A practical guide for estimating animal density using camera traps: Focus on the REST model

Estimating animal density and finding the factors that influence it are central in wildlife conservation and management but challenging to achieve, particularly in forested areas. Camera trapping is a pervasive method in forest mammal survey and a plausible technique to overcome this challenge. This report provides a practical guide for conducting a camera trap survey to estimate the density of forest mammals applying the random encounter and staying time (REST) model. We firstly provide a brief explanation about the structure and assumptions of the REST model. Next, we describe essential points during different steps in planning a survey: determination of objectives, design of camera placement, choice of camera models, camera setting, the layout of the camera station, and list of covariates. We then develop detail-oriented instruction for conducting a survey and analysing the obtained video data. We encourage camera trap surveyors to provide the practised protocols of their surveys, which will be helpful to other camera trappers.

A Longitudinal Study of the Bladder Cancer Applying a State-Space Model with Non-Exponential Staying Time in States

A longitudinal study for 847 bladder cancer patients for a period of fifteen years is presented. After the first surgery, the patients undergo successive ones (recurrences). A state-model is selected for analyzing the evolution of the cancer, based on the distribution of the times between recurrences. These times do not follow exponential distributions, and are approximated by phase-type distributions. Under these conditions, a multidimensional Markov process governs the evolution of the disease. The survival probability and mean times in the different states (levels) of the disease are calculated empirically and also by applying the Markov model, the comparison of the results indicate that the model is well-fitted to the data to an acceptable significance level of 0.05. Two sub-cohorts are well-differenced: those reaching progression (the bladder is removed) and those that do not. These two cases are separately studied and performance measures calculated, and the comparison reveals details about the characteristics of the patients in these groups.

Steel logistics park layout based on market basket analysis and accessibility

In this study, we used market basket analysis and land accessibility for the layout of MG Steel Logistics Park. Due to the unreasonable cargo space layout, the outbound trucks in the MG Steel Logistics Park detour and transfer, which caused congestion. Using market basket analysis, this research took outbound trucks as the research object to measure the degree of correlation between cargo locations. Then, we measured the convenience of cargo locations by the accessibility and matched it with the steel outbound frequency. We established a model and got the layout allocation plan with the maximum degree of relevance and the minimum difference in cargo-location matching as the target. In the solution algorithm, we use roulette method and the elite retention strategy to improve the genetic algorithm. Finally, we compared the results before and after optimization. We found that the number of truck transfers was reduced by 33%, and the truck staying time was reduced by 21%.

Effects of Sesame Oil Aroma on Mice after Exposure to Water Immersion Stress: Analysis of Behavior and Gene Expression in the Brain

(1) Background: Sesame has been popular as a healthy food since ancient times, and effects of the aroma component of roasted sesame are also expected. However, little research has been reported on its scent; (2) Methods: Jcl:ICR male mice were housed under water immersion stress for 24 h. Then, the scent of saline or sesame oil was inhaled to stress groups for 90 min. We investigated the effects of sesame oil aroma on the behavior and brains of mice; (3) Results: In an elevated plus maze test, the rate of entering to open arm and the staying time were decreased by the stress. These decrements were significantly enhanced by sesame oil aroma. Stress had a tendency to increase the serum corticosterone concentration, which was slightly decreased by the aroma. Expression of Kruppel-like factor-4 (Klf-4) and Dual-specificity phosphatase-1 (Dusp-1) in the striatum were increased by water immersion stress, and the level of Klf-4 and Dusp-1 in the striatum and hippocampus were significantly attenuated by sesame oil aroma (4) Conclusions: The present results strongly suggest that the odor component of sesame oil may have stress suppressing effects. Moreover, Klf-4 and Dusp-1 may be sensitive stress-responsive biomarkers.

Optimal management of distance-based location registration using embedded Markov chain

In this study, we deal with a Distance-Based Registration with Implicit Registration, which is an enhanced scheme of the Distance-Based Registration in mobile-cellular networks. In comparisons with other Location Registration schemes, various studies on the Distance-Based Registration scheme and performance have been performed. However, a real network hierarchy has not been properly reflected in the performance evaluation of the Distance-Based Registration. To accurately evaluate the registration and paging costs of the Distance-Based Registration, a real network hierarchy should reflect that a mobile network is made up of many Visitor Location Register areas. Furthermore, we use an embedded Markov-Chain model in the Visitor Location Register hierarchy, which can reflect not only the Implicit Registration effect of the outgoing calls of user equipment but also cell staying time of the user equipment that may follow a general distribution. Without consideration of the Visitor Location Register, the paging cost decreases due to a small paging area, but the location registration cost rises because of frequent inter Visitor Location Register. The numerical results according to the various conditions show an accurate evaluation of the Distance-Based Registration performance in a real network hierarchy and the general cell staying time. Generally, the total signaling cost will increase when we consider the Visitor Location Register. However, for more appropriate evaluation of the Distance-Based Registration performance, it is necessary to consider the Visitor Location Register hierarchy.

Effects of Supraphysiological Doses of Testosterone Cypionate and Stanozolol on Neuronal Density of Basolateral and Medial Amygdala and on the Anxious Behavior of Mice

Supraphysiological doses of anabolic-androgenic steroids (AAS) have been associated to possible nerve tissue damage and behavioral effects. Considering the lack of knowledge of the neural aspects involved in these behavioral alterations, this work aimed to analyze the anxious behavior response or aggressiveness, besides quantifying the neuronal density of the basolateral amygdala (BLA) and of the ventral posterior nucleus (VPN) of the medial amygdala. The animals received doses of testosterone cypionate (CT Group) and stanozolol (ST Group) twice a week for 33 days. The effects of chronic administration of AAS related to anxious behavior (as determined by the elevated plus maze [EPM] test) in male animals are observed in a lower number of entries (< 45.25%), and a shorter staying time spent in the open arms (< 41.9%) was observed in the ST. In female animals, a longer staying time spent in the closed arms of the EPM test was observed in the CT (> 15%) as well as a shorter staying time spent in the open arms for CT (< 17.1%) also to ST (< 52.1%). Regarding the neuronal density in BLA, a significant reduction in neuronal density of male animals (17.55%) was observed only in CT, whereas for females, significant differences were found in CT (19.16%) and ST (18.36%). The reduction of neuronal density in VPN in male animals was 13.55% in CT and 17.68% in ST, whereas in group of females it was 13.53% and 14.32%, respectively for CT and ST. Therefore, the two steroids used in this experiment were able to significantly reduce neuronal density in two analyzed areas, regardless of sex, suggesting that indiscriminate use of these substances causes death of brain amygdala neurons.

Loitering Detection Based on Pedestrian Activity Area Classification

Loitering detection can help recognize vulnerable people needing attention and potential suspects harmful to public security. The existing loitering detection methods used time or target trajectories as assessment criteria, and only handled some simple loitering circumstances because of complex track. To solve these problems, this paper proposes a loitering detection method based on pedestrian activity area classification. The paper first gave loitering definition from a new perspective using the size of pedestrian activity area. The pedestrian loitering behaviors were divided into three categories. The proposed algorithms dynamically calculate enclosing rectangle, ellipse, and sector of pedestrian activity areas through curve fitting based on trajectory coordinates within given staying time threshold. The loitering is recognized if the pedestrian activity is detected to be constrained in an area within a certain period of time. The algorithm does not need to calculate complex trajectories. The PETS2007 dataset and our own self-collected simulated test videos were tested. The experimental results show that the proposed method accurately detected the pedestrian loitering, not only detected some loitering that the existing methods could not detect, but also distinguishing different types of loitering. The proposed method is effectiveness, robust, and simplified in implementation.