Updated Coefficients Research Articles

Wavelet-based spatiotemporal sparse quaternion dictionary learning for reconstruction of multi-channel vibration data

Accurate reconstruction of multi-source data information plays an essential role in remote intelligent operation, and prognostic and health maintenance (RIO-PHM) of industrial systems. However, traditional signal reconstruction methods such as compressed sensing fail to capture the spatio-temporal characteristics and coupling nature of the multi-source or multi-channel data. To alleviate this bottleneck, in this paper, a new wavelet-based spatiotemporal sparse quaternion dictionary learning (WSTS-QDL) algorithm is formulated for the reconstruction of multi-channel vibration data for the first time. Specifically, the wavelet-based spatiotemporal sparse low-rank matrix (SLRM) algorithm is elaborated and the sparse coefficient matrix of the multi-channel signals can be estimated using the split Bregman iteration (SBI) technique. Then, quaternion-based dictionary learning is introduced for multi-channel data reconstruction according to the updated sparse coefficient matrix during quaternion dictionary learning. Eventually, two equipmental scenarios including run-to-failure data of rolling bearing in bearing test bench and vibration signal of the failured bearing in corn thresher, are utilized for verification. The experimental results demonstrate that the highest recovery accuracy performance with scoring function and the lowest errors are achieved by the proposed method in contrast with the state-of-the-art benchmarks such as orthogonal matching pursuit (OMP) method and spatiotemporal sparse Bayesian learning (SSBL), and the waveform of phase space trajectory and points cloud distribution of the Poincare section in the original signal are similar/same to that obtained by the proposed method.

Three-dimensional large eddy simulation urban neighborhood model with updated building drag coefficient and universal multiscale Smagorinsky model

Three-dimensional large eddy simulation urban neighborhood model with updated building drag coefficient and universal multiscale Smagorinsky model

Exploring the first-stage ignition and model optimization in the comprehensive study of n-dodecane oxidation

n-Dodecane is commonly employed as a surrogate for investigating the combustion characteristics of jet and diesel fuels. Enhancing comprehension of its combustion behavior and developing accurate chemical kinetics models for simulating combustion is of paramount importance in engine development. This study focuses on a detailed exploration of n-dodecane oxidation kinetics under low-temperature conditions and presents a novel dataset concerning the first-stage ignition delay time. A broad spectrum of experimental conditions is investigated, encompassing a range of temperature (600 ∼ 1350 K), pressure (5 ∼ 20 atm), equivalence ratios (0.5 ∼ 1.0), and dilution gases (N2 and Ar). Additionally, combustion experiments in a pure oxygen environment are performed, contributing valuable data to existing research. To enhance the precision of the chemical reaction kinetics model of n-dodecane, this study integrates updated rate coefficients obtained from the latest theoretical calculations for specific reaction classes. The improved rate rule provides a more accurate reference for the construction of the chemical reaction kinetics model of long straight alkane. The resulting improved model excels in accurately predicting both the first-stage ignition delay time and the total ignition delay time under a wide range of operational conditions. Additionally, the model performance is rigorously evaluated through a comprehensive assessment against a diverse array of datasets gathered from various literature references. The results show that, in contrast to the previously proposed model, this enhanced model provides highly reliable predictions over a broad range of parameters.

Improving Irrigation Management of Cotton with Small Unmanned Aerial Vehicle (UAV) in Texas High Plains

The rapid decline in water availability for irrigation on the Texas High Plains (THP) is a significant problem affecting crop production and the viability of a large regional economy worth approximately USD 7 billion annually. This region is the largest continuous cotton-producing area in the United States, and the timely delivery and efficient use of irrigation water are critical to the sustainability and profitability of cotton production in this region. Current irrigation scheduling must be improved to reduce water consumption without compromising crop production. Presently, irrigation scheduling based on reference evapotranspiration (ETo) is limited due to the lack of reliable and readily available in-field weather data and updated crop coefficients. Additionally, in-field variability in crop water demand is often overlooked, leading to lower irrigation efficiency. To address these challenges, we explored the potential use of an unmanned aerial vehicle (UAV)-based crop monitoring system to support irrigation management decisions. This study was conducted in Lubbock, Texas, in 2022, where high temporal and spatial resolution images were acquired using a UAV from a cotton field experiment with four irrigation levels. Soil moisture and canopy temperature sensors were deployed to monitor crop response to irrigation and rainfall. The results indicated a significant effect of water stress on crop growth (revealed by UAV-based canopy cover (CC) measurements), yield, and fiber quality. Strong correlations between multi-temporal CC and lint yield (R2 = 0.68 to 0.88) emphasized a clear trend: rainfed treatments with lower yields exhibited reduced CC, while irrigated plots with higher CC displayed increased yields. Furthermore, irrigated plots produced more mature and uniform fibers. This study also explored various evapotranspiration calculation approaches indicating that site-specific CC measurements obtained from a UAV could significantly reduce irrigation application. A regression model linking evapotranspiration to canopy cover demonstrated promising potential for estimating water demand in crops with an R2 as high as 0.68. The findings highlight the efficacy of UAV-based canopy features in assessing drought effects and managing irrigation water in water-limited production regions like the THP.

Assessing seismic displacements and early warning using kinematic PPP with MADOCA real-time products: A case study of 2023 Kahramanmaraş (Türkiye) earthquakes

Early warning and emergency hazard response studies in large earthquakes require rapid and reliable determination of earthquake magnitude. The magnitude of an earthquake can be estimated based on peak ground displacement (PGD) values captured from high-rate GNSS records. In this study, two major earthquakes that hit Kahramanmaraş Province on February 6, 2023, were investigated by using the real-time Global Navigation Satellite System (GNSS) Precise Point Positioning (PPP) technique to confirm the usability of GNSS in early warning. Data from high-rate (1-Hz) GNSS stations were evaluated with the real-time kinematic PPP approach utilizing the multi-GNSS advanced demonstration tool for orbit and clock analysis (MADOCA) products and JPL's GipsyX software. In addition, static PPP was also used to identify the permanent displacements caused by earthquakes. Static PPP results demonstrated that significant displacements were detected at stations close to the epicenters, particularly the 446.86 cm horizontal displacement in the EKZ1 station. Considering the kinematic PPP results revealed that when PGD values calculated from seismic waves, functional model, and updated coefficients were implemented, the moment magnitude of the Pazarcık earthquake was estimated as Mw 7.78, which was reported as Mw 7.8 by USGS and Mw 7.7 by AFAD, whilst the magnitude of the Elbistan earthquake was computed as Mw 7.56, which was reported as Mw 7.5 by USGS and 7.6 by AFAD. Overall, this study validates the effectiveness of the real-time GNSS PPP as an attractive alternative for analyzing coseismic events and supporting early warning.

On the conditions for absolute minimum fuel burn for turbofan powered, civil transport aircraft and a simple model for wave drag

Abstract In a recent series of papers, Poll and Schumann have been developing a simple model for estimating fuel burn for turbofan powered, civil transport aircraft for a given mass, Mach number and flight level and in a specified ambient temperature profile for all phases of flight. This paper focuses upon the combination of Mach number and flight level at which an aircraft cruises with the absolute minimum fuel burn. For a given aircraft type, the information necessary to determine these conditions must be specified and this poses a challenge. An initial attempt to obtain these data has been described previously by the first author. In this paper, the optimum conditions are found using a completely different approach. Starting from first principles and using established theory, the equations governing the situation where engine overall efficiency and airframe lift-to-drag ratio both have local maxima at the same flight condition are developed. This special case is termed the “design optimum” condition and, for a specified aircraft mass and a specified atmospheric temperature versus pressure profile, it gives the lowest possible fuel burn for any aircraft and engine combination. The design optimum occurs at a particular Mach number and Reynolds number, and it is a fixed characteristic of the aircraft. The analysis reveals the significance of Reynolds number variations, wave drag, including its derivatives with respect to both lift coefficient and Mach number, and the atmospheric properties. Whilst wave drag is notoriously difficult to determine accurately, it is found that solutions to the equations are not particularly sensitive to the accuracy of this quantity. Consequently, a simple, physically realistic model can give good results. An appropriate model is developed and a complete, approximate solution is obtained. Taking the International Standard Atmosphere as the design atmosphere, results are presented for the 53 aircraft types previously considered by Poll and Schumann. Relative to the design optimum conditions, when Reynolds number is constant and wave drag is zero, compressibility alone reduces L/D by about 5%, reduces lift coefficient by about 1.5% and increases drag coefficient by about 3.5%. Reynolds number variation has little effect upon L/D, but it reduces lift coefficient and drag coefficient by a further 7% and 8% respectively. The reduction in lift coefficient has a significant impact on the optimum cruise flight level. In general, an aircraft’s operating optimum will not coincide with its design optimum, but deviations are expected to be small. Therefore, using the design optimum solution as a reference point, an improved version of the operating optimum estimation method described by Poll and Schumann in previous work is developed. This allows the estimation of the conditions for absolute minimum fuel burn for an aircraft of given mass flying thorough any atmosphere. Updated coefficients for the 53 aircraft types are given.

Experimental and kinetic modeling study on ammonia/polyoxymethylene dimethyl ether 2 oxidation in a jet-stirred reactor

The oxidation of ammonia/polyoxymethylene dimethyl ether 2 (NH3/PODE2) was investigated in a jet-stirred reactor with ammonia addition of 10 %, 25 %, and 50 % in mole fraction. Atmospheric experiments were conducted at an equivalence ratio of 1.0, within the temperature range of 500–1100 K. The initial fuel mole fraction and residence time were fixed at 0.5 % and 2 s, respectively. PODE2 and NH3, along with other intermediates and products such as C1-C2 hydrocarbons and permanent gases, were analyzed using gas chromatography and Fourier transform infrared spectroscopy. The experimental results demonstrate that the addition of NH3 has little impact on the consumption of PODE2, primarily influencing the mole fraction of hydrocarbon intermediates. All three blends exhibited negative temperature coefficient (NTC) behaviors. However, NTC behavior was weakened as the NH3 blending ratios increased due to the competition for O2 at low temperatures. A detailed kinetic model for PODE2/NH3 blends was constructed, incorporating updated rate coefficients from the recent literature and analogy methods. The model also considers the interaction between PODE2 and NH3, which was investigated through reaction pathway analysis and sensitivity analysis. Simulated results show that the mole fraction profiles are reasonably predicted by this model at the test conditions. The interaction between PODE2 and NH3 is facilitated by CH3, NH2 radicals, and NO-NO2 cycle. The rapid reversible reaction between NO and NO2 alters the reaction pathway of radicals in the blends. At low temperatures, PODE2 in blend follows the same oxidation pathway as pure PODE2, while NH3 oxidation is affected by the introduction of additional HO2 and H from PODE2. New OH formation pathways involving NH2, NO, and NO2 occur, while the decomposition of H2O2 is inhibited, thereby affecting the oxidation of PODE2 at intermediate temperatures. Additionally, a notable decrease in the intermediates with carbon–carbon double bonds is observed, due to the consumption of CH3 through the reaction NO2 + CH3 = NO + CH3O. This important reaction also promotes the oxidation of CH3 and the NO-NO2 cycle, resulting in an improvement in system reactivity.

A robust optimization approach for inventory management with limited-time discounts and service-level requirement under demand uncertainty

A multi-period inventory management problem is considered for a retailer offering limited-time discounts and having a joint service-level requirement over the discount periods under demand uncertainty. In each period, the retailer, only knowing a reference value and the bounds of the uncertain demand, has to determine the order quantity of the product before demand realizations to maximize the total profit over the planning horizon while achieving the required service level over the discount periods. A budgeted uncertainty set is adopted to accommodate demand uncertainty and a joint chance constraint is used to formulate the service-level requirement. The retailer problem is formulated as an affinely adjustable robust chance-constrained model and is transformed into a linear program. A double-layer iterative approach is proposed to solve the problem. The outer layer uses a posteriori method to update the budget coefficient. The inner layer solves the affinely adjustable robust chance-constrained model with the updated budget coefficient, and obtains the updated order quantities. A case study based on real data demonstrates that the proposed approach outperforms other approaches by better balancing the average realized profit and the realized service level. Moreover, the results show that the retailer can obtain a larger average realized profit by gradually than abruptly changing the prices.

Radiation Protection Considerations for Cancer Patients with End-stage Renal Disease Receiving 131 I Treatment.

Differentiated thyroid cancer (DTC) is commonly treated first with a partial or complete thyroidectomy, followed by radioiodine (RAI) ablative therapy to eliminate remaining cancer cells. In such treatments, physical decay and urinary excretion are the primary means of 131 I. As such, patients with impaired urinary ability clearance, such as patients with end-stage renal disease (ESRD) whose urinary ability is impaired by dysfunction, can retain abnormally high activities of RAI, posing a concern to both the patient and those with whom the patient interacts. Additionally, ESRD patients are commonly administered dialysis therapy, wherein their blood is externally cycled through a dialyzer (hemodialysis) or filtered by instilling a dialysate fluid into the peritoneum (peritoneal dialysis) to filter uremic toxins from their blood that accumulate due to kidney dysfunction. These factors make determining release and dosing for ESRD patients receiving RAI therapy dependent on a plurality of variables. An evaluation of the current patient release guidelines, as given in US Nuclear Regulatory Commission (US NRC) Regulatory Guide 8.39 Rev. 1 for ESRD patients receiving RAI, has yet to be addressed. In this study, a biokinetic model for 131 I in ESRD patients receiving dialysis has been developed, improving on traditional two-compartment models, reflective of kinetics from multi-compartment models with updated transfer coefficients modified to reflect the different physiological functions of compartments. This updated biokinetic model was integrated with Monte Carlo radiation transport calculations using stylized computational hermaphroditic phantoms to calculate dose rate coefficients in exposure scenarios and compared with those of the point source models of NRC Reg Guide 8.39 Rev. 1 (and the proposed verbiage in Rev. 2). Results demonstrated that the baseline models of Rev. 1 and Rev. 2 overestimated the effective dose rate to an exposed individual for the majority of time post-administration, where both models overestimated the total dose to the maximally exposed individual. However, the application of several patient-specific modifying factors to the Rev. 2 model resulted in an overestimation by only a factor of 1.25, and in general, the results produced with the patient-specific modifications provide improved convergence with the dose rate coefficients computed in this study for ESRD patients.

Pharmacodynamics, safety, tolerability and pharmacokinetics of a single oral dose of an engineered phenylalanine ammonia-lyase in patients with phenylketonuria

The cornerstone treatment of hyperphenylalaninemia (HPA) and phenylketonuria (PKU) is a lifelong low-protein diet with phenylalanine (Phe) free L-amino acid supplements. However, the PKU diet has significant shortcomings, and there is a clinically unmet need for new therapeutics to improve patient outcomes. CDX-6114 is a modified phenylalanine ammonia-lyase (PAL) enzyme obtained by a mutation in the Anabaena variabilis PAL sequence. CodeEvolver® protein engineering technology has been applied to improve the degradation resistance of the enzyme. In our first phase I trial, 19 patients were given a single oral dose of CDX-6114 at 7.5 g, 2.5 g, 0.7 g, or placebo in a cross-over design. After an overnight fast, patients received a standardised breakfast of 20 g of protein, thus exceeding the dietary recommendations for a single meal in patients with PKU. Plasma levels of Phe and cinnamic acid (CA) were measured over a 5-h period following CDX-6114 dosing. During the development of CDX-6114, a stability assessment using reverse-phase high-performance liquid chromatography (HPLC) assay revealed two peaks. The second peak was identified as CA. It was not previously known that as part of the mechanism of action, the CA remained associated with the protein following the conversion of Phe. Thus, recalculating the historical PAL enzyme amounts in CDX-6114 bulk substance was necessary. An updated extinction coefficient was achieved by applying a correction factor of 0.771 to previously reported doses. Postprandial plasma levels of Phe increased in all dose cohorts over time between 10% and 30% from baseline, although the actual peak of Phe levels was not achieved within the 5-h observation. When accounting for the interquartile ranges, these concentrations were similar to the placebo. As plasma levels of Phe were no longer a reliable marker for pharmacodynamics, the consistently detectable amount of CA seen in all patients who received CDX-6114 provided proof of the enzymatic activity of CDX-6114 in metabolising gastrointestinal Phe. Peak levels of CA were seen shortly after CDX-6114 intake, with a rapid decline, and remained low compared with the plasma Phe levels. This pattern indicates a short half-life, possibly due to the liquid formulation or the inability to withstand the lower pH in the human stomach compared with animal models in earlier studies. This was the first trial in patients with PKU to establish the safety and tolerability of CDX-6114. A single dose of CDX-6114 was safe and well tolerated, with no serious adverse events or presence of anti-drug antibodies detected. Efficacy will be explored in future trials using an optimised formulation.

SAFOTEB project: towards new approaches for the reliability assessment of existing prestressed bridge

AbstractThis paper presents the structure of new collaborative research project entitled SAFOTEB “A reviewed SAfety FOrmat for structural reliability assessment of post‐TEnsioned concrete Bridges”. The research aims at assessing the reliability of the current safety format and developing specific suggestions for existing concrete bridges with post‐tensioned cables. To date, no European code provides specific guidance for such a purpose. Indeed, the status of conservation and possible defects of the cables may be hidden, enlarging the uncertainties in the structural assessment of such constructions. The basic steps of the research are: (i) definition of the probabilistic models for the main variables concerning the assessment of existing post‐tensioned prestressed concrete bridges; (ii) reliability assessment and calibration of updated safety coefficients for the partial factors method; (iii) evaluation of the residual life and model updating through real‐time continuous monitoring systems. The full procedure will be applied on existing case study structures used as benchmarks. The project is funded by FABRE, an Italian research consortium composed by universities and research institutions aimed at the evaluation and monitoring of bridges, viaducts, tunnels and other structures.

A Study on the Hydrodynamics and Coupling Effects of the Multibody Floating Photovoltaic (FPV) Concept

Floating photovoltaics (FPVs) have been developed rapidly in the past few years and will gradually become the “third pillar” of the photovoltaic industry. To better understand the performance of FPV floaters, this paper provides an in-depth study on the hydrodynamics of a single FPV module and the coupling effects of multiple modules. The results show that a conventional frequency domain approach, which includes both panel and Morison models, may not necessarily provide realistic results. Even after adding an additional damping matrix for the floaters based on empirical values from the oil and gas (O&G) industry, and a free surface damping model between the pontoons, the responses were still not convincing. Therefore, a nonlinear time-domain hydrodynamic solver was introduced. Further studies and comparisons were performed to understand the behavior of the module, and some updated damping coefficients were summarized. Thereafter, a multibody hydrodynamic model was built to check the coupling effects. With the additional damping surface on the gap surface among the modules, some attempts were made to derive reasonable results, when the model test was not available. Preliminary studies of both a scaled-down system (with 9 modules and mooring lines) and a full-scale system (with 90 modules, buoys, and mooring systems) were also investigated, and some initial results were demonstrated.

The Mean Moment of Inertia for Irregularly Shaped Phobos and Its Application to the Constraint for the Two-Layer Interior Structure for the Martian Moon

The interior structure of Phobos has been the subject of debate in recent years, with the moment of inertia being a determining factor. To study this structure, we modeled Phobos with a two-layer structure and calculated its mean density and moment of inertia using updated gravity coefficients of degree-2 and forced libration amplitudes. By minimizing the misfit between modeled and derived moment of inertia, and observed and modeled mean density, we determined the frequency distribution for estimated parameters, including the core radius rc, core density ρc, and density ρm of the outer layer. Our results indicate that the optimized core radius is around 8.2 km for our models, along with a core density compromise of approximately 2500 kg·m−3, and an outer layer density of around 1400 kg·m−3. These values have remarkable sensitivity to the misfit function, implying a higher density likely inside Phobos compared to the outer layer. Given that the large core density was associated with ice content, it suggested that the fractional ice content in the outer layer is approximately 11% with a rock density of 2200 kg·m−3, while the content in the core is lower at 2.4% with a rock density of 3000 kg·m−3. The methodology introduced in this study can be further used to study the interior structure of irregularly shaped asteroids.

Evaluating potato evapotranspiration and crop coefficients in the Columbia Basin of Washington state

The current potato crop coefficient values have yet to be updated to account for newly released potato cultivars and changing climate since their inception in the 1970s. In irrigation scheduling, crop coefficients, representing three development stages, play a critical role in modeling evapotranspiration. In this study, we developed crop coefficients and evaluated crop evapotranspiration trends of five Pacific Northwest-grown russet cultivars. The field study was conducted during 2018, 2019, and 2020 growing seasons at the Washington State University Irrigated Agricultural Research and Extension Center near Othello, Washington. The potato cultivars included Alturas, Clearwater Russet, Ranger Russet, Russet Burbank, and Umatilla Russet. Crop evapotranspiration was computed using a combination of environmental and soil sensors and the soil water balance method. Crop coefficient values were developed by dividing crop evapotranspiration by reference evapotranspiration based on alfalfa. Soil water content measurements revealed that Alturas and Clearwater Russet’s water consumption was significantly higher than that of Russet Burbank during the last eight weeks before harvest. During the mid-season, crop evapotranspiration calculations of Alturas and Clearwater Russet were nearly identical, averaging 7.22 mm day−1. In contrast, the lowest crop evapotranspiration was observed in Russet Burbank, with 6.89 mm day−1. The average crop coefficient values resulting from evaluating five full-season russet potato cultivars were determined to be 0.40 during the initial stage, 0.95 during the mid-season, and 0.57 during the late-season stage. This study offers valuable information to potato growers in the Columbia Basin, enabling them to make informed decisions by providing updated crop coefficient values for determining evapotranspiration and affording them with insight into the water consumption patterns of five distinct russet potato cultivars.

Comparison of two software programs used to determine the relative supersaturation of urine ions.

Relative supersaturation (RSS) values for urine crystals are a measure of the risk of urinary stone formation and have been shown to be lowered in foods shown to aid in the management of urolithiasis. In order to calculate RSS in pets, computer programs have been developed to calculate RSS and aid in the understanding of stone formation in veterinary medicine. However, some older programs have not been updated for use in animals, and the specific coefficients used are not publically available. One of the first RSS programs was developed in BASIC computer language and published in 1985 which was called EQUIL2. The EQUIL2 program was updated to a compiled version compatible with a PC platform. However, the formulas could not be read or altered. This study evaluates a new program with known coefficients to the original EQUIL2 program. The RSS values of the two programs were compared through a t-test, calculating the r2 from correlation analysis, Lin's concordance correlation coefficient, and by a Bland-Altman analysis of outputs from the two programs using urine samples from healthy dogs and cats. Our results show that for both magnesium ammonium phosphate (struvite) and calcium oxalate, the RSS values of the original program could be calculated from the new programs RSS values. Although the actual RSS values were different (as might be expected through the use of the updated coefficients and different thermodynamic stability constants in the calculations) the results were highly correlated, finding elevations and reductions in RSS proportionally in the same urine samples. The current work creates a foundation for using the modernized program to calculate RSS and provides a shared method for understanding the risk of struvite and calcium oxalate stone formation.

The Bias Dynamics Model: Correcting for Meta-biases in Therapeutic Prediction

AbstractInferences from clinical research results to estimates of therapeutic effectiveness suffer due to various biases. I argue that predictions of medical effectiveness are prone to failure because current medical research overlooks the impacts of a particularly detrimental set of biases: meta-biases. Meta-biases are linked to higher-level characteristics of medical research and their effects are only observed when comparing sets of studies that share certain meta-level properties. I offer a model for correcting research results based on meta-research evidence, the bias dynamics model, which employs regularly updated empirical bias coefficients to attenuate estimates of therapeutic effectiveness.

Body condition changes at sea: Onboard calculation and telemetry of body density in diving animals

Abstract The ability of marine mammals to accumulate sufficient lipid energy reserves is vital for mammals' survival and successful reproduction. However, long‐term monitoring of at‐sea changes in body condition, specifically lipid stores, has only been possible in elephant seals performing prolonged drift dives (low‐density lipids alter the rates of depth change while drifting). This approach has limited applicability to other species. Using hydrodynamic performance analysis during transit glides, we developed and validated a novel satellite‐linked data logger that calculates real‐time changes in body density (∝lipid stores). As gliding is ubiquitous amongst divers, the system can assess body condition in a broad array of diving animals. The tag processes high sampling rate depth and three‐axis acceleration data to identify 5 s high pitch angle glide segments at depths >100 m. Body density is estimated for each glide using gliding speed and pitch to quantify drag versus buoyancy forces acting on the gliding animal. We used tag data from 24 elephant seals (Mirounga spp.) to validate the onboard calculation of body density relative to drift rate. The new tags relayed body density estimates over 200 days and documented lipid store accumulation during migration with good correspondence between changes in body density and drift rate. Our study provided updated drag coefficient values for gliding (Cd,f = 0.03) and drifting (Cd,s = 0.12) elephant seals, both substantially lower than previous estimates. We also demonstrated post‐hoc estimation of the gliding drag coefficient and body density using transmitted data, which is especially useful when drag parameters cannot be estimated with sufficient accuracy before tag deployment. Our method has the potential to advance the field of marine biology by switching the research paradigm from indirectly inferring animal body condition from foraging effort to directly measuring changes in body condition relative to foraging effort, habitat, ecological factors and anthropogenic stressors in the changing oceans. Expanding the method to account for diving air volumes will expand the system's applicability to shallower‐diving (<100 m) species, facilitating real‐time monitoring of body condition in a broad range of breath‐hold divers.

Adaptive Model Predictive Current Control for PMLSM Drive System

This article proposes an adaptive model predictive current control (AM-MPCC) for surface-mounted permanent magnet linear synchronous motor systems to simultaneously enhance the robustness against permanent magnet flux, inductance, and resistance mismatches. First, the conventional continuous control set model predictive control is analyzed, illustrating that parameter variations will inevitably deteriorate the current regulation performance. Then, an adaptive predictive model, which involves a disturbance term and an optimized current change rate coefficient, is proposed. The optimal coefficient is estimated using a steady-state incremental model and the steepest descent method at each control period. A discrete-time sliding mode disturbance observer is devised based on the adaptive model with updated coefficients to achieve the disturbance term. Finally, an exponential reaching law-based-reference trajectory is defined for the cost function of AM-MPCC to adjust the current approach trajectory. Experimental results verify the excellent robustness performances of the proposed method.

A self-adjusting ant colony clustering algorithm for ECG arrhythmia classification based on a correction mechanism

Background and objectiveAs a representative type of cardiovascular disease, persistent arrhythmias can often become life-threatening. In recent years, machine learning-based ECG arrhythmia classification aided methods have been effective in assisting physicians with their diagnosis, but these methods have problems such as complex model structures, poor feature perception ability, and low classification accuracy. MethodsIn this paper, a self-adjusting ant colony clustering algorithm for ECG arrhythmia classification based on a correction mechanism is proposed. This method does not distinguish between subjects when establishing the dataset in order to reduce the effect of differences in ECG signal features between individuals, thus improving the robustness of the model. When the classification is achieved, a correction mechanism is introduced to correct outliers caused by the accumulation of errors in the classification process in order to improve the classification accuracy of the model. According to the principle that the flow rate of gas can be increased under the convergence channel, a dynamically updated pheromone volatilization coefficient ρ, namely the increased flow rate ρ, is introduced to help the model converge more stably and faster. As the ants move, the next transfer target is selected by a truly self-adjusting transfer method, and the transfer probability is dynamically adjusted according to the pheromone concentration and the path distance. ResultsBased on the MIT-BIH arrhythmia dataset, the new algorithm achieved classification of five heart rhythm types, with an overall accuracy of 99.00%. Compared to other experimental models, the classification accuracy of the proposed method represents a 0.2% to 16.6% improvement, and compared to other current studies, the classification accuracy of the proposed method is 0.65% to 7.5% better. ConclusionsThis paper addresses the shortcomings of ECG arrhythmia classification methods based on feature engineering, traditional machine learning and deep learning, and presents a self-adjusting ant colony clustering algorithm for ECG arrhythmia classification based on a correction mechanism. Experiments demonstrate the superiority of the proposed method compared to basic models as well as those with improved partial structures. Furthermore, the proposed method achieves very high classification accuracy with a simple structure and fewer iterations than other current methods.

The Identity and Chemistry of C7H7 Radicals Observed during Soot Formation

We used aerosol mass spectrometry coupled with tunable synchrotron photoionization to measure radical and closed-shell species associated with particle formation in premixed flames and during pyrolysis of butane, ethylene, and methane. We analyzed photoionization (PI) spectra for the C7H7 radical to identify the isomers present during particle formation. For the combustion and pyrolysis of all three fuels, the PI spectra can be fit reasonably well with contributions from four radical isomers: benzyl, tropyl, vinylcyclopentadienyl, and o-tolyl. Although there are significant experimental uncertainties in the isomeric speciation of C7H7, the results clearly demonstrate that the isomeric composition of C7H7 strongly depends on the combustion or pyrolysis conditions and the fuel or precursors. Fits to the PI spectra using reference curves for these isomers suggest that all of these isomers may contribute to m/z 91 in butane and methane flames, but only benzyl and vinylcyclopentadienyl contribute to the C7H7 isomer signal in the ethylene flame. Only tropyl and benzyl appear to play a role during pyrolytic particle formation from ethylene, and only tropyl, vinylcyclopentadienyl, and o-tolyl appear to participate during particle formation from butane pyrolysis. There also seems to be a contribution from an isomer with an ionization energy below 7.5 eV for the flames but not for the pyrolysis conditions. Kinetic models with updated and new reactions and rate coefficients for the C7H7 reaction network predict benzyl, tropyl, vinylcyclopentadienyl, and o-tolyl to be the primary C7H7 isomers and predict negligible contributions from other C7H7 isomers. These updated models provide better agreement with the measurements than the original versions of the models but, nonetheless, underpredict the relative concentrations of tropyl, vinylcyclopentadienyl, and o-tolyl in both flames and pyrolysis and overpredict benzyl in pyrolysis. Our results suggest that there are additional important formation pathways for the vinylcyclopentadienyl, tropyl, and o-tolyl radicals and/or loss pathways for the benzyl radical that are currently unaccounted for in the present models.