The 1994 positive Indian Ocean Dipole event as investigated by the transfer routes of oceanic wave energy

The present study investigates the interannual variability of the tropical Indian Ocean (IO) based on the transfer routes of wave energy in a set of 61-year hindcast experiments using a linear ocean model. To understand the basic feature of the IO Dipole mode, this paper focuses on the 1994 pure positive event. Two sets of westward transfer episodes in the energy flux associated with Rossby waves (RWs) are identified along the equator during 1994. One set represents the same phase speed as the linear theory of equatorial RWs, while the other set is slightly slower than the theoretical phase speed. The first set originates from the reflection of equatorial Kelvin waves at the eastern boundary of the IO. On the other hand, the second set is found to be associated with off-equatorial RWs generated by southeasterly winds in the southeastern IO, which may account for the appearance of the slower group velocity. A combined empirical orthogonal function (EOF) analysis of energy-flux streamfunction and potential reveals the intense westward signals of energy flux are attributed to off-equatorial RWs associated with predominant wind input in the southeastern IO corresponding to the positive IO Dipole event.

Length at Maturity, Sex Ratio, and Proportions of Maturity of the Giant Electric Ray, Narcine entemedor, in Its Septentrional Distribution

The size at which a certain fraction of a fish population reaches sexual maturity is an important parameter of life history. The estimation of this parameter based on logistic or sigmoid models could provide different ogives and values of length at maturity, which must be analyzed and considered as a basic feature of biological reproduction for the species. A total of 305 individuals of Narcine entemedor (N. entemedor) were obtained from artisanal fisheries in the Bahía de La Paz, Mexico. For the organisms sampled, sexes were determined and total length (TL) in cm was measured from October 2013 to December 2015. The results indicated that the females were larger, ranging from 48.5 cm to 84 cm TL, while males varied from 41.5 cm to 58.5 cm TL. The sex ratio was dominated by males ranging from 45–55 cm TL, while females were more abundant from 60 to 85 cm TL. Mature females were present all year long, exhibiting a continuous annual reproductive cycle. The length at maturity data were described by the Gompertz model with value of 55.87 cm TL. The comparison between models, and the model selection between them, showed that the Gompertz model had maximum likelihood and smaller Akaike information criterion, indicating that this model was a better fit to the maturity proportion data of N. entemedor.

Recognition of Metal Ion Ligand-Binding Residues by Adding Correlation Features and Propensity Factors

The realization of many protein functions is inseparable from the interaction with ligands; in particular, the combination of protein and metal ion ligands performs an important biological function. Currently, it is a challenging work to identify the metal ion ligand-binding residues accurately by computational approaches. In this study, we proposed an improved method to predict the binding residues of 10 metal ion ligands (Zn2+, Cu2+, Fe2+, Fe3+, Co2+, Mn2+, Ca2+, Mg2+, Na+, and K+). Based on the basic feature parameters of amino acids, and physicochemical and predicted structural information, we added another two features of amino acid correlation information and binding residue propensity factors. With the optimized parameters, we used the GBM algorithm to predict metal ion ligand-binding residues. In the obtained results, the Sn and MCC values were over 10.17% and 0.297, respectively. Besides, the Sn and MCC values of transition metals were higher than 34.46% and 0.564, respectively. In order to test the validity of our model, another method (Random Forest) was also used in comparison. The better results of this work indicated that the proposed method would be a valuable tool to predict metal ion ligand-binding residues.

Judicial Approaches to the Criminalisation of Marital Rape

In India, as in different traditional cultures, women have been and still are treated in a number of inhumane ways. They are controlled, prone to assault and abuse and risk rape not only outside but within their own homes. Moreover, marital rape is not considered a crime in India. The article attempts to analyse Indian rape laws and to show that exemption for marital rape does not align with the fundamental principles of justice and equality, which is the basic feature of the Indian Constitution. The article argues that the exemption clause should be repealed, and marital rape be criminalised. The article further discusses the approach of the Indian judiciary towards the issue of criminalisation of marital rape.

La complessità dei diritti personali e il dibattito sul Codice civile uniforme in India

SOMMARIO: 1. Introduzione - 2. La logica dell’uniformazione - 3. Due significati di “complessità”. The complexity of personal laws and the debate on the Uniform Civil Code in India ABSTRACT: The promulgation of the Uniform Civil Code, envisaged in the Indian Constitution as a Directive Principle of State Policy, has been at the center of a debate on overcoming the application of personal laws in matters of family and succession that has always been present in the Indian context and has recently been revived. The contribution identifies as useful keys for analysis on the one hand the logic of uniformisation as choice and, on the other hand, complexity, understood both as the operational difficulty of managing a system of laws applied on a personal basis and as a basic feature of continuous interactions between different principles and rules in a highly pluralistic context.

Reassessment of the Concept of Momentum in Econophysics

We examine the most basic feature of the economic process - momentum - under the point of view of analogies with physical laws, as they were reformulated recently [1]. Our approach is applied with minimal assumptions and we conclude that the inclusion of entropy as an effective variable in econophysics may bring a new vision of economic progress and the possibility to harness economic waves as a means to transport development from rich to poor countries using trade and technological progress. A new technical indicator for the stock market is proposed offering double opportunities on enter and exit trades, when compared to the Relative Strength Index usually used in analysis of financial markets.

Ship Targets Detection in Remote Sensing Images Based on Improved Faster-RCNN

An improved algorithm is proposed to solve the problems of inaccurate recognition and low recall of Faster-Regions with Convolutional Neural Network (Faster-RCNN) algorithm for the detection of ship targets in remote sensing images. The algorithm is based on the Faster-RCNN network framework. Aiming at the small size and dense distribution of ship targets in remote sensing images, the feature extraction network is improved to enhance the detection ability of small targets. ResNet50 is used as the basic feature extraction network of the algorithm,and the hole residual block is introduced for multi-layer feature fusion to construct a new feature extraction network,which improves the feature extraction capability of the algorithm. The experimental results show that compared with the Faster-RCNN algorithm, this algorithm can learn more abundant target features in smaller pixel areas, thereby effectively improving the detection accuracy of ship targets.

Oceanography of the Arabian Sea during the southwest monsoon season Part II: Stratification and circulation

The distribution of mass in the Arabian Sea during the southwest monsoon season, 1963 is presented through several vertical sections and spatial distribution charts of the thermosteric anomaly. The circulation patterns in the upper 200 m are derived. The basic feature of circulation is found to be the formation of several cyclonic and anti-cyclonic cells. Upwelling off the southwest coast of India has been explained on a more rational basis than has been assumed hitherto. It is now attributed partly due to the divergence in the current field and partly due to the cyclonic motion around Laccadive and Maldive Island.

Brain Activity Recognition Method Based on Attention-Based RNN Mode

Brain activity recognition based on electroencephalography (EEG) marks a major research orientation in intelligent medicine, especially in human intention prediction, human–computer control and neurological diagnosis. The literature research mainly focuses on the recognition of single-person binary brain activity, which is limited in the more extensive and complex scenarios. Therefore, brain activity recognition in multiperson and multi-objective scenarios has aroused increasingly more attention. Another challenge is the reduction of recognition accuracy caused by the interface of external noise as well as EEG’s low signal-to-noise ratio. In addition, traditional EEG feature analysis proves to be time-intensive and it relies heavily on mature experience. The paper proposes a novel EEG recognition method to address the above issues. The basic feature of EEG is first analyzed according to the band of EEG. The attention-based RNN model is then adopted to eliminate the interference to achieve the purpose of automatic recognition of the original EEG signal. Finally, we evaluate the proposed method with public and local data sets of EEG and perform lots of tests to investigate how factors affect the results of recognition. As shown by the test results, compared with some typical EEG recognition methods, the proposed method owns better recognition accuracy and suitability in multi-objective task scenarios.

DA-M2Det: An Iris Classification Network for UBM Images

Primary angle closure glaucoma (PACG) is primarily diagnosed by ophthalmologists through morphological analysis of the iris in ultrasonic biomicrocopy(UBM). In recent years, Deep convolutional neural networks (CNNs) show potential for quick category definition in eye disease. According to the characteristics of iris in UBM images, we proposed a network (DenseNet and Attention gate) DA-M2Det to automatic classification iris morphology. Firstly, in the framework of M2Det network, We used the backbone of DenseNet to replace the VGG backbone of M2Det, better extraction of basic feature layers. Secondly, three scales of attention gate (AG) was added to the Thinned U-shape Module (TUM), enable the network to pay more attention to the iris region. Finally, we use the retraining method to further improve the accuracy of iris classification. The classification results of VGG-16, M2Det, ResNet-50 and DA-M2Det networks are compared experimentally. The results show that, in three different iris shapes (including arch, flat and depression), DA-M2Det achieves an average classification accuracy of 85%, which is higher than that of the other three networks. Experimental results show that DA-M2Det can accurately classify irises into three categories, assisting ophthalmologists to quickly diagnose the cause of glaucoma and accurately perform clinical treatment thereby.