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Finding low-energy structures of ligand-protected clusters is challenging due to the enormous conformational space and the high computational cost of accurate quantum chemical methods for determining the structures and energies of conformers. Here, we adopted and utilized a kernel rigid regression based machine learning method to accelerate the search for low-energy structures of ligand-protected clusters. We chose the Au25(Cys)18 (Cys: cysteine) cluster as a model system to test and demonstrate our method. We found that the low-energy structures of the cluster are characterized by a specific hydrogen bond type in the cysteine. The different configurations of the ligand layer influence the structural and electronic properties of clusters. [ABSTRACT FROM AUTHOR]

A new approach for the calculation of eigenstates with the state-averaged (multi-layer) multi-configurational time-dependent Hartree (MCTDH) approach is presented. The approach is inspired by the recent work of Larsson [J. Chem. Phys. 151, 204102 (2019)]. It employs local optimization of the basis sets at each node of the multi-layer MCTDH tree and successive downward and upward sweeps to obtain a globally converged result. At the top node, the Hamiltonian represented in the basis of the single-particle functions (SPFs) of the first layer is diagonalized. Here p wavefunctions corresponding to the p lowest eigenvalues are computed by a block Lanczos approach. At all other nodes, a non-linear operator consisting of the respective mean-field Hamiltonian matrix and a projector onto the space spanned by the respective SPFs is considered. Here, the eigenstate corresponding to the lowest eigenvalue is computed using a short iterative Lanczos scheme. Two different examples are studied to illustrate the new approach: the calculation of the vibrational states of methyl and acetonitrile. The calculations for methyl employ the single-layer MCTDH approach, a general potential energy surface, and the correlation discrete variable representation. A five-layer MCTDH representation and a sum of product-type Hamiltonian are used in the acetonitrile calculations. Very fast convergence and order of magnitude reductions in the numerical effort compared to the previously used block relaxation scheme are found. Furthermore, a detailed comparison with the results of Avila and Carrington [J. Chem. Phys. 134, 054126 (2011)] for acetonitrile highlights the potential problems of convergence tests for high-dimensional systems. [ABSTRACT FROM AUTHOR]

We have designed a [Fe(SH)4H]− model with the fifth proton binding either to Fe or S. We show that the energy difference between these two isomers (∆E) is hard to estimate with quantum-mechanical (QM) methods. For example, different density functional theory (DFT) methods give ∆E estimates that vary by almost 140 kJ/mol, mainly depending on the amount of exact Hartree–Fock included (0%–54%). The model is so small that it can be treated by many high-level QM methods, including coupled-cluster (CC) and multiconfigurational perturbation theory approaches. With extrapolated CC series (up to fully connected coupled-cluster calculations with singles, doubles, and triples) and semistochastic heat-bath configuration interaction methods, we obtain results that seem to be converged to full configuration interaction results within 5 kJ/mol. Our best result for ∆E is 101 kJ/mol. With this reference, we show that M06 and B3LYP-D3 give the best results among 35 DFT methods tested for this system. Brueckner doubles coupled cluster with perturbaitve triples seems to be the most accurate coupled-cluster approach with approximate triples. CCSD(T) with Kohn–Sham orbitals gives results within 4–11 kJ/mol of the extrapolated CC results, depending on the DFT method. Single-reference CC calculations seem to be reasonably accurate (giving an error of ∼5 kJ/mol compared to multireference methods), even if the D1 diagnostic is quite high (0.25) for one of the two isomers. [ABSTRACT FROM AUTHOR]

Clustering has become an indispensable tool in the presence of increasingly large and complex datasets. Most clustering algorithms depend, either explicitly or implicitly, on the sampled density. However, estimated densities are fragile due to the curse of dimensionality and finite sampling effects, for instance, in molecular dynamics simulations. To avoid the dependence on estimated densities, an energy-based clustering (EBC) algorithm based on the Metropolis acceptance criterion is developed in this work. In the proposed formulation, EBC can be considered a generalization of spectral clustering in the limit of large temperatures. Taking the potential energy of a sample explicitly into account alleviates requirements regarding the distribution of the data. In addition, it permits the subsampling of densely sampled regions, which can result in significant speed-ups and sublinear scaling. The algorithm is validated on a range of test systems including molecular dynamics trajectories of alanine dipeptide and the Trp-cage miniprotein. Our results show that including information about the potential-energy surface can largely decouple clustering from the sampled density. [ABSTRACT FROM AUTHOR]

We introduce a Monte-Carlo method that allows for the simulation of a polymeric phase containing a weak polyelectrolyte, which is coupled to a reservoir at a fixed pH, salt concentration, and total concentration of a weak polyprotic acid. The method generalizes the established grand-reaction method by Landsgesell et al. [Macromolecules 53, 3007–3020 (2020)] and, thus, allows for the simulation of polyelectrolyte systems coupled to reservoirs with a more complex chemical composition. In order to set the required input parameters that correspond to a desired reservoir composition, we propose a generalization of the recently published chemical potential tuning algorithm of Miles et al. [Phys. Rev. E 105, 045311 (2022)]. To test the proposed tuning procedure, we perform extensive numerical tests for both ideal and interacting systems. Finally, as a showcase, we apply the method to a simple test system that consists of a weak polybase solution that is coupled to a reservoir containing a small diprotic acid. The complex interplay of the ionization of various species, the electrostatic interactions, and the partitioning of small ions leads to a non-monotonous, stepwise swelling behavior of the weak polybase chains. [ABSTRACT FROM AUTHOR]

A multivariant statistical approach was used to identify treatment conditions that improve the survivability of structural reactive material (SRM) projectiles upon launch and enhance energy release upon impact. The study included both mechanical testing of projectiles as well as their reactive characterization. The projectiles were launched in a high-velocity impact-ignition testing system and impacted an anvil for vented chamber calorimetry. This study examined a link between ultimate compressive stress and combustion performance. Two treatments were applied to consolidated aluminum projectiles including annealing and addition of silica (SiO2) inclusions. Results showed annealing at moderate temperatures resulted in intact SRM projectiles upon launch. Adding small concentrations (1–2 wt. %) of SiO2 to the SRM promoted fragmentation and combustion performance upon impact. Compared to the untreated projectiles, annealing with SiO2 inclusion processing treatments improved the energy conversion efficiency from 37–84% (for untreated projectiles) up to 54–98%. Increasing interparticle dislocation recovery by annealing while balancing inclusions promoting fragmentation upon impact was the key to optimizing combustion performance for SRM ballistic impact applications. [ABSTRACT FROM AUTHOR]

We present equations of motion (EOMs) for general time-dependent wave functions with exponentially parameterized biorthogonal basis sets. The equations are fully bivariational in the sense of the time-dependent bivariational principle and offer an alternative, constraint-free formulation of adaptive basis sets for bivariational wave functions. We simplify the highly non-linear basis set equations using Lie algebraic techniques and show that the computationally intensive parts of the theory are, in fact, identical to those that arise with linearly parameterized basis sets. Thus, our approach offers easy implementation on top of existing code in the context of both nuclear dynamics and time-dependent electronic structure. Computationally tractable working equations are provided for single and double exponential parametrizations of the basis set evolution. The EOMs are generally applicable for any value of the basis set parameters, unlike the approach of transforming the parameters to zero at each evaluation of the EOMs. We show that the basis set equations contain a well-defined set of singularities, which are identified and removed by a simple scheme. The exponential basis set equations are implemented in conjunction with the time-dependent modals vibrational coupled cluster (TDMVCC) method, and we investigate the propagation properties in terms of the average integrator step size. For the systems we test, the exponentially parameterized basis sets yield slightly larger step sizes compared to the linearly parameterized basis set. [ABSTRACT FROM AUTHOR]

Deep learning has emerged as a promising paradigm to give access to highly accurate predictions of molecular and material properties. A common short-coming shared by current approaches, however, is that neural networks only give point estimates of their predictions and do not come with predictive uncertainties associated with these estimates. Existing uncertainty quantification efforts have primarily leveraged the standard deviation of predictions across an ensemble of independently trained neural networks. This incurs a large computational overhead in both training and prediction, resulting in order-of-magnitude more expensive predictions. Here, we propose a method to estimate the predictive uncertainty based on a single neural network without the need for an ensemble. This allows us to obtain uncertainty estimates with virtually no additional computational overhead over standard training and inference. We demonstrate that the quality of the uncertainty estimates matches those obtained from deep ensembles. We further examine the uncertainty estimates of our methods and deep ensembles across the configuration space of our test system and compare the uncertainties to the potential energy surface. Finally, we study the efficacy of the method in an active learning setting and find the results to match an ensemble-based strategy at order-of-magnitude reduced computational cost. [ABSTRACT FROM AUTHOR]

We present an unsupervised data processing workflow that is specifically designed to obtain a fast conformational clustering of long molecular dynamics simulation trajectories. In this approach, we combine two dimensionality reduction algorithms (cc_analysis and encodermap) with a density-based spatial clustering algorithm (hierarchical density-based spatial clustering of applications with noise). The proposed scheme benefits from the strengths of the three algorithms while avoiding most of the drawbacks of the individual methods. Here, the cc_analysis algorithm is applied for the first time to molecular simulation data. The encodermap algorithm complements cc_analysis by providing an efficient way to process and assign large amounts of data to clusters. The main goal of the procedure is to maximize the number of assigned frames of a given trajectory while keeping a clear conformational identity of the clusters that are found. In practice, we achieve this by using an iterative clustering approach and a tunable root-mean-square-deviation-based criterion in the final cluster assignment. This allows us to find clusters of different densities and different degrees of structural identity. With the help of four protein systems, we illustrate the capability and performance of this clustering workflow: wild-type and thermostable mutant of the Trp-cage protein (TC5b and TC10b), NTL9, and Protein B. Each of these test systems poses their individual challenges to the scheme, which, in total, give a nice overview of the advantages and potential difficulties that can arise when using the proposed method. [ABSTRACT FROM AUTHOR]

In today's fast-changing power systems, it is vital to have a protection system that can distinguish between power swing and fault conditions. With advanced protective devices (Digital Relays), an appropriate protection strategy can be established to identify power swing and fault conditions individually. The proposed algorithm uses the sliding window concept, which requires very little computational data unless any abnormal conditions exist in the power system. Modified Full Cycle Discrete Fourier Transform (MFCDFT) is more effective in the extraction of the fundamental phasors from the original complex signal by effectively removing the harmonics and DC components. An adaptive impedance characteristic-based MFCDFT is utilized for the discrimination of power swing and fault in this work. Several fault scenarios and power swings are generated on the test system concurrently and independently from the relay station at varied distances. PSCAD/EMTDC is utilized on a single-machine infinite bus system to analyze various test conditions. The simulation is utilized in this case to collect data from various test circumstances. After obtaining the data, the MFCDFT algorithm along with adaptive impedance estimation is performed using MATLAB code. After examining various test results, it is discovered that the suggested technique correctly recognizes power swings and various fault scenarios. It can also identify the difference between stable and unstable power swings. According to the results, the proposed technique is proficient at spotting fault and power swing conditions. In addition, the algorithm ensures dependable operation with quick detection and avoids maloperation under a typical swing condition. [ABSTRACT FROM AUTHOR]

Commercial panels of microsatellite (STR) loci are focused on the use of DNA of the domestic dog (Canis lupus familiaris) and are often inapplicable for genotyping the DNA of the gray wolf (Canis lupus lupus). We propose a CPlex test system, including one hexa‐ and 12 tetranucleotide autosomal STR loci, as well as two sex loci, that is equally efficient in DNA identification of biological samples of the wolf and the dog. Analysis of molecular variance between samples revealed significant differentiation values (FST = 0.0784, p < 0.001), which allows to use the panel to differentiate wolf and dog samples. Population subdivision coefficients (θ‐values) were calculated for each of the 13 STR loci of the developed test system. It was shown that the values of the genotype frequency for dogs and wolves, without and with considering the θ‐value, differ by three orders of magnitude (for dogs 8.9 × 10−16 and 2.1 × 10−14 and for wolves 1.9 × 10−15 and 4.5 × 10−14, respectively). The use of population subdivision coefficients will allow to identify the most reliable results of an expert identification study and the power of exclusion provided by the STR loci of the CPlex test system makes it possible to achieve a reliable level of evidence in forensic DNA analysis of both wolves and dogs. The test system has been validated for use in forensic identification of the dog and wolf based on biological traces found at crime scenes, as well as for individual identification and establishing biological relationship of animals of these species. [ABSTRACT FROM AUTHOR]

A scale model experimental study is conducted addressing howl occurring during engine tests in the Propulsion Systems Laboratory (PSL) of NASA Glenn Research Center. The aim is to understand the sources of the howling noise and find possible remedies. It is shown that a jet discharged into the model of the PSL entrance duct gives rise to high levels of low frequency noise. This occurs apparently due to duct acoustic modes randomly excited by the jet. Wire-mesh screens of various mesh size and configuration as well as tabs, placed at the end of the model duct, are shown to affect the noise. Comparative effects of these configurations are studied, and some are found to alleviate the low-frequency noise significantly. Based on these results, the equivalent of a 4-mesh screen is recommended as the end treatment for the duct of the PSL facility. [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]

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]

Highly variable pandemic coronavirus SARS-CoV-2, which causes the hazardous COVID-19 infection, has been persistent in the human population since late 2019. A prompt assessment of individual and herd immunity against the infection can be accomplished by using rapid tests to determine antiviral antibody levels. The microneutralization assay (MN) is one of the most widely used diagnostic methods that has been proposed to assess the qualitative and quantitative characteristics of virus-specific humoral immunity in COVID-19 convalescents or vaccine recipients. However, some aspects of the assay, such as sensitivity and time cost, need improvement. Here, we developed an express test, which may be potentially used in clinical practice for the assessment of serum-caused SARS-CoV-2 inhibition in infected cell cultures. It implies the detection and counting of coronaviral fluorescent-forming units (FFU) and includes two sequentially used developing components: biotinylated mouse monoclonal antibodies against the recombinant N protein of SARS-CoV-2 (B.1) and the recombinant EGFP-streptavidin fusion protein. Due to the universal specificity of the antibodies, our analytical tool is suitable for the detection of various strains of SARS-CoV-2 when determining both the infectious titer of viruses and the titer of serum virus-neutralizing antibodies. The developed two-component test system is characterized by high sensitivity, a reduced number of analytic stages and low assay cost, as well as by flexibility, since it may be modified for detection of other pathogens using the appropriate antibodies. [ABSTRACT FROM AUTHOR]

To sustain the clean energy transition without interruption and to ensure the reliable operation of the transmission system, it is required to have enough additional transmission capacity in the future horizons. The transmission expansion planning (TEP) problem is a core issue in deciding additional transmission capacity in the planning activities. TEP aims to find the best expansion plan while satisfying technical and economic constraints. In this study, a new binary version of the original FBI algorithm called the BFBI (binary forensic-based investigation) algorithm is developed to solve the binary TEP problem. The effectiveness and performance of the developed BFBI are assessed by implementing it in two different test systems: the standard Garver 6-bus test system and the modified 400 kV Turkish grid. Seasonal scenarios are created for 5- and 10-year planning periods to cover all possible generation and load conditions and to assess the impact of the increased share of RES on the grid in the TEP studies conducted for the modified 400 kV Turkish grid created as a bulk realistic grid. The TEP problem is solved by including investment, reliability, and operational costs in two different objective functions for cases while considering the N-1 contingency criterion. The efficacy and robustness of the BFBI algorithm are justified by comparing it with well-known algorithms such as GA and PSO. [ABSTRACT FROM AUTHOR]

Rationale: Mass spectrometry imaging (MSI) elevates the power of conventional mass spectrometry (MS) to multidimensional space, elucidating both chemical composition and localization. However, the field lacks any robust quality control (QC) and/or system suitability testing (SST) protocols to monitor inconsistencies during data acquisition, both of which are integral to ensure the validity of experimental results. To satisfy this demand in the community, we propose an adaptable QC/SST approach with five analyte options amendable to various ionization MSI platforms (e.g., desorption electrospray ionization, matrix‐assisted laser desorption/ionization [MALDI], MALDI‐2, and infrared matrix‐assisted laser desorption electrospray ionization [IR‐MALDESI]). Methods: A novel QC mix was sprayed across glass slides to collect QC/SST regions‐of‐interest (ROIs). Data were collected under optimal conditions and on a compromised instrument to construct and refine the principal component analysis (PCA) model in R. Metrics, including mass measurement accuracy and spectral accuracy, were evaluated, yielding an individual suitability score for each compound. The average of these scores is utilized to inform if troubleshooting is necessary. Results: The PCA‐based SST model was applied to data collected when the instrument was compromised. The resultant SST scores were used to determine a statistically significant threshold, which was defined as 0.93 for IR‐MALDESI‐MSI analyses. This minimizes the type‐I error rate, where the QC/SST would report the platform to be in working condition when cleaning is actually necessary. Further, data scored after a partial cleaning demonstrate the importance of QC and frequent full instrument cleaning. Conclusions: This study is the starting point for addressing an important issue and will undergo future development to improve the efficiency of the protocol. Ultimately, this work is the first of its kind and proposes this approach as a proof of concept to develop and implement universal QC/SST protocols for a variety of MSI platforms. [ABSTRACT FROM AUTHOR]

The nondestructive spectral analysis of surface waves (SASW) technique determines the shear wave velocities along the wide wavelength range using Rayleigh-type surface waves that propagate along pairs of receivers on the surface. The typical configuration of source-receivers consists of a vertical source and three vertical receivers arranged in a linear array. While this approach allows for effective site characterization, laterally variable sites are often challenging to characterize. In addition, in a traditional SASW test configuration system, where sources are placed in one direction, the data are collected more on one side, which can cause an imbalance in the interpretation of the data. Data interpretation issues can be resolved by moving the source to opposite ends of the original array and relocating receivers to perform a second complete set of tests. Consequently, two different Vs profiles can be provided with only a small amount of additional time at sites where lateral variability exists. Furthermore, the testing procedure can be modified to enhance the site characterization during data collection. The advantages of performing SASW testing in both directions are discussed using a real case study. [ABSTRACT FROM AUTHOR]

This research emphasizes a meta-heuristic modified ant lion optimizer (MALO) optimization approach for the simultaneous utilization of DSTATCOM devices and distributed photovoltaic (PV) sources with network reconfiguration in a radial power distribution scheme. In a radial power distribution network with network reconfiguration, the majority of the research is based on constant power model analysis. However, it is noticed that load models have a substantial impact on the distributed PV sources and the DSTATCOM device's optimal size and position. The effect of the constant power (CP) and polynomial (ZIP) with load growth load models for the simultaneous insertion of distributed PV sources and DSTATCOM devices with network reconfiguration is examined in this research work for power system planning. The penetration levels of distributed PV sources considered for the investigation are 25%, 50%, 75%, and 100%. The principal objective of this research is to reduce network total power losses, enhance the voltage magnitude profile at all buses, and reduce the overall operating cost while adhering to equality and inequality constraints. The proposed algorithm is verified on 118-node test systems. The investigation is carried out for planning network upgrading to a high-voltage distribution system (HVDS) on 317 nodes in the rural Bangalore Electricity Supply Company Limited (BESCOM) radial distribution scheme. The simulated results obtained with this method are validated with the BAT algorithm and techniques available in the literature. It is observed that in the IEEE 118-bus system, via the simultaneous placement and sizing of PV sources considering a 25% penetration level and DSTATCOM devices during network reconfiguration, the total power loss reduction is 41.47% and 42.98% for the constant power model and ZIP with the load growth model. For the 317-bus system, the total power loss reduction observed for 11 kV is 49.77% and 59.34% for the constant power model and ZIP model with load growth. Similarly, for the 22 kV system, the power loss reduction observed is 51.69% and 55.75% for the constant power model and ZIP with the load growth model. [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]

Molecular rings of N carbon atoms (cyclo[N]carbons, or CN) are excellent benchmarking systems for testing quantum chemical theoretical methods and valuable precursors to other carbon-rich materials. Odd-N cyclocarbons, which have been elusive to date, are predicted to be even less stable than even-N cyclocarbons. We report the on-surface synthesis of cyclo[13]carbon, C13, by manipulation of decachlorofluorene with a scanning probemicroscope tip. We elucidated the properties of C13 by experiment and theoretical modeling. C13 adopts an open-shell configuration with a triplet ground state and a kinked geometry, which shows different extents of distortion and carbene localization depending on themolecular environment. Moreover, we prepared and characterized the C13 dimer, cyclo[26]carbon, demonstrating the potential of cyclocarbons and their precursors as building blocks for carbon allotropes. [ABSTRACT FROM AUTHOR]

The dual-mode combustor model of a kerosene-fueled dual-mode scramjet engine was investigated through a series of combustion experiments with different mode on the resistance heating direct-connected test system at Northwestern Polytechnical University. The experiment simulated the actual combustion process under the conditions of an inlet total pressure ranging from 600 to 900 kPa, an inlet total temperature of 810 K, and an inlet Mach number of 2.0. The results show that as the equivalence ratio of kerosene increases, the combustor goes through three modes sequentially: pure scramjet mode, dual-mode scramjet mode, and dual-mode ramjet mode. The peak pressure ratio of the combustor corresponding to the combustion mode transition boundary is 1.95 and 3.5, respectively, and the Mach number at the exit of the isolator is 2.26 and 1.0, respectively. The mode transition boundary remains unchanged regardless of the inlet total pressure. When the position of the peak pressure point is stably located near the upstream cavity, the combustor operates in dual-mode ramjet mode, while when the position of the peak pressure point is stably located near the downstream cavity, the combustor operates in dual-mode scramjet mode. As the position of the measurement point gets closer to the downstream, the relative coefficient of wall pressure change becomes higher in terms of wall pressure measurement. The greatest variation in the relative coefficient of wall pressure occurs at x = 370 mm, indicating the highest sensitivity. It is the most suitable parameter for controlling the fuel flow of the dual-mode scramjet. [ABSTRACT FROM AUTHOR]

The reconfiguration of electrical distribution systems has been addressed in numerous scientific studies. Thus, several techniques and models are considered, especially to reduce electrical losses and improve the voltage profile. However, it is clear that even with the increase in research, which has been accentuated since the last decade, the locational pricing and the transmission costs allocation is little explored. In this regard, the proposed method is a distribution system reconfiguration (DSR) optimization problem focused on minimizing the use of the transmission system. In order to validate the meta‐heuristic employed for the DSR, the IEEE 33 and 69 node test systems are used as a proof of concept. In addition, case studies with four substations, three different transmission cost allocation techniques, and transmission system capacity scenarios are analyzed. Numerical results showed an important transmission expansion deferral with consequent decrease in overall costs compared to the classic DSR. The transmission network use of system (TNUoS) charges can play a crucial role in reducing the total cost of the electrical system, promoting distributors to change their feeder patterns so that a larger share of loads access substations with lower charges. [ABSTRACT FROM AUTHOR]

At present, the usage of various energy sources in the electricity grid has formed new challenges like power quality effectiveness, energy utilization, and voltage stabilization. With the recognition of smart grid, the maintenance of power quality (PQ) has been regarded as the challenging one. Primarily, APF are employed in an attempt to recompense the issues associated with power quality, as they can filter out promptly and responds vibrantly. Here, in this work, an IEEE 9 Bus System based on WSCC is introduced along with UPQC combined DPFC system. To accommodate a renewable energy source, one of the generators test system. MGWO approach-based PID device is combined with DC Source as a converter for 3-phase inverter. This arrangement is studied using Simulation in both cases with and without DPFC. In addition, the performance estimation is done in terms of parameters like load voltage and current, shunt voltage and series current, and grid current along with their THD values. Based on the outcome, it is found that the proposed UPQC–DPFC combination helps in effective harmonic elimination and increased power storage at the output side. [ABSTRACT FROM AUTHOR]

This research investigates the role of various energy storage systems (ESS) in improving the power system resiliency. Different ESS configurations are analyzed individually and in combination to assess their impact on system performance. Additionally, a fuzzy-based controller (PIλDN + FFOPI) is proposed as a secondary controller for load frequency control, with control parameters optimized using an improved Volleyball Premier League algorithm (IVPL). This algorithm leverages the powerful synergy of opposition-based learning and the versatility of the VPL algorithm, resulting in a highly effective and innovative approach. To validate the proposed approach, the modified Kundur's 2-area test system under deregulation is first utilized, and its effectiveness is confirmed through testing with both step and random load disturbances. Sensitivity analysis is conducted to evaluate system performance across a wide range of parameter variations. Furthermore, the modified IEEE 39 bus system is utilized to assess compatibility and scalability. Results demonstrate the effectiveness of combined ESS configurations and the fuzzy-based controller in enhancing system stability and reliability. This research contributes to power system engineering by offering insights into the benefits of energy storage systems for dynamic response enhancement. The proposed fuzzy-based control strategy, tuned by the IVPL algorithm, presents a promising approach for improving power system performance and stability. [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]

Rolling contact fatigue (RCF) cracks online detection using eddy current testing (ECT) is in urgent demand. However, RCF cracks detection and evaluation in this way under moving conditions remains challenging due to the velocity effect in ECT. This paper aims to study the response of a transmitter-receiver eddy current probe to cracks under moving conditions and evaluate the depth and inclination angle of RCF cracks. In this paper, a high-speed eddy current testing system is developed to experimentally investigate the influence of coil gap, detection speed, and the lift-off on the eddy current probe's response under moving conditions. In addition, the temporal and amplitude features of the eddy current signal are extracted to characterise the depth and inclination angle of the RCF cracks. The experimental results indicate the eddy current probe's response can be improved by increasing the coil gap (coil centre distance) suitably, which can be done to compensate for the attenuation of the eddy current signal caused by detection speed and lift-off. The probe's response hardly changes with an increase in detection speed when the driver and pick-up coils of the eddy current probe completely overlap. The crack depth and inclination angle can be evaluated under moving conditions. [ABSTRACT FROM AUTHOR]

This study describes a laboratory model of a battery energy storage system (BESS) designed for testing algorithms aimed at reducing peak power consumption in railway traction substations. The system comprises a DC/DC converter and battery energy storage. This article details a laboratory model of a bidirectional buck-boost DC/DC converter, which is used to transfer energy between the battery energy storage and a DC line. It presents an analysis of DC/DC converter systems along with simulation studies. Furthermore, the results of laboratory tests on the DC/DC converter model are also provided. The control algorithm of the system in the traction substation is focused on reducing peak power, offering benefits such as lower charges for the railway operator due to the possibility of reducing contracted power requirements. From the perspective of the power grid, the reduction in power fluctuations and, consequently, voltage sags, is advantageous. This paper includes a description of a hardware simulator for verifying the system's control algorithms. The verification of the control algorithms was performed through experimental tests conducted on a laboratory model (a hardware simulator) of the system for dynamic load reduction in traction substations, on a power scale of 1:1000 (5.5 kW). The experimental tests on the laboratory model (hardware simulator) demonstrated the effectiveness of the algorithm in reducing the peak power drawn from the power source. [ABSTRACT FROM AUTHOR]

A multimodal detection system with complementary capabilities for efficient detection was developed for impurity detection. The system consisted of a visible light camera, a multispectral camera, image correction and registration algorithms. It can obtain spectral features and color features at the same time and has higher spatial resolution than a single spectral camera. This system was applied to detect impurities in Pu'er tea to verify its high efficiency. The spectral and color features of each pixel in the images of Pu'er tea were obtained by this system and used for pixel classification. The experimental results showed that the accuracy of a support vector machine (SVM) model based on combined features was 93%, which was 7% higher than that based on spectral features only. By applying a median filtering algorithm and a contour detection algorithm to the label matrix extracted from pixel-classified images, except hair, eight impurities were detected successfully. Moreover, taking advantage of the high resolution of a visible light camera, small impurities could be clearly imaged. By comparing the segmented color image with the pixel-classified image, small impurities such as hair could be detected successfully. Finally, it was proved that the system could obtain multiple images to allow a more detailed and comprehensive understanding of the detected items and had an excellent ability to detect small impurities. [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]

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]

This paper introduces a virtual consensus‐based wide area differential protection method through cooperative control concepts and graph theory. Using multi‐agent systems eliminates the need for a direct telecommunication connection between the protective relays to implement the proposed differential protection. In addition, applying telecommunication subgraphs facilitates the establishment of numerous differential protection areas. Collaboration between protected areas is facilitated by common agents, establishing a wide‐area cooperative protection network. The capability of the network operator to define various protection areas and the collaboration between these areas ensure the versatility of the proposed method for various protection purposes. The present paper primarily represents the application of the proposed protection system as a wide‐area supervisor protection for distance relays. Performance evaluations on an IEEE 39‐bus test system illustrate the method's effectiveness in various scenarios. The results show enhanced power system stability and resilience, particularly when traditional methods struggle to detect power swings with high impedance variation rates. [ABSTRACT FROM AUTHOR]

The global warming crisis, together with environmental concerns, has already led governments to replace traditional fossil‐fuel cars with low‐emission Electric Vehicles (EVs). This replacement has resulted in the addition of a large number of EVs capable of connecting to the grid. A coordinated charging method is needed to promote EVs on a large scale while preventing grid overloading. In this work, EVs are categorized based on their battery capacity, as cars, trucks, and buses. A charging/discharging mechanism based on Real Time Pricing for each hour is developed for a 20‐min block that has been formed. The locations of EV charging stations have been identified using Voltage Stability Index. In the present work, the power loss when Distributed Generator (DG) units are deployed after the EVs are located in the system for charging and discharging is analyzed. The DGs are considered as solar‐based or wind‐based generators for studying the economic benefit of such an investment under two different weather scenarios and topologies on standard test systems. The results thus obtained give an insight into the various technical and economic benefits. [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]

Rosa centifolia L. and Rosa gallica L. (Rosaceae) are grown as raw materials for valuable essential oils and hydrosols. There are scarce data about the biological activities and the genoprotective potential of the hydrosols of these roses. The aim of the study was to provide information on their cytotoxic/genotoxic activity and anti-cytotoxic/anti-genotoxic capacity against mutagenic N-methyl-N′-nitro-N-nitrosoguanidine (MNNG). The evaluation was performed using classical tests for chromosomal aberrations and micronuclei in the higher plant Hordeum vulgare and human lymphocyte test systems. The experimental schemes included combined hydrosol and mutagen treatment. Both hydrosols (6, 14, 20%) had no cytotoxic effect on barley and showed low genotoxicity in both test systems as the injuries were enhanced to a lesser extent compared to the controls. Lymphocytes were more susceptible than H. vulgare. Under the conditions of combined treatment, it was found that the two hydrosols possessed good anti-cytotoxic and anti-genotoxic potential against MNNG. Both rose products exerted genoprotective potential to a similar extent, decreasing the frequencies of aberrations in chromosomes and micronuclei to a significant degree in both types of cells when non-toxic concentrations of hydrosols were applied before MNNG. This was performed both with and without any inter-treatment time. The observed cytoprotective/genoprotective potential suggests that these hydrosols are promising for further application in phytotherapy and medicine. [ABSTRACT FROM AUTHOR]

The term pyric herbivory was first introduced in 2009, describing how fire shapes herbivory as burned areas attract herbivores and, simultaneously, herbivory shapes fuel load and fire behaviour. Pyric herbivory results in a mosaic of patches with varying levels of herbivory and grazing intensity fire intensity and frequency. The importance of pyric herbivory for ecosystem heterogeneity and biodiversity has been described for North American, Australian and African systems, but the concept remains largely untested in a European context.We introduced fire and herbivory in a full‐factorial experiment in a temperate European wood‐pasture system to test whether pyric herbivory operates in ways comparable to grassy systems elsewhere in the world. Using camera traps, we observed the behaviour of cattle in burned subplots (49 m2) compared with unburned subplots. We measured grass height and the proportion of the subplot that burned as variables affecting cattle preference and to assess how grazing affects fire behaviour. We also examined the effect on plant species and life‐form composition after six seasons of treatment.Cattle spent more time grazing in burned than in unburned subplots in the most productive paddock, where a larger proportion of the subplot burned. The proportion of a subplot that burned was positively related to pre‐fire grass height. Moreover, both grass height and the proportion of subplot burned declined in the burned subplots during the 6‐year study period and fire and cattle grazing altered the relative cover of graminoids and shrubs (Rubus spp.), with more graminoids in grazed and/or burned subplots and more shrubs in ungrazed subplots at the end of the study.Synthesis and applications. In our temperate European wood pasture, fire and (cattle) grazing interacted in ways comparable to pyric herbivory in grassy ecosystems elsewhere in the world, especially in the most productive paddock. Fire attracted grazing, with cattle grazing longer on subplots that burned more fully. Grazing also affected fire, where over the course of our experiment cattle grazing reduced grass height and the proportion of a subplot that burned. We suggest that pyric herbivory is an interesting management method to further explore in the European context to address the loss of biodiversity in open ecosystems, particularly in more productive sites. [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: The landing error scoring system test is a standard for assessing the risk of non-contact injuries and has not yet been developed for Chinese college soccer programs. OBJECTIVE: To establish a test evaluation standard for the landing error scoring system to provide a basis for evaluating the risk of non-contact injuries in college soccer students. METHODS: A prospective cohort study was designed in which 219 athletes from 10 college soccer teams were tested with the standard landing error scoring system, and the subjects were followed up by questionnaires and medical examinations for non-contact injuries of the lower extremities and trunk for 1 year after testing to determine sex differences and assessment criteria for the landing error scoring system test indicators. RESULTS AND CONCLUSION: The total score of the landing error scoring system was (8.22±1.65) points for 219 subjects, (8.29±1.74) for males and (8.07±1.44) for females, with no significant difference between males and females (P > 0.05). Within 1 year after the test, the overall injury rate of 219 subjects was 10.05% and the morbidity rate was 15.98%; the injury rate of male subjects with non-contact injury of the lower limbs and trunk was 12.75% and the morbidity rate was 20.13%; the injury rate of female subjects with non-contact injury of the lower limbs and trunk was 4.29% and the morbidity rate was 7.14%. There were no significant differences in the injury rate between men and women (P < 0.05). The total score of the landing error scoring system was higher in the injury group than in the non-injury group [(9.50±1.14) vs. (8.08±1.64), P < 0.01]; for male subjects, the total score of the landing error scoring system was higher in the injury group than in the non-injury group [(9.63±1.12) vs. (8.09 ± 1.73), P < 0.01]. The area under the curve for the total score of the landing error scoring system was 0.773 (P=0.000), which had a diagnostic value for the risk of non-contact injury of the lower extremities and trunk in male subjects, with a best cut-off point of 8.5, sensitivity of 0.842, specificity of 0.623, positive likelihood ratio of 2.233, negative likelihood ratio of 0.254, relative risk factor of 8.400, and odds ratio of 8.816; the total score of the landing error scoring system was not applicable for assessing the risk of non-contact injury of the lower extremities and trunk in female subjects. To conclude, the landing error scoring system test can be used as a criterion to assess the risk of non-contact injury to the lower extremity and trunk in Chinese college male soccer players, with an optimal cut-off point of 8.5. The risk of non-contact injury to the lower extremity and trunk is 8.40 times higher in male athletes with a landing error scoring system test score of ≥ 8.5 than in male athletes with a score of < 8.5. [ABSTRACT FROM AUTHOR]

Modern vehicles equipped with Advanced Driver Assistance Systems (ADAS) rely heavily on sensor fusion to achieve a comprehensive understanding of their surrounding environment. Traditionally, the Kalman Filter (KF) has been a popular choice for this purpose, necessitating complex data association and track management to ensure accurate results. To address errors introduced by these processes, the application of the Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter is a good choice. This alternative filter implicitly handles the association and appearance/disappearance of tracks. The approach presented here allows for the replacement of KF frameworks in many applications while achieving runtimes below 1 ms on the test system. The key innovations lie in the utilization of sensor-based parameter models to implicitly handle varying Fields of View (FoV) and sensing capabilities. These models represent sensor-specific properties such as detection probability and clutter density across the state space. Additionally, we introduce a method for propagating additional track properties such as classification with the GM-PHD filter, further contributing to its versatility and applicability. The proposed GM-PHD filter approach surpasses a KF approach on the KITTI dataset and another custom dataset. The mean OSPA(2) error could be reduced from 1.56 (KF approach) to 1.40 (GM-PHD approach), showcasing its potential in ADAS perception. [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]

In view of the prominent and intractable problems of frequent high temperature alarms of the communication equipment and high energy consumption of air conditioners in Zhengzhou communication outdoor cabinets, a temperature control system with heat pipe as the main part and air conditioner as the auxiliary part is proposed in this paper. A prototype is developed and its applications are discussed. The annual field test shows the system works well, and it has a remarkable energy saving efficiency. [ABSTRACT FROM AUTHOR]

This article presents research findings on 3H in abiotic environmental compartments, specifically, the 'water-soil-air' system. All of the research areas are located within the Semipalatinsk Test Site (STS): the perimeter of the 'Degelen' site, the riverside zone of the Shagan river and the 'background' area–the southeastern part of the STS (SEP). As research progressed, numerical values of 3H and its species were revealed in various environmental compartments. The presence of 3H was registered not only in underground nuclear test locations but also in the 'background' area–SEP. Maximum 3H tritium concentrations in the water were detected at the 'Degelen' site (up to 57000±5000 Bq/kg) and the Shagan riv (up to 61500±6000 Bq/kg), in the air of the 'Degelen' site (up to 56±11 Bq/m3), in the soil of the 'Degelen' site (up to 5170±500 Bq/kg) and the Shagan riv (4100±400 Bq/kg) in the free water, at SEP (up to 1710±170 Bq/kg) in the organic constituent. Based upon all of the findings, 3H was found to be readily distributed in abiotic environmental compartments depending on certain conditions. Research suggests that water plays a key role in 3H migration processes in the natural system of interest. The second most but equally important constituent is soil and microorganisms of plant and animal origin living there. These assumptions are indirectly proven by research findings that show the HTO and HT air concentration dynamics depending on the sampling location. [ABSTRACT FROM AUTHOR]

Fundamental lateral mode frequency of a spacecraft is determined experimentally by performing a base excited vibration testing. For the above vibration testing, the spacecraft is mounted on the slip table of the shaker system. It is shown in this work that even if the test fixture is quite stiff, the fundamental lateral mode of the spacecraft can be influenced by the slip table system. The frequency obtained in the test is lower than the base fixed frequency. In this mode, even though the test fixture does not undergo bending, the slip table undergoes bending resulting in rotation of the test fixture. The stiffness of the bearing and the bending stiffness of the slip table are the causes of reduction in stiffness. A mathematical model that represents this behavior is developed for two typical shaker-slip table systems, one having a capacity of about 150 kN force and the other about 300 kN force. It is seen that the test system can cause a drop of about 3 Hz for a 3000 kg class of spacecraft, while using 150 kN shaker system. This is quite significant as their frequencies are in the range of 12–15 Hz. [ABSTRACT FROM AUTHOR]

Adaptive protection is an efficient way to tackle the changing topologies in distribution grids caused by the penetration of renewable energy sources. Effective operation of an adaptive protection scheme requires a fast and reliable communication network. However, inherent time delays can adversely impact the effectiveness of Adaptive Protection Schemes (APSs). This manuscript classifies delays into two types and proposes a method or each type to overcome the effects caused by the corresponding type of delay with an improved APS algorithm. The algorithm uses a combination of centralized and decentralized signaling to counter different types of delays. The improved algorithm is tested on a Canadian 9 bus urban benchmark distribution network. MATLAB Simulink environment is used to simulate the 9 bus benchmark distribution network. The results obtained are demonstrated with the improved scheme on stated test system. [ABSTRACT FROM AUTHOR]

Purpose: Although the challenges associated with big data are increasing, the question of the most suitable big data analytics (BDA) platform in libraries is always significant. The purpose of this study is to propose a solution to this problem. Design/methodology/approach: The current study identifies relevant literature and provides a review of big data adoption in libraries. It also presents a step-by-step guide for the development of a BDA platform using the Apache Hadoop Ecosystem. To test the system, an analysis of library big data using Apache Pig, which is a tool from the Apache Hadoop Ecosystem, was performed. It establishes the effectiveness of Apache Hadoop Ecosystem as a powerful BDA solution in libraries. Findings: It can be inferred from the literature that libraries and librarians have not taken the possibility of big data services in libraries very seriously. Also, the literature suggests that there is no significant effort made to establish any BDA architecture in libraries. This study establishes the Apache Hadoop Ecosystem as a possible solution for delivering BDA services in libraries. Research limitations/implications: The present work suggests adapting the idea of providing various big data services in a library by developing a BDA platform, for instance, providing assistance to the researchers in understanding the big data, cleaning and curation of big data by skilled and experienced data managers and providing the infrastructural support to store, process, manage, analyze and visualize the big data. Practical implications: The study concludes that Apache Hadoops' Hadoop Distributed File System and MapReduce components significantly reduce the complexities of big data storage and processing, respectively, and Apache Pig, using Pig Latin scripting language, is very efficient in processing big data and responding to queries with a quick response time. Originality/value: According to the study, there are significantly fewer efforts made to analyze big data from libraries. Furthermore, it has been discovered that acceptance of the Apache Hadoop Ecosystem as a solution to big data problems in libraries are not widely discussed in the literature, although Apache Hadoop is regarded as one of the best frameworks for big data handling. [ABSTRACT FROM AUTHOR]