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Abstract Background Calcaneal osteomyelitis (CO) poses a formidable challenge in treatment due to the distinct anatomical structure and functional properties of the calcaneus. The present study endeavors to furnish a thorough and comprehensive understanding of the clinical manifestations, therapeutic strategies, and therapeutic outcomes pertaining to pediatric calcaneal osteomyelitis (PCO) by conducting a meticulous synthesis and analysis of cases reported in the literature. Methods A systematic search of the PubMed, Embase, and Cochrane Library databases was conducted to identify English-language studies analyzing PCO between 2000 and 2021. The quality of the included studies was assessed using the National Institutes of Health (NIH) assessment scale. Effective data were extracted and analyzed. Results A total of 42 studies, encompassing 128 patients, fulfilled the established inclusion criteria. The gender distribution revealed a male-to-female ratio of 2:1 (81 boys and 40 girls). The median age at the time of diagnosis was 8 years, while the median duration of symptoms was 0.6 month. Trauma emerged as the primary etiology (41 cases, 54%), and limited activity was the most prevalent symptom (68 cases). The positive rate for pathogen culture was 75.4% (49/65), with Staphylococcus aureus being the most commonly isolated pathogen (28 cases, 57.1%). Surgical intervention was performed in 51% (64/126) of the patients, with debridement serving as the primary surgical strategy. The rate of infection recurrence was 6.8% (8/118), and the risk of below-knee amputation was 0.8% (1/124). Conclusions PCO occurred more frequently in male patients, with trauma being the primary underlying cause and Staphylococcus aureus being the most prevalent bacterial pathogen isolated. Over half of the patients underwent surgical intervention. Nonetheless, it is imperative that treatment strategies undergo further refinement, as approximately 7% of patients experienced infection recurrence.

Background: Calcaneal osteomyelitis (CO) poses a formidable challenge in treatment due to the distinct anatomical structure and functional properties of the calcaneus. The present study endeavors to furnish a thorough and comprehensive understanding of the clinical manifestations, therapeutic strategies, and therapeutic outcomes pertaining to pediatric calcaneal osteomyelitis (PCO) by conducting a meticulous synthesis and analysis of cases reported in the literature. Methods: A systematic search of the PubMed, Embase, and Cochrane Library databases was conducted to identify English-language studies analyzing PCO between 2000 and 2021. The quality of the included studies was assessed using the National Institutes of Health (NIH) assessment scale. Effective data were extracted and analyzed. Results: A total of 42 studies, encompassing 128 patients, fulfilled the established inclusion criteria. The gender distribution revealed a male-to-female ratio of 2:1 (81 boys and 40 girls). The median age at the time of diagnosis was 8 years, while the median duration of symptoms was 0.6 month. Trauma emerged as the primary etiology (41 cases, 54%), and limited activity was the most prevalent symptom (68 cases). The positive rate for pathogen culture was 75.4% (49/65), with Staphylococcus aureus being the most commonly isolated pathogen (28 cases, 57.1%). Surgical intervention was performed in 51% (64/126) of the patients, with debridement serving as the primary surgical strategy. The rate of infection recurrence was 6.8% (8/118), and the risk of below-knee amputation was 0.8% (1/124). Conclusions: PCO occurred more frequently in male patients, with trauma being the primary underlying cause and Staphylococcus aureus being the most prevalent bacterial pathogen isolated. Over half of the patients underwent surgical intervention. Nonetheless, it is imperative that treatment strategies undergo further refinement, as approximately 7% of patients experienced infection recurrence. [ABSTRACT FROM AUTHOR]

Family resilience is an important issue in dealing with the Covid-19 pandemic in Indonesia, because of the negative impact not only on health aspects, but also on economic aspects that change family behavior. The purpose of this article is to present the available literature on the situation of family resilience at the family level that is required to face the new normal or adaptive process during the coronavirus outbreak. Qualitative research methods with synthetic analysis are used in this study. The data is sourced from 11 scientific articles collected through Google Scholar from 2020 to 2022. The results of the study show that the impact of the pandemic is unpredictable, posing a threat to family welfare. This is certainly a concern for family resilience that pays attention to: needs, complaints, comfort and alternative solutions, and the management of a family's expectations. [ABSTRACT FROM AUTHOR]

Background: Current information were still limited regarding clinical characteristics, diagnosis, and treatment efficacy of calcaneal osteomyelitis (CO). The present study summarized similarities and differences between diabetes-related CO (DRCO) and trauma-related CO (TRCO) based on synthesis analysis of literature-reported cases.Methods: We searched the PubMed, Embase, and Cochrane Library databases to find English studies reporting DRCO and TRCO published between January 2000 and December 2021. Effective data were extracted and synthesized for comparisons.Results: Altogether 108 studies with 278 DRCO and 403 TRCO patients were analyzed. The ratio of females among the DRCO patients was significantly higher than that of the TRCO patients (37.4% vs 24.3%, P < 0.001). The median age at diagnosis of the DRCO patients was statistically older than the TRCO patients (56 vs 44 years, P < 0.001). The median symptom duration of the DRCO patients was longer than the TRCO patients (4 vs 2 months, P = 0.136), with ulcer and sinus as the top symptoms for the DRCO and TRCO patients, respectively. The positive rate of pathogen culture for the DRCO patients was significantly higher than that for the TRCO patients (94.8% vs 69.5%, P < 0.001). The DRCO patients had higher risks of infection relapse (32.3% vs 16.3%, P < 0.001) and amputation (24.8% vs 1.4%, P < 0.001), and a higher all-cause mortality (4.9% vs 1.3%, P = 0.03) than the TRCO patients.Conclusion: DRCO and TRCO shared similar and different clinical features and diagnostic issues. However, compared with TRCO, the clinical efficacy and prognosis of DRCO were worse. [ABSTRACT FROM AUTHOR]

Based on our previous contributions about UAV target tracking and recognition, this paper continues to do the synthesis analysis for the ellipsoidal method for the above practical problem. Given a nonlinear system or linear system, corresponding to the motion equation for the considered target, the UAV target tracking and recognition is to identify the unknown but bounded noise, then ellipsoidal method is proposed to achieve this goal. The main step for ellipsoidal method is to compute one intersection operation between one ellipsoid and a strip. Through our own mathematical derivations, this intersection part is also an ellipsoid. The centre of the final ellipsoid is deemed as the accurate state estimation from the generated ellipsoidal sequences. To alleviate the deficiency of our previous contributions, synthesis analysis for ellipsoidal method is also derived to complete the efficiency. Finally, one simulation example confirms our ellipsoidal method for UAV target tracking and recognition. [ABSTRACT FROM AUTHOR]

Based on our previous contributions about UAV target tracking and recognition, this paper continues to do the synthesis analysis for the ellipsoidal method for the above practical problem. Given a nonlinear system or linear system, corresponding to the motion equation for the considered target, the UAV target tracking and recognition is to identify the unknown but bounded noise, then ellipsoidal method is proposed to achieve this goal. The main step for ellipsoidal method is to compute one intersection operation between one ellipsoid and a strip. Through our own mathematical derivations, this intersection part is also an ellipsoid. The centre of the final ellipsoid is deemed as the accurate state estimation from the generated ellipsoidal sequences. To alleviate the deficiency of our previous contributions, synthesis analysis for ellipsoidal method is also derived to complete the efficiency. Finally, one simulation example confirms our ellipsoidal method for UAV target tracking and recognition.

This new paper combines errors-in-variable (EIV) system with closed loop situation to consider a more complex closed loop EIV system. Consider the identification problem for closed loop EIV system, synthesis analysis is completed from the point of system identification field. Firstly, the reason about why closed loop EIV system is useful in academy and practice is explained in detail. Secondly, to identify that unknown plant, existing in closed loop EIV system with the measurement and process noise simultaneously, nonparametric estimate is proposed to be one plant estimate through our own mathematical derivation. Then statistical analysis above nonparametric estimate is studied to show the unbiased property. Thirdly, for the rational transfer function as the unknown plant, parameterized by one unknown parameter vector, the plant identification is transferred into one parameter estimate, so after reformulating the parameterized input-output relation for closed loop EIV system, least squares solution is derived to be biased. To avoid this explicit biased term, bias compensated estimate and an iterative least squares estimate are proposed to improve the overall identification performance. Finally, one practical example is to show the existence of our considered closed loop EIV system, and the detailed numerical results prove our proposed identification strategies.

This paper shows our new contributions on data driven model predictive control, such as persistent excitation, optimal state feedback controller, output predictor and stability. After reviewing the definition of persistent excitation and its important property, the idea of data driven is introduced in model predictive control to construct our considered data driven model predictive control, whose state information and output variable are generated by measured data online. Variation tool is applied to obtain the optimal controller or predictive controller through our own derivation. Furthermore, for the cost function in data driven model predictive control, its preliminary stability is analysed by using the linear matrix inequality and one single optimal state feedback controller is given. To bridge the gap between our derived results and other control strategies, output predictor is constructed from the point of data driven idea, i.e. using some collected input–output data from one experiment to establish the output predictor at any later time instant. Finally, one simulation example is given to prove the efficiency of our derived results.

Background and aims: Hyperaccumulator plants exhibit extreme ecophysiological characteristics, which make them suited for phytoremediation. Understanding their ecological strategies might help identify the species and functions to be favored in phytoremediation, restoration, and conservation projects for metalliferous sites. Methods: Here, we identified the hyperaccumulator species in the worldwide plant trait database TRY and cross-referenced these trait syndromes associated with the ability of plants to concentrate metals. This allows us to link trace element hyperaccumulation with broader plant ecological strategies. Results: Hyperaccumulator plant species tend to have smaller leaves and poorer competitive ability compared to non-hyperaccumulator plant species. Contrary to expectations, we found no indication of hyperaccumulator plants being more resource-conservative on the leaf economics spectrum. However, these data remain fragmentary as only 2.7% of hyperaccumulator plant species have their traits published in the TRY database. Conclusion: The recent development of trait-based models to construct plant communities providing optimal ecosystem services (e.g., phytoremediation, restoration) requires further research to identify predictable trait-service relationships. We thus call for an international collaborative sampling effort to measure traits in more hyperaccumulator plant species. [ABSTRACT FROM AUTHOR]

This paper shows our new contributions on data driven model predictive control, such as persistent excitation, optimal state feedback controller, output predictor and stability. After reviewing the definition of persistent excitation and its important property, the idea of data driven is introduced in model predictive control to construct our considered data driven model predictive control, whose state information and output variable are generated by measured data online. Variation tool is applied to obtain the optimal controller or predictive controller through our own derivation. Furthermore, for the cost function in data driven model predictive control, its preliminary stability is analysed by using the linear matrix inequality and one single optimal state feedback controller is given. To bridge the gap between our derived results and other control strategies, output predictor is constructed from the point of data driven idea, i.e. using some collected input–output data from one experiment to establish the output predictor at any later time instant. Finally, one simulation example is given to prove the efficiency of our derived results. [ABSTRACT FROM AUTHOR]

We present a direct data driven model reference control framework for flight simulation table from both the theoretical analysis and engineering application. Sate of the art direct driven model reference control designs the unknown controller based on the input-output data and guarantees the actual model converge to the reference model, under a case of no any priori knowledge for the unknown plant. We improve this direct data driven model reference control strategy by considering its stability validation and synthesis analysis for nonlinear controller. The resulting direct data driven model reference control scheme can be implemented to ensure flight simulation table rotate accuracy, resulting in improved performance index. As the main technical contribution, we show that the proposed direct data driven model reference control framework also ensures closed loop stability and suitable extension for nonlinear controller.

Based on our previous contributions about UAV target tracking and recognition, this paper continues to do the synthesis analysis for the ellipsoidal method for above practical problem. Given a nonlinear system or linear system, corresponding to the motion equation for the considered target, the UAV target tracking and recognition is to identify the unknown but bounded noise, then ellipsoidal method is proposed to achieve this goal. The main step for ellipsoidal method is to compute one intersection operation between one ellipsoid and a strip. Through our own mathematical derivations, this intersection part is also an ellipsoid. The center of the final ellipsoid is deemed as the accurate state estimation from the generated ellipsoidal sequences. To alleviate the deficiency of our previous contributions, synthesis analysis for ellipsoidal method is also derived to complete the efficiency. Finally, one simulation example confirms our ellipsoidal method for UAV target tracking and recognition.

Northeast China, the important grain‐producing region in China, is under threat from soil degradation because of long‐term conventional tillage (CT). The adoption of conservation tillage is anticipated to restore soil fertility, maintain crop yields and enhance sustainability. However, the integrated effects of conservation tillage practice on crop yields and soil organic carbon (SOC) remain unclear. In this meta‐analysis of peer‐reviewed studies conducted in the Northeast China region, we assess crop yields and SOC values under no‐till, ridge tillage and subsoiling tillage practices. The results indicate that in areas with mean annual temperatures (MAT) below 3°C, crop yields were significantly (p <.05) higher under ridge tillage (0.8%) and subsoiling tillage (13.1%) compared with CT, whereas yields reduced under no‐till (−3.7%). Ridge tillage generally had a similar effect on crop yield as no‐till, without the negative impact in colder regions. We also report that no‐till practice increased SOC concentrations by 24.1%, 43.9% and 17.4% in areas of higher temperature (MAT > 6°C), low mean annual precipitation (MAP) (<500 mm) and continuous cropping conditions, respectively. Ridge tillage and subsoiling tillage also had positive effects on SOC concentrations (to a lesser degree than no‐till), indicating that conservation tillage can enhance SOC in Northeast China. Overall, the implementation of different conservation tillage measures in Northeast China was found to enhance crop yields and sequester carbon. We recommend that ridge tillage is used in colder areas and that subsoiling tillage is used in rotation with other tillage measures to maintain crop yields. [ABSTRACT FROM AUTHOR]

Abstract Background Framingham Stroke Risk Score (FSRS) is the most well-regarded risk appraisal tools for evaluating an individual’s absolute risk on stroke onset. However, several widely accepted risk factors for stroke were not included in the original Framingham model. This study proposed a new model which combines an existing risk models with new risk factors using synthesis analysis, and applied it to the longitudinal Atherosclerosis Risk in Communities (ARIC) data set. Methods Risk factors in original prediction models and new risk factors in proposed model had been discussed. Three measures, like discrimination, calibration and reclassification, were used to evaluate the performance of the original Framingham model and new risk prediction model. Results Modified C-statistics, Hosmer-Lemeshow Test and classless NRI, class NRI were the statistical indices which, respectively, denoted the performance of discrimination, calibration and reclassification for evaluating the newly developed risk prediction model on stroke onset. It showed that the NEW-STROKE (new stroke risk score prediction model) model had higher modified C-statistics, smaller Hosmer-Lemeshow chi-square values after recalibration than original FSRS model, and the classless NRI and class NRI of the NEW-STROKE model over the original FSRS model were all significantly positive in overall group. Conclusion The NEW-STROKE integrated with seven literature-derived risk factors outperformed the original FSRS model in predicting the risk score of stroke. It illustrated that seven literature-derived risk factors contributed significantly to stroke risk prediction.

Global positioning system (GPS) detection technology has several advantageous characteristics (i.e., all-weather applications, high accuracy, high spatial and temporal resolution, and low cost), and GPS tracking and monitoring techniques for water vapor have developed rapidly in recent years. The GPS-precipitable water vapor (GPS-PWV), obtained through inversion using this technology can reflect the water vapor inflow and outflow in a vertical air column above a certain area in nearly real-time, which is especially important for areas of severe water vapor variation. In this paper, we studied the relationship between GPS-PWV variation and actual precipitation. The specific aim was to identify the underlying physical mechanisms driving the variation and to further strengthen the utility of GPS-PWV in forecasts and warnings of severe convection weather. We concluded that (1) rapid rise in the GPS-PWV in the long-term low-level data predicted the arrival of precipitation and was therefore useful in weather forecasts; (2) the GPS-PWV variation was closely related with the movement of the water vapor transfer belt; (3) the atmosphere showed an unstable energy structure before the GPS-PWV increase; and (4) local motion was strongly related with the development and maintenance of precipitation.

Abstract Disaster resilience has become an important societal goal which captures the attention of academics and decision makers from various disciplines and sectors. Developing tools or metrics for measuring and monitoring progress of resilience is a critical component that requires extensive research to achieve better understanding. However, different fields have different emphases and the knowledge gained from the various studies are scattered and fragmented. To provide an integration of the literature and reflect on the current state of resilience measurement, we conducted a synthesis analysis through a systematic review of 174 scholarly articles on disaster resilience measurement from 2005 to 2017. Using a review table designed for this study and content analysis, we extracted key information from each article on resilience definition, type of measurement method, resilience indicators used, and proposed adaptation strategies. Results indicate that 39.7% of the articles used qualitative methods for resilience measurement and 39.1% of the articles used quantitative methods. However, only 10.3% of all the 174 articles conducted empirical validation of their proposed resilience indices. The three most frequently suggested adaptation strategies were empowering local governments and leaders, raising community awareness, and enhancing community infrastructure and communication. These findings suggest that future research need to incorporate validation and inferential ability into resilience measurement. Extending from static resilience measurement to dynamic system modeling and bridging the disconnection between resilience scientific research and practical actions are also pressing needs. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to determine the influence of sex on choroidal thickness (CT) in healthy adults. Methods: Healthy Chinese adults were recruited and complete ophthalmic examinations were performed. The choroid was imaged by swept-source optical coherence tomography and the macular CT in Early Treatment Diabetic Retinopathy Study grids was obtained by the intrinsic automated segmentation software. CT in males and females was compared after controlling other factors. All of the published studies in PubMed were systemically tracked, and a syntheses analysis of the combined data of the present study and previous studies was performed to address this issue further. Results: A total of 104 healthy adults were included, of whom 38 (37%) were male and 66 (63%) were female. Older age and longer axial length (AL) each were significantly associated with thinner CT. After controlling for age and AL, the foveal CT and average macular CT were 25.5 μm (95% CI: 0.5-50.4 μm) and 22.1 μm (95% CI: 2.7-41.4 μm) thicker in men than in women, respectively. Significant differences in CT between males and females were also observed in inner and outer rings after controlling for age and AL (P < 0.05). After strict screening, 15 previously reported studies were determined to be eligible for inclusion. The combination of data collected from 2821 males and 3389 females provided further evidence that the choroid is thicker in males, with a pooled mean difference of 19.5 μm (95% CI: 11.4 to 27.6) for foveal CT and 14.7 μm (95% CI: 6.8 to 22.6) for average CT. Conclusion: Our study of Chinese subjects, along with the syntheses analysis, strengthens the evidence that CT is greater in males than in females, based on OCT measurements. This observation may be pertinent for the sex disparities in some clinical conditions related to CT. [ABSTRACT FROM AUTHOR]

In this study, the winter-summer-winter seasonal variation characteristics of the atmospheric temperature in northern East Asia (NEA) during the past 60 years are analyzed. The results revealed a type of new seasonal variation mechanism of temperature: winter-winter recurrence (WWR). This study initially discussed the formation mechanism of WWR from the angle of the relationship between the WWR and the atmospheric internal factors and external forcing. The main conclusions are summarized as follows: (1) The winter-summer-winter continuous variation of the AO anomaly index has consistent characteristics with the atmospheric variation of the WWR in the NEA, and their 60-year correlation coefficient reaches 0.43, passing the 95% significance level. It is indicated that the seasonal anomaly of the AO has a certain influence on the WWR; (2) Overall, the PDO maintains a negative phase in the negative WWR years, while it displays the opposite feature in the positive WWR years. The negative (positive) anomaly of PDO is favourable to the occurrence of sustainable low (high) temperatures in the NEA, and may be the important external driving factor for motivating the WWR in the NEA; (3) The binary regression, based on the PDO and AO indexes successfully reproduces the curve of TWWR-HG, which is significantly correlated with the WWR index TWWR, and can reproduce the time-height profile of the WWR characteristics from 400 to 1,000 hPa. Therefore, it is concluded that the WWR of the atmospheric temperatures in the NEA is the result of the combined action of the PDO and AO. [ABSTRACT FROM AUTHOR]

The low of synthesis analysis capabilities of students in resolving a problem or physical symptoms due to the lack of application of the method of problem-solving, so it caused low student learning outcomes. Therefore, conducted research that aims at improving the synthesis of analysis capabilities of students. Special purpose research to describe: (1) lesson plan implementation (2) procedural skill (3) learning outcomes (4) students response. The kind of research using classroom action research with Hopkins model that consisting of three cycles, each cycle includes plan, action/observation, and reflective. Data obtained through a test, observation, questionnaires, and documentation. The data were analyzed by descriptive qualitative and quantitative. Research findings: (1) lesson plan implementation in good categories (2) procedural skills students indicated synthesis analysis capabilities of students was increased (3) the students learning outcomes, that at present the percentage of classical exhaustiveness in cycles I 11,43% (not exhaustive), in cycles II 88,57% (exhaustive), in cycles III 94,29% (exhaustive) (4) the response of students to the problem solving methods through direct instruction in good categories.

Forest ecosystems sequester large amounts of atmospheric CO 2 , and the contribution from forests in Asia is not negligible. Previous syntheses of carbon fluxes in Asian ecosystems mainly employed estimates of eddy covariance measurements, net ecosystem production (NEP), gross primary production (GPP), and ecosystem respiration (RE); however, to understand the variability within carbon cycles, fluxes such as autotropic respiration (AR), net primary production (NPP), litterfall, heterotrophic respiration (HR), and soil respiration (SR) need to be analyzed comprehensively in conjunction with NEP, GPP, and RE. Here we investigated the spatial variability of component fluxes of carbon balance (GPP, AR, NPP, litterfall, HR, SR, and RE) in relation to climate factors, between carbon fluxes, and to NEP using observations compiled from the literature for 22 forest sites in monsoon Asia. We found that mean annual temperature (MAT) largely relates to the spatial variability of component fluxes in monsoon Asian forests, with stronger positive effect in the mid–high latitude forests than in the low latitude forests, but even stronger relationships were identified between component fluxes regardless of regions. This finding suggests that the spatial variability of carbon fluxes in monsoon Asia is certainly influenced by climatic factors such as MAT, but that the overall spatial variability of AR, NPP, litterfall, HR, SR, and RE is rather controlled by that of productivity (i.e., GPP). Furthermore, component fluxes of the mid–high and low latitude forests showed positive and negative relationships, respectively, with NEP. Further investigation identified a common spatial variability in NEP and annual aboveground biomass changes with respect to GPP. The relationship between GPP and NEP in the mid–high latitudes implies that productivity and net carbon sequestration increase simultaneously in boreal and temperate forests. Meanwhile, the relationship between GPP and NEP in the low latitudes indicates that net carbon sequestration decreases with productivity, potentially due to the regional contrast in nitrogen depositions and stand age within sub-tropical and tropical forests; however, it requires further data syntheses or modelling investigations for confirmation of its general validity. These unique features of monsoon Asian forest carbon fluxes provide useful information for improving ecosystem model simulations, which still differ in their predictability of carbon flux variability. [ABSTRACT FROM AUTHOR]

In this study, the effect of changes in operating conditions is considered following a three–step procedure. Firstly, the process is simulated based on the design data for model validation and model–based optimization. The presented best-fitted kinetic and thermodynamic models in the literatures are utilized to analyze the trends and kinetic features related to methanol synthesis. The variations in the operating conditions such as the inlet temperature and the mole fractions of CO and CO 2 significantly affect the methanol production rate. Low operating performance of the heat exchangers and the alterations in operating conditions contribute to increase of the amount of purge gas of the process from its predicted quantity in the design condition. Since it has been anticipated that the purge gas may rise, a no–flow flare (zero flaring) has been designed and the excess of purge gas is burnt in this flare. Secondly, the process is simulated based on the operating data to calculate the streams conditions. Thirdly, the analysis and statistical optimization are performed. Applying response surface methodology (RSM), the operating conditions of this plant are optimized via simulator–based experimental design in order to maximize methanol production. RSM is a collection of mathematical and statistical techniques useful for modeling and analysis of problems in which a response of interest is influenced by several variables and the objective is to optimize this response. Consequently, the results of the statistical analysis prove that the methanol production rate increases by 7% applying the optimal operating conditions. [ABSTRACT FROM AUTHOR]

Synthesis analysis refers to a statistical method that integrates multiple univariate regression models and the correlation between each pair of predictors into a single multivariate regression model. The practical application of such a method could be developing a multivariate disease prediction model where a dataset containing the disease outcome and every predictor of interest is not available. In this study, we propose a new version of synthesis analysis that is specific to binary outcomes. We show that our proposed method possesses desirable statistical properties. We also conduct a simulation study to assess the robustness of the proposed method and compare it to a competing method. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

• New synthesis-analysis offers insights on trends in wheat N utilization efficiency. • A nonlinear model explained wheat grain yield as a function of N uptake (i.e. NUtE). • There are greater opportunities to increase NUtE in fall- than winter-sown wheat. • Increases in NUtE originated from dilution of grain protein concentration. • Identifying the determinants of NUtE will increase yield limited by N uptake. Understanding factors underpinning the variability in nitrogen (N) utilization efficiency (NUtE) [i.e. grain yield per unit of N uptake at maturity (Nup MAT)] is critical to direct future improvements in breeding and agronomic management. To our knowledge, no study has summarized changes in wheat NUtE across a wide range of experimental conditions. We performed a synthesis-analysis using published data to provide a global perspective of NUtE trends in wheat by (i) benchmarking against yield limited by Nup MAT , and (ii) assessing factors contributing to the variation in NUtE. The final database encompassed 55 studies (n = 529). A nonlinear model explained yield as a function of Nup MAT. The gap between actual yield and Nup MAT -limited yield was negligible at the lowest range of Nup MAT and increased to ∼2000 kg ha−1 as Nup MAT levels increased. Hence, opportunities to enhance yield through improving NUtE would be more likely at greater-than-average yield and Nup MAT levels. The negative correlation between grain protein concentration and the residuals between NUtE and Nup MAT indicated a challenge to increase yield without penalizing grain protein. Further, there are greater opportunities to increase NUtE in fall- than winter-sown wheat. Identifying the determinants of NUtE will enable to narrow the gap between actual and Nup MAT -limited yields. [ABSTRACT FROM AUTHOR]