Hasil untuk "River, lake, and water-supply engineering (General)"

GUO Li-jin, CHEN Jian-zheng

[Objective] The time series of reservoir water quality indices,especially dissolved oxygen content, exhibit strong nonlinearity,high complexity,and uncertainty,which lead to insufficient accuracy of single prediction models.This study aims to construct a high-precision hybrid prediction model that integrates time series decomposition,intelligent optimization,and residual correction,thereby significantly improving the prediction accuracy of dissolved oxygen (DO) content and providing reliable support for water environment management and pollution early warning. [Methods] The core procedures of the proposed hybrid prediction model are as follows. 1) Data decomposition and reconstruction. Singular spectrum analysis (SSA) was applied to decompose the dissolved oxygen time series, and the series was reconstructed into trend components, periodic components, and residual components to reduce sequence complexity and highlight features at different frequencies. 2) An improved dung beetle optimizer (IDBO) which integrates piecewise chaotic mapping and opposition-based learning strategies was designed to enhance population diversity and initialization quality. The improved IDBO was used to optimize key hyperparameters of the GRU network, including the number of hidden layer neurons and the initial learning rate. 3) Component prediction and residual correction. The GRU model optimized by IDBO was used to predict the trend component and periodic components separately. A residual series prediction difference correction method (DCM) was proposed. The residual component was first predicted using GRU, and the difference sequence between the predicted values and the observed values was calculated. Variational mode decomposition (VMD) was then applied to the difference sequence to fully extract high-frequency detail information. Each decomposed component was predicted using GRU and aggregated to obtain the predicted difference values. Finally, the predicted differences were compensated into the initial residual prediction to obtain the corrected residual prediction results. 4) Model integration and validation. The prediction results of the three components were aggregated to obtain the final DO prediction values. Measured dissolved oxygen data from Daheiting Reservoir in Tangshan, Hebei Province were used for experiments. The dataset contained 2352 records with a sampling interval of four hours. Root mean square error (RMSE), mean absolute error (MAE), mean relative error (MRE), and the coefficient of determination (R2) were used as evaluation metrics. The proposed model was compared with GRU, SSA-GRU, SSA-DBO-GRU, SSA-IDBO-GRU, and models reported in the literature such as LSTM and PSO-GRU. [Results] The proposed SSA-IDBO-GRU-DCM hybrid model achieved the best performance among all comparative models. The prediction errors were significantly reduced, with an RMSE of 0.580 2 mg/L, an MAE of 0.329 2 mg/L, an MRE of 0.0269, and an R2 of 0.918 8. Ablation experiments confirmed that the proposed IDBO improvement strategies effectively enhanced hyperparameter optimization accuracy. The residual difference correction method (DCM) significantly improved the prediction performance of the residual component and was the key factor contributing to the overall accuracy improvement. These results fully demonstrated the effectiveness and superiority of the “decomposition-optimization-correction” framework. [Conclusion] SSA effectively decouples the complex characteristics of water quality time series. IDBO efficiently and accurately optimizes GRU hyperparameters. The proposed VMD-GRU-based residual difference correction method (DCM) is the key innovation for improving overall prediction accuracy. The proposed model significantly improves the prediction accuracy of dissolved oxygen content and provides an efficient and reliable new approach for reservoir dissolved oxygen prediction. Future work can extend this framework to the prediction of other key water quality parameters such as ammonia nitrogen and total phosphorus, and further explore the integration of natural evolutionary strategies to improve computational efficiency and generalization ability.

Jingyue Li, André Storhaug

With the advancement of Agentic AI, researchers are increasingly leveraging autonomous agents to address challenges in software engineering (SE). However, the large language models (LLMs) that underpin these agents often function as black boxes, making it difficult to justify the superiority of Agentic AI approaches over baselines. Furthermore, missing information in the evaluation design description frequently renders the reproduction of results infeasible. To synthesize current evaluation practices for Agentic AI in SE, this study analyzes 18 papers on the topic, published or accepted by ICSE 2026, ICSE 2025, FSE 2025, ASE 2025, and ISSTA 2025. The analysis identifies prevailing approaches and their limitations in evaluating Agentic AI for SE, both in current research and potential future studies. To address these shortcomings, this position paper proposes a set of guidelines and recommendations designed to empower reproducible, explainable, and effective evaluations of Agentic AI in software engineering. In particular, we recommend that Agentic AI researchers make their Thought-Action-Result (TAR) trajectories and LLM interaction data, or summarized versions of these artifacts, publicly accessible. Doing so will enable subsequent studies to more effectively analyze the strengths and weaknesses of different Agentic AI approaches. To demonstrate the feasibility of such comparisons, we present a proof-of-concept case study that illustrates how TAR trajectories can support systematic analysis across approaches.

Michelle Döring, Jannes Malanowski, Stefan Neubert

Recently, the River Method was introduced as novel refinement of the Split Cycle voting rule. The decision-making process of River is closely related to the well established Ranked Pairs Method. Both methods consider a margin graph computed from the voters' preferences and eliminate majority cycles in that graph to choose a winner. As ties can occur in the margin graph, a tiebreaker is required along with the preferences. While such a tiebreaker makes the computation efficient, it compromises the fundamental property of neutrality: the voting rule should not favor alternatives in advance. One way to reintroduce neutrality is to use Parallel-Universe Tiebreaking (PUT), where each alternative is a winner if it wins according to any possible tiebreaker. Unfortunately, computing the winners selected by Ranked Pairs with PUT is NP-complete. Given the similarity of River to Ranked Pairs, one might expect River to suffer from the same complexity. Surprisingly, we show the opposite: We present a polynomial-time algorithm for computing River winners with PUT, highlighting significant structural advantages of River over Ranked Pairs. Our Fused-Universe (FUN) algorithm simulates River for every possible tiebreaking in one pass. From the resulting FUN diagram one can then directly read off both the set of winners and, for each winner, a certificate that explains how this alternative dominates the others.

Qiaolin Qin, Ronnie de Souza Santos, Rodrigo Spinola

Context. The rise of generative AI (GenAI) tools like ChatGPT and GitHub Copilot has transformed how software is learned and written. In software engineering (SE) education, these tools offer new opportunities for support, but also raise concerns about over-reliance, ethical use, and impacts on learning. Objective. This study investigates how undergraduate SE students use GenAI tools, focusing on the benefits, challenges, ethical concerns, and instructional expectations that shape their experiences. Method. We conducted a survey with 130 undergraduate students from two universities. The survey combined structured Likert-scale items and open-ended questions to investigate five dimensions: usage context, perceived benefits, challenges, ethical and instructional perceptions. Results. Students most often use GenAI for incremental learning and advanced implementation, reporting benefits such as brainstorming support and confidence-building. At the same time, they face challenges including unclear rationales and difficulty adapting outputs. Students highlight ethical concerns around fairness and misconduct, and call for clearer instructional guidance. Conclusion. GenAI is reshaping SE education in nuanced ways. Our findings underscore the need for scaffolding, ethical policies, and adaptive instructional strategies to ensure that GenAI supports equitable and effective learning.

Mohammed Latif Siddiq, Arvin Islam-Gomes, Natalie Sekerak et al.

Reproducibility is a cornerstone of scientific progress, yet its state in large language model (LLM)-based software engineering (SE) research remains poorly understood. This paper presents the first large-scale, empirical study of reproducibility practices in LLM-for-SE research. We systematically mined and analyzed 640 papers published between 2017 and 2025 across premier software engineering, machine learning, and natural language processing venues, extracting structured metadata from publications, repositories, and documentation. Guided by four research questions, we examine (i) the prevalence of reproducibility smells, (ii) how reproducibility has evolved over time, (iii) whether artifact evaluation badges reliably reflect reproducibility quality, and (iv) how publication venues influence transparency practices. Using a taxonomy of seven smell categories: Code and Execution, Data, Documentation, Environment and Tooling, Versioning, Model, and Access and Legal, we manually annotated all papers and associated artifacts. Our analysis reveals persistent gaps in artifact availability, environment specification, versioning rigor, and documentation clarity, despite modest improvements in recent years and increased adoption of artifact evaluation processes at top SE venues. Notably, we find that badges often signal artifact presence but do not consistently guarantee execution fidelity or long-term reproducibility. Motivated by these findings, we provide actionable recommendations to mitigate reproducibility smells and introduce a Reproducibility Maturity Model (RMM) to move beyond binary artifact certification toward multi-dimensional, progressive evaluation of reproducibility rigor.

Wenfei Liu, Xiaoling Su, Gengxi Zhang et al.

Abstract Projection of future dry‐wet evolution is essential for making long‐term regional climate adaptation strategies. In this study, the projection of regional dry‐wet evolution is conducted with a careful consideration on uncertainty attribution. The Evaporative Stress Index (ESI) is adopted due to its physical mechanisms for taking evaporative demand into account. A three‐dimensional framework is constructed for quantifying the range of uncertainty of the ESI in which six Global Climate Models (GCMs) in Coupled Model Intercomparison Project 6 (CMIP6), three latest Shared Socioeconomic Pathway (SSP) scenarios, and six Potential Evapotranspiration Models (PETMs) are used. The framework provides 108 different ESI simulations for two future periods: 2041–2070 (mid‐future) and 2071–2100 (far‐future). An agglomerative‐hierarchical clustering method and the Analysis of Variance methodology are employed to evaluate the relative contribution of each uncertainty source. The region of Northwest China is used as a case to illustrate the effectiveness of the proposed framework. The results indicate that most of the parts in Northwest China would experience dry mitigation in both mid‐future and far‐future periods. Projected ESI by PM[CO2] model and ACCESS‐ESM1‐5 suggestes a higher tendency for dry mitigation. Hierarchical clustering analysis of the 108 sets of ESI predictions indicate that most clusters are dominated by GCM forcing, and one cluster is dominated by the SSP1‐2.6 scenario. Furthermore, GCM‐related uncertainty′s relative contribution to the total projection uncertainty is the greatest, with an average value of 49.98% in the far future (i.e., 2071–2100 s). Although the contribution of SSP uncertainty is smaller (21.68%−28.43%), it increases in far‐future over mid‐future. The case study indicates that the large scale ensemble prediction of ESI and its uncertainty analysis provide a more comprehensive data set on climate change and help water managers to gain in‐depth understanding of future trends of drought projections.

Rudrajit Choudhuri, Dylan Liu, Igor Steinmacher et al.

Conversational Generative AI (convo-genAI) is revolutionizing Software Engineering (SE) as engineers and academics embrace this technology in their work. However, there is a gap in understanding the current potential and pitfalls of this technology, specifically in supporting students in SE tasks. In this work, we evaluate through a between-subjects study (N=22) the effectiveness of ChatGPT, a convo-genAI platform, in assisting students in SE tasks. Our study did not find statistical differences in participants' productivity or self-efficacy when using ChatGPT as compared to traditional resources, but we found significantly increased frustration levels. Our study also revealed 5 distinct faults arising from violations of Human-AI interaction guidelines, which led to 7 different (negative) consequences on participants.

Tiina Nõges, Sirje Vilbaste, Mark J. McCarthy et al.

We analysed long-term (1992–2020) changes in fertiliser use, wastewater treatment, and river water nutrient status in Estonia (N-E Europe) in the context of changing socio-economic situations and legislation. We hypothesised that improved regulation of fertiliser usage and wastewater treatment are reflected as declining riverine nutrient concentrations, with the largest relative improvements occurring in catchments with initially high proportions of point source loading. We analysed nutrient dynamics in 16 rivers differing by catchment land use, population and livestock densities. Data on fertiliser use and wastewater treatment originated from the Statistics Estonia database, and riverine nutrient concentrations from the State Environmental Monitoring Database. We clustered the rivers by their catchment properties and analysed trends in their nutrient status. Point source nutrient loading reductions explained most of the decline in riverine nutrient concentrations, whereas application of mineral fertilisers has increased, hindering efforts to reach water quality and nutrient load targets set by the EU Water Framework Directive and the Baltic Sea Action Plan. Highest nitrogen concentrations and strongest increasing trends were found in rivers within the Nitrate Vulnerable Zone, indicating violation of the EU Nitrates Directive. To comply with these directives, resource managers must address non-point source nutrient loading from river watersheds. HIGHLIGHTS Drop in point source loading explained the decline in riverine nitrogen (N) and phosphorus (P) since 1994.; Fertiliser and wastewater management measures failed short to meet the water quality and nutrient load targets set by the EU Water Framework Directive.; Highest N concentrations and strongest increasing trends were found in rivers within the nitrate vulnerable zone violating the EU Nitrates Directive.;

Jonas Olsson, Anita Verpe Dyrrdal, Erika Médus et al.

Short-duration rainfall extremes are associated with a range of societal hazards, notably pluvial flooding but in addition, e.g., erosion-driven nutrient transport and point-source contamination. Fundamental for all analysis, modelling and risk assessment related to short-duration rainfall extremes is the access to and analysis of high-resolution observations. In this study, sub-daily rainfall observations from 543 meteorological stations in the Nordic–Baltic region were collected, quality-controlled and consistently analyzed in terms of records, return levels, geographical and climatic dependencies, time of occurrence of maxima and trends. The results reflect the highly heterogeneous rainfall climate in the region, with longitudinal and latitudinal gradients as well as local variability, and overall agree with previous national investigations. Trend analyses in Norway and Denmark indicated predominantly positive trends in the period 1980–2018, in line with previous investigations. Gridded data sets with estimated return levels and dates of occurrence (of annual maxima) are provided open access. We encourage further efforts towards international exchange of sub-daily rainfall observations as well as consistent regional analyses in order to attain the best possible knowledge on which rainfall extremes are to be expected in present as well as future climates. HIGHLIGHTS Sub-daily annual rainfall maxima have been collected from national observation networks in the Nordic–Baltic region, including a total of 543 stations.; A consistent regional analysis of records, return levels, geographical and climatic dependencies, time of occurrence of maxima and trends is performed.; Gridded data sets with return levels and time of occurrence are provided open access.;

Sasun Hambardzumyan, Abhinav Tuli, Levon Ghukasyan et al.

Traditional data lakes provide critical data infrastructure for analytical workloads by enabling time travel, running SQL queries, ingesting data with ACID transactions, and visualizing petabyte-scale datasets on cloud storage. They allow organizations to break down data silos, unlock data-driven decision-making, improve operational efficiency, and reduce costs. However, as deep learning usage increases, traditional data lakes are not well-designed for applications such as natural language processing (NLP), audio processing, computer vision, and applications involving non-tabular datasets. This paper presents Deep Lake, an open-source lakehouse for deep learning applications developed at Activeloop. Deep Lake maintains the benefits of a vanilla data lake with one key difference: it stores complex data, such as images, videos, annotations, as well as tabular data, in the form of tensors and rapidly streams the data over the network to (a) Tensor Query Language, (b) in-browser visualization engine, or (c) deep learning frameworks without sacrificing GPU utilization. Datasets stored in Deep Lake can be accessed from PyTorch, TensorFlow, JAX, and integrate with numerous MLOps tools.

Firuz Kamalov, Ho-Hon Leung

The rapid advances in technology over the last decade have significantly altered the nature of engineering knowledge and skills required in the modern industries. In response to the changing professional requirements, engineering institutions have updated their curriculum and pedagogical practices. However, most of the changes in the curriculum have been focused on the core engineering courses without much consideration for the auxiliary courses in mathematics and sciences. In this paper, we aim to propose a new, augmented mathematics curriculum aimed at meeting the requirements of the modern, technology-based engineering workplace. The proposed updates require minimal resources and can be seamlessly integrated into the existing curriculum.

A. Darwich, F. Aprile

This case study was conducted in Tupé lake a Ria black water lake in the Negro River basin, Central Amazonian, with historical data from 2001 to 2018. The aim was to propose a unidirectional laminar flow model, relating it to the limnological data, in special temperature and dissolved oxygen in the water column. Climatological, geomorphological and hydrological data as well as general environmental factors were included for the construction and study of the water circulation model. The Tupé lake (3º01'33.5 ”- 3º02'47.8” S; 60º14'57.5 ”- 60º16'1.2” W) is supplied in most of the time by waters coming from forest streams. As a result, the lake has specific properties of circulation and flow of nutrients, being considered a meromictic lake with permanent stratification. Although the statistical test suggests that there is no difference in the average density between the vertical layers of water, the observed pattern confirms exactly the opposite, reinforcing the existence of permanent stratification due to uneven mass densities between the epilimnion and hypolimnion. The continuous and almost permanent unidirectional laminar flow from the forest streams guarantees the state of non-conservation of energy at the bottom of the lake, with constant renewal and variation of this behavior. A laminar flow model was established for the lake, highlighting the partial circulation of water in the epilimnion. The condition of permanent stratification is not common to be observed. Thus, with these results, a model can be established to help identify this behavior in other Ria lakes in the Amazon region.

Eldar Alisherov

The Kyrgyz Republic possesses 2 % of power resources of the Central Asia and 30 % of hydropower resources and only oone-tenth usedly. The minor and medium hydroelectric power stations would allow electrifying more widely the areas located far away from general power supply systems, contributing development of animal husbandry and mountain agriculture, small industrial and social objects, especially in remote areas. Along with that they could bring considerable contribution to the development of power supply sources of the Kyrgyz Republic. Implementation of development prospects of minor and medium water-power engineering requires an effective utilization of hydropower resources of the small rivers in Kyrgyzstan, attraction of investors for construction, reconstruction and restoration of the written off minor and medium hydroelectric power stations.

C. Wardropper, A. Mase, Jiangxiao Qiu et al.

Abstract Understanding public perceptions of the importance of ecosystem services (ES) is crucial for the development and communication of sustainable management and policies. Yet public perspectives on ES and their sociocultural and geographic patterns are not well understood. This study asks: Which ES are perceived as more or less important by the general public?; Which ES are considered most similar when the public are asked to evaluate the importance of specific water, agricultural and natural resources ES?; And, what individual and geographic factors are associated with perceived importance of different ES? We conducted a survey of residents in an urban and agricultural watershed in the U.S. Upper Midwest (n = 1136). This study asked respondents about a wider range of ES than is typical, and examines how ecological worldviews influence the perceived importance of ES. Respondents rated regional provision of drinking and surface water quality, clean lakes and rivers for wildlife, and a reliable supply of drinking and surface water most important. Those with a stronger ecological worldview tended to rate natural areas and processes as more important and agricultural products as less important than respondents with a more anthropocentric worldview. Perceived importance of various ES was also predicted by other individual-level factors relating to livelihood, outdoor recreation, and proximity to lakes, forests and agriculture. For example, respondents with livelihoods dependent on agriculture rated agricultural products and rural character highly. These findings bolster the case for more context-specific assessments of public importance ratings for environmental benefits to inform planning and management.

Melencio C. Jalova Jr., Abdulnassar D. Lomantong, Lorelie G. Calibo et al.

This study was carried out to assess potential heavy metal contamination in the muscles of three commonly consumed fish species in Lake Lanao and to determine associated health risks that may endanger local community residents who consume these fishes. The concentrations of Arsenic (As), Cadmium (Cd), Chromium (Cr), Mercury (Hg) and Lead (Pb) were assessed in the muscles of Glossogobius giurus, Oreochromis niloticus and Giuris margaritacea and were measured via atomic absorption spectrophotometry. Statistical analysis showed that heavy metal concentrations in the muscles of the three fish species collected from the two different locations in the lake are not significantly different (P>0.05) except for O. niloticus. Recorded amounts of the five heavy metals in the present study were lower than the maximum and standard levels except for Pb. Four (As, Cd, Cr, and Hg) among the five pollutants of concern obtained Non-carcinogenic Hazard Quotient (NHQ) values that are less than one, while NHQ values for Pb range between 815.6 and 1396.03 for all fish samples obtained from both sampling stations. The continued consumption of G. giuris, O. niloticus and G. margaritacea collected from Marawi City and Tugaya, Lanao del Sur posed a high likelihood for local residents to contract adverse non-carcinogenic impacts, specifically by Pb. This does not necessarily hold true for the whole of Lake Lanao however, due to limitations related to representativeness. Steps should be taken to manage the risks posed by the consumption of G. giuris, O. niloticus, and G. margaritacea from Marawi City and Tugaya, Lanao del Sur, especially in consideration of vulnerable groups such as children, pregnant women and their developing fetus, and people with existing health conditions. 2 Jalova Jr. et al. 2021 The Israeli Journal of Aquaculture – Bamidgeh • IJA.73.2021.1426167 Introduction Lakes are essential to human well-being. They provide a wide range of ecosystem services including flood control, biodiversity, climate change mitigation, river flow regulation, hydropower supply, as well as water purification and storage. In recent decades, emerging global threats closely linked to anthropogenic pressures such as land-use intensification, nutrient enrichment, hydrological modification, aquaculture and fisheries, climate change, and water depletion have been driving forces of changes in lakes and reservoirs. These pressures have caused habitat loss and degradation, eutrophication and pollution, food web alteration, and physical degradation in many inland bodies. Another emerging threat to lake sustainability is the ever-increasing number of emerging contaminants brought about by technological advances which add more waste products and chemicals into the environment. These contaminants are new compounds with little environmental regulation and whose impacts are still not completely clear. They range from personal care products and illicit drugs to endocrine disrupting compounds, which can pose a serious threat to both aquatic ecosystems and human health. Additionally, the presence of micro-plastics and anti-microbial resistance in lakes are increasing because of the widespread use of these products. Agriculture, aquaculture, and livelihood development caused a higher level of antimicrobial resistance in surface water systems, consequently, causing health problems to water users (Ho and Goethals, 2019). Fishing, being one of the most important ecosystem services provided by inland aquatic ecosystems, contributes significantly in meeting the basic human need for food. With the increasing world population, fish consumption meets the demand for food among lakeshore communities while also serving as a substitute for beef, pork and another animal protein (Béné et al. 2015). Lake Lanao is the largest lake in Mindanao with a total area of 347 sq km and is considered as one of the 17 ancient lakes on earth. Known as a pre-historic and socioculturally significant lake, Lake Lanao shelters a great biodiversity of aquatic life forms. Through the years however, the lake has not been spared from various anthropogenic activities associated with the growing demand of the lake’s resources—the water for domestic and agricultural use and hydro-power generation, contact recreation, boating, laundry and bathing, ritual use, water sports, fishes for domestic consumption and livelihood—among other numerous related uses. (Angagao et al., 2017). Heavy metals are metallic chemical elements that occur as natural constituents of the earth’s crust. They are toxic even at low concentrations and are considered as persistent environmental pollutants since they cannot be degraded or destroyed. As trace elements, some heavy metals are essential to maintain the metabolism of the human body. However, these can lead to poisoning at higher concentrations. Their toxicity depends on several factors including the dose, route of exposure, chemical species, as well as the age, gender, genetics, and nutritional status of exposed individuals (Tchounwou et al., 2012). The bio-toxic effects associated with heavy metals poisoning (cadmium, lead, arsenic, mercury, zinc, copper and aluminum) have the following general signs: gastrointestinal (GI) disorders, diarrhea, stomatitis, tremor, hemoglobinuria (condition causing a rust–red color to stool), ataxia, paralysis, vomiting and convulsion, depression, and pneumonia when volatile vapors and fumes are inhaled (Duruibe et al., 2007; McCluggage, 1991). The nature of effects could be toxic (acute, chronic or sub-chronic), neurotoxic, carcinogenic, mutagenic or teratogenic. The dangers associated with human consumption of potentially contaminated fishes could be averted with the application of scientific inquiries that are appropriate and timely. This study sought to assess potential risks to public health, the results of which will also serve to inform and forewarn the Meranao lakeshore communities and their respective local governments about the possible contamination of fishery resources in Lake Lanao. The study was limited on the determination of heavy metal concentrations in three commonly consumed fishes sourced in Lake Lanao. The findings were compared against the recommended standard and maximum levels allowed in fishes and other foods. Furthermore, health risks were evaluated only in consideration of human consumption of fishes which are potentially contaminated with As, Cd, Cr, Hg, and Pb. Assessment of heavy metals 3 The Israeli Journal of Aquaculture – Bamidgeh • IJA.73.2021.1426167 Materials and Methods Study site The study was conducted in two sampling sites—first of which is the lakeshore of Marawi City an urban community and known as the center of trade, commerce, and industry in the province of Lanao del Sur (Figure 1). The first sampling site/station is located proximate to the most affected area during the Marawi armed conflict that occurred in 1997 instigated by ISIS-inspired rebels. This point is also located nearest to the source or headwaters of the Agus river. The second sampling site/station is located in the lakeshore of the Municipality of Tugaya, which is about 26.3 km from Marawi City. Tugaya is known for manufacturing traditional Maranao arts and crafts, such as back-strap loom weaving, tapestry weaving, and other kinds of handmade textile manufacture; foundry casting of various forms of brass or bronze vessels, instruments, and decorative items; wood-carving and mother-of-pearl inlay work; metalwork and silverand gold-smiting. Collection of samples Commonly consumed fish species (10-15 individuals of each species) namely, Kadurog (Glossobius giuris; average weight 0.13 ± 0.07 kg and average length 192.0 ± 44.2 cm), Nile tilapia (Oreochromis niloticus; 0.30 ± 0.17 kg and 195.6 ± 47.1 cm) and Katolong (Giuris margaritacea; 0.034 ± 0.011 kg and 112.4 ± 12.6 cm) were collected from three sub-stations located in each of the two sampling stations. Fish samples were transported to the laboratory in boxes filled with ice. The mean length and weight of the fish were recorded. All fish samples were kept at low temperature until analysis (Öztürk et al., 2009). The fish samples were thoroughly washed with distilled water to remove any adhering contaminants, and they were put on a dissection tray and thawed at room temperature. They were dissected using a knife and forceps, and the intestine, guts and bones were removed. Muscle tissues of fish (dorsal and ventral muscle) were used in this study since it is the most edible part of the fish (Listrat et al., 2016). All the samples were immediately transported to a competent and duly-accredited laboratory for the processing of the samples and determination of heavy metals. Sample preparation Muscle portion was put in a clean Petri dish and dried in an oven at 120 ± 2oC for 48 hours through which a constant weight was obtained. Before acid digestion, the dried muscle was pulverized to a fine powder using a mortar and pestle and stored in a freezer (-4oC) prior to analysis. One gram of each sample (powder) was mixed with 20 ml distilled water and diluted using HNO3 (55%) and HClO4 (70%) mixed concentration in 100 ml Erlenmeyer flask on a heating digester (200 to 250°C) until a clear solution was obtained and the volume was reduced to approximately 15 ml. This solution was then filtered using Whatman no. 1 filter paper into the volumetric flask and diluted to 50 ml. The prepared samples were analyzed using Atomic Absorption Spectrophotometer (Perkin Elmer Inc.). Data analysis and comparison Descriptive statistics such as average and standard deviation values were calculated. Finally, the mean concentration of heavy metals found in the different fish samples were compared to the recommended accepted value provided by FAO/WHO to check if the present value of heavy metals are within the standard and tolerable limits or not. Health risk assessment The health risks associated with ingesting A

Worlanyo Kwadjo Siabi, Emmanuel Degraft-Johnson Owusu-Ansah, Helen Michelle Korkor Essandoh et al.

Nearly 6494 boreholes with iron (Fe) and manganese (Mn) concentrations above permissible limits of 0.3 mg/L and 0.4 mg/L respectively in Ghana have been abandoned because of ineffective water treatment solutions. Activated carbon prepared from teak (Tectona grandis) and shea (Vitellaria paradoxa) charcoal (ACM), of effective grain sizes 0.075–0.2 mm and 0.2–2.0 mm was found to achieve 92.5–100% Fe and Mn removal in batch tests. The experiments, which were repeated for natural groundwater with a low flow similar to boreholes simulated with handpumps and limited mechanized water systems achieved similar Fe and Mn adsorption levels. Data on Fe and Mn adsorption for varying ACM mass and grain sizes, using fixed columns in continuous flow tests were fitted to Adam-Bohart, Thomas and Yoon-Nelson adsorption models to generate data for improvement in water treatment designs. The objective of this modelling process is to develop a prediction mechanism for ACM mass and grain size needed for the design of Fe and Mn removal plants for groundwater with various characteristics. Adsorption constants obtained for Yoon-Nelson; 0.3095 and Adams-Bohart; 0.07335 at R2 values of 0.9728 and 0.9841 respectively are appropriate for generating ACM mass needed, when the target contaminant is Fe and Mn

Jihyeok Park, Seungmin An, Dongjun Youn et al.

Modern programming follows the continuous integration (CI) and continuous deployment (CD) approach rather than the traditional waterfall model. Even the development of modern programming languages uses the CI/CD approach to swiftly provide new language features and to adapt to new development environments. Unlike in the conventional approach, in the modern CI/CD approach, a language specification is no more the oracle of the language semantics because both the specification and its implementations can co-evolve. In this setting, both the specification and implementations may have bugs, and guaranteeing their correctness is non-trivial. In this paper, we propose a novel N+1-version differential testing to resolve the problem. Unlike the traditional differential testing, our approach consists of three steps: 1) to automatically synthesize programs guided by the syntax and semantics from a given language specification, 2) to generate conformance tests by injecting assertions to the synthesized programs to check their final program states, 3) to detect bugs in the specification and implementations via executing the conformance tests on multiple implementations, and 4) to localize bugs on the specification using statistical information. We actualize our approach for the JavaScript programming language via JEST, which performs N+1-version differential testing for modern JavaScript engines and ECMAScript, the language specification describing the syntax and semantics of JavaScript in a natural language. We evaluated JEST with four JavaScript engines that support all modern JavaScript language features and the latest version of ECMAScript (ES11, 2020). JEST automatically synthesized 1,700 programs that covered 97.78% of syntax and 87.70% of semantics from ES11. Using the assertion-injection, it detected 44 engine bugs in four engines and 27 specification bugs in ES11.

Davide Vanzo, Samuel Peter, Lukas Vonwiller et al.

Modelling river physical processes is of critical importance for flood protection, river management and restoration of riverine environments. Developments in algorithms and computational power have led to a wider spread of river simulation tools. However, the use of two-dimensional models can still be hindered by complexity in the setup and the high computational costs. Here we present the freeware BASEMENT version 3, a flexible tool for two-dimensional river simulations that bundles solvers for hydrodynamic, morphodynamic and scalar advection-diffusion processes. BASEMENT leverages different computational platforms (multi-core CPUs and graphics processing units GPUs) to enable the simulation of large domains and long-term river processes. The adoption of a fully costless worflow and a light GUI facilitate its broad utilization. We test its robustness and efficiency in a selection of benchmarks. Results confirm that BASEMENT could be an efficient and versatile tool for research, engineering practice and education in river modelling.

David Reynolds, Nicholas Dacre

As Engineering Education Research (EER) develops as a discipline it is necessary for EER scholars to contribute to the development of learning theory rather than simply being informed by it. It has been suggested that to do this effectively will require partnerships between Engineering scholars and psychologists, education researchers, including other social scientists. The formation of such partnerships is particularly important when considering the introduction of business-related skills into engineering curriculum designed to prepare 21st Century Engineering Students for workplace challenges. In order to encourage scholars beyond Engineering to engage with EER, it is necessary to provide an introduction to the complexities of EER. With this aim in mind, this paper provides an outline review of what is considered rigorous research from an EER perspective as well as highlighting some of the core methodological traditions of EER. The paper aims to facilitate further discussion between EER scholars and researchers from other disciplines, ultimately leading to future collaboration on innovative and rigorous EER.