MuLSi-Co: Multilayer Sinks and Cooperation-Based Data Routing Techniques for Underwater Acoustic Wireless Sensor Networks (UA-WSNs)

Designing an efficient, reliable, and stable algorithm for underwater acoustic wireless sensor networks (UA-WSNs) needs immense attention. It is due to their notable and distinctive challenges. To address the difficulties and challenges, the article introduces two algorithms: the multilayer sink (MuLSi) algorithm and its reliable version MuLSi-Co using the cooperation technique. The first algorithm proposes a multilayered network structure instead of a solid single structure and sinks placement at the optimal position, which reduces multiple hops communication. Moreover, the best forwarder selection amongst the nodes based on nodes’ closeness to the sink is a good choice. As a result, it makes the network perform better. Unlike the traditional algorithms, the proposed scheme does not need location information about nodes. However, the MuLSi algorithm does not fulfill the requirement of reliable operation due to a single link. Therefore, the MuLSi-Co algorithm utilizes nodes’collaborative behavior for reliable information. In cooperation, the receiver has multiple copies of the same data. Then, it combines these packets for the purpose of correct data reception. The data forwarding by the relay without any latency eliminates the synchronization problem. Moreover, the overhearing of the data gets rid of duplicate transmissions. The proposed schemes are superior in energy cost and reliable exchanging of data and have more alive and less dead nodes.

Multi-Source and Multi-Representation Adaptation for Cross-Domain Electroencephalography Emotion Recognition

Due to the non-invasiveness and high precision of electroencephalography (EEG), the combination of EEG and artificial intelligence (AI) is often used for emotion recognition. However, the internal differences in EEG data have become an obstacle to classification accuracy. To solve this problem, considering labeled data from similar nature but different domains, domain adaptation usually provides an attractive option. Most of the existing researches aggregate the EEG data from different subjects and sessions as a source domain, which ignores the assumption that the source has a certain marginal distribution. Moreover, existing methods often only align the representation distributions extracted from a single structure, and may only contain partial information. Therefore, we propose the multi-source and multi-representation adaptation (MSMRA) for cross-domain EEG emotion recognition, which divides the EEG data from different subjects and sessions into multiple domains and aligns the distribution of multiple representations extracted from a hybrid structure. Two datasets, i.e., SEED and SEED IV, are used to validate the proposed method in cross-session and cross-subject transfer scenarios, experimental results demonstrate the superior performance of our model to state-of-the-art models in most settings.

A novel intramandibular joint facilitates feeding versatility in the sixbar distichodus

The intramandibular joint (IMJ) is a secondary point of movement between the two major bones of the lower jaw. It has independently evolved in several groups of teleost fishes, each time representing a departure from related species in which the mandible functions as a single structure rotating only at the quadratomandibular joint (QMJ). In this study, we examine kinematic consequences of the IMJ novelty in a freshwater characiform fish, the herbivorous Distichodus sexfasciatus. We combine traditional kinematic approaches with trajectory-based analysis of motion shapes to compare patterns of prey capture movements during substrate biting, the fish's native feeding mode, and suction of prey from the water column. We find that the IMJ enables complex jaw motions and contributes to feeding versatility by allowing the fish to modulate its kinematics in response to different prey and to various scenarios of jaw-substrate interaction. Implications of the IMJ include context-dependent movements of lower versus upper jaws, enhanced lower jaw protrusion, and the ability to maintain contact between the teeth and substrate throughout the jaw closing or biting phase of the motion. The IMJ in D. sexfasciatus appears to be an adaptation for removing attached benthic prey, consistent with its function in other groups that have evolved the joint. This study builds on our understanding of the role of the IMJ during prey capture and provides insights into broader implications of the innovative trait.

On the Question of the Continuity of Saite Traditions in Dynasty 30 (Cambridge, Fitzwilliam Museum E.5.1909; Brooklyn, Brooklyn Museum 56.152)

When W.M. Flinders Petrie excavated the Palace of Apries he uncovered a limestone block with inscriptions on both sides. This block was published in 1909 and is now kept in the Fitzwilliam Museum in Cambridge. Bernard Bothmer first compared the Cambridge block to another one kept in the Brooklyn Museum. He emphasized that they correspond closely and that the representations differ only minutely. After Bothmer’s publication, both artifacts were considered as originally parts of a single structure. In this contribution the function of the monument of which this block was originally a part will be investigated. The proposed interpretation gives rise to a new reading of religious representations of the ancient Egyptians. It is not about overcoming the barriers of the underworld, but about the practical use of spirits. The texts tell us about the Egyptian belief in affiliating oneself with the spirit of an important person for using it for personal purposes.

Multi-band Antenna with CSRR Loaded Ground Plane and Stubs Incorporated Patch for WiMAX/WLAN Applications

This paper proposes a novel compact, single structure, multi-band antenna along with tested results for wireless local area networks (WLAN) and Worldwide Interoperability for Microwave Access (WiMAX) applications. In this work, modified complementary split-ring resonators (CSRR) were incorporated in the ground layer of the patch to achieve permeable bands to accommodate multi-resonance frequencies in a single device. The proposed antenna design supported the upgraded performance and led to desirable size reduction. Open stubs were incorporated at the edges of the triangle batch to get the improved reflection coefficient responses. It resulted in specific band spectra of 2.4 / 3.4 / 5.1 / 5.8GHz for WLAN/WiMAX applications. For constructive antenna design, CST microwave studio simulation software was utilized. S11 parameter was observed as -24dB at 2.4GHZ, -32dB at 3.4GHz. -15dB at 5.1GHz and -22dB at 5.8GHz bands. Field patterns of each band were observed. The parametric study of the arrangement and positioning of the CSRR unit cell was examined. Excellent consistency between the experimental and simulated results revealed the capability of the projected structure to perform with improved gain.

3D Structure From 2D Microscopy Images Using Deep Learning

Understanding the structure of a protein complex is crucial in determining its function. However, retrieving accurate 3D structures from microscopy images is highly challenging, particularly as many imaging modalities are two-dimensional. Recent advances in Artificial Intelligence have been applied to this problem, primarily using voxel based approaches to analyse sets of electron microscopy images. Here we present a deep learning solution for reconstructing the protein complexes from a number of 2D single molecule localization microscopy images, with the solution being completely unconstrained. Our convolutional neural network coupled with a differentiable renderer predicts pose and derives a single structure. After training, the network is discarded, with the output of this method being a structural model which fits the data-set. We demonstrate the performance of our system on two protein complexes: CEP152 (which comprises part of the proximal toroid of the centriole) and centrioles.

Archaic and innovative phenomena in the case paradigms of the Erzya dialects in the Volga region and the Southern Urals

Introduction. The modern differentiation of the Erzya dialects in the Volga region and the Southern Urals is the result of a long historical development. The migration of the Mordovians from their former places of residence contributed to their formation. The fact that in these regions the Erzya lived isolated from the rest of the Mordovians and contacted directly with peoples having different patterns of language contributed to preserving archaic phenomena of the base language and appearing innovative components in the structure of the dialects under study. The purpose of the work is to identify and describe archaic phenomena and innovations in the case paradigms of the study area. Materials and Methods. The article is based on the field materials collected by the authors during linguistic expeditions in the places of concentration of the Erzya in the territory of the Volga region and the Southern Urals. The dialectal material was collected based on the questionnaire, reflecting the lexical, phonetic and morphological variations of linguistic phenomena. The descriptive and comparative historical methods were used to analyze language material. Results and Discussion. The study of the linguistic material of the Volga region and the Southern Urals showed the differences in the case paradigms of the noun from the corresponding paradigms of the Erzya codified languages and other Mordovian dialects. In analysis showed that in the paradigms of the definite declension singular, there are different sets of cases and there is no single structure of word forms. Some paradigms are archaic, consistent, and logical. In the composition of others, new formations have developed, homonymous case suffixes and postpositional constructions have appeared. Conclusion. The main dialect types of the Erzya languages were developed before the migration processes to the eastern territories of the modern residence of the Erzya. The isolated development of the dialects of the Volga region and the Southern Urals made it possible both to preserve archaic phenomena in the paradigms of the definite declension and to develop new formations uncharacteristic for them.

LPbyCD: a new scalable and interpretable approach for Link Prediction via Community Detection in bipartite networks

Many aspects from real life with bi-relational structure can be modeled as bipartite networks. This modeling allows the use of some standard solutions for prediction and/or recommendation of new relations between objects in such networks. In this work, we combine an existing bipartite local models method with approaches for link prediction from communities to address the link prediction problem in this type of networks. The motivation of this work stems from the importance of an application task, drug–target interaction prediction. Searching valid drug candidates for a given biological target is an essential part of modern drug development. We model the problem as link prediction in a bipartite multi-layer network, which helps to aggregate different sources of information into one single structure and as a result improves the quality of link prediction. We adapt existing community measures for link prediction to the case of bipartite multi-layer networks, propose alternative ways for exploiting communities, and show experimentally that our approach is competitive with the state-of-the-art. We also demonstrate the scalability of our approach and assess interpretability. Additional evaluations on data of a different origin than drug–target interactions demonstrate the genericness of the proposed approach.