Search

Addressing the issue of shrinking saline lakes around the globe has turned into one of the most pressing issues for sustainable water resource management. While it has been established that natural climate variability, human interference, climate change, or a combination of these factors can lead to the depletion of saline lakes, it is crucial to investigate each case and diagnose the potential causes of this devastating phenomenon. On that note, this study aims to promote a comprehensive analytical framework that can reveal any significant depletion patterns in lakes while analyzing the potential reasons behind these observed changes. The methodology used in this study is based on statistical analysis, data mining techniques, and remote sensing-based datasets. To achieve the objective of this study, Maharlou Lake has been selected to demonstrate the application of the proposed framework. The results revealed two types of depletion patterns in the lake’s surface area: a sharp breaking point in 2007/2008 and a gradual negative trend, which was more pronounced in dry seasons and less prominent in wet seasons. Furthermore, the analysis of hydro-climatic variables has indicated the presence of abrupt and gradual changes in these variables’ time series, which could be interpreted as a signal that climate change and anthropogenic drought are changing the basin’s status quo. Lastly, analyzing the statistically significant correlation between hydro-climatic variables and the lake’s surface area showed the potential connection between the observed changing patterns. The results obtained from data mining models suggest that Maharlou Lake has undergone a morphological transformation and is currently adopting these new conditions. If preventive measures are not taken to revive Maharlou Lake, the tipping point might have been reached, and reviving the lake could be improbable, if not impossible.

Boron (B) is a plant nutrient and a limited mineral resource. Therefore, secondary B sources such as end-of-life cellulose fiber insulation (CFI) should be preferred for B fertiliser production over primary borates. In addition, crop B fertilisation is challenging because B is only weakly adsorbed in soils and prone to leaching in particular if the soil pH is below 7. The objectives of this study were to assess the effect of pyrolysed CFI (B-Biochar) on crop B uptake in the field and on B leaching in a lysimeter study. B-Biochar was pyrolysed at 600 °C and tested (1) in a field experiment with maize (Zea mays L.) and sunflower (Helianthus annuus L.), and (2) in a lab microlysimeter experiment to study B leaching under simulated rainfall. In the field experiment, B concentration in plant tissue increased by up to 100% with B-Biochar compared to the control (from 29.6 to 61.6 mg B/kg in young sunflower leaves) and was only slightly lower (-10% to -20%) than with water-soluble Na-tetraborate (Borax). This lower uptake was attributed to the slow-release properties of the B-Biochar. In the lysimeter experiment, 41% and 55% of added B through B-Biochar was leached below 16 cm depth when fertilised with 1 and 2 kg B/ha, respectively, but B concentration of the leachate remained below the 1 mg B/L threshold value for drinking water in the European Union. In conclusion, CFI has a strong potential as a secondary B source for fertiliser production, and pyrolysis appears to be a suitable process for that purpose. During the processing of CFI to fertiliser, more focus should be given to slow B release in the future in order to reduce losses by leaching.

Simple Summary: This multicenter study (n = 1133, inclusion criteria: 3.5 cm maximum tumor size and preoperative indication for a boost) provides detailed data on acute and long-term toxicities in breast cancer patients undergoing breast-conserving surgery combined with an anticipated intraoperative boost with low-energy X-rays followed by whole breast irradiation. Toxicity assessments, based on LENT SOMA criteria, were performed annually up to 10 years of follow-up. IORT boost was completed in 90% and EBRT in 97% of cases. No grade 3 or 4 acute toxicities were observed, with mild acute side effects reported in a small proportion of patients. Chronic toxicities were seen in 16.2% of patients with teleangiectasia, 14.3% with grade ≥ 2 fibrosis, 3.4% with grade ≥ 2 pain, and 1.1% with hyperpigmentation. The results show that the therapy is safe and feasible in terms of toxicity and confirms intraoperative boost as a standard method of boost application in a large prospective cohort. In the context of breast cancer treatment optimization, this study prospectively examines the feasibility and outcomes of utilizing intraoperative radiotherapy (IORT) as a boost in combination with standard external beam radiotherapy (EBRT) for high-risk patients. Different guidelines recommend such a tumor bed boost in addition to whole breast irradiation with EBRT for patients with risk factors for local breast cancer recurrence. The TARGIT BQR (NCT01440010) is a prospective, multicenter registry study aimed at ensuring the quality of clinical outcomes. It provides, for the first time, data from a large cohort with a detailed assessment of acute and long-term toxicity following an IORT boost using low-energy X-rays. Inclusion criteria encompassed tumors up to 3.5 cm in size and preoperative indications for a boost. The IORT boost, administered immediately after tumor resection, delivered a single dose of 20 Gy. EBRT and systemic therapy adhered to local tumor board recommendations. Follow-up for toxicity assessment (LENT SOMA criteria: fibrosis, teleangiectasia, retraction, pain, breast edema, lymphedema, hyperpigmentation, ulceration) took place before surgery, 6 weeks to 90 days after EBRT, 6 months after IORT, and then annually using standardized case report forms (CRFs). Between 2011 and 2020, 1133 patients from 10 centers were preoperatively enrolled. The planned IORT boost was conducted in 90%, and EBRT in 97% of cases. Median follow-up was 32 months (range 1–120, 20.4% dropped out), with a median age of 61 years (range 30–90). No acute grade 3 or 4 toxicities were observed. Acute side effects included erythema grade 1 or 2 in 4.4%, palpable seroma in 9.1%, punctured seroma in 0.3%, and wound healing disorders in 2.1%. Overall, chronic teleangiectasia of any grade occurred in 16.2%, fibrosis grade ≥ 2 in 14.3%, pain grade ≥ 2 in 3.4%, and hyperpigmentation in 1.1%. In conclusion, a tumor bed boost through IORT using low-energy X-rays is a swift and feasible method that demonstrates low rates in terms of acute or long-term toxicity profiles in combination with whole breast irradiation. [ABSTRACT FROM AUTHOR]

Objectives: Coronavirus disease 2019 (COVID-19) represents a major pandemic threat that has spread to more than 212 countries with more than 432,902 recorded deaths and 7,898,442 confirmed cases worldwide so far (on June 14, 2020). It is crucial to investigate the spatial drivers to prevent and control the epidemic of COVID-19. Methods: This is the first comprehensive study of COVID-19 in Iran; and it carries out spatial modeling, risk mapping, change detection, and outbreak trend analysis of the disease spread. Four main steps were taken: comparison of Iranian coronavirus data with the global trends, prediction of mortality trends using regression modeling, spatial modeling, risk mapping, and change detection using the random forest (RF) machine learning technique (MLT), and validation of the modeled risk map. Results: The results show that from February 19 to June 14, 2020, the average growth rates (GR) of COVID-19 deaths and the total number of COVID-19 cases in Iran were 1.08 and 1.10, respectively. Based on the World Health Organisation (WHO) data, Iran’s fatality rate (deaths/0.1 M pop) is 10.53. Other countries’ fatality rates were, for comparison, Belgium – 83.32, UK – 61.39, Spain – 58.04, Italy – 56.73, Sweden – 48.28, France – 45.04, USA – 35.52, Canada – 21.49, Brazil – 20.10, Peru – 19.70, Chile – 16.20, Mexico– 12.80, and Germany – 10.58. The fatality rate for China is 0.32 (deaths/0.1 M pop). Over time, the heatmap of the infected areas identified two critical time intervals for the COVID-19 outbreak in Iran. The provinces were classified in terms of disease and death rates into a large primary group and three provinces that had critical outbreaks were separate from the others. The heatmap of countries of the world shows that China and Italy were distinguished from other countries in terms of nine viral infection-related parameters. The regression models for death cases showed an increasing trend but with some evidence of turning. A polynomial relationship was identified between the coronavirus infection rate and the province population density. Also, a third-degree polynomial regression model for deaths showed an increasing trend recently, indicating that subsequent measures taken to cope with the outbreak have been insufficient and ineffective. The general trend of deaths in Iran is similar to the world's, but Iran’s shows lower volatility. Change detection of COVID-19 risk maps with a random forest model for the period from March 11 to March 18 showed an increasing trend of COVID-19 in Iran’s provinces. It is worth noting that using the LASSO MLT to evaluate variables’ importance, indicated that the most important variables were the distance from bus stations, bakeries, hospitals, mosques, ATMs (automated teller machines), banks, and the minimum temperature of the coldest month. Conclusions: We believe that this study's risk maps are the primary, fundamental step to take for managing and controlling COVID-19 in Iran and its provinces.

Self-assembled molecular capsules, host structures that form spontaneously when their building blocks are mixed, have been known since the 1990s. They share some basic similarities with enzyme pockets, as they feature defined hydrophobic binding pockets that are able to bind molecules of appropriate size and shape. The potential to utilize such host structures for catalysis has been explored since their discovery; however, applications that solve current challenges in synthetic organic chemistry have remained limited. In this short article, we discuss the challenges associated with the use of molecular capsules as catalysts, and highlight some recent applications of supramolecular capsules to overcome challenges in synthetic organic chemistry.

Natural hazards are often studied in isolation. However, there is a great need to examine hazards holistically to better manage the complex of threats found in any region. Many regions of the world have complex hazard landscapes wherein risk from individual and/or multiple extreme events is omnipresent. Extensive parts of Iran experience a complex array of natural hazards – floods, earthquakes, landslides, forest fires, subsidence, and drought. The effectiveness of risk mitigation is in part a function of whether the complex of hazards can be collectively considered, visualized, and evaluated. This study develops and tests individual and collective multi-hazard risk maps for floods, landslides, and forest fires to visualize the spatial distribution of risk in Fars Province, southern Iran. To do this, two well-known machine-learning algorithms – SVM and MARS – are used to predict the distribution of these events. Past floods, landslides, and forest fires were surveyed and mapped. The locations of occurrence of these events (individually and collectively) were randomly separated into training (70%) and testing (30%) data sets. The conditioning factors (for floods, landslides, and forest fires) employed to model the risk distributions are aspect, elevation, drainage density, distance from faults, geology, LULC, profile curvature, annual mean rainfall, plan curvature, distance from man-made residential structures, distance from nearest river, distance from nearest road, slope gradient, soil types, mean annual temperature, and TWI. The outputs of the two models were assessed using receiver-operating-characteristic (ROC) curves, true-skill statistics (TSS), and the correlation and deviance values from each models for each hazard. The areas-under-the-curves (AUC) for the MARS model prediction were 76.0%, 91.2%, and 90.1% for floods, landslides, and forest fires, respectively. Similarly, the AUCs for the SVM model were 75.5%, 89.0%, and 91.5%. The TSS reveals that the MARS model was better able to predict landslide risk, but was less able to predict flood-risk patterns and forest-fire risk. Finally, the combination of flood, forest fire, and landslide risk maps yielded a multi-hazard susceptibility map for the province. The better predictive model indicated that 52.3% of the province was at-risk for at least one of these hazards. This multi-hazard map may yield valuable insight for land-use planning, sustainable development of infrastructure, and also integrated watershed management in Fars Province.

This study examines the relations of structures and shapes of streambed evolution after dam break floods. A flume was used to simulate dam-break floods with variations of initial upstream water levels and variance, from uniform to graded, of the bed sediments. Detailed measurements of the evolution and composition were made during these experiments. The data indicate that intense scour occurred immediately downstream of the “dam break” in both uniform and graded sediments. The resulting bed surfaces of graded sediments showed coarse-fine-coarse structures in the areas with the lowest scour and highest deposition and various type of cluster (i.e. line and heap). This pattern was not observed in beds of uniform sediment. The scour hole changes from circular to oval-shaped in both uniform and graded sediments with increasing bed slopes. Keywords: Dam break, Experimental, Bed-surface composition, Graded and uniform sediment, Scour.

Copyright of Anaesthesiologie & Intensivmedizin is the property of DGAI e.V. - Deutsche Gesellschaft fur Anasthesiologie und Intensivmedizin e.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)