This paper presents a finite element analysis of the bi-directional orthogonal model, which incorporates individual crack strain separation and tracking. The objective of the research is to expand the current shear friction model to manage bi-directional cracking at any angle, allowing for a more universal model that can be applied to intricate structures and non-proportional loading cases. The proposed model was initially developed as a total strain-based model, with the assumption that crack strains are equivalent to total strains, but was subsequently recalculated to improve accuracy by separating crack strains from total strains. Furthermore, a separate crack strain formulation was created to account for strains in the concrete's uncracked portions and locked-in crack strains. The article then discusses the testing of various convergence methods and loading programs to achieve high convergence. Comparative analyses of the generalized shear friction model with other models for crack orientation and loading cases similar to those of a reinforced concrete membrane are also presented. The MATLAB program successfully applied the bi-directional cracking model for one finite element under a uniform cyclical strain state, using a secant stiffness formulation.

It is meaningful to monitor and identify the concrete cracks as they will seriously reduce the fatigue life of pavement. In this paper a new method based on distributed long-gauge optic fiber sensing is proposed to implement the crack identification. Firstly, the damage indicator, namely strain curve envelope area ratio (SCEAR), is proposed and calculated with the measured strain in time series when the plane goes across the pavement where the sensors are installed. Then the indicators with different sensors are normalization by the value of the indicator from one referenced sensor where damage normally will not happen. If the crack happens within the sensing gauge of the sensor, the value of damage indicator SCEAR from the sensor will increase. Therefore, the crack will be identified with the change of the damage indicator. The effect of the proposed method is first verified by some simulations of prefabricated pavement as the cracks can be accurately identified by the proposed method. Moreover, the influence from the aircraft, such as taxiing position, aircraft load and aircraft type, is not obvious enough to mislead the identification results. Lastly the static loading tests were implemented with one small-scale model of prefabricated concrete pavement in the lab. From the experimental results the prefabricated cracks inside the pavement slab can be identified accurately with the proposes method as the parameter SCEAR is increased by about 100% at the crack position, while it is only changed by about 3% at the undamaged position.

This article raise a topic of critical examination of polypropylene, a key polymeric material, and its extensive application within the automotive industry, particularly focusing on the manufacturing of brake fluid reservoirs. The study aims to enhance the understanding of polypropylene's behavior under mechanical stresses through a series of laboratory destruction tests and numerical simulations, emphasizing the Finite Element Method (FEM). A novel aspect of this research is the introduction of the PEAK parameter, a groundbreaking approach designed to assess the material's resilience against varying states of strain, known as triaxiality. This parameter facilitates the identification of critical areas prone to crack initiation, thereby enabling the optimization of component design with a minimized safety margin, which is crucial for cost-effective production. The methodology involves conducting burst tests to locate crack initiation sites, followed by FEM simulations to determine the PEAK threshold value for the Sabic 83MF10 polypropylene material. The study successfully validates the predictive capability of the PEAK parameter, demonstrating a high correlation between simulated results and actual laboratory tests. This validation underscores the potential of the PEAK parameter as a predictive tool for enhancing the reliability and safety of polypropylene automotive components. The research presented in this article contributes significantly to the field of material science and engineering by providing a deeper insight into the mechanical behavior of polypropylene and introducing an effective tool for predicting crack initiation in automotive components. The findings hold promise for advancing the design and manufacturing processes in the automotive industry, with potential applications extending to other sectors.

Conventional approaches in Structural Health Monitoring (SHM) tend to be complex, destructive, and time-intensive. Additionally, they often require a large number of sensors to thoroughly assess structural integrity. In this study, we present a novel, non-destructive SHM framework based on machine learning (ML) for the accurate detection and localization of structural cracks. This approach leverages a minimal number of strain gauge sensors linked via Bluetooth communication. The framework is validated through empirical data collected from 3D carbon fiber-reinforced composites, including three distinct specimens, ranging from crack-free samples to specimens with up to ten cracks of varying lengths and depths. Strain data from five sensors were analyzed using a combination of Shewhart charts, Grubbs Test (GT), and a hierarchical clustering algorithm, specifically designed to evaluate and classify fractures. Our ML-based framework offers a streamlined and efficient alternative to traditional laboratory procedures, delivering precise crack detection with significant potential for applications in the composites industry.

Motivated by the PEACOC project on metal recovery from solid wastes, an innovative magnetic density separation (MDS) process has been developed for granular material sorting. It has intrinsic advantages over the existing industrialized MDS by eliminating fluid turbulence and particle jamming problems. The new MDS applies an inclined planar magnet and a horizontal basin containing a static magnetic fluid as the separation medium. A particle sliding phenomenon is identified as a feature of the process which could help the separation. The MDS successfully sorted shredded PCBAs to concentrate valuable metals and sorted shredded wires to reduce metallic contaminants in the plastic fractions. A pilot scale facility is introduced to show the design to achieve continuous production and to reduce the consumption of ferrofluid.

Road cracks significantly affect the serviceability and safety of roadways, especially in mountainous terrain. Traditional inspection methods, such as manual detection, are excessively time-consuming, labor-intensive, and inefficient. Additionally, multi-function detection vehicles equipped with various sensors are expensive and not suitable for mountainous roads due to poor conditions. To address these challenges, this study proposes a customized Unmanned Aerial Vehicles (UAV) inspection system designed for automatic crack detection. The system focuses on enhancing autonomous capabilities in mountainous terrains by incorporating embedded algorithms for route planning, autonomous navigation, and automatic crack detection. The slide window method is proposed to enhance the autonomous navigation of UAV flights by generating path planning in mountainous roads. This method compensates for GPS/IMU positioning errors, particularly in GPS-denied or GPS-drift scenarios. Moreover, the YOLOv8 algorithm is introduced to conduct autonomous crack detection from UAV imagery in the offboard module. To validate our UAV inspection system's performance, we conducted several experiments to assess its accuracy, robustness, and efficiency. The experimental results demonstrate that our UAS inspection system accurately estimates the flight trajectory along the mountainous road for autonomous navigation. Furthermore, the experimental detection results also demonstrate that the YOLOv8 algorithm achieves higher recognition accuracy compared to the YOLOv5, and YOLOv7-tiny algorithms, exceeding 3.1%,and 6.8% of mAP, respectively. In summary, the UAV inspection system proposed in this study can provide a useful tool and technological guidance for the regular inspection of mountainous roads.

Numerous image processing techniques (IPTs) have been employed to detect crack defects, offering an alternative to human-conducted onsite inspections. These IPTs manipulate images to extract defect features, particularly cracks in surfaces produced through Additive Manufacturing (AM). This article presents a vision-based approach that utilizes deep convolutional neural networks (CNNs) for crack detection in AM surfaces. Traditional image processing techniques face challenges with diverse real-world scenarios and varying crack types. To overcome these challenges, our proposed method leverages CNNs, eliminating the need for extensive feature extraction. Annotation for CNN training is facilitated by LabelImg without the requirement for additional IPTs. The trained CNN, enhanced by OpenCV preprocessing techniques, achieves an outstanding 99.54% accuracy on a dataset of 14,982 annotated images with resolutions of 1536 × 1103 pixels. Evaluation metrics exceeding 96% precision, 98% recall, and a 97% F1-score highlight the precision and effectiveness of the entire process.

Pavement crack detection is one of the key links in highway pavement maintenance management. In the current road crack detection, the network model easily ignores the shallow geometric features of cracks and cannot extract the key feature information of cracks. Aiming at the above problems, an EC-YOLOX network model is proposed. The CFPN is constructed to cross-fuse different scale features to solve the feature scale invariance. In the strengthen feature extraction layer, ECANet is fused to enhance the ability to pay attention to key information. The WEIoU loss function is proposed, which assigns different penalty terms to the target box in the vertical and horizontal directions. In terms of data, geometric distortion constraint correction is performed on the single-point perspective pavement image. The experimental data show that the accuracy of EC-YOLOX on the self-built data set reaches 76.34% [email protected], which is 4.45% higher than that of YOLOX. The loss curve of EC-YOLOX is smoother than that of YOLOX, and the minimum training loss value is 2.136, which is 0.648 lower than the minimum loss value 2.784 of YOLOX. Many experiments have verified the effectiveness of EC-YOLOX in improving the detection effect in pavement crack detection.

In electromagnetic ultrasonic testing, it is difficult to recognize small-size bottom cracks by time of flight (ToF), and the lift-off fluctuation of the probe affects the accuracy and consistency of the inspection results. In order to overcome the difficulty, a novel EMAT (electromagnetic acoustic transducer)-PEC (pulse eddy current) composite sensor is designed. We use amplitude of bottom echo recorded by EMAT to identify the tiny bottom crack as well as the amplitude of PEC signals picked up by the integrated symmetric coils to measure the average lift-off of the probe in real time. Firstly, the effects of lift-off and bottom cracks on amplitude of bottom echo are distinguished combining the theoretical analysis and finite element method (FEM). And then an amplitude correction method based on the fusion of EMAT and PEC signals is proposed to reduce the impact of lift-off on the defect signal. The experimental results demonstrate that the designed composite sensor can effectively detect the bottom crack as small as 0.1mm* 0.3mm. The signal fusion method can accurately correct the amplitude of defect signal and the relative error is less than ±8%.

Dielectric elastomers, such as thermoplastic polyurethanes (TPU), are widely used as dielectric layer, emulation layer and substrate of flexible and stretchable devices. To construct capacitors and actuators that work stably upon deformation, it has become an urgent need to investigate the evolution of dielectricity under stress and strain. However, the lack of effective methods for estimating the dielectric constant of elastomers under strain poses a big challenge. This article reports a device for in-situ measuring the dielectric constant of TPU under strain. It is found that upon stretching TPU to a strain of 400%, its dielectric constant decreases from 8.47 to 2.94. In addition, combined Fourier-transform infrared spectroscopy, X-ray scattering technique, and atomic force microscopy have been utilized to characterize the evolution of microstructure under strain. The investigation under tensile strain reveals that a decreased density and average size of polarized hard domains, along with a tendency of the molecular chains to align in parallel with the tensile stress. The evolution of the microstructures results in a reduction of the dielectric constant parallel to the electric field in TPU. Our work provides valuable experimental reference for improving the stability of flexible sensors and actuators based on dielectric elastomers.

One of the major concerns in structural health management (SHM) is the early detection of a growing crack. Using this, future damage due to crack propagation can be mitigated or eliminated by implementing proper repair and maintenance. Acoustic Emission (AE) is a non-destructive testing (NDT) method with potential applications for locating and monitoring fatigue cracks. The research presented in this paper focuses on SHM using AE. A novel AE signal analysis approach was proposed in order to detect crack initiation and assess small crack lengths. Experimental investigation indicated that initiation of a crack could be identified through the statistical analysis of the resulting features of the AE signals. A probabilistic AE-based model for small fatigue crack sizing was developed and the uncertainties of the model were estimated. In addition, a probabilistic model validation approach was implemented to confirm accurate estimation of the results. The outcome of this research can be used to evaluate the integrity of structures under fatigue loading. The proposed approach can also be applied as an approach to manage health and assess prognosis of structures.

The holistic approach of One Health, which sees human, animal, plant, and environmental health as a unit, rather than discrete parts, requires not only interdisciplinary cooperation, but standardized methods for communicating and archiving data, enabling participants to easily share what they have learned and allow others to build upon their findings.Ongoing work by NCBI and the GenomeTrakr project illustrates how open data platforms can help meet the needs of federal and state regulators, public health laboratories, departments of agriculture, and universities. Here we describe how microbial pathogen surveillance can be transformed by having an open access database along with Best Practices for contributors to follow. First, we describe the open pathogen surveillance framework, hosted on the NCBI platform. We cover the current community standards for WGS quality, provide an SOP for assessing your own sequence quality and recommend QC thresholds for all submitters to follow. We then provide an overview of NCBI data submission along with step by step details. And finally, we provide curation guidance and an SOP for keeping your public data current within the database. These Best Practices can be models for other open data projects, thereby advancing the One Health goals of Findable, Accessible, Interoperable and Re-usable (FAIR) data.

As the number of end-of-life vehicles continues to grow, the field of separation technology for broken copper and aluminium parts of end-of-life vehicles has emerged as a significant area of research. As a key technology for the separation of non-magnetic non-ferrous metals, such as copper and aluminium, eddy current separation can achieve efficient separation of non-magnetic non-ferrous metals according to their differing conductivity and density. Nevertheless, further research is required in the separation of large-scale broken copper and aluminium parts of end-of-life vehicles. This paper presents a novel magnetic roller model comprising circumferential and axial periodic arrangements of permanent magnets. A single permanent magnet was constructed as an equivalent current model, and the magnetic scalar potential equations were solved using simulation tools. This allowed the distribution of the magnetic field outside the magnetic roller to be studied. The results demonstrate that the novel permanent magnet array magnetic roller can enhance the magnetic field intensity and action distance of the external magnetic field, which is more conducive to the separation of large-scale broken copper and aluminium parts of scrap cars. The findings of this research provide a theoretical foundation for the separation of scrap car broken copper and aluminium parts.

This article presents research on selected materials with the aim of determining their rare earth element (REE) content and attempting to intensify it. The test material was coal slurry, which is a waste product from the operation of a preparation plant of a closed coal mine. Research on REE concentration intensification tests was carried out using magnetic separation. Laboratory analyses determining the REE content in the samples obtained, were carried out using the inductively coupled plasma ionisation mass spectrometry (ICP-MS) technique. Carrying out this research by the KOMAG Institute of Mining Technology, is a continuation of work related to making mining waste economically useful and determining a new source of REE recovery. Previous research and development work showed REE content (scandium 40.49 ppm) in the coal slurries studied. The result of the work carried out is the determination of the economic utility of REE recovery from the studied waste.

Lactoperoxidase (LP), which is a high-value minor whey protein, has recently drawn extensive attention from research scientists and industry due to its multi-function and potential therapeutic applications. In this study, the separation and optimization of two similar-sized proteins, LP and lactoferrin (LF) were investigated using strong cation exchange column chromatography. Optimization was started with central composite design based experiments to characterize the importance of different decision variables. The three variables used in the optimization were flow rate, length of gradient and final salt concentration in the linear elution gradient step. The obtained empiric functional model represented the effect of the significant factors on the yield as the objective function. Afterwards, the calibrated mechanistic model was employed to predict accurate optimal set of variables. The optimal operating points were found and the results were compared with validation experiments. Predictions respecting yield confirmed a very good agreement with experimental results while keeping purity, a product quality characteristic, equal or above to a predefined value.

A dynamic impact test was performed on as-rolled AZ31 alloy with gradient microstructure under various strains. The microstructural evolution and mechanical properties were systematically investigated. As the strain rate gradually increases, an increasing number of twins are formed, facilitating dynamic recrystallization (DRX), and the mechanical properties are also gradually improved as well. The microstructure becomes heterogeneous at higher strain rates, but the peak stress decreases. The impact process results in significantly higher performance due to microstructural refinement, work hardening by dislocations and precipitates. In addition, both the adiabatic shear band and the adjacent crack experience a temperature rise that exceeds the recrystallization temperature of the alloy. This observation also explains the presence of ultrafine recrystallized grains within the adiabatic shear band and the appearance of molten metal around the crack.

In the case of a Cu-Mo-W polymetallic ore, the wastewater from the scheelite cleaning flowsheet contains large amounts of residual flocculants and metal ions, and the separation of chalcopyrite and molybdenite require a large number of environmentally harmful depressants. Therefore, it is necessary to find new methods to reduce the environmental and cost pressures of wastewater treatment and the use of depressants. In this work, the flotation wastewater from scheelite cleaning flowsheet for the separation of chalcopyrite and molybdenite by selective surface passivation was investigated for the first time. Flotations of single minerals and artificially mixed minerals with or without immersion pretreatment in the presence and absence of aeration were performed. The results showed that pulp pH had no effect on the flotation of either mineral, and a molybdenite recovery of 93.22% with chalcopyrite recovery of 10.77% was achieved under the conditions of 10 days of immersion pretreatment with aeration, 350 mg/L of kerosene, and 100 mg/L of MIBC. By combining the electrochemical cyclic voltammetry analysis and characterization by XRD and SEM, the selective surface passivation mechanism of chalcopyrite was discussed, which could be due to the coverage of the insoluble oxidation products, especially jarosite. This work has simultaneously achieved the depressant-free flotation separation of molybdenite and chalcopyrite and the reuse of scheelite flotation wastewater, which is of great significance for environmental protection and cost saving.

A reliable and efficient rail track defect detection system is essential for maintaining rail track integrity and avoiding safety hazards and financial losses. Eddy current (EC) testing is a non-destructive technique that can be employed for this purpose. The trade-off between spatial resolution and lift-off should be carefully considered in practical applications to distinguish closely spaced cracks such as those caused by rolling contact fatigue (RCF). A multi-channel eddy current sensor array has been developed to detect defects on rails. Based on the sensor scanning data, defect reconstruction along the rails is achieved using an inverse algorithm that includes both direct and iterative approaches. In experimental evaluations, the EC system with the developed sensor is used to measure defects on a standard test piece of rail with a probe lift-off of 4-6 mm. The reconstruction results clearly reveal cracks at various depths and spacings on the test piece.

This review delves into the growing field of flexible and stretchable strain sensors utilized in human gait analysis, focusing on determining knee bending angle and muscle activities when a human subject walks. Recent advancements have enabled these sensors to accurately capture biomechanical parameters while accommodating the body's natural movements. We examine the principles underlying these sensors' design and fabrication techniques, emphasizing their flexibility, stretchability, and biocompatibility for seamless integration into wearable systems. Through critical evaluation of existing methodologies, we assess the reliability and validity of these sensors in quantifying gait parameters. Furthermore, we discuss this technology's clinical and research implications, highlighting its potential in personalized rehabilitation and sports performance optimization. We provide an overview of flexible strain sensors and their application for analyzing human walking gait, especially for observing walking gait in rehabilitation programs. First, we present the basic working principles of various flexible strain sensors. Second, by the application of flexible strain sensors as walking gait monitoring. Finally, current challenges and future opportunities in this research area are discussed. By synthesizing current knowledge and outlining future directions, this review aims to provide insights for researchers and practitioners seeking to leverage flexible and stretchable strain sensors for comprehensive human gait analysis.

The problems of modeling the human bladder and its stress-strain state under external static influence were considered. A method for identification of the anisotropic biomechanical characteristics of bladder tissue was proposed. A FEM model was created, which accepts into regard that the bladder is surrounded by fiber and affected by surrounding organs, and partially protected by pelvic bones. The model considered the presence of constant hydrostatic pressure on the walls of the bladder when it is full. It has been shown that isotropic mechanical characteristics of biological tissue can be used for studying the deformed state of a filled bladder if the filled bladder 300 ml is considered as initial non-deformed stage. This was shown by modeling and verification the effect of the external static force on the bladder. Numerical experiments were conducted based on the constructed model. To validate the results obtained, a series of natural experiments on the effect of external pressure on the bladder under ultrasound control was conducted. In the future, it is planned to use the constructed model to study rupture deformations of the bladder under the influence of static and dynamic loads.

This paper conducts an extensive literature review focusing on the utilisation of crack tip plasticity as a crucial parameter in determining and enhancing crack growth models. The review encompasses a comprehensive analysis of various methodologies, predominantly emphasising numerical simulations of crack growth models while also considering analytical approaches. Although experimental investigations are not the focus of this review, their relevance and interplay with numerical and analytical methods are acknowledged. The paper critically examines these methodologies, providing insights into their advantages and limitations. Ultimately, this review aims to offer a holistic understanding of the role of crack tip plasticity in the development of effective crack growth models, highlighting the synergies and gaps between theoretical, experimental, and simulation-based approaches.

In this paper, we investigated the formation isolation regulation issue regarding multiple autonomous underwater vehicles (AUVs) characterized by a "leader-follower" framework. Considering the cooperative-competitive relationship among the follower AUVs and the impact of unknown external disturbances, an extended state observer was designed based on backstepping to mitigate these disturbances, and an event-triggered control scheme was designed to realize the two-part consensus control within the multi-AUV system. Through rigorous theoretical analysis, it is shown that the system achieves asymptotic steadiness and is free from zeno behavior under the proposed event-triggered control scheme. Finally, numerical simulations confirm the efficiency of the regulation strategy in achieving formation separation within the multi-AUV, where the trajectory tracking errors of individual AUVs gather in a compact vicinity close to the source and the structure converges was achieved, with the absence of zeno behavior also demonstrated.

With the offshore oil-gas fields entering decline phase, high-efficiency separation of oil-gas-water mixtures becomes a significant challenge. As essential equipment for separation, the three-phase separators play a key role in Offshore Oil-Gas production. However, level control is critical in the operation of three-phase gravity separators on offshore facilities, as it directly affects the efficacy and safety of the separation process. This paper introduces an advanced deep deterministic policy gradient with adaptive learning rate weights (ALRW-DDPG) control algorithm, which improves the convergence and stability of the conventional DDPG algorithm. An adaptive learning rate weight function is meticulously designed, and an ALRW-DDPG algorithm network is constructed for simulating three-phase separator liquid level control. The effectiveness of the ALRW-DDPG algorithm is subsequently validated through simulation experiments. The results show that the ALRW-DDPG algorithm achieves a 15.38% improvement in convergence rate compared to the traditional DDPG algorithm, and the control error is significantly smaller than that of PID and DDPG algorithms.

Fabrication of durable materials with excellent oil adsorption capacity and separation performance for the treatment of oily wastewater is meaningful based on smart responsiveness. Herein, a solvent-responsive melamine sponge (MS) was developed via silanization followed by the in-situ growth of zeolitic imidazolate framework-8 (ZIF-8). Detailed characterization of the resultant composite MS was conducted using scanning electron microscopy (SEM), energy dispersive spectrometer (EDS), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). The multiscale hierarchical MS substrate exhibited highly hydrophobic property in the pH range of 1-11, along with a satisfactory adsorption capacity in the range of 65.4-134.2 g/g for different oils. The modified surface transformed from superhydrophobicity/superlipophilicity to superhydrophilicity/underwater superoleophobicity upon ethanol wetting, reverting to its original superhydrophobic state upon drying. The separation flux of the MS substrate was above 1.5×104L/m2h for both oil and water removal, along with the separation efficiency more than 98.7%. No obvious changes of the separation performance after 50 successive immiscible oil/water separation indicated the excellent durability and robustness of the anchored ZIF-8 nanoparticles on the surface of modified MS substrate. More importantly, oil-in-water emulsion separation was successfully carried out via the ZIF-8 MS composite with a high separation efficiency over 99.1%. The developed smart sponge with high oil absorption capacity, excellent chemical stability and fire resistance exhibited a wide range of potential practical applications in the convenient treatment of oily wastewater.

This paper seeks to model the crack propagation in of AAs (aluminum-alloys) 2524-T3 and 7050-T7452 subjected to fatigue loading at low temperature. Fatigue crack growth tests were performed on AAs 2524-T3 and 7050-T7452 subjected to constant-amplitude and actual random-spectra loading histories at room temperature of about 25 °C and at cryogenic temperature of -70 °C, respectively, to determine their crack growth properties and residual lives. The interaction mechanisms between cryogenic temperature and the fatigue load were deduced on the basis of the results of fractographic analysis. Temperature-dependent residual lives under actual random-spectrum load history were modeled based on a modified accumulation damage rule by accounting for the load interaction. Good correlation was achieved between the predictions and actual experiments, demonstrating the practical and effective use of the proposed method.

Abstract: Toxicity of emerging organic pollutants to photosystems of aquatic plants are still not well clarified. This study aimed to develop a novel ecotoxicological experimental protocol based on nanoscale electrochemical mapping of photosynthetic oxygen evolution of aquatic plants by SECM (scanning electrochemical microscopy). The protocol was also checked by confocal laser scanning microscopy (CLSM), the traditional Clark oxygen electrode method and chlorophyll fluorescence technique. The typical persistent organic pollutant 2,4-dichlorophenol (2,4-DCP) in water environment and the common aquatic Microsorium pteropus (M. pteropus) were chosen as the model organic pollutant and tested plant, respectively. It was found that the SECM method could well discriminated the responses of stoma micromorphology and spatial pattens of photosynthetic oxygen evolution on single stoma. The shape of stoma blurred with increasing 2,4-DCP concentration, which was in good agreement with the CLSM images. The dose-response curves and IC50 values obtained from the SECM data were verified by the data measured by the traditional Clark oxygen electrode method and chlorophyll fluorescence test. The IC50 value of single stoma oxygen emission of 24 h exposed plant leave, which was derived from the SECM current data (32535 μg L-1), was close to those calculated from the maximum photosynthetic efficiency (Fv/Fm) measured by chlorophyll fluorescence test (33963 μg L-1), and the Clark oxygen electrode method photosynthetic oxygen evolution rate (32375 μg L-1). The 72 h and 96 h 2,4-DCP exposure data further confirmed the reliability of the nanoscale stoma oxygen emission mapping methodology for ecotoxicological assessment. In this protocol, the procedures for how to collect effective electrochemical data and how to extract useful information from the single stoma oxygen emission pattern were well established. This study showed that SECM is a feasible and reliable ecotoxicological tool for evaluation of toxicity of organic pollutants to higher plants with unique nanoscale visualization advantage over the conventional methods.

Dye/salt separation has gained increasing attention in recent years, prompting the quest for cost-effective and environmentally-friendly raw materials for synthesis high performance nanofiltration (NF) membrane for effective dye/salt separation. Herein, a high-performance loose structured NF membrane was fabricated by via a simple vacuum filtration method using a green nanomaterial, 2,2,6,6-tetramethylpiperidine-1-oxide radical (TEMPO)-oxidized cellulose nanofiber (TOCNF), by sequentially filtrating larger-size and finer-size TOCNFs on a microporous substrate, followed by cross-linked with trimesoyl chloride. The resultant TCM membrane possesses a separating layer composed entirely of pure TOCNF, eliminating the need for other polymer or nanomaterials additives. TCM membranes exhibits high performance and effective dye/salt selectivity. Scanning Electron Microscope (SEM) analysis shows that the TCM membrane with Fine-TOCNF layer has a tight layered structure. Further characterizations via Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) confirm the presence of functional groups and chemical bonds of the crosslinked membrane. Notably, the optimized TCM-5 membrane exhibits a rejection rate of over 99% for various dyes (Congo red, orange yellow) and 14.2% for NaCl, showcasing a potential candidate for efficient dye wastewater treatment.

This article presents a new input device for spastic patients and others with similar symptoms. The sensor consists of a disc used to determine positions and can replace standard joysticks in medical devices such as electric-powered wheelchairs. Using a standard joystick while operating a powered wheelchair can result in dangerous situations when spastic movements occur and extremities cramp making them uncontrollable. To avoid this, a disc was developed that can be controlled with any body part. By shifting weight (x- and y-axis) the disc can tilt in any direction creating a proportional output signal and can also be pushed down in the center (z-axis) to open a menu on a screen for example. When spasms occur it is impossible for users to get stuck on the input device because the disc is flat and can be mounted within a control panel. Body parts coming into contact with the disc would merely slide across the disc without triggering unintentional actions. The sensor presented here is also adaptive and can be adjusted to fit a user’s strength and range of motion. This proposal aims to develop an input device that enables spastic patients to operate sensitive systems safely.

Temperature-responsive separation membranes can significantly change their permeability and separation properties in response to changes in their surrounding temperature, improving efficiency and reducing membrane costs. This study focuses on the modification of commercial polyvinylidene fluoride (PVDF) membranes with amphiphilic temperature-responsive copolymer and inorganic nanoparticles. We prepared an amphiphilic temperature-responsive copolymer which the hydrophilic poly(N-isopropyl acrylamide) (PNIPAAm) was side-linked to a hydrophobic polyvinylidene fluoride (PVDF) skeleton. Subsequently, PVDF-g-NIPAAm polymer and graphene oxide (GO) blended with PVDF to prepare temperature-responsive separation membranes. The results showed that temperature-responsive polymers with different NIPAAm grafting ratios were successfully prepared by adjusting the material ratio of PVDF to NIPAAm. PVDF-g-NIPAAm was blended with PVDF with different grafting ratios to obtain separate membranes with different temperature responses. GO and PVDF-g-NIPAAm formed a relatively stable hydrogen bond network, which improved the internal structure and mechanical properties of the membrane without affecting the temperature response, thus extending the service life of the membrane.

Background and Objectives: High job strain is worsening the outcome in coronary artery disease, CAD. Severe dissatisfaction on workplace, imbalance between high demands , and low rewards, are affecting the quality of life, and diminishing the duration of life, especially in CAD patients. Our study included two samples : CAD patients (experimental group), and without CAD patients, but with traditional risk factors (control group). The main objective of the study was the role played by high sensitivity C reactive protein, hs CRP, and microalbuminuria, as mediators of job strain and CAD relationship. Secondary objectives were the following: identification of the most vulnerable patients( with significant job strain) and intervention towards this category, for cardiovascular events prevention (primary or secondary). Materials and Methods: The utilized methods were the following : clinical exam; electrocardiogram; echocardiogram; non contrast enhanced computed chest tomography; laboratory findings ( lipid profile, glycemia, hs CRP, microalbuminuria); type D scale, DS 14; depression questionnaire, PHQ-9; and satisfaction with work scale, SWWS. Results: The highest values for hs CRP and microalbuminuria were noticed in patients with the lowest Likert score, for both samples CAD, and without CAD patients. The highest job strain was noticed in females. More than half of CAD patients ,with low Likert scores, revealed myocardial infarction. Conclusions: Microalbuminuria and hs CRP were statistical significant in the study as intercessors, in job strain and CAD relationship. The most vulnerable patients for vascular events were females, in both groups : CAD and “CAD waiting desk”. In CAD sample, the vascular vulnerability was also increased by high job strain.

Vibro-fluidized dry coal beneficiation involves the unavoidable mixing of -1 mm coal dust into the fluidized bed, which compromises the stability and homogeneity of the bed density and reduces the effectiveness of fine-grained coal separation. In order to understand the features of coal powder separation and mixing (-1 mm) in a vibrating fluidized bed, as well as to achieve a uniform and stable bed density, a wide-grained dense medium consisting of -1 mm coal dust and 0.3-0.15 mm magnetite powder was homogeneously mixed in this work. The degree of density separation in the entire bed was examined, as well as the local mixing properties of the Wide-grained Dense Medium. It was discovered that when low vibrational energy was introduced at the same gas velocity, particle separation was enhanced in comparison to the usual fluidized bed. Little bubbles were found to ensnare fine coal dust and migrate upward, increasing density separation. The introduction of high vibrational energy leads to particle disorder within the bed and an increase in the level of particle mixing. The beneficial effects of vibration on the bed are diminished when the gas velocity is gradually increased under specified vibration circumstances. This causes big bubbles to develop more frequently, which increases particle mixing. Among them, the 1-0.5 mm fine-grained coal exhibits the best mixing state; it is less impacted by variations in air velocity and vibration levels, whereas the -0.5 mm coal dust is more affected by each of these variables. Furthermore, a wide range of air velocity regulation without a significant segregation state change was discovered to be achievable by the particle system under vibration circumstances of f=25Hz A=1mm and f=25Hz A=2mm.

1) Background: Ultrasound-based strain imaging is now available in several ultrasound (US) scanners. Strain ratio (SR) can be used to quantify strain recorded simultaneously in two different user-selected areas, ideally exposed to the same amount of stress. The aim of this study was to evaluate SR variability when assessed in an in-vitro setup with a tissue-mimicking phantom, on resected tissue samples and in live tissue scanning with endoscopic applications. 2) Material and methods: Retrospective analysis of SR for quantification of elastic contrasts in a tissue-mimicking phantom containing four homogenous inclusions, in 38 resected bowel wall lesions and in 48 focal pancreatic lesions examined in vivo. Median SR and the inter-quartile range (IQR) was calculated on all external and endoscopic US-applications. The IQR/median provides a measure of the SR variability focusing on the two percentiles of the data closest to the median value. 3) Results: The overall variability of SR was lowest in a tissue-mimicking phantom (mean QR/median SR: 0.07). In resected bowel wall lesions representing adenomas, adenocarcinomas or Crohn lesions, the variability increased (mean IQR/Median: 0.62). During an endoscopic examination of focal pancreatic lesions in vivo, the variability increased further (mean IQR/Median: 2.04). 4) Conclusion: SR variability increased when assessed on different targets with growing heterogeneity and biological variability as one moved from homogeneous media to live tissues and endoscopic application. This may indicate a limitation for the accuracy SR evaluation in clinical applications.

Structural health monitoring has been studied by a number of researchers as well as various industries to keep up with the increasing demand for preventive maintenance routines. This work presents a novel method for reconstruct prompt, informed strain/stress responses at the hot spots of the structures based on strain measurements at remote locations. The structural responses measured from usage monitoring system at available locations are decomposed into modal responses using empirical mode decomposition. Transformation equations based on finite element modeling are derived to extrapolate the modal responses from the measured locations to critical locations where direct sensor measurements are not available. Then, two numerical examples (a two-span beam and a 19956-degree of freedom simplified airfoil) are used to demonstrate the overall reconstruction method. Finally, the present work investigates the effectiveness and accuracy of the method through a set of experiments conducted on an aluminium alloy cantilever beam commonly used in air vehicle and spacecraft. The experiments collect the vibration strain signals of the beam via optical fiber sensors. Reconstruction results are compared with theoretical solutions and a detailed error analysis is also provided.

The extended finite element method (XFEM) is now widely used in crack simulations and the direction of propagation of the XFEM crack in SS-304 has been quite interesting. This paper discusses the direction,θ(+ve in anti-clockwise direction), of the XFEM crack (under mode-I) propagation based on the von Mises stress-field around the crack-tip for static loading under the light water reactors (LWRs) conditions. The Mises core region from the crack-tip is chosen for β=〖90〗^o, the angle between the load and the initial crack. Experimental data for LWRs’environment is obtained and the simulations have been carried out applying three different static loads and results for the direction of the crack are calculated by measuring the stress-field around the crack-tip. It has been found that the direction of the XFEM varies inversely as the stress-field around the crack tip is increased. The computational results have been compared with the numerical results based on the minimum strain energy density criterion[S-criterion].

Leaf springs are critical components for the railway vehicle safety in which they are installed. Although these components are produced in high-strength alloyed steel and designed to operate under cyclic loading conditions in the high-cyclic fatigue region, their failure is still possible to occur and hence lead to economic and human catastrophes. The aim of this document is precisely to characterise the mechanical crack growth behaviour of the 51CrV4 spring steel representative of leaf springs under cyclic conditions, that is, crack propagation in mode I. The common fatigue crack growth prediction models (Paris and Walker) considering the effect of stress ratio and parameters such as propagation threshold, critical stress intensity factor and crack closure ratio are also determined using statistical methods, which resulted in good approximations with respect to the experimental results. Lastly, the fracture surfaces under the different test conditions were analysed using SEM, with no significant differences to declare. As a result of this research work, it is expected that the developed properties and fatigue crack growth prediction models can assist design and maintenance engineers in understanding fatigue behaviour in the initiation and propagation phase of cracks in leaf springs for railway freight wagons.

The insufficient toughness of concrete can lead to the occurrence of crack expansion, ultimately resulting in a decline in the physical and mechanical properties such as bearing capacity and deformation characteristics of structural components. In severe cases, this may lead to brittle failure, where the entire structure and system fail suddenly without significant deformation after being stressed. Additionally, during the process of shear and bending failure of reinforced concrete beams, the cracks generated on the side of the beam are mostly I-II composite cracks. Considering the material nonlinearity and geometric irregularity of reinforced concrete, it is of great significance to study the dynamic evolution law of crack expansion in reinforced concrete members. Based on experimental data, this paper aims to utilize the nonlinear finite element simulation software Abaqus to conduct finite element simulations of crack expansion in simple supported reinforced concrete beams. By accurately controlling the constitutive curves of concrete and reinforcement materials, the design of seismic performance of structural members can be enhanced, thereby making essential contributions to the preliminary analysis of actual crack control engineering. The nonlinear finite element results indicate that the joint cracks of the frame with the floor slab primarily manifest as flexural cracks, with the concrete damage degree of the floor slab being higher than that of the beam. This finding underscores the importance of considering the behavior of concrete and reinforcement materials in designing for seismic performance and crack control in actual engineering applications.

The DEAD-box RNA helicase DDX3X is a multifunctional protein involved in RNA metabolism and stress responses. In this study, we investigated the role of RG/RGG motifs in the dynamic process of liquid-liquid phase separation (LLPS) of DDX3X using cell-free assays and explored their potential link to cancer development through bioinformatic analysis. Our results demonstrate that the number, location, and composition of RG/RGG motifs significantly influence the ability of DDX3X to undergo phase separation and form self-aggregates. Mutational analysis revealed that the spacing between RG/RGG motifs and the number of glycine residues within each motif are critical factors in determining the extent of phase separation. Bioinformatic analysis of cancer genomic datasets uncovered a significant enrichment of DDX3X mutations in RG/RGG motifs across multiple cancer types, particularly in the N-terminal region of the protein. Furthermore, we found that DDX3X is co-expressed with the stress granule protein G3BP1 in several cancer types and can undergo co-phase separation with G3BP1 in a cell-free system, suggesting a potential functional interaction between these proteins in phase-separated structures. DDX3X and G3BP1 may interact through their RG/RGG domains and subsequently exert important cellular functions under stress situation. Collectively, our findings provide novel insights into the role of RG/RGG motifs in modulating DDX3X phase separation and their potential contribution to cancer pathogenesis.

The pursuit of materials that offer both wear comfort and protection for functional and protective clothing has led to the exploration of weft-knitted spacer structures. Traditional cushioning materials such as spacer fabrics and laminated foam often suffer from deformation under compression stresses, thus compromising their protective properties. This study investigates the enhancement of the force absorption, stress-strain and thermal properties of weft-knitted spacer fabrics with inlays. Surface yarns with optimal stretchability and thermal properties are used and combined with elastic yarns in various patterns to fabricate nine different inlay samples. The mechanical and thermal properties of these samples are systematically analyzed, including their compression, stretchability, thermal comfort and surface properties. The results show that the inlay spacer fabric exhibits superior compression properties and thermal conductivity compared to traditional laminated foam and spacer fabrics, while maintaining stretchability, thus providing a better performance than traditional fabrics for protective clothing and wearable cushioning products. This study further confirms that the type of inlay yarn and inlay structure are crucial factors that significantly influence the thermal, tensile and compressive properties of fabric. This research provides valuable insights into the design and development of advanced textile structures to improve wear comfort and protection in functional garment applications.

Separation Distances are used throughout the world to protect people and assets from the potential hazardous effects from propellants, explosives, and pyrotechnics. The current separation distances for Hazard Division (HD) 1.3 substances and articles used in the United States, in some cases, may not adequately protect against the effects from heat flux and debris when those substances and articles are ignited in a confined structure. Multiple tests in such a confined scenario with HD 1.3 substances have shown that the heat flux and debris hazards could result in injury at distances beyond the current specified explosives safety separation distance (ESSD). Herein are recommended ESSD’s for confined as well as unconfined HD 1.3 articles and substances based on the analysis of hundreds of tests. Recommended ESSD’s include a smaller value for unconfined quantities less than 145 kilograms and ESSD’s that are consistent with NATO distances for confined substances and articles.

The presented work offers a novel process scheme for valorizing historical Pb-Zn slag, which involves crushing, grinding, and then using separation techniques to concentrate valuable components (nonferrous metals). This methodology could have a significant impact on the global beneficiation of metallurgical slags since, in theory, it is significantly more simple, environmentally friendly, and cost-effective than standard pyrometallurgical or hydrometallurgical procedures. According to previous physicochemical and mineralogical studies, Pb-Zn slag from "Topilnica" Veles is a valuable secondary raw material. This inhomogeneous technogenic resource contains substantial amounts of nonferrous metals (Pb, Zn, Cu, and Ag). However, laboratory tests have indicated that the Pb-Zn slag contains a very uneven valuable metals amounts, ranging from several g/ton to several tens of g/ton. The main issue is that traditional metallurgical procedures for releasing beneficial elements are not commercially viable since the valuable elements are "trapped" within amorphous aluminosilicates or intergrowths of alloy grains and glassy phases. Gravity concentration (Wilfley 13 shaking table) and magnetic separation (Davis separator and disk separator) were used to obtain the final concentrate following comminution and grindability testing. The gravity concentration proved more effective. This streamlined approach of valorizing Pb-Zn slag can reduce the need for hazardous chemicals used in hydrometallurgical refinement operations, as well as the extremely high temperatures required for pyrometallurgical processing. This is the first investigation into the feasibility of this novel approach, which includes direct investigations of the Pb-Zn slag feed using these alternative technologies. After extracting the valuable metals, the amorphous aluminosilicate part of the Pb-Zn slag can be reapplied as an alternative raw material in the building sector, adding to the circularity of the suggested approach..

This study employs the phase-field regularized cohesion model (PF-CZM) to simulate crack propagation and damage behavior in porous granite. We investigate how pore radius (r), initial crack-pore distance (D), and pore-crack angle (θ) impact crack propagation. The simulation findings reveal that, with a fixed deflection angle and initial crack-pore distance, larger pores are more likely to induce crack extension under identical loading conditions. Moreover, with r and θ keeping constant, the crack extension can be divided into two stages: from its initiation to the lower edge of the pore and then from the lower edge to the upper boundary of the model. By varying the values of D and r, we derive multiple combinations of different D/r ratios and pore radii. These results demonstrate that with constant r, cracks tend to deflect toward the pore closer to the initial crack. Conversely, when D is maintained constant, cracks will preferentially deflect toward pores with a larger r. In summary, the numerical simulation of rock pores and initial cracks, based on the PF-CZM, exhibits remarkable predictive capabilities and holds significant potential in advancing rock fracture analysis.

This study investigates by hybrid approach of classical calculations and numerical explicit FEM simulation the strain rate sensitive hardening of Polypropylene Sabic 83MF10 under dynamic tension loads. The Cowper-Symonds model is employed to characterize the non-linear increase in yield strength with strain rate, within the range of 0,01 to 1 [1⁄s]. For lower strain rates, a drastic decrease in yield strength is observed, suggesting the significant influence of creep and relaxation phenomena. The study proposes further research incorporating viscoelastic properties for a more comprehensive material model. Additionally, the study observes a disproportionate increase in yield strength for samples with smaller radius, indicating a dependency on triaxiality which suggests further research on the Drucker-Prager model for this material. The study concludes by recommending a broader range of input parameters for future studies, including the Johnson-Cook model and comparison of tensile test results with compression test results.

Membranes are a selective barrier that allows certain species (molecules and ions) to pass through while blocking others. Some rely on size exclusion, where larger molecules get stuck while smaller ones permeate through. Others use differences in charge or polarity to attract and repel specific species. Membranes can be used to purify air and water by allowing only air and water molecules to pass through but preventing contaminants such as microorganisms and particles or to separate target gas or vapor, such as H2, CO₂, from other gases. The higher the flux and selectivity, the better a material is for membranes. The desirable performance can be tuned through material type (polymers, ceramics, and biobased materials), microstructure (porosity and tortuosity), and surface chemistry. Most membranes are made from plastic from petroleum-based resources, which contribute to global climate change and plastic pollution. Cellulose can be an alternative sustainable resource to make renewable membranes. Cellulose exists in plant cell walls as natural fibers, which can be broken down into smaller components such as cellulose fibrils, nanofibrils, nanocrystals, and cellulose macromolecules through mechanical and chemical processing. Membranes made from reassembling these particles and molecules have variable pore architecture, porosity, and separation properties and therefore have a wide range of applications in nano-, micro-, and ultrafiltration or forward osmosis. Despite their advantages, cellulose membranes face some challenges. Improving the selectivity of membranes for specific molecules often comes at the expense of permeability. The stability of cellulose membranes in harsh environments or under continuous operation needs further improvement. Research is ongoing to address these challenges and develop advanced cellulose membranes with enhanced performance. This article reviews the microstructure, fabrication methods, and potential applications of cellulose membranes, providing some critical insights into processing-structure-property relationships for current state-of-the-art cellulosic membranes that could be used to rationally improve their performance.

The durability of bridge decks is a critical factor in ensuring the safety and longevity of transportation infrastructure. This article explores advanced materials and innovative techniques designed to mitigate cracking in bridge decks, a common issue that can compromise structural integrity and increase maintenance costs. It provides a comprehensive review of cutting-edge solutions such as Fiber-Reinforced Polymers (FRP), High-Performance Concrete (HPC), Ultra-High Performance Concrete (UHPC), and self-healing concrete technologies. Each material is analyzed for its ability to enhance strength, reduce permeability, and improve resistance to environmental stressors. Additionally, the article examines the role of surface treatments, sealants, and routine maintenance practices in prolonging the life of bridge decks. By synthesizing current research and practical applications, this article offers valuable insights and recommendations for engineers, contractors, and policymakers seeking to advance bridge deck durability through innovative materials and methodologies.

Fracture of viscoplastic materials is a complex process due to its time-dependent and plastic responses. Numerical simulation for fracture plays a significant role in crack prediction and failure analysis. In recent years, the phase field model is becoming a competitive approach to predict crack growth and has been extended to inelastic materials such as elasto-plastic, viscoelastic and viscoplastic materials, etc. However, the contribution of inelastic energy to crack growth is seldom studied. For this reason, we implement the phase field model coupled with a viscoplastic constitutive in finite element framework, in which the elastic energy and inelastic energy are used as crack driving energy. The implicit algorithm for a viscoplastic constitutive is presented, this procedure is suitable for other viscoplastic constitutive relations. The strain rate effect, creep effect, stress relaxation effect and cyclic loading responses are tested using a single element model with different inelastic energy contributions; A titanium alloy plate specimen and a stainless-steel plate specimen under tension are studied compared with the experimental observations in existing literature. The results show that the above typical damage phenomenon and fracture process can be well reproduced; The inelastic energy significantly affects the force-displacement responses but has slight effect on the crack paths.

Crack inspection is important to monitor the structural health of pavement structures and to facilitate an easier rehabilitation process. Currently, pavement crack inspection is conducted manually, which is inefficient and costly at the same time. For solving the problem, this work has developed a robotic system for automated data collection and analysis in real-time. The robotic system navigates on the pavement and collects visual images from the surface. A deep learning-based semantic segmentation framework named RCDNet was proposed and implemented on the onboard computer of the robot to identify cracks from the visual images. Simulation results show that the deep learning model obtained 96.29% accuracy for predicting the images. The proposed robotic system was tested on both indoor and outdoor environments and was observed that it can complete inspecting a 3m × 2m grid within 10 minutes and a 2.5m × 1m grid within 6 minutes. This outcome shows that the proposed robotic method can drastically reduce the time of manual inspection. Furthermore, a severity map based on the results from visual images was also generated to provide an idea of which locations should be paid more attention to repair in a test grid.

In order to achieve the dual carbon goal and simplify the decarbonization process, a CO2 recovery process of the fire-flooding exhaust was designed. The process adopted the two-stage membrane separation method to recover CO2 and obtain high purity CO2 rich flow, and then through the mixed refrigerant liquefaction and rectification column, food grade liquid CO2 was obtained. HYSYS process simulation shows that for the fire-flooding exhaust with a flow rate of 1000 kg/h and a given composition, the process can achieve a CO2 recovery of 69.02%, total product sales S=2086.8 yuan/h, and specific power consumption of 2.818 kW∙h/kg. On this basis, a hybrid simulation platform of HYSYS & Matlab was established. Taking the specific power consumption of the product as the objective function, sequential quadratic programming (SQP) algorithm was adopted to optimize the process, and the optimized specific power consumption was reduced by 18.8%. Finally, by adjusting N2/CO2 components, the adaptability of the optimization condition was analyzed.

This research work has been based on a previous study by the authors that characterized the behavior of a polyimide-coated FBG sensor in a structural monitoring system. Sensors applied to structural health monitoring are affected in the presence of a state of multidirectional strains simultaneously. The previous study observed the influence of transverse strain (ε_y) while keeping longitudinal strain constant (ε_x), where the direction x is the direction of the optical fiber. The present study developed an experimental methodology which has consisted of carrying out a campaign of biaxial tests on cruciform specimens with three embedded FBG sensors coated with polyimide, acrylate and ORMOCER®. Applying the Strain–Optic Theory as reference, a comparison of the results obtained with the different coatings has been studied. This experimental work has done it possible to study the influence of transverse strain (ε_y) in the longitudinal measurement of each of the FBG sensor and the influence of the coating material. Finally, the calibration procedure as well as the strain sensitivity factor K for each sensor has been defined.

When describing the tribological behaviour of technical surfaces, the need for full length scale microtopographic characterization often arises. The self-affine of surfaces and the characterization of self-affine by a fractal dimension and its implantation into tribological models are commonly used. The goal of our present work was to determine the frequency range of fractal behaviour of surfaces by analysing the microtopographic measurements of a brake plunger. We also wanted to know if the bifractal and multifractal behaviour can be detected in real machine parts. As a result, we developed a new methodology for determining the fractal range boundaries to separate the nano- and micro-roughness. In order to reach our goals, we used atomic force microscope (AFM) and stylus instrument to provide measurements in wide frequency range (19 nm - 3 mm). As a result of the power spectral density (PSD) based fractal evaluation, it was found that the examined surface could not be characterized by a single fractal dimension and that we developed a methodology for stopping the margin of validity of each fractal dimension, and we also developed a methodology for determining the limits of validity of certain fractal dimensions.

The combination of neural network and beamforming has been proved to be very effective in multi-channel speech separation. But its performance faces a challenge in complex environment. In this paper, an iteratively refined multi-channel speech separation method is proposed for the challenge, where the proposed is composed of initial separation and iterative separation. In initial separation, the time-frequency domain dual-path recurrent neural network neural network (TFDPRNN), minimum variance distortionless response (MVDR) beamformer and post-separation (also TFDPRNN) are cascaded for obtaining the first additional input in iterative separation. In iterative separation, the MVDR beamformer and post-separation are iteratively used, where the output of the MVDR beamformer is used as an additional input of the post-separation network and the final output comes from post-separation module. This iteration of the beamformer and post-separation is fully employed for promoting their individual optimization, which ultimately improves the overall performance of speech separation in multi-speaker scenarios. Experiments on the spatialized version of the WSJ0-2mix corpus show that our proposed method is significantly better than the current popular methods. In addition, the method also has a good effect on the dereverberation task.

Several specific types of ordinary and generalized separation axioms of a generalized topological space have been defined and investigated for various purposes from time to time in the literature of topological spaces. Our recent research in the field of a new class of generalized separation axioms of a generalized topological space is reported herein as a starting point for more generalized classes.

We report a simple and high-performance flexible strain sensor based on liquid metal nanoparticles (LMNPs) on polyimide substrate by laser induced deposition. The LMNPs were prepared by ultrasonic method, and then the femtosecond laser direct writing technology was used to induce the assembly and deposition of the LMNPs to form liquid metal microwires. Laser local sintering enhances the connection between particles, and a wearable strain sensor was fabricated with the high sensitivity as high as 76.18, the good linearity (a correlation coefficient of 0.999) in a wide sensing rage, the fast response/recovery time of 159 ms/120 ms. Attributed to these extraordinary strain sensing performances, the sensor can sense various dynamic strains in real time, monitor both subtle physiological activities and large human motions. It can be adhered to human skin, and well reflect the change of facial expression and realize real-time monitoring of facial expression. And the vocal cord vibration can be detected for speech recognition while the sensor attached to the outside of the throat.

The emergence of drug resistant pathogenic bacteria is increasingly challenging conventional antibiotics. Plant derived flavonoids are considered as potential alternatives to antibiotics due to their antimicrobial properties. However, the mechanisms by which flavonoids modulate pathogenic microorganisms’ growth are not fully understood. In our previous studies we found that Rutin, a kind of flavonoids showed inhibition against Klebsiella pneumoniae strains. In order to better understand its inhibitory mechanism on strain growth, we used both Rutin and Luteolin as treatments to incubate K. pneumoniae ATCC700603 strain. After incubation for 4 hours, the homogenous and differential effects of two different flavonoids on the growth of K. pneumoniae were evaluated. The integrated metabolomic and transcriptomic analysis was performed. The expression levels of 5,483 genes and the contents of 882 metabolites were measured. The differentially expressed genes (DEGs) and metabolites (DEMs) were screened and analyzed. The correlation between DEGs and DEMs were also studied. Our results showed that Rutin could inhibit the strain growth by changing metabolic pathways and ABC transporters pathways. Our study also revealed FU841_RS17580 and FU841_RS19145 as functional genes that played vital roles in the strain growth.

Natural gas hydrate has gained significant attention in recent years. To safely and sustainably exploit the natural gas from gas hydrate-bearing sediments, it is crucial to understand the long-term mechanical characteristics of the hydrate reservoir. In this study, the influence of hydrate and fine particles on the strain rate dependence of hydrate-bearing sediments under plane strain conditions has been studied. The experimental results show that the strain rate dependency of the mechanical properties of hydrate-bearing sediments is positively correlated with hydrate saturation instead of the morphology of hydrate in sediments. The residual strength of hydrate-bearing sediments is primarily controlled by the hydrate saturation and is independent of the strain rate. Changes in hydrate saturation, and fines content, can affect the relationship between the strain rate and shear band angle. Finally, the local volumetric expansion effect of hydrate-bearing sediments without fines content is more significant and shows a strong strain rate dependence characteristic. Overall, this study provides valuable insights into the long-term mechanical characteristics of hydrate reservoirs. These insights can contribute to the development of a constitutive model of hydrate-bearing sediments with time-dependence in the future, and which is meaningful to the exploitation of natural gas hydrate.

Despite polycarbonate (PC) being a widely used engineering plastic, its notch and crack sensitivity pose challenges in critical applications. To address this, PC was blended with elastomeric polymers to explore the improvement in toughness. This study systematically investigates the toughening mechanisms of PC blended with acrylonitrile-butadiene-styrene (ABS), copolyether ester elas-tomer (COPE), and ABS and styrene-ethylene-butylene-styrene (SEBS) copolymer grafted with maleic anhydride (MA). The morphology and mechanical behavior were evaluated under qua-si-static and high-speed tensile tests and Charpy impact tests using optical, electronic, and atomic force microscopy and Raman spectroscopy. The morphological analysis reveals cavitation and crazing phenomena for COPE and SEBS-g-MA systems, and mostly debonding for ABS, indicating an improvement in toughening. While the addition of ABS improves the PC plastic deformation, modifying ABS with maleic anhydride enhances the elastic modulus. Blending PC with SEBS-g-MA increases the strain at break, and the addition of COPE significantly improves the deformation behavior of PC (by around 115%). This comparative study provides valuable insights into the performance of different PC-elastomer blends under similar conditions, supporting the selection of appropriate materials for given applications.

Abstract: A. baumannii exhibits resilience in harsh environments and progressively develops resistance to diverse antibacterial agents over time. This adaptability poses a significant challenge in treating an infection caused by this bacterium within healthcare settings. The presence of peptidoglycan, a crucial precursor for cell wall synthesis, contributes to this challenge. Peptidoglycan serves not only as a structural support in bacterial cells but also provides protection against adverse environmental conditions. The synthesis of the peptidoglycan layer involves a group of substrates such as N-acetylglucosamine (GlcNAc) and N-acetylmuramic acid (MurNAc), within a three-partitioned process occurring in the membrane, periplasmic space, and cytoplasm of each bacterium. Initiated in the cytoplasm and extending to the inner cell membrane, this synthesis starts with the production of nucleotide precursors. The first step involves the synthesis of UDP-GlcNAc, orchestrated by Glm (GlmS, GlmM, and GlmU) enzymes using fructose-6-phosphate. Subsequently, enzymes from the Mur family, namely MurB, MurA, MurD, MurC, MurI, MurF, and MurE, synthesize UDP-N-acetylmuramyl-pentapeptide (UDP-Mpp) from UDP-GlcNAc. Concurrently, on the cytosolic side, the production of membrane-surrounded undecaprenyl phosphate occurs, involving membrane-side proteins MraY and MurG in the biosynthesis of peptidoglycan. This review emphasizes updated information on Mur family proteins, encompassing physicochemical properties, nature of binding site, number and type of binding site residues, functional domain details, three-dimensional structural aspects, and their functions within bacterial cells. Special attention is directed towards their enzymatic role in peptidoglycan biosynthesis due to the limited availability of precursors in the market. Additionally, the review provides a comprehensive summary of existing inhibitors and ongoing efforts in identifying new targeted inhibitors, recognizing these enzymes as potential candidates for antibacterial drug design and discovery.

Cracks on concrete surfaces are vital factors affecting construction safety. Accurate and efficient crack detection can prevent safety accidents. Using drones to photograph cracks on a concrete surface and detect them through computer vision technology has the advantages of accurate target recognition, simple practical operation, and low cost. To solve this problem, an improved CenterNet concrete crack-detection model is proposed. First, a channel-space attention mechanism is added to the original model to enhance the ability of the convolution neural network to pay attention to the image. Second, a feature selection module is introduced to scale the feature map in the downsampling stage to a uniform size and combine it in the channel dimension. In the upsampling stage, the feature selection module adaptively selects the combined features and fuses them with the output features of the upsampling. Finally, the target size loss is optimised from a Smooth L1 Loss to IoU Loss to improve its inability to adapt to targets of different sizes. The experimental results show that the improved CenterNet model reduces the FPS by 123.7, increases the GPU memory by 62MB, increases the FLOPs by 3.81, and increases the AP by 0.154 compared with the original model. The GPU memory occupancy remained stable during the training process and exhibited good real-time performance and robustness.

The latest life-origin literature is reviewed, along with grouping and classification of the most enduring models of abiogenesis. New trends are identified in origin-of-life thought. Astrobiology continues to deal mostly with inorganic and very elementary organic reactions in extreme environments. Nonequilibrium thermodynamics has received a great deal of attention. Attempts have been made to relate Bejan’s Constructal Law to life and abiogenesis. RNA World preclusions only seem to have grown, while ribozyme/peptide models have expanded. The biosemiotic movement and code biology is gaining influence in refining a more complete description of life. Prof James Tour at Rice University in a fourteen-lecture series lists a number of synthetic biochemical hurtles remaining that still need to be overcome. But the need for some sort of informational recipe, instruction, steering and control now seems to be the most prominent area of focus and concern. Even a protometabolism needed active selection and controls rather than mere constraints or law. The latest literature still does not elucidate how protometabolism was orchestrated in an inanimate, pre-evolutionary environment.

The link of fracture analysis of large ships is an essential part of the structural safety of ships. However, the finite element analysis of large structure according to the traditional method not only has high requirements on the computer, but also the influence of the mesh encryption at special locations makes further requirements on the accuracy of the ship. In this paper, based on the extended finite element method (XFEM) and the multi-point constraint method (MPC), the dynamic crack expansion process of the rectangular plate containing cracks under the multi-scale model is comparatively studied by using ABAQUS simulation software Finally, the applicability of the method is verified by applying the multi-scale model of ship nodes. The results show that the computational effort of the multi-scale model is significantly reduced with the same accuracy and allowable error, which proves the accuracy and efficiency of the method.

The objective of this study is to investigate the aquatic-toxic effects of glyoxal-containing cellulose ether with four different glyoxal concentrations (0, 1.4, 2.3 and 6.3%) in response to global chemical regulations, e.g., European Union Classification, Labeling and Packaging (EU CLP). Tests of the aquatic-toxic effects of glyoxal-containing cellulose ether on 11 freeze-dried microbial strains, Microcystis aeruginosa, Daphnia magna and zebrafish embryos were designed as an initial stage for toxicity screening, and were performed with the standardized toxicity test guidelines. Glyoxal-containing cellulose ether showed no significant toxic effects in the toxicity tests for the 11 freeze-dried microbial strains, Daphnia magna and zebrafish embryos. Alternatively, 6.3% glyoxal-containing cellulose ether led to more than a 60% reduction of Microcystis aeruginosa growth after 7 days of exposure. Approximately 10% developmental abnormalities (e.g., bent spine) in zebrafish embryos were also observed in the group exposed to 6.3% glyoxal-containing cellulose ether after 6 days of exposure. These results imply that <6.3% glyoxal-containing cellulose ether results in non-toxic effects on the acute toxicity of aquatic organisms. However, ≥6.3% glyoxal-containing cellulose ether may affect the health of aquatic organisms with long-term exposure. In order to better evaluate the eco-safety of cellulosic products contained in glyoxal, further studies regarding the toxic effects of glyoxal-containing cellulose ether with long-term exposure are required. The results from this study allow us to evaluate the auatic-toxic effects of glyoxal-containing cellulosic products, under EU chemical regulations, on the health of aquatic organisms.

To encourage proper waste management from electrical and electronic devices (e-waste), it is necessary to invest heavily in the development of recycling technologies. One way to improve the process is to automate separating the shredded parts of e-waste using a robot. This paper's literature review, utilizing the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) framework, showcases potential robotic technologies for e-waste separation. However, the intricate design of these devices can pose significant challenges in their implementation. Various legal, organizational, and sociological obstacles have left Serbia's e-waste management practice underdeveloped, resulting in an unsatisfactory recycling rate. In this paper we examined the possibility of using robots on the precise example of recycling refrigerators in a recycling center in Eastern Serbia, concluding that such a solution would have multiple positive effects, both on the employees and the working environment, on the operations of the recycling center itself, and on increasing the e-waste recycling rate in the country.

Probiotic feed additives have attracted considerable research interest in recent years because the effectiveness of probiotics can differ across microbial strains and the supplemented macroorganisms. The present study was conducted on 16 lambs divided into two groups (C - control and E - experimental). The examined lambs were aged 11 days at the beginning of the experiment and 40 days at the end of the experiment. The diet of group E lambs was supplemented with a multi-strain probiotic formulation (Lactobacillus plantarum AMT14, Lactobacillus plantarum AMT4, Lactobacillus rhamnosus AMT15, and Bifidobacterium animalis AMT30), whereas group C lambs did not receive the probiotic additive. At the beginning of the experiment (day 0) and on experimental days 15 and 30, blood was sampled from the jugular vein to determine and compare: phagocytic activity (PHAGOTEST) and oxidative metabolism (PHAGOBURST) of peripheral blood granulocytes and monocytes by flow cytometry. An analysis of the phagocytic activity of granulocytes and monocytes revealed significantly higher levels of phagocytic activity (expressed as the percentage of phagocytic cells and mean fluorescence intensity) in lambs administered the multi-strain probiotic formulation than in the control group. The probiotic feed additive also exerted a positive effect on the oxidative metabolism of both granulocytes and monocytes (expressed as the percentage of oxidative metabolism and mean fluorescence intensity) after stimulation with Escherichia coli bacteria and with PMA (4-phorbol-12-β-myristate-13-acetate).

This study uses a mass-spring-damping system to simulate the repeated strain of liquefaction cyclic triaxial tests. The two results are compared in this paper to understand the feasibility of the mass-spring-damping system developed in this paper and the feasibility of future research on this related topic and development potential. The main factors affecting this mode's repeated strain are the spring coefficient k and the external force Q0. The spring coefficient has an inverse relationship but does not increase in multiples. The external force has a direct proportional relationship but does not increase the result- a non-multiple increase. When the pore water pressure of the liquefied cyclic triaxial test specimen rises, it will cause the specimen to liquefy, decreasing effective stress, shear modulus G, and damping ratio D, causing an increase in strain. The shear modulus and damping ratio are related to the spring coefficients k and c. Both are variables that change with time. This article takes an original thin-tube specimen at point A in the Yunlin area in Taiwan as a testing example. Through Mathematica software, it can be obtained that the mass m=1kg, the spring coefficient k=244e-0.1t kgf/cm, and the damping coefficient c=0.739e-0.257t kgf-s/cm and external force Q0=10.1sin2πt kg; Finally, this study selected the original thin-tube specimens from four locations in the Yunlin area, and simulated the repeated strain amount of the cyclic triaxial test specimens through a spring-damping system. The results show that the spring-damping system is feasible for simulated cyclic triaxial tests because the model is simple and the parameters are easy to understand and obtain, which also shows the extensibility of this model. Preliminary results of the research show that this model can further simulate the repeated strain obtained by cyclic triaxial tests without considering the increased trend in pore water pressure and the decrease in effective stress during cyclic loading.

The fatigue life of welded joints under cyclic loading is a complex process that can be roughly divided into fatigue crack initiation, crack propagation and final fracture. Usually, these phases are evaluated separately. Several methods are available to estimate the extent of the different phases in welded components, such as stress-based fatigue concepts for crack initiation or linear elastic fracture mechanics for crack propagation; however, distinguishing these phases in welded components is a complex procedure and often relies on assumptions such as transition crack sizes. The objective of this study is to investigate the relationship between fatigue crack initiation and propagation in welded joints using artificially notched specimens with welded joints characteristics of different notch acuity (different radii and opening angle). The experiments show that the investigated relationship basically depends on the notch acuity, the load level and the stress ratio.

The microstructure of Al-5Fe-1.5Er alloy was characterized and analyzed by using XRD, SEM, TEM and EDS. The effect of microstructure on the behavior of crack initiation and propagation was investigated by in situ tensile testing. Results show that the microstructure consists of α-Al matrix, Al₃Fe, Al₄Er, eutectic phase Al₃Fe + Al₄Er, while the 1.5 wt.% Er was added in Al-5Fe alloy. The twin structure of the Al₃Fe phase was observed, and the twin plane is {001}. Moreover, a continuous concave and convex interface structure of the Al₄Er has been found. Al₃Fe is in the form of a sheet with a clear gap inside.In situ tensile tests of the alloy at room temperature show that the crack initiation occured mainly in the Al₃Fe phase, and that the crack propagation modes include intergranular and transgranular expansion. Crack transgranular expansion is due to the strong binding ability between Al₄Er phases and surrounding organization, and the continuous concave and convex interface structure of the Al₄Er provides a significant meshing effect on the matrix and eutectic structure.

Environmentally friendly and low-cost sensors are needed for the next generation disposable electronics applications. Given its low-cost, availability and biodegradability, paper-based devices are a very promising. Here we demonstrate the fabrication of a tungsten disulphide (WS2) strain sensor on standard copy paper. The WS2 is deposited through direct abrasion of WS2 powder against the paper surface making the fabrication of the device low-tech and cost effective. The fabricated strain gauge devices present gauge factors up to ~70 for strains in the ± 0.5 % range. These values are ~ 9 times larger than that obtained on devices with the same geometry but using a graphite film instead a WS2 as a sensitive material. We demonstrate the potential of these WS2-on-paper strain gauges by integrating them directly on a paper cantilever to sense mass and forces. We show how this very simple device can detect sub-milligram masses. Moreover, we also demonstrate the capability of transducing motion in mechanical resonators by gluing a WS2-on-paper strain gauge on their surface.

Abstract: Imaging devices of less than 300,000 pixels are mostly used for sewage conduit exploration due to the petty nature of the survey industry in Korea. P articular ly , devices of less than 100,000 pixels are still widely used, and the environment for image processing is very bitter . Since the sewage conduit image s covered in this study ha ve a very low resolution (240 × 320 = 76,800 pixels), it is very difficult to detect cracks. Because most of the resolution of the sewe r conduit images are very low in Korea, this problem of low resolution was selected as the subject of study. Cracks were detected through a total of six steps of improving the crack in Step 2, finding the optimal threshold value in Step 3, and applying an algorithm to detect cracks in Step 5. Cracks were effectively detected by the optimal parameters in Steps 2 and 3 and the user algorithm in Step 5. Desp ite the very low resolution, the cracked image s showed 96.4% accuracy of detection, and the non cracked image s showed 94.5% accuracy . Moreover, the analysis was excellent in quality , also . It is believed that the findings of this study can be effectively u sed for crack detection with low resolution images.

An autonomous concrete crack inspection system is necessary for preventing hazardous incidents arising from deteriorated concrete surfaces. In this paper, we represent a concrete crack detection framework to aid the process of automated inspection. The proposed approach employs a deep convolutional neural network architecture for crack segmentation from concrete image. The proposed network alleviates the effect of gradient vanishing problem present in deep neural network architectures. A feature silencing module is incorporated in the crack detection framework, for eliminating unnecessary feature maps from the network. The overall performance of the network significantly improves as a result. Experimental results support the benefit of incorporating feature silencing within a convolutional neural network architecture for improving the network’s robustness, sensitivity, and specificity. An added benefit of the proposed architecture is its ability to accommodate for the trade-off between specificity (positive class detection accuracy) and sensitivity (negative class detection accuracy) with respect to the target application. Furthermore, the proposed framework achieves a high precision rate and processing time than crack detection architectures present in literature.

In this paper, the ductile fracture mechanism is discussed. The results of the numerical and experimental analyses are used to estimate of the onset of the crack front growth . It is assumed that the ductile fracture in front of the crack starts at the location along the crack front where the accumulated effective plastic strain reaches a critical value. It is also assumed that the critical effective plastic strain depends on the stress triaxiality and the Lode angle. The experimental programme was performed using five different specimen geometries, three different materials and three different temperatures of +20°C, -20°C and -50°C. Using the experimental data and the results of the finite element computations, the critical effective plastic strains are determined for each material and each temperature. However, before the critical effective plastic strain is determined, a careful calibration of the stress–strain curves was performed after modification of the Bai–Wierzbicki procedure. Finally, by analysing the experimental results recorded during the interrupted fracture tests and scanning microscopy observations, the research hypothesis is verified.

The advancement of performance in the domain of flexible wearable strain sensors has become increasingly significant due to extensive research on laser-induced graphene (LIG). An innovative doping modification technique is required owing to the limited progress achieved by adjusting laser parameters to enhance LIG’s performance. By pre-treating with AgNO3, we successfully manufactured LIG with a uniform dispersion of silver nanoparticles across its surface. The experimental results for the flexible strain sensor exhibit exceptional characteristics, including low resistance (183.4 Ω), high sensitivity (426.8), a response time of approximately 150 ms, and a relaxation time of about 200 ms. Moreover, this sensor demonstrates excellent stability under various tensile strains and remarkable repeatability during cyclic tests lasting up to 8,000 s. Additionally, this technique yields favorable results in finger bending and hand back stretching experiments, holding significant reference value for preserving the inherent characteristics of LIG preparation in a single-step and in situ manner.

Analysis of Fatigue Strain, Fatigue Modulus and Fatigue Damage for the modeling of concrete plays a vital role in the evolution material behaviour which is heterogeneous and anisotropic in nature. In this paper, the Level-S nonlinear fatigue strain curve, fatigue modulus curve, residual strain curve of concrete in compression, tension, flexure and torsional fatigue loading were proposed using strain life approach. The parameters such as physical meaning, the ranges, and the impact on the shape of the curve were discussed. Then, the evolution model of fatigue modulus was established based on the fatigue strain evolution model, fatigue modulus evaluation model, residual strain evaluation model, secondary strain evaluation model. The hypothesis of fatigue modulus is inversely related with the fatigue strain amplitude. The fatigue evolution of concrete damages the bond between material grains, changed the orientation of structure of molecules and affects the elastic properties resulting in the reduction of material stiffness and modulus by utilizing strain life analysis, regarding stiffness degradation and inelastic deformation by formation of microcracking, macro cracking, cracking which is heterogeneous and anisotropic in nature . This paper presents the Fatigue Strain Life Model and analyses of fatigue strain, fatigue modulus and damage parameters of concrete which is capable of predicting stiffness degradation, inelastic deformation, strength reduction under fatigue loading. Hence, the obtainable results were compared with experimental results for the validation of the proposed model.

The recent Planck Legacy release confirmed the existence of an enhanced lensing amplitude in the cosmic microwave background (CMB) power spectra, which endorses the positive curvature of the early Universe with a confidence level exceeding 99%. In this study, the pre-existing curvature is incorporated to extend the field equations where the derived wave function of the Universe is utilized to model Universe evolution with reference to the scale factor of the early Universe and its radius of curvature upon the emission of the CMB. The wave function reveals both positive and negative solutions, implying that matter and antimatter of early Universe plasma evolve in opposite directions as distinct Universe sides. The wave function indicates that a nascent hyperbolic expansion is followed by a first phase of decelerating expansion away from early plasma during the first 10 Gyr, and then, a second phase of accelerating expansion in reverse directions, whereby both Universe sides free-fall towards each other under gravitational acceleration. Simulations of the predicted conformal curvature evolution demonstrate the fast orbital speed of outer stars owing to the external fields exerted on galaxies as they travel through conformally curved space-time. Finally, the wave function predicts an eventual time-reversal phase comprising rapid spatial contraction that culminates in a Big Crunch, signalling a cyclic Universe. These findings reveal that early plasma could have separated and evolved into distinct sides that collectively and geometrically influencing the Universe evolution, physically explanting the effects attributed to dark matter and energy.

The term “conservation,” as it relates to biodiversity in a Western context, has a storied past and as conservation science and societal values have evolved, consensus over its precise meaning has remained elusive. The broad scope of contemporary definitions hampers effective communication during a period of environmental crisis and is troublesome for any derivative concept which aims to empirically quantify the efforts of the conservation sector. This presents an avoidable hindrance to the systematic planning of the conservation field. To help remedy this situation, we provide an outcome separation framework that is based on the expected degree of separation between an action’s proximate outcome, from its intended, ultimate outcome for a habitat and/or species. Framing a definition of conservation through this lens of outcome separation allows for conservation-related actions to be clearly categorized into one of three discrete tiers: primary, secondary, and tertiary. A distillation of this tiered framework also provides a new definition of biodiversity conservation that is more rigorous and adaptable to future conceptual evolutions of the field.

Chromatographic separation is a critical technique in the manufacturing processes of both chemical products and biopharmaceuticals. Its principle relies on exploiting the differences in distribution between the stationary and mobile phases to achieve the separation of mixtures. The precision of substance concentration during separation directly impacts the quality and usability of the final product. Therefore, the development of an effective and precise separation control technique has long been a vital concern in the field of chromatographic separation control. Currently, the employment of Simulated Moving Bed (SMB) technology for chromatographic separation, which allows for continuous feed, has been recognized as a cutting-edge technique. SMB is a continuous process technology that enhances the efficiency of adsorbents within the bed. This sequential multi-column SMB technology not only increases production capacity but also reduces the consumption of solvents and water. It is acknowledged as one of the cleanest manufacturing technologies in the biopharmaceutical industry. However, multi-column SMB involves various variables such as flow rates in multiple sections and valve switching times, rendering its system control highly complex. Unlike traditional control objectives that aim to minimize control output errors, the control objective of SMB is to achieve a specific proportion of substance concentration. Consequently, designing and implementing traditional control theories for SMB is challenging, leading to SMB systems largely being controlled based on simple PLC controls. Moreover, these controls are often applicable only to single or a few-column SMB setups, limiting the effectiveness of high-capacity applications. To achieve effective control of SMB, this study employs an adjustable intelligent fuzzy controller with a structure like an approximate neural network (NN) for SMB control research. Simulation results demonstrate that the intelligent controller effectively achieves desirable control outcomes for the SMB system.

Separation and detection of cells and particles in a suspension are essential for various applications, including biomedical investigations and clinical diagnostics. Microfluidics realizes the miniaturization of analytical devices by controlling the motion of a small volume of fluids in microchannels and microchambers. Accordingly, microfluidic devices have been widely used in particle/ cell manipulation processes. Different microfluidic methods for particle separation include dielectrophoretic, magnetic, optical, acoustic, hydrodynamic, and chemical techniques. Dielectrophoresis (DEP) is a method for manipulating polarizable particles’ trajectories in non-uniform electric fields using unique dielectric characteristics. It provides several advantages for dealing with neutral bioparticles owing to its sensitivity, selectivity, and noninvasive nature. This review provides a detailed study on the signal-based DEP methods that use the applied signal parameters, including frequency, amplitude, phase, and shape for cell/particle separation and manipulation. Rather than employing complex channels or time-consuming fabrication procedures, these methods realize sorting and detecting the cells/particles by modifying the signal parameters while using a simple device. In addition, these methods can significantly impact clinical diagnostics by making low-cost and rapid separation possible.

Detecting gear rim fatigue cracks using vibration signal analysis is often a challenging task, which typically requires a series of signal processing steps to detect and enhance fault features. This task becomes even harder in helicopter planetary gearboxes due to the complex interactions between different gear sets, and the presence of vibration from sources other than the planetary gear set. In this paper, we propose an effectual processing algorithm to isolate and enhance rim crack features and to trend crack growth in planet gears. The algorithm is based on using cepstrum editing (or liftering) of the hunting tooth synchronous averaged signals (angular domain) to extract harmonics and sidebands of the planet gears, and low-pass filtering and minimum entropy deconvolution (MED) to enhance extracted fault features. The algorithm has been successfully applied to a vibration dataset collected from a planet gear rim crack propagation test undertaken in the Helicopter Transmission Test Facility (HTTF) at DSTG Melbourne. In this test, a seeded notch generated by an electric discharge machine (EDM) was used to initiate a fatigue crack that propagated through the gear rim body over 94 load cycles. The proposed algorithm demonstrated a successful isolation of incipient fault features and provided a reliable trending capability to monitor crack progression. Results of a comparative analysis showed that the proposed algorithm outperformed the traditional signal processing approach.

A model to rationalize the effects of test temperature and microstructural variables on the creep crack growth (CCG) and creep-fatigue crack growth (CFCG) rates in ferritic steels is described. The model predicts that as the average spacing between grain boundary particles that initiate creep cavities decrease, the CCG and CFCG rates increase. Further, CCG data at several temperatures collapse into a single trend when a temperature compensated CCG rate derived from the model is used. CCG and CFCG behavior measured at different temperatures is used to assess the effects of variables such as differences between basemetal (BM), weldmetal (WM) and the heat-affected zone (HAZ) regions. The model is demonstrated for Grade 22 and Grade 91 steels using data from literature. It is shown that differences between the CCG behavior of Grade 22 steel in new and ex-service conditions are negligible in the BM and WM regions but not in the HAZ region. The CCG behavior of Grade 91 steels can be separated into creep-ductile and creep-brittle regions. The creep-brittle tendency is linked to the presence of excess trace element concentrations in the material chemistry. Significant differences found in the CCG rates between BM and the WM and HAZ regions of Grade 91 steel were explained.

In this paper thermo-mechanical behavior of 4D printed Polylactic Acid (PLA) was investigated, focusing on its response to varying strain rates and temperatures below the glass transition temperature. Dynamic mechanical analysis and uniaxial tensile tests confirmed PLA's dependency on strain rate, showcasing its sensitivity to external stimuli. Stress-strain curves exhibited typical thermoplastic behavior, with yield stresses varying with strain rates, underscoring PLA's responsiveness to different deformation speeds. Clear strain rate dependence was observed, particularly at quasi-static rates, with temperature and strain rate fluctuations significantly influencing PLA's mechanical properties, including yield stress and deformation behavior. Isothermal compression tests demonstrated predictable stress-strain curves with distinct yield points, while adiabatic tests reveal additional complexities such as heat accumulation leading to further softening. Thermal imaging revealed temperature increase during deformation, highlighting the material's thermo-sensitive nature. These findings provide the basis for future research with the focus on advanced modeling techniques and mitigation strategies for self-heating effects, aiming to enhance PLA-based product reliability and performance in applications with deformations at higher strain rates, while also developing models to simulate shape recovery in 4D printed PLA structures at both cold and hot programming temperatures.

Introduction: Left ventricular dysfunction in an independent predictor of mortality in Chagas disease. Global longitudinal strain (GLS) is an emerging echocardiographic modality with possible incremental value in early detection of cardiac involvement. Objective: Compare left ventricular function with multiple echocardiographic parameters between patients with the indeterminate and chronic forms of Chagas and perform a literature review. Methods: In this observational study, 11 patients with a confirmed diagnosis of Chagas disease were evaluated. Individuals were distributed as follows: 5 with the indeterminate and 6 with the chronic forms. Conventional echocardiographic evaluation was followed by GLS measurement. Results: The mean left ventricle ejection fraction LVEF was 33 ± 2.88 and the mean GLS of the left ventricle was - 10.76 ± 2.20 in the chronic form as compared to 57.80 ± 6.49 and - 17.34 ± 3.82, respectively in the indeterminate group. Contractility was reduced in segments of the inferior, inferoseptal and anteroseptal walls in both groups. Conclusion: Analysis of longitudinal strain in the indeterminate form has potential incremental value to the conventional analysis of ejection fraction when compared to patients with chronic Chagas cardiomyopathy, especially with individual segmental analysis but the impact and clinical significance of these techniques is still unknown.

The geometry of structural members can influence the fatigue crack growth rate. In the paper, the T-stress depending on the element's geometry is used to quantify the effect of geometry on the fatigue crack growth rate. A series of fatigue tests on three-point bending specimens with different initial crack lengths were conducted. As a result, the dependence of the crack growth rate on the T-stress value was obtained.

The determination of crack propagation velocities can provide valuable information for a better understanding of damage processes of concrete. The spatio-temporal analysis of crack patterns developing at a speed of several hundred meters per second is a rather challenging task. In the paper, a photogrammetric procedure for the determination of crack propagation velocities in concrete specimens using high-speed camera image sequences is presented. A cascaded image sequence processing which starts with the computation of displacement vector fields for a dense pattern of points on the specimen’s surface between consecutive time steps of the image sequence chain has been developed. These surface points are triangulated into a mesh, and as representations of cracks, discontinuities in the displacement vector fields are found by a deformation analysis applied to all triangles of the mesh. Connected components of the deformed triangles are computed using region-growing techniques. Then, the crack tips are determined using principal component analysis. The tips are tracked in the image sequence and the velocities between the time stamps of the images are derived. A major advantage of this method as compared to established techniques is in the fact of its allowing for spatio-temporally resolved, full-field measurements rather than point-wise measurements and that information on crack width can be obtained simultaneously. To validate the experimentation, the authors processed image sequences of tests on four compact-tension specimens performed on a split-Hopkinson tension bar. The images were taken by a high-speed camera at a frame rate of 160,000 images per second. By applying to these datasets the image sequence processing procedure as developed, crack propagation velocities of about 800 m/s were determined with a precision in the order of 50 m/s.

Road surface monitoring more specifically crack detection on the surface of the road pavement is a complicated task which is found vital due to critical nature of roads as elements of transportation infrastructure. Cracks on the road pavement is detectable using remotely sensed imagery or car mounted platforms. UAV’s are also considered as useful tools for acquiring reliable information about the pavement of the road. In This paper, an automatic method for crack detection on the road pavement is proposed using acquired videos from UAV platform. Selecting key frames and generating Ortho-image, violating non road regions in the scene are removed. Then through an edge based approach hypothesis crack elements are extracted. Afterwards, through SVM based classification true cracks are detected. Developing the proposed method, the generated results show 75% accuracy in crack detection while less than 10% of cracks are omitted.

Abstract: The most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) is the presence of poly-PR/GR dipeptide repeats which are encoded by the C9orf72 gene. Recently, it was shown that poly-PR/GR alters chromatin accessibility which results in stabilization and enhancement of transcriptional activity of the tumor suppressor p53 in several neurodegenerative disease models. Reduction of p53 protein levels in cell and model organisms protects against neurotoxicity of poly-PR, and partially protects against neurotoxicity of poly-GR. Here, we aimed to study the detailed molecular mechanisms how p53 contributes to poly-PR/GR mediated neurodegeneration. Using a combination of biophysical techniques such as nuclear magnetic resonance (NMR) spectroscopy, fluorescence polarization, turbidity assays and differential interference contrast (DIC) microscopy, we found that p53 physically interacts with poly-PR/GR and triggers liquid-liquid phase separation of p53. We identified p53 transactivation domain 2 (TAD2) as the main binding site for PR25/GR25 and show that binding of poly-PR/GR to p53 is mediated by a network of electrostatic and/or hydrophobic interactions. Our findings might help to understand the mechanistic role of p53 in poly-PR/GR - associated neurodegeneration.

In this paper, we introduce a new class of open sets that is called is*-open set . Also, we present the notion of is*-continuous, is*-open, is*-irresolute, is*-totally continuous, and is-contra-continuous mappings, and we investigate some properties of these mappings. Furthermore, we introduce some is*-separation axioms, and is*-mappings are related with is*-separation axioms. . .

Mill scale is the by-product of iron and steel industry. It can be recycled via sinter plant or solid as sinter feed materials. 85 to 90% of the constituent particles are more than 0.008 inches. The iron content is near around 70 %, with a very small amount of alkaline compounds and non-ferrous metals. Mill scale is polluted and contaminated with lubricants, oils and greases from the equipment. In this experiment for recovering of oil from mill scale, it is treated with three different methods. Then all methods were compared according to the ability of oil elimination and iron recovered. After washing and boiling with surfactants, large amount of polluted waste water becomes a problem for environment so this wastewater was utilized for making of Microbial Fuel Cells (MFCs), production of electricity in MFC depends on the biodegradation of organic materials, so different waste were added in wastewater for making MFC. The remaining of MFC was converted in bioethanol, biodiesel and biofertilizer. So this research is economical and environmentally friendly and fulfilled the important aspect of green environment with zero waste. It will be a mile stone in the research of metallurgy, environmental engineering, recycling technology and zero waste management.

Existing studies often lack a systematic solution for Unmanned Aerial Vehicles (UAV) inspection system, which hinders their widespread application in crack detection. To enhance its practicality, this study proposes a formal and systematic framework for UAV inspection systems, specifically designed for automatic crack detection and pavement distress evaluation. The framework integrates UAV data acquisition, deep learning based crack identification, and road damage assessment in a comprehensive and orderly manner. Firstly, the flight control strategy is presented, and road crack data is collected using the DJI Mini 2 UAV imagery, establishing a high-quality UAV crack image datasets with ground truth information. Secondly, a validation and comparison study is conducted to enhance the automatic crack detection capability and provide an appropriate deployment scheme for UAV inspection systems. This study develops automatic crack detection models based on mainstream deep learning algorithms(namely, Faster-RCNN, YOLOv5s, YOLOv7-tiny, and YOLOv8s) in urban road scenarios. The results demonstrate that the Faster-RCNN algorithm achieves the highest accuracy and is suitable for online data collection of UAV and offline inspection at work stations. Meanwhile, the YOLO models, while slightly lower in accuracy, are the fastest algorithm and are suitable for lightweight deployment of UAV with online collection and real-time inspection. Quantitative measurement methods for road cracks are presented to assess road damage, which will enhance the application of UAV inspection systems and provide factual evidence for maintenance decisions made by road authorities.

The analysis concerned a thin-walled plate with a circular central hole made of CFRP (Carbon Fiber Reinforced Polymer) material. The test object was subjected to a tensile test to investigate the cracking mechanism of the composite structure. The tests were performed using two independent test methods experimentally and numerically. In the experiment, the force was recorded as a function of elongation of the tensile plate and the elongation of the plate was investigated using an Aramis non-contact optical measurement system. As part of the numerical analysis, an FEM model adequate to the experimental conditions was performed in the Abaqus system. The fracture process was modeled using the extended finite element method XFEM. This approach enabled the structure of the composite to be investigated over the full range of tensile loading. The behaviour of the circular hole plate before the damage symptoms was investigated, the damage initiation force was determined, then the initial cracking and delamination of the layers were analysed, as well as the crack propagation process leading to the complete failure of the composite structure (cracking of all laminate layers).

The effects of build orientation and heat treatment on the crack growth behavior of 316L stainless steel (SS) fabricated via a selective laser melting (SLM) additive manufacturing process were investigated. Significant growth of available research results of additively manufactured metallic parts still needs to be improved. The most important issue connected with properties after additive manufacturing is properties high anisotropy, especially from the fatigue point of view. The research included crack growth behavior of additively manufactured 316L in comparison to conventionally made reference material. Both groups of samples were obtained using precipitation heat treatment. Different build orientation in additively manufactured samples and rolling direction in reference samples were taken into account as well. Precipitation heat treatment of additively manufactured parts allowed to reach similar microstructure and tensile properties to elements conventionally made. The heat treatment positively affected fatigue properties. Additionally, precipitation heat treatment of additively manufactured elements significantly affected the reduction of fatigue cracking velocity and changed the fatigue cracking mechanism.

The analysis of network structure is essential to many scientific areas, ranging from biology to sociology. As the computational task of clustering these networks into partitions, i.e., solving the community detection problem, is generally NP-hard, heuristic solutions are indispensable. The exploration of expedient heuristics has led to the development of particularly promising approaches in the emerging technology of quantum computing. Motivated by the substantial hardware demands for all established quantum community detection approaches, we introduce a novel QUBO based approach that only needs number-of-nodes many qubits and is represented by a QUBO-matrix as sparse as the input graph's adjacency matrix. The substantial improvement on the sparsity of the QUBO-matrix, which is typically very dense in related work, is achieved through the novel concept of separation-nodes. Instead of assigning every node to a community directly, this approach relies on the identification of a separation-node set, which - upon its removal from the graph - yields a set of connected components, representing the core components of the communities. Employing a greedy heuristic to assign the nodes from the separation-node sets to the identified community cores, subsequent experimental results yield a proof of concept. This work hence displays a promising approach to NISQ-ready quantum community detection, catalyzing the application of quantum computers for the network structure analysis of large scale, real world problem instances.}

NMR spectral datasets, especially in systems with limited samples, can be difficult to interpret if they contain multiple chemical components (phases, polymorphs, molecules, crystals, glasses, etc…) and the possibility of overlapping resonances. In this paper, we benchmark several blind source separation techniques for analysis of NMR spectral datasets containing negative intensity. For benchmarking purposes, we generated a large synthetic datasbase of quadrupolar solid-state NMR-like spectra that model spin-lattice T1 relaxation or nutation tip/flip angle experiments. Our benchmarking approach focused exclusively on the ability of blind source separation techniques to reproduce the spectra of the underlying pure components. In general, we find that FastICA (Fast Independent Component Analysis), SIMPLISMA (SIMPLe-to-use-Interactive Self-modeling Mixture Analysis), and NNMF (Non-Negative Matrix Factorization) are top-performing techniques. We demonstrate that dataset normalization approaches prior to blind source separation do not considerably improve outcomes. Within the range of noise levels studied, we did not find drastic changes to the ranking of techniques. The accuracy of FastICA and SIMPLISMA degrades quickly if excess (unreal) pure components are predicted. Our results indicate poor performance of SVD (Singular Value Decomposition) methods, and we propose alternative techniques for matrix initialization. The benchmarked techniques are also applied to real solid state NMR datasets. In general, the recommendations from the synthetic datasets agree with the recommendations and results from the real data analysis. The discussion provides some additional recommendations for spectroscopists applying blind source separation to NMR datasets, and for future benchmark studies. Applications of blind source separation to NMR datasets containing negative intensity may be especially useful for understanding complex and disordered systems with limited samples and mixtures of chemical components.

Bioprocesses for the production of renewable energies and materials lack efficient separation processes for the utilized microorganisms such as algae and yeasts. Dissolved air flotation (DAF) and microflotation are promising approaches to overcome this problem. The efficiency of these processes depends on the ability of microorganisms to aggregate with microbubbles in the flotation tank. In this study, different new or adapted aggregation models for microbubbles and microorganisms are compared and investigated for their range of suitability to predict the separation efficiency of microorganisms from fermentation broths. The complexity of the heteroaggregation models range from an algebraic model to a 2D population balance model (PBM) including the formation of clusters containing several bubbles and microorganisms. The effect of bubble and cell size distributions on the flotation efficiency is considered by applying PBMs, as well. To determine the impact of the model assumptions, the modeling approaches are compared and classified for their range of applicability. Evaluating computational fluid dynamics (CFD) of a DAF system shows the heterogeneity of the fluid dynamics in the flotation tank. Since analysis of the streamlines of the tank show negligible backmixing, the proposed aggregation models are coupled to the CFD data by applying a Lagrangian approach.

This paper aims to quantify the influence of hydrogen embrittlement on Wierzbicki and Xue (W-X) model parameters. This model has 4 parameters which have been obtained by tensile tests on smooth specimens, tensile notch specimens, single notch tensile specimens (SENT) and pure shear specimens. Hydrogen embrittlement has been obtained by electrolytic method. Application of the (W-X) model has been done to get the local resistance used to predict failure by the Volumetric Method (VM). An example is given for the case of an embedded pipe submitted to service pressure and lateral seismic displacement. The effect of this displacement is then assimilated to the shearing of the straight section of the pipe. The pipe shows a corrosion defect considered a semi-elliptical crack. The influence of hydrogen embrittlement on local strain resistance and safety factors is discussed.

In recent years, two-dimensional (2D) materials have attracted significant attention due to their distinctive properties, including exceptional mechanical flexibility and tunable electronic properties. Via the first-principles calculation, we investigate the effect of strain on the electronic properties of monolayer SnP2S6 and GeP2S6. We find that monolayer SnP2S6 is an indirect band gap semiconductor, while monolayer GeP2S6 is a direct band gap semiconductor. Notably, under uniform biaxial strains, SnP2S6 undergoes an indirect-to-direct band gap transition at 4.0% biaxial compressive strains, while GeP2S6 exhibits a direct-to-indirect transition at 2.0% biaxial tensile strain. The changes of the conduction band edge can be attributed to the high-symmetry point Γ being more sensitive to strain than K. Thus, the relocation of the conduction-band and valence-band edges in monolayer SnP2S6 and GeP2S6 induces a direct-to-indirect and indirect-to-direct band-gap transition respectively. Consequently, the strain is an effective band engineering scheme which is crucial for the design and development of next-generation nanoelectronic and optoelectronic devices.

Cannabidiol (CBD) is a non-intoxicating compound extracted from Cannabis sativa, showing antidepressant-like effects in different rodent models. However, inconsistent results have been described depending on the species and the strain used to assess depressive-like behaviour. Moreover, only a few studies have investigated the effect of CBD in female rodents. Therefore, we aimed to i) investigate the effects of CBD in two different strains of mice (Swiss and C57BL/6) and in a rat model of depression based on selective breeding (Flinders Sensitive and Resistant Lines, FSL and FRL) subjected to tests predictive of antidepressant-like effects; and ii) investigate the influence of sex in the effects of CBD in both mice and rats. CBD induced an antidepressant-like effect in male Swiss but not in female Swiss or C57BL/6 mice in the tail suspension test (TST). In male FSL rats, CBD produced an antidepressant-like effect one-hour post-injection. However, in female FSL, CBD induced a bimodal effect, increasing the immobility time at one hour and decreasing it at two hours. Ketamine produced an antidepressant-like effect in male and female FSL rats at different doses. In conclusion, strain, sex, and administration time affect CBD's behavioural response to rodents exposed to tests predictive of antidepressant effects.

Polydimethylsiloxane (PDMS) is one of the most popular elastomers and has been used in different fields, especially in biomechanics research. Among the many interesting features of this material, its hyperelastic behaviour stands out, which allows the use of PDMS in various applications, like the ones that mimic soft tissues. However, the hyperelastic behaviour is not linear and needs detailed analysis, especially the characterization of shear strain. In this work, two approaches, numerical and experimental, were proposed to characterize the effect of shear strain on PDMS. The experimental method was implemented as a simple shear testing associated with 3D digital image correlation and was made using two specimens with two thicknesses of PDMS (2 and 4 mm). A finite element software was used to implement the numerical simulations, in which four different simulations using the Mooney-Rivlin, Yeoh, Gent, and Polynomial hyperelastic constitutive models were performed. These approaches showed that the maximum value of shear strain occurred in the central region of the PDMS, and higher values emerged for the 2 mm PDMS thickness. Qualitatively, in the central area of the specimen, the numerical and experimental results have similar behaviours and the values of shear strain are close. For higher values of displacement and thicknesses, the numerical simulation results move further away from experimental values.

Structural displacement is an important metric for assessing structural conditions because it has a direct relationship with the structural stiffness. Many bridge displacement measurement techniques have been developed, but most methods require fixed reference points in the vicinity of the target structure which limits field implementations. A promising alternative is to use reference-free measurement techniques that indirectly estimate the displacement by using measurements such as acceleration, and strain. This paper proposes novel reference-free bridge displacement estimation by the fusion of single acceleration with pseudo-static displacement derived from co-located strain measurements. First, we propose a conversion of the strain at the center of a beam into displacement based on the geometric relationship between strain and deflection curves with reference-free calibration. Second, an adaptive Kalman filter is proposed to fuse the displacement generated by strain with acceleration by recursively estimate the noise covariance of displacement from strain measurements which is vulnerable to measurement condition. Both numerical and experimental validations are presented to demonstrate the efficiency and robustness of the proposed approach.

Research on White Etching Cracks (WEC) apparent in multiple bearing applications has identified various drivers to cause them. Lubricants, Electricity combined with contact mechanics are proven to catalyze WEC significantly. However, none of them is solely causing WEC by its own, instead combinations discretize whether WEC appears or not. Hence, the WEC topic appears to be multidimensional, making WEC still unpredictable. The current paper is about a systematic study by the use of a DGBB test rig on how lubricant chemicals combined with electricity and by varying oil flow and pressure lead to WEC. It becomes evident, that even WEC critical conditions turn to be WEC free by simply increasing the oil flow and decrease the contact pressure.

On the aero-engine combustor liner, a phenomenon of overheating resembling a hot spot exists, accompanied by a preferential peeling of the YSZ thermal barrier coating that will negatively affect the service life of the component. The temperature gradient of the hot spot may affect the YSZ fracture pattern.In this paper, the morphological and property changes of YSZ sintering is investigated experimentally, and a coupled analysis of the YSZ Crack Propagation Mode under the hot spot is performed using ABAQUS. The results show that the pore fractal size D of YSZ increases by 15%. Inside the hot spot region, the coating has a shear stress of 75MPa. By inserting Cohesive units globally in the model to simulate the random crack initiation and propagation, unlike the thinning of YSZ layered peeling caused by uniform superheating, hot spot will cause the crack initiation at the tip of the pores inside the coating and the oblique propagation, eventually forming an oblique crack connection through the pores. When the temperature gradient reaches 30K/mm, the crack propagation is 40% greater than in a uniform temperature field; consequently, the YSZ in the hot spot boundary region with a greater temperature gradient results in more severe bulk peeling.

Fracture analysis of reinforced concrete deep beam strengthened with carbon fiber-reinforced polymer (CFRP) plates was carried out. The present research aims to find out whether the crack propagation in a strengthened deep beam follows linear elastic fracture mechanics (LEFM) theory or nonlinear fracture mechanics theory. To do so, a new energy release rate based on nonlinear fracture mechanics theory was formulated on the finite element method and the discrete cohesive zone model (DCZM) was developed in deep beams. To validate and compare with numerical models, three deep beams with rectangular cross-sections were tested. The code results based on nonlinear fracture mechanics models were compared with experimental results and ABAQUS results carried out based on LEFM. The predicted values of initial stiffness, yielding point and failure load, energy absorption, and compressive strain in the concrete obtained by the proposed model were very close to the experimental results. However, the ABAQUS software results have greater differences with the experimental results. For example, the predicted failure load for the shear-strengthened deep beam using the proposed model has only 6.3% differences compared to the experimental result. However, the predicted failure load using ABAQUS software based on LEFM has greater differences (25.1%) compared to the experimental result.

We aimed to investigate the relationship between membrane material and development of membrane fouling in a membrane bioreactor (MBR) using membranes with different pore sizes and hydrophilicities. Batch filtration tests were performed using submerged single hollow fiber membrane ultrafiltration (UF) modules with different polymeric membrane materials including cellulose acetate (CA), polyethersulfone (PES), and polyvinylidene fluoride (PVDF) with activated sludge taken from a municipal wastewater treatment plant. The three UF hollow fiber membranes were prepared by a non-solvent-induced phase separation method and had similar water permeabilities and pore sizes. The results revealed that transmembrane pressure (TMP) increased more sharply for the hydrophobic PVDF membrane than for the hydrophilic CA membrane in batch filtration tests, even when membranes with similar permeabilities and pore sizes were used. PVDF hollow fiber membranes with smaller pores had greater fouling propensity than those with larger pores. In contrast, CA hollow fiber membranes showed good mitigation of membrane fouling regardless of pore size. The results obtained in this study suggest that the surface hydrophilicity and pore size of UF membranes clearly affect the fouling properties in MBR operation when using activated sludge.