A unified framework for online trip destination prediction

Trip destination prediction is an area of increasing importance in many applications such as trip planning, autonomous driving and electric vehicles. Even though this problem could be naturally addressed in an online learning paradigm where data is arriving in a sequential fashion, the majority of research has rather considered the offline setting. In this paper, we present a unified framework for trip destination prediction in an online setting, which is suitable for both online training and online prediction. For this purpose, we develop two clustering algorithms and integrate them within two online prediction models for this problem. We investigate the different configurations of clustering algorithms and prediction models on a real-world dataset. We demonstrate that both the clustering and the entire framework yield consistent results compared to the offline setting. Finally, we propose a novel regret metric for evaluating the entire online framework in comparison to its offline counterpart. This metric makes it possible to relate the source of erroneous predictions to either the clustering or the prediction model. Using this metric, we show that the proposed methods converge to a probability distribution resembling the true underlying distribution with a lower regret than all of the baselines

Parental age effects on neonatal white matter development.

OBJECTIVE: Advanced paternal age is associated with poor offspring developmental outcome. Though an increase in paternal age-related germline mutations may affect offspring white matter development, outcome differences could also be due to psychosocial factors. Here we investigate possible cerebral changes prior to strong environmental influences using brain MRI in a cohort of healthy term-born neonates. METHODS: We used structural and diffusion MRI images acquired soon after birth from a cohort (n = 275) of healthy term-born neonates. Images were analysed using a customised tract based spatial statistics (TBSS) processing pipeline. Neurodevelopmental assessment using the Bayley-III scales was offered to all participants at age 18 months. For statistical analysis neonates were compared in two groups, representing the upper quartile (paternal age ≥38 years) and lower three quartiles. The same method was used to assess associations with maternal age. RESULTS: In infants with older fathers (≥38 years), fractional anisotropy, a marker of white matter organisation, was significantly reduced in three early maturing anatomical locations (the corticospinal tract, the corpus callosum, and the optic radiation). Fractional anisotropy in these locations correlated positively with Bayley-III cognitive composite score at 18 months in the advanced paternal age group. A small but significant reduction in total brain volume was also observed in in the infants of older fathers. No significant associations were found between advanced maternal age and neonatal imaging. CONCLUSIONS: The epidemiological association between advanced paternal age and offspring outcome is extremely robust. We have for the first time demonstrated a neuroimaging phenotype of advanced paternal age before sustained parental interaction that correlates with later outcome

Antibodies That Induce Phagocytosis of Malaria Infected Erythrocytes: Effect of HIV Infection and Correlation with Clinical Outcomes

HIV infection increases the burden of disease of malaria in pregnancy, in part by impairing the development of immunity. We measured total IgG and phagocytic antibodies against variant surface antigens of placental-type CS2 parasites in 187 secundigravidae (65% HIV infected). In women with placental malaria infection, phagocytic antibodies to CS2VSA were decreased in the presence of HIV (p = 0.011) and correlated positively with infant birth weight (coef = 3.57, p = 0.025), whereas total IgG to CS2VSA did not. Phagocytic antibodies to CS2VSA are valuable tools to study acquired immunity to malaria in the context of HIV co-infection. Secundigravidae may be an informative group for identification of correlates of immunity

The Role of Individual Variables, Organizational Variables and Moral Intensity Dimensions in Libyan Management Accountants’ Ethical Decision Making

This study investigates the association of a broad set of variables with the ethical decision making of management accountants in Libya. Adopting a cross-sectional methodology, a questionnaire including four different ethical scenarios was used to gather data from 229 participants. For each scenario, ethical decision making was examined in terms of the recognition, judgment and intention stages of Rest’s model. A significant relationship was found between ethical recognition and ethical judgment and also between ethical judgment and ethical intention, but ethical recognition did not significantly predict ethical intention—thus providing support for Rest’s model. Organizational variables, age and educational level yielded few significant results. The lack of significance for codes of ethics might reflect their relative lack of development in Libya, in which case Libyan companies should pay attention to their content and how they are supported, especially in the light of the under-development of the accounting profession in Libya. Few significant results were also found for gender, but where they were found, males showed more ethical characteristics than females. This unusual result reinforces the dangers of gender stereotyping in business. Personal moral philosophy and moral intensity dimensions were generally found to be significant predictors of the three stages of ethical decision making studied. One implication of this is to give more attention to ethics in accounting education, making the connections between accounting practice and (in Libya) Islam. Overall, this study not only adds to the available empirical evidence on factors affecting ethical decision making, notably examining three stages of Rest’s model, but also offers rare insights into the ethical views of practising management accountants and provides a benchmark for future studies of ethical decision making in Muslim majority countries and other parts of the developing world

Intrinsic gain modulation and adaptive neural coding

In many cases, the computation of a neural system can be reduced to a receptive field, or a set of linear filters, and a thresholding function, or gain curve, which determines the firing probability; this is known as a linear/nonlinear model. In some forms of sensory adaptation, these linear filters and gain curve adjust very rapidly to changes in the variance of a randomly varying driving input. An apparently similar but previously unrelated issue is the observation of gain control by background noise in cortical neurons: the slope of the firing rate vs current (f-I) curve changes with the variance of background random input. Here, we show a direct correspondence between these two observations by relating variance-dependent changes in the gain of f-I curves to characteristics of the changing empirical linear/nonlinear model obtained by sampling. In the case that the underlying system is fixed, we derive relationships relating the change of the gain with respect to both mean and variance with the receptive fields derived from reverse correlation on a white noise stimulus. Using two conductance-based model neurons that display distinct gain modulation properties through a simple change in parameters, we show that coding properties of both these models quantitatively satisfy the predicted relationships. Our results describe how both variance-dependent gain modulation and adaptive neural computation result from intrinsic nonlinearity.Comment: 24 pages, 4 figures, 1 supporting informatio

A transcriptomic snapshot of early molecular communication between Pasteuria penetrans and Meloidogyne incognita

© The Author(s). 2018Background: Southern root-knot nematode Meloidogyne incognita (Kofoid and White, 1919), Chitwood, 1949 is a key pest of agricultural crops. Pasteuria penetrans is a hyperparasitic bacterium capable of suppressing the nematode reproduction, and represents a typical coevolved pathogen-hyperparasite system. Attachment of Pasteuria endospores to the cuticle of second-stage nematode juveniles is the first and pivotal step in the bacterial infection. RNA-Seq was used to understand the early transcriptional response of the root-knot nematode at 8 h post Pasteuria endospore attachment. Results: A total of 52,485 transcripts were assembled from the high quality (HQ) reads, out of which 582 transcripts were found differentially expressed in the Pasteuria endospore encumbered J2 s, of which 229 were up-regulated and 353 were down-regulated. Pasteuria infection caused a suppression of the protein synthesis machinery of the nematode. Several of the differentially expressed transcripts were putatively involved in nematode innate immunity, signaling, stress responses, endospore attachment process and post-attachment behavioral modification of the juveniles. The expression profiles of fifteen selected transcripts were validated to be true by the qRT PCR. RNAi based silencing of transcripts coding for fructose bisphosphate aldolase and glucosyl transferase caused a reduction in endospore attachment as compared to the controls, whereas, silencing of aspartic protease and ubiquitin coding transcripts resulted in higher incidence of endospore attachment on the nematode cuticle. Conclusions: Here we provide evidence of an early transcriptional response by the nematode upon infection by Pasteuria prior to root invasion. We found that adhesion of Pasteuria endospores to the cuticle induced a down-regulated protein response in the nematode. In addition, we show that fructose bisphosphate aldolase, glucosyl transferase, aspartic protease and ubiquitin coding transcripts are involved in modulating the endospore attachment on the nematode cuticle. Our results add new and significant information to the existing knowledge on early molecular interaction between M. incognita and P. penetrans.Peer reviewedFinal Published versio

Cancer Stem Cell-Like Cells Derived from Malignant Peripheral Nerve Sheath Tumors

This study aims to examine whether or not cancer stem cells exist in malignant peripheral nerve sheath tumors (MPNST). Cells of established lines, primary cultures and freshly dissected tumors were cultured in serum free conditions supplemented with epidermal and fibroblast growth factors. From one established human MPNST cell line, S462, cells meeting the criteria for cancer stem cells were isolated. Clonal spheres were obtained, which could be passaged multiple times. Enrichment of stem cell-like cells in these spheres was also supported by increased expression of stem cell markers such as CD133, Oct4, Nestin and NGFR, and decreased expression of mature cell markers such as CD90 and NCAM. Furthermore, cells of these clonal S462 spheres differentiated into Schwann cells, smooth muscle/fibroblast and neurons-like cells under specific differentiation-inducing cultural conditions. Finally, subcutaneous injection of the spheres into immunodeficient nude mice led to tumor formation at a higher rate compared to the parental adherent cells (66% versus 10% at 2.5×105). These results provide evidence for the existence of cancer stem cell-like cells in malignant peripheral nerve sheath tumors

A survey of energy drink consumption patterns among college students

<p>Abstract</p> <p>Background</p> <p>Energy drink consumption has continued to gain in popularity since the 1997 debut of Red Bull, the current leader in the energy drink market. Although energy drinks are targeted to young adult consumers, there has been little research regarding energy drink consumption patterns among college students in the United States. The purpose of this study was to determine energy drink consumption patterns among college students, prevalence and frequency of energy drink use for six situations, namely for insufficient sleep, to increase energy (in general), while studying, driving long periods of time, drinking with alcohol while partying, and to treat a hangover, and prevalence of adverse side effects and energy drink use dose effects among college energy drink users.</p> <p>Methods</p> <p>Based on the responses from a 32 member college student focus group and a field test, a 19 item survey was used to assess energy drink consumption patterns of 496 randomly surveyed college students attending a state university in the Central Atlantic region of the United States.</p> <p>Results</p> <p>Fifty one percent of participants (<it>n </it>= 253) reported consuming greater than one energy drink each month in an average month for the current semester (defined as energy drink user). The majority of users consumed energy drinks for insufficient sleep (67%), to increase energy (65%), and to drink with alcohol while partying (54%). The majority of users consumed one energy drink to treat most situations although using three or more was a common practice to drink with alcohol while partying (49%). Weekly jolt and crash episodes were experienced by 29% of users, 22% reported ever having headaches, and 19% heart palpitations from consuming energy drinks. There was a significant dose effect only for jolt and crash episodes.</p> <p>Conclusion</p> <p>Using energy drinks is a popular practice among college students for a variety of situations. Although for the majority of situations assessed, users consumed one energy drink with a reported frequency of 1 – 4 days per month, many users consumed three or more when combining with alcohol while partying. Further, side effects from consuming energy drinks are fairly common, and a significant dose effect was found with jolt and crash episodes. Future research should identify if college students recognize the amounts of caffeine that are present in the wide variety of caffeine-containing products that they are consuming, the amounts of caffeine that they are consuming in various situations, and the physical side effects associated with caffeine consumption.</p

Optimization of MicroCT Imaging and Blood Vessel Diameter Quantitation of Preclinical Specimen Vasculature with Radiopaque Polymer Injection Medium

Vascular networks within a living organism are complex, multi-dimensional, and challenging to image capture. Radio-angiographic studies in live animals require a high level of infrastructure and technical investment in order to administer costly perfusion mediums whose signals metabolize and degrade relatively rapidly, diminishing within a few hours or days. Additionally, live animal specimens must not be subject to long duration scans, which can cause high levels of radiation exposure to the specimen, limiting the quality of images that can be captured. Lastly, despite technological advances in live-animal specimen imaging, it is quite difficult to minimize or prevent movement of a live animal, which can cause motion artifacts in the final data output. It is demonstrated here that through the use of postmortem perfusion protocols of radiopaque silicone polymer mediums and ex-vivo organ harvest, it is possible to acquire a high level of vascular signal in preclinical specimens through the use of micro-computed tomographic (microCT) imaging. Additionally, utilizing high-order rendering algorithms, it is possible to further derive vessel morphometrics for qualitative and quantitative analysis

The Developing Human Connectome Project: a minimal processing pipeline for neonatal cortical surface reconstruction

The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WU-MINN Human Connectome Project (HCP), and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processing pipeline for the structural Magnetic Resonance Imaging (MRI) of the developing neonatal brain. This proposed pipeline consists of a refined framework for cortical and sub-cortical volume segmentation, cortical surface extraction, and cortical surface inflation, which has been specifically designed to address considerable differences between adult and neonatal brains, as imaged using MRI. Using the proposed pipeline our results demonstrate that images collected from 465 subjects ranging from 28 to 45 weeks post-menstrual age (PMA) can be processed fully automatically; generating cortical surface models that are topologically correct, and correspond well with manual evaluations of tissue boundaries in 85% of cases. Results improve on state-of-the-art neonatal tissue segmentation models and significant errors were found in only 2% of cases, where these corresponded to subjects with high motion. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, supporting the modelling of emerging patterns of brain connectivity