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Copyright of Engineering Mechanics / Gongcheng Lixue is the property of Engineering Mechanics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents the application of the Comparison of Flow Pattern Distribution (CFPD) method for detecting water leakage and understanding consumption behaviors at both microscale and macroscale. Implemented at Lille University's Scientific Campus, this research utilizes Automated Meter Reading (AMR) to collect real-time water supply and consumption data. The research successfully identified several significant leak events by analyzing this data with the CFPD method on weekly and daily scales. The analysis of the data resulted in identifying the seasonal and operational consumption patterns across different periods of the year. The findings highlight the effectiveness of the CFPD method in achieving water conservation and operational efficiency, consequently contributing to the UN Sustainable Development Goal (SDG) 6 concerning clean water and sanitation. [ABSTRACT FROM AUTHOR]

When water pipelines undergo scenarios such as valve closure or leakage, they often operate in a gas-liquid two-phase flow state, which can easily cause abnormal pressure fluctuations, exacerbating the destructiveness of water hammer and affecting the safe operation of the pipeline. To study the problem of abnormal fluctuations in complex water pipelines, this paper establishes a transient flow model for gas-containing pipelines, considering unsteady friction, and solves it using the discrete gas cavity model (DGCM). It also studies the influence of factors such as valve closing time, initial flow rate, gas content rate, leakage location, and leakage amount on the end-of-valve pressure. Furthermore, it locates the leakage position using a genetic algorithm-backpropagation neural network (GA-BP neural network). The results show that increasing the valve closing time, increasing the gas content rate, decreasing the initial flow rate, and increasing the leakage amount all reduce the pressure peak inside the pipeline. The model constructed using the GA-BP neural network effectively predicts the leakage location with a mean absolute percentage error (MAPE) of 9.26%. The research results provide a reference for studies related to the safety protection of water conveyance projects. [ABSTRACT FROM AUTHOR]

Virtual Prototypes (VPs) at the Electronic System Level (ESL) are being increasingly adopted by the semiconductor industry and play an important role in modernizing the System-on-Chips (SoCs) design flow to raise design productivity and reduce time-to-market constraints. Due to their early availability and significantly faster simulation speed in comparison to Register Transfer Level (RTL) designs, VPs are used as reference models for lower levels of abstraction. Leveraging VPs and extending their use cases for early security validation are shown as a promising direction. As the cost of fixing any security flaws increases with the stage of development, VP-based security validation can significantly avoid costly iterations. In this article, we present a novel VP-based dynamic information flow analysis approach at the ESL, consisting of three main phases which are runtime behavior extraction (in terms of transactions), transactions transformation, and security validation. The proposed approach empowers designers to validate the information flow policies of a given VP-based SoC against the most occurring security threat models which are information leakage (confidentiality) and unauthorized access to data in a memory (integrity). Experimental results including an extensive set of standard benchmarks and two real-world VP-based SoCs demonstrate the scalability and applicability of the proposed approach. [ABSTRACT FROM AUTHOR]

This study determined how temperature affected the early growth of seedlings of Calobota sericea (Thunb.) Boatwr. & B.-E.van Wyk. One-month-old C. sericea seedlings were grown at constant temperatures of 2.5, 5, 10 and 20 °C for 30 days. After 30 days the plants were removed and shoot length, root length, stem thickness, number of leaves, middle leaflet length, leaf width, petiole length, shoot fresh and dry mass, and cell membrane stability through electrolyte leakage from the leaves, and shoot water content were measured. Results showed that the optimum temperature for C. sericea seedling growth was approximately 10 °C. Significant seedling mortality was observed at 20 °C, while no mortality was observed between 2.5 and 5 °C, and less than 4% of seedlings died at 10 °C. The majority of measured morphological variables in this study increased significantly from 2.5 °C and 5 °C, reaching a maximum at 10 °C before decreasing significantly at 20 °C. Electrolyte leakage from leaves was significantly more at 2.5 °C and at 20 °C, suggesting that seedlings were more stressed at these temperatures. In conclusion, even though C. sericea has a wide optimum germination temperature range, early seedling growth requires a narrow temperature range for optimum growth and development. [ABSTRACT FROM AUTHOR]

The cutting operation significantly affects the shelf-life of fresh-cut produce due to the mechanical damage impacting molecular, physiological, and sensory responses, depending on tissue type and tool characteristics. The degree of sharpness (DoS), defined as the force required to cut a reference body, is crucial for this process. A methodology was developed to objectively evaluate cutting damage on fresh-cut 'Golden Delicious' apples using three knives at four DoS levels (30, 100, 140, and 190 N) to cut 96 apples into 288 slices. The study assessed color, visual acceptance score, electrolytic leakage, and nutritional quality over 14 days at 5 °C. A two-way ANOVA showed no significant correlation between DoS and nutritional quality. However, a* values and browning index significantly increased with DoS, with values rising from 39.4 and 2.7 at 30 N to 41.4 and 3.1, respectively, at 190 N. The best visual acceptance score (4.0) and shelf-life (14 days) were at 30 N, while the worst score (2.9) and shelf-life (5 days) were at 190 N. Positive correlations were found between DoS and both browning index and a* value, with coefficients r of 0.97 and 0.93, respectively, highlighting the importance of using sharp tools for optimal post-cutting quality. [ABSTRACT FROM AUTHOR]

Deep learning methods have significantly advanced profiling side-channel attacks. Finding the optimal set of hyperparameters for these models remains challenging. Effective hyperparameter optimization is crucial for training accurate neural networks. In this work, we introduce a novel hill climbing optimization algorithm that is specifically designed for deep learning in profiled side-channel analysis. This algorithm iteratively explores hyperparameter space using gradient-based techniques to make precise, localized adjustments. By incorporating performance feedback at each iteration, our approach efficiently converges on optimal hyperparameters, surpassing traditional Random Search methods. Extensive experiments—covering protected implementations, leakage models, and various neural network architectures—demonstrate that our hill climbing method consistently achieves superior performance in over 80% of test cases, predicting the secret key with fewer attack traces and outperforming both Random Search and state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

As hydrogen energy, a clean energy source, is to be developed and utilized on a large scale, the construction of long-distance hydrogen pipelines and related stations along the route is also increasing. To study the dispersion patterns of hydrogen leakage under different conditions, a three-dimensional FLACS model of the hydrogen station was established. Simulations of hydrogen leakage and dispersion were conducted under different leakage pressures, leakage apertures, and leakage temperatures in the presence of obstacles. The dispersion ranges of flammable gas clouds were compared, and the influencing factors were analyzed. The results show that obstacles cause changes in the direction of hydrogen leakage, leading to a rapid increase in the dispersion range. In scenario 7, within 7 s (8 s to 15 s), the area of the flammable gas cloud rapidly increases to 73.3% of the entire station area. The increase of leakage pressure and leakage aperture both result in a larger dispersion range of the flammable gas cloud. For low-pressure leakage at 4 MPa, the change in leakage aperture has a more significant impact, while for large aperture leakage at 100 mm, the change in leakage pressure has a more significant impact. When the leakage temperature increases from 293 K to 353 K, the thermal motion of hydrogen molecules accelerates, but the change in leakage temperature does not significantly affect the dispersion range of the gas cloud. This study can provide a reference for the prevention and control of leakage accidents in hydrogen station. [ABSTRACT FROM AUTHOR]

Aiming at the shortcomings of existing holographic reconstruction algorithms, which are complex and easily affected by noise, this project proposes a semantic partitioning U-Net for high-resolution reconstruction. Firstly, a method based on the edge-neural network is proposed to obtain more image semantic information and improve the model training effect. Secondly, the effective channel attention mechanism of deep neural networks is introduced to enhance the attention to the detailed information in the holographic image. This further improves the accuracy of the neural network. The convergence rate of the neural network is accelerated by introducing a linear element with leakage correction. Experimental results show that this method can quickly reconstruct phase and brightness images with better detail, better edge texture and flat background. Holographic images of various sizes can be reproduced. The research of this project will lay a foundation for applying holographic image enhancement technology based on deep learning. [ABSTRACT FROM AUTHOR]

Double auction provides a cost-effective manner for sellers/buyers in smart grid. Due to concerns about information leakage, the asks/bids from sellers/buyers are sealed, making it challenging to select potential winners. To address this problem, the concept of public key encryption with equality test is deployed in double auction, since it is able to perform information retrieval over secure asks/bids. However, previous solutions suffer from the following two limitations: (i) unable to check inconsistent secure asks/bids due to the lack of tester-verifiable mechanism; (ii) incurring high matching time costs caused by one-to-one secure asks/bids. Therefore, we propose the VerDA, a secure double auction retrieval system with verifiable equality retrieval towards multiple secure asks/bids. Technically, to achieve the property of consistency over secure asks/bids, we develop the tester-verifiable technology by combining the decryption module and test module. To improve the efficiency of retrieval, we introduce secure multi-asks/bids testing function by augmenting the number of inputs in a same retrieval process. Moreover, we implement VerDA based on the PJM dataset in real cloud environment, where the experimental results show practical performance with encryption and test costs amounting to only 57.4% and 18.7% compared to state-of-the-art solution. [ABSTRACT FROM AUTHOR]

We primarily examined the effect of leakage delays on finite-time stability problems for genetic regulatory networks with interval time-varying delays. Since leakage delays can occur within the negative feedback components of networks and significantly impact their dynamics, they may potentially cause instability or suboptimal performance. The derived criteria encompass both leakage delays and discrete interval time-varying delays through the construction of a LyapunovKrasovskii function. We employed the estimation of various integral inequalities and a reciprocally convex technique. Additionally, these models consider lower bounds on delays, which may be either positive or zero, and allow for the derivatives of delays to be either positive or negative. Consequently, new criteria for genetic regulatory networks with interval time-varying delays under the effect of leakage delays are expressed in the form of linear matrix inequalities. Ultimately, a numerical example is presented to show the effect of leakage delays and to emphasize the significance of our theoretical findings. [ABSTRACT FROM AUTHOR]

Pipeline infrastructure plays a critical role in the transportation of vital resources, including oil, gas, and water. However, pipeline failures and leaks can have devastating consequences, resulting in environmental damage, economic losses, and risk to human life. Traditional methods of leak detection, such as visual inspection and pressure testing, are often time-consuming, labor-intensive, and unreliable. With the advent of wireless sensor networks (WSNs), there is an opportunity to revolutionize pipeline monitoring and leak detection. In this paper, we present a system that can monitor and detect leakage early, to enable engineers carry out prompt maintenance. This is made possible by the use of a network of nodes in a WSN, placed along a pipeline, each of which is capable of measuring and reporting varying flow rates, indicative of possible leakages. The system design consists of three major layers namely, the nodes layer, the cloud layer (for data logging), and the reporting layer. Tests were conducted under various conditions. The results show that with no leakages, the average flow rates for nodes 1, 2, 3, and 4 were 16.89747978, 16.89935602, 16.90978163, and 16.93380634 respectively. Furthermore, percentage flow rate differences of -0.02550353, 29.959675, and 30.3944134 were recorded for nodes 2, 3, and 4 respectively, after leakages occurred. The high values of the percentage difference for nodes 3 and 4 indicate a significant discrepancy in flow rate, worthy of physical inspection. The system is capable of detecting faults and leakages, even in the event of sensor failure, or network disruption. [ABSTRACT FROM AUTHOR]

Background: Tracheoesophageal speech is one of the most effective method used for voice rehabilitation after laryngectomy. The main limitation is the need for periodic voice prothesis (VP) replacements. The process of developing VP usage complications is still unexplored. The aim of this study was to assess the level of cytokines (IL‐1β, IL‐6, IL‐8, IL‐10, TNFα) and pepsin in saliva as potential factors reducing VP longevity. Methods: Prospective double‐blind randomized clinical trial was conducted (NCT04268459). Patients were randomly divided into two groups depending on VP replacement regimen (regular—every 3 months, or irregular—when complications occur). Levels of IL‐1β, IL‐6, IL‐8, IL‐10, TNFα, and pepsin in saliva samples (fasting and after eating) of laryngectomized patients were measured using ELISA tests. Results: Fifty‐two patients (26 in both groups) with control group (7 patients) participated in the study. The level of IL‐1β, IL‐6, IL‐8, IL‐10, TNFα, and pepsin did not differ according to regularity of VP replacements (p = 0.301–0.801). IL‐6 levels were significantly higher when VP complications occurs (p = 0.012). Conclusions: The saliva components were not significantly different depending on the frequency of VP replacements. IL‐6 plays an important role in the development of VP use complications. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The use of inulin in food is highly appreciated by consumers because of its prebiotic effect. In this study, the effects of increasing additions (5, 10 and 20%) of inulin as a substitute for wheat flour in bread production were investigated with regard to the physical, technological and rheological properties of the flour blends. Inulin reduced the water-binding capacity from 1.4 g/100 g with 0 flour to 0.80 g/100 g with the 20% inulin addition, while there were no statistical differences in the oil-binding capacity. The addition of inulin also influenced the yeast rates, especially in the samples with 5 and 10% addition. On the farinograph, inulin caused a reduction in water absorption (40.75 g/100 g with 20% inulin), an increase in dough development time (18.35 min with 10% inulin) and dough stability (13.10 min with 10% inulin). The mixograph showed a longer kneading time for the sample with 20% inulin (8.70 min) than for the control (4.61 min). In addition, there was an increase in dough firmness and tightness due to the addition of inulin (W: 203 × 10−4 J; P/L: 4.55 for the 20% inulin sample) compared with the control. The physical and technological properties of the loaves were evaluated at time 0 and after 4 days (T4). The addition of inulin reduced the volume of the bread while increasing the weight, albeit with a weight loss at T4 (compared to T0) of 4.8% for the 20% inulin and 14.7% for the control. The addition of inulin caused a darkening of the crust of the enriched bread, proportional to the increase in inulin content. In addition, the inulin content ranged from 0.82 g/100 g in the control to 14.42 g/100 g in the 20% inulin bread, while the predicted glycemic index ranged from 94.52 in the control to 89.39 in the 20% inulin bread. The available data suggest that the formulation with 5% inulin provides the highest performance. [ABSTRACT FROM AUTHOR]

Leakage is a major complication for ostomates, causing anxiety, low self-esteem and psychological distress. It also leads to an increased utilisation of healthcare services, placing a financial burden on the NHS. Despite advances in stoma products, leakage remains a primary concern for patients. Heylo, the first product to provide pre-leak notifications, aims to address this issue. This article explores the experiences of three patients who trialled Heylo after reporting a significant impact from leakage on the Leakage Impact Assessment tool. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Drainage & Irrigation Machinery Engineering / Paiguan Jixie Gongcheng Xuebao is the property of Editorial Department of Drainage & Irrigation Machinery Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

High‐temperature metallic phase‐change material is a very promising material alternative to traditional sensible heat‐storage materials in thermal energy storage systems. Nevertheless, the challenges such as their susceptibility to corrosive behavior, vulnerability to leakage, and proneness to oxidation in high‐temperature liquid phase present significant constraints that hinder their widespread applications. In this article, an approach to fabricate millimeter‐scale phase‐change capsules for macroscopic encapsulation of Al with high‐thermal‐conductive AlN shell is introduced. The study encompasses the preparation of Al@AlN macrocapsules with inner cavity, which can accommodate thermal volume expansion, through the direct powder formation combined with a two‐step sintering process, under a comparative evaluation of the atmospheric treatments involving N2, O2, and Ar. As the result, a calcination temperature of 1000 °C in Ar atmosphere is proper for the capsule formation. The Al metal core of the as‐obtained capsule shows a latent heat of fusion of 347.4 J g−1 and a melting temperature of 655.6 °C. The Al@AlN capsules also exhibit good thermal and stability, ensuring their potential application in high‐temperature heat storage and utilization. [ABSTRACT FROM AUTHOR]

Background: This study models the consequences of oil pipeline leakage using PHAST software, focusing on a segment crossing the Jarahi River in Southwest Iran. The goal is to understand potential environmental and safety impacts, establish safe zones for different leakage scenarios, and suggest strategies for risk mitigation. Methods: High-risk factors were identified through Failure Mode and Effects Analysis (FMEA). Consequences of pipeline leakage were simulated in PHAST software under varied scenarios, considering factors such as gap size, seasonal weather conditions, and location. This approach enabled assessment of safe distances in case of fire, explosion, or release of toxic substances. Results: Leakage consequences varied by gap size and seasonal conditions. For example, a 200-mm pipeline gap produced maximum substance concentrations of 160,860 mg/L in summer and 166,695 mg/L in winter. Safe distance thresholds also differed; in winter, the safe distance was 275 m, while in summer it reached 520 m. Radiation and blast wave intensities were higher in winter due to environmental stability, indicating greater risks. Conclusion: PHAST software proves valuable in modeling pipeline leakages and determining safety perimeters. The findings highlight the need for ongoing risk management, especially in sensitive areas like the Jarahi River. Routine safety inspections and enhanced environmental safeguards are recommended to minimize potential hazards and protect surrounding ecosystem

Abstract Background In this report, we presented two cases of sudden onset abdominal wall leakages of inguinal hernia in patients undergoing peritoneal dialysis (PD). Case presentation A total of 519 patients with end-stage kidney disease underwent PD at our hospital between March 2006 and March 2023. Among them, 39 patients [7.5%; 36 men (92%); mean age, 66 years; median PD duration, 1.7 years] developed inguinal hernias, with an incidence rate of 0.85 per 100 dialysis patient-years. Two patients (0.4%; both men; age/PD duration, 65/4.6 years and 74/1.7 years) experienced sudden onset abdominal wall leakages of inguinal hernia, with a rupture rate of 0.04 per 100 dialysis patient-years. In these cases of sudden onset abdominal wall leakages, both patients underwent tension-free hernioplasty; one patient was shifted to hemodialysis due to discomfort experienced from the right groin to the thigh area, while the other patient remained on PD. Conclusions Clinicians should consider the possibility of sudden onset abdominal wall leakages of inguinal hernia in PD patients.

Recently, some travertine landscape groups in Huanglong Scenic Spot have been degraded to varying degrees. Surface water leakage, blackening and desertification have occurred on a large scale in the dense distribution area of Salix cupularis shrub, which has adversely affected the core value of the Huanglong World Natural Heritage Site. The relationship between shrub expansion and leakage enhancement has not been fully understood. In this study, travertine pool group of typical shrub area was selected in the north of Yingyue Pool in the upper reaches of Huanglong, and 4 shrub cover levels were set: no shrub (coverage 60%). In-situ infiltration test was conducted to determine the leakage intensity and to evaluate the changes of travertine pore structure and permeability parameters in shrub area. With the comparison of the leakage intensities in different shrub cover level areas, the mechanism of surface water leakage of travertine under the influence of Salix cupularis scrub is summarized. The results show that (1) the leakage intensity increases with the increase of coverage. When the coverage of Salix cupularis shrub exceeds 60%, the leakage intensity changes significantly, which should be related to the rapid diversion of large pores. (2) Under the influence of algae activities and decomposition of plant residues, new travertine with more pores and holes is formed in the scrub area, resulting in higher natural leakage intensity than that in the non-scrub area. (3) The root activities of Salix cupularis shrub changes the primary travertine structure, leading to loose primary travertine and increases of pore diameter, effective porosity, and permeability coefficient. The enhanced groundwater seepage resulted in enhanced overall surface water leakage in the travertine pool. (4) The transformation of travertine pore structure by Salix cupularis roots is depended on the root cleavage. The dissolution of travertine cement by root solution leads travertine to uniform loose accumulation. The results show that the root and algal activities in Salix cupularis scrub area mainly control the process of surface water leakage enhancement. This study have basic value for the evolution analysis and conservation of Huanglong travertine natural heritage landscape.

During the operational phases of the upper reservoir in a pumped storage power station, the water level, leakage area, and hydraulic gradient of the upper reservoir alter dynamically due to the cyclic pumping and draining activities. The rising groundwater level during storage introduces distinct leakage conditions within the reservoir basin, characterized by unsaturated, partially saturated, and saturated states. Consequently, reservoir basin leakage exhibits variability across these states. To address this issue, this study formulated rational assumptions corresponding to the three leakage states in a reservoir basin and derived analytical expressions for seepage calculation based on Darcy's law and the principles governing groundwater flow refraction. A case study was conducted to investigate the relationship between various factors and leakage. The results showed that leakage primarily depended on the permeability of the impermeable layer in the reservoir basin. The upper reservoir leakage was estimated, and the calculated leakage generally agreed with the measurements, offering insights into the leakage mechanism of the Liyang pumped storage power station. In addition, the reasons for disparities between measured and calculated leakage were analyzed, and the reliability of the developed method was validated. The findings of this study provide a foundation for the seepage control design of upstream reservoirs in similar projects.

The paper investigates the sources of water leakage in Mokattam, Cairo, Egypt. It is considered a high-risk zone for landslides due to the presence of problematic soil, topography, and water conditions. The objective is to mitigate the negative impact of underground water on landslide disasters. The proposed methodology involves field visits, satellite image processing, Ground Penetration Radar scanning, chemical and isotope analysis of water, and evaluating the water and sanitary networks within the study area. The findings revealed that the underground water is formed because of the continuous leakage from the existing networks. Moreover, there was no evidence of any aquifers, particularly at Ain Mosa floating point. Thus, the accumulated water in the unsaturated zone is not sustainable for long-term development for its limited potential and poor quality. Consequently, immediate action plan is required to assess and upgrade the water and sanitary networks through the implementation of innovative technologies for such hydrogeologic conditions

Deep learning algorithms are increasingly employed to exploit side-channel information, such as power consumption and electromagnetic leakage from hardware devices, significantly enhancing attack capabilities. However, relying solely on power traces for side-channel information often requires adequate domain knowledge. To address this limitation, this work proposes a new attack scheme. Firstly, a Convolutional Neural Network (CNN)-based plaintext-extended bilinear feature fusion model is designed. Secondly, multi-model intermediate layers are fused and trained, yielding in the increase of the amount of effective information and generalization ability. Finally, the model is employed to predict the output probability of three public side-channel datasets (e.g. ASCAD, AES _ HD, and AES _ RD), and analyze the recovery key guessing entropy for each key to efficiently assess attack efficiency. Experimental results showcase that the plaintext-extended bilinear feature fusion model can effectively enhance the Side-Channel Attack (SCA) capabilities and prediction performance. Deploying the proposed method, the number of traces required for a successful attack on the ASCAD _ R dataset is significantly reduced to less than 914, representing an 70.5% reduction in traces compared to the network in Convolutional Neural Network-Visual Geometry Group (CNNVGG16) with plaintext, which incorporating plaintext features before the fully connected layer. Compared to existing solutions, the proposed scheme requires only 80% of the power traces for the attack mask design using only 75 epochs. As a result, the power of the proposed method is well proved through the different experiments and comparison processes. [ABSTRACT FROM AUTHOR]

[Display omitted] Thermochromic dyes (TCDs) based on a three-component color change system suffer from solid rigidity and liquid leakage issues because of the intrinsic solid–liquid phase change performance, resulting in difficulty in temperature visualization applications for smart wearable fields. Despite considerable efforts in microencapsulation of thermochromic dyes, designing and fabricating essentially flexible thermochromic phase change films still need to be explored. Herein, a one-sided adhesive gradient-crosslinked thermochromic film is reported to address these issues to make a trade-off between stability and flexibility, excellent thermochromic performance, and temperature visualization. The thermochromic wearable films have been fabricated exploiting tea polyphenol thermochromic dyes, vinyl dimethylsiloxane, and hydrosilicone oil via the salt-template-assisted method and gradient crosslinking strategy, which have porous structures with an average pore size of 12.8 μm and a porosity of 28 %. Due to the spatial limiting threshold effect of the porosity structure, interconnected 3D polysiloxane porous networks can provide ample support for tea polyphenol thermochromic dyes and effectively prevent liquid leakage. Upon heating, the thermochromic film changes from blue to white with the K/S value decreasing from 7.69 to 0.78 and the Δ E * increasing from 2.7 to 16.1 at 610 nm, and the color-changing temperature is 42 °C. Gradient crosslinked thermochromic films exhibit excellent temperature-responsive color change properties, desirable one-side adhesion, and thermal energy storage, enabling multicolor temperature displays and temperature-controlled multilevel information transfer. [ABSTRACT FROM AUTHOR]

Due to the significant advantages of methane sensitivity and area-type leakage detection, tunable diode laser absorption spectroscopy (TDLAS) gas detection has been promoted as an effective method for microleakage monitoring in oil and gas stations. However, the output of the TDLAS detector is the integral concentration (IC). Based on the relevant research, the alarm threshold and risk are assessed via the gas concentration rather than the IC. How to evaluate the concentration of leaked gas clouds based on IC from TDLAS detectors is still a challenge. To address this problem, the characteristics of IC and the influence of the laser path, wind speed and leakage rate were studied via computational fluid dynamics (CFD). A neural network classification model (NNCM) was proposed to obtain the probability distribution of the maximal concentration along the laser path (Cmax). The results indicated that the IC is strongly correlated with the Cmax. Considering the accuracy and operability, the NNCM with input features of IC, wind speed and angle of laser path was selected. Field tests showed that the developed model achieved the concentration evaluation of leaked gas clouds. Additionally, the NNCM can also quantify the uncertainty of the results, which avoids misjudgments caused by deviations. [ABSTRACT FROM AUTHOR]

A two-input function is a dual PRF if it is a PRF when keyed by either of its inputs. Dual PRFs are assumed in the design and analysis of numerous primitives and protocols including HMAC, AMAC, TLS 1.3 and MLS. But, not only do we not know whether particular functions on which the assumption is made really are dual PRFs; we do not know if dual PRFs even exist. What if the goal is impossible? This paper addresses this with a foundational treatment of dual PRFs, giving constructions based on standard assumptions. This provides what we call a generic validation of the dual PRF assumption. Our approach is to introduce and construct symmetric PRFs, which imply dual PRFs and may be of independent interest. We give a general construction of a symmetric PRF based on a function having a weak form of collision resistance coupled with a leakage hardcore function, a strengthening of the usual notion of hardcore functions we introduce. We instantiate this general construction in two ways to obtain two specific symmetric and dual PRFs, the first assuming any collision-resistant hash function and the second assuming any one-way permutation. A construction based on any one-way function evades us and is left as an intriguing open problem. [ABSTRACT FROM AUTHOR]

Purpose: Diffusion‐weighted imaging (DWI) suffers from geometric distortion and chemical shift artifacts due to the commonly used Echo Planar Imaging (EPI) trajectory. Even with fat suppression in DWI, severe B0 and B1 variations can result in residual fat, which becomes both a source of image artifacts and a confounding factor in diffusion‐weighted contrast in distinguishing benign and malignant tissues. This work presents a method for acquiring distortion‐free diffusion‐weighted images using spatiotemporal acquisition and joint reconstruction. Water‐fat separation is performed by chemical‐shift encoding. Methods: Spatiotemporal acquisition is employed to obtain distortion‐free images at a series of echo times. Chemical‐shift encoding is used for water‐fat separation. Reconstruction and separation are performed jointly in the spat‐spectral domain. To address the shot‐to‐shot motion‐induced phase in DWI, an Fast Spin Echo (FSE)‐based phase navigator is incorporated into the sequence to obtain distortion‐free phase information. The proposed method was validated in phantoms and in vivo for the brain, head and neck, and breast. Results: The proposed method enables the acquisition of distortion‐free diffusion‐weighted images in the presence of B0 field inhomogenieties commonly observed in the body. Water and fat components are separated with no obvious spectral leakage artifacts. The estimated Apparent Diffusion Coefficient (ADC) is comparable to that of multishot DW‐EPI. Conclusion: Distortion‐free, water‐fat separated diffusion‐weighted images in body can be obtained through the utilization of spatiotemporal acquisition and joint reconstruction methods. [ABSTRACT FROM AUTHOR]

The periodic-cell model was proposed to simulate the successive contacts between the labyrinth fin and multiple honeycomb cells. With the experimental data, the finite-element-analysis (FEA) method with the periodic-cell model was validated. The effects of incursion parameters (i.e. incursion depth, incursion rate and sliding velocity) on the contact force, frictional temperature, material loss, and worn geometry of the honeycomb seal during the incursion process were studied. With the predicted worn geometry, the sealing performance degradation in the honeycomb seal was analyzed. The results showed that the proposed periodic-cell model has an excellent accuracy in predicting the wear behavior of honeycomb seal in rubbing events. The contact force between the honeycomb liner and labyrinth fin is pronounced especially at low sliding velocity and high incursion rate conditions, which increases the possibility of wear damage in the rotor part. At low sliding velocity and low incursion rate conditions, the frictional heat transferring to rotor part is increased, which increases the thermal stress near the contact region of the rotor part. As the clearance gap of honeycomb seal increases from 0.6 mm to 0.9 mm in the rubbing event, the leakage rate is increased by about 12%, and the carry-over effects downstream of the worn cells are increased. [ABSTRACT FROM AUTHOR]

Segmented radial seals are modern technologies used in aeronautic engines and space turbopumps. They consist of several circumferential segments assembled as an annular ring freely mounted on the rotor. A circumferential (garter) spring tightens the segments around the shaft. The segments can move radially relative to each other, sliding against a casing and following the dynamic displacements of the rotor. Two similar segmented seals made of different materials were tested. The results showed different leakage flow rates and different correlations between leakage and wear rate. For example, the leakage rate decreases with wear for one seal and increases for the other. For explaining these results, wear was correlated with the microstructure of the materials of the two seals. Profilometric analyses were made for the two seals, highlighting that wear was not localised in the same areas. Raman spectra maps were taken on the pads of the segment in contact with the rotor and microstructural changes caused by friction were enlightened. The evolution of residual stresses was measured for new and worn segments. These findings strengthen the results obtained from profilometric wear analyses. They also allow a more precise understanding of tribological degradation scenarios depending on the operating conditions and the properties of the material.

In the operation of water distribution networks in cities, leakage from pipes always causes problems for human health and for the environment. Leakage openings in pipes may exist in different shapes. Circular holes are common in corroded and punched pipes. In the leakage studies, the area of these openings is usually assumed to be fixed and the leakage exponent is about 0.5. In this study, an analytical equation has been presented with two purposes. First, Examining the changes in the leak area and leakage exponent of circular holes. Second, providing an equation that contains more parameters than the general leakage equations. By using such an equation, the accuracy of leakage estimation is increased due to the direct involvement of the effective parameters. Also, for the possibility of modeling different leakage equations, including the present equation, a new hydraulic analysis model has been developed. This model tries to improve leakage modeling by including more capabilities than the existing hydraulic analysis models. Results showed that the leak area in circular holes is not fixed and changes due to different parameters. Comparison of the present equation and the orifice equation showed a significant difference which confirms that the orifice equation cannot be always used for circular leaks. In the study of leakage exponent, it was found that for polyethylene pipes, the leakage exponent is higher than value of 0.5 mentioned in the other studies and it can take different values depending on the leakage position in the network. Increasing the hole diameter did not affect the leakage exponent, but increased the leakage coefficient. On the other hand, for steel pipes, the leakage coefficient was fixed and the exponent remained around 0.5. Finally, the results showed the usefulness of the developed hydraulic analysis model for implementing the scenarios defined in this study.

This paper is a summary of many of the key findings on the application of geosynthetics in tailings storage facilities. Topics include the compressibility and permeability of tailings, the equations predicting leakage through circular and non-circular geomembrane holes, the effect of the subgrade permeability, and the effect of a lateral drainage system within tailings on leakage predictions. Two commonly encountered engineering problems relating to the piping through circular geomembrane holes and the opening width of non-circular defective geomembrane seams are given to demonstrate the potential application of leakage prediction equations. Meanwhile, issues related to the subgrade imperfection and the long-term performance of both high-density polyethylene (HDPE) and bituminous geomembranes in tailings storage applications are addressed. The research highlights that an appropriate HDPE geomembrane liner can be expected to perform very well for an extremely long time, limiting leakage and contaminant migration from the facility into the surrounding environment if the liner is well constructed on a suitable subgrade.

Abstract Objectives Due to the COVID-19 pandemic and the shortage of the National Institute for Occupational Safety & Health (NIOSH)-approved N95 respirators, the Food and Drug Administration granted an Emergency Use Authorization to allow the use of non-NIOSH approved respirators provided that these respirators must undergo tests by a protocol of TEB-APR-STP-0059, similar methods of NIOSH standard testing procedure. This initiative safeguards the quality of respirators and the effectiveness of occupational protection. The dataset of all the testing results could benefit further analysis of COVID-19 infection rates in relation to different types of N95 respirators used and identify potential correlations of various test parameters in the testing system for validation. The analysis enhances understanding of the quality, effectiveness, and performance of N95 respirators in the prevention of respiratory infectious transmission and develops improved occupational safety measures. Data description The dataset was transformed, transcribed, and compiled from the official testing data of non-NIOSH-approved N95 respirators reported in the NIOSH website under the Centers for the Disease Control and Prevention in the United States. The dataset included details of 7,413 testing results of N95 respirators (manufacturer, model, and maximum and minimum filtration efficiency) and test parameters (flow rate, initial filter resistance, and initial percent leakage). Supplementary items were added to increase the availability of data analysis and enhance the interpretability of the assessments of the quality of N95 respirators.

ORCs are often designed with the lower pressure limited by the ambient pressure, to avoid air leaking into the working fluid. Safely lowering this limit will be beneficial for power-production efficiency. First, cycle operations with air inleak are investigated. Exemplary cases with n-pentane and benzene are used. The investigation combines tools from thermodynamics of cycle working fluids, pump operation and analysis and combustion science. It appears that pumps customarily used in ORC will forward only liquid, and air mixing into the working fluid at the high-pressure side will not be sufficient for flammable conditions. Next, combustion properties of the air/working fluid mixture in the condenser are evaluated. Transient zero-dimensional and one-dimensional steady state laminar premixed flames are applied for the modelling. Detailed chemical mechanisms from the CRECK and TDTVT groups are used for benzene and n-pentane. It is found that some substances, like pentane, will not make flammable mixtures within the conditions of the power cycle. However, fluids that at the relevant temperatures have saturation pressure much lower than the ambient, might give flammable mixtures with air inleak. For potential sub-ambient use of these, ignition energy sources and quenching geometries have to be considered carefully.

This study investigates the differential responses of two maize genotypes, SC180 and SC168, to salt stress, aiming to elucidate the mechanisms underlying salinity tolerance and identify traits associated with improved stress resilience. Salinity stress, imposed by 150 mM NaCl, adversely affected various growth parameters in both genotypes. SC180 exhibited a more pronounced reduction in shoot length (13.6%) and root length (13.6%) compared to SC168, which showed minimal reductions (3.0% and 2.3%, respectively). Additionally, dry weight losses in SC180's leaves, stems, and roots were significantly greater than those in SC168. Under salinity stress, both genotypes accumulated Na+ in all organs, with SC168 showing higher Na + concentrations. However, K+ levels decreased more significantly in SC180's leaves than in SC168's. The study also assessed physiological responses, noting that SC180 experienced a substantial reduction in relative water content (RWC) in leaves (22.7%), while SC168's RWC remained relatively stable (5.15%). Proline accumulation, a marker for osmotic adjustment, increased 2.3-fold in SC168 compared onefold in SC180. Oxidative stress indicators, such as electrolyte leakage and hydrogen peroxide levels, were elevated in both genotypes under salt stress, with SC180 showing higher increases (48.5% and 48.7%, respectively) than SC168 (35.25% and 22.0%). Moreover, antioxidant enzymes (APX, CAT, POD, SOD, GR) activities were significantly enhanced in SC168 under salinity stress, whereas SC180 showed no significant changes in these activities. Stress indices, used to quantify and compare salinity tolerance, consistently ranked SC168 as more tolerant (average rank = 1.08) compared to SC180 (average rank = 1.92). Correlation analyses further confirmed that SC168's superior tolerance was associated with better Na + regulation, maintenance of K+ levels, and a robust antioxidant defense system. In conclusion, SC168 demonstrated greater resilience to salinity stress, attributed to its efficient ion regulation, stable water status, enhanced osmotic adjustment, and strong antioxidant response. These findings provide valuable insights for breeding and developing salinity-tolerant maize varieties. [ABSTRACT FROM AUTHOR]

Time-dependent conduction in epitaxial superlattice (SL) strain relief layers of GaN high electron mobility transistors on 200 mm engineered substrates with a poly-AlN core was observed and analyzed. This phenomenon occurs when the devices were operated with substrate bias of ∼−300 V for 101–103 s. The formation of the conduction path is related to trap-assisted leakage through the SLs on the engineered substrates; de-trapped carriers spread out vertically and laterally within a portion of the SLs, leading to a higher electrical field across the rest of the layers. This conduction mechanism may be hidden during the devices' normal operation (target 650–1200 V). It could lead to undesired effects during the operation of the devices, such as a time-dependent dynamic Ron. More resistive SLs will potentially reduce the impact of this phenomenon. [ABSTRACT FROM AUTHOR]

A region-based level-set active contour is the preferred choice for image-segmentation tasks, when the region of interest is defined by weak edges. While, the minimization of an energy functional leads to the contour’s conformation to object boundary, the energy is composed of contour’s internal and image-dependent external energies. In such a model, the overall motion (expansion/shrinkage) of contour is controlled by its area-energy, whereas the length-energy controls the contour’s elasticity. Traditionally, these two internal energies are weighted by scalar constants, which remain fixed throughout the level-set evolution. Both the internal energies are responsible for the contour’s regularization only, whereas the contour converges due to the minimization of external energies. Further, inappropriate weighting results into an inaccurate segmentation either because of premature convergence, or leakage beyond the object boundary. To address these issues, an adaptive spatially weighted region-based active contour (ASWRAC) is proposed. The weights are assigned adaptively to the internal energy terms at successive steps of evolution. This basically removes the need of weight initialization for an improved segmentation process. Additionally, the proposed weights are modeled as vectors, depending on the local regional statistics of the image. This causes the originally internal energies to also reflect external characteristics. Moreover, the time-step used in the discrete implementation of level-set evolution is also managed adaptively. This restricts the contour’s leakage beyond the region of interest. The suggested technique is tested on brain MR slices and other biomedical images from public databases. Comparison of the obtained results with state-of-the-art techniques shows its superiority in segmentation accuracy measured using the metrics: dice Similarity Coefficient, sensitivity, and specificity. [ABSTRACT FROM AUTHOR]

High expansion (Hi‐Ex) foam is recommended to suppress the leakage and diffusion of cryogenic liquid due to its light weight and large volume. However, the disadvantages of low stability and high break rate under environmental conditions are all limited the further application in vapor mitigation and fire extinguishing. So that, this paper focus on the effect and mechanism of nanoparticles in stabilizing Hi‐Ex foam. Three kinds of nanoparticles with different concentration were selected to evaluate the effect of foam half‐life and the mechanism of particles on improving the foam stability. The results indicated that different particle concentrations can improve the foam stability to a specific extent, and the maximum improving of half‐life can increase by 95.4% in the presence of the hydrophilic SiO2 at .5 wt%. Meanwhile, the hydrophilicity, size, and morphology of the particles have a specific impact on the foam stability. The foam expansion rate first increased and then decreased. From the microscopic point of view, the bubble size gradually increases with time by two processes of ripening and coalescence and satisfied in a logarithmic distribution. While, the liquid film thickness remarkably decreases due to foam drainage without particles and the adsorption and accumulation of nanoparticles on foam lamella can provide a spatial barrier for the film thinning and the inter bubble diffusion. Finally, the microscopic interaction mechanism on improving the foam stability has been further explored and revealed in these two aspects. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate the ventilated cavitating flow behavior, through experimental and numerical methods. The experiments are performed for a test model placed in a water tunnel and a high-speed camera is used to image the formation and collapse of the supercavity. For the numerical simulations, Ansys CFX commercial software is employed to solve the Reynolds-averaged Navier–Stokes (RANS) equations and additional transport equation for the liquid volume fraction in the unsteady condition. Both the experimental observation and numerical prediction show a hysteresis behavior for ventilated supercavity in which the value of the air entrainment coefficient required to maintain the supercavity in the formation process is less than the amount required to form it. The good agreement observed between the numerical prediction and experimental data, revealed the accuracy and capability of the numerical scheme. Also, the numerical simulation shows that the variations in the supercavity length, in addition to the air entrainment, are a function of the air leakage regime from the closure region of supercavity. [ABSTRACT FROM AUTHOR]

A DC‐DC converter with high boost and low switching voltage stress is proposed by combining switched capacitor (SC) and coupled inductor (CL) techniques based on a conventional boost circuit. The design methodology of this converter includes substituting SC for a single switch in the boost converter, combining CL, and integrating a resonant boost circuit for absorbing leakage inductance. The improved power switch topology in this design has lower voltage stress, lower diode current stress, fewer total components, and common ground than other conventional DC‐DC converters. The operating modes and steady state analysis of the converter are provided in terms of leakage inductance utilization, with component stress derivation and theoretical efficiency analysis. In addition, comparisons with other dc‐dc converters are made. Subsequently, experiments were conducted on a 200 W DC‐DC converter prototype to verify the reliability of the converter. [ABSTRACT FROM AUTHOR]

Faced with climate change and increasing environmental pollution, countries around the world are actively exploring strategies for clean, renewable energy. However, under high-pressure conditions, hydrogen leaks can lead to spontaneous combustion, which significantly raises the safety risk of hydrogen applications. This study employs fluid dynamic simulation methods to investigate the development process of shock waves within tubes. It analyzes the effect of release conditions on the propagation speed and shock wave intensity, revealing the impact of shock wave intensity on the temperature distribution and gas composition variation within the hydrogen-air mixture boundary layer. The results show that the tube length and bends have relatively little impact on the shock waves, while discharge pressure and tube diameter significantly affect the propagation speed and intensity of shock waves. Combined with dimensional analysis and data fitting, a predictive model for autoignition of high-pressure hydrogen leakage is established: (P r / P a)((DXr x(H₂) r O₂)) /V s 2) = 1505(X / D)−1.329. • Studied the influence of the discharge conditions on the propagation process of the excitation wave in the tube. • Elucidated the microscopic influence of the leading shock wave on the gas properties at the boundary layer. • Propose a prediction model for spontaneous combustion of high-pressure hydrogen leakage. [ABSTRACT FROM AUTHOR]

Liquid hydrogen leaks can lead to the formation of solid-air deposition near the leakage source, and oxygen enrichment may exacerbate the risk of ignition of liquid hydrogen and combustible clouds. This study, based on NASA's large-scale liquid hydrogen leakage experiments, constructed a three-dimensional model to dissect the evaporation/condensation and melting/solidification processes of air components (water, oxygen, and nitrogen), aiming to analyze the phase transitions of each air component and study the concentration and extent changes of condensed air components and solid-air deposition over time. The findings indicated that after the leakage stopped, the concentrations of liquid nitrogen and oxygen initially increased and then decreased below the leakage source, related to the heat absorption from liquid hydrogen evaporation and ground heat exchange, while the range of solid-air deposition gradually diminished. This model provides a reliable prediction of solid-air deposition formation, offering a reference for further research. [Display omitted] • Condensation and solidification processes of nitrogen and oxygen are considered separately. • The concentration and range of liquid nitrogen and liquid oxygen continue to increase after the leakage is stopped. • The solidification range of nitrogen and oxygen decreases after the liquid hydrogen evaporates completely. • Thermal conductivity of ground conditions affects the duration of solid-air deposition. [ABSTRACT FROM AUTHOR]

Accurate segmentation of the pulmonary airway tree is crucial for diagnosing lung diseases. To tackle the issues of low segmentation accuracy and frequent leaks in existing methods, this paper proposes a precise segmentation method using quasi-spherical region-constrained wavefront propagation with tracheal wall gap sealing. Based on the characteristic that the surface formed by seed points approximates the airway cross-section, the width of the unsegmented airway is calculated, determining the initial quasi-spherical constraint region. Using the wavefront propagation method, seed points are continuously propagated and segmented along the tracheal wall within the quasi-spherical constraint region, thus overcoming the need to determine complex segmentation directions. To seal tracheal wall gaps, a morphological closing operation is utilized to extract the characteristics of small holes and locate low-brightness tracheal wall gaps. By filling the CT values at these gaps, the method seals the tracheal wall gaps. Extensive experiments on the EXACT09 dataset demonstrate that our algorithm ranks third in segmentation completeness. Moreover, its performance in preventing airway leaks is significantly better than the top-two algorithms, effectively preventing large-scale leak-induced spread. [ABSTRACT FROM AUTHOR]

NS1 is an elusive dengue protein, involved in viral replication, assembly, pathogenesis, and immune evasion. Its levels in blood plasm are positively related to disease severity like thrombocytopenia, hemorrhage, and vascular leakage. Despite its pathogenic roles, NS1 is being used in various vaccine formulations due to its sequence conservancy, ability to produce protective antibodies and low risk for inducing antibody-dependent enhancement. In this study, we have used bioinformatics tools and reported literature to develop an NS1 variant (dNS1). Molecular docking studies were performed to evaluate the receptor-binding ability of the NS1 and dNS1 with TLR4. NS1 and dNS1 (153 to 312 amino acid region) genes were cloned, expressed and protein was purified followed by refolding. Docking studies showed the binding of NS1 and dNS1 with the TLR4 receptor which suggests that N and C-terminal sequences of NS1 are not critical for receptor binding. Antibodies against NS1 and dNS1 were raised in rabbits and binding affinity of anti-dNS1 anti-NS1 sera was evaluated against both NS1 and dNS1. Similar results were observed through western blotting which highlight that N and C-terminal deletion of NS1 does not compromise the immunogenic potential of dNS1 hence, supports its use in future vaccine formulations as a substitute for NS1. [ABSTRACT FROM AUTHOR]

The influence of pressure and environment on urban polyethylene (PE) gas pipeline makes structural deterioration and leaking to the pipeline and pipeline easy. This paper proposes an analysis method for optimizing Variational Mode Decomposition (VMD) algorithm. Firstly, the optimal bandwidth is obtained by using the adaptive weighted frequency band entropy (AFBE), and the optimal quadratic penalty factor is obtained by curve fitting. Then, the AFBE is used as the fitness function, and the optimal decomposition level is obtained by the optimized beetle whisker search algorithm. Experimental results show that the signal-to-noise ratio (SNR) is improved by 12.74% on average. [ABSTRACT FROM AUTHOR]

The widespread of renewable energy sources often requires DC‐DC power converters with higher operational flexibility and voltage gain capability. The Y‐source converter offers significant features to fill this demand, but its performance can be negatively affected by coupled‐inductor leakage inductances. This paper presents simplified models for the Y‐source DC‐DC converter (YSDC) that, although not directly including the presence of leakage inductances, offer a satisfactory description of how the converter operates in terms of its steady‐state behavior, small‐signal dynamics, and estimation of power losses. These models allow for a comprehensive analysis of how non‐ideal components in the converter affect the determination of the YSDC voltage gain and efficiency and allow one to identify the most interesting design alternatives to satisfy the current and voltage stress constraints placed on the converter power switches, thus excluding undesired converter design alternatives. Experimental results with a 280 W real converter, using coupled‐inductor with leakage inductances, present results similar to those of switched circuit simulations and the derived models, thus confirming that the simplified models present satisfactory adherence to the real converter performance over the majority extent of the maximum duty cycle. [ABSTRACT FROM AUTHOR]

Reduced-scale CO2 release experiments in shallow aquifers serve as crucial monitoring strategies for detecting unintended CO2 leakage into potable aquifers within Carbon Capture and Storage (CCS) projects. Understanding site-specific geological, hydrogeological, and climatic features is essential. However, accurately tracing changes in groundwater quality due to this process and using hydrochemical parameters for CO2 leakage diagnosis require establishing a solid, seasonally relevant baseline to avoid misinterpretation. This study focuses on detailing the geological, hydrogeological, and geophysical characteristics of the TECNOPUC-Viamão CO2 controlled-release experimental site in Rio Grande do Sul, Brazil. It presents a comprehensive three-year investigation into the seasonal natural background hydrochemistry. Field characterization involved recognition boreholes, in-situ infiltration and Slug Tests, topographic surveys, DC resistivity measurements, and groundwater sampling campaigns for physicochemical, major, minor, trace elements, and δ¹³C-DIC evaluation. Results indicate the area comprises a granite-derived multilayer phreatic aquifer with two distinct hydrostratigraphic units (St and Aa). These units differ in lithological composition, hydraulic conductivities (St: 10− 4 m/s, Aa: 10− 8 m/s), apparent resistivities, and physicochemical and hydrochemical compositions. The St unit shows slightly neutral pH, higher temperature, EC, ORP, DO, Ca, Mg, K, Fe, Mn, Sr, B, HCO3−, and DIC concentrations, with δ¹³C-DIC between − 3 to -8‰. Conversely, the Aa unit displays slightly acidic pH, lower temperature, EC, ORP, higher DO fluctuation, Na, SO42−, Cl−, NO3−, Zn, Al, Ni concentrations, lower HCO3−, DIC levels, with δ¹³C-DIC ranging between − 6 to -11‰. Additionally, seasonal monitoring campaign revealed that there is a clear temperature-related influence on K, Na and trace elements (Fe, Ba, Mn, Al, B, and Zn) behavior (but not in Ca, Mg, Sr and Ni), which could impact further interpretation of the results during the upcoming CO2 injection phase, and that the Control Charts can confidently serve as a valuable tool in understanding the inherent natural hydrochemical trends. [ABSTRACT FROM AUTHOR]