Fitting Strategy Research Articles

Improving Condensed-Phase Water Dynamics with Explicit Nuclear Quantum Effects: The Polarizable Q-AMOEBA Force Field.

We introduce a new parametrization of the AMOEBA polarizable force field for water denoted Q-AMOEBA, for use in simulations that explicitly account for nuclear quantum effects (NQEs). This study is made possible thanks to the recently introduced adaptive Quantum Thermal Bath (adQTB) simulation technique which computational cost is comparable to classical molecular dynamics. The flexible Q-AMOEBA model conserves the initial AMOEBA functional form, with an intermolecular potential including an atomic multipole description of electrostatic interactions (up to quadrupole), a polarization contribution based on the Thole interaction model and a buffered 14-7 potential to model van der Waals interactions. It has been obtained by using a ForceBalance fitting strategy including high-level quantum chemistry reference energies and selected condensed-phase properties targets. The final Q-AMOEBA model is shown to accurately reproduce both gas-phase and condensed-phase properties, notably improving the original AMOEBA water model. This development allows the fine study of NQEs on water liquid phase properties such as the average H-O-H angle compared to its gas-phase equilibrium value, isotope effects, and so on. Q-AMOEBA also provides improved infrared spectroscopy prediction capabilities compared to AMOEBA03. Overall, we show that the impact of NQEs depends on the underlying model functional form and on the associated strength of hydrogen bonds. Since adQTB simulations can be performed at near classical computational cost using the Tinker-HP package, Q-AMOEBA can be extended to organic molecules, proteins, and nucleic acids opening the possibility for the large-scale study of the importance of NQEs in biophysics.

Can internet use change sport participation behavior among residents? Evidence from the 2017 Chinese General Social Survey.

The popularization of the internet has promoted the implementation of China's national fitness strategy and created conditions for Chinese residents to participate in sports. The internet is an essential medium for disseminating sports knowledge, and the use of the internet can change sport participation behaviors. Therefore, the internet can be used to popularize sports knowledge and promote the participation of all people in sports and thus improve the health of the entire population. This study attempts to empirically analyse how the use of the internet changes sport participation behavior. Utilizing data from the 2017 China General Social Survey, a probit model, ivprobit model, and bias-corrected non-parametric percentile bootstrap test were used to analyse the impact of internet use on sport participation behavior. The empirical results show that internet use significantly increased the probability of participation in sports by Chinese residents. Heterogeneity test results showed that internet use was more effective in promoting sport participation in middle-aged groups, groups of older persons, unmarried groups, and groups with a high school education or above. The mediating effect test results showed that internet use influenced residents' participation in sports by promoting social interaction, leisure and entertainment, and learning and recharging. The internet has changed participation in sports; specifically, the use of the internet promotes sport participation. Additionally, internet use has a more obvious impact on improving the sport participation behavior of middle-aged, older, unmarried, and middle- and higher-educated individuals. Internet social interaction, internet entertainment and internet learning are effective channels to encourage Chinese residents to participate in sports and improve their health.

Spatially resolved broadband absorption spectroscopy measurements of temperature and multiple species (NH, OH, NO, and NH[formula omitted]) in atmospheric-pressure premixed ammonia/methane/air flames

The temperature and multi-species concentration distributions, including NH, OH, NO, and NH3, are of great importance to the research on ammonia/methane combustion mechanisms. However, there is scarce research simultaneously measuring these parameters in atmospheric-pressure ammonia/methane flames. In this work, we proposed a measurement method based on the ultraviolet broadband absorption spectroscopy (BAS) to realize the simultaneous measurement of temperature and multiple species concentrations for the first time (absolute concentrations for OH, NH, and NO, and relative concentrations for NH3). Due to the strong absorption of the electronic transitions in the ultraviolet range, the proposed method offers low detection limits for concentration measurements. Taking NH radicals as an example, the detection limit is as low as 31 ppb at 1700 K. High sensitivity for temperature measurements is also achieved due to the multi-line spectra of OH broadband absorption. Moreover, a fitting strategy was proposed to separate the NO and NH3 spectra near 225 nm, enabling a simultaneous determination of both species. We established an optical system based on the proposed BAS method with a spatial resolution of approximately 0.1 mm to perform spatially resolved measurements of temperature and multiple species on atmospheric ammonia/methane/air flames. The ammonia/methane flames were investigated at different equivalence ratios (0.9, 1.0, and 1.1) and different ammonia mole fractions in fuels (10%, 30%, and 50%). As investigated, NH and NH3 concentrations increased linearly with increasing ammonia mole fractions, while OH and NO concentrations decreased in similar trends with increasing equivalence ratios. The experimentally measured temperature and multi-species concentrations were compared with computational fluid dynamics (CFD) simulations using the mechanism of the CRECK modeling group. Good agreements were achieved in absolute values, spatial profiles, and variations with equivalence ratios and ammonia mole fractions.

Stem-Loop I of the Tembusu Virus 3'-Untranslated Region Is Responsible for Viral Host-Specific Adaptation and the Pathogenicity of the Virus in Mice.

ABSTRACTTembusu virus (TMUV), an avian mosquito-borne flavivirus, was first identified from Culex tritaeniorhynchus in 1955. To validate the effects of the 3′-untranslated region (3′UTR) in viral host-specific adaptation, we generated a set of chimeric viruses using CQW1 (duck strain) and MM 1775 (mosquito strain) as backbones with heterogeneous 3′UTRs. Compared with rMM 1775, rMM-CQ3′UTR (recombinant MM 1775 virus carrying the 3′UTR of CQW1) exhibited enhanced proliferation in vitro, with peak titers increasing by 5-fold in duck embryonic fibroblast (DEF) cells or 12-fold in baby hamster kidney (BHK-21) cells; however, the neurovirulence of rMM-CQ3′UTR was attenuated in 14-day-old Kunming mice via intracranial injection, with slower weight loss, lower mortality, and reduced viral loads. In contrast, rCQ-MM3′UTR showed similar growth kinetics in vitro and neurovirulence in mice compared with those of rCQW1. Then, the Stem-loop I (SLI) structure, which showed the highest variation within the 3′UTR between CQW1 and MM 1775, was further chosen for making chimeric viruses. The peak titers of rMM-CQ3′UTRSLI displayed a 15- or 4-fold increase in vitro, and the neurovirulence in mice was attenuated, compared with that of rMM 1775; rCQ-MM3′UTRSLI displayed comparable multiplication ability in vitro but was significantly attenuated in mice, in contrast with rCQW1. In conclusion, we demonstrated that the TMUV SLI structure of the 3′UTR was responsible for viral host-specific adaptation of the mosquito-derived strain in DEF and BHK-21 cells and regulated viral pathogenicity in 14-day-old mice, providing a new understanding of the functions of TMUV 3′UTR in viral host switching and the pathogenicity changes in mice.IMPORTANCE Mosquito-borne flaviviruses (MBFVs) constitute a large number of mosquito-transmitted viruses. The 3′-untranslated region (3′UTR) of MBFV has been suggested to be relevant to viral host-specific adaptation. However, the evolutionary strategies for host-specific fitness among MBFV are different, and the virulence-related structures within the 3′UTR are largely unknown. Here, using Tembusu virus (TMUV), an avian MBFV as models, we observed that the duck-derived SLI of the 3′UTR significantly enhanced the proliferation ability of mosquito-derived TMUV in baby hamster kidney (BHK-21) and duck embryonic fibroblast (DEF) cells, suggesting that the SLI structure was crucial for viral host-specific adaptation of mosquito-derived TMUVs in mammalian and avian cells. In addition, all SLI mutant viruses exhibited reduced viral pathogenicity in mice, indicating that SLI structure was a key factor for the pathogenicity in mice. This study provides a new insight into the functions of the MBFV 3′UTR in viral host switching and pathogenicity changes in mice.

Towards Auditory Profile-Based Hearing-Aid Fittings: BEAR Rationale and Clinical Implementation.

(1) Background: To improve hearing-aid rehabilitation, the Danish ‘Better hEAring Rehabilitation’ (BEAR) project recently developed methods for individual hearing loss characterization and hearing-aid fitting. Four auditory profiles differing in terms of audiometric hearing loss and supra-threshold hearing abilities were identified. To enable auditory profile-based hearing-aid treatment, a fitting rationale leveraging differences in gain prescription and signal-to-noise (SNR) improvement was developed. This report describes the translation of this rationale to clinical devices supplied by three industrial partners. (2) Methods: Regarding the SNR improvement, advanced feature settings were proposed and verified based on free-field measurements made with an acoustic mannikin fitted with the different hearing aids. Regarding the gain prescription, a clinically feasible fitting tool and procedure based on real-ear gain adjustments were developed. (3) Results: Analyses of the collected real-ear gain and SNR improvement data confirmed the feasibility of the clinical implementation. Differences between the auditory profile-based fitting strategy and a current ‘best practice’ procedure based on the NAL-NL2 fitting rule were verified and are discussed in terms of limitations and future perspectives. (4) Conclusion: Based on a joint effort from academic and industrial partners, the BEAR fitting rationale was transferred to commercially available hearing aids.

Rotation-aware dynamic temporal consistency with spatial sparsity correlation tracking

Recently, discriminative correlation filter (DCF)-based trackers have been widely applied to visual tracking. However, a significant problem of DCF-based trackers is that the model uses the fixed patterns of temporal modeling and fails to suppress the distractive features. To obviate the issue, we propose the dynamic temporal consistency with spatial sparsity correlation filter. The dynamics refers to the adaptive temporal consistency hidden in the response maps and dynamic lasso constraint moderated by the prior knowledge. Unlike the classical temporal modeling method applied to filter model, we exploit the consistency of the response maps to perceive adaptive temporal continuity modeling to enable the filter to have self-regularized ability. Temporal modeling and spatial sparsity are incorporated in a unified optimization learning model and optimized together with ADMM algorithm and Sherman-Morrison formula. In particular, the tracking performance is hindered by the weak capacity to rotation variation. For the sake of estimating the rotation angle accurately to maintain rotation invariance, we explore the coarse-to-fine rotation estimation module. The coarse rotation is supported by the angle pool and the part-based tracker. By introducing the connected hyper ellipse fitting strategy to eliminate fake distractors to ensure a pure target region, the fine level attempts to achieve the optimal rotation angle with the minimum second order statistical bias. The design enables the filter to train with the recovered rotated image instead of axis-aligned bounding box, which attributes to alleviating the impact of ambiguous region and concentrating on the interested target. Extensive experimental results validate the superiority of the proposed method against other state-of-the art trackers and exhibit a remarkable generality in the rotated challenging scenarios. • Dynamic temporal modeling can make the filter highlight the ever-changing region. • Dynamic temporal consistency modeling and spatial sparsity are incorporated in a unified optimization learning model. • The connected hyper ellipse fitting strategy tries to achieve the optimal rotation angle. • Comprehensive experiments have fully demonstrated the superior performance of our proposed method.

PROMOVENDO O DESENVOLVIMENTO DA FORÇA ESPORTIVA COM BASE NA INTEGRAÇÃO DA APTIDÃO FÍSICA E DA SAÚDE NACIONAL

ABSTRACT Objective: Sports play a crucial role in China’s national sportsmanship. Therefore, it is necessary to further promote China’s development as a sports powerhouse. People’s health needs to be raised to the pinnacle of the national fitness strategy, and the government should seriously implement people’s health work. Methods: the construction of the “Powerful Country for Sports” and “Healthy China” provides a more precise direction for the development of national fitness and opens a broader path for the development of national health. The dream of a powerful country in sports has a long history, and different times have different definitions. Results: building a sports power is a strategic project for the development of modern socialist capability with Chinese characteristics. Accelerating the construction of a sports power is related to national prosperity and rejuvenation, and is closely related to the happiness of the people. Conclusions: the barrier preventing the sustainable development of national sports break and create a new driving force for the development of a sports power only by solving the problem of displacement in building a sports power and promoting the deep integration of national fitness and health. Level of evidence II; Therapeutic studies - investigation of treatment results.

Strategies for Determining the Cascade Rate in MHD Turbulence: Isotropy, Anisotropy, and Spacecraft Sampling

Exact laws for evaluating cascade rates, tracing back to the Kolmogorov “4/5” law, have been extended to many systems of interest including magnetohydrodynamics (MHD), and compressible flows of the magnetofluid and ordinary fluid types. It is understood that implementations may be limited by the quantity of available data and by the lack of turbulence symmetry. Assessment of the accuracy and feasibility of such third-order (or Yaglom) relations is most effectively accomplished by examining the von Kármán–Howarth equation in increment form, a framework from which the third-order laws are derived as asymptotic approximations. Using this approach, we examine the context of third-order laws for incompressible MHD in some detail. The simplest versions rely on the assumption of isotropy and the presence of a well-defined inertial range, while related procedures generalize the same idea to arbitrary rotational symmetries. Conditions for obtaining correct and accurate values of the dissipation rate from these laws based on several sampling and fitting strategies are investigated using results from simulations. The questions we address are of particular relevance to sampling of solar wind turbulence by one or more spacecraft.

Older males whistle better: Age and body size are encoded in the mating calls of a nest-building amphibian (Anura: Leptodactylidae)

Courtship acoustic displays in anuran amphibians are energetically costly and risky, but have a major role in mating success since they encode relevant information regarding the caller’s identity and status. Age and size are essential traits shaping fitness, reproductive success and life-history strategies, and thus are expected to also have a role in courtship displays. We tested this assumption in a species of nest-building frogs,Leptodactylus bufonius, in northern Argentina. We conducted the first detailed quantitative description of the males’ mating calls and assessed the effects of biological traits (i.e., body size parameters and individual age) and local climate (i.e., air temperature and humidity) on the main acoustic features of these calls (i.e., call duration, inter-call duration, dominant frequency, and dominant frequency modulation). The calls were short (mean ± SE, 0.163 ± 0.004 s), whistle-like, single notes with harmonic structure. The dominant frequency (1381.7 ± 16.2 Hz) decreased with arm length (χ2= 5.244, df = 1,p= 0.022) and had an upward modulation (456.4 ± 11.0 Hz) which increased with age (χ2= 4.7012, df = 1,p= 0.030). Call duration and dominant frequency were the most static parameters at intra-individual level, indicating their role in individual recognition. Temperature and humidity shaped the temporal acoustic parameters, and the dominant frequency. Our findings suggest that the acoustic features of the mating calls in amphibians could promote female mate choice in relation to both size and age and open up new questions for future research: are females more attracted to older males, and what are the specific costs and benefits? We suggest that mating calls may direct female preferences toward males of certain size and age classes, ultimately shaping the life-history strategies in a given population. Finally, we found discrepancies in the mating calls ofL. bufoniusrecorded from Corrientes and those previously described from other populations, which suggests that multiple species may have been recorded under the same name.

The moving target tracking and segmentation method based on space-time fusion

At present, the target tracking method based on the correlation operation mainly uses deep learning to extract spatial information from video frames and then performs correlations on this basis. However, it does not extract the motion features of tracking targets on the time axis, and thus tracked targets can be easily lost when occlusion occurs. To this end, a spatiotemporal motion target tracking model incorporating Kalman filtering is proposed with the aim of alleviating the problem of occlusion in the tracking process. In combination with the segmentation model, a suitable model is selected by scores to predict or detect the current state of the target. We use an elliptic fitting strategy to evaluate the bounding boxes online. Experiments demonstrate that our approach performs well and is stable in the face of multiple challenges (such as occlusion) on the VOT2016 and VOT2018 datasets with guaranteed real-time algorithm performance.

Precise Two-Dimensional Tilt Measurement Sensor with Double-Cylindrical Mirror Structure and Modified Mean-Shift Algorithm for a Confocal Microscopy System

To improve the accuracy of three-dimensional (3D) surface contour measurements of freeform optics, a two-dimensional (2D) tilt measurement sensor for confocal microscopy (CM) systems is proposed based on a double-cylindrical mirror structure. First, the proposed system is accurately modeled. Second, we introduce a modified mean–shift-based peak-extraction algorithm with a novel kernel function (MSN) because the reflectivity of the measured object and fluctuation of the light source affect the measurement accuracy. Third, a partition fitting (PF) strategy is proposed to reduce the fitting error and improve the measurement accuracy. Simulations and experiments reveal that the robustness, speed, and angular prediction accuracy of the system effectively improved as a function of MSN and PF. The developed sensor can measure the 2D tilt, where each tilt is a composition of two separate dimensions, and the mean prediction errors in the 2D plane from −10°–+10° are 0.0134° (0.067% full scale (F.S)) and 0.0142° (0.071% F.S). The sensor enables the optical probe of a traditional CM to obtain accurate and simultaneous estimates of the 2D inclination angle and spatial position coordinates of the measured surface. The proposed sensor has potential in 3D topographic reconstruction and dynamic sampling rate optimization for 3D contour detection.

Predicting Aided Outcome With Aided Word Recognition Scores Measured With Linear Amplification at Above-conversational Levels.

Many hearing aid (HA) users receive limited benefit from amplification, especially when trying to understand speech in noise, and they often report hearing-related residual activity limitations. Current HA fitting strategies are typically based on pure-tone hearing thresholds only, even though suprathreshold factors have been linked to aided outcomes. Furthermore, clinical measures of speech perception such as word recognition scores (WRSs) are performed without frequency-specific amplification, likely resulting in suboptimal speech audibility and thus inaccurate estimates of suprathreshold hearing abilities. Corresponding measures with frequency-specific amplification ("aided") would likely improve such estimates and enable more accurate aided outcome prediction. Here, we investigated potential links between either unaided WRSs or aided WRSs measured at several above-conversational levels and two established HA outcome measures: The Hearing-In-Noise Test (HINT) and the International Outcome Inventory for Hearing Aids (IOI-HA). Thirty-seven older individuals with bilateral hearing impairments participated. Two conditions were tested: unaided and aided, with all stimuli presented over headphones. In the unaided condition, the most comfortable level (MCL) for the presented speech stimuli, WRS at MCL+10 dB as well as uncomfortable levels (UCLs) for narrowband noise stimuli were measured. In the aided condition, all stimuli were individually amplified according to the "National Acoustic Laboratories-Revised, Profound" fitting rule. Aided WRSs were then measured using an Interacoustics Affinity system at three above-conversational levels, allowing for the maximum aided WRS as well as the presence of "rollover" in the performance-intensity function to be estimated. Multivariate data analyses were performed to examine the relations between the HINT (measured using a simulated HA with the NAL-RP amplification) or IOI-HA scores (for the participants' own HAs) and various potential predictors (age, pure-tone average hearing loss, unaided WRS, aided WRS, rollover presence [ROp], and UCL). Aided WRSs predicted the HINT scores better than any other predictor and were also the only significant predictor of the IOI-HA scores. In addition, UCL and ROp in the aided WRSs were significant predictors of the HINT scores and competed for variance in the statistical models. Neither age nor pure-tone average hearing loss could predict the two aided outcomes. Aided WRSs can predict HA outcome more effectively than unaided WRSs, age or pure-tone audiometry and could be relatively easily implemented in clinical settings. More research is necessary to better understand the relations between ROp, UCL and speech recognition at above-conversational levels.

Many‐objective evolutionary algorithm assisted by a novel angle‐based fitness strategy

SummaryMeasuring the convergence of solutions is greatly significant for many‐objective optimization problems. Although various methods have been proposed regarding this issue, they still suffer from the performance consistency on different problems. For this issue, this article proposes a novel angle‐based fitness strategy. To be specific, the convergence of solutions is defined with adaptive key solutions, which are determined by the angles between solutions. Based on the novel angle‐based fitness strategy, this article designs a many‐objective evolutionary algorithm assisted by a novel angle‐based fitness strategy. Experiments are conduced to verify the performance of the proposed method in comparison with other state‐of‐the‐art methods. The experimental analyzes illustrate the outstanding performance of the proposed method for many‐objective optimization problems.

Validation of an Empirical Subwaveform Retracking Strategy for SAR Altimetry

The sea level retrievals from the latest generation of radar altimeters (the SAR altimeters) are still challenging in the coastal zone and areas covered by sea ice and require a dedicated fitting (retracking) strategy for the waveforms. In the framework of the European Space Agency’s Baltic + Sea Level (ESA Baltic SEAL) project, an empirical retracking strategy (ALES + SAR), including a dedicated sea state bias correction, has been designed to improve the sea level observations in the Baltic Sea, characterised by a jagged coastline and seasonal sea ice coverage, without compromising the quality of open ocean data. In this work, the performances of ALES + SAR are validated against in-situ data in the Baltic Sea. Moreover, variance, crossover differences and power spectral density of the open ocean data are evaluated on a global scale. The results show that ALES + SAR performances are of comparable quality to the ones obtained using physical-based retrackers, with relevant advantages in coastal and sea ice areas in terms of quality and quantity of the sea level data.

Adjustment Method of “FAST” Active Reflector Based on Optimal Fitting Strategy

The adjustment method of the fast active reflector of “Chinese heavenly eye” is studied. Firstly, this paper studies the offset characteristics of fast main cable node position, combined with the position of the celestial body to be measured, the follow-up coordinate system is established, and the optimal fitting model of active reflector adjustment based on discrete main cable node is established by using the idea of optimal fitting of the ideal surface. Secondly, the genetic algorithm is used to solve the minimum root mean square error (RMSE). The offset of the triangular reflector is driven by the offset of the main cable node, so that the working area is closer to the ideal paraboloid, and the maximum electromagnetic wave signal receiving ratio is achieved. Finally, rotate the coordinate data of each main cable node according to the known celestial body angle and use the Lagrange operator method to obtain the shortest distance from the actual offset point to the ideal paraboloid as the objective function, with the radial expansion range of the actuator and the variation range of the distance between adjacent points as constraints, and the size of the electromagnetic wave contact area is the basis for judging the amount of information, and a reflector adjustment model for the optimal displacement strategy of discrete main cable nodes is established. Through the test, concluded that the optimal fitting strategy is ideal, the model can accurately obtain the fast active reflector adjustment method under the constraint conditions. Through the test, the conclusion that the optimal fitting strategy is ideal is obtained, and the fast active reflector adjustment method that the model can accurately obtain under the constraints is verified.

Minimal number of sampling directions for robust measures of the spherical mean diffusion weighted signal: Effects of sampling directions, b-value, signal-to-noise ratio, hardware, and fitting strategy

Several recent multi-compartment diffusion MRI investigations and modeling strategies have utilized the orientationally-averaged, or spherical mean, diffusion-weighted signal to study tissue microstructure of the central nervous system. Most experimental designs sample a large number of diffusion weighted directions in order to calculate the spherical mean signal, however, sampling a subset of these directions may increase scanning efficiency and enable either a decrease in scan time or the ability to sample more diffusion weightings. Here, we aim to determine the minimum number of gradient directions needed for a robust measurement of the spherical mean signal. We used computer simulations to characterize the variation of the measured spherical mean signal as a function of the number of gradient directions, while also investigating the effects of diffusion weighting (b-value), signal-to-noise ratio (SNR), available hardware, and spherical mean fitting strategy. We then utilize empirically acquired data in the brain and spinal cord to validate simulations, showing experimental results are in good agreement with simulations. We summarize these results by providing an intuitive lookup table to facilitate the determination of the minimal number of sampling directions needed for robust spherical mean measurements, and give recommendations based on SNR and experimental conditions.

Regularized Spectral Spike Response Model: A Neuron Model for Robust Parameter Reduction.

The modeling procedure of current biological neuron models is hindered by either hyperparameter optimization or overparameterization, which limits their application to a variety of biologically realistic tasks. This article proposes a novel neuron model called the Regularized Spectral Spike Response Model (RSSRM) to address these issues. The selection of hyperparameters is avoided by the model structure and fitting strategy, while the number of parameters is constrained by regularization techniques. Twenty firing simulation experiments indicate the superiority of RSSRM. In particular, after pruning more than 99% of its parameters, RSSRM with 100 parameters achieves an RMSE of 5.632 in membrane potential prediction, a VRD of 47.219, and an F1-score of 0.95 in spike train forecasting with correct timing (±1.4 ms), which are 25%, 99%, 55%, and 24% better than the average of other neuron models with the same number of parameters in RMSE, VRD, F1-score, and correct timing, respectively. Moreover, RSSRM with 100 parameters achieves a memory use of 10 KB and a runtime of 1 ms during inference, which is more efficient than the Izhikevich model.

Sequential shape heritability during confined comminution

This study analyzes the evolving shape distribution of sand grains undergoing fracture during confined comminution. Digital images from 3D x-ray tomography scans of a sand specimen subjected to one-dimensional compression are used. To quantify grain shape evolution, three fitting protocols are proposed and used in conjunction with a tracking algorithm recording the breakage history of individual particles. This strategy enables the detection of incremental breakage events, as well as the quantification of correlations between the morphological properties before (parent particles) and after breakage (child particles). Regardless of the fitting strategy, the results show that the most frequent morphology of the child particles is strongly correlated with that of their corresponding parents. This phenomenon, here defined shape heritability, was found to be stronger in finer, elongated particles and to become more prevalent at higher breakage levels. In addition, direct inspection of individual breakage events indicated that the fracture patterns responsible for size reduction vary with the shape of the parent particles. These results shed light on the dynamics of particle shape evolution during comminution and can constitute the basis to define ultimate shape characteristics attained by particles undergoing pervasive breakage.

Advancing traditional strategies for testing hydrological model fitness in a changing climate

Mitigation of adverse effects of global warming relies on accurate flow projections under climate change. These projections usually focus on changes in hydrologic signatures, such as 100-year floods, which are estimated through statistical analyses of simulated flows under baseline and future conditions. However, models used for these simulations are traditionally calibrated to reproduce entire flow series, rather than statistics of hydrologic signatures. Here, we consider this dichotomy by testing whether performance indicators (e.g., Nash-Sutcliffe coefficient) are informative about model ability to reproduce distributions and trends in the signatures. Results of streamflow simulations in 50 high-latitude catchments with the 3DNet-Catch model show that high model performances according to traditional indicators do not assure that distributions or trends in hydrologic signatures are well reproduced. We, therefore, suggest that performance in reproducing distributions and trends in hydrologic signatures should be included in the process of model selection for climate change impacts studies.

Macromolecular background signal and non-Gaussian metabolite diffusion determined in human brain using ultra-high diffusion weighting.

PurposeDefinition of a macromolecular MR spectrum based on diffusion properties rather than relaxation time differences and characterization of non‐Gaussian diffusion of brain metabolites with strongly diffusion‐weighted MR spectroscopy.MethodsShort echo time MRS with strong diffusion‐weighting with b‐values up to 25 ms/μm2 at two diffusion times was implemented on a Connectom system and applied in combination with simultaneous spectral and diffusion decay modeling. Motion‐compensation was performed with a combined method based on the simultaneously acquired water and a macromolecular signal.ResultsThe motion compensation scheme prevented spurious signal decay reflected in very small apparent diffusion constants for macromolecular signal. Macromolecular background signal patterns were determined using multiple fit strategies. Signal decay corresponding to non‐Gaussian metabolite diffusion was represented by biexponential fit models yielding parameter estimates for human gray matter that are in line with published rodent data. The optimal fit strategies used constraints for the signal decay of metabolites with limited signal contributions to the overall spectrum.ConclusionThe determined macromolecular spectrum based on diffusion properties deviates from the conventional one derived from longitudinal relaxation time differences calling for further investigation before use as experimental basis spectrum when fitting clinical MR spectra. The biexponential characterization of metabolite signal decay is the basis for investigations into pathologic alterations of microstructure.