Longer Time Window Research Articles

Bans on eating and drinking: What do investors think?

This study examines the stock return responses to the declaration by the Chinese government of five restrictions on the drinking of alcohol. We propose that a teetotal effect occurred when the stock returns of alcohol companies dropped after these announcements. We classify alcohol companies into those that produced Chinese liquor and those that produced non-Chinese liquor and argue that Chinese liquor was more seriously affected by the restriction than non-Chinese liquor. We further classify Chinese liquor into top- and bottom-quality Chinese liquor. Through our analysis, we observed distinct patterns in the stock returns of these companies over different time periods. First, our results indicate the existence of a teetotal effect on the event day, especially for top-quality Chinese liquor. Next, the abnormal returns became positive in the days following the event, varying between the second, third, and fourth days. Finally, the returns show a mixed pattern for an even longer time window. We then explain these observations. The first negative effect was a result of the market shocks from the news; then Chinese investors believed that the demand for high-quality Chinese liquor would not be reduced because of the endurance of the drinking culture of China. Finally, people accepted the restrictions.

Investigating and comparing the IRIS spectral lines Mg II, Si IV, and C II for flare precursor diagnostics

Context. Reliably predicting solar flares can mitigate the risks of technological damage and enhance scientific output by providing reliable pointings for observational campaigns. Flare precursors in the spectral line Mg II have been identified. Aims. We extend previous studies by examining the presence of flare precursors in additional spectral lines, such as Si IV and C II, over longer time windows, and for more observations. Methods. We trained neural networks and XGBoost decision trees to distinguish spectra observed from active regions that lead to a flare and those that did not. To enhance the information within each observation, we tested different masking methods to preprocess the data. Results. We find average classification true skill statistics (TSS) scores of 0.53 for Mg II, 0.44 for Si IV, and 0.42 for C II. We speculate that Mg II h&k performs best because it samples the highest formation height range, and is sensitive to heating and density changes in the mid- to upper chromosphere. The flaring area relative to the field of view has a large effect on the model classification score and needs to be accounted for. Combining spectral lines has proven difficult, due to the difference in areas of high probability for an imminent flare between different lines. Conclusions. Our models extract information from all three lines, independent of observational bias or GOES X-ray flux precursors, implying that the physics encoded in a combination of high resolution spectral data could be useful for flare forecasting.

Study on the effects of accident-tolerant fuels on the safety of CPR1000 nuclear power plants

Abstract In this paper, CPR1000 Nuclear power plant was taken as the reference unit. According to CPR1000 Probabilistic Safety Analysis (PSA), the Large Break loss of coolant accident (LOCA), Medium Break LOCA, Small Break LOCA, Station Blackout (SBO), Total Loss of Feed water (TLOFW) and Anticipated transient without trip (ATWT) with Loss of Main Feed water (LOMF) were selected as the representative accident scenarios. The house holding deterministic programs LOCUST were used to analyze each of the above selected scenarios for five different accident tolerant fuels (ATF). The effects on accident process, reactor core damage time, system success criteria and personnel response time were analyzed under the above scenarios. The above results for the five ATF materials were compared to those for standard UO2-Zr in the same scenarios, then some useful conclusions were obtained which can be used to support ATF material selection. In the end, based on the deterministic calculations, the effects of different ATF materials on CPR1000 PSA results such as core damage frequency (CDF) were evaluated in detail with traditional PSA software Risk Spectrum. According to the results, ATFs have some advantages on core damage time, success criteria or operators’ action time window. But the CDF was changed little compared to standard UO2-Zr system. Through the studies, it is found the most important thing is that due to the much longer time windows some new plant modifications can be provided to mitigate the accidents which can contribute to the plant safety and decrease risk more.

Quantitative inversion of soil trace elements from spectroscopic effects across multiple crop growth periods

Human health is directly impacted by trace components found in soil, for which hyperspectral remote sensing technology offers a novel way to rapidly assess dynamic soil environmental quality. In most studies, the premise of quantitative inversion on soil elements is that the known target elements will cause growth stress. However, such stress is unusual in non-polluted areas. Consequently, broad-area soil trace element monitoring in non-contaminated areas remains challenging. Spectral inversion of plant material has a longer time window and is more sensitive to elemental changes than soil spectral inversion (bare soil period). In this work, we conducted a wheat pot experiment with concentration gradients of four trace elements (Fe, B, Mo, and Zn), analyzed leaf (jointing stage) and spike (maturity period) samples using spectral measurements and chemical tests, and filtered the characteristic positions and inverse modeling using the spectra of the element-accumulating preference organs in plant canopies. The canopy aggregation sites differed for each element, and both simple linear regression (SLR) and multiple linear regression (MLR) models based on the spectra of canopy aggregation sites achieved high accuracy. The results of this study enable the construction of an inverse model of plant spectra-plant element content-elements in soil, which can serve as a reference for soil monitoring and assessment in typical crop cover areas.

Critical thresholds of long-pressure reactivity index and impact of intracranial pressure monitoring methods in traumatic brain injury

BackgroundModerate-to-severe traumatic brain injury (TBI) has a global mortality rate of about 30%, resulting in acquired life-long disabilities in many survivors. To potentially improve outcomes in this TBI population, the management of secondary injuries, particularly the failure of cerebrovascular reactivity (assessed via the pressure reactivity index; PRx, a correlation between intracranial pressure (ICP) and mean arterial blood pressure (MAP)), has gained interest in the field. However, derivation of PRx requires high-resolution data and expensive technological solutions, as calculations use a short time-window, which has resulted in it being used in only a handful of centers worldwide. As a solution to this, low resolution (longer time-windows) PRx has been suggested, known as Long-PRx or LPRx. Though LPRx has been proposed little is known about the best methodology to derive this measure, with different thresholds and time-windows proposed. Furthermore, the impact of ICP monitoring on cerebrovascular reactivity measures is poorly understood. Hence, this observational study establishes critical thresholds of LPRx associated with long-term functional outcome, comparing different time-windows for calculating LPRx as well as evaluating LPRx determined through external ventricular drains (EVD) vs intraparenchymal pressure device (IPD) ICP monitoring.MethodsThe study included a total of n = 435 TBI patients from the Karolinska University Hospital. Patients were dichotomized into alive vs. dead and favorable vs. unfavorable outcomes based on 1-year Glasgow Outcome Scale (GOS). Pearson’s chi-square values were computed for incrementally increasing LPRx or ICP thresholds against outcome. The thresholds that generated the greatest chi-squared value for each LPRx or ICP parameter had the highest outcome discriminatory capacity. This methodology was also completed for the segmentation of the population based on EVD, IPD, and time of data recorded in hospital stay.ResultsLPRx calculated with 10–120-min windows behaved similarly, with maximal chi-square values ranging at around a LPRx of 0.25–0.35, for both survival and favorable outcome. When investigating the temporal relations of LPRx derived thresholds, the first 4 days appeared to be the most associated with outcomes. The segmentation of the data based on intracranial monitoring found limited differences between EVD and IPD, with similar LPRx values around 0.3.ConclusionOur work suggests that the underlying prognostic factors causing impairment in cerebrovascular reactivity can, to some degree, be detected using lower resolution PRx metrics (similar found thresholding values) with LPRx found clinically using as low as 10 min-by-minute samples of MAP and ICP. Furthermore, EVD derived LPRx with intermittent cerebrospinal fluid draining, seems to present similar outcome capacity as IPD. This low-resolution low sample LPRx method appears to be an adequate substitute for the clinical prognostic value of PRx and may be implemented independent of ICP monitoring method when PRx is not feasible, though further research is warranted.

IV Thrombolysis in Basilar Artery Occlusion: Outcomes and Comparison With Endovascular Thrombectomy.

Recanalization is considered a prerequisite for favorable outcome in basilar artery occlusion (BAO). Intravenous thrombolysis (IVT) has been successfully used for eligible patients with BAO well beyond the 4.5-hour time window but has been largely underrepresented in the best medical management arms in recent randomized controlled trials of recanalization therapy in BAO. We aimed to analyze the outcomes of patients with BAO treated with IVT only and to compare IVT with endovascular thrombectomy (EVT). This observational single-center, retrospective cohort study included consecutive patients with BAO treated with IVT and/or EVT up to 48 hours of symptom onset during 1995-2022. The primary outcome was favorable functional outcome (modified Rankin Scale 0-3) at 3 months collected by a stroke physician by phone. In the first part, we described the outcomes and factors associated with functional outcome in the IVT-only cohort during 1995-2022. In the second part, we used doubly robust inverse probability-weighted regression adjustment models to compare functional outcome of patients treated with IVT vs EVT+/-IVT during 2010-2022. In the whole cohort of 376 patients with acute BAO treated with recanalization therapy, 245 (65.2%) received only IVT. In the IVT-only cohort, most patients had moderate-to-severe clinical presentation (median NIH Stroke Scale 18) but no extensive early ischemic changes in the posterior circulation on admission. Half of them had onset-to-treatment time over 6 hours. 46.5% of the IVT-treated patients achieved 3-month favorable functional outcome, whereas mortality was 35.9%. sICH occurred in 11.1%. In a multivariable analysis, younger age, milder symptom severity, and less baseline ischemic changes predicted favorable functional outcome. In the 2010-2022 cohort, when compared with patients treated with EVT+/-IVT (n = 121), the IVT-only cohort (n = 122) had higher odds for favorable functional outcome (IVT 58.2% vs EVT 43.0% (aOR 2.82 [95% CI 1.31-6.05]). IVT alone produced outcomes comparable with those in recent trials of endovascular BAO recanalization. Furthermore, in head-to-head comparison in our cohort, the IVT-only approach was more often associated with favorable outcome than EVT+/-IVT. Thus, it should not be overlooked as the first-line recanalization therapy in acute BAO, even in longer time windows. This study provides Class IV evidence that tPA is as effective as thrombectomy for basilar artery thrombosis.

Service time window selection for attended home deliveries: a case study for urban and rural areas

Attended home deliveries are one of the most challenging logistics services with different customer expectations and challenges in urban and rural areas. For different demand densities, retailers must strike a balance between providing excellent customer service and optimizing routing efficiency. While customers often expect delivery promises with narrow time windows, research has demonstrated that longer time windows can increase the flexibility and the ability to accept more customers. However, it is not clear how different demand densities impact flexibility and customer acceptance. To serve as many customers as possible with excellent service quality, this paper reviews and expands on ideas for offering short and long time windows in a flexible manner in urban and rural areas. This study proposes different methods for providing customers with time windows of different lengths and investigates their performance based on a case study in Vienna and Upper Austria.

Real-time prediction of distance and PGA from P-wave features using Gradient Boosting Regressor for on-site earthquake early warning applications

SUMMARY On-site earthquake early warning (EEW) systems represent an important way to reduce seismic hazard. Since these systems are fast in providing an alert and reliable in the prediction of the ground motion intensity at targets, they are particularly suitable in the areas where the seismogenic zones are close to cities and infrastructures, such as Central Italy. In this work, we use Gradient Boosting Regressor (GBR) to predict peak ground acceleration (PGA), and hypocentral distance (D) starting from P-wave features. We use two data sets of waveforms from two seismic sequences in Central Italy: L'Aquila sequence (2009) and the Amatrice–Norcia–Visso sequence (2016–2017), for a total of about 80 000 three-component waveforms. We compute 60 different features related to the physics of the earthquake using three different time windows (1 s, 2 s and 3 s). We validate and train our models using the 2016–2017 data sets (the bigger one) and we test it on the 2009 data set. We study the performances of GBR predicting D and PGA in terms of prediction scores, finding that the models can well predict both targets even using 1 s window, and that, as expected, the results improve using longer time windows. Moreover, we perform a residual analysis on the test set finding that the PGA can be predicted without any bias, while the D prediction presents a correlation with the moment magnitude. In the end, we propose a prototype for a probabilistic on-site EEW system based on the prediction of D and PGA. The proposed system is a threshold-based approach and it releases an alert on four possible levels, from 0 (far and small event) to 3 (close and strong event). The system computes the probability related to each alert level. We test two different set of thresholds: the Felt Alert and the Damage Alert. Furthermore, we consider the lead time (LT) of the PGA to distinguish between useful alerts (positive LT) and Missed Alerts (MA). In the end, we analyse the performance of such a system considering four possible scenarios: Successful Alert (SA), Missed Alert (MA), Overestimated Alert (OA) and Underestimated Alert (UA). We find that the system obtains SA rate about 80 per cent at 1 s, and that it decreases to about 65 per cent due to the increase in MA. This result shows how the proposed system is already reliable at 1 s, which would be a huge advantage for seismic prone regions as Central Italy, an area characterized by moderate-to-large earthquakes (Mw < 7).

Quantitative MRI of Gd-DOTA Accumulation in the Mouse Brain After Intraperitoneal Administration: Validation by Mass Spectrometry.

In mice, intraperitoneal (ip) contrast agent (CA) administration is convenient for mapping microvascular parameters over a long-time window. However, continuous quantitative MRI of CA accumulation in brain over hours is still missing. To validate a quantitative time-resolved MRI technique for mapping the CA kinetics in brain upon ip administration. Prospective, animal model. 25 C57Bl/6JRj mice underwent MRI. 7-T, gradient echo sequence. Gd-DOTA concentration was monitored by MRI (25 s/repetition) over 135 minutes with (N = 15) and without (N = 10) ip mannitol challenge (5 g/kg). After the final repetition, the brains were sampled to quantify gadolinium by mass spectrometry (MS). Upon manual brain segmentation, the average gadolinium concentration was compared with the MS quantification in transcardially perfused (N = 20) and unperfused (N = 5) mice. Precontrast T1-maps were acquired in 8 of 25 mice. One-tailed Spearman and Pearson correlation between gadolinium quantification by MRI and by MS, D'Agostino-Pearson test for normal distribution, Bland-Altman analysis to evaluate the agreement between MRI and MS. Significance was set at P-value <0.05. MRI showed that ip administered CA reached the blood compartment (>5 mM) within 10 minutes and accumulated continuously for 2 hours in cerebrospinal fluid (>1 mM) and in brain tissue. The MRI-derived concentration maps showed interindividual differences in CA accumulation (from 0.47 to 0.81 mM at 2 hours) with a consistent distribution resembling the pathways of the glymphatic system. The average in-vivo brain concentration 2 hours post-CA administration correlated significantly (r = 0.8206) with the brain gadolinium quantification by MS for N = 21 paired observations available. The presented experimental and imaging protocol may be convenient for monitoring the spatiotemporal pattern of CA uptake and clearance in the mouse brain over 2 hours. The quantification of the CA from the MRI signal in brain is corroborated by MS. N/A TECHNICAL EFFICACY: Stage 1.

Deep net classification of drum strike location with non-uniformmembrane tension

Tuning inaccuracies in snare drum membranes can cause inconsistent spectro-temporal changes (e.g., timbre differences) exacerbated by drumhead strike location. This experimental study assesses the potential for developing a deep net classifier for strike drum location, using a Non-UniformlyTuned Snare (NUTS) dataset, comprising 12,107 individual snare drum hits recorded in an anechoic chamber. Unique features of this dataset include its substantial size, additional novel features comprising physical attributes of the drum, and a performance-based classification schema. A series of deep net classifiers are trained using Bayesian hyperparameter optimization, on a subset of 8685 strikes of the NUTS dataset, whose acoustic features are extracted at nine different averaged time-windows(23–2000 ms). A comparison is then made against similar models supplemented by domain knowledge of 15 different combinations of non-uniform membrane tension, whose measures are recorded near the sixteen tuning lugs for each strike. Results found above chance model accuracies, and some performance benefits of including the tuning information as domain knowledge between equivalent trials. Shorter window sizes performed worse than longer time windows, and per-class F1-scores suggest complex spectro-temporal time variant changes caused by dis-uniform membrane tension, which could have implications for performers wishing to broaden the sonic capabilities of the instrument.

Simultaneous identifying the infarct core, collaterals, and penumbra after acute ischemic stroke with a low-immunogenic MRI nanoprobe

Ischemic stroke is one of the leading causes of disability and mortality. The collaterals provide an alternative pathway to preserve the ischemic brain tissue, and determine the penumbra range, where the neurons are salvageable. Therefore, accurately monitoring the collaterals and identifying the penumbra are crucial. Herein, a low-immunogenic nanoprobe-based MRI strategy is developed to simultaneously identify the infarct core, collaterals distribution, and ischemic penumbra distributions. The low-immunogenic nanoprobe was constructed by covalently attaching self-peptide on the surface of biocompatible Fe3O4 nanoparticles as a stealth coating. Both in vitro and in vivo experiments clearly revealed that the nanoprobes can effectively avoid capture by macrophages, and exhibited prolonged blood half-life to continuously enhance the contrast of blood vessels in a longer time window in susceptibility-weighted imaging (SWI), which enabled the delineation of the collaterals and ischemic penumbra. More importantly, combined with the diffusion-weighted imaging (DWI), the infarct core, collateral vessels, and the ischemic penumbra range can be identified simultaneously. In this context, the stroke progress including infarct core growth, collateral vessel formation, and penumbra distribution, can be better understood. This nanoprobe-based strategy thus offers a practical route for precise diagnosis of ischemic stroke, which remains a challenge for conventional MRI strategies.

Stronger spatial bias induced more by numbers in mind than numbers in eye: Evidence from event-related potentials

The relationship between number and space is an important issue in numerical cognition. The spatial-numerical association of response codes (SNARC) effect is a classic example of the association between numbers and spaces. It refers to the phenomenon whereby left-handed responses occur faster to small number and right-handed responses occur faster to large number. The current study explored the shared and distinct neural correlates of the SNARC effect considering numbers in eye and numbers in mind, by using event-related potentials (ERPs) technology. In each trial of the task, participants were asked to press freely one of two keys as a response to a number presented visually (numbers in eye) or via imagination (numbers in mind). The behavioral results indicated that the free-choice key presses were affected by the magnitudes of the numbers either in eye or in mind. Electrophysiological results observed that the SNARC effect appeared only in the 110–140 ms time window for numbers in eye. In contrast, for numbers in mind, the SNARC effect appeared during a longer time window (110–330 ms). These results suggest that both, numbers in eye and numbers in mind, can induce spatial bias at the early stimulus-representation stage, but the time duration of the spatial bias is longer for numbers in mind than numbers in eye. This may reflect a closer connection between numbers in mind and mental number line.

SPECT Imaging with Tc-99m-Labeled HYNIC-FAPI-04 to Extend the Differential Time Window in Evaluating Tumor Fibrosis

The so-far used Ga-68- or F-18-labelled tracers are of a relative short time window in differentiating tumor fibrosis. SPECT applicable imaging probe, 99mTc-HYNIC-FAPI-04, was synthesized and evaluated in tumor cells and animal models of FAP-positive glioma and FAP-negative hepatoma, and then compared with 18F-FDG or 68Ga-FAPI-04 PET/CT. The radio-labeling rate of 99mTc-HYNIC-FAPI-04 was greater than 90%, and the radiochemical purity was >99% after purification with sep-pak C18 column. In vitro cell uptake experiments of 99mTc-HYNIC-FAPI-04 showed good FAP binding specificity, and the cellular uptake significantly decreased when blocked by DOTA-FAPI-04, reflecting the similar targeting mechanism of HYNIC-FAPI-04 and DOTA-FAPI-04. SPECT/CT imaging showed that U87MG tumor was distinguishable and of a high uptake of 99mTc-HYNIC-FAPI-04 (2.67 ± 0.35 %ID/mL at 1.5 h post injection (h P.I.), while tumor signal of FAP-negative HUH-7 was as low as 0.34 ± 0.06 %ID/mL. At 5 h P.I., U87MG tumor was still distinguishable (1.81 ± 0.20 %ID/mL). In comparison, although U87MG tumor was of obvious 68Ga-FAPI-04 uptake and clearly visible at 1 h P.I., the tumorous radioactive signals were fuzzy at 1.5 h P.I. 99mTc-HYNIC-FAPI-04 specifically bound to FAP-positive tumors and qualified with the ability of evaluating tumor fibrosis over longer time windows.

The spatial signature of Plasmodium vivax and Plasmodium falciparum infections: quantifying the clustering of infections in cross-sectional surveys and cohort studies

BackgroundOver the last decades, enormous successes have been achieved in reducing malaria burden globally. In Latin America, South East Asia, and the Western Pacific, many countries now pursue the goal of malaria elimination by 2030. It is widely acknowledged that Plasmodium spp. infections cluster spatially so that interventions need to be spatially informed, e.g. spatially targeted reactive case detection strategies. Here, the spatial signature method is introduced as a tool to quantify the distance around an index infection within which other infections significantly cluster.MethodsData were considered from cross-sectional surveys from Brazil, Thailand, Cambodia, and Solomon Islands, conducted between 2012 and 2018. Household locations were recorded by GPS and finger-prick blood samples from participants were tested for Plasmodium infection by PCR. Cohort studies from Brazil and Thailand with monthly sampling over a year from 2013 until 2014 were also included. The prevalence of PCR-confirmed infections was calculated at increasing distance around index infections (and growing time intervals in the cohort studies). Statistical significance was defined as prevalence outside of a 95%-quantile interval of a bootstrap null distribution after random re-allocation of locations of infections.ResultsPrevalence of Plasmodium vivax and Plasmodium falciparum infections was elevated in close proximity around index infections and decreased with distance in most study sites, e.g. from 21.3% at 0 km to the global study prevalence of 6.4% for P. vivax in the Cambodian survey. In the cohort studies, the clustering decreased with longer time windows. The distance from index infections to a 50% reduction of prevalence ranged from 25 m to 3175 m, tending to shorter distances at lower global study prevalence.ConclusionsThe spatial signatures of P. vivax and P. falciparum infections demonstrate spatial clustering across a diverse set of study sites, quantifying the distance within which the clustering occurs. The method offers a novel tool in malaria epidemiology, potentially informing reactive intervention strategies regarding radius choices of operations around detected infections and thus strengthening malaria elimination endeavours.

Good collaterals and better outcomes after EVT for basilar artery occlusion: A systematic review and meta-analysis.

Stroke caused by acute basilar artery occlusion (BAO) is devastating with high dependency and mortality. Recent trials have demonstrated the efficacy of endovascular treatment (EVT) for acute BAO, while pretreatment collaterals may be a valuable prognostic indicator for post-EVT outcomes. To systematically review and synthesize evidence on the associations between pretreatment collateral status and outcomes after EVT in acute BAO. We retrieved relevant full-text articles published in English since 1 January 2010, reporting associations between pretreatment collateral status and outcomes after EVT for BAO, by searching MEDLINE and Embase. The primary outcome was favorable or good 90-day functional outcome (modified Rankin Scale [mRS] 0-2 or 0-3); secondary outcomes included successful recanalization, symptomatic intracranial hemorrhage, final infarct volume, and 90-day mortality. Risk ratios (RRs) with 95% confidence intervals (CIs) for good versus poor collaterals on the outcomes were synthesized using random-effects models. Subgroup and sensitivity analyses were conducted for the primary outcome. Overall, 29 primary studies (2995 participants) were included in qualitative review, among which 16 studies (1447 participants) were meta-analyzed. With different imaging modalities and methods to grade the collateral status, good collaterals were found in 33-85% of patients in the individual primary studies (I2 = 95.2%, p < 0.001), with a pooled proportion of 51% (95% CI: 40-62%) across all studies. Good pretreatment collaterals were associated with a doubled rate of favorable/good 90-day functional outcome (RR = 2.03, 95% CI: 1.63-2.51, p < 0.001), a higher rate of successful recanalization (RR = 1.23, 95% CI: 1.04-1.45, p = 0.015), and reduced 90-day mortality (RR = 0.59, 95% CI: 0.43-0.81, p = 0.001) after EVT for BAO. None of the primary studies reported the associations of good collaterals with the other secondary outcomes. Subgroup analyses revealed possibly more prominent protective effect of good pretreatment collaterals over the primary outcome, in studies with longer time windows in patient eligibility criteria for EVT (p = 0.028 for between-subgroup heterogeneity). In patients with BAO receiving EVT, good pretreatment collateral status was associated with a higher chance of favorable 90-day functional outcome, despite the various methods in grading the collateral circulation. Efforts are needed for more standardized collateral assessment in BAO, for more reliable and generalizable investigations of its clinical implications.

Long-term fatigue estimation on offshore wind turbines interface loads through loss function physics-guided learning of neural networks

Offshore wind turbines are exposed during their serviceable lifetime to a wide range of loads from aero-, hydro- and structural dynamics. This complex loading scenario will have an impact on the lifetime of the asset, with fatigue remaining the key structural design driver for the substructure, e.g. the monopile. The ability to monitor the progression of fatigue life of these assets has recently become an operational concern. To achieve a monitoring alternative to strain gauges (cost-prohibitive farm-wide installation), supervisory control and data acquisition (SCADA) systems, often coupled with acceleration measurements, have been used. Existing work focused primarily on ten-minute fatigue load estimation. However, fatigue accumulates over time and the ability to accurately monitor this accumulation of fatigue over a longer time-window is paramount. In this contribution we investigate a novel approach using nine months of real-world SCADA and acceleration ten-minute statistics as inputs of a neural network model for long-term DEM estimation. This is further enhanced by including physical information relative to the problem at hand into the neural network model, in a so-called physics-informed machine learning approach. Specifically, we employ a custom loss function – the Minkowski logarithmic error – which prioritizes conservativeness (over-prediction of fatigue rates) and to embed the damage accumulation into the machine learning model.In the results and discussion section, we use Tower-TP interface load measurements for three real-world turbines to demonstrate the concept. First a model is trained on one turbine, before being applied to all three locations. The model performance is compared to direct measurements of fatigue progression at all three locations and a control loss function (the mean squared logarithm error) in both the Fore-Aft and Side-Side loading directions. The novel physics-informed model clearly outperforms the control loss function in accumulated fatigue predictions with errors below 3% on accumulated damage equivalent moment estimates. Additionally, the model’s long-term performance is checked according to varying timescales (hourly, daily, weekly or monthly accumulation of DEM) and it is seen that the spread on the error rapidly reduces and converges to zero. Finally, the long-term DEM is accumulated into a monthly accumulated fatigue damage. We also see how the error on this begins to converge after 6+ months, which opens the door for extrapolation.

Evaluating pricing strategies for premium delivery time windows

In the challenging environment of attended home deliveries, pricing delivery options can play a crucial role to ensure profitability and service quality of retailers. To differentiate between standard and premium delivery options, many retailers include time windows of various lengths and fees within their offer sets. Even though customers prefer short delivery time windows, longer time windows can help maintaining flexibility and profitability for the retailer. We classify pricing strategies along two dimensions: static versus dynamic price setting and whether an offer set can include one or multiple price points. For static pricing, we implement price configurations that reflect current business practice. For the dynamic pricing, we adapt routing mechanisms that consider the flexibility within the underlying route plan during the booking process and set delivery fees accordingly. To evaluate the pricing strategies under plausibly realistic conditions, we model customer behavior through a nested logit model. This model represents customer choice as sequential decisions between premium and standard time windows. We perform a computational study considering realistic travel and demand data to investigate the effectiveness of static and dynamic time window pricing. Finally, we offer managerial insights and an outlook into applying strategic analysis to decide on price setting strategies.

The innovative 52g Mn for positron emission tomography (PET) imaging: Production cross sectionmodeling and dosimetric evaluation.

Manganese is a paramagnetic element suitable for magnetic resonance imaging (MRI) of neuronal function. However, high concentrations of Mn2 + can be neurotoxic. 52g Mn may be a valid alternative as positron emission tomography (PET) imaging agent, to obtain information similar to that delivered by MRI but using trace levels of Mn2 + , thus reducing its toxicity. Recently, the reaction V(α,x)52g Mn has been proposed as a possible alternative to the standard Cr(p,x)52g Mn one, but improvements in the modeling were needed to better compare the two productionroutes. This work focuses on the development of precise simulations and models to compare the 52g Mn production from both reactions in terms of amount of activity and radionuclidic purity (RNP), as well as in terms of dose increase (DI) due to the co-produced radioactive contaminants, versus pure 52g MnCl2 . The nuclear code Talys has been employed to optimize the V(α,x)52g Mn cross sectionby tuning the parameters of the microscopic level densities. Thick-target yields have been calculated from the expression of the rates as energy convolution of cross sectionsand stopping powers, and finally integrating the time evolution of the relevant decay chains. Dosimetric assessments of [ Mn]Cl2 have been accomplished with OLINDA software 2.2.0 using female and male adult phantoms and biodistribution data for 52g MnCl2 in normal mice. At the end, the yield of Mn radioisotopes estimated for the two production routes have been combined with the dosimetric results, to assess the DI at different times after the end of theirradiation. Good agreement was obtained between cross-sectioncalculations and measurements. The comparison of the two reaction channels suggests that V(α,x)52g Mn leads to higher yield and higher purity, resulting in more favorable radiation dosimetry forpatients. Both V(α,x) and Cr(p,x) production routes provide clinically acceptable 52g MnCl2 for PET imaging. However, the V(α,x)52g Mn reaction provides a DI systematically lower than the one obtainable with Cr(p,x)52g Mn and a longer time window in which it can be used clinically (RNP ≥ 99%).

Influence of the trigger time window on the detection of gas turbine trip

Gas turbine (GT) trip is one of the most disrupting events that affect GT operation, since its occurrence causes a reduction of equipment remaining useful life as well as revenue loss because of business interruption. Thus, early detection of incipient symptoms of GT trip is crucial to ensure efficient operation and lower operation and maintenance costs. This paper applies a data-driven methodology that employs a Long Short-Term Memory (LSTM) neural network and a clustering technique to identify the time point at which trip symptoms are triggered. The same methodology also partitions trips into homogeneous clusters according to their most likely trigger position. The methodology is applied to two real-world case studies composed of a collection of trips, of which the causes are different, taken from various fleets of industrial GTs. Data collected from twenty sensors during three days of operation before trip occurrence are analyzed. For each trigger scenario, this paper investigates different lengths of the training and testing time window (namely “trigger time window”), by considering up to 24, 18, 12 or 6 hours before and after the considered trigger position. The results demonstrate that longer time windows allow an improvement of the predictive capability.

Mind the gap: Distributed practice enhances performance in a MOBA game.

Understanding how humans master complex skills has the potential for wide-reaching societal benefit. Research has shown that one important aspect of effective skill learning is the temporal distribution of practice episodes (i.e., distributed practice). Using a large observational sample of players (n = 162,417) drawn from a competitive and popular online game (League of Legends), we analysed the relationship between practice distribution and performance through time. We compared groups of players who exhibited different play schedules using data slicing and machine learning techniques, to show that players who cluster gameplay into shorter time frames ultimately achieve lower performance levels than those who space their games across longer time windows. Additionally, we found that the timing of intensive play periods does not affect final performance-it is the overall amount of spacing that matters. These results extend some of the key findings in the literature on practice and learning to an ecologically valid environment with huge n. We discuss our work in relation to recent studies that have examined practice effects using Big Data and suggest solutions for salient confounds.