Hasil untuk "Harbors and coast protective works. Coastal engineering. Lighthouses"

Zenghui Wang, Junqiang Xia, Chengzheng Yu et al.

Retrogressive erosion, a critical process impacting river engineering structures, channel geomorphology, and reservoir sediment management, manifests primarily in two distinct forms: rotating and stepped bed deformation. The former type is dominated by sediment entrainment, whereas the latter is dominated by mass failure. Simulating these processes accurately, particularly predicting which form will dominate, poses significant challenges for existing numerical models. This study addresses this gap by developing and validating a numerical model capable of simulating both rotating and stepped retrogressive erosion with automatic adjustment between the two types. The model integrates governing equations for unsteady nonuniform flow and nonequilibrium sediment transport with specialized modules for each erosion type. The rotating erosion module incorporates sediment entrainment theories suitable for high flow velocities and steep slopes, accounting for shear dilatancy effects. The stepped erosion module employs force equilibrium analysis to predict the critical horizontal erosion distance at the step toe to induce mass failure. A key feature is the implementation of a criterion based on the ratio of shear stresses at the top and bottom of the overfall relative to the critical shear stress, allowing the model to adapt the simulation approach on the basis of evolving hydrodynamic conditions. The hydrodynamic and sediment transport equations are solved at each time step, and the criterion is applied to determine whether the rotating or stepped erosion model is used to further solve bed deformation. Model calibration and verification were performed via laboratory flume data covering various inflow discharges, initial step heights, and bed material properties. For rotating-type erosion simulations, the model demonstrated high accuracy, with Nash–Sutcliffe efficiencies (NSEs) for water surface and bed elevation calculations generally exceeding 0.9. The calculated cumulative erosion amounts also agreed well with the measurements, with relative errors mostly less than 10 % in the later stages. The maximum Froude number, which was located at the end of the foreset reach, increased from 1.72 to 3.40 during the entire test. The maximum sediment concentration was almost constant. For stepped erosion, the model successfully replicated the characteristic headcut migration, although the results were sensitive to the erodibility coefficient. The errors of predicted overall migration rate were within 12.5 % of the measured values. The developed model provides a robust tool for predicting retrogressive erosion dynamics and is uniquely capable of handling both rotating and stepped forms.

Ken W. Krauss, Jeremy R. Conrad, Jamie A. Duberstein et al.

J.N. “Ding” Darling National Wildlife Refuge (DDNWR) is located on Sanibel Island along the southwestern coast of Florida, USA. There, eutrophication attributed to agricultural discharge along the Caloosahatchee River has affected the area’s aquatic habitat. In anticipation of additional nutrient loading, we experimentally fertilized mangrove forests with nitrogen (+N; NH4) and phosphorus (+P; P2O5) for 3 years, and monitored soil and pneumatophore CO2 fluxes and tree sap flow from two mangrove species. Furthermore, we modeled individual tree and stand water use, from which we developed carbon (C) budgets for +N and + P vs. control simulations based on a novel application of water use efficiency conversion. Many of the measured response variables provided hints of subtle changes in response to +P rather than +N, which were enhanced when scaled. From this, we found that additional P loading is expected to reduce both gross and net primary productivity as well as CO2 uptake via net ecosystem exchange of C, likely pressing the system beyond metabolic capacity and leading to a 48–62% decrease in projected lateral C export. Greater eutrophication will likely compound vulnerabilities to sea-level rise submergence, especially where P concentrations are high and already reducing soil surface elevations.

Ziqiang Mao, Yiguo Ran, Qiao Chen et al.

Accurate quantification of sediment sources is essential for assessing bank erosion, mitigating reservoir sedimentation, and ensuring long-term sustainability. However, estimates for ungaged areas remain uncertain due to systematic monitoring gaps, and modeling efforts often lack reliability because of insufficient sediment records. To address this issue, grain size distributions (GSDs) were analyzed for two sediment cores, approximately 2.7 m in length, collected from the RangDu (RD) and ZhongXian (ZX) areas in the Three Gorges Reservoir (TGR), China. Suspended sediment from the mainstream and primary bank-derived materials from ungaged areas served as end members for quantitative source apportionment. Sedimentation periods were inferred by correlating temporal grain-size variations with precipitation intensity. The results indicate that both cores recorded continuous sedimentation from 2012 to 2022. The contribution of primary bank-derived materials from ungaged areas exhibited significant seasonal and spatial variations, averaging 36 % in the RD core (2012–2019) and 3.6 % in the slow-flow ZX core (2015–2022). Topographic and hydrodynamic conditions facilitated greater deposition of suspended materials in slow-flow areas compared to the main channel. The substantial contribution of bank-derived materials to reservoir sediment systems highlights the critical influence of wet-season rainfall on bank erosion and associated reservoir sediment. Nevertheless, given the current limitations in core sample quantity and temporal coverage, future studies should extend sedimentary conditions and temporal scope of sediment records for better understanding the impacts of precipitation, particularly extreme precipitation events, on bank erosion and reservoir sedimentation processes under global climate change.

Misagh Parhizkar, Manuel Esteban Lucas-Borja, Nikolaos Tziolas et al.

Very few studies have explored the effectiveness of polyacrylamide (PAM) application on soil in mitigating rill erosion, especially in deforested environments. This study has measured the soil detachment capacity (Dc) on samples of deforested soil (untreated or treated with PAM). Dc has been estimated by flume experiments under three bed slopes (6.9 %, 17.2 %, and 18.2 %) and five flow discharges (0.078, 0.096, 0.116, 0.138, and 0.154 L·s−1) together with three key soil properties (cation exchange capacity, mean weight diameter of soil aggregates, and organic matter content). Compared to the untreated soil, Dc has significantly (p < 0.05) decreased on average by 38 % after the PAM application, while the cation exchange capacity, stability of soil aggregates, and organic matter content have increased (p < 0.001) by 50 % to over 100 %. However, Dc is weakly correlated to the latter soil properties (r < 0.33, p < 0.05). A clear discrimination between treated and untreated sites has been revealed by a multivariate statistical analysis. The soil erodibility parameter (Kr) and critical shear stress (τc) in rills have also been estimated through linear regressions on Dc for use in erosion models. Dc can be accurately estimated by linear equations using the stream power as a predictor (R2 > 0.77). Overall, the study has demonstrated that PAM is an effective soil amendment that reduces soil detachment in rills of deforested hillslopes by about 40 %.

Estela Carbonell-Garzon, Angela Mateo, Laura Leyva et al.

Human activities have driven habitat degradation and biodiversity loss in marine ecosystems, highlighting the need for strategies that reconcile food production with ecosystem restoration. Restorative aquaculture has emerged as a potential tool to enhance habitat complexity, nutrient cycling, and biodiversity. The review highlighted a global imbalance between mussel production and research on its ecological benefits, with most studies emphasizing environmental impacts rather than positive ecosystem effects. Mussel farms enhance habitat complexity and provide trophic subsidies through mussel fall-off, supporting higher abundances of crustaceans and echinoderms, including commercial species such as lobsters. Ecological effects vary with spatial scale, production type (inshore vs. offshore), substrate characteristics, and farm structure. This review highlights both the ecological benefits and potential risks, including ecological traps. Research gaps include the need for quantitative assessments and long-term monitoring. Mussel farms act as both trophic and structural facilitators, demonstrating how low-trophic aquaculture can synergistically support marine biodiversity and ecosystem resilience. Properly managed, mussel farming could transition from a food production activity to a regenerative ecological tool.

Emma Verling, Maria Power, Melanie Biausque et al.

The impacts of climate change have become more widespread and frequent, and society is beginning to recognise the connection between it and the biodiversity crisis. Communities have the capacity to play a key role in the success of multi-stakeholder nature restoration projects, but examples of successful projects, in which communities are the architects of the action – as opposed to the recipients of it – are not well documented. This study used a participatory evaluation research approach to explore a multi-stakeholder, community-led restoration project at Harper’s Island Wetlands, Co. Cork, Ireland to understand the elements of success and to extract key learnings for other communities. In order to rapidly upscale nature restoration and biodiversity protection globally, there is an urgent need to gain speed and momentum, identifying innovative approaches and disseminating them appropriately. The insights from this case study highlight four key components to be considered by groups at the beginning of community-led projects: setting up a core committee, assigning clear roles within the committee, creating a short-, medium- and long-term strategy and beginning practical tasks as soon as possible. This research serves as a step towards preparing blueprints to inform research, policy and practice in this space to enable stakeholders to respond collectively

Zihao Tang, Bruce W. Melville, Naresh Singhal et al.

Microbially induced calcite precipitation (MICP) is an emerging method for mitigating scour and erosion. The present study experimentally investigates the efficacy of MICP as a local scour countermeasure for offshore wind turbine monopile foundations under both clear water and live-bed conditions. Bacteria were enriched using activated sludge. Analyses conducted included urease activity monitoring, unconfined compression testing, and examination using scanning electron microscopy. Various depths for the MICP protection elevation were tested in clear water conditions, and the resulting scour topography was mapped using photogrammetry techniques. Investigations were conducted on bedform migration and leading-edge scour upstream of the MICP protection, considering various protection elevations. The results indicated that MICP protection can provide effective scour protection under both clear water and live-bed conditions. Discussions in this study also extend to the erosion and potential collapse of the MICP protection structure. Flow undercut rate were also examined for evaluating potential failure of MICP protection structures, and the elevation of MICP protection has a significant influence on mitigating flow undercutting. Full protection efficiency was observed under clear water conditions when the MICP protection elevation was at the bed level and the flow intensity was relatively low (V/Vc = 0.65), while the highest average protection efficiency (47.73%) among all flow intensities was recorded when the MICP protection elevation was at 0.6D below the bed.

Juan Carlos Alcérreca-Huerta, Oscar F. Reyes-Mendoza, Laura Carrillo et al.

Unprecedented quantities of pelagic sargassum since 2011 have demanded technical and management responses. Inappropriate measures might worsen environmental impacts, particularly in low-income regions and protected natural areas that also require low-cost, socio-ecologically integrated alternatives. This study aims to evaluate the effectiveness and local perception of sargassum clean-up treatments developed through a community–academic collaboration within a socio-ecological systems framework in the marine protected area Xcalak Reefs National Park (PNAX), at the southernmost Mexican Caribbean coast. In 2019 and 2021, clean-up efforts were implemented through the national PROREST program and a self-organized community group of 35–40 members supported by a multidisciplinary research advisory team. Monitoring in 2021 estimated sargassum removal at 4012 m² over 50–75 work hours. Although average shoreline retreat was obtained (<i>δ_mean</i> = −0.22 m), final accretion of ~0.96 m alleviated community concerns about erosion linked to clean-up activities. The most effective and socially accepted clean-up treatment involved sargassum spreading, collection, drying, and revetment-type beach protection, reducing odors and harmful fauna. However, treatments aimed at shoreline stabilization were impractical, raising doubts about their long-term efficacy. These findings highlight the relevance of integrating ecological performance and social perception in sargassum management, especially where co-management with local communities in marine protected areas is needed.

Ana Beatriz A. de M. Salata, Marília G. A. Pereira, Isabelle F. S. de Lima et al.

Brazil suffered the largest oil spill disaster in its history, beginning on August 2019, affecting the Northeast coast. This study proposes a chemical investigation of oils from the 2019 spill in Brazil, which had naturally undergone different weathering processes in terrestrial and aquatic environments after an extended period of exposure. Three samples were collected at different times and under distinct environmental conditions, coded as spilled oil (SO), oil recovered from the aquatic environment (SA), and oil collected from the terrestrial environment (ST), the latter two having spent more time naturally exposed to aquatic and terrestrial environments. The analyses were performed by gas chromatography–mass spectrometry (GC-MS) and electrospray ionization coupled with Fourier transform ion cyclotron resonance mass spectrometry (ESI FT-ICR MS). The results of the GC-MS analysis indicated that, although the samples share a common geochemical origin, the SA and ST samples showed a decrease in the intensity of <i>n</i>-alkane distribution compared to the SO sample, mainly attributed to evaporation and biodegradation processes. FT-ICR MS analysis identified dozens of classes of ESI(+) and ESI(–) compounds, most of them rich in sulfur and oxygen, with the highest intensities and quantities of molecular formulas in the SA and ST samples. Diagnostic ratios for heteroatom classes concluded that the SA and ST samples had undergone a higher level of weathering, mainly associated with photooxidation and biodegradation processes. Thus, the combined use of GC-MS and FT-ICR MS proved to be a robust approach for the detailed characterization of spilled oils, contributing to a clearer understanding of the extent and type of weathering in samples from the 2019 Brazilian spill.

Yang Li, Jianjun Zhang, Yawei Hu et al.

Flow discharge, slope gradient, and erosion time are widely recognized as crucial factors in determining rill erosion and its morphological characteristics. However, the relative importance of these three factors needs to be further elaborated to refine the understanding of rill erosion. In the current study, scour experiments were done under various conditions, including five flow discharges (0.5, 1.0, 1.5, 2.0, and 2.5 mm/min), five slope gradients (5°, 10°, 15°, 20°, and 25°), and durations of 20, 40, and 60 min. The resulting rill erosion process and its related morphological characteristics have been documented and analyzed. The results demonstrate that the average soil loss rate increased significantly with the increase inflow discharge and slope gradient. The individual effect of flow discharge (38.35%) was more pronounced than that of slope gradient (18.38%). Increasing flow discharge, slope gradient, and scouring time intensified the occurrence of headward erosion. Over extended erosion durations, rill length, width, depth, and volume all experienced increases. Additionally, with higher flow discharge and steeper slope gradient, the rill width-depth ratio decreased, indicating that rills became narrower and deeper. The individual effect of flow discharge on all rill morphological characteristics was more pronounced than that of slope gradient and scouring time. Except for rill length, the slope gradient had a greater impact on rill morphological characteristics than scouring time. Importantly, a significant portion of the runoff's potential energy was channeled into soil erosion rather than kinetic energy in sediment-laden flow. Based on the principle of energy conservation, the occurrence of rills reduced the energy required for soil erosion from 83.84 to 598.96 J/kg to 2.22–37.53 J/kg. The current study deepens the understanding of rill erosion mechanisms on the Loess Plateau in China and provides a scientific foundation for soil erosion control.

Joseph Dellicarpini, Mark Borrelli, Stephen T. Mague et al.

The real-time forecast estimates of total water levels (TWL) associated with coastal storms by the Boston Office of the National Weather Service (NWS), and the analysis, identification, and field mapping of storm tide pathways (STP) by the Center for Coastal Studies (CCS) within the forecast region, has led to improved model forecasts, enhanced allocation of resources prior to storm impact (e.g., placement of flood control measures, identification of evacuation routes, development of applications to visualize and communicate threats, etc.), and increased public awareness of the practical implications of sea level rise and storm-related coastal flooding. Both NWS modeling and STP mapping are discussed here. The coupling of these methods began in 2016–2017 in Provincetown, MA, and its utility was highlighted during the new storm of record for most of southern New England, a nor’easter in January 2018. The use of this information by managers, stakeholders, and the public has increased since combining the TWL modeling and STP mapping in an online portal in 2021, and it continues to be used by emergency managers and the public to plan for approaching coastal storms.

Sharon Guardado, Risha Parveen, Zheying Zhang et al.

The integration of Large Language Models (LLMs) in Requirements Engineering (RE) education is reshaping pedagogical approaches, seeking to enhance student engagement and motivation while providing practical tools to support their professional future. This study empirically evaluates the impact of integrating LLMs in RE coursework. We examined how the guided use of LLMs influenced students' learning experiences, and what benefits and challenges they perceived in using LLMs in RE practices. The study collected survey data from 179 students across two RE courses in two universities. LLMs were integrated into coursework through different instructional formats, i.e., individual assignments versus a team-based Agile project. Our findings indicate that LLMs improved students' comprehension of RE concepts, particularly in tasks like requirements elicitation and documentation. However, students raised concerns about LLMs in education, including academic integrity, overreliance on AI, and challenges in integrating AI-generated content into assignments. Students who worked on individual assignments perceived that they benefited more than those who worked on team-based assignments, highlighting the importance of contextual AI integration. This study offers recommendations for the effective integration of LLMs in RE education. It proposes future research directions for balancing AI-assisted learning with critical thinking and collaborative practices in RE courses.

Justus Bogner, Roberto Verdecchia

From its early foundations in the 1970s, empirical software engineering (ESE) has evolved into a mature research discipline that embraces a plethora of different topics, methodologies, and industrial practices. Despite its remarkable progress, the ESE research field still needs to keep evolving, as new impediments, shortcoming, and technologies emerge. Research reproducibility, limited external validity, subjectivity of reviews, and porting research results to industrial practices are just some examples of the drivers for improvements to ESE research. Additionally, several facets of ESE research are not documented very explicitly, which makes it difficult for newcomers to pick them up. With this new regular ACM SIGSOFT SEN column (SEN-ESE), we introduce a venue for discussing meta-aspects of ESE research, ranging from general topics such as the nature and best practices for replication packages, to more nuanced themes such as statistical methods, interview transcription tools, and publishing interdisciplinary research. Our aim for the column is to be a place where we can regularly spark conversations on ESE topics that might not often be touched upon or are left implicit. Contributions to this column will be grounded in expert interviews, focus groups, surveys, and position pieces, with the goal of encouraging reflection and improvement in how we conduct, communicate, teach, and ultimately improve ESE research. Finally, we invite feedback from the ESE community on challenging, controversial, or underexplored topics, as well as suggestions for voices you would like to hear from. While we cannot promise to act on every idea, we aim to shape this column around the community interests and are grateful for all contributions.

Hashini Gunatilake, John Grundy, Rashina Hoda et al.

Empathy plays a critical role in software engineering (SE), influencing collaboration, communication, and user-centred design. Although SE research has increasingly recognised empathy as a key human aspect, there remains no validated instrument specifically designed to measure it within the unique socio-technical contexts of SE. Existing generic empathy scales, while well-established in psychology and healthcare, often rely on language, scenarios, and assumptions that are not meaningful or interpretable for software practitioners. These scales fail to account for the diverse, role-specific, and domain-bound expressions of empathy in SE, such as understanding a non-technical user's frustrations or another practitioner's technical constraints, which differ substantially from empathy in clinical or everyday contexts. To address this gap, we developed and validated two domain-specific empathy scales: EmpathiSEr-P, assessing empathy among practitioners, and EmpathiSEr-U, capturing practitioner empathy towards users. Grounded in a practitioner-informed conceptual framework, the scales encompass three dimensions of empathy: cognitive empathy, affective empathy, and empathic responses. We followed a rigorous, multi-phase methodology, including expert evaluation, cognitive interviews, and two practitioner surveys. The resulting instruments represent the first psychometrically validated empathy scales tailored to SE, offering researchers and practitioners a tool for assessing empathy and designing empathy-enhancing interventions in software teams and user interactions.

Dinesh Eswararaj, Ajay Babu Nellipudi, Vandana Kollati

The automotive industry generates vast amounts of data from sensors, telemetry, diagnostics, and real-time operations. Efficient data engineering is critical to handle challenges of latency, scalability, and consistency. Modern data lakehouse formats Delta Parquet, Apache Iceberg, and Apache Hudi offer features such as ACID transactions, schema enforcement, and real-time ingestion, combining the strengths of data lakes and warehouses to support complex use cases. This study presents a comparative analysis of Delta Parquet, Iceberg, and Hudi using real-world time-series automotive telemetry data with fields such as vehicle ID, timestamp, location, and event metrics. The evaluation considers modeling strategies, partitioning, CDC support, query performance, scalability, data consistency, and ecosystem maturity. Key findings show Delta Parquet provides strong ML readiness and governance, Iceberg delivers high performance for batch analytics and cloud-native workloads, while Hudi is optimized for real-time ingestion and incremental processing. Each format exhibits tradeoffs in query efficiency, time-travel, and update semantics. The study offers insights for selecting or combining formats to support fleet management, predictive maintenance, and route optimization. Using structured datasets and realistic queries, the results provide practical guidance for scaling data pipelines and integrating machine learning models in automotive applications.

Jerrica M. Waddell, Christina C. Pater, Michael R. S. Coffin et al.

<i>Zostera marina</i> is an ecologically valuable species that has been declining due to anthropogenic environmental stressors. In this study, spatial and temporal indicators of eelgrass stress, such as coverage and biomass, were compared with the isotopic composition of C, N, and S to understand the mechanism(s) of plant stress. Eelgrass samples were collected in June, July, and August of 2020 at five stations along an estuary spatial gradient in the southern Gulf of St. Lawrence to measure above- and below-ground biomass and tissue isotopes in eelgrass leaves and roots/rhizomes. Eelgrass biomass was lowest at the innermost sampling station, which coincided with eutrophication-induced hypoxia relative to outer sampling stations. δ¹³C levels at the upstream station were depleted compared to downstream stations. Comparatively, δ¹⁵N and δ³⁴S findings were not correlated with plant biomass. Thus, sulfide intrusion was not a major stressor for eelgrass in this estuary. Between the years 2014 and 2020, eelgrass coverage was found to have increased, which coincided with high and low recorded external nutrient loads from the Wheatley River, respectively. Ultimately, these findings indicate that isotopic composition and biomass can be useful in assessing the health of eelgrass in temperate estuaries.

Sarina Niedzwiedz, Tobias Reiner Vonnahme, Thomas Juul-Pedersen et al.

Kelps (Phaeophyceae, Laminariales) are ecosystem engineers along Arctic rocky shores. With ongoing climate change, the frequency and intensity of marine heatwaves are increasing. Further, extensive meltwater plumes darken Arctic fjords. Assessing the effect of a sudden temperature increase at the cold-distribution limit of cold-temperate kelp species, we compared the responses of two kelp species (Agarum clathratum, Saccharina latissima) to realistic Arctic summer heatwave scenarios (4–10°C) under low- and high-light conditions (3; 120 μmol photons m−2 s−1) for 12 days. We found high-light causing physiological stress in both species (e.g., lower photosynthetic efficiency of photosystem II), which was enhanced by cold and mitigated by warm temperatures. Under low-light conditions, we found no temperature response, probably due to light limitation. Both species acclimated to light variations by adjusting their chlorophyll a concentration, meeting cellular energy requirements. A. clathratum had ~150% higher phlorotannin concentrations than S. latissima, possibly acting as herbivore-deterrent. Our findings suggest competitive advantages of kelps on different Arctic coasts with ongoing warming: A. clathratum has advantages in future areas, with low-light intensities, and possibly high grazing pressure and S. latissima in areas with high-light intensities and low grazing pressure. Species composition changes might have cascading consequences on ecosystem functioning.

Paloma Alcorlo, Susana García-Tiscar, María Rosario Vidal-Abarca et al.

The goal of this project is to assess the state of marine biodiversity in the Natura 2000 marine network in Spain and analyze the impact of fishing policies on it. The study focuses on three marine demarcations in Spain: North Atlantic, South Atlantic, and the Strait of Gibraltar and Alborán Sea. The research uses the DPSIR (Drivers of Change-Pressure-State-Impact-Response) framework, a multi-criteria analysis approach to understand the relationships between biodiversity loss, fishing, marine ecosystem integrity, and the provision of ecosystem services. Our results revealed a significant decline in biodiversity since 1985 in the four marine areas studied; this loss was more pronounced in the Gulf of Cadiz (in Andalusia) and less intense in the northern regions of Spain (Galicia and Asturias). This trend aligns with the global degradation of marine ecosystems and loss of biodiversity caused by human activities. The main drivers behind this decline are economic factors promoting industrial fishing and overexploitation. However, there has been a reduction in the industrial fishing fleet since the 2000s, supported by the European Maritime and Fisheries Fund for transitioning toward sustainable fishing methods. Despite the increase in regulations and the establishment of marine protected areas, these measures have not been effective enough to stop the loss of marine biodiversity. The results highlight the importance of combining administrative measures such as creating marine protected areas and implementing fisheries management regulations with the preservation of cultural services provided by these ecosystems. Successful governance models that involve collaboration between fishermen and decision-makers have been observed in northern Galicia and the Gulf of Cádiz.

Isaiah Lahr, Saghir Alfasly, Peyman Nejat et al.

Searching for similar images in archives of histology and histopathology images is a crucial task that may aid in patient matching for various purposes, ranging from triaging and diagnosis to prognosis and prediction. Whole slide images (WSIs) are highly detailed digital representations of tissue specimens mounted on glass slides. Matching WSI to WSI can serve as the critical method for patient matching. In this paper, we report extensive analysis and validation of four search methods bag of visual words (BoVW), Yottixel, SISH, RetCCL, and some of their potential variants. We analyze their algorithms and structures and assess their performance. For this evaluation, we utilized four internal datasets ($1269$ patients) and three public datasets ($1207$ patients), totaling more than $200,000$ patches from $38$ different classes/subtypes across five primary sites. Certain search engines, for example, BoVW, exhibit notable efficiency and speed but suffer from low accuracy. Conversely, search engines like Yottixel demonstrate efficiency and speed, providing moderately accurate results. Recent proposals, including SISH, display inefficiency and yield inconsistent outcomes, while alternatives like RetCCL prove inadequate in both accuracy and efficiency. Further research is imperative to address the dual aspects of accuracy and minimal storage requirements in histopathological image search.

Siddhant Dutta, Iago Leal de Freitas, Pedro Maciel Xavier et al.

Federated Learning (FL) is a decentralized machine learning approach that has gained attention for its potential to enable collaborative model training across clients while protecting data privacy, making it an attractive solution for the chemical industry. This work aims to provide the chemical engineering community with an accessible introduction to the discipline. Supported by a hands-on tutorial and a comprehensive collection of examples, it explores the application of FL in tasks such as manufacturing optimization, multimodal data integration, and drug discovery while addressing the unique challenges of protecting proprietary information and managing distributed datasets. The tutorial was built using key frameworks such as $\texttt{Flower}$ and $\texttt{TensorFlow Federated}$ and was designed to provide chemical engineers with the right tools to adopt FL in their specific needs. We compare the performance of FL against centralized learning across three different datasets relevant to chemical engineering applications, demonstrating that FL will often maintain or improve classification performance, particularly for complex and heterogeneous data. We conclude with an outlook on the open challenges in federated learning to be tackled and current approaches designed to remediate and improve this framework.