Brittle and ductile yielding in soft materials.

Many soft materials yield under mechanical loading, but how this transition from solid-like behavior to liquid-like behavior occurs can vary significantly. Understanding the physics of yielding is of great interest for the behavior of biological, environmental, and industrial materials, including those used as inks in additive manufacturing and muds and soils. For some materials, the yielding transition is gradual, while others yield abruptly. We refer to these behaviors as being ductile and brittle. The key rheological signatures of brittle yielding include a stress overshoot in steady-shear-startup tests and a steep increase in the loss modulus during oscillatory amplitude sweeps. In this work, we show how this spectrum of yielding behaviors may be accounted for in a continuum model for yield stress materials by introducing a parameter we call the brittility factor. Physically, an increased brittility decreases the contribution of recoverable deformation to plastic deformation, which impacts the rate at which yielding occurs. The model predictions are successfully compared to results of different rheological protocols from a number of real yield stress fluids with different microstructures, indicating the general applicability of the phenomenon of brittility. Our study shows that the brittility of soft materials plays a critical role in determining the rate of the yielding transition and provides a simple tool for understanding its effects under various loading conditions.

Multispecies coexistence in fragmented landscapes.

Spatial dynamics have long been recognized as an important driver of biodiversity. However, our understanding of species' coexistence under realistic landscape configurations has been limited by lack of adequate analytical tools. To fill this gap, we develop a spatially explicit metacommunity model of multiple competing species and derive analytical criteria for their coexistence in fragmented heterogeneous landscapes. Specifically, we propose measures of niche and fitness differences for metacommunities, which clarify how spatial dynamics and habitat configuration interact with local competition to determine coexistence of species. We parameterize our model with a Bayesian approach using a 36-y time-series dataset of three Daphnia species in a rockpool metacommunity covering >500 patches. Our results illustrate the emergence of interspecific variation in extinction and recolonization processes, including their dependencies on habitat size and environmental temperature. We find that such interspecific variation contributes to the coexistence of Daphnia species by reducing fitness differences and increasing niche differences. Additionally, our parameterized model allows separating the effects of habitat destruction and temperature change on species extinction. By integrating coexistence theory and metacommunity theory, our study provides platforms to increase our understanding of species' coexistence in fragmented heterogeneous landscapes and the response of biodiversity to environmental changes.

Dorsolateral Striatum is a Bottleneck for Responding to Task-Relevant Stimuli in a Learned Whisker Detection Task in Mice.

A learned sensory-motor behavior engages multiple brain regions, including the neocortex and the basal ganglia. How a target stimulus is detected by these regions and converted to a motor response remains poorly understood. Here, we performed electrophysiological recordings and pharmacological inactivations of whisker motor cortex and dorsolateral striatum to determine the representations within, and functions of, each region during performance in a selective whisker detection task in male and female mice. From the recording experiments, we observed robust, lateralized sensory responses in both structures. We also observed bilateral choice probability and preresponse activity in both structures, with these features emerging earlier in whisker motor cortex than dorsolateral striatum. These findings establish both whisker motor cortex and dorsolateral striatum as potential contributors to the sensory-to-motor (sensorimotor) transformation. We performed pharmacological inactivation studies to determine the necessity of these brain regions for this task. We found that suppressing the dorsolateral striatum severely disrupts responding to task-relevant stimuli, without disrupting the ability to respond, whereas suppressing whisker motor cortex resulted in more subtle changes in sensory detection and response criterion. Together these data support the dorsolateral striatum as an essential node in the sensorimotor transformation of this whisker detection task.SIGNIFICANCE STATEMENT Selecting an item in a grocery store, hailing a cab - these daily practices require us to transform sensory stimuli into motor responses. Many decades of previous research have studied goal-directed sensory-to-motor transformations within various brain structures, including the neocortex and the basal ganglia. Yet, our understanding of how these regions coordinate to perform sensory-to-motor transformations is limited because these brain structures are often studied by different researchers and through different behavioral tasks. Here, we record and perturb specific regions of the neocortex and the basal ganglia and compare their contributions during performance of a goal-directed somatosensory detection task. We find notable differences in the activities and functions of these regions, which suggests specific contributions to the sensory-to-motor transformation process.

Optimizing spatio-temporal correlation structures for modeling food security in Africa: a simulation-based investigation.

This study investigates the impact of spatio- temporal correlation using four spatio-temporal models: Spatio-Temporal Poisson Linear Trend Model (SPLTM), Poisson Temporal Model (TMS), Spatio-Temporal Poisson Anova Model (SPAM), and Spatio-Temporal Poisson Separable Model (STSM) concerning food security and nutrition in Africa. Evaluating model goodness of fit using the Watanabe Akaike Information Criterion (WAIC) and assessing bias through root mean square error and mean absolute error values revealed a consistent monotonic pattern. SPLTM consistently demonstrates a propensity for overestimating food security, while TMS exhibits a diverse bias profile, shifting between overestimation and underestimation based on varying correlation settings. SPAM emerges as a beacon of reliability, showcasing minimal bias and WAIC across diverse scenarios, while STSM consistently underestimates food security, particularly in regions marked by low to moderate spatio-temporal correlation. SPAM consistently outperforms other models, making it a top choice for modeling food security and nutrition dynamics in Africa. This research highlights the impact of spatial and temporal correlations on food security and nutrition patterns and provides guidance for model selection and refinement. Researchers are encouraged to meticulously evaluate the biases and goodness of fit characteristics of models, ensuring their alignment with the specific attributes of their data and research goals. This knowledge empowers researchers to select models that offer reliability and consistency, enhancing the applicability of their findings.

Improving the Cost-efficiency of Preventive Chemotherapy: Impact of New Diagnostics on Stopping Decisions for Control of Schistosomiasis.

BACKGROUND: Control of schistosomiasis (SCH) relies on the regular distribution of preventive chemotherapy (PC) over many years. For the sake of sustainable SCH control, a decision must be made at some stage to scale down or stop PC. These "stopping decisions" are based on population surveys that assess whether infection levels are sufficiently low. However, the limited sensitivity of the currently used diagnostic (Kato-Katz [KK]) to detect low-intensity infections is a concern. Therefore, the use of new, more sensitive, molecular diagnostics has been proposed. METHODS: Through statistical analysis of Schistosoma mansoni egg counts collected from Burundi and a simulation study using an established transmission model for schistosomiasis, we investigated the extent to which more sensitive diagnostics can improve decision making regarding stopping or continuing PC for the control of S. mansoni. RESULTS: We found that KK-based strategies perform reasonably well for determining when to stop PC at a local scale. Use of more sensitive diagnostics leads to a marginally improved health impact (person-years lived with heavy infection) and comes at a cost of continuing PC for longer (up to around 3 years), unless the decision threshold for stopping PC is adapted upward. However, if this threshold is set too high, PC may be stopped prematurely, resulting in a rebound of infection levels and disease burden (+45% person-years of heavy infection). CONCLUSIONS: We conclude that the potential value of more sensitive diagnostics lies more in the reduction of survey-related costs than in the direct health impact of improved parasite control.

Robust data integration from multiple external sources for generalized linear models with binary outcomes.

We aim to estimate parameters in a generalized linear model (GLM) for a binary outcome when, in addition to the raw data from the internal study, more than 1 external study provides summary information in the form of parameter estimates from fitting GLMs with varying subsets of the internal study covariates. We propose an adaptive penalization method that exploits the external summary information and gains efficiency for estimation, and that is both robust and computationally efficient. The robust property comes from exploiting the relationship between parameters of a GLM and parameters of a GLM with omitted covariates and from downweighting external summary information that is less compatible with the internal data through a penalization. The computational burden associated with searching for the optimal tuning parameter for the penalization is reduced by using adaptive weights and by using an information criterion when searching for the optimal tuning parameter. Simulation studies show that the proposed estimator is robust against various types of population distribution heterogeneity and also gains efficiency compared to direct maximum likelihood estimation. The method is applied to improve a logistic regression model that predicts high-grade prostate cancer making use of parameter estimates from 2 external models.

Simultaneous variable selection and estimation in semiparametric regression of mixed panel count data.

Mixed panel count data represent a common complex data structure in longitudinal survey studies. A major challenge in analyzing such data is variable selection and estimation while efficiently incorporating both the panel count and panel binary data components. Analyses in the medical literature have often ignored the panel binary component and treated it as missing with the unknown panel counts, while obviously such a simplification does not effectively utilize the original data information. In this research, we put forward a penalized likelihood variable selection and estimation procedure under the proportional mean model. A computationally efficient EM algorithm is developed that ensures sparse estimation for variable selection, and the resulting estimator is shown to have the desirable oracle property. Simulation studies assessed and confirmed the good finite-sample properties of the proposed method, and the method is applied to analyze a motivating dataset from the Health and Retirement Study.

Predicting the multivariate zero-inflated counts: A novel model averaging method under Pearson loss.

Excessive zeros in multivariate count data are often observed in scenarios of biomedicine and public health. To provide a better analysis on this type of data, we first develop a marginalized multivariate zero-inflated Poisson (MZIP) regression model to directly interpret the overall exposure effects on marginal means. Then, we define a multiple Pearson residual for our newly developed MZIP regression model by simultaneously taking heterogeneity and correlation into consideration. Furthermore, a new model averaging prediction method is introduced based on the multiple Pearson residual, and the asymptotical optimality of this model averaging prediction is proved. Simulations and two empirical applications in medicine are used to illustrate the effectiveness of the proposed method.

Conceptualization of the term "ecological validity" in neuropsychological research on executive function assessment: a systematic review and call to action.

OBJECTIVE: "Ecological validity" (EV) is classically defined as test's ability to predict real-world functioning, either alone or together with test's similarity to real-world tasks. In neuropsychological literature on assessment of executive functions (EF), EV is conceptualized inconsistently, leading to misconceptions about the utility of tests. The goal of this systematic review was to examine how EV is conceptualized in studies of EF tests described as ecologically valid. METHOD: MEDLINE and PsychINFO Databases were searched. PRISMA guidelines were observed. After applying inclusion and exclusion criteria, this search yielded 90 articles. Deductive content analysis was employed to determine how the term EV was used. RESULTS: About 1/3 of the studies conceptualized EV as the test's ability to predict functional outcomes, 1/3 as both the ability to predict functional outcome and similarity to real-world tasks, and 1/3 were either unclear about the meaning of the term or relied on notions unrelated to classical definitions (e.g., similarity to real-world tasks alone, association with other tests, or the ability to discriminate between populations). CONCLUSIONS: Conceptualizations of the term EV in literature on EF assessment vary grossly, subsuming the notions of criterion, construct, and face validity, as well as sensitivity/specificity. Such inconsistency makes it difficult to interpret clinical utility of tests that are described as ecologically valid. We call on the field to require that, at minimum, the term EV be clearly defined in all publications, or replaced with more concrete terminology (e.g., criterion validity).

Water rights trading planning and its application in water resources management: A water-ecology-food nexus perspective.

Nexus approach provides an effective perspective for implementing synergetic management of water resources. In this study, an interval two-stage chance-constrained water rights trading planning model under water-ecology-food nexus perspective (ITCWR-WEF) is proposed to analyze the interaction between water trading and water-ecology-food (WEF) nexus, which fills in the water resources management gaps from a novel nexus perspective. ITCWR-WEF incorporates hydrological simulation with soil and water assessment tool (SWAT), water rights configuration with interval two-stage chance-constrained programming (ITCP), and multi-criterion analysis with Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). The developed ITCWR-WEF is applied to a real case of Daguhe watershed, which has characteristics of water scarcity, food producing areas and fragile ecosystem. Initial water rights allocation is addressed before the trading. Mechanisms analysis is designed to reveal mutual effect of water rights trading and WEF nexus. Optimal water management scenario is identified through multi-criterion analysis. Results reveal that the mechanism of water rights trading with WEF nexus under low constraint-violation risk level of water availability and environment capacity is recommended to promote the rational water resources allocation to balance the economic goals, water environment and water supply security, as well as ecological and food water demand guarantees.

Premorbid body weight predicts weight loss in both anorexia nervosa and atypical anorexia nervosa: Further support for a single underlying disorder.

OBJECTIVE: For adolescents, DSM-5 differentiates anorexia nervosa (AN) and atypical AN with the 5th BMI-centile-for-age. We hypothesized that the diagnostic weight cut-off yields (i) lower weight loss in atypical AN and (ii) discrepant premorbid BMI distributions between the two disorders. Prior studies demonstrate that premorbid BMI predicts admission BMI and weight loss in patients with AN. We explore these relationships in atypical AN. METHOD: Based on admission BMI-centile < or ≥5th, participants included 411 female adolescent inpatients with AN and 49 with atypical AN from our registry study. Regression analysis and t-tests statistically addressed our hypotheses and exploratory correlation analyses compared interrelationships between weight loss, admission BMI, and premorbid BMI in both disorders. RESULTS: Weight loss in atypical AN was 5.6 kg lower than in AN upon adjustment for admission age, admission height, premorbid weight and duration of illness. Premorbid BMI-standard deviation scores differed by almost one between both disorders. Premorbid BMI and weight loss were strongly correlated in both AN and atypical AN. DISCUSSION: Whereas the weight cut-off induces discrepancies in premorbid weight and adjusted weight loss, AN and atypical AN overall share strong weight-specific interrelationships that merit etiological consideration. Epidemiological and genetic associations between AN and low body weight may reflect a skewed premorbid BMI distribution. In combination with prior findings for similar psychological and medical characteristics in AN and atypical AN, our findings support a homogenous illness conceptualization. We propose that diagnostic subcategorization based on premorbid BMI, rather than admission BMI, may improve clinical validity. PUBLIC SIGNIFICANCE: Because body weights of patients with AN must drop below the 5th BMI-centile per DSM-5, they will inherently require greater weight loss than their counterparts with atypical AN of the same sex, age, height and premorbid weight. Indeed, patients with atypical AN had a 5.6 kg lower weight loss after controlling for these variables. In comparison to the reference population, we found a lower and higher mean premorbid weight in patients with AN and atypical AN, respectively. Considering previous psychological and medical comparisons showing little differences between AN and atypical AN, we view a single disorder as the most parsimonious explanation. Etiological models need to particularly account for the strong relationship between weight loss and premorbid body weight.

The ownership memory self-reference effect shifts recognition criterion but not recognition sensitivity.

Information referenced to the self is retrieved more accurately than information referenced to others, known as the memory self-reference effect. It is unclear, however, whether social context (identity of the other) or task factors alter decision-making processes. In a virtual object allocation task, female participants sorted objects into their own or another's (stranger or mother) basket based on a colour cue. Subsequently, they performed a recognition memory task in which they first indicated whether each object was old or new, and then whether it had been allocated to themselves or to the other. We obtained owner-specific hit rates and false-alarm rates and applied signal detection theory to derive separate recognition sensitivity (d') and recognition criterion parameters (c) for self- and other-owned objects. While there was no clear evidence of a recognition self-reference effect, or a change in sensitivity, participants adopted a more conservative recognition criterion for self- compared with other-owned objects, and particularly when the other-referent was the participant's mother compared with the stranger. Moreover, when discriminating whether the originally presented objects were self- or other-owned, participants were biased toward ascribing ownership to the 'other'. We speculate that these findings reflect ownership-based changes in decisional processing during the recognition memory self-reference paradigm.

Assessing students with dyslexia and other reading difficulties through multiple diagnostic assessments.

This article aims to assist practitioners in understanding dyslexia and other reading difficulties and assessing students' learning needs. We describe the essential components of language and literacy, universal screening, diagnostic assessments, curriculum-based measurement and eligibility determination. We then introduce four diagnostic assessments as examples, including norm-referenced assessments (i.e. the Comprehensive Test of Phonological Processing second edition and the Woodcock-Johnson IV Tests of Achievement) and criterion-referenced assessments (i.e. the Gallistel-Ellis Test of Coding Skills and the Dynamic Indicators of Basic Early Literacy Skills). Finally, We use a makeup case as a concrete example to illustrate how multiple diagnostic assessments are recorded and how the results can be used to inform intervention and eligibility for special education services.

Signs of perceptual disorder during movement were reliably assessed in children with cerebral palsy in Sweden.

AIM: The aim of this Swedish study was to evaluate the assessment of clinical signs of perceptual disorder in children with cerebral palsy (CP). METHODS: Three experienced raters assessed 56 videos of 19 children from 1 to 18 years of age with bilateral spastic CP, which were recorded by colleagues at an Italian hospital. Six signs were evaluated for inter-rater reliability and criterion validity. Clinical applicability was evaluated by assessing inter-rater reliability between 47 Swedish clinicians, who examined 15 of the videos during face-to-face and online education seminars. There were 41 physiotherapists, two occupational therapists and four doctors, with 1-37 years of clinical experience and a median of 10 years. RESULTS: The experienced raters demonstrated moderate to almost perfect inter-rater reliability (kappa 0.54-0.81) and criterion validity (0.54-0.87) for startle reaction, upper limbs in startle position, averted eye gaze and eye blinking. The clinicians recognised these signs with at least moderate reliability (0.56-0.88). Grimacing and posture freezing were less reliable (0.22-0.35) and valid (0.09-0.50). CONCLUSION: Four of the six signs of perceptual disorder were reliably recognised by experienced raters and by clinicians after education seminars. Extended education and larger study samples are needed to recognise all the signs.

Likelihood comparisons in bounded outcome score analysis must be internally consistent.

Clinical trial endpoints are often bounded outcome scores (BOS), which are variables having restricted values within finite intervals. Common analysis approaches may treat the data as continuous, categorical, or a mixture of both. The appearance of BOS data being simultaneously continuous and categorical easily leads to confusions in pharmacometrics regarding the appropriate domain for model evaluation and the circumstances under which data likelihoods can be compared. This commentary aims to clarify these fundamental issues and facilitate appropriate pharmacometric analyses.

1H and 13C NMR spectra of infinitene and the ring current effect of the aromatic molecule.

The spatial magnetic properties (through-space NMR shieldings-TSNMRSs-actually the ring current effect in 1H NMR spectroscopy) of the recently synthesized infinitene (the helically twisted [12]circulene) have been calculated using the GIAO perturbation method employing the nucleus-independent chemical shift (NICS) concept and visualized as iso-chemical-shielding surfaces (ICSS) of various size and direction. Both 1H and 13C chemical shifts of infinitene and the aromaticity of this esthetically very appealing molecule have been studied subject to the ring current effect thus obtained. This spatial magnetic response property of TSNMRSs dominates the different magnitude of 1H and 13C chemical shifts, especially in the cross-over section of infinitene, which is unequivocally classified as an aromatic molecule based on the deshielding belt of its ring current effect. Differences in aromaticity of infinitene compared with isolated benzene can also be qualified and quantified on the magnetic criterion.

Novel program for automatic calculation of EPG variables.

The electrical penetration graph (EPG) technique is the most powerful tool for studying the feeding behavior of pierce-sucking insects. However, calculating EPG variables is often very time-consuming, and consequently, several software programs have been developed for the automatic calculation of EPG variables. Here we present a new user-friendly Excel Workbook that uses a standardized list of EPG variables and follows expert guidelines for calculating them. The program developed in Visual Basic for Applications (VBA) is a step up from the existing software and allows easy data analysis and interpretation. It also includes a novel option for dealing with the common problem of "truncated"-waveforms artificially terminated by the end of recording. The only requirement to run the program is Microsoft Excel software running under a PC environment. The Workbook was validated by calculating variables from EPG recordings of aphids and psyllids and the results obtained were compared with those of existing software such as the Sarria Workbook. Our EPG Workbook provides researchers with a reliable and standardized tool for the automatic calculation of up to 127 EPG variables from phloem-sap-sucking insects.

UAV Path Optimization for Angle-Only Self-Localization and Target Tracking Based on the Bayesian Fisher Information Matrix.

In this paper, new path optimization algorithms are developed for uncrewed aerial vehicle (UAV) self-localization and target tracking, exploiting beacon (landmark) bearings and angle-of-arrival (AOA) measurements from a manoeuvring target. To account for time-varying rotations in the local UAV coordinates with respect to the global Cartesian coordinate system, the unknown orientation angle of the UAV is also estimated jointly with its location from the beacon bearings. This is critically important, as orientation errors can significantly degrade the self-localization performance. The joint self-localization and target tracking problem is formulated as a Kalman filtering problem with an augmented state vector that includes all the unknown parameters and a measurement vector of beacon bearings and target AOA measurements. This formulation encompasses applications where Global Navigation Satellite System (GNSS)-based self-localization is not available or reliable, and only beacons or landmarks can be utilized for UAV self-localization. An optimal UAV path is determined from the optimization of the Bayesian Fisher information matrix by means of A- and D-optimality criteria. The performance of this approach at different measurement noise levels is investigated. A modified closed-form projection algorithm based on a previous work is also proposed to achieve optimal UAV paths. The performance of the developed UAV path optimization algorithms is demonstrated with extensive simulation examples.

Efficient Aperture Fill Time Correction for Wideband Sparse Array Using Improved Variable Fractional Delay Filters.

To solve the problem of aperture fill time (AFT) for wideband sparse arrays, variable fractional delay (VFD) FIR filters are applied to eliminate linear coupling between spatial and time domains. However, the large dimensions of the filter coefficient matrix result in high system complexity. To alleviate the computational burden of solving VFD filter coefficients, a novel multi-regultion minimax (MRMM) model utilizing the sparse representation technique has been presented. The error function is constrained by the introduction of L2-norm and L1-norm regularizations within the minimax criterion. The L2-norm effectively resolves the problems of overfitting and non-unique solutions that arise in the sparse optimization of traditional minimax (MM) models. Meanwhile, the use of multiple L1-norms enables the optimal design of the smallest sub-filter number and order of the VFD filter. To solve the established nonconvex model, an improved sequential-alternating direction method of multipliers (S-ADMM) algorithm for filter coefficients is proposed, which utilizes sequential alternation to iteratively update multiple soft-thresholding problems. The experimental results show that the optimized VFD filter reduces system complexity significantly and corrects AFT effectively in a wideband sparse array.

Metrology for Indoor Radon Measurements and Requirements for Different Types of Devices.

Indoor radon measurements have been conducted in many countries worldwide for several decades. However, to date, there is a lack of a globally harmonized measurement standard. Furthermore, measurement protocols in the US (short-term tests for 2-7 days) and European Union countries (long-term tests for at least 2 months) differ significantly, and their metrological support is underdeveloped, as clear mathematical algorithms (criteria) and QA/QC procedures considering fundamental ISO/IEC concepts such as "measurement uncertainty" and "conformity assessment" are still absent. In this context, for many years, the authors have been advancing and refining the theory of metrological support for standardizing indoor radon measurements based on a rational criterion for conformity assessment within the ISO/IEC concepts. The rational criterion takes into account the main uncertainties arising from temporal variations in indoor radon and instrumental errors, enabling the utilization of both short- and long-term measurements while ensuring specified reliability in decision making (typically no less than 95%). The paper presents improved mathematical algorithms for determining both temporal and instrumental uncertainties. Additionally, within the framework of the rational criterion, unified metrological requirements are formulated for various methods and devices employed in indoor radon measurements.