Warning Signals Research Articles

Spatially differential regulation of ATF2 phosphorylation contributes to warning coloration of gregarious locusts.

Warning coloration are common defense strategies used by animals to deter predators. Pestilential gregarious locusts exhibit a notable black-brown pattern as a form of warning coloration. However, the mechanisms regulating this distinctive pattern remain largely unknown. Here, we revealed that the black and brown integuments of locusts are governed by varying amounts of β-carotene and β-carotene-binding protein (βCBP) complexes. βCBP expression is regulated by the bZIP transcription factor activation transcription factor 2 (ATF2), which is activated by protein kinase C alpha in response to crowding. Specifically, ATF2 is phosphorylated at Ser327 and translocates to the nucleus, where it binds to the βCBP promoter and stimulates overexpression. Differential phosphorylation of ATF2 leads to the divergent black and brown coloration in gregarious locusts. The accumulation of red pigments vital for creating the brown sternum depends on βCBP overexpression. The spatial variation in ATF2 phosphorylation enables locusts to rapidly adapt to changing environment for aposematism.

Detecting signs of model change with continuous model selection based on descriptive dimensionality

We address the issue of detecting changes of models that lie behind a data stream. The model refers to an integer-valued structural information such as the number of free parameters in a parametric model. Specifically we are concerned with the problem of how we can detect signs of model changes earlier than they are actualized. To this end, we employ continuous model selection on the basis of the notion of descriptive dimensionality (Ddim). It is a real-valued model dimensionality, which is designed for quantifying the model dimensionality in the model transition period. Continuous model selection is to determine the real-valued model dimensionality in terms of Ddim from a given data. We propose a novel methodology for detecting signs of model changes by tracking the rise-up/descent of Ddim in a data stream. We apply this methodology to detecting signs of changes of the number of clusters in a Gaussian mixture model and those of the order in an auto regression model. With synthetic and real data sets, we empirically demonstrate its effectiveness by showing that it is able to visualize well how rapidly model dimensionality moves in the transition period and to raise early warning signals of model changes earlier than they are detected with existing methods.

In paired preference tests, domestic chicks innately choose the colour green over red, and the shape of a frog over a sphere when both stimuli are green

Many animals express unlearned colour preferences that depend on the context in which signals are encountered. These colour biases may have evolved in response to the signalling system to which they relate. For example, many aposematic animals advertise their unprofitability with red warning signals. Predators’ innate biases against these warning colours have been suggested as one of the potential explanations for the initial evolution of aposematism. It is unclear, however, whether unlearned colour preferences reported in a number of species is truly an innate behaviour or whether it is based on prior experience. We tested the spontaneous colour and shape preferences of dark-hatched, unfed, and visually naive domestic chicks (Gallus gallus). In four experiments, we presented chicks with a choice between either red (a colour typically associated with warning patterns) or green (a colour associated with palatable cryptic prey), volume-matched spheres (representing a generalised fruit shape) or frogs (representing an aposematic animal’s shape). Chicks innately preferred green stimuli and avoided red. Chicks also preferred the shape of a frog over a sphere when both stimuli were green. However, no preference for frogs over spheres was present when stimuli were red. Male chicks that experienced a bitter taste of quinine immediately before the preference test showed a higher preference for green frog-shaped stimuli. Our results suggest that newly hatched chicks innately integrate colour and shape cues during decision making, and that this can be augmented by other sensory experiences. Innate and experience-based behaviour could confer a fitness advantage to novel aposematic prey, and favour the initial evolution of conspicuous colouration.

A review on plankton as a bioindicator: A promising tool for monitoring water quality

AbstractBioindicators have become increasingly popular and have contributed significant amounts of useful information to the process of managing water resources. The ability of a species (or species assemblage) to adapt to a certain range of chemical, physical, and biological conditions is one criterion that can be used to assess the quality of its surrounding environment. Planktons that react quickly to changes in their environment have proven to be particularly valuable, and the identification of certain indicator species has become increasingly common in the process of determining the quality of the water. The “health” of an aquatic system can be inferred from the presence or absence of plankton, which act as early warning signals. When compared with the expense of assessing harmful contaminants, the overall cost of conducting routine monitoring of biological communities is far lower and has a higher degree of reliability. The ability of bioindicators to identify indirect biotic effects of pollutants, which is something that many physical or chemical tests are unable to do, is another advantage of using bioindicators. Different aquatic species as bioindicators tolerate different environmental conditions, and their different tolerances to particular environments help in identifying a particular environmental condition. Phytoplankton species like Euglena viridis, Oscillatoria limosa, Nitzschia palea, and Scenedesmus quadricauda, and zooplankton species like Branchionus sp., Molina sp., Keratella cochlearis, Daphnia sp., and Cyclopus sp. indicate water pollution. This review's objective is to highlight some recent research on planktons, focusing on their capabilities and opportunities for application as bioindicators of water quality.

Protocol for establishing a model for integrated influenza surveillance in Tamil Nadu, India.

The potential for influenza viruses to cause public health emergencies is great. The World Health Organisation (WHO) in 2005 concluded that the world was unprepared to respond to an influenza pandemic. Available surveillance guidelines for pandemic influenza lack the specificity that would enable many countries to establish operational surveillance plans. A well-designed epidemiological and virological surveillance is required to strengthen a country's capacity for seasonal, novel, and pandemic influenza detection and prevention. Here, we describe the protocol to establish a novel mechanism for influenza and SARS-CoV-2 surveillance in the four identified districts of Tamil Nadu, India. This project will be carried out as an implementation research. Each district will identify one medical college and two primary health centres (PHCs) as sentinel sites for collecting severe acute respiratory infections (SARI) and influenza like illness (ILI) related information, respectively. For virological testing, 15 ILI and 10 SARI cases will be sampled and tested for influenza A, influenza B, and SARS-CoV-2 every week. Situation analysis using the WHO situation analysis tool will be done to identify the gaps and needs in the existing surveillance systems. Training for staff involved in disease surveillance will be given periodically. To enhance the reporting of ILI/SARI for sentinel surveillance, trained project staff will collect information from all ILI/SARI patients attending the sentinel sites using pre-tested tools. Using time, place, and person analysis, alerts for abnormal increases in cases will be generated and communicated to health authorities to initiate response activities. Advanced epidemiological analysis will be used to model influenza trends over time. Integrating virological and epidemiological surveillance data with advanced analysis and timely communication can enhance local preparedness for public health emergencies. Good quality surveillance data will facilitate an understanding outbreak severity and disease seasonality. Real-time data will help provide early warning signals for prevention and control of influenza and COVID-19 outbreaks. The implementation strategies found to be effective in this project can be scaled up to other parts of the country for replication and integration.

Flash drought evaluation using evaporative stress and evaporative demand drought indices: a case study from Awash River Basin (ARB), Ethiopia

Drought is one of the most devastating phenomena that affect the livelihood of most communities in Ethiopia as they have low adaptive capacity. Recent advancements in remote sensing and drought investigations have made it possible to identify a new type of flash drought that has rapid intensification with a short duration (i.e., less than 1 month unlike conventional droughts). This study intends to identify flash drought in the Awash River Basin (ARB) based on Moderate Resolution Imaging Spectroradiometer (MODIS) data of actual evapotranspiration and potential evapotranspiration using Evaporative Demand Drought Index (EDDI) and Evaporative Stress Index (ESI) indices. The flash drought result exhibited that agricultural lands, grasslands, vegetation areas, and irrigational croplands along the river were vulnerable to flash drought in the ARB. Using ESI, the area of ARB that experienced flash drought in 2002, 2008, 2009, 2012, and 2015 were 23%, 40%, 20%, 40%, and 24%, respectively. These intense flash drought areas can be used as drought monitoring sites. The flash drought extent of EDDI is more compared to ESI because of ESI’s dependency on vegetation coverages and soil moisture. The lowland downstream part of the ARB is highly prone to flash drought, particularly in the major rainy season (MRS) and the last two months of the minor rainy season (mRS). EDDI can discern the onset of flash drought better compared to ESI, but both can be used as a drought early warning mechanisms to minimize agricultural losses and drought-associated risks in the basin.

Analysing financial stability reports as crisis predictors with the use of text-mining

Central bank analyses and external communication play an important role in maintaining its credibility, as well as effectiveness of monetary and macroprudential policies. A financial stability report is one of the main channels of communication between central banks and the financial market. The aim of the study is to verify whether the linguistic content of those reports contains early warning signals of an upcoming financial crisis. We carefully select 848 words related to Early Warning Indicators and examine whether their appearance in the 604 financial stability reports published by 18 central banks could have indicated an impending global financial crisis (2007+). We use the novel approach of joint application of text-mining and the concept of receiver operating characteristic curve to compare the frequency of selected words before and after the global financial crisis. According to the results, the linguistic content of financial stability reports does not emit any early warning signals (except for the single case of the Central Bank of Iceland). On the one hand, this may indicate potential weaknesses in the quality of analyses in those reports, but on the other hand, it may show a central bank's deliberate avoidance of actions prompting negative effects of a ‘self-fulfilling prophecy’.

Loss-of-Control Prediction of a Quadcopter Using Recurrent Neural Networks

Loss of control (LOC) is a prevalent cause of drone crashes. Onboard prevention systems should be designed requiring low computing power, for which data-driven techniques provide a promising solution. This study proposes the use of recurrent neural networks (RNNs) for LOC prediction. Four architectures were trained in order to identify which RNN configuration is most suitable and if this model can predict LOC for changing aerodynamic characteristics, wind conditions, quadcopter types, and LOC events. One-hundred and seventy-two real-world LOC events were conducted using a 53 g Tiny Whoop, a 73 g URUAV UZ85, and a 265 g GEPRC CineGO quadcopter. For these flights, LOC was initiated by demanding an excessive yaw rate (2000 deg/s), which provokes an unrecoverable upset and subsequent crash. All RNNs were trained using only onboard sensor measurements. It was found that the commanded rotor values provided the clearest early warning signals for LOC because these values showed saturation before LOC. Moreover, all four architectures could correctly and reliably predict the impending LOC event 2 s before it actually occurred. Furthermore, to investigate generality of the methodology, the predictors were successfully applied to flight data in which the quadcopter mass, blade diameter, and blade count were varied.

Pupal warning color development in above‐ground pupating species but cryptic color in ground‐surface pupating species of the nine‐spotted diurnal moths (Erebidae: Arctiinae: Syntomini)

AbstractInsects usually have cryptic colors to avoid detection by visually hunting predators. However, if the insects acquire toxic or repellent substances against predators, some of them develop conspicuous coloration to exhibit their unpalatability. Such warning colors allow insects to survive. In the nine‐spotted diurnal moths (Erebidae: Arctiinae: Syntomini), we found the above‐ground pupating species to have conspicuous colored pupae, but the ground‐surface pupating species to have cryptic colored pupae. In this study, the relationships between unpalatability and coloration of these pupae are examined among three species of Amata and one species of Syntomoides. Pupae of the two species (A. germana and A. flava) are conspicuous in their color pattern with seven black dotted lines longitudinally on their pale‐yellow bodies. These pupae are exposed to the aerial predators in a coarse silk mesh hanging from leaves and/or branches. The other two species (A. fortunei and S. imaon) pupate in spaces under stones, fallen twigs and leaves on the ground surface, and the pupae in a coarse silk cocoon is cryptic dark brown. Their pupation site selections are reproduced in the rearing glass vessels. Palatability assessment using lizards as a potential predator suggests that pupae of A. germana, A. flava and A. fortunei are unpalatable and the lizard's feeding response decreases with experience. However, pupae of S. imaon are all eaten (palatable). Finally, the possible evolutionary scenario of pupal colors of these four species is discussed in relation to pupation site selection and palatability.

Anticipating critical transitions in psychological systems using early warning signals: Theoretical and practical considerations.

Many real-world systems can exhibit tipping points and multiple stable states, creating the potential for sudden and difficult to reverse transitions into a less desirable regime. The theory of dynamical systems points to the existence of generic early warning signals that may precede these so-called critical transitions. Recently, psychologists have begun to conceptualize mental disorders such as depression as an alternative stable state, and suggested that early warning signals based on the phenomenon of critical slowing down might be useful for predicting transitions into depression and other psychiatric disorders. Harnessing the potential of early warning signals requires us to understand their limitations as well as the factors influencing their performance in practice. In this article, we (a) review limitations of early warning signals based on critical slowing down to better understand when they can and cannot occur, and (b) study the conditions under which early warning signals may anticipate critical transitions in online-monitoring settings by simulating from a bistable dynamical system, varying crucial features such as sampling frequency, noise intensity, and speed of approaching the tipping point. We find that, in sharp contrast to their reputation of being generic or model-agnostic, whether early warning signals occur or not strongly depends on the specifics of the system. We also find that they are very sensitive to noise, potentially limiting their utility in practical applications. We discuss the implications of our findings and provide suggestions and recommendations for future research. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

A Head-Mounted Assistive Device for Visually Impaired People with Warning System from Object Detection and Depth Estimation

People with visual impairment use white cane as their traditional method for perceiving the surroundings. However, the utilization of a cane is limited by its length and orientation. In Thailand, the obstacles on paveway in daily life are not located only on the floor but also above knee level which sometimes could be harmful to pedestrians, especially blind people. A head-mounted assistive device is developed to be an enhancement used with a cane for the visually impaired to comprehend their environment both lower and higher the knee level. The assistive device is designed to be compact and light-weight. It could also send the tactile feedback as a warning from vibration motors mounted on the device. To generate a warning signal, YOLOv4 is used to detect the location of obstacles and depth map from the stereo camera is used to estimate the distance mapping into 4 defined ranges: dangerous, very close, close and fine. The results indicate that the head-mounted assistive device has the ability to perceive obstacles locating farther than 0.9 m. The prediction returned 9.23%, 14.63% and 7.86% error when estimating the depth of obstacles at 1.3 m., 2.8 m. and 4.2 m. respectively. The average execution time for the device to return the command controlling vibration motors is 0.13 second and the maximum estimated time for the motor to send the haptic feedback is 1.05 second.

Increasingly cautious sampling, not the black colouration of unpalatable prey, is used by fish in avoidance learning.

The efficiency of aposematic colouration of prey is based on the innate bias or facilitation of avoidance learning of predators. In many toxic bufonids, larvae are uniformly black, which is considered a warning signal. We compared fish predation on normal (black) and 'transient albino' (greyish) common toad Bufo bufo tadpoles that did not differ in toxicity or activity. In a two-stage experiment, each fish was presented with tadpoles of one colour in the first trial and the other colour in a subsequent trial. While tadpoles sampled by fish were typically not ingested, some died from injuries. The attack rate did not differ between tadpole phenotypes nor trials, irrespective of which phenotype was the first exposed to the fish. However, during the second trial, the sampled tadpoles, independent of colouration, were mouthed by fish for shorter periods and tadpole mortality decreased. The duration of mouthing also declined with an increasing number of attacks during subsequent trials. We conclude that in single-species prey populations, black tadpole colouration is not a warning signal as it does not accelerate predator learning about prey unprofitability. Our results indicate that with growing experience, predators sample potentially toxic prey more cautiously. This may explain why natural selection does not eliminate aposematic morphs even if predators continuously sample conspicuous prey.

Scenario Planning of PLN Indonesia Power in 2030: To Be a Leading Green and Sustainable Power Generation Company

Following the company's transformation in 2023, PLN IP's generating capacity now reached 21 GW, establishing it as the largest power generation company in Southeast Asia. However, most of PLN IP's power plants rely on fossil fuels. Therefore, the purpose of this study is to formulate a strategy that enables PLN IP to become a leading sustainable company and support Indonesia's target of achieving a renewable energy mix of 24.8% by 2030. The scenario planning method is used in this study to anticipate and prepare for future critical uncertainties that may impact the business of PLN IP. Critical uncertainties are obtained from analyzing the company's business, which is then elaborated with the results of semi-structured interviews from internal and external stakeholders. Five scenarios have been identified, namely: Parking the Bus, Kick & Rush, Tiki Taka, Gegenpressing, and Catenaccio. Each scenario is driven by a different critical uncertainty, consisting of electricity supply and demand, fuel prices, regulations, technological advancements, and investments. Key leading indicators of driving factors have been determined to detect potential scenario trends as early warning signals. This study is expected to serve as a reference for policymakers and stakeholders in the electricity sector to apply a balanced strategy for providing clean, reliable, and affordable electricity in Indonesia.

Signal detectability and boldness are not the same: the function of defensive coloration in nudibranchs is distance-dependent.

Aposematic signals visually advertise underlying anti-predatory defences in many species. They should be detectable (e.g. contrasting against the background) and bold (e.g. using internal pattern contrast) to enhance predator recognition, learning and memorization. However, the signalling function of aposematic colour patterns may be distance-dependent: signals may be undetectable from a distance to reduce increased attacks from naïve predators but bold when viewed up close. Using quantitative colour pattern analysis, we quantified the chromatic and achromatic detectability and boldness of colour patterns in 13 nudibranch species with variable strength of chemical defences in terms of unpalatability and toxicity, approximating the visual perception of a triggerfish (Rhinecanthus aculeatus) across a predation sequence (detection to subjugation). When viewed from an ecologically relevant distance of 30 cm, there were no differences in detectability and boldness between well-defended and undefended species. However, when viewed at closer distances (less than 30 cm), well-defended species were more detectable and bolder than undefended species. As distance increased, detectability decreased more significantly than boldness for defended species. For undefended species, boldness and detectability remained comparatively consistent, regardless of viewing distance. We provide evidence for distance-dependent signalling in aposematic nudibranchs and highlight the importance of distinguishing signal detectability from boldness in studies of aposematism.

Adaptive Scenario Planning Development for Indonesian Upstream Oil and Gas Industry: Case Study of PT Kelola Migas in Managing Mature Field Phase

The global economic conditions after the COVID pandemic, which have not fully recovered, the vulnerability of global oil prices due to unpredictable external factors, global pressure for decarbonization efforts and the fulfillment of Environmental, Social and Governance (ESG) parameters to support energy transition, the less competitive condition of oil and gas reserves in Indonesia, and the contract schemes and fiscal incentives in Indonesia that are considered unattractive by investors are part of the tip of the iceberg of uncertainty in the external conditions of the upstream oil and gas industry in Indonesia. In relation to the above conditions, PT Kelola Migas (PT KM) requires a comprehensive strategy formulation process based on a long-term understanding of potential future scenarios that focus on external factors as uncontrollable factors that will significantly impact the company. This research is conducted with a focus on the use of adaptive scenario planning methodology, which will provide a fresh perspective for PT KM in utilizing strategic tools oriented towards the medium and long term. Exploring the implications and mitigation options for each scenario is conducted to provide strategic choices in facing potential situations. The identification of early warning signals for each scenario is also carried out as indicators of changes in the current situation towards one scenario or another.

Application and Exploration of Early Warning Mechanism in Abnormal Use of Large Sharing Instruments

With the continuous investment of the national "Double First Class" universities, the financial investment of universities has increased year by year, and the purchased instruments have correspondingly grown rapidly. At the same time, the performance evaluation standards for large-scale shared instruments by national ministries and commissions are gradually improving, and higher requirements are being put forward for instrument sharing and management. In the process of large-scale instrument sharing in universities, there are common problems such as insufficient management personnel, inadequate management, and difficulty in implementing responsibilities. By utilizing the usage data in the shared platform data warehouse, analyzing relevant data such as usage time intervals, personal behavior, and user affiliation units, a preliminary evaluation of the reasonable usage interval is made. Combined with the use of early warning mechanisms, feedback from users is utilized to continuously optimize the usage warning values, This provides a solution for strengthening the digital management of large-scale instruments.

An enhancement in the management practices of geoduck clam Panopea globosa: The estimation of reference points in the short and long term

For sedentary species under fishing pressure, a precautionary approach is required to avoid collapses. Therefore, the estimation of early warning signals prior to population collapse is a powerful tool for prioritizing the best fishery management practices. In Mexico, the fishery of geoduck clam began in 2000 as a profitable activity given the high demand for the resource in East and Southeast Asia countries. In the short term, Panopea globosa exhibited a rapid depletion, mainly because the legal regulations did not determine reference points (RPs) for harvest. In this study, three approaches were analyzed: i) a biomass model based on spatial distribution, Bt/B0; ii) an age structured yield-per-recruit model, YPRA; and iii) a size structured yield-per-recruit model, YPRL, providing the estimation of reference points in the short and long term for the species. The results indicated that the long-term reference point (Bt/B0) was reached during 2018, suggesting the implementation of recovery actions rather than continuing with fishing pressure on geoduck clam. Comparatively, the short term reference points (YPRA and YPRL) were not sufficiently informative on the annual stock condition; however, they showed negative tendencies on the yield per recruit over time. In this study, the estimation of complementary RPs provides a direct contribution to geoduck clam fishery management, which completes one more step in the process of adaptive management, avoiding losses in short term yield and long term overfishing. However, the active participation of governmental agencies is necessary to incorporate this new knowledge into the legal Mexican fishery guidelines.

Reproductive interference is stronger than expected in Heliconius butterflies

AbstractIn animals, reproductive interference associated with mimicry can result in the evolution of private communication channels, as suggested for Heliconius butterflies, where cryptic color wavelength would drive male preference for conspecific over intergeneric co‐mimics. Here, we tested this hypothesis in two co‐mimic pairs (intra and intergeneric) and measured the efficacy and symmetry of color pattern as a reproductive barrier in a non‐co‐mimic, possibly hybridizing pair of Heliconius species. We conducted pairwise experiments of preference where a group of males was presented to a conspecific and heterospecific female model made with real wings and free of chemical volatiles. We did not detect any indication of the expected use of cryptic recognition signals to mate choice in the intergeneric co‐mimic pair. Additionally, we detected an unexpected male preference for heterospecific female models between intrageneric co‐mimics towards the species with larger red patches, suggesting a supernormal stimulus based on a general preference for the red color. Finally, we found an asymmetry in the behavioral reproductive barrier between the non‐co‐mimic closely related species that also agrees with the hypothesis of a general preference for red and with an expected permeability of the reproductive barrier between them. Since the costs imposed by heterospecific courtships can limit the convergence of signaling phenotypes, our results contribute to explaining the maintenance of multiple aposematic color pattern between unpalatable and closely related sympatric Heliconius species.

EWSmethods: an R package to forecast tipping points at the community level using early warning signals, resilience measures, and machine learning models

Early warning signals (EWSs) represent a potentially universal tool for identifying whether a system is approaching a tipping point, and have been applied in fields including ecology, epidemiology, economics, and physics. This potential universality has led to the development of a suite of computational approaches aimed at improving the reliability of these methods. Classic methods based on univariate data have a long history of use, but recent theoretical advances have expanded EWSs to multivariate datasets, particularly relevant given advancements in remote sensing. More recently, novel machine learning approaches have been developed but have not been made accessible in the R (www.r‐project.org) environment. Here, we present EWSmethods – an R package that provides a unified syntax and interpretation of the most popular and cutting edge EWSs methods applicable to both univariate and multivariate time series. EWSmethods provides two primary functions for univariate and multivariate systems respectively, with two forms of calculation available for each: classical rolling window time series analysis, and the more robust expanding window. It also provides an interface to the Python machine learning model EWSNet which predicts the probability of a sudden tipping point or a smooth transition, the first of its form available to R users. This note details the rationale for this open‐source package and delivers an introduction to its functionality for assessing resilience. We have also provided vignettes and an external website to act as further tutorials and FAQs.

Mechanical strain signal based early warning for failure of different prismatic lithium-ion batteries

Thermal runaway propagation (TRP) is the most challenging safety issue of lithium-ion battery systems. An early warning signal is promising for providing time to mitigate or prevent TRP and further disasters timely. This study investigates the strain characteristics of different format prismatic batteries during the TR/TRP processes, dividing the strain-changing trend into three stages according to the complex chemical composition interactions and TR features. Experimental results prove that the signal provides more than a 500s interval for a timely solution from the battery management system. Besides, the maximum strain increment (Δεmax)/capacity(Q)-Q equalization is quantitively analyzed. Moreover, Δεmax-Q and RI-Q equalizations are proposed to reveal the TR mechanical feature and guide the TR warning threshold definition of battery management systems (BMSs). Furthermore, the strain-changing trend and warning effect is also proved in TRP tests. TRP strain mechanism is unlocked from the mechanical deformation perspective. Battery deformation is opposite to the TRP direction, which guides accident analysis. This study proposes a cheap and reliable warning signal for an in-line configuration battery system, with only one strain gauge attached to the surface center of the first/last battery casing, which has more potential to guarantee the active safety of battery systems.