Multiphase machines are often chosen due to their enhanced fault tolerance. Six-phase ones are especially convenient because they may be fed by off-the-shelf three-phase converters. In particular, those with symmetrical windings offer superior postfault capabilities. On the other hand, estimation of the stator resistance is important for purposes such as thermal monitoring and preserving control performance. Resistance estimation by dc-signal injection provides low sensitivity to parameter deviations compared with other techniques. It has previously been shown that the dc signal can be added in the non-torque-producing (x-y) plane of a six-phase machine to avoid the torque disturbances that typically arise in three-phase machines. However, extending this method to the case of an open-phase fault (OPF) is not straightforward, because of the associated current restrictions. This paper addresses dc-signal injection in a symmetrical six-phase induction motor with an OPF. It is shown that, in contrast to healthy operation, the postfault dc injection should be carefully performed so that minimum copper loss, peak phase current and zero-sequence braking torque are achieved. A solution that attains optimum performance in all these aspects simultaneously is proposed. Adapted controller and resistance estimation are also presented. Experimental results confirm the theory.
The fabrication of integrated circuits (ICs) employing two-dimensional (2D) materials is a major goal of semiconductor industry for the next decade, as it may allow the extension of the Moore’s law, aids in in-memory computing and enables the fabrication of advanced devices beyond conventional complementary metal-oxide-semiconductor (CMOS) technology. However, most circuital demonstrations so far utilizing 2D materials employ methods such as mechanical exfoliation that are not up-scalable for wafer-level fabrication, and their application could achieve only simple functionalities such as logic gates. Here, we present the fabrication of a crossbar array of memristors using multilayer hexagonal boron nitride (h-BN) as dielectric, that exhibit analog bipolar resistive switching in >96% of devices, which is ideal for the implementation of multi-state memory element in most of the neural networks, edge computing and machine learning applications. Instead of only using this memristive crossbar array to solve a simple logical problem, here we go a step beyond and present the combination of this h-BN crossbar array with CMOS circuitry to implement extreme learning machine (ELM) algorithm. The CMOS circuit is used to design the encoder unit, and a h-BN crossbar array of 2D hexagonal boron nitride (h-BN) based memristors is used to implement the decoder functionality. The proposed hybrid architecture is demonstrated for complex audio, image, and other non-linear classification tasks on real-time datasets.
Objective To disseminate the portable sequencer MinION in developing countries for the main purpose of battling infectious diseases, we found a consortium called Global Research Alliance in Infectious Diseases (GRAID). By holding and inviting researchers both from developed and developing countries, we aim to train the participants with MinION’s operations and foster a collaboration in infectious diseases researches. As a real-life example in which resources are limited, we describe here a result from a training course, a metagenomics analysis from two blood samples collected from a routine cattle surveillance in Kulan Progo District, Yogyakarta Province, Indonesia in 2019. Results One of the samples was successfully sequenced with enough sequencing yield for further analysis. After depleting the reads mapped to host DNA, the remaining reads were shown to map to Theileria orientalis using BLAST and OneCodex. Although the reads were also mapped to Clostridium botulinum, those were found to be artifacts derived from the cow genome. An effort to construct a consensus sequence was successful using a reference-based approach with Pomoxis. Hence, we concluded that the asymptomatic cow might be infected with T. orientalis and showed the usefulness of sequencing technology, specifically the MinION platform, in a developing country.
Prediction algorithms for protein or gene structures, including transcription factor binding from sequence information, have been transformative in understanding gene regulation. Here we ask whether human transcriptomic profiles can be predicted solely from the expression of transcription factors (TFs). We find that the expression of 1600 TFs can explain >95% of the variance in 25,000 genes. Using the light-up technique to inspect the trained NN, we find an over-representation of known TF-gene regulations. Furthermore, the learned prediction network has a hierarchical organization. A smaller set of around 125 core TFs could explain close to 80% of the variance. Interestingly, reducing the number of TFs below 500 induces a rapid decline in prediction performance. Next, we evaluated the prediction model using transcriptional data from 22 human diseases. The TFs were sufficient to predict the dysregulation of the target genes (rho = 0.61, P < 10 ⁻²¹⁶ ). By inspecting the model, key causative TFs could be extracted for subsequent validation using disease-associated genetic variants. We demonstrate a methodology for constructing an interpretable neural network predictor, where analyses of the predictors identified key TFs that were inducing transcriptional changes during disease.
Using mid-infrared plasmons to trigger visible surface enhanced Raman spectroscopy signals within a nanocavity represents new opportunities for fundamental investigation of light–matter interaction within quantum regimes, requiring improved sensing capabilities enabled by well-designed nano/microstructures and characterization systems.
The physical properties of carbon materials can be altered by doping. For instance, the electronic properties of graphene can be modulated by controlling the substitutional doping of the carbon lattice with N. In addition, C–N bonding configurations with three ring types are recognized: pyridinic-N, pyrrolic-N, and graphitic-N. Controlling the type and relative density of various types of substitutional N is an important objective that requires an extremely high level of precision when the atomic lattice is constructed. This control can be accomplished only via bottom-up methods, such as chemical vapor deposition (CVD). The number of reports on N-doped graphene (NDG) grown via CVD has increased over the past decade, but a reliable wafer-scale production strategy that can realize the desired atomic-precision growth of NDG is still lacking. To identify the most promising strategies and analyze the consistency of the results published in the literature, we review the CVD growth and characterization of two-dimensional NDG and two of the most popular applications of NDG films: field-effect transistors and energy storage devices.
Background Profiling the plant root architecture is vital for selecting resilient crops that can efficiently take up water and nutrients. The high-performance imaging tools available to study root-growth dynamics with the optimal resolution are costly and stationary. In addition, performing nondestructive high-throughput phenotyping to extract the structural and morphological features of roots remains challenging. Results We developed the Multiple XL ab: a modular, mobile, and cost-effective setup to tackle these limitations. The system can continuously monitor thousands of seeds from germination to root development based on a conventional camera attached to a motorized multiaxis-rotational stage and custom-built 3D-printed plate holder with integrated light-emitting diode lighting. We also developed an image segmentation model based on deep learning that allows the users to analyze the data automatically. We tested the Multiple XL ab to monitor seed germination and root growth of Arabidopsis developmental, cell cycle, and auxin transport mutants non-invasively at high-throughput and showed that the system provides robust data and allows precise evaluation of germination index and hourly growth rate between mutants. Conclusion Multiple XL ab provides a flexible and user-friendly root phenotyping platform that is an attractive mobile alternative to high-end imaging platforms and stationary growth chambers. It can be used in numerous applications by plant biologists, the seed industry, crop scientists, and breeding companies.
Background In hot deserts daily/seasonal fluctuations pose great challenges to the resident organisms. However, these extreme ecosystems host unique microenvironments, such as the rhizosheath–root system of desert speargrasses in which biological activities and interactions are facilitated by milder conditions and reduced fluctuations. Here, we examined the bacterial microbiota associated with this structure and its surrounding sand in the desert speargrass Stipagrostis pungens under the contrasting environmental conditions of summer and winter in the Sahara Desert. Results The belowground rhizosheath–root system has higher nutrient and humidity contents, and cooler temperatures than the surrounding sand. The plant responds to the harsh environmental conditions of the summer by increasing the abundance and diversity of extracellular polymeric substances (EPS) compared to the winter. On the contrary, the bacterial community associated with the rhizosheath–root system and its interactome remain stable and, unlike the bulk sand, are unaffected by the seasonal environmental variations. The rhizosheath–root system bacterial communities are consistently dominated by Actinobacteria and Alphaproteobacteria and form distinct bacteria communities from those of bulk sand in the two seasons. The microbiome-stabilization mediated by the plant host acts to consistently retain beneficial bacteria with multiple plant growth promoting functions, including those capable to produce EPS, which increase the sand water holding capacity ameliorating the rhizosheath micro-environment. Conclusions Our results reveal the capability of plants in desert ecosystems to stabilize their below ground microbial community under seasonal contrasting environmental conditions, minimizing the heterogeneity of the surrounding bulk sand and contributing to the overall holobiont resilience under poly-extreme conditions.
Improving the atom utilization of metals and clarifying the M–M’ interaction is both greatly significant in assembling high-performance ultra-light electromagnetic wave-absorbing materials. Herein, a high-temperature explosion strategy has been successfully applied to assemble the hierarchical porous carbon sponge with Co–Fe decoration via the pyrolysis of the energetic metal organic framework. The as-constructed hybrid displays a superior reflection loss (RL) value of − 57.7 dB and a specific RL value of − 192 dB mg ⁻¹ mm ⁻¹ at 12.08 GHz with a layer thickness of 2.0 mm (loading of 15 wt%). The off-axis electron hologram characterizes the highly distributed numerous polarized nanodomain variable capacitors, demonstrating the dipole and interfacial polarization along the edges of the nanopores. More importantly, the X-ray absorption spectroscopy analysis verifies the mutual interaction between the metal cluster and carbon matrix and the electronic coupling responsible for the greatly improved electromagnetic wave absorption.
We continue the investigation on the spectrum of operators arising from the discretization of partial differential equations. In this paper we consider a three field formulation recently introduced for the finite element least-squares approximation of linear elasticity. We discuss in particular the distribution of the discrete eigenvalues in the complex plane and how they approximate the positive real eigenvalues of the continuous problem. The dependence of the spectrum on the Lamé parameters is considered as well and its behavior when approaching the incompressible limit.
In this work, 38 different organic emerging contaminants (ECs), belonging to various chemical classes such as pharmaceuticals (PhCs), endocrine-disrupting chemicals (EDCs), benzotriazoles (BTRs), benzothiazoles (BTHs), and perfluorinated compounds (PFCs), were initially identified and quantified in the biologically treated wastewater collected from Athens’ (Greece) Sewage Treatment Plant (STP). Processes already used in existing STPs such as microfiltration (MF), nanofiltration (NF), ultrafiltration (UF), UV radiation, and powdered activated carbon (PAC) were assessed for ECs’ removal, under the conditions that represent their actual application for disinfection or advanced wastewater treatment. The results indicated that MF removed only one out of the 38 ECs and hence it was selected as pretreatment step for the other processes. UV radiation in the studied conditions showed low to moderate removal for 5 out of the 38 ECs. NF showed better results than UF due to the smaller pore sizes of the filtration system. However, this enhancement was observed mainly for 8 compounds originating from the classes of PhCs and PFCs, while the removal of EDCs was not statistically significant. Among the various studied technologies, PAC stands out due to its capability to sufficiently remove most ECs. In particular, removal rates higher than 70% were observed for 9 compounds, 22 were partially removed, while 7 demonstrated low removal rates. Based on our screening experiments, future research should focus on scaling-up PAC in actual conditions, combining PAC with other processes, and conduct a complete economic and environmental assessment of the treatment.
The hybrid indirect evaporative cooling-mechanical vapor compression (IEC-MVC) process is an emerging cooling technology that combines the advantages of IEC and MVC, i.e., effective temperature and humidity control, high energy efficiency, and low water consumption. This paper presents an experimental study of the hybrid IEC-MVC process. A 1-Rton pilot is fabricated by connecting IEC and MVC in series, and its performance is evaluated under different operating conditions (outdoor air temperature and humidity, air flowrate, compressor frequency). Results revealed that the outdoor air temperature and humidity could be lowered to 5–15 °C and 5–10 g/kg, respectively. The IEC handles 35%–50% of the total cooling load, and the energy consumption can be reduced by 15%–35% as compared to standalone MVC. Moreover, the condensate collected from the evaporator can compensate for >70% of water consumption in IEC, making the system applicable in arid regions. Based on the derived results, a simplified empirical model is developed for rapid evaluation of the IEC-MVC process, and the energy-saving potential in major cities of Saudi Arabia is estimated.
The pump and probe technique in Raman spectroscopy is used to demonstrate the phonon transport properties of an In0.05Ga0.95N/GaN heterostructure. The pump laser generates phonons via the energy relaxation of the generated carriers in the electronic energy bands of the InGaN layer, and the Raman signal is obtained using the probe laser. In the present study, 532-nm and 325-nm lasers are utilized. The phonon transport from the InGaN layer to the GaN layer across the heterointerface is blocked near the crystal defects inherited from the GaN layer. This phenomenon is consistent with our previous report demonstrating the blocking of phonon transport across the In0.16Ga0.84N/GaN heterointerface near the misfit dislocations in the In0.16Ga0.84N layer. Lateral phonon transport over a distance of 20 μm is observed, which is dominated by diffusive phonon transport. This method has the advantage of enabling the study of phonon transport processes inside and at interfaces of films with crystal defects by visualizing the shift of phonon-mode energies due to local heating.
This paper presents an experimental and numerical investigation of a spark-ignited (SI) cooperative fuel research (CFR) engine fueled with different liquefied petroleum gas (LPG) fuels and exhaust gas recirculation (EGR). The effects of LPG fuel composition on engine combustion characteristics are initially evaluated at two different compression ratios (CR). Results show normal combustion at CR 7 and heavy knocking combustion at CR 10 for all the tested fuels, with a more substantial impact for the LPG fuel with high proportions of n-butane species. The Livengood-Wu (LW) integral method is then used to analyze the knock occurrence risk of individual fuel based on the reactivity of the tested fuels. The introduction of EGR then demonstrates the potential of knock intensity reduction below the borderline knock limit. A zonal-based kinetic interactions study is also performed to understand the knock mitigation effectiveness of EGR over the pressure–temperature domain relevant to SI engine operation. Finally, a multidimensional, computational fluid dynamics (CFD) simulation model is shown to predict the LPG combustion characteristics and presents the evolution of in-cylinder temperature and chemical species to demonstrate the development of end-gas autoignition events without and with EGR.
MILD (moderate or intense low-oxygen dilution) combustion is a promising technology for mitigating NOx emission from fuel combustion, but the combustion stability becomes an issue when using low-preheat air due to the slower reaction at the burner exit. In this study, an inverse-diffusion flame (IDF) burner configuration is proposed to enhance the combustion stability of MILD regime. The burner features an earlier preheat of fuel stream instead of usually adopted air stream, and can be also operated in traditional diffusion swirling combustion mode. Experiments are conducted in a model combustor to examine the effect of varying burner load (P) and equivalence ratio (φ) on flame topology, pollutant (CO and NO) emission performance, as well as flame emitting spectrum for this burner. It shows that increasing P can enhance the combustion stabilities of both swirling mode and MILD mode, and MILD combustion is found unable to be sustained when P is lower than 2 kW. Increasing φ enlarges the flame liftoff distance under swirling combustion, but has a much smaller effect on MILD combustion. Emission data shows a nearly 50 % reduction of NO by MILD combustion comparing to swirling combustion in all operating cases. Spectra analysis suggests a higher sensitivity of the flame response to the operating parameters under swirling combustion in respect to MILD combustion. A longer combustion chamber is found to produce a lower CO emission but has negligible effect on NO emission. Flow field and temperature distributions by further numerical simulation clearly demonstrate the effectiveness of fuel preheat by adopting IDF burner configuration for enhancing the flame stability when adopting normal temperature air in MILD combustion.
In this paper, a thorough review of the current state of the hydrogen phase equilibrium approaches is presented. Potential applications of phase equilibrium calculations for the accurate simulation of the entire process are then identified. Based on the first and second laws of thermodynamics, an advanced constant (N), volume (V), and temperature (T) (NVT) flash calculation scheme is developed for fluid mixtures containing hydrogen, which can be used to calculate the phase equilibrium for various feed compositions. We produce reasonable predictions of the phase transition under various environmental conditions for a number of engineering scenarios during the hydrogen production and storage processes, thus demonstrating the effectiveness and robustness of the proposed phase equilibrium calculation scheme.
Due to the widespread proliferation of distributed generation resources and the current market situation, ensuring the security and reliability of power grids against fault events has become a more challenging task. The aim of this paper is to compare different power flow techniques for power grid vulnerability assessment against symmetrical fault incidents using bus impedance matrix. In this study, first, the relationship of the post-fault voltage phasor at each bus with the pre-fault voltage phasors at that bus and the faulted bus, impedance matrix elements, and fault impedance is investigated through power system analysis under pre-fault and post-fault circumstances. Subsequently, the accuracy of different iterative and non-iterative power flow algorithms, i.e. Newton Raphson (NR), Fast Decoupled (FD), and Direct Current (DC) methods, for the power grid vulnerability assessment is compared. To achieve this, the fault analysis at each bus is performed commencing with a very large fault impedance and ending with the fault impedance at which one of the buses reaches the low voltage violation limit. Finally, to appraise the proposed strategy, several simulations have been undertaken on IEEE 14 bus system using MATLAB software. The simulation results indicate that the power grid vulnerability against symmetrical faults is highly influenced by the type of applied power flow technique.
The Kingdom of Saudi Arabia (KSA) has vast geothermal energy resources. When developed, these markedly strengthen the country's goals of achieving a carbon-neutral economy. To demonstrate the feasibility and techno-economic performance of small-scale, hydrothermal well doublet systems for direct use in KSA, we perform reservoir and wellbore flow and heat-transport simulations as well as an economic analysis. The maximum permissible flowrate is constrained to avoid thermoelastic fracturing in the near-wellbore region. Reservoir conditions of a sedimentary basin along the Red Sea coast (near Al Wajh) provide an ideal study case to which we add economic parameters considered representative for KSA. We derive a Levelized Cost of Heat (LCOH) ranging from 49 to 128 $/MWh for 50-mD hydrothermal doublet systems with an optimal well spacing of 600 m and a flowrate ranging from 110 kg/s to 50 kg/s. LCOH is strongly influenced by decreasing reservoir transmissivity. Also, a minimum injection temperature is required to avoid thermoelastic fracturing. Our economic analysis further highlights that capacity factor and well-drilling cost have the greatest impact on LCOH. Thus, this study provides a guide and workflow to conduct techno-economic investigations for decision-making, risk mitigation, optimizing geothermal-energy-extraction and economic-performance conditions of hydrothermal doublet systems.
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