Predicting Stock Market Price Using Neural Network Model

The present article predicts the movement of daily Indian stock market (S&P CNX Nifty) price by using Feedforward Neural Network Model over a period of eight years from January 1st 2008 to April 8th 2016. The prediction accuracy of the model is accessed by normalized mean square error (NMSE) and sign correctness percentage (SCP) measure. The study indicates that the predicted output is very close to actual data since the normalized error of one-day lag is 0.02. The analysis further shows that 60 percent accuracy found in the prediction of the direction of daily movement of Indian stock market price after the financial crises period 2008. The study indicates that the predictive power of the feedforward neural network models reasonably influenced by one-day lag stock market price. Hence, the validity of an efficient market hypothesis does not hold in practice in the Indian stock market. This article is quite useful to the investors, professional traders and regulators for understanding the effectiveness of Indian stock market to take appropriate investment decision in the stock market.

Exploring Post COVID-19 Outbreak Intradaily Mobility Pattern Change in College Students: A GPS-Focused Smartphone Sensing Study

With the outbreak of the COVID-19 pandemic in 2020, most colleges and universities move to restrict campus activities, reduce indoor gatherings and move instruction online. These changes required that students adapt and alter their daily routines accordingly. To investigate patterns associated with these behavioral changes, we collected smartphone sensing data using the Beiwe platform from two groups of undergraduate students at a major North American university, one from January to March of 2020 (74 participants), the other from May to August (52 participants), to observe the differences in students' daily life patterns before and after the start of the pandemic. In this paper, we focus on the mobility patterns evidenced by GPS signal tracking from the students' smartphones and report findings using several analytical methods including principal component analysis, circadian rhythm analysis, and predictive modeling of perceived sadness levels using mobility-based digital metrics. Our findings suggest that compared to the pre-COVID group, students in the mid-COVID group generally 1) registered a greater amount of midday movement than movement in the morning (8–10 a.m.) and in the evening (7–9 p.m.), as opposed to the other way around; 2) exhibited significantly less intradaily variability in their daily movement; 3) visited less places and stayed at home more everyday, and; 4) had a significant lower correlation between their mobility patterns and negative mood.

Scale and Landscape Features Matter for Understanding Waterbird Habitat Selection

Clarifying species-environment relationships is crucial for the development of efficient conservation and restoration strategies. However, this work is often complicated by a lack of detailed information on species distribution and habitat features and tends to ignore the impact of scale and landscape features. Here, we tracked 11 Oriental White Storks (Ciconia boyciana) with GPS loggers during their wintering period at Poyang Lake and divided the tracking data into two parts (foraging and roosting states) according to the distribution of activity over the course of a day. Then, a three-step multiscale and multistate approach was employed to model habitat selection characteristics: (1) first, we minimized the search range of the scale for these two states based on daily movement characteristics; (2) second, we identified the optimized scale of each candidate variable; and (3) third, we fit a multiscale, multivariable habitat selection model in relation to natural features, human disturbance and especially landscape composition and configuration. Our findings reveal that habitat selection of the storks varied with spatial scale and that these scaling relationships were not consistent across different habitat requirements (foraging or roosting) and environmental features. Landscape configuration was a more powerful predictor for storks’ foraging habitat selection, while roosting was more sensitive to landscape composition. Incorporating high-precision spatiotemporal satellite tracking data and landscape features derived from satellite images from the same periods into a multiscale habitat selection model can greatly improve the understanding of species-environmental relationships and guide efficient recovery planning and legislation.

Emerging dynamics from high-resolution spatial numerical epidemics

Simulating nationwide realistic individual movements with a detailed geographical structure can help optimize public health policies. However, existing tools have limited resolution or can only account for a limited number of agents. We introduce Epidemap, a new framework that can capture the daily movement of more than 60 million people in a country at a building-level resolution in a realistic and computationally efficient way. By applying it to the case of an infectious disease spreading in France, we uncover hitherto neglected effects, such as the emergence of two distinct peaks in the daily number of cases or the importance of local density in the timing of arrival of the epidemic. Finally, we show that the importance of super-spreading events strongly varies over time.

Evaluation of the Presence of ASFV in Wolf Feces Collected from Areas in Poland with ASFV Persistence

African swine fever (ASF), caused by a DNA virus (ASFV) belonging to genus Asfivirus of the Asfarviridae family, is one of the most threatening diseases of suids. During last few years, it has spread among populations of wild boars and pigs in countries of Eastern and Central Europe, causing huge economical losses. While local ASF occurrence is positively correlated with wild boar density, ecology of this species (social structure, movement behavior) constrains long-range disease transmission. Thus, it has been speculated that carnivores known for high daily movement and long-range dispersal ability, such as the wolf (Canis lupus), may be indirect ASFV vectors. To test this, we analyzed 62 wolf fecal samples for the presence of ASFV DNA, collected mostly in parts of Poland declared as ASF zones. This dataset included 20 samples confirmed to contain wild boar remains, 13 of which were collected near places where GPS-collared wolves fed on dead wild boars. All analyzed fecal samples were ASFV-negative. On the other hand, eight out of nine wild boar carcasses that were fed on by telemetrically studied wolves were positive. Thus, our results suggest that when wolves consume meat of ASFV-positive wild boars, the virus does not survive the passage through intestinal tract. Additionally, wolves may limit ASFV transmission by removing infectious carrion. We speculate that in areas where telemetric studies on large carnivores are performed, data from GPS collars could be used to enhance efficiency of carcass search, which is one of the main preventive measures to constrain ASF spread.

High Temporal Resolution Measurements of Movement Reveal Novel Early-Life Physiological Decline in C. elegans

Age-related physiological changes are most notable and best-studied late in life, while the nature of aging in early- or middle-aged individuals has not been explored as thoroughly. In C. elegans, studies of movement vs. age generally delineate three distinct phases: sustained, youthful movement; a discrete onset of rapidly progressing impairment; and gross immobility. We investigated whether this first period of early-life adult movement is simply a sustained “healthy” level of high function followed by a discrete “movement catastrophe” — or whether there are early-life changes in movement that precede future physiological declines. To determine how movement varies during early adult life, we followed isolated individuals throughout life with a previously unachieved combination of duration and temporal resolution. By tracking individuals across the first six days of adulthood, we observed declines in movement starting as early as the first two days of adult life, as well as high interindividual variability in total daily movement. These findings suggest that movement is a highly dynamic behavior early in life, and that factors driving movement decline may begin acting as early as the first day of adulthood. Using simulation studies based on acquired data, we suggest that too infrequent sampling in common movement assays limits observation of early-adult changes in motility, and we propose feasible alternate strategies and a framework for designing assays with increased sensitivity for early movement declines.

Effect of sex, age, and reproductive status on daily activity levels and activity patterns in jaguars (Panthera onca)

All animals, including carnivores, adapt their daily activity duration and distribution to satisfy food demands, breed, or avoid mortality risk. We used the kernel density method to estimate daily movement activity levels and movement activity patterns of jaguars in Hato Piñero, in Venezuelan Western Llanos, based on 3,656 jaguar detection time records from two and a half years of camera trapping. Jaguars were active for 11.7 h per day on average and exhibited mostly nocturnal and crepuscular activity pattern, however, with marked differences between sex/age/reproductive groups. Reproductive females had the highest daily activity level (13.2 h/day), followed by adult males (10.9 h/day), non-reproductive females (10.5 h/day), and cubs (8.7 h/day). Activity patterns also differed, with males and reproductive females having activity peaks at the same hours after sunset and before sunrise, cubs in the night and after sunrise, while non-reproductive females were most active during night hours. This study was the first to document the effect of sex, age, and reproductive status on daily level and activity pattern in the jaguar.

Exploring Post COVID-19 Outbreak Intradaily Mobility Pattern Change in College Students: a GPS-focused Smartphone Sensing Study (Preprint)

UNSTRUCTURED With the outbreak of the COVID-19 pandemic in 2020, most colleges and universities move to restrict campus activities, reduce indoor gatherings and move instruction online. These changes required that students adapt and alter their daily routines accordingly. To investigate patterns associated with these behavioral changes, we collected smartphone sensing data using the Beiwe platform from two groups of undergraduate students at a major North American university, one from January to March of 2020 (74 participants), the other from May to August (52 participants), to observe the differences in students' daily life patterns before and after the start of the pandemic. In this paper, we focus on the mobility patterns evidenced by GPS signal tracking from the students' smartphones and report findings using several analytical methods including principal component analysis, circadian rhythm analysis, and predictive modeling of perceived sadness levels using mobility-based digital metrics. Our findings suggest that compared to the pre-COVID group, students in the mid-COVID group generally (1) registered a greater amount of midday movement than movement in the morning (8-10am) and in the evening (7-9pm), as opposed to the other way around; (2) exhibited significantly less intradaily variability in their daily movement, and (3) had a significant lower correlation between their mobility patterns and negative mood.

Fitness cost from fluctuating ultraviolet radiation in Daphnia magna

Solar ultraviolet radiation (UVR) is an important environmental threat for organisms in aquatic systems, but its temporally variable nature makes the understanding of its effects ambiguous. The aim of our study was to assess potential fitness costs associated with fluctuating UVR in the aquatic zooplankter Daphnia magna . We investigated individual survival, reproduction and behaviour when exposed to different UVR treatments. Individuals exposed to fluctuating UVR, resembling natural variations in cloud cover, had the lowest fitness (measured as the number of offspring produced during their lifespan). By contrast, individuals exposed to the same, but constant UVR dose had similar fitness to control individuals (not exposed to UVR), but they showed a significant reduction in daily movement. The re-occurring threat response to the fluctuating UVR treatment thus had strong fitness costs for D. magna , and we found no evidence for plastic behavioural responses when continually being exposed to UVR, despite the regular, predictable exposure schedule. In a broader context, our results imply that depending on how variable a stressor is in nature, populations may respond with alternative strategies, a framework that could promote rapid population differentiation and local adaptation.