Order acceptance in food processing systems with random raw material requirements

This study considers a food production system that processes a single perishable raw material into several products having stochastic demands. In order to process an order, the amount of raw material delivery from storage needs to meet the raw material requirement of the order. However, the amount of raw material required to process an order is not exactly known beforehand as it becomes evident during processing. The problem is to determine the admission decisions for incoming orders so as to maximize the expected total revenue. It is demonstrated that the problem can be modeled as a single resource capacity control problem. The optimal policy is shown to be too complex for practical use. A heuristic approach is proposed which follows rather simple decision rules while providing good results. By means of a numerical study, the cases where it is critical to employ optimal policies are highlighted, the effectiveness of the heuristic approach is investigated, and the effects of the random resource requirements of orders are analyzed

Exploring the ability of the variable-resolution Community Earth System Model to simulate cryospheric–hydrological variables in High Mountain Asia

Earth system models (ESMs) can help to improve the understanding of climate-induced cryospheric–hydrological impacts in complex mountain regions, such as High Mountain Asia (HMA). Coarse ESM grids, however, have difficulties in representing cryospheric–hydrological processes that vary over short distances in complex mountainous environments. Variable-resolution (VR) ESMs can help to overcome these limitations through targeted grid refinement. This study investigates the ability of the VR Community Earth System Model (VR-CESM) to simulate cryospheric–hydrological variables such as the glacier surface mass balance (SMB) over HMA. To this end, a new VR grid is generated, with a regional grid refinement up to 7 km over HMA. Two coupled atmosphere–land simulations are run for the period 1979–1998. The second simulation is performed with an updated glacier cover dataset and includes snow and glacier model modifications. Comparisons are made to gridded outputs derived from a globally uniform 1∘ CESM grid, observation-, reanalysis-, and satellite-based datasets, and a glacier model forced by a regional climate model (RCM). Climatological biases are generally reduced compared to the coarse-resolution CESM grid, but the glacier SMB is too negative relative to observation-based glaciological and geodetic mass balances, as well as the RCM-forced glacier model output. In the second simulation, the SMB is improved but is still underestimated due to cloud cover and temperature biases, missing model physics, and incomplete land–atmosphere coupling. The outcomes suggest that VR-CESM could be a useful tool to simulate cryospheric–hydrological variables and to study climate change in mountainous environments, but further developments are needed to better simulate the SMB of mountain glaciers.</p

Application of a stochastic weather generator to assess climate change impacts in a semi-arid climate: The Upper Indus Basin

Assessing local climate change impacts requires downscaling from Global Climate Model simulations. Here, a stochastic rainfall model (RainSim) combined with a rainfall conditioned weather generator (CRU WG) have been successfully applied in a semi-arid mountain climate, for part of the Upper Indus Basin (UIB), for point stations at a daily time-step to explore climate change impacts. Validation of the simulated time-series against observations (1961–1990) demonstrated the models’ skill in reproducing climatological means of core variables with monthly RMSE of <2.0 mm for precipitation and ⩽0.4 °C for mean temperature and daily temperature range. This level of performance is impressive given complexity of climate processes operating in this mountainous context at the boundary between monsoonal and mid-latitude (westerly) weather systems. Of equal importance the model captures well the observed interannual variability as quantified by the first and last decile of 30-year climatic periods. Differences between a control (1961–1990) and future (2071–2100) regional climate model (RCM) time-slice experiment were then used to provide change factors which could be applied within the rainfall and weather models to produce perturbed ‘future’ weather time-series. These project year-round increases in precipitation (maximum seasonal mean change:+27%, annual mean change: +18%) with increased intensity in the wettest months (February, March, April) and year-round increases in mean temperature (annual mean +4.8 °C). Climatic constraints on the productivity of natural resource-dependent systems were also assessed using relevant indices from the European Climate Assessment (ECA) and indicate potential future risk to water resources and local agriculture. However, the uniformity of projected temperature increases is in stark contrast to recent seasonally asymmetrical trends in observations, so an alternative scenario of extrapolated trends was also explored. We conclude that interannual variability in climate will continue to have the dominant impact on water resources management whichever trajectory is followed. This demonstrates the need for sophisticated downscaling methods which can evaluate changes in variability and sequencing of events to explore climate change impacts in this region

Two phase 3 trials of inclisiran in patients with elevated LDL cholesterol

BACKGROUND Inclisiran inhibits hepatic synthesis of proprotein convertase subtilisin-kexin type 9. Previous studies suggest that inclisiran might provide sustained reductions in low-density lipoprotein (LDL) cholesterol levels with infrequent dosing. METHODS We enrolled patients with atherosclerotic cardiovascular disease (ORION-10 trial) and patients with atherosclerotic cardiovascular disease or an atherosclerotic cardiovascular disease risk equivalent (ORION-11 trial) who had elevated LDL cholesterol levels despite receiving statin therapy at the maximum tolerated dose. Patients were randomly assigned in a 1:1 ratio to receive either inclisiran (284 mg) or placebo, administered by subcutaneous injection on day 1, day 90, and every 6 months thereafter over a period of 540 days. The coprimary end points in each trial were the placebo-corrected percentage change in LDL cholesterol level from baseline to day 510 and the time-adjusted percentage change in LDL cholesterol level from baseline after day 90 and up to day 540. RESULTS A total of 1561 and 1617 patients underwent randomization in the ORION-10 and ORION-11 trials, respectively. Mean (SD) LDL cholesterol levels at baseline were 104.738.3 mg per deciliter (2.710.99 mmol per liter) and 105.539.1 mg per deciliter (2.731.01 mmol per liter), respectively. At day 510, inclisiran reduced LDL cholesterol levels by 52.3% (95% confidence interval [CI], 48.8 to 55.7) in the ORION-10 trial and by 49.9% (95% CI, 46.6 to 53.1) in the ORION-11 trial, with corresponding time-adjusted reductions of 53.8% (95% CI, 51.3 to 56.2) and 49.2% (95% CI, 46.8 to 51.6) (P&lt;0.001 for all comparisons vs. placebo). Adverse events were generally similar in the inclisiran and placebo groups in each trial, although injection-site adverse events were more frequent with inclisiran than with placebo (2.6% vs. 0.9% in the ORION-10 trial and 4.7% vs. 0.5% in the ORION-11 trial); such reactions were generally mild, and none were severe or persistent. CONCLUSIONS Reductions in LDL cholesterol levels of approximately 50% were obtained with inclisiran, administered subcutaneously every 6 months. More injection-site adverse events occurred with inclisiran than with placebo

Improved detection of fluorescently labeled microspheres and vessel architecture with an imaging cryomicrotome

Due to spectral overlap, the number of fluorescent labels for imaging cryomicrotome detection was limited to 4. The aim of this study was to increase the separation of fluorescent labels. In the new imaging cryomicrotome, the sample is cut in slices of 40 μm. Six images are taken for each cutting plane. Correction for spectral overlap is based on linear combinations of fluorescent images. Locations of microspheres are determined by using the system point spread function. Five differently colored microspheres were injected in vivo distributed over two major coronaries, the left anterior descending and left circumflex artery. Under absence of collateral flow, microspheres outside of target perfusion territories were not found and the procedure did not generate false positive detection when spectral overlap was relevant. In silico-generated microspheres were used to test the effect of background image, transparency correction, and color separation. The percentage of microspheres undetected was 2.3 ± 0.8% in the presence and 1.5 ± 0.4% in the absence of background structures with a density of 900 microspheres per color per cm3. The image analysis method presented here, allows for an increased number of experimental conditions that can be investigated in studies of regional myocardial perfusion

Syndromic Surveillance for Local Outbreaks of Lower-Respiratory Infections: Would It Work?

Background: Although syndromic surveillance is increasingly used to detect unusual illness, there is a debate whether it is useful for detecting local outbreaks. We evaluated whether syndromic surveillance detects local outbreaks of lower-respiratory infections (LRIs) without swamping true signals by false alarms. Methods and Findings: Using retrospective hospitalization data, we simulated prospective surveillance for LRI-elevations. Between 1999–2006, a total of 290762 LRIs were included by date of hospitalization and patients place of residence (>80% coverage, 16 million population). Two large outbreaks of Legionnaires disease in the Netherlands were used as positive controls to test whether these outbreaks could have been detected as local LRI elevations. We used a space-time permutation scan statistic to detect LRI clusters. We evaluated how many LRI-clusters were detected in 1999–2006 and assessed likely causes for the cluster-signals by looking for significantly higher proportions of specific hospital discharge diagnoses (e.g. Legionnaires disease) and overlap with regional influenza elevations. We also evaluated whether the number of space-time signals can be reduced by restricting the scan statistic in space or time. In 1999–2006 the scan-statistic detected 35 local LRI clusters, representing on average 5 clusters per year. The known Legionnaires' disease outbreaks in 1999 and 2006 were detected as LRI-clusters, since cluster-signals were generated with an increased proportion of Legionnaires disease patients (p:<0.0001). 21 other clusters coincided with local influenza and/or respiratory syncytial virus activity, and 1 cluster appeared to be a data artifact. For 11 clusters no likely cause was defined, some possibly representing as yet undetected LRI-outbreaks. With restrictions on time and spatial windows the scan statistic still detected the Legionnaires' disease outbreaks, without loss of timeliness and with less signals generated in time (up to 42% decline). Conclusions: To our knowledge this is the first study that systematically evaluates the performance of space-time syndromic surveillance with nationwide high coverage data over a longer period. The results show that syndromic surveillance can detect local LRI-outbreaks in a timely manner, independent of laboratory-based outbreak detection. Furthermore, since comparatively few new clusters per year were observed that would prompt investigation, syndromic hospital-surveillance could be a valuable tool for detection of local LRI-outbreaks. (aut. ref.

Importance of snow and glacier meltwater for agriculture on the Indo-Gangetic Plain

Densely populated floodplains downstream of Asia’s mountain ranges depend heavily on mountain water resources, in particular for irrigation. An intensive and complex multi-cropping irrigated agricultural system has developed here to optimize the use of these mountain water resources in conjunction with monsoonal rainfall. Snow and glacier melt thereby modulate the seasonal pattern of river flows and, together with groundwater, provide water when rainfall is scarce. Climate change is expected to weaken this modulating effect, with potentially strong effects on food production in one of the world’s breadbaskets. Here we quantify the space-, time- and crop-specific dependence of agriculture in the Indo-Gangetic Plains on mountain water resources, using a coupled state-of-the-art, high-resolution, cryosphere–hydrology–crop model. We show that dependence varies strongly in space and time and is highest in the Indus basin, where in the pre-monsoon season up to 60% of the total irrigation withdrawals originate from mountain snow and glacier melt, and that it contributes an additional 11% to total crop production. Although dependence in the floodplains of the Ganges is comparatively lower, meltwater is still essential during the dry season, in particular for crops such as sugar cane. The dependency on meltwater in the Brahmaputra is negligible. In total, 129 million farmers in the Indus and Ganges substantially depend on snow and glacier melt for their livelihoods. Snow and glacier melt provides enough water to grow food crops to sustain a balanced diet for 38 million people. These findings provide important information for agricultural and climate change adaptation policies in a climate change hot spot where shifts in water availability and demand are projected as a result of climate change and socio-economic growth

FLNC missense variants in familial noncompaction cardiomyopathy

The majority of familial noncompaction cardiomyopathy (NCCM) is explained by pathogenic variants in the same sarcomeric genes that are associated with hypertrophic (HCM) and dilated (DCM) cardiomyopathy. Pathogenic variants in the filamin C gene (FLNC) have been linked to HCM and DCM. We expand the spectrum of FLNC related cardiomyopathies by presenting two families with likely pathogenic FLNC variants showing familial segregation of NCCM and concurrent coarctation of the aorta and/or mitral valve abnormalities

White Matter Lesions and Outcomes After Endovascular Treatment for Acute Ischemic Stroke:MR CLEAN Registry Results

BACKGROUND: Cerebral white matter lesions (WMLs) have been associated with a greater risk of poor functional outcome after ischemic stroke. We assessed the relations between WML burden and radiological and clinical outcomes in patients treated with endovascular treatment in routine practice. METHODS: We analyzed data from the MR CLEAN Registry (Multicenter Randomized Controlled Trial of Endovascular Treatment for Acute Ischaemic Stroke in the Netherlands)-a prospective, multicenter, observational cohort study of patients treated with endovascular treatment in the Netherlands. WMLs were graded on baseline noncontrast computed tomography using a visual grading scale. The primary outcome was the score on the modified Rankin Scale at 90 days. Secondary outcomes included early neurological recovery, successful reperfusion (extended Thrombolysis in Cerebral Infarction ≥2b), futile recanalization (modified Rankin Scale score ≥3 despite successful reperfusion), and occurrence of symptomatic intracranial hemorrhage. We used multivariable logistic regression models to assess associations between WML severity and outcomes, taking the absence of WML on noncontrast computed tomography as the reference category. RESULTS: Of 3180 patients included in the MR CLEAN Registry between March 2014 and November 2017, WMLs were graded for 3046 patients and categorized as none (n=1855; 61%), mild (n=608; 20%), or moderate to severe (n=588; 19%). Favorable outcome (modified Rankin Scale score, 0-2) was achieved in 838 patients (49%) without WML, 192 patients (34%) with mild WML, and 130 patients (24%) with moderate-to-severe WML. Increasing WML grades were associated with a shift toward poorer functional outcome in a dose-dependent manner (adjusted common odds ratio, 1.34 [95% CI, 1.13-1.60] for mild WML and 1.67 [95% CI, 1.39-2.01] for moderate-to-severe WML; Ptrend, <0.001). Increasing WML grades were associated with futile recanalization (Ptrend, <0.001) and were inversely associated with early neurological recovery (Ptrend, 0.041) but not with the probability of successful reperfusion or symptomatic intracranial hemorrhage. CONCLUSIONS: An increasing burden of WML at baseline is associated with poorer clinical outcomes after endovascular treatment for acute ischemic stroke but not with the probability of successful reperfusion or symptomatic intracranial hemorrhage