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BACKGROUND: Few clinical studies have addressed nutritional risk assessment in patients with COVID-19 pneumonia admitted to the intensive care unit (ICU). OBJECTIVES: Assess the nutritional risk status of the critically ill COVID-19 pneumonia patients admitted to the ICU, and compare the nutritional risk screening tools. DESIGN: Medical record review SETTING: Tertiary critical care unit PATIENTS AND METHODS: We included adult (age >18 years) PCR-confirmed critically ill COVID-19 pneumonia cases admitted to the ICU between August 2020 and September 2021. Scoring systems were used to assess COVID-19 severity and nutritional status (mNUTRIC: modified Nutrition Risk in Critically Ill, NRS2002: Nutritional Risk Screening 2002). The 30-day mortality prediction performance of nutritional scores and survival comparisons between clinical and demographic factors were assessed. MAIN OUTCOME MEASURES: Compare the nutrition risk tools SAMPLE SIZE: 281 patients with a mean (SD) age of 64.3 (13.3) years; 143 (50.8%) were 65 years and older. RESULTS: The mean mNUTRIC score of the cases was 3.81 (1.66) and the mean NRS-2002 score was 3.21 (0.84.), and 101 (35.9%) were at high risk of malnutrition according to the mNUTRIC score and 229 (81.4%) according to the NRS 2002 score. In cases at high risk of malnutrition by the mNUTRIC score there was a greater need for invasive mechanical ventilation, vasopressors, and renal replacement therapy (P

Background: The novel coronavirus disease 2019 (COVID-19) has a broad spectrum of clinical manifestations, the most common serious clinical manifestation of the coronavirus infection being pneumonia. Unfortunately, the optimal treatment approach is still uncertain. However, many studies have been conducted on the effectiveness of several medications in the treatment of COVID-19 infection. The aim of this study was to evaluate the effectiveness of the hydroxychloroquine (HCQ) + favipiravir (FAV) treatment regimen and HCQ alone by comparing the patient’s clinical response and laboratory results on the fifth day of treatment in patients hospitalized due to COVID-19 infection. Patients and methods: This retrospective cohort study was conducted in Malatya Training and Research Hospital between March 2020 and July 2020. The study included 69 patients with confirmed COVID-19 with pneumonia. The patients were divided into 2 groups, those receiving HCQ alone and those receiving the HCQ + FAV combination. Results: A total of 69 patients were included in the study, and the mean age was 60.09±15.56 years. A statistically significant decrease was observed in C-reactive protein (CRP) levels, at the end of the fifth day, in patients who received HCQ + FAV treatment (p=0.002), whereas there was no decrease in CRP levels in patients who received HCQ treatment alone. In addition, an increase in lymphocyte count and a better fever response was observed at the end of the fifth day in patients who received HCQ + FAV (p=0.008). However, there was no statistical difference between both treatment regimens in terms of hospital stay and treatment results (p=0.008, p=0.744, p=0.517). Conclusion: Although the combination of HCQ + FAV treatment was observed to be effective on CRP levels and fever response in patients with COVID-19 pneumonia, there was no difference in terms of hospital stay and discharge.

Increasing light extraction efficiency and narrowing the angular spread of light emitted from optically thick light emitting diodes (LEDs) are desirable but difficult goals to achieve. In this paper, we design, optimize, and fabricate Vogel spiral arrays of dielectric nanostructures for optical directional extraction enhancement of incoherent emission from optically thick phosphor-converted LEDs. In order to design and optimize large-scale structures, we perform a systematic numerical investigation based on full-vector three-dimensional finite difference time domain simulations using a cloud of randomly positioned and randomly phased dipoles that approximate an incoherent Lambertian source. An analytical model based on kinematic scattering is also developed and used to parametrically study changes in the emission profile as the spiral geometry is tuned. The optimal Vogel spiral arrays are fabricated as TiO2 nanodisks atop YAG:Ce3+ blue-to-white converter layers using electron-beam lithography and reactive ion etching. Photoluminescence spectroscopy is used to experimentally measure extraction enhancement up to 2× compared to a flat reference. Finally, accurate Fourier-space (k-space) fluorescence spectroscopy is used to measure the emission intensity profile up to 54° in a single snapshot image, and we find up to a 35% enhancement in power-normalized forward emission compared to a flat reference, under remote laser excitation. The integration of optimized Vogel spiral arrays of dielectric nanoparticles with phosphor-converted LEDs will increase efficiency and narrow the directional spread of light. These effects are beneficial to a variety of active device applications, including imaging, lighting, and projecting devices that require enhanced extraction efficiency combined with directional emission.

Abstract Drought is deemed a major natural disaster that can lead to severe economic and social implications. Drought indices are utilized worldwide for drought management and monitoring. However, as a result of the inherent complexity of drought phenomena and hydroclimatic condition differences, no universal drought index is available for effectively monitoring drought across the world. Therefore, this study aimed to develop a new meteorological drought index to describe and forecast drought based on various artificial intelligence (AI) models: decision tree (DT), generalized linear model (GLM), support vector machine, artificial neural network, deep learning, and random forest. A comparative assessment was conducted between the developed AI-based indices and nine conventional drought indices based on their correlations with multiple drought indicators. Historical records of five drought indicators, namely runoff, along with deep, lower, root, and upper soil moisture, were utilized to evaluate the models’ performance. Different combinations of climatic datasets from Alice Springs, Australia, were utilized to develop and train the AI models. The results demonstrated that the rainfall anomaly drought index was the best conventional drought index, scoring the highest correlation (0.718) with the upper soil moisture. The highest correlation between the new and conventional indices was found between the DT-based index and the rainfall anomaly index at a value of 0.97, whereas the lowest correlation was 0.57 between the GLM and the Palmer drought severity index. The GLM-based index achieved the best performance according to its high correlations with conventional drought indicators, e.g., a correlation coefficient of 0.78 with the upper soil moisture. Overall, the developed AI-based drought indices outperformed the conventional indices, hence contributing effectively to more accurate drought forecasting and monitoring. The findings emphasized that AI can be a promising and reliable prediction approach for achieving better drought assessment and mitigation.

Abstract Sediment and nutrient pollution in water bodies is threatening human health and the ecosystem, due to rapid land use changes and improper agricultural practices. The impact of the nonpoint source pollution needs to be evaluated for the sustainable use of water resources. An ideal tool like the soil and water assessment tool (SWAT) can assess the impact of pollutant loads on the drainage area, which could be beneficial for developing a water quality management model. This study aims to evaluate the SWAT model’s multi-objective and multivariable calibration, validation, and uncertainty analysis at three different sites of the Yarra River drainage area in Victoria, Australia. The drainage area is split into 51 subdrainage areas in the SWAT model. The model is calibrated and validated for streamflow from 1990 to 2008 and sediment and nutrients from 1998 to 2008. The results show that most of the monthly and annual calibration and validation for streamflow, nutrients, and sediment at the three selected sites are found with Nash–Sutcliffe efficiency values greater than 0.50. Furthermore, the uncertainty analysis of the model shows satisfactory results where the p-factor value is reliable by considering 95% prediction uncertainty and the d-factor value is close to zero. The model's results indicate that the model performs well in the river's watershed, which helps construct a water quality management model. Finally, the model application in the cost-effective management of water quality might reduce pollution in water bodies due to land use and agricultural activities, which would be beneficial to water management managers.

This paper explores different methods of computing backwater depth for open-channel flow, such as one- to multi-dimensional models, finite difference approaches, and artificial intelligence methods. This paper primarily focuses on one-dimensional methods and states the implication, advantages, and disadvantages, verification process, and performance of each method. This paper discusses different parameters that influence backwater and their impact. Additionally, this paper compares the discussed one-dimensional methods with each other due to their common usage of experimental and field datasets as well as their popularity in implementation. It was concluded that while the WSPRO method significantly overestimated and the Yarnell’s method underestimated the afflux value, the measured afflux values are closest to the values computed by the energy and momentum methods.

In recent years, there has been a significant surge in interest in studies related to fractional calculus and its applications. Fractional-order analysis holds the potential to enhance the dynamic structure of chaotic systems. This study focuses on the dynamic analysis of the Chen system with low fractional-order values and its fractional-order electronic circuit. Notably, there is a lack of studies about chaotic electronic circuits in the literature with a fractional-order parameter value equal to 0.8, which makes this study pioneering in this regard. Moreover, various numerical analyses are presented to investigate the system's dynamic characteristics and complexity, such as chaotic phase planes and bifurcation diagrams. As anticipated, the voltage outputs obtained from PSpice simulations demonstrated good agreement with the numerical analysis.

Climate change impacts have the potential to alter the design rainfall estimates around the world. Decreasing trends in the summer and winter rainfall in New South Wales (NSW), Australia have already been observed due to climate variability and change. The derivation of design rainfall from historical rainfall, which is required for the design of stormwater management infrastructure, may be ineffective and costly. It is essential to consider climate change impacts in estimating design rainfall for the successful design of stormwater management infrastructure. In this study, the probability of the occurrence of daily extreme rainfall has been assessed under climate change conditions. The assessment was performed using data from 29 meteorological stations in NSW, Australia. For the evaluation of future design rainfall, the probability of the occurrence of extreme rainfall for different recurrence intervals was developed from daily extreme rainfall for the periods of 2020 to 2099 and compared with the current Australian Bureau of Meteorology (BoM) design rainfall estimates. The historical mean extreme rainfall across NSW varied from 37.71 mm to 147.3 mm, indicating the topographic and climatic influences on extreme rainfall. The outcomes of the study suggested that the future design rainfall will be significantly different from the current BoM estimates for most of the studied stations. The comparison of the results showed that future rainfall in NSW will change from −4.7% to +60% for a 100-year recurrence interval. However, for a 2-year recurrence interval, the potential design rainfall change varies from an approximately 8% increase to a 40% decrease. This study revealed that the currently designed stormwater management infrastructure will be idle in the changing climate.

Measurement(s) social innovation projects Technology Type(s) natural language processing objective Factor Type(s) Project Scores (four variables) • Project Location • Project Topic • Project Summary • Project URL • Project Source Sample Characteristic - Organism N/A Sample Characteristic - Environment social innovation system Sample Characteristic - Location global

Objective:The prognostic role of the initial lactate/albumin ratio (LAR) in critically ill patients with coronavirus disease-2019 (COVID-19) remains unknown. This study aimed to evaluate the prognostic value of the initial LAR in predicting 30-day mortality in critically ill patients with COVID-19 and compare the initial level of serum lactate and albumin for mortality prediction.Materials and Methods:A single-center and observational clinical study between April 2020 and December 2020 were retrospectively performed. Clinical and laboratory variables of patients evaluated in this study were collected within the first 24 hours following the intensive care unit (ICU) admission.Results:A total of 282 critically ill patients with COVID-19 were included in the study. The mean age of the patients was 66.34±12.08 years, wherein 179 (63.5%) were male. Patients who died within 30 days had higher lactate (p0.60.Conclusion:LAR is a useful prognostic factor for risk stratification of critically ill patients with COVID-19.

This study investigated the effectiveness of removing pollutants from roof-collected rainwater through rainwater tank, filtration using recycled foam glass and geofabrics using series of laboratory experiments. It is found that rainwater tank itself helps to remove some pollutants, especially total suspended solids (TSS). To test the efficiency of recycled foam glass as filter material, the material was used to filter rainwater collected from roof. It is found that through such filtration most of the pollutants’ concentrations in the rainwater drop by about 50%. Also, removal efficiency of a 30 cm filter media is about double compared to a filter media of 10 cm height. However, concentrations of Suspended Solids, Copper and Lead in the filtered samples were higher than the concentrations in the raw sample, which might be due to leaching of pollutants from filter media as it is found that higher the filter depth, higher the pollutants concentrations in the filtrate. To overcome these pollutants’ leaching, similar experiments conducted with geotextile layer at the bottom of the filter material revealed that through the use of geotextile layer with 30 cm filter media, significant reductions of pollutants are achievable including an 87% removal in number of Faecal Coliforms.

Most of the studies on rainwater harvesting analysis present the outcomes for particular cities, representing a single set of results for a specific city. However, in reality, significant spatial and weather variabilities may exist, due to which presenting only one set of results for a particular city would be misleading. This paper presents the potential weather and spatial variabilities on the expected water savings and supply reliability through the domestic rainwater tank for an inland city. An earlier-developed daily water balance model, eTank, was used for the calculations of annual water savings and reliability. An Australian inland city, Canberra, was selected as a case study and relevant daily rainfall data were collected from the Australian Bureau of Meteorology website. For the analysis of spatial variation, two rain gauge stations within the city of Canberra were selected. For each station, from the historical data, three years were selected as dry, average and wet years. For each weather condition, annual water savings and reliabilities were calculated for different demands with different tank sizes up to 10,000 L connected with different roof sizes. Then, variations in annual water savings and reliabilities among different weather conditions, as well as among different stations, were evaluated. It was found that, with regard to annual water savings, a maximum variation of 68.6% can be expected between dry and wet weather; however, only a 15.4% maximum spatial variation is expected among the selected stations. Regarding reliability, a maximum variation of 123% is expected between dry and wet weather. Whereas, only a 17% spatial variation is expected among the selected stations. Such a study will provide valuable insights for rainwater tank users and stakeholders on potential variabilities due to weather and spatial differences.

Interest in studies on fractional calculus and its applications has greatly increased in recent years. Fractional-order analysis has the potential to enhance the dynamic structure of chaotic systems. This study presents the implementation of a lower-order fractional electronic circuit using standard components for the Sprott K system. To our knowledge, there are no chaotic circuit realizations in the literature where the value of a fractional-order parameter is approximately 0.8, making this study pioneering in this aspect. Additionally, various numerical analyses of the system are conducted, including chaotic time series and phase planes, Lyapunov exponents, spectral entropy (SE), and bifurcation diagrams, in order to examine its dynamic characteristics and complexity. As anticipated, the voltage outputs obtained from the oscilloscope demonstrated good agreement with both the numerical analysis and PSpice simulations.

This paper presents potential upgrades to the Palm Jumeirah Island’s outer revetment to extend its design life for 50 years, considering the sea level rise (SLR) associated with climate change. The paper proposes several upgrade options to ensure that the hydraulic stability and wave overtopping discharges of the Palm Jumeirah revetment comply with the recommended design criteria based on industry guidelines. The performance of the existing revetment, in terms of the hydraulic stability and wave overtopping discharge criteria, is assessed using design wave heights (1- and 100-year events) extracted from an extreme wave analysis study on the Dubai coast. The results show that, based on the new design conditions, the existing structure should be upgraded to meet the armor stability criteria and recommended overtopping discharge values. Three different upgrade solutions are designed and analyzed to satisfy the required hydraulic stability and overtopping conditions. The suggested upgrade options are an extra armor layer, a flat berm, and a submerged breakwater offshore. The proposed upgrade solutions are preliminary designs that would require verification in terms of their geotechnical stability and physical model testing to evaluate their performance.

The detection of leakages in Water Distribution Networks (WDNs) is usually challenging and identifying their locations may take a long time. Current water leak detection methods such as model-based and measurement-based approaches face significant limitations that impact response times, resource requirements, accuracy, and location identification. This paper presents a method for determining locations in the WDNs that are vulnerable to leakage by combining six leakage-conditioning factors using logistic regression and vulnerability analysis. The proposed model considered three fixed physical factors (pipe length per junction, number of fittings per length, and pipe friction factor) and three varying operational aspects (drop in pressure, decrease in flow, and variations in chlorine levels). The model performance was validated using 13 district metered areas (DMAs) of the Sharjah Electricity and Water Authority (SEWA) WDN using ArcGIS. Each of the six conditioning factors was assigned a weight that reflects its contribution to leakage in the WDNs based on the Analytic Hierarchy Process (AHP) method. The highest weight was set to 0.25 for both pressure and flow, while 0.2 and 0.14 were set for the chlorine and number of fittings per length, respectively. The minimum weight was set to 0.08 for both length per junction and friction factor. When the model runs, it produces vulnerability to leakage maps, which indicate the DMAs’ vulnerability classes ranging from very high to very low. Real-world data and different scenarios were used to validate the method, and the areas vulnerable to leakage were successfully identified based on fixed physical and varying operational factors. This vulnerability map will provide a comprehensive understanding of the risks facing a system and help stakeholders develop and implement strategies to mitigate the leakage. Therefore, water utility companies can employ this method for corrective maintenance activities and daily operations. The proposed approach can offer a valuable tool for reducing water production costs and increasing the efficiency of WDN.

This paper aims to present the result of commonly used extreme wave analysis distribution methods applied to a long-term wave hindcast at a point in the Arabian Gulf near the coastline of Dubai, United Arab Emirates. The wave data were hindcasted for a total period of 40 years, starting from 1 January 1979 to 31 December 2018. This analysis aims to support the design, repair, and maintenance of coastal structures near the Dubai coast. A 2.5 m threshold is selected using the Peak Over Threshold method to filter the storm data for the extreme wave analysis. Different distribution methods are used for this analysis such as Log-normal, Gumbel, Weibull, Exponential, and Generalized Pareto Distribution (GPD). The significant wave heights are predicted for different return periods. The GPD distribution appears to fit the data best compared to the other distribution methods. Many coastal projects are being planned near the Dubai coastline. Hence, the analysis presented in this paper would be useful in designing safe and efficiently designed projects.

Due to accurate capability to detect weak signal, chaotic oscillators have become an interesting topic for many scientific researches. In this paper, two hyperchaotic Lorenz systems are presented to detect weak signal. These systems are chosen because of their parametric variety and high applicability. Dynamic behaviors of two hyperchaotic systems are analysed in detail. For this purpose, the Lyapunov exponent values and bifurcation behaviours of two hyperchaotic systems are analysed for weak signal detection applications. The relationship between the system state and the amplitude of the weak signal is defined by examining the Lyapunov exponents of the system. So, dynamic characteristics of two chaotic oscillators are observed by this way. The critical chaotic parametric threshold value of a chaotic system is easily determined by the bifurcation analysis. The bifurcation threshold value named as tangent bifurcation point is the most suitable one to detect weak signal. For this purpose, the tangent bifurcation points of these systems are determined via bifurcation analysis. Additionally, weak signal detection applications of two hyperchaotic systems are also studied. The applicability of the proposed systems is shown by these applications. These systems also detect the weak signal with low signal to noise ratio (SNR). Simulation results obtained from Matlab-Simulink® program verify the studied method.

Whitings, the manifestation of high levels of suspended fine-grained calcium carbonate particles in the water, have been reported and studied worldwide. However, the triggering mechanism of whiting occurrences remains uncertain. The current study attempted to analyze potential factors that might account for whiting occurrences in a semi-enclosed gulf (namely the Arabian/Persian Gulf, hereinafter called the Gulf). First, spatial and temporal variability of whiting events and different potential driving factors (i.e., whiting seasonality, wind-induced mixing, sea surface temperature, and bathymetry) were explored and examined for five years (2015–2020). Second, as a general indicator of whiting occurrences in the Gulf, a whiting index (WI) was developed using time-series analysis and decision tree (DT) classification algorithm. Third, the correlation between the proposed WI and the spatial coverage of various whiting events was examined. Time-series analysis showed that whiting events during the winter season are associated with high winds that lasted for several days. Nevertheless, whiting events were rarely observed despite high wind speed and increased potential for CaCO3 precipitation in summer. This finding suggests that wind-driven forces might be potential sources for mixing water columns, resuspension of CaCO3 particles, and the appearance of whiting in the Gulf. The DT classification algorithm demonstrated that a minimum WI value of 1.1 can explain the initiation of most summer and winter whiting events. Furthermore, a Pearson correlation coefficient of 0.73 was measured between WI and the extent of whiting along the UAE and Qatar coastlines in the Gulf. The proposed WI shows a simple yet effective method for identifying and estimating the extent of whiting in the Gulf.

Climate change has significant effects on societies and ecosystems. Due to the strong link between climate and the hydrological cycle, water resources is one of the most affected fields by climate change. It is of great importance to investigate climate change effects on streamflows by producing future streamflow projections under different scenarios to create adaptation measures and mitigate potential impacts of climate change. The Upper Campaspe Catchment (UCC), located at North Central Victoria in Australia, is a significant catchment as it provides a large portion of total inflow to the Lake Eppalock Reservoir, which supplies irrigation to the Campaspe Irrigation district and urban water to Bendigo, Heathcote, and Ballarat cities. In this study, climate change effects on monthly streamflows in the UCC was investigated using high resolution future climate data from CSIRO and MIROC climate models in calibrated IHACRES hydrological model. The IHACRES model was found to be very successful to simulate monthly streamflow in UCC. Remarkable streamflow reductions were projected based on the climate input from both models (CSIRO and MIROC). According to the most optimistic scenario (with the highest projected streamflows) by the MIROC-RCP4.5 model in near future (2035–2064), the Upper Campaspe River will completely dry out from January to May. The worst scenario (with the lowest streamflow projection) by the CSIRO-RCP8.5 model in the far future (2075–2104) showed that streamflows will be produced only for three months (July, August, and September) throughout the year. Findings from this study indicated that climate change will have significant adverse impacts on reservoir inflow, operation, water supply, and allocation in the study area.

We designed all-silicon, multi-featured band-selective perfect absorbing surfaces based on CMOS compatible processes. The center wavelength of the band-selective absorber can be varied between 2 and 22 μm while a bandwidth as high as 2.5 μm is demonstrated. We used a silicon-on-insulator (SOI) wafer which consists of n-type silicon (Si) device layer, silicon dioxide (SiO2) as buried oxide layer, and n-type Si handle layer. The center wavelength and bandwidth can be tuned by adjusting the conductivity of the Si device and handle layers as well as the thicknesses of the device and buried oxide layers. We demonstrate proof-of-concept absorber surfaces experimentally. Such absorber surfaces are easy to microfabricate because the absorbers do not require elaborate microfabrication steps such as patterning. Due to the structural simplicity, low-cost fabrication, wide spectrum range of operation, and band properties of the perfect absorber, the proposed multi-featured perfect absorber surfaces are promising for many applications. These include sensing devices, surface enhanced infrared absorption applications, solar cells, meta-materials, frequency selective sensors and modulators. [ABSTRACT FROM AUTHOR]