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Intensification of agricultural practices has been pivotal in meeting the nutritional demands of a burgeoning global population. However, the widespread application of nitrogen (N) fertilisers has contributed to environmental pollution. In this study, we quantitatively assessed the role of international crop trade in optimising the productivity of micro-nutrients and its implications for N fertiliser use. Using a comprehensive dataset spanning from 1961 to 2019, we analysed the trade flows of seven key micro-nutrients-vitamin C (VC), vitamin B3 (VB3), vitamin B6 (VB6), calcium (Ca), magnesium (Mg), iron (Fe), and zinc (Zn)-embedded in agricultural products. We developed a novel framework to evaluate trade optimality and functionality based on the concentration-weighted productivity of micro-nutrients per kilogram of N fertiliser. Our findings reveal that while international trade has generally contributed to enhancing micro-nutrient productivity per unit of N fertiliser, trade optimality has shown a decreasing trend. High-productivity countries tend to export less relative to their potential, whereas countries with lower productivity import a larger share of crops. This decoupling suggests the need to re-evaluate trade policies to ensure that they align with sustainable agricultural practices and environmental conservation goals. We also identified potential savings in N fertiliser use through optimised trade practices, with estimated savings of 15-45 Tg of N per year. This could mitigate the negative agricultural impact and demonstrates the significant role that trade can play in achieving global sustainability targets. Overall, our research underscores the importance of aligning international crop trade with sustainable N management strategies to enhance micro-nutrient availability, improve environmental outcomes, and contribute to global efforts in achieving the Sustainable Development Goals.

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Translation elongation inhibitors are commonly used to study different cellular processes. Yet, their specific impact on transcription and mRNA decay has not been thoroughly assessed. Here we use TimeLapse sequencing to investigate how translational stress impacts mRNA dynamics in human cells. Our results reveal that a distinct group of transcripts is stabilized in response to the translation elongation inhibitor emetine. These stabilized mRNAs are short-lived at steady state and many of them encode C2H2 zinc finger proteins. The codon usage of these stabilized transcripts is suboptimal compared to other expressed transcripts, including other short-lived mRNAs that are not stabilized after emetine treatment. Finally, we show that stabilization of these transcripts is independent of ribosome quality control factors and signaling pathways activated by ribosome collisions. Our data describe a group of short-lived transcripts whose degradation is particularly sensitive to the inhibition of translation elongation.

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Motivated by applications in text mining and discrete distribution inference, we test for equality of probability mass functions of K groups of high-dimensional multinomial distributions. Special cases of this problem include global testing for topic models, two-sample testing in authorship attribution, and closeness testing for discrete distributions. A test statistic, which is shown to have an asymptotic standard normal distribution under the null hypothesis, is proposed. This parameter-free limiting null distribution holds true without requiring identical multinomial parameters within each group or equal group sizes. The optimal detection boundary for this testing problem is established, and the proposed test is shown to achieve this optimal detection boundary across the entire parameter space of interest. The proposed method is demonstrated in simulation studies and applied to analyse two real-world datasets to examine, respectively, variation among customer reviews of Amazon movies and the diversity of statistical paper abstracts.

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Background: Globally, there is a significant gap in detailed neurodevelopmental data for infants under 3 months, despite 6 weeks being identified a critical milestone for neuro-behavioural development. Normative values and optimal scores for healthy infants at 6 and 10 weeks postnatally are lacking in many settings. In South Africa, the statutory neurodevelopmental assessments at these ages exclude notable characteristics of central nervous system maturation and limit opportunities to collect data of early developmental progress. Objectives: Our study aimed to assess developmental characteristics of healthy term infants aged 6 and 10 weeks using the Hammersmith Neonatal Neurological Examination (HNNE). Method: A prospective longitudinal study was performed on 35 healthy term-born infants from low-risk pregnancies at 6 and 10 weeks' postnatal age in the Tshwane district. The statuses of infants' neurodevelopment in six domains were recorded using the HNNE. Optimality scores were derived from the raw scores of 34 items, using the 10th and 5th percentiles as cut-off points. Results: Evidences of neurodevelopmental advancements, particularly in posture, muscle tone and visual behaviour between 6 and 10 weeks were illustrated, and total examination optimality scores of 29.5 in 91% and 31.5 in 94% of infants were recorded at 6 and 10 weeks, respectively. Conclusion: This article provides data on the neurodevelopment characteristics of infants at and between 6- and 10-weeks post term ages. Clinical Implications: The findings support the viewpoint to identify important milestone characteristics during early screening.

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In this paper sharp lower error bounds for numerical methods for jump-diffusion stochastic differential equations (SDEs) with discontinuous drift are proven. The approximation of jump-diffusion SDEs with non-adaptive as well as jump-adapted approximation schemes is studied and lower error bounds of order 3/4 for both classes of approximation schemes are provided. This yields optimality of the transformation-based jump-adapted quasi-Milstein scheme.

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Subsampling is a practical strategy for analyzing vast survival data, which are progressively encountered across diverse research domains. While the optimal subsampling method has been applied to inferences for Cox models and parametric accelerated failure time (AFT) models, its application to semi-parametric AFT models with rank-based estimation have received limited attention. The challenges arise from the non-smooth estimating function for regression coefficients and the seemingly zero contribution from censored observations in estimating functions in the commonly seen form. To address these challenges, we develop optimal subsampling probabilities for both event and censored observations by expressing the estimating functions through a well-defined stochastic process. Meanwhile, we apply an induced smoothing procedure to the non-smooth estimating functions. As the optimal subsampling probabilities depend on the unknown regression coefficients, we employ a two-step procedure to obtain a feasible estimation method. An additional benefit of the method is its ability to resolve the issue of underestimation of the variance when the subsample size approaches the full sample size. We validate the performance of our estimators through a simulation study and apply the methods to analyze the survival time of lymphoma patients in the surveillance, epidemiology, and end results program.

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Extant crocodilian jaws are subject to functional demands induced by feeding and hydrodynamics. However, the morphological and ecological diversity of extinct crocodile-line archosaurs is far greater than that of living crocodilians, featuring repeated convergence towards disparate ecologies including armoured herbivores, terrestrial macropredators and fully marine forms. Crocodile-line archosaurs, therefore, present a fascinating case study for morphological and functional divergence and convergence within a clade across a wide range of ecological scenarios. Here, we build performance landscapes of two-dimensional theoretical jaw shapes to investigate the influence of strength, speed and hydrodynamics in the morphological evolution of crocodile-line archosaur jaws, and test whether ecologically convergent lineages evolved similarly optimal jaw function. Most of the 243 sampled jaw morphologies occupy optimized regions of theoretical morphospace for either rotational efficiency, resistance to Von Mises stress, hydrodynamic efficiency or a trade-off between multiple functions, though some seemingly viable shapes remain unrealized. Jaw speed is optimized only in a narrow region of morphospace whereas many shapes possess optimal jaw strength, which may act as a minimum boundary rather than a strong driver for most taxa. This study highlights the usefulness of theoretical morphology in assessing functional optimality, and for investigating form-function relationships in diverse clades.

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BACKGROUND: High birth weight (HBW) describes fetal birth weight of more than 4000 g. Infants with HBW have a high risk of developing neurological and developmental problems. Until recently, there were no studies in the literature that investigated the quality of spontaneous movements and the integrity of the developing nervous system in infants with HBW. The aims of this study were (1) to describe age-specific detailed early spontaneous movements in infants with HBW and (2) to compare the detailed early spontaneous movements of infants with HBW and normal birth weight (NBW). METHODS: Twenty-two infants with HBW (median birth weight = 4190 g) and 22 infants with NBW (median birth weight = 3255 g) were included at 10 to 19 weeks post-term age (median = 13 weeks). All infants were assessed according to General Movement Assessment using three- to five-minute video recordings. Video recordings of each infant were evaluated using Motor Optimality Score for three- to five-month-old infants-Revised score sheet. RESULTS: Motor Optimality Score-Revised (MOS-R) (P < 0.001), observed postural patterns (P < 0.001), and age-adequate movement repertoire (P = 0.005) were significantly lower in the infants with HBW. Infants with HBW had more aberrant (abnormal or absent) fidgety movements (18%) than those with NBW (0%). CONCLUSIONS: The results of this study demonstrated that the motor repertoire of infants with HBW tended to decrease more than that of those with NBW. To enable the follow-up of progression as a result of these assessments infants in need should be referred to age-adequate early intervention programs.

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The grey wolf optimizer is a widely used parametric optimization algorithm. It is affected by the structure and rank of grey wolves and is prone to falling into the local optimum. In this study, we propose a grey wolf optimizer for fusion cell-like P systems. Cell-like P systems can parallelize computation and communicate from cell membrane to cell membrane, which can help the grey wolf optimizer jump out of the local optimum. Design new convergence factors and use different convergence factors in other cell membranes to balance the overall exploration and utilization capabilities of the algorithm. At the same time, dynamic weights are introduced to accelerate the convergence speed of the algorithm. Experiments are performed on 24 test functions to verify their global optimization performance. Meanwhile, a support vector machine model optimized by the grey wolf optimizer for fusion cell-like P systems has been developed and tested on six benchmark datasets. Finally, the optimizing ability of grey wolf optimizer for fusion cell-like P systems on constrained optimization problems is verified on three real engineering design problems. Compared with other algorithms, grey wolf optimizer for fusion cell-like P systems obtains higher accuracy and faster convergence speed on the test function, and at the same time, it can find a better parameter set stably for the optimization of support vector machine parameters, in addition to being more competitive on constrained engineering design problems. The results show that grey wolf optimizer for fusion cell-like P systems improves the searching ability of the population, has a better ability to jump out of the local optimum, has a faster convergence speed, and has better stability.

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Future changes in climate, together with rising atmospheric CO 2 ${\text{CO}}_{2}$ , may reorganise the functional composition of ecosystems. Without long-term historical data, predicting how traits will respond to environmental conditions-in particular, water availability-remains a challenge. While eco-evolutionary optimality theory (EEO) can provide insight into how plants adapt to their environment, EEO approaches to date have been formulated on the assumption that plants maximise carbon gain, which omits the important role of tissue construction and size in determining growth rates and fitness. Here, we show how an expanded optimisation framework, focussed on individual growth rate, enables us to explain shifts in four key traits: leaf mass per area, sapwood area to leaf area ratio (Huber value), wood density and sapwood-specific conductivity in response to soil moisture, atmospheric aridity, CO 2 ${\text{CO}}_{2}$ and light availability. In particular, we predict that as conditions become increasingly dry, height-growth optimising traits shift from resource-acquisitive strategies to resource-conservative strategies, consistent with empirical responses across current environmental gradients of rainfall. These findings can explain both the shift in traits and turnover of species along existing environmental gradients and changing future conditions and highlight the importance of both carbon assimilation and tissue construction in shaping the functional composition of vegetation across climates.

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Codon optimality refers to the effect that codon composition has on messenger RNA (mRNA) stability and translation level and implies that synonymous codons are not silent from a regulatory point of view. Here, we investigated the adaptation of virus genomes to the host optimality code using mosquito-borne dengue virus (DENV) as a model. We demonstrated that codon optimality exists in mosquito cells and showed that DENV preferentially uses nonoptimal (destabilizing) codons and avoids codons that are defined as optimal (stabilizing) in either human or mosquito cells. Human genes enriched in the codons preferentially and frequently used by DENV are upregulated during infection, and so is the tRNA decoding the nonoptimal and DENV preferentially used codon for arginine. We found that adaptation during single-host passaging in human or mosquito cells results in the selection of synonymous mutations towards DENV's preferred nonoptimal codons that increase virus fitness. Finally, our analyses revealed that hundreds of viruses preferentially use nonoptimal codons, with those infecting a single host displaying an even stronger bias, suggesting that host-pathogen interaction shapes virus-synonymous codon choice.

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We consider the problem of optimal model averaging for partially linear models when the responses are missing at random and some covariates are measured with error. A novel weight choice criterion based on the Mallows-type criterion is proposed for the weight vector to be used in the model averaging. The resulting model averaging estimator for the partially linear models is shown to be asymptotically optimal under some regularity conditions in terms of achieving the smallest possible squared loss. In addition, the existence of a local minimizing weight vector and its convergence rate to the risk-based optimal weight vector are established. Simulation studies suggest that the proposed model averaging method generally outperforms existing methods. As an illustration, the proposed method is applied to analyze an HIV-CD4 dataset.

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Co-occurring plants show wide variation in their hydraulic and photosynthetic traits. Here, we extended 'least-cost' optimality theory to derive predictions for how variation in key hydraulic traits potentially affects the cost of acquiring and using water in photosynthesis and how this, in turn, should drive variation in photosynthetic traits. We tested these ideas across 18 woody species at a temperate woodland in eastern Australia, focusing on hydraulic traits representing different aspects of plant water balance, that is storage (sapwood capacitance, CS), demand vs supply (branch leaf : sapwood area ratio, AL : AS and leaf : sapwood mass ratio and ML : MS), access to soil water (proxied by predawn leaf water potential, ΨPD) and physical strength (sapwood density, WD). Species with higher AL : AS had higher ratio of leaf-internal to ambient CO2 concentration during photosynthesis (ci : ca), a trait central to the least-cost theory framework. CS and the daily operating range of tissue water potential (∆Ψ) had an interactive effect on ci : ca. CS, WD and ΨPD were significantly correlated with each other. These results, along with those from multivariate analyses, underscored the pivotal role leaf : sapwood allocation (AL : AS), and water storage (CS) play in coordination between plant hydraulic and photosynthetic systems. This study uniquely explored the role of hydraulic traits in predicting species-specific photosynthetic variation based on optimality theory and highlights important mechanistic links within the plant carbon-water balance.

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Speeds that minimize energetic cost during steady-state walking have been observed during lab-based investigations of walking biomechanics and energetics. However, in real-world scenarios, humans walk in a variety of contexts that can elicit different walking strategies, and may not always prioritize minimizing energetic cost. To investigate whether individuals tend to select energetically optimal speeds in real-world situations and how contextual factors influence gait, we conducted a study combining data from lab and real-world experiments. Walking kinematics and context were measured during daily life over a week (N=17) using wearable sensors and a mobile phone. To determine context, we utilized self-reported activity logs, GPS data and follow-up exit interviews. Additionally, we estimated energetic cost using respirometry over a range of gait speeds in the lab. Gross and net cost of transport were calculated for each participant, and were used to identify energetically optimal walking speed ranges for each participant. The proportion of real-world steady-state stride speeds within these ranges (gross and net) were identified for all data and for each context. We found that energetically optimal speeds predicted by gross cost of transport were more predictive of walking speeds used during daily life than speeds that would minimize net cost of transport. On average, 82.2% of all steady-state stride speeds were energetically optimal for gross cost of transport for all contexts and participants, while only 45.6% were energetically optimal for net cost of transport. These results suggest that while energetic cost is a factor considered by humans when selecting gait speed in daily life, it is not the sole determining factor. Context contributes to the observed variability in movement parameters both within and between individuals.

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Accurate estimation of photosynthesis is crucial for ecosystem carbon cycle modelling. Previous studies have established an empirical relationship between photosynthetic capacity (maximum carboxylation rate, Vcmax; maximum electron transport rate, Jmax) and leaf chlorophyll (Chl) content to infer global photosynthetic capacity. However, the basis for the Chl-Vcmax relationship remains unclear, which is further evidenced by the temporal variations in the Chl-Vcmax relationship. Using multiple years of observations of four deciduous tree species, we found that Vcmax and Jmax acclimate to photosynthetically active radiation faster (4-8 weeks) than Chl (10-12 weeks). This mismatch in temporal scales causes seasonality in the Vcmax-Chl relationship. To account for the mismatch, we used a Chl fluorescence parameter (quantum yield of Photosystem II, Φ(II)) to tighten the relationship and found Φ(II) × Chl correlated with Vcmax and Jmax (r2 = 0.74 and 0.72 respectively) better than only Chl (r2 = 0.7 and 0.6 respectively). It indicates that Φ(II) accounts for the short-term adjustment of leaf photosynthetic capacity to light, which was not captured by Chl. Our study advances our understanding of the ecophysiological basis for the empirical Vcmax-Chl relationship and how to better infer Vcmax from Chl and fluorescence, which guides large-scale photosynthesis simulations using remote sensing.

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OBJECTIVE: Aiming at the shortcomings of artificial surgical path planning for the thermal ablation of liver tumors, such as the time-consuming and labor-consuming process, and relying heavily on doctors' puncture experience, an automatic path-planning system for thermal ablation of liver tumors based on CT images is designed and implemented. METHODS: The system mainly includes three modules: image segmentation and three-dimensional reconstruction, automatic surgical path planning, and image information management. Through organ segmentation and three- dimensional reconstruction based on CT images, the personalized abdominal spatial anatomical structure of patients is obtained, which is convenient for surgical path planning. The weighted summation method based on clinical constraints and the concept of Pareto optimality are used to solve the multi-objective optimization problem, screen the optimal needle entry path, and realize the automatic planning of the thermal ablation path. The image information database was established to store the information related to the surgical path. RESULTS: In the discussion with clinicians, more than 78% of the paths generated by the planning system were considered to be effective, and the efficiency of system path planning is higher than doctors' planning efficiency. CONCLUSION: After improvement, the system can be used for the planning of the thermal ablation path of a liver tumor and has certain clinical application value.

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OBJECTIVE: To describe fidgety movements and co-occurring movements and postures in infants with myelomeningocele (MMC) and their association with mobility at preschool ages. METHODS: A retrospective cohort with early assessment via general movement assessment, followed by mobility assessment between 36 and 70 months of age. RESULTS: Twelve infants were included; 12 of 12 had fidgety movements in the upper limbs, with seven exhibiting them also in the hips and three in both the hips and ankles. The presence of fidgety movements in the lower limbs, kicking, a non-flat posture, a non-monotonous movement character, and a non-absent age-adequate movement repertoire were independently associated with mobility using the Hoffer modified classification and functional mobility scale (FMS) at 5 and 50 m. An optimality score was calculated based on leg movements and postures, ranging from 0 to 10 points. Infants who scored at least 4 points achieved household ambulation and FMS (5 m) of at least level 4. Community ambulation and an FMS (50 m) of level 5 were achieved with a score of at least 7.5. CONCLUSIONS: Assessing fidgety movements with other leg movements and postures in infants with MMC provided relevant information that could potentially predict mobility at preschool age and thus could be used for early intervention planning.

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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.

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BACKGROUND: Prechtl's General Movement Assessment (GMA) at fidgety age (3-5 months) is a widely used tool for early detection of cerebral palsy. Further to GMA classification, detailed assessment of movement patterns at fidgety age is conducted with the Motor Optimality Score-Revised (MOS-R). Inter-rater reliability and agreement are properties that inform test application and interpretation in clinical and research settings. This study aims to establish the inter-rater reliability and agreement of the GMA classification and MOS-R in a large population-based sample. METHODS: A cross-sectional study of 773 infants from birth-cohort in Perth, Western Australia. GMA was conducted on home-recorded videos collected between 12 + 0 and 16 + 6 weeks post term age. Videos were independently scored by two masked experienced assessors. Inter-rater reliability and agreement were assessed using intraclass correlation coefficient and limits of agreement respectively for continuous variables, and Cohen's Kappa and Gwet's Agreement Coefficient, and percentage agreement respectively for discrete variables. RESULTS: The classification of GMA showed almost perfect reliability (AC1 = 0.999) and agreement (99.9 %). Total MOS-R scores showed good-excellent reliability (ICC 0.857, 95 % CI 0.838-0.876) and clinically acceptable agreement (95 % limits of agreement of ±2.5 points). Substantial to almost perfect reliability and agreement were found for all MOS-R domain subscores. While MOS-R domains with higher redundancy in their categorisation have higher reliability and agreement, inter-rater reliability and agreement are substantial to almost perfect at the item level and are consistent across domains. CONCLUSION: GMA at fidgety age shows clinically acceptable inter-rater reliability and agreement for GMA classification and MOS-R for population-based cohorts assessed by experienced assessors.

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The principle of efficient coding posits that sensory cortical networks are designed to encode maximal sensory information with minimal metabolic cost. Despite the major influence of efficient coding in neuroscience, it has remained unclear whether fundamental empirical properties of neural network activity can be explained solely based on this normative principle. Here, we rigorously derive the structural, coding, biophysical and dynamical properties of excitatory-inhibitory recurrent networks of spiking neurons that emerge directly from imposing that the network minimizes an instantaneous loss function and a time-averaged performance measure enacting efficient coding. The optimal network has biologically-plausible biophysical features, including realistic integrate-and-fire spiking dynamics, spike-triggered adaptation, and a non-stimulus-specific excitatory external input regulating metabolic cost. The efficient network has excitatory-inhibitory recurrent connectivity between neurons with similar stimulus tuning implementing feature-specific competition, similar to that recently found in visual cortex. Networks with unstructured connectivity cannot reach comparable levels of coding efficiency. The optimal biophysical parameters include 4 to 1 ratio of excitatory vs inhibitory neurons and 3 to 1 ratio of mean inhibitory-to-inhibitory vs. excitatory-to-inhibitory connectivity that closely match those of cortical sensory networks. The efficient network has biologically-plausible spiking dynamics, with a tight instantaneous E-I balance that makes them capable to achieve efficient coding of external stimuli varying over multiple time scales. Together, these results explain how efficient coding may be implemented in cortical networks and suggests that key properties of biological neural networks may be accounted for by efficient coding.