MOALG: A Metaheuristic Hybrid of Multi-Objective Ant Lion Optimizer and Genetic Algorithm for Solving Design Problems

This study proposes a hybridization of two efficient algorithm’s Multi-objective Ant Lion Optimizer Algorithm(MOALO)which is a multi-objective enhanced version of the Ant Lion Optimizer Algorithm(ALO)and the Genetic Algorithm(GA).MOALO version has been employed to address those problems containing many objectives and an archive has been employed for retaining the non-dominated solutions.The uniqueness of the hybrid is that the operators like mutation and crossover of GA are employed in the archive to update the solutions and later those solutions go through the process of MOALO.A first-time hybrid of these algorithms is employed to solve multi-objective problems.The hybrid algorithm overcomes the limitation of ALO of getting caught in the local optimum and the requirement of more computational effort to converge GA.To evaluate the hybridized algorithm’s performance,a set of constrained,unconstrained test problems and engineering design problems were employed and compared with five well-known computational algorithms-MOALO,Multi-objective Crystal Structure Algorithm(MOCryStAl),Multi-objective Particle Swarm Optimization(MOPSO),Multi-objective Multiverse Optimization Algorithm(MOMVO),Multi-objective Salp Swarm Algorithm(MSSA).The outcomes of five performance metrics are statistically analyzed and the most efficient Pareto fronts comparison has been obtained.The proposed hybrid surpasses MOALO based on the results of hypervolume(HV),Spread,and Spacing.So primary objective of developing this hybrid approach has been achieved successfully.The proposed approach demonstrates superior performance on the test functions,showcasing robust convergence and comprehensive coverage that surpasses other existing algorithms.

Prospects to the formation and control of potential dimer impurity E of pantoprazole sodium sesquihydrate

Pantoprazole sodium, a substituted benzimidazole derivative, is an irreversible proton pump inhibitor which is primarily used for the treatment of duodenal ulcers, gastric ulcers, and gastroesophageal reflux disease (GERD). The monographs of European Pharmacopoeia (Ph. Eur.) and United States Pharmacopoeia (USP) specify six impurities, viz.;impurities A, B, C, D, E and F, respectively for its active pharmaceutical ingredient (API). The identification and synthesis of all impurities except impurity E are well described in the literature;however, there is no report related to impurity E. The prospects to the formation and controlling of impurity E up to -0.03% in the synthesis of pantoprazole sodium sesquihydrate (PAN) were discussed in detail for the first time. The present work described the journey towards the successful development of an optimal preparation procedure of dimer impurity E. The most plausible mechanism involved in the formation of impurity E has been proposed.

Soil Salinity Mapping and Monitoring in Arid and Semi-Arid Regions Using Remote Sensing Technology: A Review

Soil salinity is a serious environmental problem especially in arid and semiarid areas. It either occurs naturally or is human-induced. High levels of soil salinity negatively affect crop growth and productivity leading land degradation ultimately. Thus, it is important to monitor and map soil salinity at an early stage to enact effective soil reclamation program that helps lessen or prevent future increase in soil salinity. Remote sensing has outperformed the traditional method for assessing soil salinity offering more informative and professional rapid assessment techniques for monitoring and mapping soil salinity. Soil salinity can be identified from remote sensing data obtained by different sensors by way of direct indicators that refer to salt features that are visible at the soil surface as well as indirect indicators such as the presence of halophytic plant and assessing the performance level of salt-tolerant crops. The purposes of this paper are to 1) discuss some soil salinity indicators;2) review the satellite sensors and methods used for remote monitoring, detecting and mapping of soil salinity, particularly in arid and semi-arid regions;3) review various spectral vegetation and salinity indices that have been developed and proposed for soil salinity detection and mapping, with an emphasis on soil salinity mapping and assessment in arid and semi-arid regions;and 4) highlight the most important issues limiting the use of remote sensing for soil salinity mapping, particularly in arid and semi-arid regions.

Investigating the Use of Remote Sensing and GIS Techniques to Detect Land Use and Land Cover Change: A Review

The accuracy of change detection on the earth’s surface is important for understanding the relationships and interactions between human and natural phenomena. Remote Sensing and Geographic Information Systems (GIS) have the potential to provide accurate information regarding land use and land cover changes. In this paper, we investigate the major techniques that are utilized to detect land use and land cover changes. Eleven change detection techniques are reviewed. An analysis of the related literature shows that the most used techniques are post-classification comparison and principle component analysis. Post-classification comparison can minimize the impacts of atmospheric and sensor differences between two dates. Image differencing and image ratioing are easy to implement, but at times they do not provide accurate results. Hybrid change detection is a useful technique that makes full use of the benefits of many techniques, but it is complex and depends on the characteristics of the other techniques such as supervised and unsupervised classifications. Change vector analysis is complicated to implement, but it is useful for providing the direction and magnitude of change. Recently, artificial neural networks, chi-square, decision tree and image fusion have been frequently used in change detection. Research on integrating remote sensing data and GIS into change detection has also increased.

Land Use and Land Cover Change Detection in the Saudi Arabian Desert Cities of Makkah and Al-Taif Using Satellite Data

Land use/land cover (LULC) changes have become a central issue in current global change and sustainability research. Saudi Arabia has undergone significant change in land use and land cover since the government embarked on a course of intense national development 30 years ago, as a result of huge national oil revenues. This study evaluates LULC change in Makkah and Al-Taif, Saudi Arabia from 1986 to 2013 using Landsat images. Maximum likelihood and object-oriented classification were used to develop LULC maps. The change detection was executed using post-classification comparison and GIS. The results indicated that urban areas have increased over the period by approximately 174% in Makkah and 113% in Al-Taif. Analysis of vegetation cover over the study area showed a variable distribution from year to year due to changing average precipitation in this environment. Object-based classification provided slightly greater accuracy than maximum likelihood classification. Information provided by satellite remote sensing can play an important role in quantifying and understanding the relationship between population growth and LULC changes, which can assist future planning and potential environmental impacts of expanding urban areas.

Impact of three dimensional printing in orthopedics

The primary objective of this article is to explore effects of latest development in the area of three dimensional(3D)printing&to assess its abilities,and further undertake helpful reporting.Here the focus is to assess ad vantages of 3D printing in orthopedics and analyze how 3D printed models help solve complex 3D orthopedics distortions.This study identified that 3D models manufactured by 3D printing models reduce medical parts de velopment cost and surgical planning time.Integrating 3D printing with orthopaedics helps in understanding the conditions of problems and achieving the operation succssfully.This technology can enable doctors/surgeons to design,produce,recreate and plan operations more accurately,carefully,and economicaly.3D models can assist specialists with a visual comprehension of the patient-particular pathology and life structures.Innovation in 3D printing initiated a scaffold for the virtual outline and execution of medical procedures.This research proposes the utilisation of 3D printers as an elective procedure for the fabrication of parts.It empowers surgeons/patients for better raining,education and research.In the future,there is a foreseeable expansion of additive manufacturing in orthopedics.

Cr （Ⅲ） Removal from Synthetic Waste Water by Using Water Pond Mud

The pollution of aquatic ecosystem by heavy metals has assumed serious proportions due to their toxicity and accumulative behavior. The toxicity metal is dependent on its chemical form and therefore removal of metal is more meaningful than the estimation of its concentrations. In this study, the batch experiments were carried out under 30℃ to study the effect of pH, initial Cr concentration, adsorbent dose and contact time on the removal of Cr （lII）. The maximum adsorption efficiency （99%） was observed when 1.5 g of pond mud was used for removal ofCr （Ⅲ） from test solution containing 150 mg·Cr / 100 ml. The optimal pH and contact time recorded during the study were 6 and 10.0, respectively.

Modelling Impacts of Climate Change on Maize (<i>Zea mays</i>L.) Growth and Productivity: A Review of Models, Outputs and Limitations

The use of crop modelling in various cropping systems and environments to project and upscale agronomic decision-making under the facets of climate change has gained currency in recent years. This paper provides an evaluation of crop models that have been used by researchers to simulate maize growth and productivity. Through a systematic review approach, a comprehensive assessment of 186 published articles was carried out to establish the models and parameterization features, simulated impacts on maize yields and adaptation strategies in the last three decades. Of the 23 models identified, CERES-maize and APSIM models were the most dominant, representing 49.7% of the studies undertaken between 1990 and 2018. Current research shows projected decline in maize yields of between 8% - 38% under RCP4.5 and RCP8.5 scenarios by the end of the 21st century, and that adaptation is essential in alleviating the impacts of climate change. Major agro-adaptation options considered in most papers are changes in planting dates, cultivars and crop water management practices. The use of multiple crop models and multi-model ensembles from general circulation models (GCMs) is recommended. As interest in crop modelling grows, future work should focus more on suitability of agricultural lands for maize production under climate scenarios.

Are there Monthly Variations in Water Quality in the Amman, Zarqa and Balqa Regions, Jordan?

This study investigated the monthly variation of water quality in the Amman-Zarqa and Balqa regions in Jordan in terms of pH, ammonium, nitrate and conductivity. During 2004 there was no monthly variation in water quality for most of the tested parameters. All readings were above the accepted range except for pH, indicating that land use does have an impact on water quality irrespective of urban, industrial or agricultural usage. The water quality remained for the most part below the maximum levels for drinking standards in Jordan, but these standards are often below the WHO recommendations. The pH was found to fluctuate through the year. Nitrate levels were highly seasonal in irrigated lands but remained stable over basin covered by other land uses. Ammonium levels were high in areas of urbanisation and intensive animal husbandry as a consequence of effluent infiltration, peaking during the wet season due to increased infiltration. These results indicate that, over an annual cycle, the variation in water quality remains constant;however the continued drawdown of the aquifer system will inevitably lead to deterioration in the parameters investigated.

Cervical cancer:a tale from HPV infection to PARP inhibitors

Globally,cervical cancer(CxCa)ranks 4th common cancer among females and led to 569,847 incidences and 311,365 deaths in 2018.80%of CxCa cases occur due to persistent infection with a high-risk subtype of human papillomavirus(HPV-16 and 18).Smoking,high par-ity,and co-infection with type 2 herpes simplex or HIV are other known risk factors for CxCa.Major histological subtypes are squamous(70%)and adenocarcinoma(25%).Presently,concur-rent radiation plus cisplatin(CDDP)-based chemotherapy is the standard treatment for CxCa patients.However,CDDP resistance and toxic side effects limit its efficacy,leading to a poorer response rate and an expected overall survival ranging from 10 to 17.5 months.Reduced drug uptake,increased DNA damage repair,increased CDDP inactivation,and overexpressed Bcl-2 or caspase inhibition,are primarily accountable mechanisms for CDDP resistance and improving CDDP’s efficacy remains the major challenge.Poly(ADP-ribosyl)polymerase-1,an effective mediator of nucleotide excision repair pathway,is involved in DNA repair as well as maintaining genomic stability and is significantly expressed in malignant lymphomas,hepa-tocellular-,cervical-and colorectal carcinoma,which has been approved effective in mainte-nance therapy and may serve as an effective target to enhance CDDP sensitivity in CxCa.Here,we summarize the etiology and epidemiology of and treatment for CxCa,the mechanism responsible for chemotherapy resistance,PARP inhibitor as a possible therapy for CxCa,and other possible chemotherapeutic options for CxCa treatment.

Experimental and numerical evaluation of multidirectional compressive and flexure behavior of three-dimensional printed concrete

Three-dimensional concrete printing(3DCP)can proliferate the industrialization of the construction sector,which is notoriously conservative and indolent toward changes.However,the mechanical behavior of 3DCP should be characterized and modeled considering the interfaces when its performance is thoroughly compared to that of the existing concrete construction methods.This study presents an experimental and numerical investigation of uniaxial compression and three-point bending(TPB)tests on extruded 3DCP beams in different loading directions.The orientation of translational and depositional interfaces with respect to the direction of loading influenced the strength.Both the elastic and post-damage behavior of the 3DCP specimens were compared with those of the conventionally cast specimen under quasi-static loading conditions.Despite the higher compressive strength of the casted specimen,the flexural strength of the 3DCP specimens was higher.This study employed the finite element and cohesive zone models of the appropriate calibrated traction-separation law to model fracture in the notched TPB specimens.Furthermore,the real-time acoustic emission test revealed the nature of failure phenomenon of three-dimensional-printed specimens under flexion,and accordingly,the cohesive law was chosen.The predicted load-displacement responses are in good agreement with the experimental results.Finally,the effects of cohesive thickness and notch shape on the performance under bending were explored through parametric studies.

Propagation of waves over a rugged topography

The propagation of waves in shallow waters is affected by the bottom topography unlike deep water waves of the coastal environment.Due to the interaction of the wave with bed topography,the wave transformation processes occur.Refraction,diffraction,shoaling,and breaking are the wave transforma-tion processes that occur in the coastal environment.The significant wave height over rugged topography is a standardized statistics to denote the characteristic height of the random waves in a sea state.There-fore,the objective of the present study is to predict the significant wave height over rugged topography.The SWAN standalone and SWAN DHH platform are used to predict significant wave height over rugged topography in Mehamn harbour,Norway.The SWAN model results are almost similar to the lab data of Vold and Lothe(2009)for all the 22 scenarios at all the output locations.Further,the four cases reported by Taehun(2011)and lab data from Vold and Lothe(2009)for that four cases are compared with the SWAN model results.It is observed that the SWAN model results are much closer to the lab data of Vold and Lothe(2009).