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Experiments were conducted to investigate the shear behaviour of large deep beams subjected to uniform load. Six tests were performed on specimens with identical cross sections and reinforcing, but under different loading configurations. Variables included: span, degree of cracking prior to loading, proximity to a disturbed region near a reaction, and type of flexural stress on the loaded face. The findings indicate a specific set of variables resulting in unconservative predictions made using a strut-and-tie model for simply-supported beams subjected to uniform load, confirming and validating recent results by other researchers. A fanning strut model is proposed and is shown to provide more conservative results. The emerging trend of high capacity in continuous uniformly-loaded specimens is supported by the experimental results, as is the high capacity of specimens uniformly-loaded on their flexural tension face. Further, the high strength of specimens with suboptimal crack orientations supports recent experimental work.

Aims/hypothesisSmall cohort studies raise the hypothesis that corneal nerve abnormalities (including corneal nerve fibre length [CNFL]) are valid non-invasive imaging endpoints for diabetic sensorimotor polyneuropathy (DSP). We aimed to establish concurrent validity and diagnostic thresholds in a large cohort of participants with and without DSP.MethodsNine hundred and ninety-eight participants from five centres (516 with type 1 diabetes and 482 with type 2 diabetes) underwent CNFL quantification and clinical and electrophysiological examination. AUC and diagnostic thresholds were derived and validated in randomly selected samples using receiver operating characteristic analysis. Sensitivity analyses included latent class models to address the issue of imperfect reference standard.ResultsType 1 and type 2 diabetes subcohorts had mean age of 42 ± 19 and 62 ± 10 years, diabetes duration 21 ± 15 and 12 ± 9 years and DSP prevalence of 31% and 53%, respectively. Derivation AUC for CNFL was 0.77 in type 1 diabetes (p < 0.001) and 0.68 in type 2 diabetes (p < 0.001) and was approximately reproduced in validation sets. The optimal threshold for automated CNFL was 12.5 mm/mm2 in type 1 diabetes and 12.3 mm/mm2 in type 2 diabetes. In the total cohort, a lower threshold value below 8.6 mm/mm2 to rule in DSP and an upper value of 15.3 mm/mm2 to rule out DSP were associated with 88% specificity and 88% sensitivity.Conclusions/interpretationWe established the diagnostic validity and common diagnostic thresholds for CNFL in type 1 and type 2 diabetes. Further research must determine to what extent CNFL can be deployed in clinical practice and in clinical trials assessing the efficacy of disease-modifying therapies for DSP.

Accurately predicting the lifetime of complex, nonlinear systems such as lithium-ion batteries is critical for accelerating technology development. However, diverse aging mechanisms, significant device variability and dynamic operating conditions have remained major challenges. We generate a comprehensive dataset consisting of 124 commercial lithium iron phosphate/graphite cells cycled under fast-charging conditions, with widely varying cycle lives ranging from 150 to 2,300 cycles. Using discharge voltage curves from early cycles yet to exhibit capacity degradation, we apply machine-learning tools to both predict and classify cells by cycle life. Our best models achieve 9.1% test error for quantitatively predicting cycle life using the first 100 cycles (exhibiting a median increase of 0.2% from initial capacity) and 4.9% test error using the first 5 cycles for classifying cycle life into two groups. This work highlights the promise of combining deliberate data generation with data-driven modelling to predict the behaviour of complex dynamical systems. Accurately predicting battery lifetime is difficult, and a prediction often cannot be made unless a battery has already degraded significantly. Here the authors report a machine-learning method to predict battery life before the onset of capacity degradation with high accuracy.

In this randomized trial, sensor-augmented pump therapy was compared with a regimen of multiple daily insulin injections in adults and children with inadequately controlled type 1 diabetes. Pump therapy was associated with a significant improvement in glycated hemoglobin levels, as compared with injection therapy. Improved glycemic control can reduce the microvascular and macrovascular complications associated with type 1 diabetes mellitus, 1 – 3 and diabetes practitioners are continuously challenged to optimize glucose control while minimizing severe hypoglycemia and weight gain. Insulin pumps and systems for continuous glucose monitoring represent technologies designed to assist patients with type 1 diabetes in safely reaching glycemic goals. Among adults, the use of an insulin pump has been shown to reduce glycated hemoglobin levels without an increased risk of hypoglycemia, as compared with a regimen of multiple daily insulin injections, but results in children have been inconsistent. 4 Recent studies have suggested . . .

Ultraviolet-B (UVB)-induced inflammation produces a dose-dependent mechanical and thermal hyperalgesia in both humans and rats, most likely via inflammatory mediators acting at the site of injury. Previous work has shown that the gene expression of cytokines and chemokines is positively correlated between species and that these factors can contribute to UVB-induced pain. In order to investigate other potential pain mediators in this model we used RNA-seq to perform genome-wide transcriptional profiling in both human and rat skin at the peak of hyperalgesia. In addition we have also measured transcriptional changes in the L4 and L5 DRG of the rat model. Our data show that UVB irradiation produces a large number of transcriptional changes in the skin: 2186 and 3888 genes are significantly dysregulated in human and rat skin, respectively. The most highly up-regulated genes in human skin feature those encoding cytokines (IL6 and IL24), chemokines (CCL3, CCL20, CXCL1, CXCL2, CXCL3 and CXCL5), the prostanoid synthesising enzyme COX-2 and members of the keratin gene family. Overall there was a strong positive and significant correlation in gene expression between the human and rat (R = 0.8022). In contrast to the skin, only 39 genes were significantly dysregulated in the rat L4 and L5 DRGs, the majority of which had small fold change values. Amongst the most up-regulated genes in DRG were REG3B, CCL2 and VGF. Overall, our data shows that numerous genes were up-regulated in UVB irradiated skin at the peak of hyperalgesia in both human and rats. Many of the top up-regulated genes were cytokines and chemokines, highlighting again their potential as pain mediators. However many other genes were also up-regulated and might play a role in UVB-induced hyperalgesia. In addition, the strong gene expression correlation between species re-emphasises the value of the UVB model as translational tool to study inflammatory pain.

Simultaneously optimizing many design parameters in time-consuming experiments causes bottlenecks in a broad range of scientific and engineering disciplines 1 , 2 . One such example is process and control optimization for lithium-ion batteries during materials selection, cell manufacturing and operation. A typical objective is to maximize battery lifetime; however, conducting even a single experiment to evaluate lifetime can take months to years 3 – 5 . Furthermore, both large parameter spaces and high sampling variability 3 , 6 , 7 necessitate a large number of experiments. Hence, the key challenge is to reduce both the number and the duration of the experiments required. Here we develop and demonstrate a machine learning methodology  to efficiently optimize a parameter space specifying the current and voltage profiles of six-step, ten-minute fast-charging protocols for maximizing battery cycle life, which can alleviate range anxiety for electric-vehicle users 8 , 9 . We combine two key elements to reduce the optimization cost: an early-prediction model 5 , which reduces the time per experiment by predicting the final cycle life using data from the first few cycles, and a Bayesian optimization algorithm 10 , 11 , which reduces the number of experiments by balancing exploration and exploitation to efficiently probe the parameter space of charging protocols. Using this methodology, we rapidly identify high-cycle-life charging protocols among 224 candidates in 16 days (compared with over 500 days using exhaustive search without early prediction), and subsequently validate the accuracy and efficiency of our optimization approach. Our closed-loop methodology automatically incorporates feedback from past experiments to inform future decisions and can be generalized to other applications in battery design and, more broadly, other scientific domains that involve time-intensive experiments and multi-dimensional design spaces. A closed-loop machine learning methodology of optimizing fast-charging protocols for lithium-ion batteries can identify high-lifetime charging protocols accurately and efficiently, considerably reducing the experimental time compared to simpler approaches.

QUESTION: Are plant traits more closely correlated with mean annual temperature, or with mean annual precipitation? LOCATION: Global. METHODS: We quantified the strength of the relationships between temperature and precipitation and 21 plant traits from 447,961 species‐site combinations worldwide. We used meta‐analysis to provide an overall answer to our question. RESULTS: Mean annual temperature was significantly more strongly correlated with plant traits than was mean annual precipitation. CONCLUSIONS: Our study provides support for some of the assumptions of classical vegetation theory, and points to many interesting directions for future research. The relatively low R² values for precipitation might reflect the weak link between mean annual precipitation and the availability of water to plants.

This article summarizes the experience of a single institution in treating patients with metastatic testicular tumors that did not respond to cisplatin-based chemotherapy. High-dose chemotherapy with hematopoietic stem-cell rescue was potentially curative in such cases. In patients with metastatic testicular tumors that did not respond to cisplatin-based chemotherapy, high-dose chemotherapy with hematopoietic stem-cell rescue was potentially curative. Germ-cell tumors are curable even in the presence of metastatic disease. 1 – 3 An international collaboration has established that metastatic germ-cell tumors can be classified into good-, intermediate-, and poor-risk disease, with corresponding cure rates of 90 to 95%, 75%, and 40 to 50%, respectively. 4 Hereinafter, we refer to these categories as low-, intermediate-, and high-risk disease, respectively. Patients with tumors that relapse or with tumors that progress despite initial chemotherapy are candidates for salvage therapy. The few patients with anatomically confined disease are amenable to surgical extirpation. 5 For most patients, however, the options include salvage chemotherapy with cisplatin plus ifosfamide . . .

Metabolomics is the study of small molecules (metabolites), within cells, tissues and biofluids. Maternal metabolites can provide important insight into the health and development of both mother and fetus throughout pregnancy. This study assessed metabolic profiles in the maternal circulation prior to and at the time of diagnosis of preeclampsia and fetal growth restriction. Maternal plasma samples were collected from two independent cohorts: (1) Established disease cohort: 50 participants diagnosed with early-onset preeclampsia (< 34 weeks’ gestation), 14 with early-onset fetal growth restriction, and 25 gestation-matched controls. (2) Prospective cohort, collected at 36 weeks’ gestation before diagnosis: 17 participants later developed preeclampsia, 49 delivered infants with fetal growth restriction (birthweight < 5th centile), and 72 randomly selected controls. Metabolic evaluation was performed by Metabolomics Australia on the Agilent 6545 QTOF Mass Spectrometer. In the established disease cohort, 77 metabolites were altered in circulation from participants with preeclampsia – increased l -cysteine (3.73-fold), l -cystine (3.28-fold), l -acetylcarnitine (2.57-fold), and carnitine (1.53-fold) (p < 0.05). There were 53 metabolites dysregulated in participants who delivered a fetal growth restriction infant—including increased levulinic acid, citric acid (1.93-fold), and creatine (1.14-fold) (p < 0.05). In the prospective cohort, 30 metabolites were altered in participants who later developed preeclampsia at term – reduced glutaric acid (0.85-fold), porphobilinogen (0.77-fold) and amininohippuric acid (0.82-fold) (p < 0.05) was observed. There were 5 metabolites altered in participants who later delivered a fetal growth restriction infant – including reduced 3-methoxybenzenepropanoic acid (p < 0.05). Downstream pathway analysis revealed aminoacyl-tRNA biosynthesis to be most significantly altered in the established cohort in preeclampsia (13/48 hits, p < 0.001) and fetal growth restriction (7/48 hits, p < 0.001). The predictive cohort showed no significant pathway alterations. This study observed altered metabolites in maternal plasma collected before and after diagnosis of a preeclampsia or fetal growth restriction. While a significant number of metabolites were altered with established disease, few changes were observed in the predictive cohort. Thus, metabolites measured in this study may not be useful as predictors of preeclampsia or fetal growth restriction.

PurposeDrawing on institutional theory, this study aims to analyse the regulation of executive remuneration as espoused in the United Kingdom (UK) codified corporate governance principles, focussing on sources of advice to decision-makers, the nature of the advice sought and given, and interaction of those involved in the process.Design/methodology/approachA qualitative research design was used. Data were assembled from interviewing non-executive board/remuneration committee members; institutional investors; external remuneration consultants and internal human resources (HR)/reward specialists. Results were analysed in accordance with the Gioia technique.FindingsTensions inherent in the interpretation of corporate governance codes are illustrated. Emphasis on independent advice combined with constraints on decision-makers' capacity to navigate the nuances of a complex field and reputational concerns risks standardised instead of bespoke remuneration approaches aligned with corporate contexts.Practical implicationsThere is a role for internal HR advisors to add value through their potential to reduce the gap within remuneration committees between institutional contexts and independent decision-making, facilitating more strategic human resource management inspired executive remuneration.Originality/valueApplication of institutional theory indicates the relevance of balancing external with internal sources to secure advice that is horizontally and vertically aligned within an organisation to meet the letter and spirit of corporate governance norms. Extending the explanatory power of institutional theory, care is needed though not to overlook the normative underpinnings of professional advisors' own value sets.