Root water uptake under non-uniform transient salinity and water stress

The study described in this thesis focuses on the quantitative understanding of water uptake by roots under separate and combined salinity and water stresses. The major difficulty in solving Richards' equation stems from the lack of a sink term function that adequately describes root water uptake. From the existing microscopic and macroscopic sink term functions, the empirical macroscopic approach was chosen because it requires the least number of parameters whose values can readily be determined. All existing reduction functions as well as those newly developed in this study are used in the macroscopic model and tested against experimental data. The experimentally obtained data are used to derive the parameter values needed for the simulation model HYSWASOR. The experiments cover root water uptake by alfalfa under salinity stress, water stress, and combined salinity and water stress. This order is followed with the analysis of the data and the simulation.Under salinity stress , both experimental and simulated results indicate that the well-known linear crop response function can be used as a reduction function. The parameter values available in the literature for different reduction functions cannot provide acceptable agreement with the experimental data. When experimentally derived parameters are used in the simulation model, the agreement becomes much closer, but calibration is still needed. The parameter values obtained by calibration differ slightly from the experiments, because the experimentally derived parameter values are based upon mean soil solution salinity. Both experimental and simulation results indicate that different salinity reduction functions can provide almost the same results if the parameter values are well specified. For practical use the linear reduction function with the least number of parameters appears to be adequate.Under water stress , all existing reduction functions as well as the one developed in this study are tested on the experimental data. Since the trend of the experimental relative transpiration versus mean soil water pressure head is nonlinear, the linear reduction function cannot fit the data. The existing nonlinear reduction functions can fit only half of the data range satisfactorily. The best agreement is obtained with the newly developednonlinear two-threshold reduction function .The parameter values obtained by calibration differ only slightly from those of the experiments. Soil water pressure head heterogeneity over the root zone does not play an important role in water uptake. The roots appear to take up water from the relatively wetter parts of the root zone to compensate for the water deficit in the drier parts. On the first day after irrigation both relative transpiration and relative leaf water head are almost the same for the stressed and non-stressed plants. While the simulated transpiration agrees closely with the experimental data, the main reason for the discrepancy between the simulated and actual water contents appears to be water uptake during the night.Under combined water and salinity stress , the additive and multiplicative reduction functions are first tested against the experimental data and then inserted in the simulation model. A new combination reduction function is introduced that differs conceptually from the additive and multiplicative functions. Both the experimental and simulated results show that the newly proposed model fits the data best, while the worst results are obtained with the simple additive model.</p

Microgrid working conditions identification based on cluster analysis &amp;#x2013; a case study from Lambda Microgrid

This article presents the application of cluster analysis (CA) to data proceeding from a testbed microgrid located at Sapienza University of Rome. The microgrid consists of photovoltaic (PV), battery storage system (BESS), emergency generator set, and different types of load with a real-time energy management system based on supervisory control and data acquisition. The investigation is based on the area-related approach - the CA algorithm considers the input database consisting of data from all measurement points simultaneously. Under the investigation, different distance measures (Euclidean, Chebyshev, or Manhattan), as well as an approach to the optimal number of cluster selections. Based on the investigation, the four different clusters that represent working conditions were obtained using methods to define an optimal number of clusters. Cluster 1 represented time with high PV production; cluster 2 represented time with relatively low PV production and when BESS was charged; cluster 3 represents time with relatively high PV production and when BESS was charged; cluster 4 represents time without PV production. Additionally, after the clustering process, a deep analysis was performed in relation to the working condition of the microgrid

Is sentinel node mapping possible in surgically removed ectopic axillary breast cancer? A case report

We reported a 24-year-old female patient with the history of ectopic axillary breast cancer which was removed surgically. Sentinel node mapping was performed for lymphatic axillary staging of this patient with two injections of the 99m-Tc-phytate in both ends of the surgical scar. Lymphoscintigraphy showed an axillary sentinel node which was harvested during surgery and was not pathologically involved. Our case showed that sentinel node mapping is possible for ectopic axillary breast cancer patients even after excisional biopsy of the index lesion

Microgrid working conditions identification based on cluster analysis. A case study from lambda microgrid

This article presents the application of cluster analysis (CA) to data proceeding from a testbed microgrid located at Sapienza University of Rome. The microgrid consists of photovoltaic (PV), battery storage system (BESS), emergency generator set, and different types of load with a real-time energy management system based on supervisory control and data acquisition. The investigation is based on the area-related approach - the CA algorithm considers the input database consisting of data from all measurement points simultaneously. Under the investigation, different distance measures (Euclidean, Chebyshev, or Manhattan), as well as an approach to the optimal number of cluster selections. Based on the investigation, the four different clusters that represent working conditions were obtained using methods to define an optimal number of clusters. Cluster 1 represented time with high PV production; cluster 2 represented time with relatively low PV production and when BESS was charged; cluster 3 represents time with relatively high PV production and when BESS was charged; cluster 4 represents time without PV production. Additionally, after the clustering process, a deep analysis was performed in relation to the working condition of the microgrid

Operation and Planning of Energy Hubs Under Uncertainty - a Review of Mathematical Optimization Approaches

Co-designing energy systems across multiple energy carriers is increasingly attracting attention of researchers and policy makers, since it is a prominent means of increasing the overall efficiency of the energy sector. Special attention is attributed to the so-called energy hubs, i.e., clusters of energy communities featuring electricity, gas, heat, hydrogen, and also water generation and consumption facilities. Managing an energy hub entails dealing with multiple sources of uncertainty, such as renewable generation, energy demands, wholesale market prices, etc. Such uncertainties call for sophisticated decision-making techniques, with mathematical optimization being the predominant family of decision-making methods proposed in the literature of recent years. In this paper, we summarize, review, and categorize research studies that have applied mathematical optimization approaches towards making operational and planning decisions for energy hubs. Relevant methods include robust optimization, information gap decision theory, stochastic programming, and chance-constrained optimization. The results of the review indicate the increasing adoption of robust and, more recently, hybrid methods to deal with the multi-dimensional uncertainties of energy hubs

A historical and future impact assessment of mining activities on surface biophysical characteristics change : A remote sensing-based approach

Mining activities and associated actions cause land-use/land-cover (LULC) changes across the world. The objective of this study were to evaluate the historical impacts of mining activities on surface biophysical characteristics, and for the first time, to predict the future changes in pattern of vegetation cover and land surface temperature (LST). In terms of the utilized data, satellite images of Landsat, and meteorological data of Sungun mine in Iran, Athabasca oil sands in Canada, Singrauli coalfield in India and Hambach mine in Germany, were used over the period of 1989-2019. In the first step, the spectral bands of Landsat images were employed to extract historical LULC changes in the study areas based on the homogeneity distance classification algorithm (HDCA). Thereafter, a CA-Markov model was used to predict the future of LULC changes based on the historical changes. In addition, LST and vegetation cover maps were calculated using the single channel algorithm, and the normalized difference vegetation index (NDVI), respectively. In the second step, the trends of LST and NDVI variations in different LULC change types and over different time periods were investigated. Finally, a CA-Markov model was used to predict the LST and NDVI maps and the trend of their variations in future. The results indicated that the forest and green space cover was reduced from 9.95 in 1989 to 5.9 Km(2) in 2019 for Sungun mine, from 42.14 in 1999 to 33.09 Km(2) in 2019 for Athabasca oil sands, from 231.46 in 1996 to 263.95 Km(2) in 2016 for Singrauli coalfield, and from 180.38 in 1989 to 133.99 Km(2) in 2017 for Hambach mine, as a result of expansion and development of of mineral activities. Our findings about Sungun revealed that the areal coverage of forest and green space will decrease to 15% of the total study area by 2039, resulting in reduction of the mean NDVI by almost 0.06 and increase of mean standardized LST from 0.52 in 2019 to 0.61 in 2039. our results further indicate that for Athabasca oil sands (Singrauli coalfield, Hambach mine), the mean values of standardized LST and NDVI will change from 0.5 (0.44 and 0.4) and 0.38 (0.38, 0.35) in 2019 (2016, 2017) to 0.57 (0.5, 0.47) and 0.33 (0.32, 0.28), in 2039 (2036, 2035), respectively. This can be mainly attributed to the increasing mining activities in the past as well as future years. The discussion and conclusions presented in this study can be of interest to local planners, policy makers, and environmentalists in order to observe the damages brought to the environment and the society in a larger picture.Peer reviewe

Leiomyosarcoma with Unusual Macroscopic Features: A Case Report

Uterine sarcoma is a rare tumor of mesodermal origin, accounting for 2-6% of uterine malignancies. Leiomyosarcoma (LMS) has been reported in only 1% of all uterine malignancies and is regarded as the most common primary uterine sarcoma. Herein, we present a case of LMS with unusual macroscopic features. The patient was a 61-year-old woman with LMS, which consisted of a large cystic mass (88×136 mm), containing six liters of brownish fluid on the right side of the pelvis and abdomen. The fundus of the uterus was ruptured by the solid part of the tumor. For treatment, total hysterectomy, salpingo-oophorectomy and the optimal resection of tumoral parts were carried out. Overall, the distinctive biological behavior and poor overall survival of uterine sarcoma challenge the post-operative management of this tumor. According to the one-year follow-up, the patient was disease-free. Unfortunately, no further information is at hand beyond this period