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Figure 5 in A PROTOCOL FOR RECORDING BEHAVIORAL ACTIVITY DURING LONGEVITY STUDIES OF ADULT CHIRONOMIDAE Abstract

Figure 5. Percent of behaviors recorded by adult flies collected from Valley Creek during longevity experi- ments with adults incubated at different temperatures.

Figure 2 in A PROTOCOL FOR RECORDING BEHAVIORAL ACTIVITY DURING LONGEVITY STUDIES OF ADULT CHIRONOMIDAE Abstract

Figure 2. Example of data sheet and daily records of behavior for a male and female collected from on snow, 17 Febru- ary 2019, adjacent to Hay Creek, Goodhue County, MN. The female oviposited in the vial on Day 4, post collection.

Figure 4 in A PROTOCOL FOR RECORDING BEHAVIORAL ACTIVITY DURING LONGEVITY STUDIES OF ADULT CHIRONOMIDAE Abstract

Figure 4. Percent of behaviors recorded by adult flies collected from Trout Brook during longevity experi- ments with adults incubated at different temperatures.

Figure 2. A in Oviposition behavior and host records for the parasitic midge Trichochilus lacteipennis (Johannsen) (Chironomidae: Orthocladiinae)

Figure 2. A female Trichochilus lacteipennis with egg string fully extruded, as it descended toward the water surface just prior to releasing the eggs.

Figure 3. A in Oviposition behavior and host records for the parasitic midge Trichochilus lacteipennis (Johannsen) (Chironomidae: Orthocladiinae)

Figure 3. A string of Trichochilus lacteipennis eggs suspended in water near the bottom of a glass rearing vessel.

Figure 1 in Oviposition behavior and host records for the parasitic midge Trichochilus lacteipennis (Johannsen) (Chironomidae: Orthocladiinae)

Figure 1. Two adult female Trichochilus lacteipennis hovering over Lake Umbagog, in the process of extruding strings of eggs.

Figure 4 in Oviposition behavior and host records for the parasitic midge Trichochilus lacteipennis (Johannsen) (Chironomidae: Orthocladiinae)

Figure 4. Four Trichochilus lacteipennis pupae revealed by incision of the outer lamella (marsupium) of the right gill of an Elliptio complanata.

Figure 3 in A PROTOCOL FOR RECORDING BEHAVIORAL ACTIVITY DURING LONGEVITY STUDIES OF ADULT CHIRONOMIDAE Abstract

Figure 3. Percent of behaviors recorded by adult flies collected from Hay Creek during longevity experiments with adults incubated at different temperatures.

opencc-zeroDec 2022View details →

Behavioral responses of terrestrial mammals to COVID-19 lockdowns

COVID-19 lockdowns in early 2020 reduced human mobility, providing an opportunity to disentangle its effects on animals from those of landscape modifications. Using GPS data, we compared movements and road avoidance of 2300 terrestrial mammals (43 species) during the lockdowns to the same period in 2019. Individual responses were variable, with no change in average movements or road avoidance behavior, likely due to variable lockdown conditions. However, under strict lockdowns, 10-day 95th percentile displacements increased by 73%, suggesting increased landscape permeability. Animals' 1-hour 95th percentile displacements declined by 12%, and animals were 36% closer to roads in areas of high human footprint, indicating reduced avoidance during lockdowns. Overall, lockdowns rapidly altered some spatial behaviors, highlighting variable but substantial impacts of human mobility on wildlife worldwide.

opencc-by-4.0Jun 2023View details →

CESNET-MINER22-TS: Periodic Behavior Features of Cryptomining Communication

CESNET-MINER22-TS: Periodic Behavior Features of Cryptomining CommunicationDatasets were created for the paper: Enhancing DeCrypto: Finding Cryptocurrency Miners Based on Periodic Behavior -- Josef Koumar, Richard Plný, Tomáš Čejka -- which was published at The 19th International Conference on Network and Service Management (CNSM) 2023. Please cite usage of our datasets as:  <blockquote>J. Koumar, R. Plný and T. Čejka, "Enhancing DeCrypto: Finding Cryptocurrency Miners Based on Periodic Behavior," 2023 19th International Conference on Network and Service Management (CNSM), Niagara Falls, ON, Canada, 2023, pp. 1-7, doi: 10.23919/CNSM59352.2023.10327904.</blockquote> The files cesnet_miner22_design_with_FTS_proba.zip and cesnet_miner22_evaluation_with_FTS_proba.zip contain one .csv file with IP flows. The IP flows were taken from the CESNET-MINER22 dataset [1], which was created by monitoring national research and educational network CESNET2. Furthermore, we add two features ID_DEPENDENCY (string) and PERIODICITY_PROBA (double). ID_DEPENDENCY is an ID of a network dependency (see the article [2]) and the PERIODICITY_PROBA is the predicted probability by FTS analysis. The files from periodicity_features.zip contain periodic behavior features for Machine Learning. The files names are in format "{evaluation/design}.periodicity_features.{TIME_INTERVAL}.{SIG_SPACE}.{PER_LEVEL}.csv" and have the following format of columns:<ul><li>id_dependency -- Identification of a network dependency observed as a Flow time series (FTS).</li><li>label -- The labels ("Miner" or "Other") of periodic FTS.</li><li>packet_value -- Value of Clear periodic behavior of the metric packet.</li><li>packet_value_x -- Value of the interval's lower value of Sinusoidal periodic behavior of the metric packets.</li><li>packet_value_y -- Value of the interval's upper value of Sinusoidal periodic behavior of the metric packets.</li><li>packet_mean -- Mean value of the metric packet.</li><li>packet_std -- Standard deviation value of the metric packet.</li><li>packet_skewness -- Skewness value of the metric packet.</li><li>packet_kurtosis -- Kurtosis value of the metric packet.</li><li>bytes_value -- Value of Clear periodic behavior of the metric bytes.</li><li>bytes_value_x -- Value of the interval's lower value of Sinusoidal periodic behavior of the metric bytes.</li><li>bytes_value_y -- Value of the interval's upper value of Sinusoidal periodic behavior of the metric bytes.</li><li>bytes_mean -- Mean value of the metric bytes.</li><li>bytes_std -- Standard deviation value of the metric bytes.</li><li>bytes_skewness -- Skewness value of the metric bytes.</li><li>bytes_kurtosis -- Kurtosis value of the metric bytes.</li><li>duration_value -- Value of Clear periodic behavior of the metric duration.</li><li>duration_value_x -- Value of the interval's lower value of Sinusoidal periodic behavior of the metric duration.</li><li>duration_value_y -- Value of the interval's upper value of Sinusoidal periodic behavior of the metric duration.</li><li>duration_mean -- Mean value of the metric duration.</li><li>duration_std -- Standard deviation value of the metric duration.</li><li>duration_skewness -- Skewness value of the metric duration.</li><li>duration_kurtosis -- Kurtosis value of the metric duration.</li><li>difftimes_value -- Value of Clear periodic behavior of the metric difftimes.</li><li>difftimes_value_x -- Value of the interval's lower value of Sinusoidal periodic behavior of the metric difftimes.</li><li>difftimes_value_y -- Value of the interval's upper value of Sinusoidal periodic behavior of the metric difftimes.</li><li>difftimes_mean -- Mean value of the metric difftimes.</li><li>difftimes_std -- Standard deviation value of the metric difftimes.</li><li>difftimes_skewness -- Skewness value of the metric difftimes.</li><li>difftimes_kurtosis -- Kurtosis value of the metric difftimes.</li><li>max_power -- Represent the maximum power of the LS periodogram.</li><li>max_frequency -- Describe the frequency of the maximum power of the LS periodogram.</li><li>min_power -- Represent the minimum power of the LS periodogram.</li><li>min_frequency -- Describe the frequency of the minimum power of the LS periodogram.</li><li>spectral_energy -- Represents the total energy present at all frequencies in LS periodogram.</li><li>spectral_entropy -- The degree of randomness or disorder in the LS periodogram.</li><li>spectral_kurtosis -- Indicates a nonstationary or non-Gaussian behavior in the power spectrum.</li><li>spectral_skewness -- The measure of peakedness or flatness of power spectrum.</li><li>spectral_rolloff -- It is defined as frequency below 85% of the distribution power.</li><li>spectral_cetroid -- Indicates at which frequency the energy of a spectrum is centered upon.</li><li>spectral_spread -- It is the difference between the highest and lowest frequency in the power spectrum.</li><li>spectral_slope -- The slope of the power spectrum trend in a given frequency range.</li><li>spectral_crest -- Refers to the rate of shift of the sign of a wave, which is the rate of change from negative to positive or the reverse.</li><li>spectral_flux -- The rate of change of periodogram power with increasing frequency.</li><li>spectral_bandwidth -- Describes the difference between upper and lower frequencies at which spectral energy is half its maximum value.</li></ul> The files from time_series.zip contain FTS of used time interval. The file names are in format "{evaluation/design}.time_series.{TIME_INTERVAL}.csv" and have the following format of columns:<ul><li>ID_DEPENDENCY -- Identification of a network dependency observed as a FTS.</li><li>N_FLOWS -- Number of flows in time series, i.e., number of data points.</li><li>N_PACKETS -- Number of packets in time series, i.e., the sum of metric PACKETS.</li><li>N_BYTES -- Number of bytes in time series, i.e., the sum of metric PACKETS.</li><li>PACKETS -- The array containing the time series metric number of packets in the IP flow.</li><li>BYTES -- The array containing the time series metric number of bytes in the IP flow.</li><li>START_TIMES -- The array containing the time series time axis of the flows starts.</li><li>END_TIMES -- The array containing the time series time axis of the flows ends.</li><li>LABELS -- The array of labels ("Miner" of "Other") of each datapoint.</li></ul> [1] Richard Plný et al. CESNET-MINER22: Datasets of Cryptomining Communication. Zenodo, October 2022.[2] Koumar, Josef, and Tomáš Čejka. "Network traffic classification based on periodic behavior detection." 2022 18th International Conference on Network and Service Management (CNSM). IEEE, 2022.

opencc-zeroJun 2023View details →

Data for: Home security cameras as a tool for behavior observations and science equity

Reliably capturing transient animal behavior in the field and laboratory remains a logistical and financial challenge, especially for small ectotherms. Here, we present a camera system that is affordable, accessible, and suitable to monitor small, cold-blooded animals historically overlooked by commercial camera traps, such as small amphibians. The system is weather-resistant, can operate offline or online, and allows collection of time-sensitive behavioral data in laboratory and field conditions with continuous data storage for up to four weeks. The lightweight camera can also utilize phone notifications over Wi-Fi so that observers can be alerted when animals enter a space of interest, enabling sample collection at proper time periods. We present our findings, both technological and scientific, in an effort to elevate tools that enable researchers to maximize use of their research budgets. We discuss the relative affordability of our system for researchers in South America, which is home to the largest population of ectotherm diversity.

opencc-by-4.0Jul 2016View details →

Figure 2 in Bombus impatiens (Hymenoptera: Apidae) display reduced pollen foraging behavior when marked with bee tags vs. paint

Figure 2. Curves showing the cumulative percentage of bees that performed sonication on Solanum lycopersicum L. after being marked with paint vs. bee tags, out of the total number of marked bees recovered by the end of the experiment (n paint = 83; n tag = 94; n missing = 34). The "+" symbols indicate censored data — bees that never were observed collecting pollen after being marked, within the time constraints of the experiment.

opencc-zeroJun 2023View details →

Differences in boundary behavior in the 3D vertex and Voronoi models

An important open question in the modeling of biological tissues is how to identify the right scale for coarse-graining, or equivalently, the right number of degrees of freedom. For confluent biological tissues, both vertex and Voronoi models, which differ only in their representation of the degrees of freedom, have effectively been used to predict behavior, including fluid-solid transitions and cell tissue compartmentalization, which are important for biological function. However, recent work in 2D has hinted that there may be differences between the two models in systems with heterotypic interfaces between two tissue types, and there is a burgeoning interest in 3D tissue models. Therefore, we compare the geometric structure and dynamic sorting behavior in mixtures of two cell types in both 3D vertex and Voronoi models. We find that while the cell shape indices exhibit similar trends in both models, the registration between cell centers and cell orientation at the boundary are significantly different between the two models. We demonstrate that these macroscopic differences are caused by changes to the cusp-like restoring forces introduced by the different representations of the degrees of freedom at the boundary and that the Voronoi model is more strongly constrained by forces that are an artifact of the way the degrees of freedom are represented. This suggests that vertex models may be more appropriate for 3D simulations of tissues with heterotypic contacts.

opencc-zeroJun 2023View details →

Data from: Recombination as an enforcement mechanism of prosocial behavior in cooperating bacteria

Prosocial behavior is ubiquitous despite the relative fitness costs carried by cooperative individuals. However, the stability of cooperation in populations is fragile, and often maintained through enforcement. We propose that homologous recombination provides such a mechanism in bacteria. Using an agent-based model of recombination in a population of bacteria playing a public goods game, we demonstrate how changes in recombination rate affect the proportion of cooperating cells. In our model, recombination converts cells to a different strategy, either freeloading (cheaters) or cooperation, based on the strategies of neighboring cells and the recombination rate. Increasing the recombination rate expands the parameter space in which cooperators dominate freeloaders. However, increasing the recombination rate alone is neither sufficient nor necessary. Intermediate benefits of cooperation, lower population viscosity, and higher population size can promote cooperation in a population of cheater strains. Our findings demonstrate how recombination influences the persistence of cooperative behavior in bacteria.

Fig. 3 in Motor Stereotypic Behaviors In Zoo Rhesus Monkeys: A Case Study Of The Central Zoo, Kathmandu, Nepal

Fig. 3. Motor stereotypic behavior performed by the captive rhesus monkeys; A — under different time of the day; B — under different begging intensities (ns = statistically not significant difference).

Fig. 4. Probable relationship between the MSB and begging. A in Motor Stereotypic Behaviors In Zoo Rhesus Monkeys: A Case Study Of The Central Zoo, Kathmandu, Nepal

Fig. 4. Probable relationship between the MSB and begging. A — by controlling for sex of the captive monkeys; and, B — by controlling for the different probability of the visitor-monkey interaction (Min. — minutes).

Fig. 2 in Motor Stereotypic Behaviors In Zoo Rhesus Monkeys: A Case Study Of The Central Zoo, Kathmandu, Nepal

Fig. 2. Motor stereotypic behavior shown by the captive rhesus monkeys: A — difference between males and females; and B — on the basis of the different rearing histories (*** statistically significant difference).

Fig. 1 in Motor Stereotypic Behaviors In Zoo Rhesus Monkeys: A Case Study Of The Central Zoo, Kathmandu, Nepal

Fig. 1. Mean time invested on motor stereotypic behavior per focal sampling bout of 30 minutes by adult males and females (*** statistically significant difference).

opencc-by-4.0Nov 2022View details →

Apulian Aqueduct demo site: daily time series of simulated system behavior for future inflows conditions (RCP4.5)

This dataset contains the daily time series obtained from the strategic model simulation, considering net estimated inflows (natural springs and main reservoirs of Apulian aqueduct - demo site 1) considering climate projection RCP 4.5 and two decades, in the medium (2050-2059) and long-term future (2090-2099). In all simulations, a modified version of the drinking water demand is considered, following a different distribution of the populations, an increase in density in coastal areas also due to investments in the tourism sector, to the detriment of density in inland areas. For each decade, two simulations are performed, with or without the rehabilitation of some well-fields making the water withdrawn drinkable with innovative purification techniques. . More precisely, the dataset contains: <ul> <li>the daily level of the main reservoirs;</li> <li>the water supplied to all users (drinking water users, irrigation, and industrial districts) from each reservoir;</li> <li>the corresponding single irrigation and industrial deficit;</li> <li>the total drinking water deficit;</li> <li>the aggregated distribution cost.</li> </ul> Two simulations are performed, with or without the environmental flow constraint acting on each reservoir release activated. <ul> <li>Temporal coverage: 2050-2059; 2090-2099</li> <li>Spatial coverage: <ul> <li>Springs: Sele, Calore;</li> <li>Reservoirs: Conza, Locone, Monte Cotugno, Occhito, Pertusillo;</li> <li>Users: drinking water users, irrigation, and industrial districts supplied by Apulian aqueduct.</li> </ul> </li> <li>Unit of measure: m, m3/s depending on the variable</li> </ul> More information and details on the content of this dataset can be found in Project Ô <a href="https://zenodo.org/record/7576611">Deliverable D4.4</a>.