Complete Life Cycle Research Articles

Analysis of acoustic field characteristics of mesoscale eddies throughout their complete life cycle

Mesoscale eddies exert a profound influence on oceanic temperature and salinity structures, thereby altering the ecological environment and acoustic propagation characteristics. Prior research on acoustic propagation beneath mesoscale eddy effects has predominantly concentrated on fragmented, snapshot-style analyses. In contrast, this study employs a holistic approach by integrating multi-source data to elucidate oceanic temperature and salinity structures, ultimately impacting their ecological environment and acoustic propagation. While the existing paper, this study adopts a more comprehensive and successional methodology. Through the amalgamation of multi-source data, this research introduces an innovative mesoscale eddy tracking algorithm and an enhanced Gaussian eddy model. Utilizing the BELLHOP ray theory model, this investigation scrutinizes the acoustic field characteristics of a cyclonic eddy and a typical anticyclonic eddy (CE-AE) pair exhibiting complete life cycles in the Northwest Pacific. The results reveal that the complete life cycles of mesoscale eddies substantially impact the acoustic field environment. As a CE intensifies, the convergence zone (CZ) distance diminishes, the CZ width expands, and the direct wave (DW) distance shortens. Conversely, an intensifying AE increases the CZ distance, contracts the CZ width, and prolongs the DW distance. This paper presents a quantitative analysis to delineate the critical factors influencing eddy life cycles, indicating that both eddy intensity and deformation parameters significantly affect acoustic propagation characteristics, with eddy intensity exerting a more substantial influence. This research substantially contributes to the application of sea surface altimetry data for underwater acoustic studies and provides preliminary insights into the impacts of eddy parameters on underwater acoustic propagation within typical mesoscale eddy environments. Moreover, this research offers a foundation for future investigations into the intricate relationships between eddy dynamics and acoustic propagation in oceanic systems.

Immature stages of the Zebra Hairstreak butterfly, Arawacus separata (Lepidoptera: Lycaenidae): a model organism for studies on mimicry and mutualism

Hairstreak butterflies are model organisms in evolutionary biology due to the variety of predator-avoidance strategies they possess, including false head mimicry and symbiosis with ants, both of which Zebra Hairstreaks employ. Natural history information is basic for the generation of hypothesis-driven research in ecology and evolution, especially for holometabolous organisms. Here, the complete life cycle of the Zebra Hairstreak Arawacus separata is described for the first time. The natural history records, including citizen science, for other Zebra Hairstreaks species in Eumaeini were also reviewed. Host plant records for A. separata indicate that its caterpillars are oligophagous on Solanaceae, being locally specialized on the shrub Cestrum strigilatum (Solanaceae). Development from egg to adult was found to last ~30 days. Caterpillars underwent four instars with cryptic coloration and texture. The larval tegument is covered by short dendritic setae and pore cupola organs (PCOs), and, from the second instar on, shows a dorsal nectary organ (DNO). Caterpillars live on plants surrounded by ants throughout their entire ontogeny. Facultative symbiosis was observed in all instars with seven ant species in four genera. Myrmecophily is potentiated by honeydew-producing hemipterans and attractive sap of leaf lesions. Territory occupancy of males and non-aerial contests suggest a neglected role of sexual selection in the evolution of the false-head traits. Due to the typical false-head wing coloration pattern and myrmecophily, A. separata is proposed as a model organism to study mimicry and mutualism.

Examining the Carbon Footprint of Conferences with an Emphasis on Energy Consumption and Catering

This research study presents a comparison of an in-person and an online conference in terms of environmental impact and energy efficiency. The main goal of our research was to prepare a complete life cycle assessment of a two-day (15-h), 200-participant in-person and online conference based on different impact assessment methods. Life cycle assessments focus on the numerical determination of the decarbonization of conference consumption (lunch, dinner, food and beverage consumption during breaks), conference organization (discussions, correspondence, abstract booklet, registration package), travel, and infrastructure. The meals were examined by connecting the stages of preparation, cooking, consumption and end-of-life cycle as a cradle-to-grave analysis. We paid particular attention to the calculation of energy consumption. After carbon footprint comparisons, the areas with the highest impacts with pie diagrams were identified. Lastly, a SWOT chart and an SAP-LAP analysis diagram summarize the achievable objectives and challenges. In conclusion, there is no outstanding difference between the impact assessment methods for the carbon footprint investigation. Travel contributes 57% of the overall carbon footprint at in-person conferences, while the environmental impact of meals holds the second largest share, at 8.41 kg CO2 equivalent/person/hour. Excluding meals and travel, the calculated carbon footprint is 0.362 kg CO2 equivalent/person/hour (only considering the effect of preparation, organization, administration and registration package). Our initial hypothesis was that an online conference reduces decarbonization, which the results confirm.

Establishment of the complete life cycle of Calicophoron daubneyi under experimental conditions

Establishment of the complete life cycle of Calicophoron daubneyi under experimental conditions

ESR Essentials: how to get to valuable radiology AI: the role of early health technology assessment-practice recommendations by the European Society of Medical Imaging Informatics.

AI tools in radiology are revolutionising the diagnosis, evaluation, and management of patients. However, there is a major gap between the large number of developed AI tools and those translated into daily clinical practice, which can be primarily attributed to limited usefulness and trust in current AI tools. Instead of technically driven development, little effort has been put into value-based development to ensure AI tools will have a clinically relevant impact on patient care. An iterative comprehensive value evaluation process covering the complete AI tool lifecycle should be part of radiology AI development. For value assessment of health technologies, health technology assessment (HTA) is an extensively used and comprehensive method. While most aspects of value covered by HTA apply to radiology AI, additional aspects, including transparency, explainability, and robustness, are unique to radiology AI and crucial in its value assessment. Additionally, value assessment should already be included early in the design stage to determine the potential impact and subsequent requirements of the AI tool. Such early assessment should be systematic, transparent, and practical to ensure all stakeholders and value aspects are considered. Hence, early value-based development by incorporating early HTA will lead to more valuable AI tools and thus facilitate translation to clinical practice. CLINICAL RELEVANCE STATEMENT: This paper advocates for the use of early value-based assessments. These assessments promote a comprehensive evaluation on how an AI tool in development can provide value in clinical practice and thus help improve the quality of these tools and the clinical process they support. KEY POINTS: Value in radiology AI should be perceived as a comprehensive term including health technology assessment domains and AI-specific domains. Incorporation of an early health technology assessment for radiology AI during development will lead to more valuable radiology AI tools. Comprehensive and transparent value assessment of radiology AI tools is essential for their widespread adoption.

The Impact of Cumulus Clouds and CCN Regeneration on Aerosol Vertical Distribution and Size

Abstract This study employs a high-resolution (10m) System for Atmospheric Modeling (SAM) coupled with the Spectral Bin Microphysical (SBM) scheme to thoroughly investigate the processes governing the evolution of aerosol properties within and outside a shallow cumulus cloud. The model encompasses the complete life cycle of cloud droplets, starting from their formation through their evolution until their complete evaporation or sedimentation to the ground. Additionally, the model tracks the aerosols’ evolution both within droplets and in the air. Aerosols are transported within the droplets, grow by droplet coalescence, and are released into the atmosphere after droplet evaporation (regeneration process). The aerosol concentration increases by droplet evaporation and decreases along with falling drops. So, the effects of clouds on the surrounding aerosols depend on the microphysical and dynamic processes, which in turn depend on the amount of background aerosols; here, we compare clean and polluted conditions. It is shown that the regeneration process is highly important and that shallow trade cumulus clouds significantly impact the vertical profile of aerosol concentration in the lower troposphere, as well as their size distribution, and can serve as a source of large cloud condensation nuclei. Furthermore, it is shown that both precipitating and non-precipitating boundary layer clouds contribute to a substantial increase in aerosol concentration within the inversion layer due to intense evaporation.

PopFL: A scalable Federated Learning model in serverless edge computing integrating with dynamic pop-up network

With the rapid increase in the number of Internet-of-Things (IoT) devices, the massive volume of data creates significant challenges for traditional cloud-based solutions. These solutions often lead to high latency, increased operational costs, and limited scalability, making them unsuitable for real-time applications and resource-constrained environments. As a result, edge, and fog computing have emerged as viable alternatives, reducing latency and costs by processing data closer to its source. However, managing the flow of such vast and distributed data streams requires well-structured data pipelines to control the complete lifecycle—from data acquisition at the source to processing at the edge and fog layers, and finally storage and analytics in the cloud. To dynamically handle data analytics at varying distances from the source, often on heterogeneous hardware devices with collaborative learning techniques such as Federated Learning (FL). FL enables decentralized model training by leveraging the local data on Edge Devices (EDs), thereby preserving data privacy and reducing communication overhead with the cloud. However, FL faces critical challenges, including data heterogeneity, where the non-independent and identically distributed (non-IID) nature of data degrades model performance, and resource limitations on EDs, which lead to inefficiencies in training and biases in the aggregated models.To address these issues, we propose a novel FL solution, called Pop-Up Federated Learning (PopFL) in edge networks. This solution introduces hierarchical aggregation to reduce network congestion by distributing the aggregation tasks across multiple Fog Servers (FSs), rather than relying solely on centralized cloud aggregation. To further enhance participation and resource utilization at the edge, we incorporate the Stackelberg game model, which incentivizes EDs based on their contribution and resource availability. Additionally, PopFL employs a pop-up ad-hoc network for scalable and efficient communication between EDs and FSs, ensuring robust data transmission in dynamic network conditions. Extensive experiments conducted on three diverse datasets highlight the superior performance of PopFL compared to state-of-the-art FL techniques. The results show significant improvements in model accuracy, robustness, and fairness across various scenarios, effectively addressing the challenges of data heterogeneity and resource limitations. Through these innovations, PopFL paves the way for more reliable and efficient distributed learning systems, unlocking the full potential of FL in real-world applications where low latency and scalable solutions are critical.

A business process management lifecycle framework for continuous improvement towards operational excellence: lessons learned from a longitudinal study in a Brazilian organisation

Purpose The purpose of this study is to offer a business process management (BPM) framework with information and insights on designing, implementing, using and assessing business processes for continuous improvement towards operational excellence. Design/methodology/approach An action research is carried out over two and a half years on the BPM evolution of a Brazilian entertainment organisation. Findings Research provides a novel procedural framework towards improving the understanding of how a complete lifecycle approach for BPM can be implemented for continuous improvement, embracing the critical success factors for each lifecycle phase to achieve operational excellence. Information technology and project management are critical success factors resulting in project barriers. Strategic alignment, top management support, collaborative environment, methods and methodology, and focus on users and culture are acknowledged as main enablers. Findings reinforce the importance of an organisation analysis phase to begin the BPM development and highlight the assessment and improvement phase to respond to organisational environment dynamism. Practical implications Practitioners can benefit from the lessons learnt and the proposed framework, which serves as a rigorous methodology to achieve operational excellence in their real-world settings. Originality/value This paper goes beyond the well-known design and analysis phases of BPM development, generally studied with an individual focus, offering a complete lifecycle approach for continuous improvement, analysing each phase, from the drawing board to its use and evaluation. It counts on an original longitudinal study rather than a single-time assessment study.

Satellite telemetry reveals complex mixed movement strategies in ibis and spoonbills of Australia: implications for water and wetland management.

Waterbird population and species diversity maintenance are important outcomes of wetland conservation management, but knowledge gaps regarding waterbird movements affect our ability to understand and predict waterbird responses to management at appropriate scales. Movement tracking using satellite telemetry is now allowing us to fill these knowledge gaps for highly mobile waterbirds at continental scales, including in remote areas for which data have been historically difficult to acquire. We used GPS satellite telemetry to track the movements of 122 individuals of three species of ibis and spoonbills (Threskiornithidae) in Australia from 2016 to 2023. We analysed movement distances, residency periods and areas, and foraging-site fidelity. From this we derived implications for water and wetland management for waterbird conservation. This is the first multi-year movement tracking data for ibis and spoonbills in Australia, with some individuals tracked continuously for more than five years including from natal site to first breeding attempt. Tracking revealed both inter- and intra-specific variability in movement strategies, including residency, nomadism, and migration, with individuals switching between these behaviours. During periods of residency, areas used and distances travelled to forage were highly variable and differed significantly between species. Sixty-five percent of identified residency areas were not associated with wetlands formally listed nationally or internationally as important. Tracking the movements of waterbirds provides context for coordinated allocation of management resources, such as provision of environmental water at appropriate places and times for maximum conservation benefit. This study highlights the geographic scales over which these birds function and shows how variable waterbird movements are. This illustrates the need to consider the full life cycle of these birds when making management decisions and evaluating management impacts. Increased knowledge of the spatio-temporal interactions of waterbirds with their resource needs over complete life cycles will continue to be essential for informing management aimed at increasing waterbird numbers and maintaining long-term diversity.

Three-dimensional liver organoids as a novel platform for studying hepatitis B virus infection

Hepatitis B virus (HBV) infection is a major global health problem that contributes to chronic liver diseases, such as cirrhosis and hepatocellular carcinoma. Despite advances in antiviral therapy and the availability of preventive vaccines, current treatments often do not completely eradicate the virus, particularly in chronic HBV carriers, and the incidence of liver cancer due to chronic HBV infection remains high. A major obstacle to HBV research is the lack of infection models that can accurately recapitulate the complex interactions between HBV and the host. Existing models, such as hepatoma cell lines and animal models, are limited by species-specific barriers and the lack of support for the complete viral life cycle. These limitations pose significant challenges to the study of HBV pathogenesis and the development of therapies aimed at complete eradication of HBV. In recent years, 3-dimensional (3D) liver organoids have emerged as promising in vitro model systems to study HBV infection and HBV-mediated liver disease. These organoids serve as a suitable physiologically relevant platform for investigating HBV pathogenesis, including the ability of HBV to promote liver tumorigenesis. Furthermore, liver organoids can be genetically modified, patient-derived, expanded, and biobanked, providing a powerful tool for studying HBV pathogenesis and personalized medicine, drug discovery, and screening. In this review, we explore the utilization of 3D liver organoids as a research model for studying HBV infection and HBV-associated liver cancer, highlighting their advantages over conventional models.

Fast estimation method for lithium battery state of health based on incremental capacity curve peak characteristics

State of Health (SOH) estimation for lithium-ion batteries is a complex task, often plagued by issues such as slow estimation speed and high practical application difficulty in existing methods. In this paper, capacity is established as the criterion for defining State of Health. We conducted an analysis of Incremental Capacity (IC) curves, examining the characteristic features of the incremental capacity curves throughout the entire lifecycle of lithium-ion batteries at different temperatures and charge-discharge rates. The investigation revealed that the peaks in the incremental capacity curves correspond to nearly constant State of Charge (SOC) values. Building upon this discovery, a rapid SOH estimation method based on IC curves is proposed. The method was validated using data from the complete lifecycle of 18,650 cells, yielding a maximum SOH estimation error of 3%. Furthermore, the proposed method was applied to 240 cells in an energy storage battery pack at a specific station, resulting in a maximum SOH estimation error of 3.9%. This demonstrates the feasibility of the method under practical conditions, highlighting its high precision in SOH estimation. The proposed approach holds significant promise for real-time and rapid SOH estimation and detection, offering valuable insights for battery health monitoring.

Adding Mandarin Peel Waste to a Biodegradable Polymeric Matrix: Reinforcement or Degradation Effect?

In the current context, the use of fillers derived from fruit and vegetable waste is a crucial approach to mitigate waste and promote sustainable resource use, thus contributing to product life cycle completion and the achievement of sustainability goals. This study focuses on incorporating an endemic waste hitherto considered irrelevant within a biodegradable matrix. The resulting biocomposites were carefully characterized mechanically, rheologically, and morphologically to identify the connections between processability, structure, and properties. The results show that the presence of the filler results in an increase in the stiffness of the material (up to 27% in elastic modulus) accompanied by a decrease in tensile strength (approximately 50%) and elongation at break, which is on average about 7% at the highest filler content. This behavior was attributed to poor interfacial adhesion and the influence of a degradation process caused by the presence of citric acid and/or impurities in the filler.

Genome assembly at chromosome scale with telomere ends for Pearlspot, Etroplus suratensis

The pearlspot, Etroplus suratensis is a climate resilient cichlid fish that exhibits unusual adaptation to salinity. The fish is able to complete full life cycle in diverse salinity habitats ranging from fresh water to marine environments. High-quality primary and phased genome assemblies were generated for pearlspot fish using PacBio HiFi and Arima HiC sequencing technologies, for the first time. The primary assembly is highly contiguous with contig N50 length of 36 Mb. The final assembly is of 1.247 Gb with N50 length of 51.57 Mb and 98% of the genome length anchored to 24 chromosomes. The genome was assessed to be 99.9% complete based on BUSCO evaluation and was predicted to contain 52.96% repeat elements. We have predicted 27,192 protein encoding genes, of which 21,580 were functionally annotated. The genome offers an invaluable resource to understand adaptation of pearlspot fish to diverse salinity habitats.

Comprehensive review of additive manufacturing lifecycle optimization in a cloud environment: from distributed manufacturing to postprocessing

Purpose This paper aims to offer a comprehensive review and categorization of production optimization throughout the additive manufacturing lifecycle in a cloud environment. It aims to provide a structured approach to identifying and addressing issues. Design/methodology/approach This paper systematically reviews 75 technical papers on cloud manufacturing, nesting, scheduling and postprocessing in additive manufacturing. This includes a detailed discussion of the key issues. Findings This paper introduces a production framework for the entire lifecycle of additive manufacturing in a cloud environment. This framework aids in problem identification and decision-making based on the process flow. It provides an integrated view from cloud to postprocessing, examining decision interdependencies and enhancing problem identification and organization. Originality/value To the best of the authors’ knowledge, this paper is the first to review the complete lifecycle of additive manufacturing, emphasizing the often-overlooked aspects of postprocessing and cloud manufacturing. It offers a comprehensive study of lifecycle optimization challenges and suggests ways to streamline the production process.

Data Hub for Life Cycle Assessment of Climate Change Solutions—Hydrogen Case Study

Life cycle assessment, which evaluates the complete life cycle of a product, is considered the standard methodological framework to evaluate the environmental performance of climate change solutions. However, significant challenges exist related to datasets used to quantify these environmental indicators. Although extensive research and commercial data on climate change technologies, pathways, and facilities exist, they are not readily available to practitioners of life cycle assessment in the right format and structure using an open platform. In this study, we propose a new open data hub platform for life cycle assessment, considering a hierarchical data flow starting with raw data collected on climate change technologies at laboratory, pilot, demonstration, or commercial scales to provide the information required for policy and decision-making. This platform makes data accessible at multiple levels for practitioners of life cycle assessment, while making data interoperable across platforms. The proposed data hub platform and workflow are explained through the polymer electrolyte membrane electrolysis hydrogen production as a case study. The climate change environment impact of 1.17 ± 0.03 kg CO2 eq./kg H2 was calculated for the case study. The current data hub platform is limited to evaluating environmental impacts; however, future additions of economic and social aspects are envisaged.

Integrating Process Simulation and Life Cycle Assessment for Enhanced Process Efficiency and Reduced Environmental Impact in Ferromanganese Production

Process simulation was integrated with life cycle assessment to evaluate process efficiency and environmental impact of the production of manganese ferroalloys for various production modes and different ore mineralogies. Utilizing HSC Sim, the model was designed to evaluate the production process with or without a pretreatment step, where results for simulated cases using a four-zone ferromanganese furnace model were exported to openLCA for a complete life cycle assessment. Two main production scenarios were simulated: a closed ferromanganese furnace running on the duplex method and an open furnace running on the discard slag approach. The closed furnace scenario achieved a 17.5% reduction in energy consumption and a 16.2% decrease in direct CO2 emissions with CO-rich off-gas pretreatment. The open furnace scenario showed an 11.2% reduction in energy consumption with thermal solar energy pretreatment but no change in CO2 emissions.

Distinct chikungunya virus polymerase palm subdomains contribute to viral protein accumulation and virion production.

Alphaviruses encode an error-prone RNA-dependent RNA polymerase (RdRp), nsP4, required for genome synthesis, yet how the RdRp functions in the complete alphavirus life cycle is not well-defined. Previous work using chikungunya virus has established the importance of the nsP4 residue cysteine 483 in replication. Given the location of residue C483 in the nsP4 palm domain, we hypothesized that other residues within this domain and surrounding subdomains would also contribute to polymerase function. To test this hypothesis, we designed a panel of nsP4 variants via homology modeling based on the coxsackievirus B3 3D polymerase. We rescued each variant in mammalian and mosquito cells and discovered that the palm domain and ring finger subdomain contribute to host-specific replication. In C6/36 cells, we found that while the nsP4 variants had replicase function similar to that of wild-type CHIKV, many variants presented changes in protein accumulation and virion production even when viral nonstructural and structural proteins were produced. Finally, we found that WT CHIKV and nsP4 variant replication and protein production could be enhanced in mammalian cells at 28°C, yet growing virus under these conditions led to changes in virus infectivity. Taken together, these studies highlight that distinct nsP4 subdomains are required for proper RNA transcription and translation, having major effects on virion production.

Applying Circular Thermoeconomics for Sustainable Metal Recovery in PCB Recycling

The momentum of the Fourth Industrial Revolution is driving increased demand for certain specific metals. These include copper, silver, gold, and platinum group metals (PGMs), which have important applications in renewable energies, green hydrogen, and electronic products. However, the continuous extraction of these metals is leading to a rapid decline in their ore grades and, consequently, increasing the environmental impact of extraction. Hence, obtaining metals from secondary sources, such as waste electrical and electronic equipment (WEEE), has become imperative for both environmental sustainability and ensuring their availability. To evaluate the sustainability of the process, this paper proposes using an exergy approach, which enables appropriate allocation among co-products, as well as the assessment of exergy losses and the use of non-renewable resources. As a case study, this paper analyzes the recycling process of waste printed circuit boards (PCBs) by disaggregating the exergy cost into renewable and non-renewable sources, employing different exergy-based cost allocation methods for the mentioned metals. It further considers the complete life cycle of metals using the Circular Thermoeconomics methodology. The results show that, when considering the entire life cycle, between 47% and 53% of the non-renewable exergy is destroyed during recycling. Therefore, delaying recycling as much as possible would be the most desirable option for minimizing the use of non-renewable resources.

Differences of in vitro immune responses between patent and pre-patent Litomosoides sigmodontis-infected mice are independent of the filarial antigenic stimulus used.

Lymphatic filariasis and onchocerciasis are neglected tropical diseases and cause significant public health problems in endemic countries, especially in sub-Saharan Africa. Since the human parasites are not viable in immune-competent mice, animal models have been developed, among them Litomosoides sigmodontis which permits a complete life cycle in BALB/c mice, including the development of patent infections with circulating microfilariae (Mf, the worm's offspring). To investigate the immunomodulatory properties of helminths in vitro, antigenic extracts can be prepared from different life cycle stages of the L. sigmodontis model, including adult worms, but the methods to prepare these antigens differ between research groups. This study analyzed whether different centrifugation methods during the preparation of an antigenic extract, the gender of used worms, or the different fractions (soluble or pellet) altered filarial-specific CD4+ Tcell responses. These cells were isolated from pre-patent or patent/chronic infected mice, hence those without and those with Mf, respectively. Ex vivo immune responses were compared at these two different time points of the infection as well as the parasitic parameters. Worm burden and cell infiltration were elevated in the thoracic cavity (TC) and draining mediastinal lymph nodes at the pre-patent stage. Within the TC, eosinophils were significantly up-regulated at the earlier time point of infection which was further reflected by the eosinophil-related eotaxin-1 levels. Regarding the production of cytokines by re-stimulated CD4+ T cells in the presence of different antigen preparations, cytokine levels were comparable for all used extracts. Our data show that immune responses differ between pre-patent and patent filarial infection, but not in response to the different antigenic extracts themselves.

A GIS-coupled thermal response model for predicting the population growth potential of the red cotton bug, Dysdercus koenigii (Fabricius) (Hemiptera: Pyrrhocoridae) in India under climate change conditions

Recently, the red cotton bug has become a significant menace to cotton in India. With the potential for increased habitat suitability due to predicted temperature rise of 2.5 °C under future climate change in India, this pest could become even more severe in certain regions. Addressing the knowledge gap on the temperature-driven population growth of this pest is crucial for developing a climate-resilient pest management strategy. In this study, life history data gathered at various constant temperatures (15 °C–35 °C) were used to estimate temperature thresholds and thermal requirements for the red cotton bug development. Stochastic estimation of life table parameters and validation with real-time weather data were performed. The phenology model, integrated into a geographic information system, projected the future pest status based on SSP126 temperature change scenarios for the year 2050. The temperatures between 8.35 and 10.83 °C were estimated as lower developmental thresholds for various immature life stages. The optimum and upper threshold temperatures estimated for different life stages ranged between 22.14 – 28.32 °C and 35.80–39.08 °C, respectively. Thermal requirements of 447.97° days for life cycle completion were estimated. The optimum immature survival rates (>70%) were observed at temperatures between 25 and 30 °C. The temperature-dependent decrease in generation times from 90.45 days (15 °C) to 25.44 days (35 °C) was observed, whereas maximum fecundity was recorded at 32 °C. Simulation at fluctuating temperatures across different cotton growing locations provided reasonably similar results on potential population increase (finite rate of increase: 0.99–1.04 females/female/day and a generation time of 44.25–83.97 days). Risk mapping highlighted moderate to high suitability (ERI >0.4, GI > 6, and AI >4) of various cotton growing areas under current climate, and projected shifts in suitability under future climate change. The study has generated information valuable for implementing effective and timely pest management strategies for red cotton bug. Integrating the field observations with model outputs can enhance a practical understanding of red cotton bug dynamics.