Advanced oxidation to eliminate growth inhibition and to degrade plant protection products in a recirculating nutrient solution in Rose cultivation

The EU Water Framework Directive demands a sound ecological and chemical basis for ground and surface waters. This has motivated the Dutch greenhouse industry to seek more sustainable water management procedures which will enable a zero-emission of nutrients and plant protection products (PPP) in the year 2027. Although closed soilless growing systems are widely applied in The Netherlands, it appears that discharge of nutrients varies between 5 and 40%. Discharge based on salinity is only a minor part, up to 15%. In rose cultivation, growth inhibition is the major reason for discharge of the nutrient solution. Former research could not find a proper reason for growth inhibition, but it is most likely of organic origin. The water treatment method of advanced oxidation, at which first hydrogen peroxide is added, directly followed by an exposure to UV-C light (200-280 nm), is known to degrade large organic molecules. Therefore this method has been investigated to eliminate growth inhibition and also to degrade PPPs. Among all methods advanced oxidation has been a first choice because many rose growers already possess a UV installation for elimination of pathogens from the recirculating solution. Trials with advanced oxidation have been performed at two rose nurseries at which the dosages of hydrogen peroxide (0-25 mg/L) and UV lighting (0-900 mJ/cm2) have been varied to search for indications for elimination of growth inhibition and the degradation of PPPs. After treatment samples were taken to test for growth inhibition of the solution in a bioassay, Phytotoxkit; the chemical composition; the residual amount of PPPs and the presence of micro-organisms. Preliminary results show that (1) growth inhibition exists and can be decreased, (2) plant protection products can be degraded, (3) pathogens have been eliminated and (4) composition of the nutrient solution is unchanged except for iron

The Infrared Behaviour of the Pure Yang-Mills Green Functions

We review the infrared properties of the pure Yang-Mills correlators and discuss recent results concerning the two classes of low-momentum solutions for them reported in literature; i.e. decoupling and scaling solutions. We will mainly focuss on the Landau gauge and pay special attention to the results inferred from the analysis of the Dyson-Schwinger equations of the theory and from "{\it quenched}" lattice QCD. The results obtained from properly interplaying both approaches are strongly emphasized.Comment: Final version to be published in FBS (54 pgs., 11 figs., 4 tabs

Clinical Trials in Head Injury

Traumatic brain injury (TBI) remains a major public health problem globally. In the United States the incidence of closed head injuries admitted to hospitals is conservatively estimated to be 200 per 100,000 population, and the incidence of penetrating head injury is estimated to be 12 per 100,000, the highest of any developed country in the world. This yields an approximate number of 500,000 new cases each year, a sizeable proportion of which demonstrate signficant long-term disabilities. Unfortunately, there is a paucity of proven therapies for this disease. For a variety of reasons, clinical trials for this condition have been difficult to design and perform. Despite promising pre-clinical data, most of the trials that have been performed in recent years have failed to demonstrate any significant improvement in outcomes. The reasons for these failures have not always been apparent and any insights gained were not always shared. It was therefore feared that we were running the risk of repeating our mistakes. Recognizing the importance of TBI, the National Institute of Neurological Disorders and Stroke (NINDS) sponsored a workshop that brought together experts from clinical, research, and pharmaceutical backgrounds. This workshop proved to be very informative and yielded many insights into previous and future TBI trials. This paper is an attempt to summarize the key points made at the workshop. It is hoped that these lessons will enhance the planning and design of future efforts in this important field of research.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63185/1/089771502753754037.pd

Quality indicators for patients with traumatic brain injury in European intensive care units

Background: The aim of this study is to validate a previously published consensus-based quality indicator set for the management of patients with traumatic brain injury (TBI) at intensive care units (ICUs) in Europe and to study its potential for quality measur

Changing care pathways and between-center practice variations in intensive care for traumatic brain injury across Europe

Purpose: To describe ICU stay, selected management aspects, and outcome of Intensive Care Unit (ICU) patients with traumatic brain injury (TBI) in Europe, and to quantify variation across centers. Methods: This is a prospective observational multicenter study conducted across 18 countries in Europe and Israel. Admission characteristics, clinical data, and outcome were described at patient- and center levels. Between-center variation in the total ICU population was quantified with the median odds ratio (MOR), with correction for case-mix and random variation between centers. Results: A total of 2138 patients were admitted to the ICU, with median age of 49 years; 36% of which were mild TBI (Glasgow Coma Scale; GCS 13–15). Within, 72 h 636 (30%) were discharged and 128 (6%) died. Early deaths and long-stay patients (> 72 h) had more severe injuries based on the GCS and neuroimaging characteristics, compared with short-stay patients. Long-stay patients received more monitoring and were treated at higher intensity, and experienced worse 6-month outcome compared to short-stay patients. Between-center variations were prominent in the proportion of short-stay patients (MOR = 2.3, p < 0.001), use of intracranial pressure (ICP) monitoring (MOR = 2.5, p < 0.001) and aggressive treatme

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations