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If chafing behaviours on the bottom or rocks are common, interspecific events are rare and usually involve smaller ray-finned fishes rubbing on larger sharks or manta rays. Reports on interspecific chafing between fishes and reptiles are even less common, with just one report of great barracudas (Sphyraena barracuda) using swimming hawksbill (Eretmochelys imbricata) and green turtles (Chelonia mydas) as chafing surfaces in the Southwestern Atlantic. Here, we describe a chafing interaction between a great barracuda and a hawksbill turtle in the Red Sea. Our observation provides evidence that this interaction is probably not localised but may represent a more widespread behavioural pattern than previously thought. This chafing behaviour is suggested to remove external parasites, and our observation documents the behaviour of the scraper and the scraped animal, as well as the reaction of the parasites during the same event, clearly demonstrating that chafing behaviour aims at the removal of parasitic copepods (Caligidae). We also report the evasive behaviour of the copepods during the event, providing novel information on parasite removal in reef fishes. Highlights: Great barracudas scrape the carapace of sea turtles for parasite removal. First report of parasitic copepods actively evading dislodging attempts. [ABSTRACT FROM AUTHOR]

The remarkable mechanical properties of high-performance concrete (HPC) make it indispensable in a wide range of engineering applications. Predicting HPC’s compressive strength with precision is essential to guaranteeing its structural stability and longevity. The present work introduces a novel method for predicting HPC compressive strength (CS) by utilizing the Multi-layer Perceptron (MLP) model in conjunction with three distinct optimizers, namely Northern Goshawk Optimization (NGO), Manta Ray Foraging Optimization (MRFO), and Atom Search Optimization (ASO). An effective method for capturing complex relationships between input and output variables is the multi-layer perceptron (MLP) in artificial neural networks. Developing a dependable, robust predictive model is the goal of training the MLP model on a variety of datasets of HPC mixtures and CS. As evidenced by the MLNG model’s R2 value of 0.994 and RMSE of 1.3572, the joint efforts of MRFO, NGO, and ASO during the optimization phase improve the MLP model and produce promising results. These results clarify how different optimizers play a crucial role in improving the accuracy of HPC compressive strength predictions made with the MLP model. This information helps make better decisions regarding design and construction methods for HPC. [ABSTRACT FROM AUTHOR]

Lung cancer starts in the lungs and spreads to other organs in the body. Premature identification can only help the doctor to make an exact diagnosis and it may save the life of patients. Numerous studies have been conducted in this area, but none of them attains the accuracy outcomes. To overcome this drawback, a deep multi-scale three dimensional convolutional neural network optimized with the manta ray foraging optimization algorithm is proposed in this article for lung cancer classification on CT images (LCCT-DMS3DCNN-MRFOA) which effectively classifies the lung cancer as benign or malignant. The simulation is executed in MATLAB. The ELCAP dataset is utilized to confirm the performance of the proposed LCCT-DMS3DCNN-MRFOA approach. The efficiency of the LCCT-DMS3DCNN-MRFOA approach attains 14.21%, 22.96% and 24.94% higher accuracy; 12.59%, 11.71% and 11.55% higher AUC and 59.83%, 53.05% and 61.41% lower computational time compared with existing methods. [ABSTRACT FROM AUTHOR]

The decarburization of heat and transport using electric vehicles (EVs) and heat pumps (HPs) needs an important investment in low-voltage (LV) networks. This article proposes an optimization approach to estimate the availability of headroom for domestic EV charging and optimization on LV networks under various penetrations of heat pumps. The proposed optimization approach is called dynamic differential annealed optimization (DDAO). The objective of the proposed approach is to maximize the hosting capability of low-voltage networks for EVs and HPs by optimizing the flexibility of EV charging. The DDAO is used to optimize different aspects of EV charging and LV networks. The DDAO approach is implemented in three steps: (a) HP headroom assessment, (b) EV optimization, and (c) validation. The performance of the proposed method is validated on a MATLAB platform and compared with the existing Binary Spring Search Algorithm (BSSA), Manta Ray Foraging Optimization Algorithm (MRFO), and Chaos Game Optimization methods. In comparison to the total prices of 3.5£ in BSSA, 4.5£ in MRFO, and 5.5£ in CGO, the proposed DDAO method achieves a lower total price of 3.2£. This suggests that the DDAO method is more cost-effective than the existing techniques. [ABSTRACT FROM AUTHOR]

In this work the material is first checked for its health by using point contact method. Then the behavioural characteristic of the material is found once the material is decided as healthy one. After, this the healthy material is drilled in microns to produce damage. The damaged materials are studied by point contact method and their deflections are illustrated. The behaviour of the piezoelectric material is also predicted by using hybrid Deep Convolution Neural Network based on Manta Ray Foraging Optimisation (Hybrid DCNN-MRFO). This work has attained for about 93% in accuracy. [ABSTRACT FROM AUTHOR]

Sports video classification (SVC) is now considered a challenging topic, therefore, developing an automatic sports scene classification technique has received tremendous interest. This research develops an efficient key frame extraction method and hybrid Wavelet Convolution Neural Network (WCNN) framework with optimization scheme to classify sports videos. Initially, input videos are converted into number of frames, and keyframes are extracted using Enhanced threshold with Discrete Wavelet Transform (ETDWT) method. Then, Cross Guided Bilateral Filter (CGBF) method eliminates the noise from the keyframe. After that, segmentation process is performed by the Fuzzy Equilibrium Optimizer (FEO) algorithm, and then motions are detected using the Farneback optical flow (OF) method. Finally, classification process is performed using Hybrid Wavelet Convolutional Manta Ray Foraging Optimization (HWCMRFO) algorithm to categorize different sports videos. The overall work is implemented using Python language. Simulation results proved that the proposed work achieved the highest accuracy (93.17%) compared to existing approaches. [ABSTRACT FROM AUTHOR]

This study investigates the feasibility of a relevance vector machine tuned with improved Manta-Ray foraging optimization (RVM-IMRFO) in predicting monthly pan evaporation using limited climatic input data (e.g. temperature). The accuracy of the RVM-IMRFO was evaluated by comparing it with RVM tuned by gray wolf optimization, RVM tuned with a whale optimization algorithm, and RVM tuned with Manta Ray foraging optimization concerning root mean square errors (RMSE), mean absolute errors (MAE), determination coefficient (R²) and Nash-Sutcliffe Efficiency (NSE) and new graphical inspection methods. The models were assessed using data acquired from two stations in China and data were divided into three equal parts. The models were tested using each data set. The application outcomes revealed that the proposed algorithm considerably improved the accuracy of a single RVM in monthly pan evaporation prediction by an average improvement in RMSE, MAE, R², and NSE as 27.65%, 27.53%, 8.40% and 8.63%, respectively. It is also found that the proposed algorithm showed significant dominance over others models with respect to improvement in overall mean values of RMSE, MAE, R², and NSE statistics from 34.7-38.2 to 18.2-19.5, 36.2-36.4 to 19.1-18.5, 12.5-13.8 to 3.6-3.7, and 12.4-14.6 to 3.6-3.9%, for both climatic stations, respectively. Importing extraterrestrial radiation and periodicity component (month number of the data) into the model inputs improved the prediction accuracy of the implemented models. The outcomes revealed that the RVM-IMRFO performed superior to the other methods in predicting monthly pan evaporation using only temperature data which is essential, especially in developing countries where other climatic data are missing or unavailable. The RVM model was also compared with standard multi-layer perceptron neural networks (MLPNN) and found that the first acts better than the latter in monthly pan evaporation prediction. [ABSTRACT FROM AUTHOR]

Targeting the problem of traditional sparrow search algorithms being prone to falling into local optima, a new algorithm called the Chaotic Sparrow Search Algorithm with Manta Ray Spiral Foraging (abbreviated as MSSA) is proposed. The Logistic-Sine-Cosine chaotic map and elite Reverse learning strategy are fused to initialize the population. It is experimentally demonstrated that this hybrid strategy outperforms the population after random initialization in reducing ineffective sparrow individuals. In the vigilante update stage, the spiral foraging behaviour of the manta ray population in the integrated manta ray optimization algorithm, the sparrows search around the best food source, which enhances the sparrow search algorithm's ability to explore the optimal solution. To enhance the stability of the algorithm to search for the optimum, a mixed Gaussian variational and logistic perturbation strategy is proposed to further improve the performance of the algorithm. Finally, using 12 commonly used benchmark test functions and the Wilcoxon rank sum test, MSSA was compared with other original algorithms and advanced improved algorithms, it is demonstrated that MSSA has higher accuracy and convergence performance, and the improved MSSA algorithm is applied to three types of engineering optimization problems with constraints, demonstrating its feasibility and effectiveness. [ABSTRACT FROM AUTHOR]

The main task in Wire Electrical Discharge Machining (WEDM) is to select the proper tool material for machining the workpiece to get better surface finishing and high cutting speed. To overcome these challenges, nowadays, coated electrodes are used. The main objective of this research work is to study the impact of certain input parameters such as pulse off-time, pulse on-time, servo voltage, and peak current in WEDM on Material Removal Rate (MRR), Recast Layer Thickness (RLT), and Surface Roughness (SR) output parameters by using zinc-coated brass wire as an electrode and AISI P20+Ni (DIN 1.2738) as the workpiece. One of the hardest materials used to make die for plastic moulds. The study is carried out experimentally and then compared with the design done by response surface methodology (RSM) using ANOVA and hybrid deep neural network (DNN) predicted values, which are optimised based on Manta ray foraging optimisation (MRFO) to obtain more precise outputs. The developed RSM and hybrid DNN+MRFO were designed in Design Expert 12 and MATLAB R2020a platforms and achieved 90% average prediction accuracy in the DNN+MRFO method. The experimentally obtained maximum MRR and minimum RLT and SR are 2.657 mm3/min, 7.9 µm, and 0.351 µm, respectively. The regression results showed that DNN+MRFO outperforms the RSM model. The achieved desirability at confirmatory analysis for RSM and DNN+MRFO are 0.844 and 0.921, respectively. [ABSTRACT FROM AUTHOR]

First-time observations of courtship behaviour of the Endangered shortfin devil ray Mobula kuhlii are described from the Aliwal Shoal Marine Protected Area (MPA), KwaZulu-Natal, South Africa. Three events of M. kuhlii courtship, called 'mating trains', were recorded on video during the months of November 2020 and January 2021. These included a near-term pregnant female, and two lead females followed by up to four males. The common behaviours associated with courtship were documented: multiple males following a single female, rapid speed bursts, avoidance of the female, and swerving. This study confirms that M. kuhlii mating occurs in KwaZulu-Natal waters and that courtship is similar across mobulids. The findings demonstrate the importance of the habitat provided by the Aliwal Shoal MPA for this currently unprotected species. [ABSTRACT FROM AUTHOR]

We provide the complete mitochondrial genome of the reef manta ray, Mobula alfredi, using an ezRAD approach. The total length of the mitogenome was 18,166 bp and contained 13 protein-coding genes, 22 transfer RNAs genes, two ribosomal RNA genes, and one non-coding control region. The gene organization and length are similar to other Mobula species. This reference mitogenome that includes the control region is expected to be a valuable resource for molecular-based species identification, population genomics, and phylogeography. [ABSTRACT FROM AUTHOR]

Floods are the most dangerous natural disasters globally, occurring on a large scale, and cause significant economic and environmental damage. Therefore, determining flood susceptibility is essential to reducing the flood effects on human lives and materials. The main objective of this research is to develop a novel hybrid algorithm, through combining deep neural network and Manta ray foraging optimization (DNN-MRFO), to generate flood susceptibility map for Quang Ngai province, Vietnam. A geospatial distribution analytical approach was used to generate input data, including 2176 flood locations points and 13 influencing factors. A comparative analysis of the proposed model with five models namely DNN -- particle swarm optimization (DNN-PSO), DNN -- grey wolf optimization (DNN-GWO), DNN -- social spider optimization (DNN-SSO), support vector machine (SVM), gradient boosting regression (GBR) was carried out using different evaluation indices. The result shows that combining DNN and MRFO improved flood susceptibility classification precision with an area under the curve (AUC) of 0.98. The findings of this study are significant for supporting policymakers in understanding and identifying issues, which support improve their adaptation strategies. [ABSTRACT FROM AUTHOR]

Manta ray tourism is estimated to contribute US$ 140 million annually to the global economy. The multitudes of tourists potentially disturb the animals, yet the effect of human behaviour on feeding manta rays has not been quantified. Using videos collected at feeding sites in the Maldives, we found that only 44% of observed human-manta interactions complied with existing guidelines. Human behaviours; accidental obstruction, diving too near/in front, chasing, and approaching from the front, all had a statistically significant negative effect on behaviour, resulting in feeding cessation, while passive interactions resulted in significantly less disturbance and cessation reactions. Interactions within three metres caused significantly increased avoidance behaviours. These findings support the guidelines provided by the Manta Trusts' code of conduct, which aims to develop legislation to minimise disturbance by tourism. Our key recommendations aim to ensure that the manta ray tourism industry remains sustainable and non-detrimental to the animals' natural behaviour. Visit https://swimwithmantas.org/ for video abstract. [ABSTRACT FROM AUTHOR]

Though South Africa is rich in aquatic species, little is known about the diversity and distribution of copepods that parasitize different hosts ranging from invertebrates to marine mammals. A total of 43 mobulids (34 Mobula kuhlii; two Mobula eregoodootenkee and seven Manta alfredi) were examined for infection by symbiotic copepods at the KwaZulu-Natal Sharks Board (KZNSB). Collected copepod specimens were fixed and preserved in 70% ethanol and studied with the stereo- and light microscopes. Most of the examined hosts (38) were infected with symbiotic siphonostomatoids. Ten different species representing five families were identified. Of these, seven represent new host records while four are new geographical records. The highest prevalences (>60%) were calculated for Eudactylina oliveri and Pupulina cliffi on M. eregoodootenkee and M. kuhlii while E. oliveri also exhibited the highest mean intensity values on these hosts. [ABSTRACT FROM AUTHOR]

The complete mitochondrial genome of a widely distributed pelagic ray, the Spinetail Devilray ( Mobula japanica), consists of 18,880 bp with high A+T and low G content. Gene configuration and length is similar to other vertebrates and comprises 13 protein-coding genes, 2 rRNAs genes (12S and 16S rRNA), 22 tRNAs genes, and 1 major non-coding sequence, the control region. A remarkable feature in the mitochondrial genome of M. japanica is three tandemly repeated areas in the control region, together comprising a length of almost 1500 bp, making this to our knowledge the longest elasmobranch mitochondrial genome published so far. [ABSTRACT FROM AUTHOR]

The article focuses on a study about manta ray, particularly on its massive, flapping fins that produce the shark cousin's 20-foot wingspan and the two fleshy growths curling out of its head. Information about the hornlike cephalic lobes of manta rays, which represented a curious problem to the researchers of the study, is presented.

The article looks at a study by researcher Joshua Stewart and others observed the juvenile mantas while conducting research on manta population structure at Flower Garden Banks. It mentions identification of area as a nursery highlights its importance for conservation and management and species and the importance of different habitats throughout their lives. It also mentions discovery of manta ray nursery in the Gulf of Mexico.

The planktivorous mobulid rays are a sister group to, and descended from, rhinopterid and myliobatid rays that possess a dentition showing adaptations consistent with a specialized durophagous diet. Within the Paleocene and Eocene, there are several taxa that display dentitions apparently transitional between these extreme trophic modalities, in particular the genusBurnhamia. The holotype ofBurnhamia daviesiwas studied through X-ray computed tomography (CT) scanning. Digital renderings of this incomplete but articulated jaw and dentition revealed previously unrecognized characters regarding the jaw cartilages and teeth. In addition, the genusSulcidens, gen. nov., is erected for articulated dentitions from the Paleocene previously assigned toMyliobatis. Phylogenetic analyses confirmBurnhamiaas a sister taxon to the mobulids and the Mobulidae as a sister group toRhinoptera. Shared dental characters betweenBurnhamiaandSulcidenslikely represent independent origins of planktivory within the rhinopterid-myliobatid clade. The transition from highly specialized durophagous feeding morphologies to the morphology of planktivores is perplexing but was facilitated by a pelagic swimming mode in these rays and, we propose, through subsequent transition from either meiofauna-feeding or pelagic fish-feeding to pelagic planktivory. http://zoobank.org/urn:lsid:zoobank.org:pub:511E9C39-1208-4F56-8DC1-2B92D2EDB4B3 Citation for this article: Underwood, C. J., M. A. Kolmann, and D. J. Ward. 2017. Paleogene origin of planktivory in the Batoidea. Journal of Vertebrate Paleontology. DOI: 10.1080/02724634.2017.1293068. [ABSTRACT FROM AUTHOR]