Yequelin Yudith Pariguana-Castillo, Nancy Gladis Quispe-Ccallo, Juan Eduardo Vigo-Rivera
El presente estudio evalúa las isotermas de adsorción de arsénico (III) con la biomasa de los residuos de naranja (pepa, bagazo y cáscara) en condiciones altoandinas. Iniciando con la obtención de la biomasa de los residuos de la naranja y la determinación de As de una muestra de agua subterránea de la zona sur de la ciudad de Juliaca, Perú. Para los ensayos de adsorción se empleó el equipo de prueba de jarras (200 rpm en 2 horas), con un diseño estadístico experimental de 3A x 4B; factor A (residuos de naranja, A1 = cáscara, A2 = pepa y A3 = bagazo) y factor B (masa de residuos B1 = 2 g, B2 = 3 g, B3 = 4 g y B4 = 5 g), a un pH 5, en vasos precipitados de 500 ml. Para determinar la concentración de As (III) se empleó el método de dietilditiocarbamato de plata. Además, se hizo la caracterización de las biomasas mediante el análisis de composición química de espectrometría de fluorescencia de rayos X. Los resultados de caracterización de los bioadsorbentes presentan mayor cantidad de calcio y óxido de calcio. Las mejores biomasas de adsorción se dan con 5 g de biomasa para la pepa (98.10 %) y bagazo (97.89 %), y para la cáscara se presenta con 4 g (97.59 %). Los datos obtenidos se modelaron de acuerdo con las ecuaciones de las isotermas de Langmuir, Freundlich y Temkin. Los datos experimentales mostraron mayor ajuste con el modelo de Langmuir para las tres biomasas para el proceso de adsorción de As (III).
Hydraulic engineering, Water supply for domestic and industrial purposes
Modern society relies on complex supply chains to sustain the flow of goods and services that are essential to daily life. While traditional supply chain theory assumes a clear, hierarchical flow from upstream suppliers to downstream customers, observable real-world transaction networks rarely exhibit this acyclic structure. Instead, detailed inter-firm data reveal that interwoven networks are heavily entangled by cyclic flows. Consequently, without appropriate partitioning of these massive inter-firm networks, the latent flow-hierarchical structures that are central to supply chain concepts remain obscure. To address this analytical challenge, we introduce the flow-Hierarchical Community Network Extraction (f-HiCoNE) framework. By applying combinatorial Hodge decomposition, this approach disentangles the complex inter-firm network by isolating the acyclic gradient flow to quantify the flow-hierarchical parts and partition the graph. By applying f-HiCoNE to a nationwide transaction dataset of approximately 650,000 firms, we successfully extracted functional supply-chain clusters. These clusters demonstrated strong flow-hierarchical organisation, wherein the upstream-downstream positioning of firms was accurately captured by local scalar potentials, revealing distinct geographically localised industrial ecosystems. This study provides a map that helps firms understand their surrounding environment and locate their position within an inter-firm network and opens a new research avenue focused on flow-hierarchy clustering in supply chain analysis.
Birhane Ataklti, Fethangest Woldemariyam Tesema, Ermias Hagos
et al.
ABSTRACT The study area, located in central Tigray, Ethiopia, covers 234.5 km2 and primarily relies on groundwater as its main water source. As water quality concerns grow, detailed studies on groundwater hydrogeochemistry and its suitability for consumption remain insufficient. This study investigates groundwater hydrogeochemistry and evaluates its quality for drinking purposes. In May 2020, 19 water samples were collected from various locations and analyzed for physicochemical parameters, to gain insights into groundwater quality and its influencing factors. Hydrogeochemical classification utilized ionic ratios, Piper and Schoeller diagrams, statistical methods, and water quality assessment via the water quality index (WQI). The findings revealed Ca2+ > Mg2+ > Na+ + K+ and HCO3− > SO42− > Cl− as predominant ions, with Ca–Mg–SO4–HCO3 dominating. Gibbs diagrams and scatter plots revealed water–rock interaction and silicate dissolution as key hydrogeochemical factors, supplemented by ion exchange processes and human activities. Total dissolved solid and electrical conductivity exhibited a strong correlation and were moderately correlated with the major ions. The WQI ranged from 25.6 to 215.94, averaging 69.09, classifying groundwater as excellent (15.8%), good (78.9%), and very poor (5.3%) for drinking use. These insights provide valuable input to maintain the optimal use of groundwater resources in the area.
This study evaluates the techno-economic feasibility of supplying industrial thermal loads with green hydrogen produced via water electrolysis using two pathways off-grid systems powered by co-located wind turbines and battery energy storage (BESS), and on-grid systems that procure electricity directly from the wind farm power node and operate electrolysers in response to real-time locational marginal prices (LMPs).The optimization results show that off-grid wind-to-hydrogen configurations in high-resource regions can achieve levelized costs of hydrogen (LCOH) on the order of \$7/kg, driven by high wind capacity factors and optimized BESS sizing that ensures operational continuity .Similarly in, on-grid, price-responsive operation achieves LCOH values of \$0.5/kg, reflecting sensitivity to electricity market volatility. Overall, the results suggest that Midwest wind-rich regions can support competitive green hydrogen production for industrial heat, with grid-connected electrolysers remaining attractive in locations with frequent low LMP periods. This dual-path analysis provides a transparent framework for industrial hydrogen deployment and highlights practical transition strategies for decarbonizing U.S. manufacturing.
Saeid Ghasemshirazi, Ghazaleh Shirvani, Marziye Ranjbar Tavakoli
et al.
The pharmaceutical supply chain faces escalating cybersecurity challenges threatening patient safety and operational continuity. This paper examines the transformative potential of zero trust architecture for enhancing security and resilience within this critical ecosystem. We explore the challenges posed by data breaches, counterfeiting, and disruptions and introduce the principles of continuous verification, least-privilege access, and data-centric security inherent in zero trust. Real-world case studies illustrate successful implementations. Benefits include heightened security, data protection, and adaptable resilience. As recognized by researchers and industrialists, a reliable drug tracing system is crucial for ensuring drug safety throughout the pharmaceutical production process. One of the most pivotal domains within the pharmaceutical industry and its associated supply chains where zero trust can be effectively implemented is in the management of narcotics, high-health-risk drugs, and abusable substances. By embracing zero trust, the pharmaceutical industry fortifies its supply chain against constantly changing cyber threats, ensuring the trustworthiness of critical medical operations.
Claire Marie Guimond, Tilman Spohn, Svetlana Berdyugina
et al.
Water and land surfaces on a planet interact with gases in the atmosphere and with radiation from the star. These interactions define the environments that prevail on the planet, some of which may be more amenable to prebiotic chemistry, some to the evolution of more complex life. This review article covers (i) the physical conditions that determine the ratio of land to sea on a rocky planet, (ii) how this ratio would affect climatic and biologic processes, and (iii) whether future astronomical observations might constrain this ratio on exoplanets. Water can be delivered in multiple ways to a growing rocky planet -- and although we may not agree on the contribution of different mechanism(s) to Earth's bulk water, hydrated building blocks and nebular ingassing could at least in principle supply several oceans' worth. The water that planets sequester over eons in their solid deep mantles is limited by the water concentration at water saturation of nominally anhydrous mantle minerals, likely less than 2000 ppm of the planet mass. Water is cycled between mantle and surface through outgassing and ingassing mechanisms that, while tightly linked to tectonics, do not necessarily require plate tectonics in every case. The actual water/land ratio at a given time emerges from the balance between the volume of surface water on the one hand, and on the other hand, the shape of the planet (its ocean basin volume) that is carved out by dynamic topography, the petrologic evolution of continents, impact cratering, and other surface-sculpting processes. By leveraging the contrast in reflectance properties of water and land surfaces, spatially resolved 2D maps of Earth-as-an-exoplanet have been retrieved from models using real Earth observations, demonstrating that water/land ratios of rocky exoplanets may be determined from data delivered by large-aperture, high-contrast imaging telescopes in the future.
ABSTRACT The present study was conducted out in the Upper Kebir Sub-basin [North East (NE) Algeria] aiming to evaluate the status and spatial–seasonal variability of water quality for domestic purposes using hydrogeochemical parameters and water quality indices. Surface water samples were collected from 27 selected sites, in 2020–2021 during both the wet and dry seasons and were analysed for 22 parameters. The findings were compared with WHO standards and the water quality indices were calculated. The analysis revealed that the basin was mainly polluted and showed significant seasonal and spatial variations in water quality, considerably influenced by climatic conditions (surface runoff) and human activities (urban sewage and agricultural activities). The results reveal significant spatio-temporal fluctuations and highlight areas likely to be affected by anthropogenic activities.
Our work explores North Korea's 100 MW-th Experimental Light Water Reactor (ELWR) and its potential contributions to the country's nuclear weapons program. Built at the Yongbyon Nuclear Research Center, the ELWR began operations in October 2023 and represents North Korea's first attempts at a light-water reactor using domestically-enriched, ceramic fuel. Our study examines possible configurations for energy, tritium, and tritium-plutonium co-production. Assuming a single-batch core, the ELWR can be used to annually produce 48-82 grams of tritium, which can supply 2-4 new boosted warheads each year, up to a maximum arsenal of 88-150 warheads total. Concurrent production of tritium and weapon-grade plutonium is also possible but requires reprocessing of spent ceramic fuel. These findings underscore how North Korea's nuclear capabilities may be advanced through the ELWR's dual-use potential.
The increasing scale and complexity of global supply chains have led to new challenges spanning various fields, such as supply chain disruptions due to long waiting lines at the ports, material shortages, and inflation. Coupled with the size of supply chains and the availability of vast amounts of data, efforts towards tackling such challenges have led to an increasing interest in applying machine learning methods in many aspects of supply chains. Unlike other solutions, ML techniques, including Random Forest, XGBoost, LightGBM, and Neural Networks, make predictions and approximate optimal solutions faster. This paper presents an automated ML framework to enhance supply chain security by detecting fraudulent activities, predicting maintenance needs, and forecasting material backorders. Using datasets of varying sizes, results show that fraud detection achieves an 88% accuracy rate using sampling methods, machine failure prediction reaches 93.4% accuracy, and material backorder prediction achieves 89.3% accuracy. Hyperparameter tuning significantly improved the performance of these models, with certain supervised techniques like XGBoost and LightGBM reaching up to 100% precision. This research contributes to supply chain security by streamlining data preprocessing, feature selection, model optimization, and inference deployment, addressing critical challenges and boosting operational efficiency.
Agbor Nelson Menti, Egome Regina Wotany, Agyingi Christopher
et al.
Abstract Groundwater and surface water are major sources of water supply to the inhabitants of Bertoua. Hydrogeochemical study conducted in the study area aimed at identifying the processes that control the chemistry of groundwater sources and to examine the quality of the water sources for domestic and agricultural purposes. Fifty water samples were collected from boreholes, open wells, springs, and rivers within the study area in January 2022 (the dry season). The samples were analyzed for physicochemical characteristics including pH, electrical conductivity (EC), total dissolved solids (TDS) and major ions. The water samples were acidic with 94% of pH values less than 6.5. The EC varied from 21 to 776 µS/cm and TDS (8.5–388 mg/l). The low EC and TDS indicate low mineralization and fresh water. The relative abundance of major ions (meg/l) was Ca2+> Mg2+> K+>Na+ for cations and $${\text{H}\text{C}\text{O}}_{3}^{-}$$ HCO 3 - >Cl−>NO3 −>SO4 2− for anions. These major ions concentrations were low and within the WHO guideline values for drinking water. From Piper diagram three water facies were observed; Ca-SO4, Ca-HCO3 and mixed Ca-Mg-Cl. Rock-water interaction, ion exchange, silicate weathering and anthropogenic activities were the processes responsible for the groundwater chemistry with some minor evaporative effects. Based on Sodium Adsorption Ratio and Residual Sodium Bicarbonate all samples fall in the excellent category for agriculture.
Water supply for domestic and industrial purposes, Environmental sciences
The aim of this study was to simulate the runoff in the upstream of Chehlgezi hydrometery station in the Gheshlagh Dam watershed, Kurdistan province using SWAT hydrological model. In addition, the results have been evaluated using selected efficiency criteria in the calibration and validation stages, then the performance of the SWAT model is evaluated in simulating the monthly runoff in upland of Gheshlagh Dam. The input model parameters were optimized using the SWAT-CUP optimizer. The calibration and validation of the model was done using SUFI-2 algorithm during 1989-2016 and 2016-2018 periods, respectively. The sensitivity analysis shows that the SCS runoff curve number, Manning’s "n" value for overland flow, minimum and maximum yearly rate of snowmelt, minimum water depth in the shallow aquifer for "revap" were sensitive parameters in flow simulation. The Nash-Sutcliffe and R2 values were 0.62 and 0.65 in the calibration stage, and 0.61 and 0.68 in validation stage, respectively. The results proved the efficiency of the SWAT in monthly flow simulating. According to the results, 55% of the total rainfall entering the watershed has been converted to evapotranspiration, 30% infiltrated into soil and stored as soil moisture, and 15% converted into surface flow component. The results provide useful information on watershed water balance. Flow simulation in different climatic conditions and land-use scenarios in the future can help to sound water resources management.
Environmental sciences, Water supply for domestic and industrial purposes
Nagalapalli Satish, K. Rajitha, Jagadeesh Anmala
et al.
The dynamics of trophic status estimation of case-2 water bodies on a synoptic mode for frequent intervals is essential for water quality management. The present study attempts to develop trophic status estimation approaches utilizing Landsat-8 and Sentinel-2 images as inputs. The chlorophyll-a concentration, a proxy parameter for trophic status, was estimated using the empirical method, fluorescence line height (FLH) method, and artificial neural network (ANN) approaches using spectral reflectance values as inputs. The outcomes following the empirical approaches revealed the scope of kernel normalized difference vegetation index (kNDVI) (R2 = 0.85; RMSE = 2 μg/l) for estimating the chlorophyll-a concentration using Sentinel-2 images of the Godavari River basin. Though the performance of the FLH method (R2 = 0.91; RMSE = 1.6 μg/l) was superior to kNDVI-based estimation, it lacks the capability to estimate chlorophyll-a concentration above 20 μg/l. Due to the existence of eutrophic regions within the Godavari basin (28%), adopting better approaches like ANN for trophic status estimation is essential. To accomplish the same, the Levenberg–Marquardt algorithm-based ANN was developed using non-redundant bands of Sentinel-2 as inputs, and Sentinel-3 derived chlorophyll-a values as output. The developed architecture was successful in estimating trophic status estimations at all levels.
HIGHLIGHTS
Sentinel-2 performed better than Landsat-8 for trophic status estimations.;
Sentinel-2 derived kNDVI for chlorophyll-a concentration of case-2 water bodies.;
FLH method for estimating chlorophyll-a up to mesotrophic level.;
Prospectus of Sentinel-3 generated chlorophyll-a for estimating the trophic status.;
Sentinel-2 band values as inputs and Sentinel-3 chlorophyll-a values as output of ANN for trophic status estimations.;
River, lake, and water-supply engineering (General), Water supply for domestic and industrial purposes
Atmospheric water harvesting is urgently needed given increasing global water scarcity. Current sorbent-based devices that cycle between water capture and release have low harvesting rates. We envision a radically different multi-material architecture with segregated and simultaneous capture and release. This way, proven fast-release mechanisms that approach theoretical limits can be incorporated; however, no capture mechanism exists to supply liquid adequately for release. Inspired by tree frogs and airplants, our capture approach transports water through a hydrogel membrane ``skin'' into a liquid desiccant. We report an extraordinarily high capture rate of 5.50 $\text{kg}\,\text{m}^{-2}\,\text{d}^{-1}$ at a low humidity of 35%, limited by the convection of air to the device. At higher humidities, we demonstrate up to 16.9 $\text{kg}\,\text{m}^{-2}\,\text{d}^{-1}$, exceeding theoretical limits for release. Simulated performance of a hypothetical one-square-meter device shows that water could be supplied to two to three people in dry environments. This work is a significant step toward providing new resources to water-scarce regions.
The last decades have been characterized by unprecedented technological advances, many of them powered by modern technologies such as Artificial Intelligence (AI) and Machine Learning (ML). The world has become more digitally connected than ever, but we face major challenges. One of the most significant is cybercrime, which has emerged as a global threat to governments, businesses, and civil societies. The pervasiveness of digital technologies combined with a constantly shifting technological foundation has created a complex and powerful playground for cybercriminals, which triggered a surge in demand for intelligent threat detection systems based on machine and deep learning. This paper investigates AI-based cyber threat detection to protect our modern digital ecosystems. The primary focus is on evaluating ML-based classifiers and ensembles for anomaly-based malware detection and network intrusion detection and how to integrate those models in the context of network security, mobile security, and IoT security. The discussion highlights the challenges when deploying and integrating AI-enabled cybersecurity solutions into existing enterprise systems and IT infrastructures, including options to overcome those challenges. Finally, the paper provides future research directions to further increase the security and resilience of our modern digital industries, infrastructures, and ecosystems.
Milad Baghalzadeh Shishehgarkhaneh, Robert C. Moehler, Yihai Fang
et al.
The construction industry in Australia is characterized by its intricate supply chains and vulnerability to myriad risks. As such, effective supply chain risk management (SCRM) becomes imperative. This paper employs different transformer models, and train for Named Entity Recognition (NER) in the context of Australian construction SCRM. Utilizing NER, transformer models identify and classify specific risk-associated entities in news articles, offering a detailed insight into supply chain vulnerabilities. By analysing news articles through different transformer models, we can extract relevant entities and insights related to specific risk taxonomies local (milieu) to the Australian construction landscape. This research emphasises the potential of NLP-driven solutions, like transformer models, in revolutionising SCRM for construction in geo-media specific contexts.
The water-energy nexus encompasses the interdependencies between water and energy resources identifying the existing links between the production and distribution of these resources. Therefore, understanding the water-energy nexus is crucial for developing sustainable and integrated resource management approaches. This paper proposes a decentralized co-optimization model for a micro water-energy nexus system (MWEN), aiming to optimize the combined supply of both resources to end consumers. The approach respects the separate ownership and management of the water and energy sectors while bridging the gap between their optimized operations. An enhanced version of the alternating direction method of multipliers (ADMM) is proposed, the objective-based ADMM (OB-ADMM), which is able to robustly optimize each system independently towards a common objective, only sharing information about the power consumption of water management, providing privacy for each resource provider.
Abstract In this paper, the differential quadrature and the finite difference combined method (DQ-FDM) was applied to solve the three-dimensional Burger’s equation in the determination of the 3D velocity of the flow; so that spatial terms were discretized by the differential quadrature method, and the temporal term was discretized by the finite difference method, and the resulting nonlinear equations were solved using the Newton–Raphson method. All variables were considered as dimensionless in this equation. The solution results were compared with solution results of the two-dimensional equation in the two other numerical methods available in the literature which provided an acceptable accuracy. Also, the results of the mentioned numerical method were compared with those of the fully implicit finite difference method that was solved for larger than or equal viscosities of 0.1. The results showed that by increasing time and viscosity, the longitudinal, depth and transverse velocities were decreased. The occurrence of the upward flow was observed especially in the $$\upsilon$$ υ = 0.05 in the close of the bed, end of the length and width that in the presence of very fine particles of the clay and silt shows suspension of these particles in some spaces. The position of the longitudinal, depth and transverse velocities in the plan for the passing plates through the section depth for different viscosities and times showed that by increasing viscosity and time, the position of the maximum velocities became closer to the middle of the section width. Also, stream lines were plotted in all of sections and then analyzed.
مهدی یزدیان, غلامرضا رخشنده رو, محمدرضا نیکو
et al.
مقدمه: افزایش تقاضای مصرف، رقابت بین ذینفعان مختلف، کاهش منابع آبی و قرارگرفتن در شرایط ورشکستگی آبی، مدیریت منابع آب را در سال های اخیر با چالش های زیادی مواجه کرده است.
روش: مطالعه حاضر چالش موجود بین ذینفعان بهره برداری از منابع مشترک آب، در شرایطی که دچار ورشکستگی آبی شده اند را بررسی میکند. برای حل این مشکل از کاربرد بازی جوجه استفاده شده است. بازی جوجه یک روش کاربردی از تئوری بازی ها در جهت رفع تضاد های بین دو بازیکن میباشد. هدف اصلی در این تحقیق رسیدن به الگوی مناسب رفتاری دو بازیکن با در نظر داشتن دوراندیشی مناسب میباشد. لذا در ابتدا از مدل MODFLOW برای شبیهسازی منبع آب زیرزمینی مشترک در منطقه مورد مطالعه استفاده شده است. سپس این مدل با استفاده از شبکه عصبی به یک مدل بهینهسازی دو هدفه با لحاظ کمینه کردن افت تراز آب زیرزمینی و افزایش سود متصل گردیده است. دوره مدیریتی این تحقیق چهار ساله بوده و کارآیی آن در یکی از زیرحوزه های استان گلستان واقع در شمال ایران مورد ارزیابی قرار گرفته است.
یافتهها و نتیجهگیری: در این تحقیق سطوح کشت بهینه مختلف در حالت های متفاوت از بازی به دست آمده و بر مبنای نتایج حاصل از میزان برداشت آب زیرزمینی، میزان افت دقیق سفره و سود تعیین گردیده است. نتایج نشان میدهد که ذینفعان مختلف در بهره برداری از منبع مشترک آبی با استفاده از دوراندیشی میتوانند از ضررهای راهبردی خود در آینده جلوگیری کنند.
Kazhan Othman Mohammed Salih, Tarik A. Rashid, Dalibor Radovanovic
et al.
There is no doubt that new technology has become one of the crucial parts of most people's lives around the world. By and large, in this era, the Internet and the Internet of Things (IoT) have become the most indispensable parts of our lives. Recently, IoT technologies have been regarded as the most broadly used tools among other technologies. The tools and the facilities of IoT tech-nologies within the marketplace are part of Industry 4.0. The marketplace is too regarded as a new area that can be used with IoT technologies. One of the main purposes of this paper is to highlight using IoT technologies in Industry 4.0, and the Industrial Internet of Things (IIoT) is another feature revised. This paper focuses on the value of the IoT in the industrial domain in general; it reviews the IoT and focuses on its benefits and drawbacks, and presents some of the IoT applications, such as in transportation and healthcare. In addition, the trends and facts that are related to the IoT technologies on the marketplace are reviewed. Finally, the role of IoT in telemedicine and healthcare and the benefits of IoT technologies for COVID-19 are presented as well.