La principal fuente de abastecimiento de agua potable en la mayoría de las regiones administrativas del estado de Jalisco (México) son los acuíferos subterráneos, que en muchos casos son de origen hidrotermal, los cuales se caracterizan por la presencia de compuestos químicos potencialmente nocivos para la salud humana y animal. El área de estudio de este trabajo se ubica en el noreste del estado de Jalisco, que comprende 10 municipios en dos regiones administrativas. El presente estudio tiene como objetivo determinar la tendencia de la concentración de flúor en pozos profundos que abastecen de agua potable a los municipios del área de estudio, a partir de dos evaluaciones realizadas durante los años 2021 y 2022. En los resultados se puede observar una tendencia creciente en la concentración de flúor de la mayoría de los pozos analizados en los periodos estudiados; las mayores concentraciones se reportan en las localidades de Tepatitlán, Arandas, Mexticacán y San Miguel el Alto, así como en los municipios de Valle de Guadalupe y Cañadas de Obregón; el uso de estas fuentes como agua potable representa un mayor riesgo para la salud de la población local, lo que ratifica, asimismo, una tendencia creciente en la concentración de fluoruros en las aguas subterráneas extraíd del área de estudio; una posible causa es la continua disminución en el nivel dinámico de extracción que presentan la mayoría de los pozos evaluados. Es necesario implementar programas y estrategias para garantizar la sostenibilidad de este recurso vital en ésta y otras regiones del país.
Hydraulic engineering, Water supply for domestic and industrial purposes
Las disputas urbanas en torno al agua, aunque han sido un tema constante en ciudades de todo el mundo, solo recientemente han impulsado análisis interdisciplinarios, especialmente desde enfoques teóricos llamados híbridos, como la ecología política urbana, que busca desentrañar la compleja relación entre lo político y el recurso hídrico en ámbitos metropolitanos. Este artículo se centra en analizar las alteraciones en el ciclo hidrosocial de Ecatepec, de la Zona Metropolitana del Valle de México, provocadas por el "huachicoleo" (robo de agua mediante tomas clandestinas) y sus consecuencias políticas. Se indaga si el huachicoleo busca hacer valer los derechos políticos de los ciudadanos carentes del recurso y desmantelar las redes políticas-clientelares ligadas con la precariedad hídrica. A diferencia de otros estudios, este análisis no se limita a las estrategias empleadas por aquellos que ostentan el poder sobre aquellos que carecen de él, sino que se adentra en las complejidades de la interacción. La metodología incluyó trabajo de campo y entrevistas semiestructuradas a vecinos y empleados del organismo operador de aguas del municipio durante los años 2020 y 2021. Se concluye que aunque el huachicoleo no busca primordialmente desafiar las redes de poder que limitan los derechos políticos ha tenido un impacto disruptivo en los flujos de agua y las dinámicas de poder en la región.
Hydraulic engineering, Water supply for domestic and industrial purposes
Rushikesh Ubale, Yasar Mulani, Abhay Suresh
et al.
Multi-period stock-keeping unit (SKU) allocation in supply chains is a combinatorial optimization problem that is both NP-hard and operationally critical, requiring simultaneous attention to profitability, feasibility, and diversity. Quadratic unconstrained binary optimization (QUBO) provides a principled framework for such tasks, yet prior studies often rely on simplified assumptions or omit real operational constraints. This work proposes a hybrid QUBO framework integrating three advances: (i) a quantum-derived similarity kernel, obtained from a variational RX embedding, to discourage redundant SKU selections; (ii) exact per-period capacity enforcement via slack-bit encoding to maintain feasibility; and (iii) execution on a time-multiplexed Coherent Ising Machine (CIM) benchmarked against simulated quantum annealing (SQA) and classical optimization algorithms. The resulting model, with over one million quadratic terms and about 4,100 variables, captures profit, risk, and capacity interactions within a unified formulation. On a dataset of 500 SKUs across eight planning periods, Quanfluence's CIM achieved an energy of minus 2.95 times 10 to the power of 16, producing robust solutions with 288 distinct SKUs (approximately 60 percent of the catalog), 226,813 allocated units, and 12.75 million dollars profit, all with zero capacity violations. These results demonstrate that hybrid quantum-classical QUBO methods can deliver feasible and profitable supply-chain allocations at an industrial scale.
This paper presents HERO (Hierarchical Testing with Rabbit Optimization), a novel black-box adversarial testing framework for evaluating the robustness of deep learning-based Prognostics and Health Management systems in Industrial Cyber-Physical Systems. Leveraging Artificial Rabbit Optimization, HERO generates physically constrained adversarial examples that align with real-world data distributions via global and local perspective. Its generalizability ensures applicability across diverse ICPS scenarios. This study specifically focuses on the Proton Exchange Membrane Fuel Cell system, chosen for its highly dynamic operational conditions, complex degradation mechanisms, and increasing integration into ICPS as a sustainable and efficient energy solution. Experimental results highlight HERO's ability to uncover vulnerabilities in even state-of-the-art PHM models, underscoring the critical need for enhanced robustness in real-world applications. By addressing these challenges, HERO demonstrates its potential to advance more resilient PHM systems across a wide range of ICPS domains.
Accurately predicting the lifespan of critical device components is essential for maintenance planning and production optimization, making it a topic of significant interest in both academia and industry. In this work, we investigate the use of survival analysis for predicting the lifespan of production printheads developed by Canon Production Printing. Specifically, we focus on the application of five techniques to estimate survival probabilities and failure rates: the Kaplan-Meier estimator, Cox proportional hazard model, Weibull accelerated failure time model, random survival forest, and gradient boosting. The resulting estimates are further refined using isotonic regression and subsequently aggregated to determine the expected number of failures. The predictions are then validated against real-world ground truth data across multiple time windows to assess model reliability. Our quantitative evaluation using three performance metrics demonstrates that survival analysis outperforms industry-standard baseline methods for printhead lifespan prediction.
Starting with the pioneering computations of Stokes in 1847, the search of traveling waves in fluid mechanics has always been a fundamental topic, since they can be seen as building blocks to determine the long time dynamics (which is a widely open problem). In this paper we prove the existence of time quasi-periodic traveling wave solutions for three-dimensional pure gravity water waves in finite depth, on flat tori, with an arbitrary number of speeds of propagation. These solutions are global in time, they do not reduce to stationary solutions in any moving reference frame and they are approximately given by finite sums of Stokes waves traveling with rationally independent speeds of propagation. This is a very hard small divisors problem for Partial Differential Equations due to the fact that one deals with a dispersive quasi-linear PDE in higher dimension with a very complicated geometry of the resonances. Our result is the first KAM (Kolmogorov-Arnold-Moser) result for an autonomous, dispersive, quasi-linear PDE in dimension greater than one and it is the first example of global solutions, which do not reduce to steady ones in any moving reference frame, for 3D water waves equations on compact domains.
Understanding the optical properties of various components in water Cherenkov (WC) neutrino experiments is essential for accurate detector characterization, which is critical for precise measurements. Of particular importance is the characterization of surface reflectivity within the Cherenkov volume. We present a methodology for surface reflectivity characterization using a goniometer setup, addressing the challenges associated with measurements in the air and water (or other optical media). Additionally, we discuss the broader implications of Bidirectional Reflectance Distribution Function (BRDF) measurements using a goniometer, including their industrial applications.
Abstract Acid mine drainage (AMD), characterized by its acidity and high content of heavy metals, is a significant global environmental problem that harms human health through its impact on rivers. Therefore, this study aims to identify heavy metals in both surface and underground AMD-polluted karst rivers, focusing on the Zhijin River area which is severely affected by AMD, and assess their health risks to residents. Through the collection of 30 surface water samples and 16 groundwater samples from both wet and dry seasons, the study examines the concentration, sources of pollution, and health implications of six heavy metals (Fe, Mn, Cr, Cd, As, and Hg). The results showed that Fe and Mn levels in surface water were highly polluted during both seasons, especially during the wet season, with Fe levels reaching 20.0 mg/L and Mn levels reaching 1.9 mg/L. Further correlation and principal component analyses revealed that mining activities are the primary contributors to the contamination in this region. Health risk assessments and Monte Carlo simulation, including both deterministic and probabilistic, showed that the noncarcinogenic health risk indices for surface water and groundwater were within acceptable limits for both seasons. However, groundwater poses a higher carcinogenic risk to children, with As levels during the wet season and Cr levels during the dry season warranting close monitoring. Factors such as body weight and intake rate played a crucial role in health risk evaluations. This study underscores the need for further attention to groundwater risk, temporal heterogeneity in the Zhijin River.
Java projects frequently rely on package managers such as Maven to manage complex webs of external dependencies. While these tools streamline development, they also introduce subtle risks to the software supply chain. In this paper, we present Maven-Hijack, a novel attack that exploits the order in which Maven packages dependencies and the way the Java Virtual Machine resolves classes at runtime. By injecting a malicious class with the same fully qualified name as a legitimate one into a dependency that is packaged earlier, an attacker can silently override core application behavior without modifying the main codebase or library names. We demonstrate the real-world feasibility of this attack by compromising the Corona-Warn-App, a widely used open-source COVID-19 contact tracing system, and gaining control over its database connection logic. We evaluate three mitigation strategies, such as sealed JARs, Java Modules, and the Maven Enforcer plugin. Our results show that, while Java Modules offer strong protection, the Maven Enforcer plugin with duplicate class detection provides the most practical and effective defense for current Java projects. These findings highlight the urgent need for improved safeguards in Java's build and dependency management processes to prevent stealthy supply chain attacks.
Supply chain security has become a very important vector to consider when defending against adversary attacks. Due to this, more and more developers are keen on improving their supply chains to make them more robust against future threats. On March 7th, 2024 researchers from the Secure Software Supply Chain Center (S3C2) gathered 14 industry leaders, developers and consumers of the open source ecosystem to discuss the state of supply chain security. The goal of the summit is to share insights between companies and developers alike to foster new collaborations and ideas moving forward. Through this meeting, participants were questions on best practices and thoughts how to improve things for the future. In this paper we summarize the responses and discussions of the summit. The panel questions can be found in the appendix.
Massimiliano Berti, Alberto Maspero, Paolo Ventura
We prove high-frequency modulational instability of small-amplitude Stokes waves in deep water under longitudinal perturbations, providing the first isola of unstable eigenvalues branching off from $\mathtt{i}\frac34$. Unlike the finite depth case this is a degenerate problem and the real part of the unstable eigenvalues has a much smaller size than in finite depth. By a symplectic version of Kato theory we reduce to search the eigenvalues of a $2\times 2$ Hamiltonian and reversible matrix which has eigenvalues with non-zero real part if and only if a certain analytic function is not identically zero. In deep water we prove that the Taylor coefficients up to order three of this function vanish, but not the fourth-order one.
Kelechi G. Kalu, Tanya Singla, Chinenye Okafor
et al.
Many software products are composed of components integrated from other teams or external parties. Each additional link in a software product's supply chain increases the risk of the injection of malicious behavior. To improve supply chain provenance, many cybersecurity frameworks, standards, and regulations recommend the use of software signing. However, recent surveys and measurement studies have found that the adoption rate and quality of software signatures are low. We lack in-depth industry perspectives on the challenges and practices of software signing. To understand software signing in practice, we interviewed 18 experienced security practitioners across 13 organizations. We study the challenges that affect the effective implementation of software signing in practice. We also provide possible impacts of experienced software supply chain failures, security standards, and regulations on software signing adoption. To summarize our findings: (1) We present a refined model of the software supply chain factory model highlighting practitioner's signing practices; (2) We highlight the different challenges-technical, organizational, and human-that hamper software signing implementation; (3) We report that experts disagree on the importance of signing; and (4) We describe how internal and external events affect the adoption of software signing. Our work describes the considerations for adopting software signing as one aspect of the broader goal of improved software supply chain security.
Paula Fraga-Lamas, Tiago M Fernandez-Carames, Oscar Blanco-Novoa
et al.
Shipbuilding companies are upgrading their inner workings in order to create Shipyards 4.0, where the principles of Industry 4.0 are paving the way to further digitalized and optimized processes in an integrated network. Among the different Industry 4.0 technologies, this article focuses on Augmented Reality, whose application in the industrial field has led to the concept of Industrial Augmented Reality (IAR). This article first describes the basics of IAR and then carries out a thorough analysis of the latest IAR systems for industrial and shipbuilding applications. Then, in order to build a practical IAR system for shipyard workers, the main hardware and software solutions are compared. Finally, as a conclusion after reviewing all the aspects related to IAR for shipbuilding, it is proposed an IAR system architecture that combines Cloudlets and Fog Computing, which reduce latency response and accelerate rendering tasks while offloading compute intensive tasks from the Cloud.
Mohamad H. Kazma, Salma M. Elsherif, Ahmad F. Taha
This paper studies the problem of optimal placement of water quality (WQ) sensors in water distribution networks (WDNs), with a focus on chlorine transport, decay, and reaction models. Such models are traditionally used as suitable proxies for WQ. The literature on this topic is inveterate, but has a key limitation: it utilizes simplified single-species decay and reaction models that do not capture WQ transients for nonlinear, multi-species interactions. This results in sensor placements (SP) that do not account for nonlinear WQ dynamics. Furthermore, as WQ simulations are parameterized by hydraulic profiles and demand patterns, the placement of sensors are often hydraulics-dependent. This study produces a greedy algorithm that addresses the two aforementioned limitations. The algorithm is grounded in nonlinear dynamic systems and observability theory, and yields SPs that are submodular and robust to hydraulic changes. Case studies on benchmark water networks are provided. The key findings provide practical recommendations for WDN operators.
Amir Hossein Rezapour, Mohammad Hossein Niksokhan, Hamid Abdolabadi
Optimizing water use in agriculture is crucial for sustainable resource management and increased productivity. Water footprint analysis, which measures the total water used directly and indirectly throughout a product's life cycle, offers valuable insights for improving water management practices. This study investigated the gray and white water footprints of a greenhouses cultivation, bell pepper, under different conditions including misting and pot cover. Evapotranspiration rates were used to calculate water demand under various scenarios. Nitrate (NO3), potassium (K), and total phosphorus (TP) were monitored as key chemical parameters to calculate the gray water. Three scenarios including stringent (S1), normal (S2), and lenient (S3) are established based on water quality standards. The findings revealed that misting and covering pots significantly reduced the gray water footprint compared to non-misting or uncovered scenarios. The total gray water footprint for bell peppers under misting and covered conditions was 2976 m3/ton, while it reached 3968m3/ton under non-misting and uncovered conditions, this represents a reduction of nearly 33% due to the combined effect of misting and pot cover. Importantly, water quality standards also played a significant role, with stricter standards leading to a higher gray water footprint (e.g., a difference of 2655m3/ton between scenarios S1 and S3 under misting and covered conditions).The white water footprint, representing freshwater directly used for cultivation, also varied across different scenarios.
Carlos David Mendoza García, Carmen Julia Navarro Gómez
AbstractUser water demand can be met in intermittent water supply systems, and normally it is met if they have sufficient capacity to store water in their homes to be used in the hours when it is not supplied from the public pipe network. The situation in many intermittent water supply systems is that they have enough water to cover the demand of the users but are supplying it intermittently, and the challenge is to achieve a transfer from intermittent to continuous supply. If the delivery of water is continuous, which supplies drinking water 24/7, it covers not only the basic needs of the user, but all the needs for water they may have. The present study was carried out using smart domestic water meters to obtain consumption information in an intermittently supplied pilot sector. The electromagnetic meters record the water flow through pulses and generate consumption information, which gives us the consumption pattern in volume of water and in the time it is used. During the study, multivariate statistical methods were applied to obtain information from the domestic meters and to identify, as realistically as possible, the consumption of drinking water and the relationship between consumption and specific characteristics of the users and thus anticipate future demand. The results showed a close relationship between consumption and the size of the residence. The most influential factors were the number of bathrooms and the number of occupants. A direct relationship between the pressure and the volume supplied was presumed at the beginning of the study but the opposite was found. Equipment was installed to measure the pressure in the network at the time of establishing the continuous supply of drinking water. The multivariate analysis provides a selection of the most important variables that influence and explain the behavior of the water use and consumption pattern, with the operation determined by the operating agency.
A. Santhana Krishna Kumar, Jolanta Warchol, Jakub Matusik
et al.
Abstract Numerous adsorbents have been introduced to efficiently remove heavy metals and organic dyes from environmental water samples. However, magnetic a porous network aerogels are rarely developed to capture inorganic and organic pollutants from aqueous. We herein fabricated hexagonal boron nitride nanosheets (h-BNNSs)-based on magnetic hybrid aerogels (MHAs) as a lightweight adsorbent for robust uptake of Cr(VI), As(V), methylene blue (MB) and acid orange (AO). The synthetic procedure of poly(ethyleneimine)-modified h-BNNSs (PEI-h-BNNSs) involved thermal poly condensation of melamine and boric acid, pyrolysis of the resultant products which allowed exfoliated by ultra-sonication process further functionalization with PEI-mediated modification of h-BNNSs. The as formed PEI-h-BNNSs allowed in-situ formation of magnetite nanoparticles (Fe3O4 NPs) decorated on their surfaces, which are turned to be PEI-h-BNNSs@Fe3O4 NPs. The lyophilization treatment of PEI-h-BNNSs@Fe3O4 NPs-loaded PVA hydrogels generated the MHAs with large porous structures, diverse and numerous functional groups, good super-paramagnetic and a zero net surface charge. These features enabled the proposed adsorbent (MHAs) to be utilized to efficiently remove Cr(VI), As(V), MB, and AO from an aqueous solution, with maximum adsorption capacity estimated to be 833, 426, 415, 286 mg g−1, respectively. The adsorption kinetics and isotherm data demonstrated that MHAs mediated adsorption of Cr(VI), As(V), MB and AO followed the Freundlich isotherm model and a pseudo-second-order kinetics model. This finding signifies that the MHAs exhibit heterogeneous binding behavior with multilayer chemisorption of Cr(VI), As(V), MB and AO. Subsequently, the practical application were validated by conducting their detoxification of chromium and arsenic in soli-sludge samples.
Control of warm-water supply for dialysis treatment in a hospital environment is typical of safety-critical control problems. In order to guarantee the continuity of warm-water supply satisfying physical specifications for a wide range of operating conditions, it is inevitable to consider the nonlinearity involved in a dynamic model of a warm-water supply system for the control design. In this paper, we propose to incorporate control specifications described by signal temporal logic, which is a temporal logic with semantics over finite-time signals in formal methods, into the so-called Koopman-Model Predictive Control (MPC) as a novel technique of nonlinear MPC based on the Koopman operator framework for nonlinear systems. This enables us to generate a sequence of optimal inputs such that the controlled state of a nonlinear system can satisfy the specifications. The proposal is applied to the temperature regulation of warm-water supply, and its effectiveness is established numerically.