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Stress-induced islet graft loss during the peri-transplantation period reduces the efficacy of islet transplantation. In this prospective, randomized, double-blind clinical trial, we evaluated the safety and efficacy of 60 mg/kg human alpha-1 antitrypsin (AAT) or placebo infusion weekly for four doses beginning before surgery in chronic pancreatitis (CP) patients undergoing total pancreatectomy and islet autotransplantation (TP-IAT). Subjects were followed for 12 months post-TP-IAT. The dose of AAT was safe, as there was no difference in the types and severity of adverse events in participants from both groups. There were some biochemical signals of treatment effect with a higher oxygen consumption rate in AAT islets before transplantation and a lower serum C-peptide (an indicator of islet death) in the AAT group at 15 min after islet infusion. Findings per the statistical analysis plan using a modified intention to treat analysis showed no difference in the C-peptide area under the curve (AUC) following a mixed meal tolerance test at 12 months post-TP-IAT. There was no difference in the secondary and exploratory outcomes. Although AAT therapy did not show improvement in C-peptide AUC in this study, AAT therapy is safe in CP patients and there are experiences gained on optimal clinical trial design in this challenging disease.

Meckel's diverticulum (MD) is a common congenital defect of the small intestinal tract resulting from incomplete obliteration of the vitellointestinal duct. It presents with unexplained gastrointestinal bleeding, bowel obstruction, and inflammation. In rare instances, the presentation is with perforation similar to acute appendicitis with perforation. The symptoms, clinical exam, and radiological findings of our patient, a 38-year-old male, were consistent with perforated acute appendicitis; he was found to have a perforated Meckel's diverticulum intraoperatively.

Transverse colon volvulus is a rare cause of potentially life-threatening large bowel obstruction accounting for less than 5% of colonic volvulus cases. Its diagnosis is often delayed due to nonspecific clinical features and its rarity. We report two uncommon cases of transverse colon volvulus. The first case involves a 20-year-old female who presented with acute abdominal pain and distension. The second case is a 67-year-old female with a one-week history of progressive constipation and abdominal discomfort. Computerized tomography aids in the diagnosis and definitive management requires surgical resection. Prompt diagnosis and treatment are critical due to the risk of ischemia and perforation.

Intussusception, defined as the telescoping of one segment of the gastrointestinal tract into an adjacent one, is a rare cause of abdominal pain in the adult population due to underlying benign or malignant pathology. With the liberal use of CT in the evaluation of patients with abdominal pain, the diagnosis became more reliable. Resection of the bowel segment is the recommended treatment in most cases. We are presenting the case of a 76-year-old male patient who presented with a three-week history of abdominal pain and diarrhea. The evaluation was consistent with ileocolic intussusception. Robotic resection of the right colon was performed. Pathology revealed poorly differentiated adenocarcinoma of the cecum as the underlying pathology.

The research, through a scientific study of the Al-Zubair district, tried to focus on the importance of land transport roads in general and highway transport lines in particular, and their role in creating an integrated development process in the spatial domains that they penetrate. The developmental role of this important vital sector (main road networks) in reviving and activating the development potential characterizes the study area with the spatial extension of those roads in the establishment of urban communities and planning for the development of various human activities. The research focused on analysing the developmental relationship of the main transportation roads and their impact on the Al-Zubair district using the analytical method by relying on geographic information systems (GIS) techniques and using standard methods, including the inflexion factor method and the nearest neighbour in determining the effectiveness of regional roads, and the use of the questionnaire and the adoption of planning methods to show the efficiency of the roads, including the method (the inflexion coefficient). The research reached a set of results that prove the existence of a developmental interrelationship between the regional transport routes and the areas of spatial activities of the population in the study area.

One of the extremely uncommon manifestations of malrotation is nonrotation, a condition that arises due to the complete failure of the midgut to rotate 270 degrees. The true prevalence in adults remains obscure due to the scarcity of the condition. A standard surgical approach to management is therefore lacking, and an increasing number of case reports is required to establish evidence-based recommendations. We present the case of a 39-year-old male with acute abdominal pain due to cecal volvulus in the setting of intestinal nonrotation, successfully managed with a robotic-assisted surgical approach.

In nature, streamflow pattern is characterized with high non-linearity and non-stationarity. Developing an accurate forecasting model for a streamflow is highly essential for several applications in the field of water resources engineering. One of the main contributors for the modeling reliability is the optimization of the input variables to achieve an accurate forecasting model. The main step of modeling is the selection of the proper input combinations. Hence, developing an algorithm that can determine the optimal input combinations is crucial. This study introduces the Genetic algorithm (GA) for better input combination selection. Radial basis function neural network (RBFNN) is used for monthly streamflow time series forecasting due to its simplicity and effectiveness of integration with the selection algorithm. In this paper, the RBFNN was integrated with the Genetic algorithm (GA) for streamflow forecasting. The RBFNN-GA was applied to forecast streamflow at the High Aswan Dam on the Nile River. The results showed that the proposed model provided high accuracy. The GA algorithm can successfully determine effective input parameters in streamflow time series forecasting.

The suspended sediment load (SSL) is one of the major hydrological processes affecting the sustainability of river planning and management. Moreover, sediments have a significant impact on dam operation and reservoir capacity. To this end, reliable and applicable models are required to compute and classify the SSL in rivers. The application of machine learning models has become common to solve complex problems such as SSL modeling. The present research investigated the ability of several models to classify the SSL data. This investigation aims to explore a new version of machine learning classifiers for SSL classification at Johor River, Malaysia. Extreme gradient boosting, random forest, support vector machine, multi-layer perceptron and k-nearest neighbors classifiers have been used to classify the SSL data. The sediment values are divided into multiple discrete ranges, where each range can be considered as one category or class. This study illustrates two different scenarios related to the number of categories, which are five and 10 categories, with two time scales, daily and weekly. The performance of the proposed models was evaluated by several statistical indicators. Overall, the proposed models achieved excellent classification of the SSL data under various scenarios.

The accuracy level for reservoir evaporation prediction is an important issue for decision making in the water resources field. The traditional methods for evaporation prediction could encounter numerous obstacles owing to the effect of several parameters on the shape of the evaporation pattern. The current research presented modern model called the Coactive Neuro-Fuzzy Inference System (CANFIS). Modification for such model has been achieved for enhancing the evaporation prediction accuracy. Genetic algorithm was utilized to select the effective input combination. The efficiency of the proposed model has been compared with popular artificial intelligence models according to several statistical indicators. Two different case studies Aswan High Dam (AHD) and Timah Tasoh Dam (TTD) have been considered to explore the performance of the proposed models. It is concluded that the modified GA-CANFIS model is better than GA-ANFIS, GA-SVR, and GA-RBFNN for evaporation prediction for both case studies. GA-CANFIS attained minimum RMSE (15.22 mm month −1 for AHD, 8.78 mm month −1 for TTD), minimum MAE (12.48 mm month −1 for AHD, 5.11 mm month −1 for TTD), and maximum determination coefficient (0.98 for AHD, 0.95 for TTD).

One of the major challenges and difficulties to generate optimal operation rule for dam and reservoir operation are how efficient the optimization algorithm to search for the global optimal solution and the time-consume for convergence. Recently, evolutionary algorithms (EA) are used to develop optimal operation rules for dam and reservoir water systems. However, within the EA, there is a need to assume internal parameters at the initial stage of the model development, such assumption might increase the ambiguity of the model outputs. This study proposes a new hybrid optimization algorithm based on a bat algorithm (BA) and particle swarm optimization algorithm (PSOA) called the hybrid bat–swarm algorithm (HB-SA). The main idea behind this hybridization is to improve the BA by using the PSOA in parallel to replace the suboptimal solution generated by the BA. The solutions effectively speed up the convergence procedure and avoid the trapping in local optima caused by using the BA. The proposed HB-SA is validated by minimizing irrigation deficits using a multireservoir system consisting of the Golestan and Voshmgir dams in Iran. In addition, different optimization algorithms from previous studies are investigated to compare the performance of the proposed algorithm with existing algorithms for the same case study. The results showed that the proposed HB-SA algorithm can achieve minimum irrigation deficits during the examined period and outperforms the other optimization algorithms. In addition, the computational time for the convergence procedure is reduced using the HB-SA. The proposed HB-SA is successfully examined and can be generalized for several dams and reservoir systems around the world.