A note on Gauge Theories Coupled to Gravity

We analyze the bound on gauge couplings $e\geq m/m_p$, suggested by Arkani-Hamed et.al. We show this bound can be derived from simple semi-classical considerations and holds in spacetime dimensions greater than or equal to four. Non abelian gauge symmetries seem to satisfy the bound in a trivial manner. We comment on the case of discrete symmetries and close by performing some checks for the bound in higher dimensions in the context of string theory.Comment: 15 pages, 1 figure, Late

Preliminary design and analysis of a photovoltaic-powered direct air capture system for a residential building

To promote the adoption of Direct Air Capture (DAC) systems, this paper proposes and tests a photovoltaic-powered DAC system in a generic residential building located in Qatar. The proposed DAC system can efficiently reduce CO2 concentration in a living space, thus providing an incentive to individuals to adopt it. The ventilation performance of the building is determined using Computational Fluid Dynamics (CFD) simulations, undertaken with ANSYS-CFD. The CFD model was validated using microclimate-air quality dataloggers. The simulated velocity was 1.4 m/s and the measured velocity was 1.35 m/s, which corresponds to a 3.5% error. The system decarbonizes air supplied to the building by natural ventilation or ventilation according to the ASHRAE standards. Furthermore, the performance of the photovoltaic system is analyzed using the ENERGYPLUS package of the Design Builder software. We assume that 75% of CO2 is captured. In addition, a preliminary characterization of the overall system’s performance is determined. It is determined that the amount of CO2 captured by the system is 0.112 tones/year per square meter of solar panel area. A solar panel area of 19 m2 is required to decarbonize the building with natural ventilation, and 27 m2 is required in the case of ventilation according to the ASHRAE standard

Preliminary design and analysis of a photovoltaic-powered direct air capture system for a residential building

To promote the adoption of Direct Air Capture (DAC) systems, this paper proposes and tests a photovoltaic-powered DAC system in a generic residential building located in Qatar. The proposed DAC system can efficiently reduce CO2 concentration in a living space, thus providing an incentive to individuals to adopt it. The ventilation performance of the building is determined using Computational Fluid Dynamics (CFD) simulations, undertaken with ANSYS-CFD. The CFD model was validated using microclimate-air quality dataloggers. The simulated velocity was 1.4 m/s and the measured velocity was 1.35 m/s, which corresponds to a 3.5% error. The system decarbonizes air supplied to the building by natural ventilation or ventilation according to the ASHRAE standards. Furthermore, the performance of the photovoltaic system is analyzed using the ENERGYPLUS package of the Design Builder software. We assume that 75% of CO2 is captured. In addition, a preliminary characterization of the overall system’s performance is determined. It is determined that the amount of CO2 captured by the system is 0.112 tones/year per square meter of solar panel area. A solar panel area of 19 m2 is required to decarbonize the building with natural ventilation, and 27 m2 is required in the case of ventilation according to the ASHRAE standard

Approaches in biotechnological applications of natural polymers

Natural polymers, such as gums and mucilage, are biocompatible, cheap, easily available and non-toxic materials of native origin. These polymers are increasingly preferred over synthetic materials for industrial applications due to their intrinsic properties, as well as they are considered alternative sources of raw materials since they present characteristics of sustainability, biodegradability and biosafety. As definition, gums and mucilages are polysaccharides or complex carbohydrates consisting of one or more monosaccharides or their derivatives linked in bewildering variety of linkages and structures. Natural gums are considered polysaccharides naturally occurring in varieties of plant seeds and exudates, tree or shrub exudates, seaweed extracts, fungi, bacteria, and animal sources. Water-soluble gums, also known as hydrocolloids, are considered exudates and are pathological products; therefore, they do not form a part of cell wall. On the other hand, mucilages are part of cell and physiological products. It is important to highlight that gums represent the largest amounts of polymer materials derived from plants. Gums have enormously large and broad applications in both food and non-food industries, being commonly used as thickening, binding, emulsifying, suspending, stabilizing agents and matrices for drug release in pharmaceutical and cosmetic industries. In the food industry, their gelling properties and the ability to mold edible films and coatings are extensively studied. The use of gums depends on the intrinsic properties that they provide, often at costs below those of synthetic polymers. For upgrading the value of gums, they are being processed into various forms, including the most recent nanomaterials, for various biotechnological applications. Thus, the main natural polymers including galactomannans, cellulose, chitin, agar, carrageenan, alginate, cashew gum, pectin and starch, in addition to the current researches about them are reviewed in this article.. }To the Conselho Nacional de Desenvolvimento Cientfíico e Tecnológico (CNPq) for fellowships (LCBBC and MGCC) and the Coordenação de Aperfeiçoamento de Pessoal de Nvíel Superior (CAPES) (PBSA). This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit, the Project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462) and COMPETE 2020 (POCI-01-0145-FEDER-006684) (JAT)

PANC Study (Pancreatitis: A National Cohort Study): national cohort study examining the first 30 days from presentation of acute pancreatitis in the UK

Background Acute pancreatitis is a common, yet complex, emergency surgical presentation. Multiple guidelines exist and management can vary significantly. The aim of this first UK, multicentre, prospective cohort study was to assess the variation in management of acute pancreatitis to guide resource planning and optimize treatment. Methods All patients aged greater than or equal to 18 years presenting with acute pancreatitis, as per the Atlanta criteria, from March to April 2021 were eligible for inclusion and followed up for 30 days. Anonymized data were uploaded to a secure electronic database in line with local governance approvals. Results A total of 113 hospitals contributed data on 2580 patients, with an equal sex distribution and a mean age of 57 years. The aetiology was gallstones in 50.6 per cent, with idiopathic the next most common (22.4 per cent). In addition to the 7.6 per cent with a diagnosis of chronic pancreatitis, 20.1 per cent of patients had a previous episode of acute pancreatitis. One in 20 patients were classed as having severe pancreatitis, as per the Atlanta criteria. The overall mortality rate was 2.3 per cent at 30 days, but rose to one in three in the severe group. Predictors of death included male sex, increased age, and frailty; previous acute pancreatitis and gallstones as aetiologies were protective. Smoking status and body mass index did not affect death. Conclusion Most patients presenting with acute pancreatitis have a mild, self-limiting disease. Rates of patients with idiopathic pancreatitis are high. Recurrent attacks of pancreatitis are common, but are likely to have reduced risk of death on subsequent admissions

PANC Study (Pancreatitis: A National Cohort Study): national cohort study examining the first 30 days from presentation of acute pancreatitis in the UK

Abstract Background Acute pancreatitis is a common, yet complex, emergency surgical presentation. Multiple guidelines exist and management can vary significantly. The aim of this first UK, multicentre, prospective cohort study was to assess the variation in management of acute pancreatitis to guide resource planning and optimize treatment. Methods All patients aged greater than or equal to 18 years presenting with acute pancreatitis, as per the Atlanta criteria, from March to April 2021 were eligible for inclusion and followed up for 30 days. Anonymized data were uploaded to a secure electronic database in line with local governance approvals. Results A total of 113 hospitals contributed data on 2580 patients, with an equal sex distribution and a mean age of 57 years. The aetiology was gallstones in 50.6 per cent, with idiopathic the next most common (22.4 per cent). In addition to the 7.6 per cent with a diagnosis of chronic pancreatitis, 20.1 per cent of patients had a previous episode of acute pancreatitis. One in 20 patients were classed as having severe pancreatitis, as per the Atlanta criteria. The overall mortality rate was 2.3 per cent at 30 days, but rose to one in three in the severe group. Predictors of death included male sex, increased age, and frailty; previous acute pancreatitis and gallstones as aetiologies were protective. Smoking status and body mass index did not affect death. Conclusion Most patients presenting with acute pancreatitis have a mild, self-limiting disease. Rates of patients with idiopathic pancreatitis are high. Recurrent attacks of pancreatitis are common, but are likely to have reduced risk of death on subsequent admissions. </jats:sec

Real-time flow forecasting

The main objective of this research is to develop techniques for updating deterministic river flow forecasts using feedback of real-time (on-line) flow and snowpack data. To meet this objective, previous updating methods have been reviewed and evaluated and typical error patterns in flow forecasts have been analyzed using standard techniques. In addition, a new criterion based on the coefficient of determination and coefficient of efficiency has been introduced to evaluate systematic errors in flow forecasts. Moreover, lagged linear regression has been suggested as a method for detecting and estimating timing errors. Arising from this initial work, two different updating procedures have been developed. Further work has shown that these two independent procedures can be usefully combined, leading to yet further improvement of forecast. Arising from these methods, two other additional approaches have been formulated, one for correcting timing errors and one for updating snowpack estimation parameters from flow measurements. The first of the updating methods consists of a flow updating model which was developed to update the flow forecasts of the UBC watershed model using the most recent flow measurement. The updating process is achieved using the Kalman filter technique. The performance of the updating model is mainly controlled by the relative values of two parameters of the Kalman filter technique: the measurement variance and the state variance. It is found that the measurement variance is best selected as the square of a percentage of the flow. The updating model has been applied on the Illecillewaet river basin in British Columbia. A significant improvement in flow forecasts has been observed. The second method has been developed to update parameters of an energy budget snowpack model using on-line snowpack measurements. The updating procedure is based on calculating the value of a snowpack parameter that yields a perfect correspondence between measured and calculated snowpacks. The updated value is then used in the snowpack model to enhance its future forecasts with feedback from previous snowpack measurements. The snowmelts generated by the updated snowpack model are then routed to produce flow forecasts. Applying this model on the snowpack measured at Mt. Fidelity in the upper Columbia River Basin in British Columbia showed that both the snowpack forecasts and the flow forecasts generated from these updated snowpack forecasts were greatly improved. Because the above two updating methods operate independently, they can be applied in combination whenever an appropriate measurement is available. The combined use of these two methods to data from the Illecillewaet river basin showed an additional improvement in flow forecasts. As a further development, the snowpack estimation model has been adapted so that a Kalman filter approach can be used to update snowpack estimation parameters from flow measurements. It is finally concluded that flow forecast updating requires the application of several methods, rather than one simple approach, because errors arise from various sources. In addition, updating procedures may prove useful in achieving a better calibration for watershed models.Applied Science, Faculty ofCivil Engineering, Department ofGraduat

Public values regarding an urban mangrove wetland in the United Arab Emirates

Mangrove wetlands are facing an existential threat from rapid socio-economic development. In this study, public environmental values regarding mangrove wetlands in the Ras Al Khaimah (RAK) city in the United Arab Emirates were assessed, considering gender, age, education, income, length of residency in RAK, knowledge of RAK mangrove and awareness of sustainability. A population sample of 427 respondents were face-to-face interviewed. Results suggest that mangrove value orientations are highly associated with length of residency in RAK and awareness of sustainability at significance levels of 0.003 and 0.005, respectively. Value orientations are less associated with age, knowledge of RAK mangrove and education at significance levels of 0.023, 0.039 and 0.095, respectively, being largely independent of gender and income. The majority of the respondents support the preservation of the mangroves even at the expense of economic development. This indicates the need to draft policies and regulations to safeguard the mangroves

Improving Solar Radiation Forecasting Utilizing Data Augmentation Model Generative Adversarial Networks with Convolutional Support Vector Machine (GAN-CSVR)

The accuracy of solar radiation forecasting depends greatly on the quantity and quality of input data. Although deep learning techniques have robust performance, especially when dealing with temporal and spatial features, they are not sufficient because they do not have enough data for training. Therefore, extending a similar climate dataset using an augmentation process will help overcome the issue. This paper proposed a generative adversarial network model with convolutional support vector regression, which is named (GAN-CSVR) that combines a GAN, convolutional neural network, and SVR to augment training data. The proposed model is trained utilizing the Multi-Objective loss function, which combines the mean squared error and binary cross-entropy. The original solar radiation dataset used in the testing is derived from three locations, and the results are evaluated using two scales, namely standard deviation (STD) and cumulative distribution function (CDF). The STD and the average error value of the CDF between the original dataset and the augmented dataset for these three locations are 0.0208, 0.1603, 0.9393, and 7.443981, 4.968554, and 1.495882, respectively. These values show very significant similarity in these two datasets for all locations. The forecasting accuracy findings show that the GAN-CSVR model produced augmented datasets that improved forecasting from 31.77% to 49.86% with respect to RMSE and MAE over the original datasets. This study revealed that the augmented dataset produced by the GAN-CSVR model is reliable because it provides sufficient data for training deep networks