Faulty structural design may cause multistory reinforced concrete (RC) buildings to collapse suddenly. All attempts are directed to avoid structural failure as it leads to human life danger as well as wasting time and property. Using traditional methods for predicting structural failure of the RC buildings will be time-consuming and complex. Recent research proved the artificial neural network (ANN) potentiality in solving various real-life problems. The traditional learning algorithms suffer from being trapped into local optima with a premature convergence. Thus, it is a challenging task to achieve expected accuracy while using traditional learning algorithms to train ANN. To solve this problem, the present work proposed a particle swarm optimization-based approach to train the NN (NN-PSO). The PSO is employed to find a weight vector with minimum root-mean-square error (RMSE) for the NN. The proposed (NN-PSO) classifier is capable to tackle the problem of predicting structural failure of multistoried reinforced concrete buildings via detecting the failure possibility of the multistoried RC building structure in the future. A database of 150 multistoried buildings’ RC structures was employed in the experimental results. The PSO algorithm was involved to select the optimal weights for the NN classifier. Fifteen features have been extracted from the structural design, while nine features have been opted to perform the classification process. Moreover, the NN-PSO model was compared with NN and MLP-FFN (multilayer perceptron feed-forward network) classifier to find its ingenuity. The experimental results established the superiority of the proposed NN-PSO compared to the NN and MLP-FFN classifiers. The NN-PSO achieved 90 % accuracy with 90 % precision, 94.74 % recall and 92.31 % F-Measure.

Particle swarm optimization trained neural network for structural failure prediction of multistoried RC buildings

Sclerosing encapsulating peritonitis (SEP) is a rare cause of intestinal obstruction that is characterized by a thick grayish-white fibrotic membrane encasing the small bowel. SEP can be classified as idiopathic, also known as abdominal cocoon, or secondary. It is difficult to make a definite pre-operative diagnosis. We experienced five cases of abdominal cocoon, and the case files were reviewed retrospectively for the clinical presentation, operative findings and outcome. All the patients presented with acute, subacute and chronic intestinal obstruction. Computed tomography (CT) showed characteristic findings of small bowel loops congregated to the center of the abdomen encased by a soft-tissue density mantle in four cases. Four cases had an uneventful post-operative period, one case received second adhesiolysis due to persistent ileus. The imaging techniques may facilitate pre-operative diagnosis. Surgery is important in the management of SEP.

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Idiopathic sclerosing encapsulating peritonitis (or abdominal cocoon): a report of 5 cases.

Background Abdominal cocoon (AC) is a rare disease characterized by total or partial encasement of the small bowel by a thick, fibrous membrane. Twenty-four cases are reported in this article. Our aim was to investigate the methods of diagnosis and treatment for AC. Methods The clinical manifestations, diagnoses, surgical treatments, and follow-up results of 24 cases of AC in the Department of General Surgery of the Third Affiliated Hospital of Sun Yat-sen University between January 1997 and September 2007 were retrospectively analyzed. Results Main clinical manifestations were partial or complete intestinal obstruction (87.5%) and abdominal mass (54.2%). Three cases were preoperatively diagnosed by computed axial tomography and 1 case by barium x-ray examination. The other 20 cases were diagnosed by laparotomy. All of the patients underwent surgery. In all cases, we found that part of or the entire small bowel was encapsulated in a dense, white, fibrous, cocoon-like membrane. During surgery, excision of the thick membrane and lysis of adhesions were carefully performed to release the small intestine. Postsurgical recovery in most cases was smooth, and there was no recurrence during a follow-up period of 3 months to 9 years (mean 37 months). Conclusion The clinical manifestation of AC is nonspecific; therefore, preoperative diagnosis is difficult. However, its manifestations on barium x-ray and contrast computed axial tomography scan are characteristic, and aggregate analysis of the clinic and radiologic data can increase preoperative diagnosis. The main treatment of AC is surgery, and the overall prognosis of these patients is satisfactory.

Diagnosis and treatment of abdominal cocoon: a report of 24 cases

Abdominal cocoon, the idiopathic form of sclerosing encapsulating peritonitis, is a rare condition of unknown etiology that results in an intestinal obstruction due to total or partial encapsulation of the small bowel by a fibrocollagenous membrane. Preoperative diagnosis requires a high index of clinical suspicion. The early clinical features are nonspecific, are often not recognized and it is difficult to make a definite pre-operative diagnosis. Clinical suspicion may be generated by the recurrent episodes of small intestinal obstruction combined with relevant imaging findings and lack of other plausible etiologies. The radiological diagnosis of abdominal cocoon may now be confidently made on computed tomography scan. Surgery is important in the management of this disease. Careful dissection and excision of the thick sac with the release of the small intestine leads to complete recovery in the vast majority of cases.

Idiopathic sclerosing encapsulating peritonitis: Abdominal cocoon

Sclerosing encapsulating peritonitis, or abdominal cocoon, is a relatively rare cause of intestinal obstruction, described mostly in young adolescent girls. It is characterized by a thick fibrotic peritoneum that wraps the bowel in a concertinalike fashion with some adhesions. Because of its peculia

Abdominal cocoon in a man: preoperative diagnosis and literature review.

Abdominal cocoon in children: a report of four cases.

The paper has proposed a wavelet approach to diagnoses the stator inter-turn faults of a three induction motor. This technique is based on the analysis of stator current under both healthy and faulty condition. By using the wavelet technique, the approximation signals and detail signals of the fault patterns of the machine are generated. From the generated approximation signal the severity of the fault has been determined.

Induction motor stator inter-turn fault detection using wavelet transform technique

This paper presents a comparison between multilayer perceptron neural network (MLP NN) and Radial basis feedforward neural network (RBF NN) techniques for the detection of inter-turn short circuit fault in stator winding of an induction motor The fault location process is based on the monitoring the three phase shifts between the line current and the phase voltage of the induction machine

A comparison between MLP NN and RBF NN techniques for the detection of stator inter-turn fault of an induction motor

Motivated by the superior performances of neural networks and neuro-fuzzy approaches to fault detection of a single phase induction motor, this paper studies the applicability these two approaches for detection of stator inter-turn faults in a three phase induction motor. Firstly, the paper develops an adaptive neural fuzzy inference system (ANFIS) detection strategy and then compares its performance with that of using a multi layer perceptron neural network (MLP NN) applied to stator inter-turn fault detection of a three phase induction motor. The fault location process is based on the monitoring the three phase shifts between the line current and the phase voltage of the induction machine.

Stator inter-turn fault detection of an induction motor using neuro-fuzzy techniques

The challenges of viral infection have increased in recent decades due to the emergence of resistance, cross-resistance and drying up of antiviral drug discovery. Many neglected tropical viruses including the chikungunya virus, dengue virus & Japanese encephalitis virus have gradually become global pathogens. This has further increased the burden of viral infection which necessitates the continuous development of antiviral therapy. The antiviral chemistry began with the development of thiosemicarbazide derived thiosemicarbazones as antiviral. Although very few thiosemicarbazides have progressed into clinical application, it still inspires antiviral development. During last 3 decades (1990- 2020), several efforts have been made to develop suitable antiviral by using thiosemicarbazide scaffold. Its hybridization with other pharmacophores has been used as a strategy to enhance safety and efficacy. Cyclization and substitution of thiosemicarbazides have also been used to develop potent antiviral. With the ability to form coordinate bonds, thiosemicarbazides have been used either as metal complex or chelator against viruses. This work is an attempt to systematically review the research on the use of thiosemicarbazides as an antiviral scaffold. It also reviews the structure-activity relationship and translational suitability of thiosemicarbazide derived compounds.

Rudra Narayan Dash

Papers

Abdominal cocoon in children: a report of four cases.

Induction motor stator inter-turn fault detection using wavelet transform technique

A comparison between MLP NN and RBF NN techniques for the detection of stator inter-turn fault of an induction motor

Stator inter-turn fault detection of an induction motor using neuro-fuzzy techniques

Thiosemicarbazides: Updates on Antivirals Strategy.