Complex Landscape Research Articles

A Comprehensive Study of Voltage Swell and Sag in Power Distribution Systems: Characteristics, Causes, Effects, and Mitigation Strategies

Voltage variations, such as swells and sags, are prevalent disturbances in power distribution systems, posing significant challenges to system reliability and equipment performance. This research paper provides a comprehensive study of voltage swell and sag phenomena, encompassing their characteristics, causes, effects, mitigation strategies, and case studies. The study explores the magnitude, duration, and frequency of voltage variations, delving into the underlying factors contributing to their occurrence, including switching operations, faults, and load variations. Moreover, the paper examines the detrimental effects of voltage variations on electrical equipment and industrial processes, highlighting the importance of understanding and mitigating these disturbances. Various mitigation techniques, such as voltage regulation, uninterruptible power supplies (UPS), and dynamic voltage restorers (DVRs), are evaluated for their effectiveness in minimizing the impact of voltage variations. Additionally, the paper explores the use of PWM-based Distribution Static Synchronous Compensator (DSTATCOM) as a promising solution for mitigating voltage swell and sag issues, discussing principles, design considerations, control strategies, and performance evaluation. Through case studies, simulation results, and modeling approaches using MATLAB/Simulink, the research paper offers valuable insights into the complex landscape of voltage swell and sag in power distribution systems, equipping researchers and practitioners with knowledge to address these challenges effectively.

A Study on Adverse Effect of Broken Families on Children’s Well-being

Family structure affects the emotional and psychological development of children, and whenever family breakdowns such as separation, divorce, or conflict between two parents occur, children are usually thrown into navigating complex landscapes that lead to worst developmental outcomes. This research seeks to investigate harmful effects brought by broken families to the well-being of children about stability of their emotions, mental health, social relationship, and academic performance. These children are often more predisposed to emotional problems, psychological disorders, and social isolation-the effects of which extend to their academic prowess and social relationships. This study points to the need for interventions and interventions that will help children weather the emotional fallout of family breakup. Findings highlight children of dysfunctional families are most affected in various contexts such as emotional distress, anxiety, and depression with problems of attachment that greatly challenge healthy social relationship and also the ability to deal with behavioral needs. Instability associated with family breakdown often leads to decrease in academic performance and participation in school.

Intersectionality shapes the access to various adaptive resources in climate-vulnerable contexts

Abstract Intersectional approaches are becoming essential to understanding the differential impacts of climate change and the heterogeneity of adaptive capacities. Varying factors of social and economic privileges and inequalities synergistically shape the local power structure, ultimately determining disproportionality and unequal access to adaptive resources. Using empirical data from coastal Bangladesh, which is part of the Ganges Delta, and one of the world’s -most climate-vulnerable regions, this study shows how religion, gender, and ethnicity intersect with patterns in (i) farm and non-farm incomes, (ii) land conflicts, (iii) the size of farms, and (iv) access to critical sources of weather information. The study highlights that multilayered identity, which is shaped by various structural determinants, including local power structure, can determine gendered dimensions of access to various adaptation resources. It also shows that if policymakers and development partners partially understand or do not understand the complex landscape of local vulnerability or unequal power structures including the adaptive capacity of the vulnerable populations, they would not be able to provide critical support in times of crisis. The concept of intersectionality is therefore critical in addressing adaptation and risk management challenges for regions like the Ganges Delta and other parts of the world, where people are struggling with similar social and environmental challenges.

Current trends and ethical considerations in gene therapy

Abstract. This paper explores the advancements, applications, and ethical challenges associated with gene therapy, a transformative approach to treating genetic disorders. Gene therapy corrects genetic defects at the molecular level, offering potential cures for diseases previously considered intractable. Techniques like CRISPR-Cas9 have revolutionized this field by enabling precise genetic editing. We discuss both ex vivo and in vivo methods, highlighting their applications in treating diseases such as sickle cell disease and inherited blindness. However, the implementation of gene therapy raises significant ethical and safety concerns, including the risks of germline modifications and the high costs limiting access. Safety concerns associated with viral vectors, such as potential oncogenesis and immune reactions, are also examined. The paper calls for evolved regulatory frameworks to ensure safe, ethical, and equitable access to gene therapy, underscoring the need for ongoing public engagement and education to navigate the complex landscape of genetic medicine. This study concludes that while gene therapy holds great promise, it requires evolved regulatory frameworks to ensure safe, ethical, and equitable access. Ongoing public engagement and education are essential to navigating the complex landscape of genetic medicine.

Abstract B008: Exploring the Dual Roles of RNAs as Oncogenic Drivers and Therapeutic Targets in Cancer: A Cross-Sectional Study

Abstract RNAs have emerged as pivotal molecules in the complex landscape of cancer biology, acting as both drivers of oncogenesis and therapeutic targets. This cross-sectional experimental design research explores the dual roles of RNAs, particularly focusing on the interplay between non-coding RNAs (ncRNAs), messenger RNAs (mRNAs), and their regulatory networks in various cancer types. The study systematically analyzes RNA expression profiles across a broad spectrum of cancer samples, employing high-throughput sequencing technologies combined with bioinformatics tools to identify key RNA species that contribute to tumorigenesis. The experimental design includes the collection of tumor and adjacent normal tissues from patients diagnosed with breast, lung, and colorectal cancers. RNA extraction and sequencing are performed to generate comprehensive expression profiles. Differential expression analysis is conducted to pinpoint RNAs that are significantly dysregulated in cancerous tissues compared to their normal counterparts. Subsequently, functional assays, including RNA interference (RNAi) and CRISPR/Cas9-mediated gene editing, are utilized to validate the oncogenic or tumor-suppressive roles of these RNAs in cancer cell lines. To further elucidate the mechanistic pathways, the study integrates data from RNA-binding protein immunoprecipitation (RIP) and crosslinking immunoprecipitation (CLIP) assays, providing insights into the RNA-protein interactions that influence cancer progression. Additionally, the research evaluates the therapeutic potential of targeting these RNAs, using small interfering RNAs (siRNAs) and antisense oligonucleotides (ASOs) in preclinical cancer models. Preliminary findings highlight the significance of long non-coding RNAs (lncRNAs) and micro RNAs (miRNAs) in modulating key signaling pathways involved in cell proliferation, apoptosis, and metastasis. This study underscores the importance of RNA-based diagnostics and therapeutics, paving the way for innovative treatment strategies in cancer management. Citation Format: Fathelrahman M Gameel. Exploring the Dual Roles of RNAs as Oncogenic Drivers and Therapeutic Targets in Cancer: A Cross-Sectional Study [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: RNAs as Drivers, Targets, and Therapeutics in Cancer; 2024 Nov 14-17; Bellevue, Washington. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(11_Suppl):Abstract nr B008.

An investigation into the shifting landscape preferences of rural residents in Taiwan and their relationship with ecological indicators

Rapid urbanization has significantly altered landscape environments in both urban and rural regions, and these landscapes have been demonstrated to play a pivotal role in human well-being. This study develops a coherent framework that integrates landscape change, landscape ecological indicators, and landscape preferences within the context of the evolving landscape environments of rural communities in Taiwan. Four distinct types of rural communities were selected, and a quantitative methodology was employed to investigate the variations and transformations in landscape preferences among rural residents in the context of landscape change. A qualitative methodology was employed to investigate the relationship between landscape ecological indicators and landscape preferences. The study’s findings indicate significant temporal variations in residents’ landscape preferences, with landscape beauty, stewardship, and coherence emerging as key determinants in the evaluation of these preferences. Landscape ecological indicators were found to be significantly correlated with variables such as landscape complexity, landscape beauty, openness, naturalness, and comprehensive landscape assessment. The findings of this study indicate that design planners, land managers, and public sector organizations can employ multidimensional thinking in the management of rural landscapes to align with the visual aesthetic preferences of rural residents.

Monkeys engage in visual simulation to solve complex problems.

Visual simulation-i.e., using internal reconstructions of the world to experience potential future versions of events that are not currently happening-is among the most sophisticated capacities of the human mind. But is this ability in fact uniquely human? To answer this question, we tested monkeys on a series of experiments involving the "Planko" game, which we have previously used to evoke visual simulation in human participants. We found that monkeys were able to successfully play the game using a simulation strategy, predicting the trajectory of a ball through a field of planks while demonstrating a level of accuracy and behavioral signatures comparable with those of humans. Computational analyses further revealed that the monkeys' strategy while playing Planko aligned with a recurrent neural network (RNN) that approached the task using a spontaneously learned simulation strategy. Finally, we carried out awake functional magnetic resonance imaging while monkeys played Planko. We found activity in motion-sensitive regions of the monkey brain during hypothesized simulation periods, even without any perceived visual motion cues. This neural result closely mirrors previous findings from human research, suggesting a shared mechanism of visual simulation across species. Taken together, these findings challenge traditional views of animal cognition, proposing that nonhuman primates possess a complex cognitive landscape, capable of invoking imaginative and predictive mental experiences to solve complex everyday problems.

Psychological explanations for analysts' herding behavior: A study on the impact of information cascades and reputational concerns

This study investigates the influence of information cascades and reputational concerns on analysts' herding behavior in financial markets. Using a mixed-methods approach combining archival data analysis and surveys of 5,237 financial analysts covering S&P 500 companies from 2014 to 2023, we examine the interplay between these psychological factors. Our findings reveal that both information cascades and reputational concerns significantly impact herding behavior, with a notable synergistic effect when combined. Structural equation modeling demonstrates that information cascade strength positively correlates with herding behavior (β = 0.43, p < .001), partially mediated by perceived market consensus. Reputational concerns also show a strong positive association with herding (β = 0.51, p < .001), moderated by career stage. Importantly, the interaction between information cascades and reputational concerns (β = 0.24, p < .001) suggests that their combined effect is greater than the sum of their individual impacts. This effect varies across analyst characteristics and market conditions, with stronger influences observed in small-cap stocks and high-volatility periods. Time-series analysis reveals dynamic fluctuations in these effects over time, responding to significant market events. These results contribute to the theoretical understanding of financial market behavior by integrating social influence and career concern perspectives, offering insights for both scholars and practitioners in an increasingly complex market landscape.

A nonrevisiting genetic algorithm based on multi-region guided search strategy

Recently, nonrevisiting genetic algorithms have demonstrated superior capabilities compared with classic genetic algorithms and other single-objective evolutionary algorithms. However, the search efficiency of nonrevisiting genetic algorithms is currently low for some complex optimisation problems. This study proposes a nonrevisiting genetic algorithm with a multi-region guided search to improve the search efficiency. The search history is stored in a binary space partition (BSP) tree, where each searched solution is assigned to a leaf node and corresponds to a search region in the search space. To fully exploit the search history, several optimal solutions in the BSP tree are archived to represent the most potential search regions and estimate the fitness landscape in the search space. Except for the conventional genetic operations, the offspring can also be generated through multi-region guided search strategy, where the current solution is first navigated to one of the candidate search regions and is further updated towards the direction of the optimal solution in the search history to speedup convergence. Thus, multi-region guided search can reduce the possibility of getting trapped in local optima when solving problems with complex landscapes. The experimental results on different types of test suites reveal the competitiveness of the proposed algorithm in comparison with several state-of-the-art methods.

Synthesis of a hydrological, water chemistry, and contaminants research program in the Peace-Athabasca Delta (Canada) to inform long-term monitoring of shallow lakes

In a multistressor world, evidence-based stewardship of aquatic ecosystems requires long-term monitoring data to understand the timing and magnitude of environmental change and potential causes. At the Peace-Athabasca Delta (PAD; northeastern Alberta, Canada), concern for aquatic ecosystem degradation has triggered renewed and urgent calls by Indigenous, national, and international governance bodies for implementation of a long-term lake monitoring program capable of tracking changes in hydrological conditions and contaminant deposition attributable to major energy projects located upstream, climate change, and other unnatural and natural processes. Challenges imposed by the delta's size, hydrological complexity, inaccessibility of lakes, and other factors, however, have long impeded implementation of a delta-wide lake monitoring program. To address this pressing need, here we review and synthesize results obtained during 7 years (2015–2021) of intensive, multifaceted research at 60 shallow lakes spanning the delta's broad hydroecological gradients to inform an integrated hydrology, water chemistry, and contaminants monitoring program. The research involved systematic, repeated measurements of water isotope composition, water depth variation, water chemistry and turbidity, and metal(loid) concentrations in lake surface sediment and periphytic biofilm. Results reveal marked spatial and temporal variation of hydrological processes and their affects on lake water balance and depth, strong association between hydrological processes and lake water chemistry, and that concentrations of nickel and vanadium (key oil sands indicators) remain within the range of natural variation. Correspondence of generalized additive model trendlines for isotope-derived lake evaporation-to-inflow ratios and water chemistry with climate indices (Pacific Decadal Oscillation, Oceanic Niño Index) demonstrates the sensitivity, and predictability, of lake ecosystem processes in the delta to large-scale climatic patterns. We provide recommendations for field sampling, sample analysis, data display, and integration of information for ongoing monitoring at the PAD. These approaches are readily transferable to other complex landscapes with abundant shallow waterbodies threatened by multiple stressors that may alter hydrological regimes and contaminant delivery.

Dissident Blood: Neo-Santeria in Barcelona and the Refusal of Sacrifices

This article explores the emergence and development of Neo-santeria in Barcelona, a contemporary trend of Afro-Cuban religious practices characterized by the rejection of animal sacrifice, a central ritual in traditional Santeria. The study identifies and analyzes four key arguments employed by Neo-santeros to legitimize this rejection within the secular and modern European context: the scientistic, de-traditionalist, individualistic, and ecologist arguments. Drawing on over a decade of ethnographic research, the article demonstrates how Neo-santeros navigate the tension between distancing themselves from certain traditional spiritual roots—particularly the practice of animal sacrifice—and the intertwining with European and contemporary cultural logics, particularly those related to secularism. The article situates Neo-santeria within the broader landscape of European holistic spiritualities, highlighting its strategic positioning as a religion that aligns with and challenges secularist expectations in modern Europe. The findings contribute to a deeper understanding of how Afro-Cuban religions, particularly Neo-Santería, can be defined by the ongoing creativity of their practitioners. This distinctive feature not only defines the fluid nature of these traditions but also contributes to the diversification and increased complexity of the spiritual landscape in European contexts, where Afro-Cuban practices are being intertwined in local cultural and religious frameworks.

The impact of legal uncertainties on innovating HR practices in developing countries: a case study of remote work during the healthcare crisis in Kazakhstan’s technical gas industry

This study explores the influence of legal uncertainties on the process of innovating human resources (HR) practices in developing countries. Through a case study focused on introducing remote work within Kazakhstan’s Technical Gas Industry during a healthcare crisis, we examine the multifaceted challenges and opportunities that emerge when navigating a complex legal landscape. Our findings reveal that legal uncertainties, stemming from inadequacies in legislation and the tightness of norms, significantly impede the ability to adapt and modernize HR practices during crises. Furthermore, the criticality of the company’s position within the industry, combined with a low degree of legal enforcement, underscores the concept of ‘responsibilization’ among HR professionals. This phenomenon compels HR practitioners to assume greater responsibility and make strategic decisions that occasionally push the boundaries of existing laws and regulations. In this context, we propose a novel conceptualization of responsibilization, distinct from empowerment, as it involves embracing negative legal consequences associated with proactive decision-making during crises. This study contributes significantly to our understanding of how legal uncertainties influence the process of HR innovation in developing countries, highlighting the intricate interplay between regulatory frameworks, crisis management, and organizational transformation.

The Role of Artificial Intelligence in Higher Education

The integration of Artificial Intelligence (AI) in higher education has sparked a transformative shift in pedagogical methodologies, student engagement, and academic integrity across the UK and Ireland (Dogru, et.al, 2023). This qualitative study delves into the multifaceted implications of utilising AI in academic assignments from the perspective of higher education students, drawing on semi-structured interviews carried out with higher education students. The findings reveal a variety of perceived benefits, including enhanced study efficiency, personalised learning support (Hanaba et al., 2020; Yang, 2021), and the potential of AI to level the academic playing field for students with diverse needs. However, these advantages are in contrast with students’ perceptions of a wide range of significant concerns and challenges, notably the ethical dilemmas surrounding academic honesty, the potential for student dependency on AI leading to diminished knowledge and skill development, as well as the issue of equity in relation to students’ access to AI resources. Moreover, the study stresses a critical gap in institutional guidance regarding AI use, with students voicing a need for clear, consistent guidance from universities. This paper highlights the complex landscape of AI in academia, advocating for a balanced approach that harnesses AI's potential while addressing ethical, educational, and equity challenges. The study emphasises a need for immediate and more in-depth research into the use of AI in higher education from the perspective of both students and university staff in Ireland/UK.

FunCoup 6: advancing functional association networks across species with directed links and improved user experience.

FunCoup 6 (https://funcoup.org) represents a significant advancement in global functional association networks, aiming to provide researchers with a comprehensive view of the functional coupling interactome. This update introduces novel methodologies and integrated tools for improved network inference and analysis. Major new developments in FunCoup 6 include vastly expanding the coverage of gene regulatory links, a new framework for bin-free Bayesian training and a new website. FunCoup 6 integrates a new tool for disease and drug target module identification using the TOPAS algorithm. To expand the utility of the resource for biomedical research, it incorporates pathway enrichment analysis using the ANUBIX and EASE algorithms. The unique comparative interactomics analysis in FunCoup provides insights of network conservation, now allowing users to align orthologs only or query each species network independently. Bin-free training was applied to 23 primary species, and in addition, networks were generated for all remaining 618 species in InParanoiDB 9. Accompanying these advancements, FunCoup 6 features a new redesigned website, together with updated API functionalities, and represents a pivotal step forward in functional genomics research, offering unique capabilities for exploring the complex landscape of protein interactions.

Attitudes, perceptions, and intentions toward sports betting legalization: a cluster analysis of California residents

ABSTRACT In the United States, the potential legalization of sports betting in non legal states presents a complex landscape of opportunities and challenges. This study examines California voters’ attitudes toward sports betting, the perceived impacts of its legalization, and the factors influencing their voting intentions. Utilizing the Theory of Reasoned Action (TRA), the research explores how attitudes and subjective norms shape voter behavior. A K-Means clustering analysis identified three distinct voter segments: supporters, neutrals, and opponents. The analysis revealed significant differences in voting intentions, attitudes, and perceived impacts across these clusters. These findings highlight the importance of robust policy and tailored marketing strategies that address the specific concerns and motivations of each voter segment. By providing insights into voter preferences and behaviors, this research offers valuable guidance for policymakers, operators, and stakeholders involved in the sports betting industry, supporting informed decision-making and responsible policy and messaging strategy.

The context‐dependent benefits of organic farming on pollinator biodiversity: A meta‐analysis

Abstract Agricultural intensification is driving declines in pollinator diversity and the degradation of pollination services worldwide. Organic management, which prohibits the use of synthetic inputs, has considerable potential for combatting these declines by enhancing biodiversity in agricultural landscapes. However, the efficacy of organic farming for promoting pollinator diversity has recently been questioned. We conducted a meta‐analysis to determine the effect of organic management on pollinator species richness and abundance. We compiled 42 studies across four continents and calculated a Hedges' g effect size for each of 76 species richness and 57 abundance observations. We then estimated average effect sizes overall and across five moderators. Species richness and abundance of pollinating insects tended to be higher in organic farms than conventional ones, with average effect sizes of 0.68 and 0.74, respectively. Landscape context, crop type, pollinator group, sampling location, and sampling method were factors impacting the response of pollinator diversity/abundance to organic farming. We found benefits for pollinator diversity from organic farming in all landscape types, with the strongest response in simple compared with more complex landscapes. Pollinator diversity benefited the most in habitats within organic cereal systems and the least in organic pastures. Among pollinator groups, bumblebee diversity benefitted the most, while moths and hoverflies showed positive but non‐significant responses. Higher pollinator diversity/abundance was detected in organic farms at various sampling locations. Transect sampling showed the greatest diversity gains among sampling methods. Synthesis and applications. Our results affirm that organic farming has positive effects for pollinator species richness and abundance, but benefits are variable and not guaranteed. We recommend that future studies adopt a standard sampling protocol and cover a larger geographic range to understand the global potential of organic farming to promote pollinator biodiversity. Efforts to increase pollinator abundance and diversity through organic farming should focus on organic systems involving cereal phases, especially within simple landscapes, for the most positive outcomes. However, due to high variability in pollinator responses alongside the challenges to achieve economic profitability from organic farming, crafting organic farming systems to specific farm‐scale opportunities and needs may be necessary.

Spatio-temporal trends in the frost regime reveal late frost exposure to white spruce (Picea glauca [Moench] Voss) persists in northeastern America

Abstract The characteristics of the frost regime (intensity, frequency, and timing) contribute to shaping tree species adaptations and distribution as well as ecosystem productivity and functions. However, climate change increases the variability in extreme events; therefore, the different characteristics of the frost regime may diverge under climate change. Using the BioSim 11 software, we simulated daily air temperature at 512 locations over northeastern North America between 1901–2021 to determine how the spatio-temporal trends in the frost regime varied over this complex landscape and if spatio-temporal trends in extreme climatic events such as frosts are stronger compared to changes in aggregated climate variables such as mean annual air temperature and growing degree-days. We also used an eco-physiological model to conduct a case study focussing on white spruce to determine if trees are currently more exposed to growing season frosts than they were in the past by modelling the timings of budburst using the thermal time model. Our results showed that, at 67% of locations (343 locations), the day of the year of the last frost in spring (minimum daily air temperature<0 °C) occurred, on average, earlier by seven days during 2001–2021 compared to 1901–1920, whereas it occurred, on average, later by four days at 33% of locations (169 locations). The average temporal trends in frost occurrence were similar in magnitude to the average trends in aggregated climate variables; however, their variances were larger compared to the aggregated climate metrics, showing that the frost regime does not change uniformly throughout our study area. Our case study also revealed that white spruce remains exposed to late frosts of low and intermediate intensities (minimum daily air temperature <0; <−2 °C) compared to the past but exposure to high-intensity frosts (minimum daily air temperature <−4 °C) is rare. Since extreme events such as late frosts diverge in their response to climate change compared to aggregated climate variables, the mean annual temperature is not sufficient to predict how climate change will impact ecosystems through frost regimes.

EPCO-05. GENOMIC AND CLINICAL INSIGHTS FROM A LARGE-SCALE STUDY OF 172 RETINOBLASTOMAS

Abstract Retinoblastoma, a pediatric ocular cancer, is the only central nervous system tumor visible without specialized tools, readily detectable with the naked eye. This rare childhood cancer is mainly driven by mutations in RB1 or MYCN amplification, posing significant challenges in pediatric oncology. We conducted whole exome sequencing on 172 retinoblastoma tumors along with matched blood DNA from 171 patients, which included 119 unilateral, 49 bilateral, and three trilateral cases. Our analysis identified pathogenic variants in RB1 in 76 patients and MYCN duplication in 79 cases, highlighting their crucial roles in the disease. Additionally, we found mutations in RPTOR and TSC2, components of the mTOR signaling pathway, in two patients. Notably, our copy number alteration analysis revealed recurrent arm-level changes, including gains on 1q (23.3%), 2p (20.9%), and especially 6p (41.3%), along with other changes such as 5p gain (8.1%), 17q gain (8.1%), and 16q loss (5.8%). Our findings link these genetic alterations to specific clinical features; for instance, 6p gains were associated with Rubeosis, subretinal seeds, and tumor LC beyond, while 17q gains were linked to Rubeosis. Furthermore, gene collapsing techniques identified MATR3 and CYP4F2 as additional novel retinoblastoma-related genes, and module identification analysis pinpointed retinoblastoma-associated modules including HLA-DRB1-CBL, LPAR2, RB1, and TRIM28. Our study, the largest cohort of its kind, underscores the importance of next-generation sequencing from understudied populations in uncovering the complex genetic landscape of retinoblastoma, emphasizing the potential of precision medicine to enhance therapeutic strategies and improve outcomes for retinoblastoma patients.

Malnutrition in Nepal: A Comprehensive Analysis of Micronutrient Deficiencies, Health Impacts, and Intervention Strategies

Malnutrition, particularly micronutrient deficiencies, remains a significant public health challenge in Nepal, affecting vulnerable populations such as children under five, pregnant women, and lactating mothers. This thesis examines the complex landscape of malnutrition in Nepal, focusing on the causes, health impacts, and socio-economic consequences of nutrient deficiencies. The research highlights the severe effects of malnutrition, including stunting, anaemia, and developmental delays, which contribute to broader social and economic disparities. A detailed analysis of the most affected populations and regions, based on national surveys and studies, underscores the critical need for targeted interventions. This study also evaluates existing nutrition programs in Nepal, assessing their effectiveness and identifying gaps in coverage, particularly in remote and rural areas. The findings emphasize the importance of a multi-sectoral approach that integrates nutrition-specific interventions with broader efforts to improve food security, healthcare access, and economic opportunities.

Recent progress in atmospheric modeling over the Andes – part I: review of atmospheric processes

The Andes is the longest mountain range in the world, stretching from tropical South America to austral Patagonia (12°N-55°S). Along with the climate differences associated with latitude, the Andean region also features contrasting slopes and elevations, reaching altitudes of more than 4,000 m. a.s.l., in a relatively narrow crosswise section, and hosts diverse ecosystems and human settlements. This complex landscape poses a great challenge to weather and climate simulations. The interaction of the topography with the large-scale atmospheric motions controls meteorological phenomena at scales of a few kilometers, often inadequately represented in global (grid spacing ∼200–50 km) and regional (∼50–25 km) climate simulations previously studied for the Andes. These simulations typically exhibit large biases in precipitation, wind and near-surface temperature over the Andes, and they are not suited to represent strong gradients associated with the regional processes. In recent years (∼2010–2024), a number of modeling studies, including convection permitting simulations, have contributed to our understanding of the characteristics and distribution of a variety of systems and processes along the Andes, including orographic precipitation, precipitation hotspots, mountain circulations, gravity waves, among others. This is Part I of a two-part review about atmospheric modeling over the Andes. In Part I we review the current strengths and limitations of numerical modeling in simulating key atmospheric-orographic processes for the weather and climate of the Andean region, including low-level jets, downslope winds, gravity waves, and orographic precipitation, among others. In Part II, we review how climate models simulate surface-atmosphere interactions and hydroclimate processes in the Andes Cordillera to offer information on projections for land-cover/land-use change or climate change. With a focus on the hydroclimate, we also address some of the main challenges in numerical modeling for the region.