Information content and forecasting ability of sentiment indicators: case of real estate market

We evaluate a number of real estate sentiment indices to ascertain current and forward-looking information content that may be useful for forecasting demand and supply activities. Analyzing the dynamic relationships within a Vector Auto-Regression (VAR) framework and using the quarterly US data over 1988-2010, we test the efficacy of several sentiment measures by comparing them with other coincident economic indicators. Overall, our analysis suggests that the sentiment in real estate convey valuable information that can help predict changes in real estate returns. These findings have important implications for investment decisions, from consumers' as well as institutional investors' perspectives.

Emergence of spatially heterogeneous burst suppression in a neural field model of electrocortical activity

Burst suppression in the electroencephalogram (EEG) is a well-described phenomenon that occurs during deep anesthesia, as well as in a variety of congenital and acquired brain insults. Classically it is thought of as spatially synchronous, quasi-periodic bursts of high amplitude EEG separated by low amplitude activity. However, its characterization as a “global brain state” has been challenged by recent results obtained with intracranial electrocortigraphy. Not only does it appear that burst suppression activity is highly asynchronous across cortex, but also that it may occur in isolated regions of circumscribed spatial extent. Here we outline a realistic neural field model for burst suppression by adding a slow process of synaptic resource depletion and recovery, which is able to reproduce qualitatively the empirically observed features during general anesthesia at the whole cortex level. Simulations reveal heterogeneous bursting over the model cortex and complex spatiotemporal dynamics during simulated anesthetic action, and provide forward predictions of neuroimaging signals for subsequent empirical comparisons and more detailed characterization. Because burst suppression corresponds to a dynamical end-point of brain activity, theoretically accounting for its spatiotemporal emergence will vitally contribute to efforts aimed at clarifying whether a common physiological trajectory is induced by the actions of general anesthetic agents. We have taken a first step in this direction by showing that a neural field model can qualitatively match recent experimental data that indicate spatial differentiation of burst suppression activity across cortex.

Big social data and political sentiment: the tweet stream during the UK General Election 2015 campaign

The General Election for the 56th United Kingdom Parliament was held on 7 May 2015. Tweets related to UK politics, not only those with the specific hashtag ”#GE2015”, have been collected in the period between March 1 and May 31, 2015. The resulting dataset contains over 28 million tweets for a total of 118 GB in uncompressed format or 15 GB in compressed format. This study describes the method that was used to collect the tweets and presents some analysis, including a political sentiment index, and outlines interesting research directions on Big Social Data based on Twitter microblogging.

Modulatory effect of fatty acids on fungicidal activity, respiratory burst and TNF-alpha and IL-6 production in J774 murine macrophages

The reported effects of different families of fatty acids (FA; SFA, MUFA, n-3 and n-6 PUFA) on human health and the importance of macrophage respiratory burst and cytokine release to immune defence led us to examine the influence of palmitic acid (PA), oleic acid (OA), linoleic acid, arachidonic acid, EPA and DHA on macrophage function. We determined fungicidal activity, reactive oxygen species (ROS) and cytokine production after the treatment of J774 cells with non-toxic concentrations of the FA. PA had a late and discrete stimulating effect on ROS production, which may be associated with the reduced fungicidal activity of the cells after treatment with this FA. OA presented a sustained stimulatory effect on ROS production and increased fungicidal activity of the cells, suggesting that enrichment of diets with OA may be beneficial for pathogen elimination. The effects of PUFA on ROS production were time-and dose-dependently regulated, with no evident differences between n-3 and n-6 PUFA. It was worth noting that most changes induced after stimulation of the cells with lipopolysaccharide were suppressed by the FA. The present results suggest that supplementation of the diet with specific FA, not classes of FA, might enable an improvement in host defence mechanisms or a reduction in adverse immunological reactions.

UPR induces transient burst of apoptosis in islets of early lactating rats through reduced AKT phosphorylation via ATF4/CHOP stimulation of TRB3 expression

Bromati CR, Lellis-Santos C, Yamanaka TS, Nogueira TC, Leonelli M, Caperuto LC, Gorjao R, Leite AR, Anhe GF, Bordin S. UPR induces transient burst of apoptosis in islets of early lactating rats through reduced AKT phosphorylation via ATF4/CHOP stimulation of TRB3 expression. Am J Physiol Regul Integr Comp Physiol 300: R92-R100, 2011. First published November 10, 2010; doi:10.1152/ajpregu.00169.2010.-Endocrine pancreas from pregnant rats undergoes several adaptations that comprise increase in beta-cell number, mass and insulin secretion, and reduction of apoptosis. Lactogens are the main hormones that account for these changes. Maternal pancreas, however, returns to a nonpregnant state just after the delivery. The precise mechanism by which this reversal occurs is not settled but, in spite of high lactogen levels, a transient increase in apoptosis was already reported as early as the 3rd day of lactation (L3). Our results revealed that maternal islets displayed a transient increase in DNA fragmentation at L3, in parallel with decreased RAC-alpha serine/threonine-protein kinase (AKT) phosphorylation (pAKT), a known prosurvival kinase. Wortmannin completely abolished the prosurvival action of prolactin (PRL) in cultured islets. Decreased pAKT in L3-islets correlated with increased Tribble 3 (TRB3) expression, a pseudokinase inhibitor of AKT. PERK and eIF2 alpha phosphorylation transiently increased in islets from rats at the first day after delivery, followed by an increase in immunoglobulin heavy chain-binding protein (BiP), activating transcription factor 4 (ATF4), and C/EBP homologous protein (CHOP) in islets from L3 rats. Chromatin immunoprecipitation (ChIP) and Re-ChIP experiments further confirmed increased binding of the heterodimer ATF4/CHOP to the TRB3 promoter in L3 islets. Treatment with PBA, a chemical chaperone that inhibits UPR, restored pAKT levels and inhibited the increase in apoptosis found in L3. Moreover, PBA reduced CHOP and TRB3 levels in beta-cell from L3 rats. Altogether, our study collects compelling evidence that UPR underlies the physiological and transient increase in beta-cell apoptosis after delivery. The UPR is likely to counteract prosurvival actions of PRL by reducing pAKT through ATF4/CHOP-induced TRB3 expression.

Prediction of age, sentiment, and connectivity from social media text

Social media corpora, including the textual output of blogs, forums, and messaging applications, provide fertile ground for linguistic analysis material diverse in topic and style, and at Web scale. We investigate manifest properties of textual messages, including latent topics, psycholinguistic features, and author mood, of a large corpus of blog posts, to analyze the impact of age, emotion, and social connectivity. These properties are found to be significantly different across the examined cohorts, which suggest discriminative features for a number of useful classification tasks. We build binary classifiers for old versus young bloggers, social versus solo bloggers, and happy versus sad posts with high performance. Analysis of discriminative features shows that age turns upon choice of topic, whereas sentiment orientation is evidenced by linguistic style. Good prediction is achieved for social connectivity using topic and linguistic features, leaving tagged mood a modest role in all classifications.

A sentiment-aware approach to community formation in social media

Participating in a community exemplifies the aspect of sharing, networking and interacting in a social media system. There has been extensive work on characterising on-line communities by their contents and tags using topic modelling tools. However, the role of sentiment and mood has not been studied. Arguably, mood is an integral feature of a text, and becomes more significant in the context of social media: two communities might discuss precisely the same topics, yet within an entirely different atmosphere. Such sentiment-related distinctions are important for many kinds of analysis and applications, such as community recommendation. We present a novel approach to identification of latent hyper-groups in social communities based on users’ sentiment. The results show that a sentiment-based approach can yield useful insights into community formation and metacommunities, having potential applications in, for example, mental health—by targeting support or surveillance to communities with negative mood—or in marketing—by targeting customer communities having the same sentiment on similar topics.

Individual variation in thermal performance curves: swimming burst speed and jumping endurance in wild-caught tropical clawed frogs

The importance of studying individual variation in locomotor performance has long been recognized as it may determine the ability of an organism to escape from predators, catch prey or disperse. In ectotherms, locomotor performance is highly influenced by ambient temperature (Ta), yet several studies have showed that individual differences are usually retained across a Ta gradient. Less is known, however, about individual differences in thermal sensitivity of performance, despite the fact that it could represent adaptive sources of phenotypic variation and/or additional substrate for selection to act upon. We quantified swimming and jumping performance in 18 wild-caught tropical clawed frogs (Xenopus tropicalis) across a Ta gradient. Maximum swimming velocity and acceleration were not repeatable and individuals did not differ in how their swimming performance varied across Ta. By contrast, time and distance jumped until exhaustion were repeatable across the Ta gradient, indicating that individuals that perform best at a given Ta also perform best at another Ta. Moreover, thermal sensitivity of jumping endurance significantly differed among individuals, with individuals of high performance at low Ta displaying the highest sensitivity to Ta. Individual differences in terrestrial performance increased with decreasing Ta, which is opposite to results obtained in lizards at the inter-specific and among-individual levels. To verify the generality of these patterns, we need more studies on individual variation in thermal reaction norms for locomotor performance in lizards and frogs.

War and private sentiment in Australia during 1915

This article investigates the development of a total war mentality in Australia during the First World War. Through a study of private letters and diaries, it observes the much greater level of popular commitment to the war that emerged in the middle of 1915, and an increasing acceptance throughout that year that the expanding war had taken on a life of its own, and that it would not end suddenly or without tremendous sacrifice. By the end of 1915, Australians were showing ever greater levels of dedication to a war offering increasingly less sense of how long it might continue.

A stochastic time-domain model for burst data aggregation in IEEE 802.15.4 wireless sensor networks

In many network applications, the nature of traffic is of burst type. Often, the transient response of network to such traffics is the result of a series of interdependant events whose occurrence prediction is not a trivial task. The previous efforts in IEEE 802.15.4 networks often followed top-down approaches to model those sequences of events, i.e., through making top-view models of the whole network, they tried to track the transient response of network to burst packet arrivals. The problem with such approaches was that they were unable to give station-level views of network response and were usually complex. In this paper, we propose a non-stationary analytical model for the IEEE 802.15.4 slotted CSMA/CA medium access control (MAC) protocol under burst traffic arrival assumption and without the optional acknowledgements. We develop a station-level stochastic time-domain method from which the network-level metrics are extracted. Our bottom-up approach makes finding station-level details such as delay, collision and failure distributions possible. Moreover, network-level metrics like the average packet loss or transmission success rate can be extracted from the model. Compared to the previous models, our model is proven to be of lower memory and computational complexity order and also supports contention window sizes of greater than one. We have carried out extensive and comparative simulations to show the high accuracy of our model.