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Sustainable professional integrity is the pivoting factor for maintaining the expected ethical standard of a profession. Whereas privacy of a user becomes vulnerable due to the digital transactions performed on the web. To this end, we propose a distributed framework, Jurisprudence, that preserves a user's privacy by preventing concurrent active sessions. The proposed model enables online transactions using one-time password (BLOCK-OTP) based blockchain multi-factor authentication. It encapsulates the users details and preserves the privacy of the user by preventing the invocation of concurrent transaction sessions. We deployed the system into the Ethereum test blockchain environment and tested the framework. We envisage our model to be suitable for the detection of fraudulent and malicious activities in near future. [ABSTRACT FROM AUTHOR]

This study reports the methodology for reconstructing anomalous temperature index series of China in 1368–1911 based on the REACHES database which digitizes the Chinese records quoted in the Compendium of Meteorological Records of China in the Last 3000 Years. The reconstruction adopts an ordinal scale index approach ranging from −2 (very cold) to 1 (warm). Based on the grading criteria, a total of 12,871 records were retrieved through a standard coding system established at REACHES. Sensitivity experiments were performed to test robustness of the index system and a reasonability test was conducted to develop an appropriate method for deriving areal mean temperature index. The reconstructed series were validated through comparison with early instrumental data from Global Historical Climatology Network which shows good correlations and reliability of the REACHES reconstructed index data. Annual and semi-annual (winter and summer) temperature index data series were released for the whole domain as well as the 3- and 15-subregion geographical domains in China. [ABSTRACT FROM AUTHOR]

A disturbance in a power system causes the frequency to deviate from its nominal value. The load and generation of the system are strategically adjusted to restore the synchronous frequency. This paper introduces novel shrinking-horizon model predictive control (MPC) technique, which employs a centralized controller for managing the load-frequency of a single-area power system and distributed controllers for multi-area systems. The controller optimally changes generation settings and sheds non-critical loads to make the frequency and tie-line power deviation zero. In contrast to existing approaches that use an approximate first-order transfer function model, this paper presents a structure-preserving linear state-space model for power systems. This model takes into account frequency and voltage dependencies of both load and generation, allowing for more accurate representation of power system behavior. During rescheduling, the controller minimizes additional cost associated with changes while satisfying various operational and physical constraints. The paper conducts several case studies using IEEE test systems to devise corrective action plans for both under- and over-frequency scenarios. The proposed controller's robustness is tested against disturbances originating from renewable energy sources. Furthermore, a performance comparison is drawn between the proposed controller and existing control techniques. The comparative analysis indicates that the proposed approach consistently outperforms other controllers in terms of dynamic performance improvement, measured by parameters such as settling time, overshoot, undershoot, and error reduction. It is observed that the maximum undershoot and the settling time of the frequency is the least for centralized control. Comparative studies indicate that under different circumstances, the proposed approach outperforms other controllers in dynamic performance improvement, measured by settling time, overshoot, undershoot, and error reduction. The net rescheduling cost obtained by the proposed centralized MPC, cooperative distributed MPC, and non-cooperative distributed MPC-based controllers is 38, 25, and 24% lower than the conventional PI controller used for LFC of IEEE 39-bus system. This validates the suggested controllers' cost-effectiveness. [ABSTRACT FROM AUTHOR]

Power systems are being confronted with a number of ecological and financial difficulties, and distributed generators (DGs) will be an effective solution. However, inappropriate DGs incorporation may cause additional power stability issues and system losses. DGs that are strategically positioned could solve these issues. This study implements the multi-objective fuzzified firefly algorithm (MOFFA) to integrate optimally sized DGs with six different objective functions (OBFs) on a standard IEEE 33 bus system as well as a functional 62 bus Indian distribution system (IDS) of Tamil Nadu power sector. Three distinct scenarios of multi-objective optimization problems are addressed. In Scenario 1, the objective is to minimize power loss, bus voltage deviation, and cost simultaneously. In Scenario 2, the focus is on minimizing power loss, enhancing voltage stability index (VSI), and reducing toxic gasses outflow. Lastly, in Scenario 3, the goal is to minimize bus voltage deviation, cost, and lower average voltage total harmonic distortion THDv. The integration of DGs in the IEEE-33 bus test system resulted in remarkable improvements through the optimization process. Specifically, the power loss is reduced by approximately 65.64%, the cost decreased by about 29.58%, and the toxic discharge was lowered by approximately 66.69%. In the IDS-62 bus test system, the optimization results in a noteworthy reduction of power loss to 5.1% of the total load. These substantial reductions highlight the significant progress made, showcasing the effectiveness of the optimization process and the integration of DGs in reducing energy wastage. [ABSTRACT FROM AUTHOR]

A transmission network is an important part of the power transformers to transmit the generated energy and power to the load centers. As such, the transmission network requires significant expansion costs to alleviate congestion as well as to supply an acceptable reliability level. In this matter, transmission network expansion planning (TNEP) is known as a large-scale mathematical problem including long-term effects of the power system. In this paper, long-term effect of demand response (DR) is explored on the loading rate of the system as well as subsequent line loading influence on line failure rates. To investigate the DR effectiveness on TNEP, its cost is addressed in the objective of the proposed mixed integer nonlinear planning model. Moreover, alleviating the failure rate of old lines can decrease the construction of new lines while providing the desirable reliability of the system. Furthermore, a decrease in the loading rate of existing transmission lines provides valuable gains at the horizon year. Thus, the value of the transmission system in the objective function would increase by DR. Besides, peak clipping prevents local marginal price (LMP) inflation and smoothens the LMP profile across the system buses; so congestion surpluses will decrease. Afterward, the sensitivity analysis in the simulation part is implemented to investigate how demand response can influence on value of LMP at different nodes. Eventually, the developed model is executed on IEEE 24-bus reliability test system for three scenarios in order to assess the efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

A highly specific and sensitive rapid two-signal assay was developed for the detection of Salmonella typhimurium in foods of animal origin. The invA gene of Salmonella was used as the biorecognition element and recombinase-assisted amplification (RAA) technology for signal amplification. By utilizing the specific recognition and efficient trans-cleavage activity of CRISPR/Cas12a, point-of-care testing (POCT) for S. typhimurium was achieved via lateral flow strips (LFS) and personal glucometer (PGM) biosensors as dual signal readout systems, with sensitivities of 33 CFU/mL and 20 CFU/mL, respectively. Users can select the appropriate test system on the basis of specific application requirements: LFSs are ideal for rapid onsite screening, whereas glucometer biosensors offer precise quantitative determination. This approach simplifies the use of large instruments and overcomes site constraints, demonstrating good accuracy and applicability in animal-derived samples, with significant potential for the detection of other pathogens and for use in restricted environments. [ABSTRACT FROM AUTHOR]

Automated testing of GUI elements on electronic screens by machine vision is widely used in smart manufacturing production lines. However, in the complex environment of factories, interference factors such as light reflection, platform vibration, and placement angle make it difficult for testing robots to recognize and locate GUI elements on the equipment's screen to be tested. In addition, the recognition algorithms based on screen GUI elements currently have problems such as slow detection speed and large model size, which limit the deployment of detection models on test robots. To address these problems, this paper proposes a lightweight model that can overcome the interference of the factory environment based on the YOLOv5 algorithm for recognizing GUI elements. First, a reinforced position and channel attention module (PCA) is proposed to enhance the extraction and fusion ability of weak feature elements affected by interference; then, a three-way feature pyramid network (TWFPN) module is constructed at the intermediate feature layer of the neck structure to provide more accurate localization information. Meanwhile, the loss function of the original algorithm is replaced with SIoU to improve the convergence speed. Finally, a lightweight structure combining the Ghost module and PConv is introduced into the model to reduce the model parameters and improve the detection speed. The method was evaluated on the constructed feature-enhanced GUI (FE_GUI) dataset. The final model shows a 2.7% improvement in average accuracy (mAP@0.5), a 30% reduction in model weight, and an increase in detection speed to 85 FPS compared to the original YOLOv5. The results demonstrate that the method solves the issues of element recognition and model deployment for a vision test system and surpasses existing models in terms of recognition accuracy and detection speed. [ABSTRACT FROM AUTHOR]

Hybrid estimation architectures make it possible to combine the widespread availability of conventional SCADA data with the improved accuracy and higher sampling rates of synchronized phasor measurements. A particularly appealing hybrid scheme is the so-called APSI architecture, which comprises two sequential estimation stages: a conventional SCADA-based state estimator, whose outcome is then treated as a priori information by a second stage, where available phasor measurements are cumulatively processed. As desirable features, this architecture preserves existing SCADA-based estimators and waives PMU-observability requirements. On the other hand, bad data processing for APSI estimators is a topic that still deserves additional research efforts. In this paper, we set out to improve the resilience of APSI estimators against bad data occurring both within synchrophasor measurements and SCADA data. The proposed strategy comprises two distinct actions: (a) replacing conventional algorithms in the second APSI stage by a more robust one, capable of automatic suppressing outliers in both data classes, and (b) adopting a method for tracing down SCADA gross measurements from a priori data previously identified as erroneous. The performance of the proposed methodology is assessed through tests conducted on the IEEE 14-bus, 57-bus and 118-bus test systems. [ABSTRACT FROM AUTHOR]

Crystalline materials have atomic-scale fluctuations in their chemical composition that modulate various mesoscale properties. Establishing chemistry–microstructure relationships in such materials requires proper characterization of these chemical fluctuations. Yet, current characterization approaches (e.g., Warren–Cowley parameters) make only partial use of the complete chemical and structural information contained in local chemical motifs. Here we introduce a framework based on E(3)-equivariant graph neural networks that is capable of completely identifying chemical motifs in arbitrary crystalline structures with any number of chemical elements. This approach naturally leads to a proper information-theoretic measure for quantifying chemical short-range order (SRO) in chemically complex materials and a reduced representation of the chemical motif space. Our framework enables the correlation of any per-atom property with their corresponding local chemical motif, thereby enabling the exploration of structure–property relationships in chemically complex materials. Using the MoTaNbTi high-entropy alloy as a test system, we demonstrate the versatility of this approach by evaluating the lattice strain associated with each chemical motif, and computing the temperature dependence of chemical-fluctuations length scale. [ABSTRACT FROM AUTHOR]

Global urbanization requires more stable and sustainable wastewater treatment to reduce the burden on the water environment. To address the problem of substrate inhibition of microorganisms during wastewater treatment, which leads to unstable wastewater discharge, this study proposes an approach to enhance the tolerance of bacterial community by artificially setting up a non-lethal high substrate environment. And the feasibility of this approach was explored by taking the inhibition of anammox process by nitrite as an example. It was shown that the non-lethal high substrate environment could enhance the nitrite tolerance of anammox bacterial community, as the specific anammox activity increasing up to 24.71 times at high nitrite concentrations. Moreover, the system composed of anammox bacterial community with high nitrite tolerance also showed greater resistance (two-fold) in response to nitrite shock. The antifragility of the system was enhanced without affecting the operation of the main reactor, and the non-lethal high nitrite environment changed the dominant anammox genera to Candidatus Jettenia. This approach to enhance tolerance of bacterial community in a non-lethal high substrate environment not only allows the anammox system to operate stably, but also promises to be a potential strategy for achieving stable biological wastewater treatment processes to comply with standards. To address substrate inhibition in wastewater treatment, the authors propose a non-lethal high substrate environment to enhance microbial community resistance. Testing this on anammox systems, they find increased nitrite tolerance and stability, with a shift to the dominant genus Candidatus Jettenia. [ABSTRACT FROM AUTHOR]

The power factor correction converter is the function of the front-end converter, followed by the DC–DC converter of the electric vehicle charger. It improves the power factor and regulates the output voltage and current. This research article proposes the Golden Eagle optimization for fractional order PI (FOPI) controller for Single Ended Primary Inductor Converter (SEPIC) power factor correction. The Golden eagle optimization is based on its knowledge of hunting tactics at various degrees of spiral trajectories to catch the prey. The FOPI controller has a broad range of controller parameters that provide better control and performance of the converter. The tuning of the parameters of the FOPI controller is optimized in Golden Eagle Optimization, and the Integral Absolute error with Integral Square error is used for the objective function. The optimized parameters of FOPI compare with the conventional PI controller performance. The SEPIC converter is designed and derived from the state space model by state space averaging, and the reduced model is obtained through the moment matching method. This system is tested under MATLAB/SIMULINK, and simulation results show improved settling time, fast dynamic response, reduction of inrush current, less harmonic distortion, and stability. [ABSTRACT FROM AUTHOR]

Fault fracture zones are rock formations commonly encountered in submarine tunnels, and the diffusion mechanism of slurry in fault fracture zones has a crucial impact on submarine tunnel reinforcement. Based on the seepage equation of Bingham fluid, the tortuosity parameter, fractal theory, and variable viscosity equation are introduced to establish a spherical permeation grouting model of Bingham fluid considering the slurry diffusion path and viscosity time variability. The viscosity variation law with time of sulfur aluminate cement slurry under different seawater admixture conditions was tested, and the time-varying equation of viscosity of sulfur aluminate cement slurry was obtained by fitting. A set of fault fracture zone permeation grouting test system was developed, and a fault fracture zone grouting simulation test was carried out. The study shows that the diffusion distance calculated without considering the influence of slurry diffusion path and seawater is 1.63–1.91 times of the test value, which obviously overestimates the diffusion distance; the diffusion distance calculated with considering the influence of diffusion path and seawater is 1.06–1.35 times of the test value, which is in good agreement with the test value. The research results can provide some theoretical support for the design of grouting in seawater environment. [ABSTRACT FROM AUTHOR]

Scenario-based verification defines the current state of the art for examining a vessel's control systems for reliability and safety. However, software updates after release can only be covered to a limited extent. To take changes to a deployed system into account, the design and test phase must be harmonized with the operational phase. For all phases, regulatory, technical and safety requirements provide the scope to which the development process and the scenario-based tests need to be aligned and whose specifications the System under Test (SuT) must adhere to during operation. For this reason, a procedure is needed that converts the requirements into a format that can be utilized across all phases and measured in a structured manner comparing the original system to the updated version. This work does so by combining scenario-based verification methods with formal composition and monitoring techniques based on contract-based design into an integrated development approach. It is shown how safety requirements can be transferred into a Verification Descriptor that in turn provides the foundation for the division into model-based system development, contract-based virtual integration testing and a scenario-based test environment. For the entire lifecycle of the System under Test (SuT) to be included, the extended scenario and contract descriptors are carried forward up to the operational phase, such that the previously defined properties of the SuT can be monitored and validated during runtime. The approach is designed alongside a minimal-viable system and evaluated on an actual implementation of a safety-critical maritime LiDAR-based positioning system. [ABSTRACT FROM AUTHOR]

The results of an experiment assessing the applicability of solutions of 6-oxo-2-phenylimidazo[1,2-b]pyrido[4,3-e][1,2,4]triazine-7(6H)-yl)acetic acid on plates and cellulose substrates for detecting excessive levels of volatile organic compounds associated with endometritis inflammation relative to biologically normal levels are considered. The fluorescent properties of the dye are studied using gynecological mucus from cows collected in various periods (pre- and post-partum) and nasal mucus from newborn calves. The test system responses were compared with clinically established diagnoses and the results of a microbiological study. An evaluation of the test systems revealed a false positive rate of no more than 11% and a false negative rate of 2%. Other characteristics, such as specificity, accuracy, and precision of the test systems based on 6-oxo-2-phenylimidazo[1,2-b]pyrido[4,3-e][1,2,4]triazine-7(6H)-yl)acetic acid were also assessed. The potential application of this fluorophore to the rapid on-site diagnosis of endometritis inflammation in cows is considered promising based on these findings. [ABSTRACT FROM AUTHOR]

Complex practical system designs pose significant challenges from a research perspective, often resulting in high computational requirements for analysis. Model order reduction (MOR) is a valuable technique to address this issue. This study provides a comprehensive review of the literature on MOR, focusing specifically on high-dimensional complex systems. It examines the fundamental theories and limitations of established MOR methods, including the Factor division method, Pade approximation (PA) method, Stability equation (SE) method, Differentiation method, and Routh approximation (RA) method. The study also investigates the frequency domain approach for obtaining a reduced-order model (ROM). Among the MOR methods, the PA method is a widely studied and practical approach that aims to retain the crucial dynamics of a high-dimensional complex system. This survey presents a detailed discussion of the PA method for obtaining the ROM. Additionally, six test systems are analyzed to compare the step and frequency responses generated by various MOR strategies. The integral square error criterion is used to assess the effectiveness of the reduction procedures. Finally, the study proposes a new system abatement method based on Atomic Orbital Search (AOS) optimization for obtaining the ROM of large-scale linear time-invariant (LTI) systems and designing controllers based on the reduced order model. [ABSTRACT FROM AUTHOR]

Software systems and product lines often use configurable features to specify a portfolio of product variants from a common core. Typically, their requirements also include constraints on which combinations of features are valid. Especially for larger systems and systems where the specifications are scattered among documents, the analysis of a new product's variability-related requirements is challenging. To address this, we introduce a scalable, tool-supported framework that uses a variability model to automate checks for missing and inconsistent features and constraints. Our approach also extends and scales traditional variability requirements engineering by incorporating combinatorial interaction testing techniques to build valid product variants covering all configurations in the variability model and to automatically discover faulty feature settings in failed builds. Results from evaluation on two configurable systems show that our framework is effective both at early detection of missing, incorrect, and inconsistent variability requirements and at later finding faulty feature configurations. [ABSTRACT FROM AUTHOR]

A common way of exposing functionality in contemporary systems is by providing a Web-API based on the REST API architectural guidelines. To describe REST APIs, the industry standard is currently OpenAPI-specifications. Test generation and fuzzing methods targeting OpenAPI-described REST APIs have been a very active research area in recent years. An open research challenge is to aid users in better understanding their API, in addition to finding faults and to cover all the code. In this paper, we address this challenge by proposing a set of behavioural properties, common to REST APIs, which are used to generate examples of behaviours that these APIs exhibit. These examples can be used both (i) to further the understanding of the API and (ii) as a source of automatic test cases. Our evaluation shows that our approach can generate examples deemed relevant for understanding the system and for a source of test generation by practitioners. In addition, we show that basing test generation on behavioural properties provides tests that are less dependent on the state of the system, while at the same time yielding a similar code coverage as state-of-the-art methods in REST API fuzzing in a given time limit. [ABSTRACT FROM AUTHOR]

This paper proposes a combination of a nonlinear feedback linearization control (FLC) and a second-order sliding mode (SOSM) controller to enhance the effectiveness and performance of variable speed control in an open-ended winding induction motor (OEWIM). The literature indicates that the traditional FLC with a PI controller is susceptible to disruptions from its internals as well as outside interference. The conventional sliding-mode controller can offer robust control. However, it suffers from the chattering phenomenon. The SOSMC, based on a super-twisting algorithm (STA), was designed and implemented to overcome all of these drawbacks. It is extremely difficult to obtain the optimum parameters for each FLC and SOSM controller that give good results using traditional methods due to the relatively large number of parameters. Moreover, a novel approach based on the linearly decreasing method for both inertia weight and learning constant of the particle swarm optimization (PSO) algorithm was presented to improve the variable speed control of the OEWIM. To maintain a constant switching frequency, decrease harmonic distortion, and reduce common-mode voltage (CMV), a space vector modulation technique of a seven-level inverter is suggested and implemented by supplying each end of an open-ended stator winding induction motor with three-level inverters. The advantages of the suggested control system have been confirmed using simulated results of various tests of the complete system. [ABSTRACT FROM AUTHOR]

This paper presents a novel method for conducting load flow (LF) calculations in radial distribution networks. The method is based on solving LF calculations as a constrained minimization problem using nonlinear programming CONOPT solver, integrated into general algebraic modeling system (GAMS) environment. The performance of the proposed CONOPT solver is evaluated on IEEE 33-bus and IEEE 69-bus test systems, where four cases were considered. In the first case, LF calculations were performed on standard test systems, and the results obtained using the proposed CONOPT solver were compared with three well-known power systems analysis software: EPSA, NEPLAN, and DigSilent. In the second and third cases, CONOPT is used for LF calculation in the presence of distributed generators (DGs) and shunt capacitors (SCs), respectively. In the fourth case, the proposed CONOPT solver is employed for LF calculation in the presence of electric vehicles (EVs). The simulation results show that the CONOPT solver outputs are accurate and fast in their convergence to global solutions in standard test systems in the presence of DGs, SCs, and EVs. [ABSTRACT FROM AUTHOR]

The rheological parameters of oil testing fluids play a crucial role in safely conducting oil testing operations, protecting reservoirs, and maintaining wellbore integrity, which are greatly influenced by temperature and pressure. This article conducted rheological experiments on commonly used potassium salt polymer systems and organic salt systems for oil testing fluids in the Bohai Bay Oilfield under 4–200 °C and 30–150 MPa. The experiments revealed the variation of rheological parameters with temperature and pressure. Nine commonly used rheological models were evaluated for their applicability to the two types of oil testing fluids. It was found that the Ross model was suitable for the potassium salt polymer system, while the power-law model was suitable for organic salt oil testing fluids. A new rheological parameter prediction model suitable for wide range of temperature and pressure and different testing fluid systems was proposed based on the optimized results. The average error for the potassium salt polymer system for oil testing fluids was 0.101%, and the error for the organic salt system for oil testing fluids was 0.113%. Both were superior to known rheological models and can meet the requirements of oil testing operations within the wide temperature and pressure range in the Bohai Bay Oilfield. [ABSTRACT FROM AUTHOR]

The purpose of this research is to address the problem of synchronization between two identical biological hyperchaotic snap oscillator systems with unknown parameters at a fixed time, as well as to design a new theory for synchronizing two different chaotic systems. Firstly, we designed an adaptive controller using Lyapunov stability and fixed-time stability theory to achieve synchronization between two identical biological hyperchaotic snap oscillator in fixed time under unknown parameters. Among the results obtained, we found that the synchronization time for system states occurred in a very short time compared to results in previous research. Secondly, we extended and generalized synchronization between non-identical chaotic systems by creating a theory for achieving synchronization in which adaptive control and fixed-time stability are combined. Through the new theory, the unknown parameters in chaotic systems were estimated, and the settling time was determined, which turned out to be very short and independent of the initial conditions of the system states. One of what makes the scheme important is that it can be easily applied to most chaotic and even hyperchaotic systems in the shortest possible time. Finally, we gave examples of different systems to test the feasibility and effectiveness of the scheme that was designed. [ABSTRACT FROM AUTHOR]

A long rigid-flexible coupling transmission shaft (RFCTS) is usually used to connect the dynamometer with the device under test (DUT) in semi-anechoic chamber. However, due to the parameter error and torsional vibration characteristic of RFCTS, load emulation loading accuracy of the test bench is lower. Therefore, the research focused on establishing a control-oriented vehicle powertrain system test bench (VPSTB) model based on RFCTS to further improve the load emulation loading accuracy. First, a 14-degrees of freedom (DOF) high-order lumped mass model of VPSTB is established, and the stiffness and moment of inertia equivalent parameters are obtained. Subsequently, a 7-DOF simplified control-oriented VPSTB model is established based on 14-DOF model, and the model parameters are identified by the recursive least squares estimation (RLSE) method with forgetting factor. Simultaneously, the natural frequency of 14-DOF high-order model and 7-DOF simplified model is calculated, then un-damped vibration response of the two models are compared and analyzed. Finally, simulation and experimental are carried out under open-loop and closed-loop conditions, which show that the effectiveness of 7-DOF simplified model parameters, and it also indicate that the 7-DOF simplified VPSTB model can achieve better loading accuracy of load emulation. [ABSTRACT FROM AUTHOR]

This paper introduces a test system for microwave-assisted dual-mode mechanical cutting of hard rock under true triaxial compression. The test system was developed by Northeastern University, China, to simulate the cutting and breaking of hard rock by a tunnel boring machine (TBM). The test system is mainly composed of a dual-mode mechanical cutting subsystem, a true triaxial loading subsystem and a high-power microwave presplitting subsystem. The system performs dual-mode cutting under true triaxial stress, applies a single sensor to monitor the three-dimensional force of the cutter head, and integrates the reduction in the vibration and resistance to torsion during the cutting process. Mechanical cutting tests of basalt under different amounts of microwave irradiation and true triaxial stress conditions were conducted in Chifeng, Inner Mongolia, China. The results showed that microwave radiation presplitting effectively improved the efficiency of mechanical rock breaking. However, after 180 s of microwave irradiation, true triaxial high stress inhibited the mechanical breaking of basalt in terms of the overall excavation depth. During the tests, each system performed stably. The test results verified the reliability of the test system. Highlights: A true triaxial stress microwave-assisted mechanical dual-mode cutting test system is independently developed. The proposed system simulates rock breaking by a microwave-assisted roadheader under different ground stress conditions. The cutting test system innovates in three main facets: it carries out a dual-mode cutting test system in rock breaking; it realizes a unified monitoring output of a single sensor for the three-dimensional force; and it integrates the seismic resistance and torsion resistance to create a smooth system body. As the cutting test is conducted, the effective influence range of microwave radiation on rock is verified, and the degree of influence of true triaxial high stress on microwave-assisted mechanical cutting is revealed, providing guidance for deep microwave-assisted rock breaking of roadheaders. The necessity and feasibility of the system development is thus verified. [ABSTRACT FROM AUTHOR]

Because of the crucial importance of finding a useful biomarker for further clinical trials in Machado-Joseph disease (MJD), and based on our previous studies, we aimed to evaluate whether the horizontal vestibulo-ocular reflex (VOR) gain could be a reliable neurophysiological biomarker for the clinical onset, severity, and progression of the disease. Thirty-five MJD patients, 11 pre-symptomatic genetically confirmed MJD subjects, and 20 healthy controls underwent a detailed epidemiological and clinical neurological examination including the Scale for the Assessment and Rating of Ataxia (SARA). Their VOR gain was measured using the video Head Impulse Test system. Twenty of the MJD patients were re-tested after a period of 1–3 years. Horizontal VOR gain was abnormal in 92% of MJD, 54% pre-symptomatic, and 0% healthy controls. Horizontal VOR gain in the MJD group was significantly negatively correlated with SARA score in the first (r=0.66, p<0.001) and second (r=0.61, p<0.001) examinations. There was also a significant negative correlation between the percentage of change in horizontal VOR gain and the percentage of change in SARA score across both examinations (r=−0.54, p < 0.05). A regression model of the SARA score with the horizontal VOR gain and disease duration as predictors demonstrated that both the horizontal VOR gain and the disease duration had an independent contribution to the prediction of the SARA score. The horizontal VOR gain seems to be a reliable biomarker for the clinical onset, severity, and progression of MJD and could be used in further clinical studies. [ABSTRACT FROM AUTHOR]

Minimization of power losses in distribution network (DN) is one of the vast areas of research, where researchers are performing different techniques and methods to reduce the losses. In recent times, network reconfiguration (Nr) has gained more significance in DN to reduce the losses due to its ease of implementation. Most of the work carried on Nr has usually assumed only single hour load model, which didn't vary with time. But in practical DN, load varies during the day. The tie line switching configuration obtained with single hour load model (which doesn't vary with time) is implemented in practical DN, it induces high power losses, reduces the reliability, loadability and voltage profile of the network. Most of the researchers have used single hour load model with Nr and not considered variation in load with Nr. In this study, variation in load is considered with twenty-four hour load. An investigation has been performed to find the losses obtained with variation in load for twenty-four hours. However, changing the topological of the network without disturbing the radiality is a complex non differentiable optimization problem. Nr implemented with twenty-four hour load has more complex computation as compared with single hour load. A quantum-inspired evolutionary algorithm, i.e., adaptive quantum-inspired evolutionary algorithm (AQiEA), is used to solve this complex optimization problem. In this study, two test cases are created in which the first case, uses four different scenarios to find the effect of power losses incurred in the system after opening the switches on single hour load and twenty-four hour load model. An effort has been made for optimal tie line switching configuration for twenty-four hour load instead of single hour load. In addition, an attempt has been made to maximize the economic benefits in DN with Nr on twenty-four hour load. Switching operation cost is considered to study the effect of frequent Nr on the life span of switches. Second case is used to test the efficacy of the proposed algorithm as compared with other techniques. The performance of AQiEA is tested on two IEEE standard test bus systems. Wilcoxon signed-rank test is also used to demonstrate the effectiveness of AQiEA. [ABSTRACT FROM AUTHOR]

Contingency analysis has been vastly explored within the context of power systems operation and security assessment. However, the impact of power quality indices into the contingency ranking and selection has not been well investigated in the literature. In order to fulfil this gap, a novel approach is proposed in this paper considering the effects of transmission lines outages in the voltage magnitudes and harmonic proliferation in power systems. The compensation theorem is applied to obtain the approximate effect of small changes in the elements of an electric network based on sensitivity analysis with the purpose of determining estimated harmonic voltages and currents in a lower computational time when compared with the traditional application of the iterative Newton–Raphson load flow methodology. Computational simulations are carried out using the IEEE 30 bus test system modified by the inclusion of non linear loads modelled as harmonic current injections. A comparative analysis is also presented considering the contingency selection using the proposed method, load flow algorithms and different ranking factors considering the impact of single contingencies into the power system voltages and total harmonic distortion variations. [ABSTRACT FROM AUTHOR]

This paper presents an improved directional overcurrent protection scheme using a two-stage hybrid GA-IPM algorithm. The developed approach considers the optimal time-current characteristic (TCC) selection and setting calculations of DOCRs simultaneously to protect meshed power networks. The developed formulation considers the optimal choice of the TCC curve and setting calculation simultaneously. Here, the problem is formulated as a mixed-integer nonlinear programming (MINLP) problem where a curve selection setting called curve-setting (CS) is added to the standard time multiplier-setting (TMS) and plug-setting (PS) of each relay in the DOCRs-based protection scheme. In modern relays, the selection of TCC curves is easily made from the available options. In this work, the IEC-standard curves have been considered to obtain the optimum characteristic curve selection and setting calculations. The formulated MINLP problem has been solved using the newly developed two-stage hybrid GA-IPM algorithm. In the first stage, the genetic algorithm (GA) is used to solve the problem formulated as MINLP. The obtained solution is considered the initial solution for the interior-point method (IPM) in the second state. The GA can solve the MINLP problems effectively, and IPM is superior in solving nonlinear programming problems, hence fine-tuning the results obtained by GA. The suitability and effectiveness of the proposed approach have been demonstrated on the IEEE 14 bus test system. Further, the efficacy of the developed method has been validated on an extensive IEEE 118 bus test system, and results are compared with those available in the literature. [ABSTRACT FROM AUTHOR]

The optimal reactive power dispatch (ORPD) problem is a critical factor in maintaining the safe and efficient operation of electric networks. Due to its mixed-variable nonlinear nature, addressing this problem requires an appropriate optimization algorithm. In this study, a novel approach based on the combination of artificial rabbits optimization (ARO) and gradient-based optimization (GBO) algorithms was proposed to solve the ORPD problem in electric networks. The performance of the proposed AROGBO algorithm were verified on 7 numerical optimization test functions. To evaluate the effectiveness of this hybrid AROGBO technique, standard IEEE-30, IEEE-57 bus, and IEEE-118 bus test systems were employed, with two objective functions tested for each system: minimum total power loss and minimum total voltage deviations. The AROGBO, ARO, and GBO algorithms were utilized in each case to determine the optimal values of the generator voltage, transformer tap changer positions, and reactive power compensation values. A comprehensive comparison was made between the results obtained from the hybrid AROGBO algorithm, standard ARO and GBO algorithms, and other metaheuristic optimization techniques. The simulation attainments verify the accuracy and stability of the proposed AROGBO methodology in solving the ORPD problem. [ABSTRACT FROM AUTHOR]

Power system fault diagnosis is crucial for identifying the location and causes of faults and providing decision-making support for power dispatchers. However, most classical methods suffer from significant time-consuming, memory overhead, and computational complexity issues as the scale of the power system concerned increases. With rapid development of quantum computing technology, the combinatorial optimization method based on quantum computing has shown certain advantages in computational time over existing methods. Given this background, this paper proposes a quantum computing based power system fault diagnosis method with the quantum approximate optimization algorithm. The proposed method reformulates the fault diagnosis problem as a Hamiltonian by using Ising model, which completely preserves the coupling relationship between faulty components and various operations of protective relays and circuit breakers. Additionally, to enhance problem-solving efficiency under current equipment limitations, the symmetric equivalent decomposition method of multi-z-rotation gate is utilized. Furthermore, the small probability characteristics of power system events is utilized to reduce the number of qubits. Simulation results based on the test system show that the proposed methods can achieve the same optimal results with a faster speed compared with the classical higher-order solver provided by D-Wave. [ABSTRACT FROM AUTHOR]

Passive haptics have long been used to enhance the user's experience in virtual reality (VR). However, creating props to be used in a virtual environment can be a complicated and lengthy process. Current research looks to create passive haptic props based on the layout of, or objects in, the user's real environment. However, we identify three key limitations of current research. Firstly, procedural generation introduces many unknown variables into the design process, which complicates applying such techniques to scenarios requiring knowledge of the virtual environment's layout ahead of time. Furthermore, such techniques limit the size and dimensions of the virtual space to that of the real space. Lastly, current research necessitates pre-scanning or real-time scanning of the user's real environment, often requiring specialist equipment and expertise, thus limiting its generalisability. This research proposes PropOrientedWorldRotation, a technique that attempts to answer the aforementioned limitations and simplify the process of adding haptic feedback to VR applications. We implemented this technique in a demonstration game and give an overview of the steps taken to apply the technique in a real context. We analysed the demonstration system's performance and conducted an initial user evaluation in three different physical environments. While our stress test of the system's performance highlights the necessity for certain optimisations in complex environments, our initial user feedback suggests that users experienced a stronger sense of presence and feelings of safety in our passive haptics-enhanced environment. Hence, we conclude that our proposal has the potential to enhance experiences in VR with haptic feedback. [ABSTRACT FROM AUTHOR]

The Sine–Cosine algorithm (SCA) is efficient but faces challenges in exploitative abilities, slow convergence, and exploration–exploitation balance. This study proposes a novel optimization method, the learning-based sine–cosine algorithm (L-SCA), to solve the optimal power flow (OPF) problem. The basic SCA has been modified with a learning phase operator inspired by TLBO. The SCA handles global exploration, while the learner phase of teaching–learning based optimization (TLBO) offers strong local search capabilities, which can be utilized to enhance the solution neighborhood space provided by the SCA technique. The L-SCA and original SCA algorithms address OPF in IEEE 57-bus, Algerian 59-bus, and IEEE 118-bus power systems, considering twelve cases with a focus on cost savings, voltage stability, voltage profile, emissions, and power losses. The comparative study shows that the proposed L-SCA consistently outperforms standard SCA and other reported methods in all cases for varied-scale standard test systems as well as for a practical power system, within reasonable execution times. For instance, L-SCA in the Algerian 59-bus system cut fuel costs by around 13.13% compared to initial case, equating to annual savings of $2.2 million, while in the IEEE-118 bus system, power loss is significantly reduced to 17.881 MW, marking an 86.5% reduction compared to the base case. [ABSTRACT FROM AUTHOR]

In the operation and control of power systems, load frequency control (LFC) plays a critical role in ensuring the stability and reliability of interconnected power systems. Modern power systems with significant penetration of highly variable and intermittent renewable sources present new challenges that make traditional control strategies ineffective. To address these new challenges, this paper proposes a novel LFC strategy that employs a cascaded fractional-order proportional integral-fractional-order proportional integral derivative with a derivative filter (FOPI-FOPIDN) as a controller. The parameters of the FOPI-FOPIDN are optimised using a variant of the particle swarm optimization (PSO) in the literature called ADIWACO. The effectiveness and scalability of the proposed strategy are validated by extensive simulations conducted on two- and three-area test systems and performance comparisons with recent LFC control strategies in the literature. The performance metrics used for the evaluation are ITAE values, deviations in the power flows in the tie-lines, and deviations in the frequencies of the control areas with the power systems subjected to diverse load and RES generation disturbances in several experimental scenarios. Governor dead band, communication time delay, and generation rate constraints are considered in one of the scenarios for more realistic evaluation. Again, the controller's robustness to uncertain model parameters is validated by varying the parameters of the three-area test system by ± 50%. The simulation results obtained confirm the controller's robustness and its superiority over the comparison LFC strategies in terms of the above performance metrics. [ABSTRACT FROM AUTHOR]

The creep characteristics and potential deformation patterns of gangue backfill material are crucial in backfill mining operations. This study utilizes crushed gangue from the Gangue Yard in Fuxin City as the research material. An in-house designed, large-scale, triaxial gangue compaction test system was used. Triaxial compaction creep tests were conducted on gangue materials with varying particle size distributions. Analysis was performed based on different particle sizes, stresses, and confinement pressures. The study investigates the creep characteristics of the gangue under different conditions and explores the underlying causes. It reveals the relationship between the creep deformation of gangue materials and the passage of time. Mathematical methods are applied to develop a triaxial compaction creep power law model for gangue backfill materials. Finally, the creep results are fitted using an empirical formula approach. [ABSTRACT FROM AUTHOR]

Purpose: Accurately measuring sweat sodium concentration ([Na+]) in the field is advantageous for coaches, scientists, and dieticians looking to tailor hydration strategies. The MX3 hydration testing system is a new portable analyser that uses pre-calibrated biosensors to measure sweat [Na+]. This study aimed to assess the validity and reliability of the MX3 hydration testing system. Methods: Thirty-one (11 females) recreationally active participants completed one experimental trial. During this trial, participants exercised at a self-selected pace for 45 min in a warm environment (31.5 ± 0.8 °C, 63.2 ± 1.3% relative humidity). Sweat samples were collected from three measurement sites using absorbent patches. The samples were then analysed for sweat [Na+] using both the MX3 hydration testing system and the Horiba LAQUAtwin-NA-11. The reliability of the MX3 hydration testing system was determined following two measurements of the same sweat sample. Results: The mean difference between measurements was 0.1 mmoL·L−1 (95% limits of agreement (LoA): − 9.2, 9.4). The analyser demonstrated a coefficient of variation (CV) of 5.6% and the standard error of measurement was 3.3 mmoL·L−1. When compared to the Horiba LAQUAtwin-NA-11, there was a mean difference of − 1.7 mmoL·L−1 (95% LoA: − 0.25 X ¯ , 0.25 X ¯ ) and the CV was 9.8%. Conclusion: The MX3 hydration testing system demonstrated very good single-trial reliability, moderate agreement and a very good CV relative to the Horiba LAQUAtwin-Na-11. To further validate its performance, the MX3 hydration testing system should be compared with analytical techniques known for superior reliability and validity. [ABSTRACT FROM AUTHOR]

We studied the effects of some nitrogen-containing, heterocyclic, and cyclic compounds on the rate of oxidative deamination of polyamines and putrescine in tissues with a high proliferation rate. For this purpose, the specific activities of the main enzymes of polyamine oxidative degradation — spermine oxidase (SMO), polyamine oxidase (PAO), and diamine oxidase (DAO) were determined using a cell-free test system from regenerating rat liver. The compounds methyl 2-(5-formylfuran-2-yl)benzoate and 2,7-bis-[2-(diethylamino)ethoxy]-9H-fluoren-9-one (and in the form of dihydrochloride) showed mainly activating effect on oxidative degradation of putrescine, spermidine, and spermine, which indirectly indicates their antiproliferative effect. Nitrogen-free compounds inhibited this process, thus exhibiting potentially carcinogenic properties. Correlations were calculated for activity of DAO, PAO, and SMO with 5 topological indices: Wiener (W), Rouvray (R), Balaban (J) in the Trinaistich modification, detour (Ip), and electropy (Ie). The highest dependence was noted for DAO and the Balaban index (R=-0.55), for PAO and the detour index (R=0.78), and for SMO and the electropy index (R=0.53). The remaining dependencies showed insignificant correlation strength. [ABSTRACT FROM AUTHOR]

This paper provides six metaheuristic algorithms, namely Fast Cuckoo Search (FCS), Salp Swarm Algorithm (SSA), Dynamic control Cuckoo search (DCCS), Gradient-Based Optimizer (GBO), Northern Goshawk Optimization (NGO), Opposition Flow Direction Algorithm (OFDA) to efficiently solve the optimal power flow (OPF) issue. Under standard and conservative operating settings, the OPF problem is modeled utilizing a range of objectives, constraints, and formulations. Five case studies have been conducted using IEEE 30-bus and IEEE 118-bus standard test systems to evaluate the effectiveness and robustness of the proposed algorithms. A performance evaluation procedure is suggested to compare the optimization techniques' strength and resilience. A fresh comparison methodology is created to compare the proposed methodologies with other well-known methodologies. Compared to previously reported optimization algorithms in the literature, the obtained results show the potential of GBO to solve various OPF problems efficiently. [ABSTRACT FROM AUTHOR]

Electronic medical records have the advantages of large storage capacity, convenience, improved efficiency, etc. However, since electronic medical records contain a large amount of patient's private information, if they are stored directly in the cloud server, patients may face the risk of privacy data leakage and electronic medical record data tampering. To solve the above problems, this paper proposes a secure sharing scheme of electronic medical records combining quantum key and blockchain. Based on the true randomness of quantum keys, the multi-user secure forwarding mechanism of quantum keys is designed using proxy re-encryption technology and blockchain. A fine-grained access control scheme for electronic medical records by users with different roles was proposed using data desensitization technology. To facilitate secure retrieval from the cloud server, searchable encryption technology is used. This paper analyzes the comprehensive performance level of the proposed scheme through blockchain performance testing and system efficiency testing. [ABSTRACT FROM AUTHOR]

This article aims at designing a robust wide-area damping controller (WADC) to address the problems associated with communication failures. The proposed controller is a state feedback-based controller, which uses generators' states as the controller inputs. The structure of the proposed controller's feedback gain matrix is a combination of two feedback gain matrices to achieve adequate robust performance over different disturbances and communication losses. These two feedback gain matrices are; full-scale feedback gain matrix and decentralized scale feedback gain matrix. Both models are designed by considering all generators' states are available at the controller input side. However, both matrices' structures are different from each other. The conventional LQR state feedback control technique is used to design the full-scale matrix. On the other hand, the decentralized scale matrix is computed using a structurally constrained H 2 -norm optimization technique to acquire the required structure. The full-scale model gives robust performance under different faults. Whereas, the decentralized scale matrix will result robust performance against communication failures. Therefore, to achieve superior performance under all conditions, the proposed controller can be used. To show the efficacy of the proposed controller, it is compared with different existing controllers and the results are illustrated. Simulation studies are conducted on well-known IEEE 39-bus and 68-bus test systems to validate the robustness of the proposed controller considering different faults and communication failures. [ABSTRACT FROM AUTHOR]

Power system simulation is vital for designing and evaluating the performance of electrical system protection and control devices. Although several commercial simulators exist, most are expensive and not open-source code. It is essential to develop educational and research simulators that can prepare students, allow researchers to develop new methodologies, and assist system operators in making decisions. This paper aims to present a computer simulation platform called AnaDyn (dynamic analysis), a non-commercial and open-source platform. AnaDyn is an educational/research platform that allows dynamic (transient stability), quasi-steady-state simulation, modal, and power flow analysis. Short- and long-term studies of voltage, frequency, and rotor angle instability problems can be performed. The main characteristics of AnaDyn are quasi-steady-state simulation, in which the equations are not simplified; easy integration with other tools and toolboxes, since AnaDyn is developing in MATLAB; flexible modeling that allows the inclusion of new devices and controller tests. The detailed modeling of various power system devices, the description of the numerical solution method, and the interface are also presented in this work. The platform is validated by comparing a test system's results with those obtained with Brazil's most popular commercial software. The main potentials of quasi-steady-state simulation are also presented. The results indicate that AnaDyn is efficient for educational and research studies on the stability of short- and long-term electrical systems. [ABSTRACT FROM AUTHOR]

The main contribution of this paper is the development and demonstration of a novel methodology that can be followed to develop a simulation twin of a railway track switch system to test the functionality in a digital environment. This is important because, globally, railway track switches are used to allow trains to change routes; they are a key part of all railway networks. However, because track switches are single points of failure and safety-critical, their inability to operate correctly can cause significant delays and concomitant costs. In order to better understand the dynamic behaviour of switches during operation, this paper has developed a full simulation twin of a complete track switch system. The approach fuses finite element for the rail bending and motion, with physics-based models of the electromechanical actuator system and the control system. Hence, it provides researchers and engineers the opportunity to explore and understand the design space around the dynamic operation of new switches and switch machines before they are built. This is useful for looking at the modification or monitoring of existing switches, and it becomes even more important when new switch concepts are being considered and evaluated. The simulation is capable of running in real time or faster meaning designs can be iterated and checked interactively. The paper describes the modelling approach, demonstrates the methodology by developing the system model for a novel "REPOINT" switch system, and evaluates the system level performance against the dynamic performance requirements for the switch. In the context of that case study, it is found that the proposed new actuation system as designed can meet (and exceed) the system performance requirements, and that the fault tolerance built into the actuation ensures continued operation after a single actuator failure. [ABSTRACT FROM AUTHOR]

Distributed energy systems encompass a diverse range of generation and storage solutions on the user side, where decentralized management schemes to maximize the overall social welfare are preferred considering their dispersed ownership. However, either security or privacy problems occur in recently proposed schemes. Here we report a decentralized framework leveraging the strengths of blockchain and parallelizable mathematical algorithms to overcome these potential drawbacks. The system owners bid cost functions and operating constraints through masked but coupled management subproblems, which are redistributed by the blockchain to be verifiably solved by competent peers. Such processes are iteratively executed as decisions and shadow prices are exchanged among participants, until an equilibrium is reached. The interactive framework ensures decentralized, privacy-preserving, and secure management of multiple energy sources, and reduces the total cost by 3.0 ~ 7.5% in the test system. Our results benefit the energy prosumers and promote a more active and competitive power grid. Decentralized management of distributed energy sources for lower energy costs is of high interest. Here, authors show how privacy and security concerns are addressed under a decentralization framework through blockchain and parallelizable algorithms. [ABSTRACT FROM AUTHOR]

Power system operators are faced with the problem of unit commitment belonging to mixed integer programming, which becomes very complicated, as units become large-scale and highly constrained. Because unit commitment problem is a binary problem with commitment and de-commitment, a discrete/binary optimization algorithm with superior performance is required. This paper proposes a novel hybrid binary bat algorithm for unit commitment problem, which consists of two process. To begin with, the proposed binary bat algorithm is applied to determining the commitment schedule of unit commitment problem. Specifically, an improved crossover operator based on exponential-logic-modulo map is proposed to enhance the convergence and maintain the diversity of populations. To prevent the algorithm from falling into a local optimum, a local mutation strategy performs local perturbation. Chaotic map is responsible for updating some parameters to increase the performance of the proposed algorithm. Furthermore, Lambda-iteration method is adopted to solve economic load dispatch in continuous space. Constraint handling is performed using the heuristic constraint produce. The effectiveness of the proposed algorithm is verified by benchmark functions and test systems. Additionally, the simulation results are compared with other well-established heuristic and binary approaches. [ABSTRACT FROM AUTHOR]

Infections caused by snakehead vesiculovirus (SHVV) have seen frequent outbreaks in recent years, inflicting significant losses on the snakehead aquaculture industry. Early detection is therefore essential for effective prevention and control of pathogenic infections and reduction of economic losses caused by infections. There is an urgent need for a simple, rapid, specific, sensitive, and intuitive method to monitor snakehead infected with SHVV. The aim of the present study was to develop and evaluate a loop-mediated isothermal amplification (LAMP) assay for the rapid visual detection of SHVV in snakehead. Three pairs of primers were designed according to the conserved region of phosphoprotein (P) gene sequences of SHVV and were applied for the detection of SHVV from fish samples. Time and temperature conditions for the amplification of SHVV were optimized at 65 °C and 55 min. The LAMP assay demonstrated high specificity, with no cross-reactivity with seven other viruses. Amplification results were visualized by a color change after the addition of hydroxynaphthol blue (HNB) dye. Sensitivity test results showed that the minimum detection volume with this method was 1.76 × 102 copies/μL, which was 100 times more sensitive than RT-PCR assay. We used the established LAMP system to test 50 clinical samples and detected 32 positive responses, whereas 22 positive samples out of 50 samples were detected by RT-PCR. The establishment of a visual LAMP assay further shortens the virus detection process and allows visual reading of positive responses through color changes; it is suitable for use in quarantine and field detection. Therefore, this proposed method provides a sensitive, specific, and user-friendly method for the rapid diagnosis of SHVV in snakehead farming. [ABSTRACT FROM AUTHOR]

The results of evaluating the adsorption and fluorescent properties of azolotriazine compounds and phases based on cadmium sulfide quantum dots in vapors of volatile organic compounds (biomarkers of living systems) are considered. The adsorption properties of phases based on organic dyes and encapsulated semiconductors towards vapors of alcohols, ketones, amines, acids, ammonia, and aldehydes are investigated using direct high-sensitivity piezoelectric quartz microweighing. The spectral properties and their variations in analyte vapors are investigated using various spectroscopy methods (absorption, photoluminescence). The research results are compared, and the potential for optimizing this stage is assessed. It is proposed to evaluate the consistency of methods for predicting changes in fluorescent properties in test systems for volatile organic compounds using the Kendall coefficient of concordance, W. The highest level of agreement (W = 0.89) was observed between the methods of spectrofluorimetry and direct vapor microweighing upon adsorption on phases being potential fillers of test systems. A correlation between the results obtained by different fluorescence methods (visual plate test systems and fluorimetry of phases on paper substrates) is 0.80, which confirms a high degree of consistency in assessments using them in the degree of interaction between the analytes and organic, combined fluorochromes. The methods closely related in the nature of the analytical response do not exhibit better agreement than the method of direct vapor microweighing on microphases of fluorimetric reagents of different nature (cadmium sulfide quantum dots/chitosan, organic azolotriazine compounds, mixed phases). This, in turn, enables the selection of simpler, more available, and more rapid methods and means of analysis in routine experiments. [ABSTRACT FROM AUTHOR]

Adult neurotoxicity (ANT) and developmental neurotoxicity (DNT) assessments aim to understand the adverse effects and underlying mechanisms of toxicants on the human nervous system. In recent years, there has been an increasing focus on the so-called new approach methodologies (NAMs). The Organization for Economic Co-operation and Development (OECD), together with European and American regulatory agencies, promote the use of validated alternative test systems, but to date, guidelines for regulatory DNT and ANT assessment rely primarily on classical animal testing. Alternative methods include both non-animal approaches and test systems on non-vertebrates (e.g., nematodes) or non-mammals (e.g., fish). Therefore, this review summarizes the recent advances of NAMs focusing on ANT and DNT and highlights the potential and current critical issues for the full implementation of these methods in the future. The status of the DNT in vitro battery (DNT IVB) is also reviewed as a first step of NAMs for the assessment of neurotoxicity in the regulatory context. Critical issues such as (i) the need for test batteries and method integration (from in silico and in vitro to in vivo alternatives, e.g., zebrafish, C. elegans) requiring interdisciplinarity to manage complexity, (ii) interlaboratory transferability, and (iii) the urgent need for method validation are discussed. [ABSTRACT FROM AUTHOR]

In distribution systems, the state estimation task is very complicated due to the problems arising from the unbalanced operation and network configuration changes. Additionally, the convergence process of state estimation gets affected by the loss of physical measurements due to meter failure, communication failure, and large communication time delays. To address the issue of loss of measurement data, a new deep learning approach, namely a convolutional generative adversarial imputed network (CGAIN) with modified loss functions, is proposed. A branch current-distribution system state estimation (BC-DSSE) with different percentages of missing measurement data has been implemented and studied. Furthermore, the analysis has been carried out for different types of uncertainties involving several kinds of measurement devices and pseudo-measurements for different classes of consumer loads. Also, the effect of imputed data on state estimation accuracy is tested at different operating conditions of load. The imputation performance of the CGAIN model is tested by comparing it with statistical methods, and ML/DL approaches. The benefits of the proposed model are validated by Monte Carlo simulations on the modified IEEE 13-node and IEEE 37-node unbalanced distribution test systems. Simulation results show that the proposed model can effectively impute the missed data under any operating condition. Further, the robustness of the algorithm is checked with the largest normalized residual (LNR) test for minimizing the effect of bad data. [ABSTRACT FROM AUTHOR]

In AI pandemic applications, the online automatic AI recording apparatus for official councils such as court trials, business conferences and commercial meetings will become imperative because it could let the opinion identification and consensus of participants be synchronically available to implicitly diminish social costs such as follow-up disputes and controversies. Hence, in this study, an automatic on-line multi-dialogue recording system is completely constructed, where the unbounded interleaved-state recurrent neural networks (UIS-RNN) with proposed crux improvements is exploited to achieve confident speaker-diarization. For keeping the systematic robustness, a denoising spectral-LSTM, which is precisely modified from the dual-signal transformation LSTM (DTLN), can strengthen its subsequent crux-improved UIS-RNN and automatic speech recognition (ASR). Finally, the MacBERT model is set to rectify the possible wrong words in conversed sentences according to the learned rational context. For making our system being a practical software apparatus in the use of unmarked multi-person councils, we have also completed the convenient interfaces for the operations of ASR and speaker-diarization, which can exhibit on-line denoising efficacy and speaker-diarization results as well as offer real-time hand-crafted rectifications to common users. In extensive experiments, the proposed recording system can promise high accuracy rates of online speaker diarization and speech-separated ASR. Our proposed system had been examined by the cooperated law court staffs, who offered the noise-embedded speeches of practical court field to test our system. Since the tight recording burden had been indeed noticeably alleviated in their legal-action councils, the court staffs had endorsed that the proposed entire system could be a friendly labor-saving AI apparatus for on-line automatic multi-dialogue recording. [ABSTRACT FROM AUTHOR]

A mechanistic understanding of algal growth is essential for maintaining a sustainable environment in an era of climate change and population expansion. It is known that algal growth is tightly controlled by complex interactive physical and chemical conditions. Many mathematical models have been proposed to describe the relation of algal growth and environmental parameters, but experimental verification has been difficult due to the lack of tools to measure cell growth under precise physical and chemical conditions. As such, current models depend on the specific testing systems, and the fitted growth kinetic constants vary widely for the same organisms in the existing literature. Here, we present a microfluidic platform where both light intensity and nutrient gradients can be well controlled for algal cell growth studies. In particular, light shading is avoided, a common problem in macroscale assays. Our results revealed that light and nitrogen colimit the growth of algal cells, with each contributing a Monod growth kinetic term in a multiplicative model. We argue that the microfluidic platform can lead towards a general culture system independent algal growth model with systematic screening of many environmental parameters. Our work advances technology for algal cell growth studies and provides essential information for future bioreactor designs and ecological predictions. [ABSTRACT FROM AUTHOR]

Background: A recently published article, by Reiber et al., on the representativity of macroinvertebrate communities in outdoor micro- or mesocosm studies, used as a higher tier tool in the environmental risk assessment of plant protection products (PPPs) in the EU, concluded that 'micro-/mesocosm studies do not represent natural macroinvertebrate communities'. Fundamentally, the article based its conclusion on the analysis of data from 26 streams used in a monitoring project in Germany (2018–2019), in comparison to taxa found in seven lentic micro- and mesocosm studies, conducted at four test sites (2013 – 2018), and submitted to the UBA, Germany. Results: There are multiple reasons why this conclusion is incorrect, e.g. the number of taxa, for which the Minimum Detectable Differences (MDDs) were low enough to allow a detection of direct effects in the seven lentic mesocosm studies, cannot be compared to the number of taxa just present in at least five of 26 streams. We have further investigated the data from five of the seven studies which were analysed in detail by Reiber et al. and determined that the MDDs of 12 to 18 invertebrate taxa per study fulfilled the current recommendation to allow a detection of medium effects (MDD up to 70%). However, which taxa can be considered potentially sensitive depends on the specific test item. While lentic test systems may not be suitable to test effects on typical stream taxa, taxa occurring in lentic systems such as ponds and ditches are not by definition less sensitive, or vulnerable, to pesticides than taxa living in streams, and their relative sensitivity can be checked in laboratory tests, or artificial streams, if needed. Conclusions: In our view, well conducted micro- and mesocosm studies do provide reliable and useful data for the environmental risk assessment of plant protection products covering long-term, as well as indirect, effects under semi-natural conditions. [ABSTRACT FROM AUTHOR]

For the rapid determination of bisphenol A in drinking water, a membrane test system has been developed using a conjugate of gold nanoparticles with an aptamer that specifically binds the target analyte, and a conjugate of mercaptosuccinic acid with a carrier protein impregnated in the test zone of the strip. The working principle of the test system is based on the binding of free gold nanoparticles in the test zone, formed as a result of the competitive interaction of the aptamer with bisphenol A and its release from the surface of gold nanoparticles. Conjugates of gold nanoparticles with aptamers of different compositions were obtained and tested. Optimal conditions were selected to ensure the achievement of a low detection limit for bisphenol A. The developed test system allows the detection of bisphenol A within 15 min with a detection limit of 13.5 ng/mL. The suitability of the test system was confirmed when testing drinking water; the recovery values of bisphenol A ranged from 88.2 to 101.3%. [ABSTRACT FROM AUTHOR]