Assessing the impacts of climate change on streamflow dynamics: A machine learning perspective.

This study investigates changes in river flow patterns, in the Hunza Basin, Pakistan, attributed to climate change. Given the anticipated rise in extreme weather events, accurate streamflow predictions are increasingly vital. We assess three machine learning (ML) models - artificial neural network (ANN), recurrent neural network (RNN), and adaptive fuzzy neural inference system (ANFIS) - for streamflow prediction under the Coupled Model Intercomparison Project 6 (CMIP6) Shared Socioeconomic Pathways (SSPs), specifically SSP245 and SSP585. Four key performance indicators, mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2), guide the evaluation. These models employ monthly precipitation, maximum and minimum temperatures as inputs, and discharge as the output, spanning 1985-2014. The ANN model with a 3-10-1 architecture outperforms RNN and ANFIS, displaying lower MSE, RMSE, MAE, and higher R2 values for both training (MSE = 20417, RMSE = 142, MAE = 71, R2 = 0.94) and testing (MSE = 9348, RMSE = 96, MAE = 108, R2 = 0.92) datasets. Subsequently, the superior ANN model predicts streamflow up to 2100 using SSP245 and SSP585 scenarios. These results underscore the potential of ANN models for robust futuristic streamflow estimation, offering valuable insights for water resource management and planning.

Intercomparison of SWAT and ANN techniques in simulating streamflows in the Astore Basin of the Upper Indus.

The current research work was carried out to simulate monthly streamflow historical record using Soil and Water Assessment Tool (SWAT) and Artificial Neural Network (ANN) at the Astore Basin, Gilgit-Baltistan, Pakistan. The performance of SWAT and ANN models was assessed during calibration (1985-2005) and validation (2006-2010) periods via statistical indicators such as coefficient of determination (R2), Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), and root-mean-square error (RMSE). R2, NSE, PBIAS, and RMSE values for SWAT (ANN with Architecture (2,27,1)) models during calibration are 0.80 (0.88), 0.73 (0.82), 15.7 (0.008), and 79.81 (70.34), respectively, while during validation, the corresponding values are 0.71 (0.86), 0.66 (0.95), 17.3 (0.10), and 106.26 (75.92). The results implied that the ANN model is superior to the SWAT model based on the statistical performance indicators. The SWAT results demonstrated an underestimation of the high flow and overestimation of the low flow. Comparatively, the ANN model performed very well in estimating the general and extreme flow conditions. The findings of this research highlighted its potential as a valuable tool for accurate streamflow forecasting and decision-making. The current study recommends that additional machine learning models may be compared with the SWAT model output to improve monthly streamflow predictions in the Astore Basin.

Review of Modeling Techniques for Analysis and Assessment of RC Beam-Column Joints Subjected to Seismic Loads.

Beam-column connections are the most critical components of reinforced concrete (RC) structures. They serve as a load transfer path and take a significant portion of the overall shear. Joints in RC structures constructed with no seismic provisions have an insufficient capacity and ductility under lateral loading and can cause the progressive failure of the entire structure. The joint may fail in the shear prior to the connecting beam and column elements. Therefore, several modeling techniques have been devised in the past to capture the non-linear response of such joints. Modeling techniques used to capture the non-linear response of reinforced-concrete-beam-column joints range from simplified lumped plasticity models to detailed fiber-based finite element (FE) models. The macro-modeling technique for joint modeling is highly efficient in terms of the computational effort, analysis time, and computer memory requirements, and is one of the most widely used modeling techniques. The non-linear shear response of the joint panel and interface bond-slip mechanism are concentrated in zero-length linear and rotational springs while the connecting elements are modeled through elastic elements. The shear response of joint panels has also been captured through rigid panel boundary elements with rotational springs. The computational efficiency of these models is significantly high compared to continuum models, as each joint act as a separate supe-element. This paper aims to provide an up-to-date review of macro-modeling techniques for the analysis and assessment of RC-beam-column connections subjected to lateral loads. A thorough understanding of existing models is necessary for developing new mechanically adequate and computationally efficient joint models for the analysis and assessment of deficient RC connections. This paper will provide a basis for further research on the topic and will assist in the modification and optimization of existing models. As each model is critically evaluated, and their respective capabilities and limitations are explored, it should help researchers to improve and build on modeling techniques both in terms of accuracy and computational efficiency.

Surgical management of splenic hydatidosis.

PURPOSE: This study was conducted to evaluate the surgical management of splenic hydatidosis in an area where the disease is endemic. METHOD: Over a period of 16 years, 26 patients with splenic hydatidosis underwent surgery in our department. Preoperative investigations included plain abdominal X-ray, serology, ultrasonography, and computed tomography. RESULTS: In our series, splenic hydatidosis represented 3.5% of total abdominal hydatidosis. The majority of patients presented with abdominal discomfort and palpable swelling in the left hypochondrium. Twenty-two patients were operated on electively and 4 as emergency cases, including 2 with ruptured hydatids and 2 with infected hydatids of the spleen. Isolated splenic hydatid cysts were present in 21 patients, associated liver hydatid cysts in 4, and diffuse abdominal hydatidosis in 1 patient. All patients underwent splenectomy except for one patient who initially had partial splenectomy for a lower polar cyst. This patient also ended up undergoing a splenectomy for postoperative hemorrhage. One patient died on the sixth postoperative day (mortality rate 3.8%) as a result of multiorgan failure, and 4 developed minor complications (morbidity 15.4%). CONCLUSION: Splenic hydatidosis, although rare, is the third most common type of hydatidosis after liver and lung hydatidosis. This entity should thus be kept in mind when encountering a splenic cyst especially in areas where the disease is endemic. A splenectomy remains the treatment of choice because it demonstrates low morbidity and mortality rates.

Ascariasis-induced empyema of gallbladder: report of a case.

A rare case of a 52-year-old woman with empyema of the gallbladder due to ascariasis causing an obstruction in the cystic duct is presented. She was admitted on September 20, 2000, and on September 23 an emergency cholecystectomy was performed. Ultrasonography is a highly sensitive and specific method for diagnosing gallbladder ascariasis, and a cholecystectomy is considered mandatory for the treatment of empyema of the gallbladder.