Reliable Applications Research Articles

Projecting the long‐term effects of large‐scale human influence on the spatial and functional persistence of extant longleaf pine ecosystems in the Florida Flatwoods Pyrome

AbstractDecades of human activities and fire suppression have adversely affected longleaf pine (Pinus palustris) ecosystems, which are home to high levels of diversity and endemism. These iconic ecosystems also now face challenges from urbanization and climate change, which will alter conservation outcomes over the remainder of the 21st century. To explore how long‐term, large‐scale human influences could affect the spatial and functional persistence of extant longleaf pine ecosystems in the Florida Flatwoods Pyrome, we extracted a set of 2400 longleaf pine patches ≥40 ha in size from the Florida Longleaf Pine Ecosystem Geodatabase. Projections from the FUTURES urban growth model and the Florida 2070 project indicate that development will lead to losses of existing longleaf pine habitat, reductions in longleaf pine patch size, and patches that are predominantly located in close proximity to developed areas. Finer‐scale patterns of longleaf pine loss in three focal landscapes highlighted differences in land protection, ecological setting, and development pressure and the value of using of multiple urbanization iterations. The occurrence of suitable conditions to conduct prescribed fires, a crucial tool for maintaining, improving, and restoring longleaf pine ecosystems, is projected to decrease seasonally throughout the study area. As a result, the functional persistence of ecosystems is at risk due to climate changes that increase barriers to the safe and reliable application of intentional fire. The long‐term viability of this critical ecosystem will warrant the evaluation of adaptive strategies that explicitly account for the individual and compounding effects of urban development and changing fire management conditions when considering options for ecosystem protection, management, and restoration.

A Comparative Study on GPS Navigation Systems: Attacks, Applications and Challenges for Security and Reliability

A Comparative Study on GPS Navigation Systems: Attacks, Applications and Challenges for Security and Reliability

Biosilica-coated carbonic anhydrase displayed on Escherichia coli: A novel design approach for efficient and stable biocatalyst for CO2 sequestration

A robust and stable carbonic anhydrase (CA) system is indispensable for effectively sequestering carbon dioxide to mitigate climate change. While microbial surface display technology has been employed to construct an economically promising cell-displayed CO2-capturing biocatalyst, the displayed CA enzymes were prone to inactivation due to their low stability in harsh conditions. Herein, drawing inspiration from biomineralized diatom frustules, we artificially introduced biosilica shell materials to the CA macromolecules displayed on Escherichia coli surfaces. Specifically, we displayed a fusion of CA and the diatom-derived silica-forming Sil3K peptide (CA-Sil3K) on the E. coli surface using the membrane anchor protein Lpp-OmpA linker. The displayed CA-Sil3K (dCA-Sil3K) fusion protein underwent a biosilicification reaction under mild conditions, resulting in nanoscale self-encapsulation of the displayed enzyme in biosilica. The biosilicified dCA-Sil3K (BS-dCA-Sil3K) exhibited improved thermal, pH, and protease stability and retained 63 % of its initial activity after ten reuses. Additionally, the BS-dCA-Sil3K biocatalyst significantly accelerated the CaCO3 precipitation rate, reducing the time required for the onset of CaCO3 formation by 92 % compared to an uncatalyzed reaction. Sedimentation of BS-dCA-Sil3K on a membrane filter demonstrated a reliable CO2 hydration application with superior long-term stability under desiccation conditions. This study may open new avenues for the nanoscale-encapsulation of enzymes with biosilica, offering effective strategies to provide efficient, stable, and economic cell-displayed biocatalysts for practical applications.

Genetic and ecological inheritance of plant growth-promoting rhizobacteria

Abstract Background The utilization of beneficial (Rhizo) bacteria, as an alternative to traditional fertilizers, has emerged as an eco-friendly strategy for ameliorating sustainable agricultural production. This approach aims to reduce the use of agrochemicals and minimize environmental pollution. Scope This review provides an updated insight into the ecological impact of plant growth-promoting rhizobacteria (PGPR), focusing on the resident microbiome and its potential transferability to the next generation of plants. Conclusion In this context, PGPR are assumed to alter the rhizosphere microbiome by outcompeting the existing taxa through nutrient deprivation, acidification of the environment, metabolites production, and consequently, increasing the copiotrophic taxa. Such modifications can maximize the beneficial interactions of plant-PGPR by increasing the bioavailability of nutrients and handling diverse signaling pathways. The effects of interactions within the PGPR-root system can adjust the composition of root exudates and influence the release of bioactive molecules by the root, especially under stress conditions, which can act as signals to reactivate and recruit the beneficial microbes in the rhizosphere and endosphere in favor of the plants. Such changes in microbiome structure can occur gradually over time, even if the survival rate of PGPR in soil and their re-colonization efficiency inside plant tissue are limited. The aforementioned modifications in the rhizosphere and plant microbiome have the potential to increase the survival chances of the progeny plants growing under the same stress conditions. Establishing a comprehensive and robust knowledge framework that addresses all of these issues is critical for significantly advancing the field of microbe-plant interactions and for developing reliable applications of PGPR.

Production of Reverse Transcriptase and DNA Polymerase in Bacterial Expression Systems.

DNA amplification and reverse transcription enzymes have proven to be invaluable in fast and reliable diagnostics and research applications because of their processivity, specificity, and robustness. Our study focused on the production of mutant Taq DNA polymerase and mutant M-MLV reverse transcriptase in the expression hosts Vibrio natriegens and Escherichia coli under various expression conditions. We also examined nonspecific extracellular production in V. natriegens. Intracellularly, M-MLV was produced in V. natriegens at the level of 11% of the total cell proteins (TCPs) compared with 16% of TCPs in E. coli. We obtained a soluble protein that accounted for 11% of the enzyme produced in V. natriegens and 22% of the enzyme produced in E. coli. Taq pol was produced intracellularly in V. natriegens at the level of 30% of TCPs compared with 26% of TCPs in E. coli. However, Taq pol was almost non-soluble in E. coli, whereas in V. natriegens, we obtained a soluble protein that accounted for 23% of the produced enzyme. We detected substantial extracellular production of Taq pol. Thus, V. natriegens is a suitable alternative host with the potential for production of recombinant proteins.

Distributed clustering model for energy efficiency based topology control using game theory in wireless sensor networks

In this study, we use a topology control technique to tackle the issue of energy balance and consumption minimization in wireless sensor networks. By maintaining network connection while sensibly adjusting the transmission power level, such an algorithm may reduce and balance energy usage. This study provides an energy welfare topological control using a game-theoretic approach by calculating energy welfare as usefulness metric for energy populations using the welfare function from the social sciences. Energy balance occurs when every node works to improve its local society's energy situation to the best of its ability. We demonstrate that the consequence ant game is an intriguing game with a single Nash equilibrium that is Pareto optimum. According to economic theory, Pareto optimality is a situation in which improving one person's circumstances would always make another person's worse off. We demonstrate our suggested methodology's superiority in establishing energy balance and efficiency in wireless sensor networks by contrasting the simulation results of our algorithm with those of other approaches. Our approach surpasses existing methods by a wide margin. For reliable and long-lasting wireless sensor applications, this study offers insightful information about how to maximize network performance while preserving energy resources.

Establishing evidence criteria for implementation strategies in the US: a Delphi study for HIV services

BackgroundThere are no criteria specifically for evaluating the quality of implementation research and recommending implementation strategies likely to have impact to practitioners. We describe the development and application of the Best Practices Tool, a set of criteria to evaluate the evidence supporting HIV-specific implementation strategies.MethodsWe developed the Best Practices Tool from 2022–2023 in three phases. (1) We developed a draft tool and criteria based on a literature review and key informant interviews. We purposively selected and recruited by email interview participants representing a mix of expertise in HIV service delivery, quality improvement, and implementation science. (2) The tool was then informed and revised through two e-Delphi rounds using a survey delivered online through Qualtrics. The first and second round Delphi surveys consisted of 71 and 52 open and close-ended questions, respectively, asking participants to evaluate, confirm, and make suggestions on different aspects of the rubric. After each survey round, data were analyzed and synthesized as appropriate; and the tool and criteria were revised. (3) We then applied the tool to a set of research studies assessing implementation strategies designed to promote the adoption and uptake of evidence-based HIV interventions to assess reliable application of the tool and criteria.ResultsOur initial literature review yielded existing tools for evaluating intervention-level evidence. For a strategy-level tool, additions emerged from interviews, for example, a need to consider the context and specification of strategies. Revisions were made after both Delphi rounds resulting in the confirmation of five evaluation domains – research design, implementation outcomes, limitations and rigor, strategy specification, and equity – and four evidence levels – best, promising, more evidence needed, and harmful. For most domains, criteria were specified at each evidence level. After an initial pilot round to develop an application process and provide training, we achieved 98% reliability when applying the criteria to 18 implementation strategies.ConclusionsWe developed a tool to evaluate the evidence supporting implementation strategies for HIV services. Although specific to HIV in the US, this tool is adaptable for evaluating strategies in other health areas.

Multicenter external validation of prediction models for clinical outcomes after spinal fusion for lumbar degenerative disease

BackgroundClinical prediction models (CPM), such as the SCOAP-CERTAIN tool, can be utilized to enhance decision-making for lumbar spinal fusion surgery by providing quantitative estimates of outcomes, aiding surgeons in assessing potential benefits and risks for each individual patient. External validation is crucial in CPM to assess generalizability beyond the initial dataset. This ensures performance in diverse populations, reliability and real-world applicability of the results. Therefore, we externally validated the tool for predictability of improvement in oswestry disability index (ODI), back and leg pain (BP, LP).MethodsProspective and retrospective data from multicenter registry was obtained. As outcome measure minimum clinically important change was chosen for ODI with ≥ 15-point and ≥ 2-point reduction for numeric rating scales (NRS) for BP and LP 12 months after lumbar fusion for degenerative disease. We externally validate this tool by calculating discrimination and calibration metrics such as intercept, slope, Brier Score, expected/observed ratio, Hosmer–Lemeshow (HL), AUC, sensitivity and specificity.ResultsWe included 1115 patients, average age 60.8 ± 12.5 years. For 12-month ODI, area-under-the-curve (AUC) was 0.70, the calibration intercept and slope were 1.01 and 0.84, respectively. For NRS BP, AUC was 0.72, with calibration intercept of 0.97 and slope of 0.87. For NRS LP, AUC was 0.70, with calibration intercept of 0.04 and slope of 0.72. Sensitivity ranged from 0.63 to 0.96, while specificity ranged from 0.15 to 0.68. Lack of fit was found for all three models based on HL testing.ConclusionsUtilizing data from a multinational registry, we externally validate the SCOAP-CERTAIN prediction tool. The model demonstrated fair discrimination and calibration of predicted probabilities, necessitating caution in applying it in clinical practice. We suggest that future CPMs focus on predicting longer-term prognosis for this patient population, emphasizing the significance of robust calibration and thorough reporting.

Tribological and mechanical properties improvement of G20CrNiMo alloy via fabricating gradient composite layer through ultrasonic strengthening grinding process

Fretting wear is one of the main causes of damage failure at the contact interface, which significantly limits the reliable application of mechanical parts. To address this issue, a composite microstructure comprising a gradient structure, α-Al2O3 particles, and micro-dimples was fabricated on the G20CrNiMo alloy by an improved method of ultrasonic strengthening grinding process (USGP). Subsequently, the fretting resistance and mechanical properties of the treated G20CrNiMo alloy were investigated. The results indicated that USGP could significantly enhance mechanical strength and wear resistance properties. The USGP-treated sample demonstrated an increment of approximately 25.32 % in tensile strength compared to the untreated sample. It also exhibited reductions of about 19.61 % and 49.56 % in friction coefficient and wear volume, respectively. After USGP treatment, the gradient structure incorporating dense dislocation and high-angle grain boundaries (HAGBs) limited the shear motion of the G20CrNiMo alloy, thereby enhancing its mechanical properties. Furthermore, the synergistic effect of gradient structure, Al2O3 particles, and micro-dimples effectively restricted shear deformation and formed a supplementary glaze to further improve its fretting wear resistance.

Hierarchical flower-like ytterbium benzene-1,3,5-tricarboxylate metal organic framework for simultaneous sensitive electrochemical detection of Cd2+, Pb2+ and Cu2+

Hierarchical electrochemical sensors with specific recognition function have been widely applied for trace amounts detection of metal ions, showing great significance for monitoring environmental quality. Herein, a novel flower-like ytterbium benzene-1,3,5-tricarboxylate metal-organic framework (Yb-MOF-1) was prepared by a one-step solvothermal method, which was then cast on a glassy carbon electrode to construct a sensing platform. Compared to the traditional rod-like Yb-MOF-2 prepared at a lower pH (pH = 4.26), the Yb-MOF-1 assembled from ultrathin nanosheets has a large surface area (462.356 m²/g), showing simultaneous electrochemical detection performance towards Cd2+, Pb2+ and Cu2+ in aqueous solution with detection limits of 9.22, 1.69, 15.15 nM, respectively. The experimental results demonstrate its good anti-interference and repeatability. The reliable practical application of Yb-MOF-1 for Cd2+, Pb2+ and Cu2+ detection in real water samples shows good recovery rates ranging from 95.8 % to 103.5 %, proving the effective strategy in exploring efficient electrochemical sensing materials.

Bidirectional Zero Poisson's Ratio Elastomers with Self‐Deformable Soft Mechanical Metamaterials for Stretchable Displays

AbstractStretchable displays, capable of reversible expansion, represent significant advancements in free‐form display technologies. However, the high Poisson's ratio (ν) of elastomer substrates leads to unintended deformation under tensile strain, resulting in image warping. To address this, a meta‐elastomer (ME) substrate with a bidirectional zero ν, incorporating a self‐deformable soft mechanical metamaterial (MM) frame, is introduced. The ν of the ME is precisely programmed by the interaction between the deformation of the MM frame, which exhibits a negative ν, and the elastomer matrix, which has a positive ν. The soft MM frame, stiffer than the elastomer matrix, undergoes both structural deformation and length alteration during substrate tensile strain. This synergistic effect enables achieving a nearly bidirectional zero ν, thus overcoming the limitations of conventional tessellated rigid MM composites. Furthermore, the ME substrate, which is chemically cross‐linked at the junction interface, demonstrates exceptional mechanical robustness, enduring over 180% stretching and more than 10 000 cycles. By counteracting the Poisson's effect, the ME substrate with an integrated pixel array ensures translational pixel movement along the tensile axis during bidirectional stretching, minimizing undesired pixel movement in other directions. The stretchable ME presents key advancements for implementing more stable and reliable stretchable display applications.

A theoretical framework for identifying sociocultural factors that influence nurses' compliance with early warning systems for acute clinical deterioration: A cross-sectional survey

BackgroundSystematic adoption of early warning systems in healthcare settings is dependent on the optimal and reliable application by the user. Psychosocial issues and hospital culture influence clinicians' patient safety behaviours. Objective(i) To examine the sociocultural factors that influence nurses' EWS compliance behaviours, using a theory driven behavioural model and (ii) to propose a conceptual model of sociocultural factors for EWS compliance behaviour. DesignA cross-sectional survey. SettingNurses employed in public hospitals across Queensland, Australia. ParticipantsUsing convenience and snowball sampling techniques eligible nurses accessed a dedicated web site and survey containing closed and open-ended questions. 291 nurses from 60 hospitals completed the survey. MethodsQuantitative data were analysed using ANOVA or t-tests to test differences in means. A series of path models based on the theory were conducted to develop a new model. Directed or theory driven content analysis informed qualitative data analysis. ResultsNurses report high levels of previous compliance behaviour and strong intentions to continue complying in the future (M=4.7; SD 0.48). Individual compliance attitudes (β 0.29, p<.05), perceived value of escalation (β 0.24, p<.05) and perceived ease or difficulty complying with documentation (β −0.31, p<.05) were statistically significant, predicting 24% of variation in compliance behaviour. Positive personal charting beliefs (β 0.14, p<.05) and subjective norms both explain higher behavioural intent indirectly through personal attitudes. High ratings of peer charting beliefs indirectly explain attitudes through subjective norms (β 0.20, p<.05). Perceptions of control over one's clinical actions (β −0.24, p<.05) and early warning system training (β −0.17, p<.05) directly contributed to fewer difficulties complying with documentation requirements. Prior difficulties when escalating care (β −0.31, p<.05) directly influenced the perceived value of escalating. ConclusionsThe developed theory-based conceptual model identified sociocultural variables that inform compliance behaviour (documenting and escalation protocols). The model highlights areas of clinical judgement, education, interprofessional trust, workplace norms and cultural factors that directly or indirectly influence nurses' intention to comply with EWS protocols. Extending our understanding of the sociocultural and system wide factors that hamper nurses' use of EWSs and professional accountability has the potential to improve the compliance behaviour of staff and subsequently enhance the safety climate attitudes of hospitals. Tweetable abstractA newly developed model reports nurse's personal attitudes, peer influence, perceived difficulties encountered documenting and escalation beliefs all predict early warning system compliance behaviour.

Nomogram to Predict Tube Occlusion During Hyperthermic Intraperitoneal Chemotherapy for Pseudomyxoma Peritonei.

To investigate the factors contributing to the blockage of perfusion tubes during hyperthermic intraperitoneal chemotherapy (HIPEC) in patients with appendiceal pseudomyxoma peritonei (PMP) undergoing combined cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy treatment, and to construct a nomogram for predicting the risk of tube occlusion. Observational study. Place and Duration of the Study: Department of Gastrointestinal Surgery, Central Hospital Affiliated to Shandong First Medical University, Jinan, China, from June 2017 to December 2023. Tube occlusion was defined as the inability to achieve 30 minutes of continuous unobstructed perfusion. Statistical methods such as univariate analysis, multivariate analysis, and Lasso regression were employed for data analysis. The results revealed that 27% of the 383 hyperthermic intraperitoneal chemotherapy perfusion treatments resulted in the tube occlusion events. Multivariate logistic regression analysis identified age, CA-125, CA19-9, and pathological type as the independent risk factors. A nomogram predicting the tube occlusion was constructed and validated for its predictive accuracy and clinical utility. This study successfully developed a nomogram to predict the tube occlusion risk during cytoreductive surgery combined with hyperthermic intraperitoneal chemotherapy treatment for patients with pseudomyxoma peritonei, providing valuable guidance for clinical practice and aiding in personalised treatment decisions to improve patient prognosis. However, further research is needed to validate the reliability and clinical applicability of the model, as well as to investigate the impact of tube occlusion on treatment outcomes and corresponding management strategies. Pseudomyxoma peritonei, Cytoreductive surgery, Hyperthermic intraperitoneal chemotherapy treatment, Tube occlusion, Nomogram.

Machine Learning-Enabled Acoustic Emission Signal Processing for real-time crack growth monitoring in heterogeneous structures

Heterogeneous structures pose unique challenges for structural health monitoring, demanding advanced techniques for early detection of crack propagation. Acoustic Emission (AE) is a non-destructive testing technique that relies on the detection and analysis of stress-induced high-frequency acoustic waves. It is commonly used for identifying and monitoring the development of cracks, defects, or other structural anomalies. However, raw AE data is often noisy and contains background noise and interference, which make them not suitable for reliable real-time crack monitoring applications. This study integrates AE data with machine learning algorithms to provide a proactive and accurate system for continuous crack propagation monitoring. The performance of the proposed approach for features extraction to derive relevant information from the AE signals, data labeling for training machine learning models, and the deployment of these models for real-time monitoring, are discussed.

Structural behavior and mechanical fatigue of plate and shell heat exchangers through finite element analysis

Plate and Shell Heat Exchangers (PSHE) are vital in industries due to their adaptability and efficiency. This study applied the finite element method to analyze PSHE plate behavior, which is challenging to assess experimentally. The equivalent von Mises stress field was determined for four-plate setups under different conditions: internal channel pressure, external channel pressure, and pressure in both branches. Peak stresses were found at corrugation tops during contact, varying stress levels based on operating conditions. Stresses decreased when both branches were pressurized but increased with single-branch pressurization. Internal and external pressure-only scenarios had distinct stress patterns. The chevron angle and corrugation contact points influenced plate stiffness and stress distribution. A fatigue analysis assessed plate lifespan under cyclic loads, with fatigue strength reduction factors applied according to Soderberg, Goodman, and Gerber failure criteria. This comprehensive analysis provides critical insights into PSHE plate performance, aiding in their reliable application in the industry. All numerical data obtained in this work were validated based on experimental studies previously published in the literature for stress and fatigue analysis.

A comparison and an application of reliability, reliability system, hybrid reliability system functions for Rayleigh, Pareto, and Rayleigh Pareto distributions

This study dealt with the analysis of the reliability function for hybrid systems with asymmetric components, where the operating times of these components follow Rayleigh, Pareto, and Rayleigh Pareto distributions, furthermore, we introduced a method of operation based on hybrid systems in order to increase the reliability of the machines operating times. Different simulation experiments were done to estimate the reliability function of these systems using the ML method, then a comparison was made between those estimators, the simulation results proved that the Rayleigh-Pareto distribution gives the best estimate for the reliability functions, also the estimated values for the reliability function for the hybrid parallel-series system greater than the estimated values of the reliability function for the hybrid series-parallel system, finally, the estimated reliability function values of the proposed system are better than the estimated values of the two other systems. In the application part, it was chosen the operating times for the machines of the University House for printing, publishing ,and translation in Baghdad, where the factory management depends on the system hybrid serial-parallel system to operate the factory machines, this system leads to a decrease in the reliability of the operating times of the factory machines to 50% at the first operating hour, but if the blistering hybrid system is followed, i.e. the similar machines are run in parallel, and the different machines are run in series, then the probability that the machinery system will continue to operate for four hours will be 50%.

A stepwise fast leakage localization method applying the strategy of dynamic area narrowing down for large-scale water distribution network

ABSTRACT Urban water distribution networks (WDNs) are facing serious leakage problems. As cities expand, the leakage localization burden on large WDNs gradually increases. Although methods have been widely researched, there is a lack of studies and successful applications for large-scale WDNs. To deal with this, a stepwise fast leakage localization Method, SFLLM, utilizing the `dynamic area narrowing down (DAND)' strategy and coupled leakage features (CLF) is proposed. The SFLLM includes a fast-and-dynamic stage using the DAND strategy to reduce the potential leakage area and an accurate localization stage. Only partial representative candidate locations are required to simulate leakages by DAND, and meantime CLF is used to analyze the leakage similarities so that the localization accuracy and efficiency can be improved. SFLLM was tested on a benchmark WDN, saving more than 88% of simulation by DAND strategy and achieving localization in 11 seconds. The results also proved the enhanced performance of CLF in ensuring the stability of the accuracy against various types of uncertainties that may occur in real WDNs. Moreover, three real burst leaks in an actual large-scale WDN were localized within 205 m in about 22 minutes by SFLLM, showing the method's reliable applicability in guiding field leak exploration.

MassARRAY: a high-throughput solution for rapid detection of foodborne pathogens in real-world settings.

Bacterial foodborne pathogens pose a substantial global public health concern, prompting government agencies and public health organizations to establish food safety guidelines and regulations aimed at mitigating the risk of foodborne illness. The advent of DNA-based amplification coupled with mass spectrometry, known as MassARRAY analysis, has proven to be a highly precise, sensitive, high-throughput, and cost-effective method for bacterial detection. This study aimed to develop, validate, and evaluate a MassARRAY-based assay for the detection and identification of significant enteropathogenic bacteria. The MassARRAY-based assay was developed for the detection of 10 crucial bacterial foodborne pathogens, including Campylobacter coli, Campylobacter jejuni, Clostridium perfringens, Escherichia coli, Enterococcus faecalis, Enterococcus faecium, Listeria monocytogenes, Salmonella spp., Shigella spp., and Staphylococcus aureus. The assay was optimized using the reference gDNA (n = 19), followed by validation using gDNA (n = 85) of reference and laboratory isolates. Additionally, the evaluation of the assay's reaction using a mixture of gDNA from all nine targeted species was performed. The limit of detection of the developed MassARRAY-based assay was determined using bacterial cells. Moreover, the validation method for field samples was evaluated by comparing it with standard microbiological testing methods routinely analyzed. The developed MassARRAY-based assay demonstrated 100% concordance with known bacterial pure cultures. The assay's reaction using a mixture of gDNA from all nine targeted species revealed the MassARRAY's capability to detect all targeted species in a single assay with the lowest concentration of 1 ng/μL of gDNA. The limits of detection of the assay range from 357 ± 101 to 282,000 ± 79,196 cells. Moreover, the validation of the assay in field samples revealed a 100% correlation between the data obtained from the standard microbiological method and the MassARRAY-based assay. These findings suggested that the developed MassARRAY-based assay exhibited the excellence in high-throughput detection of foodborne bacterial pathogens with high accuracy, reliability, and potential applicability within real-world field samples.

A 2D equivalent linear inversion model of bedrock motions in a layered transversely isotropic half-space

Inversion is the process that evaluates input motion on the bedrock from surface motions, primarily for use as input excitation for site seismic response or soil-structure interaction analyses. The paper presents a two-dimensional (2D) equivalent linear inversion model for bedrock motion in a multi-layered transversely isotropic (TI) half-space. Based on the exact dynamic stiffness matrices of TI soil layer and bedrock half-space, an inversion objective function is established from both horizontal and vertical surface acceleration records, and the optimization method is adopted to update the control parameters for the inversion process. Moreover, an equivalent linear method is used to account for the TI soil nonlinearity, thus realizing the nonlinear inversion for bedrock motion and incident angle. The inversion procedure is verified by using a single-layered TI soil profile model with three different materials. The numerical results demonstrate that the bedrock motion and the incident angle in the TI medium can be accurately inversed according to the surface motions and the TI site characteristics, indicating that the inversion method can be used for reliable engineering applications in the TI medium.

Experimental study of biological wastewater recovery using microbial fuel cell and application of reliability and machine learning to predict the system behavior

Today, the water crisis has necessitated wastewater recovery management more than ever. With the advancement of technology and the emergence of microbial fuel cells (MFCs), wastewater treatment has become an exceptional opportunity for electricity production. In the present work, an experimental study has been carried out for the possibility of treating the wastewater of Borujerd textile factories in a period of ten days using an MFC. In order to save time and costs for experimental studies, the reliability analysis has been used to predict the behavior of fuel cells made in simple mode and multi-anode shared cathode mode. In addition, in order to evaluate the performance of MFCs that are made at the experimental level, deep learning has been used to extract comprehensive relationships. Finally, the economic and environmental evaluation of the simple and multi-anode shared cathode MFC has been done. The research results show that the COD removal efficiency in the system constructed for textile wastewater is 73 %, while the constructed fuel cell maximum power density is 281.5 mW/m2 from wastewater recycling. Reliability analysis of the studied system shows that adding anode to the MFC increases its operational life so for a fuel cell with 6-anodes, the life of the fuel cell increases by approximately 74 days. But in the design of an MFC, it is necessary to pay attention to the cost and emission of environmental pollutants, because the increase of the anode increases the costs and emission of environmental pollutants so that the built fuel cell will function in the most optimal way possible.