the workplace--group decision support systems (GDSS). Next it discusses AST&apos;s chal- lenge to capture, dynamically and precisely, GDSS processes and outcomes. In response to these concerns, self-organizing systems theory (SOST) is reviewed and applied to problematic areas in GDSS research with the aim of advancing AST

Altered activity–rest patterns in mice with a human autosomal-dominant nocturnal frontal lobe epilepsy mutation in the β2 nicotinic receptor

High-affinity nicotinic receptors containing β2 subunits (β2^*) are widely expressed in the brain, modulating many neuronal processes and contributing to neuropathologies such as Alzheimer's disease, Parkinson's disease and epilepsy. Mutations in both the α4 and β2 subunits are associated with a rare partial epilepsy, autosomal dominant nocturnal frontal lobe epilepsy (ADNFLE). In this study, we introduced one such human missense mutation into the mouse genome to generate a knock-in strain carrying a valine-to-leucine mutation β2V287L. β2^(V287L) mice were viable and born at an expected Mendelian ratio. Surprisingly, mice did not show an overt seizure phenotype; however, homozygous mice did show significant alterations in their activity–rest patterns. This was manifest as an increase in activity during the light cycle suggestive of disturbances in the normal sleep patterns of mice; a parallel phenotype to that found in human ADNFLE patients. Consistent with the role of nicotinic receptors in reward pathways, we found that β2^(V287L) mice did not develop a normal proclivity to voluntary wheel running, a model for natural reward. Anxiety-related behaviors were also affected by the V287L mutation. Mutant mice spent more time in the open arms on the elevated plus maze suggesting that they had reduced levels of anxiety. Together, these findings emphasize several important roles of β2^* nicotinic receptors in complex biological processes including the activity–rest cycle, natural reward and anxiety

Study of fetomaternal outcome in pre-eclampsia at tertiary care centres, South Gujarat

Background: Hypertensive disorders are among the most common medical disorder during pregnancy and continue to be a serious challenge in obstetric practice. It affects about 7-15% of all gestations. In India it accounts for the third most important cause of maternal mortality. Aim if this study was to study the prevalence of pre-eclampsia and feto-maternal outcome in cases of pre-eclampsia. Methods: This was a descriptive observational study conducted over a period from February 2019 to July 2021. This study enrolled 106 cases of pre-eclampsia, cases were selected by inclusion and exclusion criteria, data were entered and analysed by using SPSS version 20. Results: A total of 106 patients were analysed. It was observed that it was more common in age group of 26 to 30 years 51%, 56% were unbooked patients. Maximum number of patients were primigravida 60%, 96% patients were from lower socioeconomic class, 37% patients had normal vaginal delivery, 63% had caesarean delivery. The most common maternal complication was eclampsia (12%), HELLP Syndrome 12%, abruptio occurred in 8% of patients. Maternal mortality occurred in 4 cases. Out of 106 babies 37 (34.93%) babies had normal outcome while 29% (27.35%) had low birth weight, 16 (15.09%) babies were IUGR, 15 (14.5%) babies were IUFD, 7 (6.6%) babies had RDS and 2 (1.8%) babies were stillbirth 40 (44.94%) babies were admitted in NICU. Conclusions: This study concludes that foetal and maternal outcome were markedly affected by pre-eclampsia and also the grave complications were more common in pre-eclampsia. So proper antenatal care, early diagnosis of pre-eclampsia and timely intervention will decrease maternal perinatal morbidity and mortality

Rainfall estimates on a gridded network (REGEN) – a global land-based gridded dataset of daily precipitation from 1950 to 2016

We present a new global land-based daily precipitation dataset from 1950 using an interpolated network of in situ data called Rainfall Estimates on a Gridded Network – REGEN. We merged multiple archives of in situ data including two of the largest archives, the Global Historical Climatology Network – Daily (GHCN-Daily) hosted by National Centres of Environmental Information (NCEI), USA, and one hosted by the Global Precipitation Climatology Centre (GPCC) operated by Deutscher Wetterdienst (DWD). This resulted in an unprecedented station density compared to existing datasets. The station time series were quality-controlled using strict criteria and flagged values were removed. Remaining values were interpolated to create area-average estimates of daily precipitation for global land areas on a 1∘ × 1∘ latitude–longitude resolution. Besides the daily precipitation amounts, fields of standard deviation, kriging error and number of stations are also provided. We also provide a quality mask based on these uncertainty measures. For those interested in a dataset with lower station network variability we also provide a related dataset based on a network of long-term stations which interpolates stations with a record length of at least 40 years. The REGEN datasets are expected to contribute to the advancement of hydrological science and practice by facilitating studies aiming to understand changes and variability in several aspects of daily precipitation distributions, extremes and measures of hydrological intensity. Here we document the development of the dataset and guidelines for best practices for users with regards to the two datasets.This research has been supported by the Australian Research Council (grant nos. DP160103439, CE110001028 and DE150100456) and the Spanish Ministry for Science and Innovation (grant no. RYC-2017-22964)Peer ReviewedPostprint (published version

Lactation and neonatal nutrition: defining and refining the critical questions.

This paper resulted from a conference entitled "Lactation and Milk: Defining and refining the critical questions" held at the University of Colorado School of Medicine from January 18-20, 2012. The mission of the conference was to identify unresolved questions and set future goals for research into human milk composition, mammary development and lactation. We first outline the unanswered questions regarding the composition of human milk (Section I) and the mechanisms by which milk components affect neonatal development, growth and health and recommend models for future research. Emerging questions about how milk components affect cognitive development and behavioral phenotype of the offspring are presented in Section II. In Section III we outline the important unanswered questions about regulation of mammary gland development, the heritability of defects, the effects of maternal nutrition, disease, metabolic status, and therapeutic drugs upon the subsequent lactation. Questions surrounding breastfeeding practice are also highlighted. In Section IV we describe the specific nutritional challenges faced by three different populations, namely preterm infants, infants born to obese mothers who may or may not have gestational diabetes, and infants born to undernourished mothers. The recognition that multidisciplinary training is critical to advancing the field led us to formulate specific training recommendations in Section V. Our recommendations for research emphasis are summarized in Section VI. In sum, we present a roadmap for multidisciplinary research into all aspects of human lactation, milk and its role in infant nutrition for the next decade and beyond