Adaptive Pattern Research Articles

The role of negative childhood experiences and internal stigma in the formation of motivation for the treatment of patients with mental disorders

Background: Motivation for treatment is an important component of patients' compliance to treatment of mental disorders, and its formation can be affected by different factors. The aim of the study: To analyze relationship between adverse childhood experiences, internal stigma and the intensity and structure of motivation to pharmaco-psychotherapy in patients with mental disorders. Materials and methods: The study involved 102 patients treated at the V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology, the Kashchenko Hospital, and the City Psychiatric Hospital No. 6. The study used the Adverse Childhood Experience (ACE) questionnaire, the Internalized Stigma of Mental Illness (ISMI) questionnaire, and the Treatment Motivation Assessment Questionnaire (TIMQ). Statistical analysis was performed using the SPSS 26.0 software package. Results: According to the results of multiple regression analysis, patients with higher education determined the improvement of patients' motivation for treatment, increasing the probability of its high intensity by 5.92 times. The presence of each additional type of adverse experience in childhood also 1.4-fold increase the odds of intensive motivation of patients. Among individual variants of negative experience, emotional abuse was associated with a tenfold decrease in odds, while observing violence against a mother or stepmother in childhood was conversely associated with a fifteenfold increase in the odds of forming an intense motivation for treatment. Conclusion: Integrative role of adverse childhood experiences is important, but, unlike the internal stigma of mental disorder, it can be equally associated with both less adaptive motivational patterns during treatment. to both more and less adaptive motivational patterns in patients in the process of their treatment.

From turbulence to recovery: tracking the cognition-sentiment-behaviour transformation among Chinese cruise industry stakeholders

ABSTRACT Amid unprecedented challenges brought by the pandemic, understanding the evolving dynamics among key stakeholders in the cruise industry becomes vital for fostering recovery and sustainable growth. This study employs a multi-faceted analytical approach, utilising Python for data collection across multiple channels and integrating Social Network Analysis, LDA Thematic Modelling, Sentiment Analysis, and the Moving Average Method. Our findings illuminate the complex interplay between cognitive adjustments, sentiment shifts, and behavioural changes that characterise stakeholders’ responses throughout the pandemic. We unveil distinctive patterns of sentiment and behavioural adaptation among different stakeholder groups, underpinned by their specific interests and objectives. The research highlights the critical roles of government and cruise companies in spearheading the industry's revival, emphasising their influential capacity to shape positive sentiment and proactive engagement in the sector's growth. Furthermore, the study reveals the vulnerability of prospective tourists to external adverse events, impacting their perceptions and potential engagement with cruise tourism. By delving into these multifaceted dynamics, this study contributes to a deeper understanding of stakeholder-oriented strategies essential for the orderly recovery and future resilience of China's cruise industry in a post-pandemic world.

Cardiac magnetic resonance patterns of left ventricular remodeling in patients with severe aortic stenosis referred to surgical aortic valve replacement

Left ventricular (LV) hypertrophy is a common finding in patients with severe aortic stenosis (AS). Cardiac magnetic resonance (CMR) is the gold-standard technique to evaluate LV remodeling. Our aim was to assess the prevalence and describe the patterns of LV adaptation in AS patients before and after surgical aortic valve replacement (AVR). Prospective study of 130 consecutive patients (71y [IQR 68–77y], 48% men) with severe AS, referred for surgical AVR. Patterns of LV remodeling were assessed by CMR. Besides normal LV ventricular structure, four other patterns were considered: concentric remodeling, concentric hypertrophy, eccentric hypertrophy, and adverse remodeling. At baseline CMR study: mean LV indexed mass: 81.8 ± 26.7 g/m2; mean end-diastolic LV indexed volume: 85.7 ± 23.1 mL/m2 and median geometric remodeling ratio: 0.96 g/mL [IQR 0.82–1.08 g/mL]. LV hypertrophy occurred in 49% of subjects (concentric 44%; eccentric 5%). Both normal LV structure and concentric remodeling had a prevalence of 25% among the cohort; one patient had an adverse remodeling pattern. Asymmetric LV wall thickening was present in 55% of the patients, with predominant septal involvement. AVR was performed in 119 patients. At 3–6 months after AVR, LV remodeling changed to: normal ventricular geometry in 60%, concentric remodeling in 27%, concentric hypertrophy in 10%, eccentric hypertrophy in 3% and adverse remodeling (one patient). Indexes of AS severity, LV systolic and diastolic function and NT-proBNP were significantly different among the distinct patterns of remodeling. Several distinct patterns of LV remodelling beyond concentric hypertrophy occur in patients with classical severe AS. Asymmetric hypertrophy is a common finding and LV response after AVR is diverse.

Development and Validation of the Eating Beliefs and Behaviors Questionnaire for Gastrointestinal Disorders (EBBQ-GID)

IntroductionPrevious studies underscore the lack of suitable assessment tools for disordered eating among individuals suffering from a gastrointestinal disorder. ObjectiveThe present study described the development and validation of the Eating Beliefs and Behaviors Questionnaire for individuals with Gastrointestinal Disorders (EBBQ-GID). MethodThe questionnaire was developed and administered online to 518 French-Canadian adults with a gastrointestinal disorder. The sample was randomly split to perform an exploratory and a confirmatory factor analysis. ResultsResults supported a 3-factor structure: Positive commitment (four items), Restrictive attitudes (three items), and Distrust in the diet (three items). Correlational analyses performed with measures of restrictive eating and binge eating supported the convergent validity of the questionnaire, especially for the Restrictive attitudes and the Distrust factors. ConclusionIn addition to filling a gap in the literature, this 10-item questionnaire is a useful short tool that can assess and distinguish disordered eating from adaptive eating patterns in a context of gastrointestinal disorders.

Development Of Agriculture Spraying Drone

The primary objective of the AGRICULTURE SPRAYING DRONE is to enhance the efficiency of agricultural spraying through the utilisation of unmanned aerial vehicles (UAVs) and also to minimise waste and adverse effects on the environment while optimising conventional agricultural spraying techniques. With the help of a 22000 mAh battery, the system combines cutting-edge parts, including the Hobby wing X6plus motors, K++ V2 flight controller, Sky Droid T12 receiver and transmitter, Hobby wing pump, flowmeter, Can hub, obstacle avoidance system, and PMU. The drone, with a total weight of 29 kg and a maximum payload capacity of 12 kg, guarantees accurate and productive spraying operations across large agricultural areas. Key characteristics include adaptive spraying patterns tailored to specific field conditions, targeted pesticide application, and real-time crop health monitoring. An additional mobile application enhances the system by offering farmers the ability to remotely operate, schedule spraying, and examine field data. In order to show how the suggested drone system may be implemented practically and its effectiveness assessed in actual agricultural settings, the article describes the system architecture and provides a use-case scenario. By enabling more effective and sustainable agricultural methods, this research advances precision agriculture technologies. Key Words: Agriculture Spraying Drone, Precision Spraying, Sustainability.

Exploring Intraspecific Trait Variation in a Xerophytic Moss Species Indusiella thianschanica (Ptychomitriaceae) across Environmental Gradients on the Tibetan Plateau.

Investigating intraspecific trait variability is crucial for understanding plant adaptation to various environments, yet research on lithophytic mosses in extreme environments remains scarce. This study focuses on Indusiella thianschanica Broth. Hal., a unique lithophytic moss species in the extreme environments of the Tibetan Plateau, aiming to uncover its adaptation and response mechanisms to environmental changes. Specimens were collected from 26 sites across elevations ranging from 3642 m to 5528 m, and the relationships between 23 morphological traits and 15 environmental factors were analyzed. Results indicated that coefficients of variation (CV) ranged from 5.91% to 36.11%, with gametophyte height (GH) and basal cell transverse wall thickness (STW) showing the highest and lowest variations, respectively. Temperature, elevation, and potential evapo-transpiration (PET) emerged as primary environmental drivers. Leaf traits, especially those of the leaf sheath, exhibited a more pronounced response to the environment. The traits exhibited apparent covariation in response to environmental challenges and indicated flexible adaptive strategies. This study revealed the adaptation and response patterns of different morphological traits of I. thianschanica to environmental changes on the Tibetan Plateau, emphasizing the significant effect of temperature on trait variation. Our findings deepen the understanding of the ecology and adaptive strategies of lithophytic mosses.

Patterns of genetic variation and local adaptation of a native herbivore to a lethal invasive plant.

Understanding the evolutionary processes that influence fitness is critical to predicting species' responses to selection. Interactions among evolutionary processes including gene flow, drift and the strength of selection can lead to either local adaptation or maladaptation, especially in heterogenous landscapes. Populations experiencing novel environments or resources are ideal for understanding the mechanisms underlying adaptation or maladaptation, specifically in locally co-evolved interactions. We used the interaction between a native herbivore that oviposits on a patchily distributed introduced plant that in turn causes significant mortality to the larvae to test for signatures of local adaptation in areas where the two co-occurred. We used whole-genome sequencing to explore population structure, patterns of gene flow and signatures of local adaptation. We found signatures of local adaptation in response to the introduced plant in the absence of strong population structure with no genetic differentiation and low genetic variation. Additionally, we found localized allele frequency differences within a single population between habitats with and without the lethal plant, highlighting the effects of strong selection. Finally, we identified that selection was acting on larval ability to feed on the plant rather than on females' ability to avoid oviposition, thus uncovering the specific ontogenetic target of selection. Our work highlights the potential for adaptation to occur in a fine-grained landscape in the presence of gene flow and low genetic variation.

Mosaic of local adaptation between white clover and rhizobia along an urbanization gradient

Abstract Urbanization frequently alters the biotic and abiotic environmental context. Variation in both the biotic and abiotic environment can result in selection mosaics that lead to locally adapted phenotypes. Ecological changes to urban environments can result in evolutionary responses across a diverse array of plants and animals, but the effects of urbanization on local adaptation and coevolution between species remain largely unstudied. Using a common garden experiment of 30 populations and 1080 plants, we tested for local adaptation in the mutualism between white clover (Trifolium repens) and rhizobia (Rhizobium leguminosarum symbiovar trifolii) along an urbanization gradient. We asked: (Q1) are white clover and rhizobia locally adapted? (Q2) Does nitrogen (N) addition mediate the strength of local adaptation? (Q3) Is the strength of local adaptation in host plants related to the strength of local adaptation in rhizobia, as expected if white clover and rhizobia are coadapting? And (Q4) how does the degree of local adaptation vary with urbanization? We found evidence for local adaptation for both white clover and rhizobia, with stronger signatures of local adaptation for rhizobia than white clover (Q1). While N addition positively affected plant biomass and negatively affected nodule density, N addition did not consistently mediate patterns of local adaptation (Q2). The strength of local adaptation was positively related between white clover and rhizobia under N addition, suggesting that soil N mediates coadaptation between white clover and rhizobia (Q3). We did not find a consistent relationship between measures of urbanization and local adaptation (Q4). Additionally, fitness responses for white clover and rhizobia were unrelated to Rhizobium abundance and local adaptation was unrelated to the broader bacterial microbiome in the soil inoculants or root endosphere. Synthesis. Our results show a spatial mosaic in local adaptation, with stronger local adaptation for rhizobia than white clover. While urbanization does influence the ecology of plant–microbe interactions, our study suggests urbanization does not disrupt local adaptation and coevolution among mutualists.

A Mosquito Parasite Is Locally Adapted to Its Host but Not Temperature.

AbstractClimate change will alter interactions between parasites and their hosts. Warming may affect patterns of local adaptation, shifting the environment to favor the parasite or host and thus changing the prevalence of disease. We assessed local adaptation to hosts and temperature in the facultative ciliate parasite Lambornella clarki, which infects the western tree hole mosquito Aedes sierrensis. We conducted laboratory infection experiments with mosquito larvae and parasites collected from across a climate gradient, pairing sympatric or allopatric populations across three temperatures that were either matched or mismatched to the source environment. Lambornella clarki parasites were locally adapted to their hosts, with 2.6 times higher infection rates on sympatric populations compared with allopatric populations, but they were not locally adapted to temperature. Infection peaked at the intermediate temperature of 12.5°C, notably lower than the optimum temperature for free-living L. clarki growth, suggesting that the host's immune response can play a significant role in mediating the outcome of infection. Our results highlight the importance of host selective pressure on parasites, despite the impact of temperature on infection success.

Comparative genomics provides insights into molecular adaptation to hypermetamorphosis and cantharidin metabolism in blister beetles (Coleoptera: Meloidae).

Blister beetles (Coleoptera: Meloidae) are currently subdivided into three subfamilies: Eleticinae (a basal group), Nemognathinae, and Meloinae. These are all characterized by the endogenous production of the defensive terpene cantharidin (CA), whereas the two most derived subfamilies show a hypermetamorphic larval development. Here, we provide novel draft genome assemblies of five species sampled across the three blister beetle subfamilies (Iselma pallidipennis, Stenodera caucasica, Zonitis immaculata, Lydus trimaculatus, and Mylabris variabilis) and performed a comparative analysis with other available Meloidae genomes and the closely-related canthariphilous species (Pyrochroa serraticornis) to disclose adaptations at a molecular level. Our results highlighted the expansion and selection of genes potentially responsible for CA production and metabolism, as well as its mobilization and vesicular compartmentalization. Furthermore, we observed adaptive selection patterns and gain of genes devoted to epigenetic regulation, development, and morphogenesis, possibly related to hypermetamorphosis. We hypothesize that most genetic adaptations occurred to support both CA biosynthesis and hypermetamorphosis, two crucial aspects of Meloidae biology that likely contributed to their evolutionary success.

A Process Mining Method for Inter-organizational Business Process Integration

Business process integration (BPI) allows organizations to connect and automate their business processes in order to deliver the right economic resources at the right time, place, and price. BPI requires the integration of business processes and their supporting systems across multiple autonomous organizations. However, such integration is complex and can face coordination complexities that occur during the resource exchanges between the partners’ processes. This article proposes a new method called Process Mining for Business Process Integration (PM4BPI) that helps process designers to perform BPI by creating new process models that cross the boundaries of multiple organizations from a collection of process event logs. PM4BPI uses federated process mining techniques to detect incompatibilities before the integration of the partners’ processes. Then, it applies process adaptation patterns to solve detected incompatibilities. Finally, organizations’ processes are merged to build a collaborative process model that crosses the organizations’ boundaries. Adapt WF_Net , an extension of a Petri net, is used to design inter-organizational business processes and adaptation patterns. An integrated care pathway is used as a case study to assess the applicability and effectiveness of the proposed method.

Genomic responses to climate: Understanding local adaptation in the Andean tree species Nothofagus pumilio and implications for a changing world

Societal Impact StatementForest trees tend to be strongly genetically adapted to their local environments, but climate change will probably subject trees to novel combinations of precipitation, temperature, and photoperiod. Local adaptation was investigated in the ecologically and economically important Patagonian tree species Nothofagus pumilio by characterizing its genetic diversity in relation to the varied environmental conditions across its range. These insights are useful for conservation and management decisions, for example by identifying suitable populations to establish seed source plantations for restoration and characterizing relationships with environmental drivers of selection to better understand how this species will respond to climate change.SummaryNothofagus pumilio is a foundation tree species that inhabits a 2000‐km‐long range in the southern Andes, a region with two perpendicular environmental gradients: temperature and photoperiod (North–South), and precipitation (West–East). We investigated local adaptation patterns by searching for relationships between environmental clines and signatures of adaptation in candidate genes related to stress response, growth, and phenology. Using a paired site sampling design within a landscape genome analysis, we analyzed 493 adult N. pumilio trees in 20 sampling sites across the species' latitudinal range. We screened 47,336 single nucleotide polymorphism (SNP) loci in 1632 contigs (i.e., coding regions along the genome). Population structure and genetic diversity analyses preceded four genome scan analyses using genetic and environmental data. Population structure and genetic diversity are mainly oriented along the latitude axis. Genome scans identified 445 outlier SNPs, which are loci showing signatures of selection. Temperature and photoperiod variables were associated with notably more outliers than precipitation. However, the most frequent biological functions among genes were water deprivation response and cold response, suggesting that stress response is comprised of complex and polygenic traits that are affected by many environmental variables. Our findings suggest that N. pumilio shows signatures of local adaptation to extant climate conditions, including temperature, photoperiod, and precipitation. However, climate change is likely to alter existing relationships among environmental conditions to which this species is currently adapted. These changes may have unpredictable consequences for the species' future survival, adaptation potential, and the people who depend upon these forests.

Program Adaptations of Special Education Teachers

Introduction: Arrangements are made in the curriculum elements due to the individual differences of students with special needs. It is necessary to determine how programs implemented in special education classrooms are adapted by teachers for program functionality. The purpose of this study is to determine special education teachers' patterns of how and in what ways they adapt their curriculum during implementation. Method: This study, which was conducted to determine the curriculum adaptation by special education teachers and the factors that cause this adaptation, used a case study design from the qualitative research approach. The sample of this study consisted of four special education teachers: two working at the secondary level of a public school and two working at a special education and rehabilitation center. In this study, data diversification was used by employing more than one data collection instrument. These included observations, interviews, and special education lesson plans. As the data needed to be examined and analyzed in detail, content analysis was used. Findings: The observations, interviews, and document reviews revealed that teachers working in special education classrooms in public and private institutions make program adaptations such as omitting, expanding, and replacing/revising. Teacher qualifications, student characteristics, school climate, program characteristics, and family expectations played a substantial role in shaping the emergence of adaptation patterns. Discussion: Based on the results, it was found that special education teachers did not implement the written (official) program exactly in their schools and classes. It was found that the student's area and level of disability was the most important reason for the difference. The differences in the areas and degrees of disability of students with special needs in public schools and private institutions shape adaptations for expansion and revising.

Adaptive thresholding pattern for fingerprint forgery detection

Adaptive thresholding pattern for fingerprint forgery detection

The soil microbiome affects patterns of local adaptation in an alpine plant under moisture stress.

The soil microbiome plays a role in plant trait expression and fitness, and plants may be locally adapted or maladapted to their soil microbiota. However, few studies of local adaptation in plants have incorporated a microbial treatment separate from manipulations of the abiotic environment, so our understanding of microbes in plant adaptation is limited. Here we tested microbial effects on local adaptation in four paired populations of an abundant alpine plant from two community types, dry and moist meadow. In a 5-month greenhouse experiment, we manipulated source population, soil moisture, and soil microbiome and measured plant survival and biomass to assess treatment effects. Dry meadow populations had higher biomass than moist meadow populations at low moisture, demonstrating evidence of local adaptation to soil moisture in the absence of microbes. In the presence of microbes, dry meadow populations had greater survival than moist meadow populations when grown with dry meadow microbes regardless of moisture. Moist meadow populations showed no signs of adaptation or maladaptation. Our research highlights the importance of microbial mutualists in local adaptation, particularly in dry environments with higher abiotic stress. Plant populations from environments with greater abiotic stress exhibit different patterns of adaptation when grown with soil microbes versus without, while plant populations from less abiotically stressful environments do not. Improving our understanding of the role microbes play in plant adaptation will require further studies incorporating microbial manipulations.

Compositional features analysis by machine learning in genome represents linear adaptation of monkeypox virus.

Introduction: The global headlines have been dominated by the sudden and widespread outbreak of monkeypox, a rare and endemic zoonotic disease caused by the monkeypox virus (MPXV). Genomic composition based machine learning (ML) methods have recently shown promise in identifying host adaptability and evolutionary patterns of virus. Our study aimed to analyze the genomic characteristics and evolutionary patterns of MPXV using ML methods. Methods: The open reading frame (ORF) regions of full-length MPXV genomes were filtered and 165 ORFs were selected as clusters with the highest homology. Unsupervised machine learning methods of t-distributed stochastic neighbor embedding (t-SNE), Principal Component Analysis (PCA), and hierarchical clustering were performed to observe the DCR characteristics of the selected ORF clusters. Results: The results showed that MPXV sequences post-2022 showed an obvious linear adaptive evolution, indicating that it has become more adapted to the human host after accumulating mutations. For further accurate analysis, the ORF regions with larger variations were filtered out based on the ranking of homology difference to narrow down the key ORF clusters, which drew the same conclusion of linear adaptability. Then key differential protein structures were predicted by AlphaFold 2, which meant that difference in main domains might be one of the internal reasons for linear adaptive evolution. Discussion: Understanding the process of linear adaptation is critical in the constant evolutionary struggle between viruses and their hosts, playing a significant role in crafting effective measures to tackle viral diseases. Therefore, the present study provides valuable insights into the evolutionary patterns of the MPXV in 2022 from the perspective of genomic composition characteristics analysis through ML methods.

An Adaptive Parallel Pattern Based Design for Molecular Dynamic Simulation

In Parallel programming, a programmer needs to understand hardware environment, programming paradigm and primitives available in the programming language. Most of the time, parallel programmes are written for a specific architecture and cannot typically adapt to other architectures Particularly, programs written for shared memory architectures are unsuitable for distributed or hybrid architectures. This paper proposes Adaptive Design Pattern for Parallel Programming to improve adaptability, flexibility with achieving performance on different architectures. Molecular Dynamics (MD) simulation is required to scale to various architectures from simple machine to cluster of workstations. In this study, MD Simulation experimented using both pure benchmark code and code based on adaptive design patterns. Redesigned MD Simulation with Adaptive Design Pattern claims parallel efficiency from 56% to 90% for different number of processing elements used. The solution demonstrates adaptability to different architectures and scalability to use with large number of atoms and long duration simulation.

The Impact of Artificial Intelligence on Cybersecurity

The aim of this research is to examine the structure of the impact of AI technology on improving cybersecurity. Also, this research focuses on using machine learning and big data analysis techniques to enhance the ability to better detect and respond to cyber threats. This research follows a qualitative methodology to meet the core research objectives of assessing the impact of Artificial Intelligence on Cybersecurity by reviewing the previous studies on this field. This research focuses on using machine learning and big data analysis techniques to enhance the ability to better detect and respond to cyber threats. The comprehensive analysis of over 20 studies published between 2015-2024 offers valuable insights into the current state and impact of AI in enhancing cybersecurity policies and practices. The findings of the research revealed that artificial intelligence and machine learning significantly expand capabilities for cyber threat detection, incident alerting, and automated response through adaptive pattern recognition across diverse monitoring sources like network traffic, endpoint behaviors and security information feeds, performed at machine scale. By constantly retraining on evolving attack trends and benign usage shifts, AI holds immense potential enhancing protection. However, sizable gaps observed between touted expectations versus measured impact today highlight obstacles of practical integration like monitoring overheads, skills shortages, result interpretability, human-AI teaming dynamics, and adversarial manipulations that could undermine or reverse security aims. While transformative upside exists long-term, pragmatic roadmaps addressing these formidable challenges using best practices around responsible AI governance appear essential to maximize gains while minimizing unintended consequences of well-intentioned systems interacting with ever stealthier threats amid zones of high operational and ethical ambiguity. The research recommends using machine learning and big data analysis techniques to enhance the ability to better detect and respond to cyber threats.

Categorising and cohabiting: practices as the site of biosocial becoming

In this article we argue that social practices, which consist of sayings and doings that extend across space and time, generate and sustain distinctive patterns of microbial interaction. In taking this approach, we position practice theory within and not outside the realm of contemporary biological processes, including processes that matter for human health. In working towards this conclusion, we show how categories and distinctions (e.g. between communicable and non-communicable disease) are embedded in medical responses and in the lives of potentially harmful bacteria like Helicobacter Pylori. Our next step is to explain how social practices engender patterns of cohabitation, interaction and mutual adaptation between microbes within and beyond the body, processes we illustrate with reference to anti-microbial resistance. The conclusion that human and microbial coexistence is, in various ways, defined by the lives of social practices provides an important bridge between the social and natural sciences and a starting point from which to approach fundamental questions about the dynamics of biosocial becoming, and the part that public policies play in these processes.

Smart Gait: A Gait Optimization Framework for Hexapod Robots

The current gait planning for legged robots is mostly based on human presets, which cannot match the flexible characteristics of natural mammals. This paper proposes a gait optimization framework for hexapod robots called Smart Gait. Smart Gait contains three modules: swing leg trajectory optimization, gait period & duty optimization, and gait sequence optimization. The full dynamics of a single leg, and the centroid dynamics of the overall robot are considered in the respective modules. The Smart Gait not only helps the robot to decrease the energy consumption when in locomotion, mostly, it enables the hexapod robot to determine its gait pattern transitions based on its current state, instead of repeating the formalistic clock-set step cycles. Our Smart Gait framework allows the hexapod robot to behave nimbly as a living animal when in 3D movements for the first time. The Smart Gait framework combines offline and online optimizations without any fussy data-driven training procedures, and it can run efficiently on board in real-time after deployment. Various experiments are carried out on the hexapod robot LittleStrong. The results show that the energy consumption is reduced by 15.9% when in locomotion. Adaptive gait patterns can be generated spontaneously both in regular and challenge environments, and when facing external interferences.