Performance Evaluation of Ingenious Crow Search Optimization Algorithm for Protein Structure Prediction

Protein structure prediction is one of the important aspects while dealing with critical diseases. An early prediction of protein folding helps in clinical diagnosis. In recent years, applications of metaheuristic algorithms have been substantially increased due to the fact that this problem is computationally complex and time-consuming. Metaheuristics are proven to be an adequate tool for dealing with complex problems with higher computational efficiency than conventional tools. The work presented in this paper is the development and testing of the Ingenious Crow Search Algorithm (ICSA). First, the algorithm is tested on standard mathematical functions with known properties. Then, the application of newly developed ICSA is explored on protein structure prediction. The efficacy of this algorithm is tested on a bench of artificial proteins and real proteins of medium length. The comparative analysis of the optimization performance is carried out with some of the leading variants of the crow search algorithm (CSA). The statistical comparison of the results shows the supremacy of the ICSA for almost all protein sequences

Analysis of Nonlinear Duopoly Game: A Cooperative Case

We make further attempts to investigate equilibrium stability of a nonlinear Cournot duopoly game. Our studies in this paper focus on the cooperation that may be obtained among duopolistic firms. Discrete time scales under the assumption of unknown inverse demand function and linear cost are used to build our models in the proposed games. We introduce and study here an adjustment dynamic strategy beside the so-called tit-for-tat strategy. For each model, the stability analysis of the fixed point is analyzed. Numerical simulations are carried out to show the complex behavior of the proposed models and to point out the impact of the models’ parameters on the cooperation

A Family of Hybrid Stochastic Conjugate Gradient Algorithms for Local and Global Minimization Problems

This paper contains two main parts, Part I and Part II, which discuss the local and global minimization problems, respectively. In Part I, a fresh conjugate gradient (CG) technique is suggested and then combined with a line-search technique to obtain a globally convergent algorithm. The finite difference approximations approach is used to compute the approximate values of the first derivative of the function f. The convergence analysis of the suggested method is established. The comparisons between the performance of the new CG method and the performance of four other CG methods demonstrate that the proposed CG method is promising and competitive for finding a local optimum point. In Part II, three formulas are designed by which a group of solutions are generated. This set of random formulas is hybridized with the globally convergent CG algorithm to obtain a hybrid stochastic conjugate gradient algorithm denoted by HSSZH. The HSSZH algorithm finds the approximate value of the global solution of a global optimization problem. Five combined stochastic conjugate gradient algorithms are constructed. The performance profiles are used to assess and compare the rendition of the family of hybrid stochastic conjugate gradient algorithms. The comparison results between our proposed HSSZH algorithm and four other hybrid stochastic conjugate gradient techniques demonstrate that the suggested HSSZH method is competitive with, and in all cases superior to, the four algorithms in terms of the efficiency, reliability and effectiveness to find the approximate solution of the global optimization problem that contains a non-convex function

An intuitionistic fuzzy entropy-based gained and lost dominance score decision-making method to select and assess sustainable supplier selection

Sustainable supplier selection (SSS) is recognized as a prime aim in supply chain because of its impression on profitability, adorability, and agility of the organization. This work introduces a multi-phase intuitionistic fuzzy preference-based model with which decision experts are authorized to choose the suitable supplier using the sustainability "triple bottom line (TBL)" attributes. To solve this issue, an intuitionistic fuzzy gained and lost dominance score (IF-GLDS) approach is proposed using the developed IF-entropy. To make better use of experts' knowledge and fully represent the uncertain information, the evaluations of SSS are characterized in the form of intuitionistic fuzzy set (IFS). To better distinguish fuzziness of IFSs, new entropy for assessing criteria weights is proposed with the help of an improved score function. By considering the developed entropy and improved score function, a weight-determining process for considered criterion is presented. A case study concerning the iron and steel industry in India for assessing and ranking the SSS is taken to demonstrate the practicability of the developed model. The efficacy of the developed model is certified with the comparison by diverse extant models

Exogenous application of low and high molecular weight organic acids differentially affected the uptake of cadmium in wheat-rice cropping system in alkaline calcareous soil

Anthropogenic cadmium (Cd) in arable soils is becoming a global concern due to its harmful effects on crop yield and quality. The current study examined the role of exogenously applied low molecular weight organic acids (LMWOAs) including oxalic acid (OxA), tartaric acid (TA) and high molecular weight organic acids (HMWOAs) like citric acid (CA) and humic acid (HA) for the bioavailability of Cd in wheat-rice cropping system. Maximum increase in root dry-weight, shoot dry-weight, and grain/paddy yields was recorded with HA for both crops. The HA significantly decreased AB-DTPA Cd in contaminated soils which remained 41% for wheat and 48% for rice compared with their respective controls. The minimum concentration of Cd in roots, shoots and grain/paddy was observed in HA treatment in both crops. The organic acids significantly increased the growth parameters, photosynthetic activity, and relative leaf moisture contents for both wheat and rice crops compared to that with the contaminated control. Application of OxA and TA increased the bioavailability of Cd in soils and plant tissues while CA and HA decreased the bioavailability of Cd in soils and plants. The highest decrease in Cd uptake, bioaccumulation, translocation factor, immobilization, translocation, harvest, and health risk indices were observed with HA while maximum increase was recorded with OxA for both wheat and rice. The results concluded that use of HMWOAs is effective in soil Cd immobilization being maximum with HA. While LMWOAs can be used for the phytoextraction of Cd in contaminated soils having maximum potential with OxA

Role of Interventional Radiology in Management of Gastrointestinal Bleeding

Gastrointestinal bleeding is a common and potentially life-threatening condition that requires prompt and effective management. Interventional radiology has emerged as a valuable tool in the management of gastrointestinal bleeding, offering minimally invasive techniques that can rapidly control bleeding and improve patient outcomes. This review aims to provide an overview of the role of interventional radiology in the management of gastrointestinal bleeding, including its various techniques and their efficacy. The review discusses the different interventional radiology procedures that can be used to diagnose and treat gastrointestinal bleeding. It also highlights the advantages of techniques used in evaluation and management, including their ability to localize and control bleeding, as well as their low complication rates and shorter recovery times compared to traditional surgical approaches. Furthermore, the review addresses the specific indications for interventional radiology in the management of gastrointestinal bleeding, as well as the role of interventional radiology in the setting of underlying conditions. Overall, this review provides a comprehensive overview of the role of interventional radiology in the management of gastrointestinal bleeding, highlighting its effectiveness and potential benefits for patients. It also emphasizes the need for further research and collaboration between interventional radiologists and gastroenterologists to optimize the use of these techniques in clinical practice

Evolving trends in the management of acute appendicitis during COVID-19 waves. The ACIE appy II study

Background: In 2020, ACIE Appy study showed that COVID-19 pandemic heavily affected the management of patients with acute appendicitis (AA) worldwide, with an increased rate of non-operative management (NOM) strategies and a trend toward open surgery due to concern of virus transmission by laparoscopy and controversial recommendations on this issue. The aim of this study was to survey again the same group of surgeons to assess if any difference in management attitudes of AA had occurred in the later stages of the outbreak. Methods: From August 15 to September 30, 2021, an online questionnaire was sent to all 709 participants of the ACIE Appy study. The questionnaire included questions on personal protective equipment (PPE), local policies and screening for SARS-CoV-2 infection, NOM, surgical approach and disease presentations in 2021. The results were compared with the results from the previous study. Results: A total of 476 answers were collected (response rate 67.1%). Screening policies were significatively improved with most patients screened regardless of symptoms (89.5% vs. 37.4%) with PCR and antigenic test as the preferred test (74.1% vs. 26.3%). More patients tested positive before surgery and commercial systems were the preferred ones to filter smoke plumes during laparoscopy. Laparoscopic appendicectomy was the first option in the treatment of AA, with a declined use of NOM. Conclusion: Management of AA has improved in the last waves of pandemic. Increased evidence regarding SARS-COV-2 infection along with a timely healthcare systems response has been translated into tailored attitudes and a better care for patients with AA worldwide

Adaptive Control of a Reverse Logistic Inventory Model with Uncertain Deteriorations and Disposal Rates

An adaptive control of a reverse logistic inventory system with unknown deterioration and disposal rates is considered. An adaptive control approach with a feedback is applied to track the inventory levels toward their goal levels. Also, the updating rules of both deterioration and disposal rates are derived from the conditions of asymptotic stability of the reference model. Important characteristics of the adaptive inventory system are discussed. The adaptive controlled system is modeled by a nonlinear system of differential equations. Finally, the numerical solution of the controlled system is discussed and displayed graphically

Adaptive Control of a Two-Item Inventory Model with Unknown Demand Rate Coefficients

This paper considers a multiitem inventory model with unknown demand rate coefficients. An adaptive control approach with a nonlinear feedback is applied to track the output of the system toward the inventory goal level. The Lyapunov technique is used to prove the asymptotic stability of the adaptive controlled system. Also, the updating rules of the unknown demand rate coefficients are derived from the conditions of the asymptotic stability of the perturbed system. The linear stability analysis of the model is discussed. The adaptive controlled system is modeled by a system of nonlinear differential equations, and its solution is discussed numerically