Mental imagery classification using one-dimensional convolutional neural network for target selection in single-channel BCI-controlled mobile robot

Neural Computing and Applications - This paper introduces the use of the one-dimensional convolutional neural network (1D-CNN) for end-to-end EEG decoding with application towards a BCI system with...     

Hyperspectral imaging-based unsupervised adulterated red chili content transformation for classification: Identification of red chili adulterants

Neural Computing and Applications - Preserving red-chili quality is of utmost importance in which the authorities demand quality techniques to detect, classify, and prevent it from impurities. For...     

Deep learning controller for nonlinear system based on Lyapunov stability criterion

Neural Computing and Applications - For the current paper, the technique of feed-forward neural network deep learning controller (FFNNDLC) for the nonlinear systems is proposed. The FFNNDLC...     

Lung nodules detection using semantic segmentation and classification with optimal features

Neural Computing and Applications - Lung cancer is a deadly disease if not diagnosed in its early stages. However, early detection of lung cancer is a challenging task due to the shape and size of...     

Full-state neural network observer-based hybrid quantum diagonal recurrent neural network adaptive tracking control

Neural Computing and Applications - This study introduces a neural network (NN) adaptive tracking controller-based reinforcement learning (RL) scheme for unknown nonlinear systems. First, an...     

An intrinsic semantic framework for recognizing image objects

The paper proposes a new approach to find semantic meanings in visual object class structure, in line with the Gestalt laws of proximity. Micro level semantic structures are formed by line segments (arcs also approximated into line segments based on pixel deviation threshold) which are in close proximity. These structures are hierarchically combined till a semantic label can be assigned. The algorithm extracts semantic groups, their inter-relations and represents these using a graph. Invariant geometrical properties of the groups and relations are used as vertex and edge labels. A graph model captures the inter class variability by analyzing the repetitiveness of structures and relations and uses it as a weighting factor for classification. The algorithm has been tested on a standard benchmark database and compared with existing approaches.     

Autonomous mapping of HL7 RIM and relational database schema

Healthcare systems need to share information within and across the boundaries in order to provide better care to the patients. For this purpose, they take advantage of the full potential of current state of the art in healthcare standards providing interoperable solutions. HL7 V3 specification is an international message exchange and interoperability standard. HL7 V3 messages exchanged between healthcare applications are ultimately recorded into local healthcare databases, mostly in relational databases. In order to bring these relational databases in compliance with HL7, mappings between HL7 RIM (Reference Information Model) and relational database schema are required. Currently, RIM and database mapping is largely performed manually, therefore it is tedious, time consuming, error prone and expensive process. It is a challenging task to determine all correspondences between RIM and schema automatically because of extreme heterogeneity issues in healthcare databases. To reduce the amount of manual efforts as much as possible, autonomous mapping approaches are required. This paper proposes a technique that addresses the aforementioned mapping issue and aligns healthcare databases to HL7 V3 RIM specifications. Furthermore, the proposed technique has been implemented as a working application and tested on real world healthcare systems. The application loads the target healthcare schema and then identifies the most appropriate match for tables and the associated fields in the schema by using domain knowledge and the matching rules defined in the Mapping Knowledge Repository. These rules are designed to handle the complexity of semantics found in healthcare databases. The GUI allows users to view and edit/re-map the correspondences. Once all the mappings are defined, the application generates Mapping Specification, which contains all the mapping information i.e. database tables and fields with associated RIM classes and attributes. In order to enable the transactions, the application is facilitated with the autonomous code generation from the Mapping Specification. The Code Generator component focuses primarily on generating custom classes and hibernate mapping files against the runtime system to retrieve and parse the data from the data source—thus allows bi-directional HL7 to database communication, with minimum programming required. Our experimental results show 35–65% accuracy on real laboratory systems, thus demonstrating the promise of the approach. The proposed scheme is an effective step in bringing the clinical databases in compliance with RIM, providing ease and flexibility.     

An Insight View on Synthetic Protocol,Surface Activity,and Biological Aspects of Novel Biocompatible Quaternary Ammonium Cationic Gemini Surfactants

In this study, we prepared a novel series of diester-functionalized cationic gemini surfactants (C_m-E2O2-C_m) containing ethylene oxide as a spacer with varying alkyl chain lengths and characterized by ¹H NMR, FT-IR, elemental analysis, and ESI-MS. The physicochemical properties of the geminis were explored by tensiometry, fluorescence, dye solubilization, and Krafft point. These geminis acquire superior surface activity than the conventional surfactants. Fluorescence spectroscopy analysis affirmed that the micropolarity and aggregation number of micelles diminished with increase in the alkyl chain length. These geminis represent a new group of amphiphiles of considerably high biodegradability, better cleavability, and low toxicity as assessed by BOD test, FT-IR analysis, and HC₅₀ analysis, respectively. They also showed significant level of antimicrobial activity toward some specified bacterial strains of Gram-positive and Gram-negative by using agar well diffusion method. Furthermore, the thermogravimetric analysis provided information regarding thermal stabilities of the newly synthesized gemini surfactants.     

Antioxidant vs. Prooxidant Properties of the Flavonoid,Kaempferol, in the Presence of Cu(II) Ions: A ROS-Scavenging Activity,Fenton Reaction and DNA Damage Study

Kaempferol is a flavonoid that occurs in tea and in many vegetables and fruits, including broccoli, cabbage, beans, grapes, apples, and strawberries. The efficacy of Kaempferol has been demonstrated in the treatment of breast, esophageal, cervical, ovarian, and liver cancers and leukemia, which very likely arises from its prooxidant properties and the activation of pro-apoptotic pathways. Indeed, this matter has already been the focus of a number of published studies and reviews. The aim of the present study was to elucidate the antioxidant vs. prooxidant properties of flavonoids in the presence of the redox-active metal, copper (II) ion, by means of the Fenton reaction. The specific motivation of this work is that, since an increased level of Cu(II) ions is known to be associated with many disease states such as neurological conditions (Alzheimer’s disease) and cancer, any interaction between these ions and flavonoids might affect the outcome of therapeutic uses of the latter. The structure of the Cu-kaempferol complex in DMSO was investigated by means of low temperature EPR spectroscopy, which confirmed the existence of at least two distinct coordination environments around the copper (II) ion. UV vis-spectra of kaempferol and its Cu(II) complex in DMSO revealed an interaction between the 5-OH (A ring) group and the 4-CO (C ring) group of kaempferol with Cu(II) ions. An ABTS assay confirmed that kaempferol acted as an effective radical scavenger, and that this effect was further enhanced in the form of the Cu(II)-kaempferol complex. Quantitative EPR spin trapping experiments, using DMPO as the spin trap, confirmed suppression of the formation of a mixture of hydroxyl, superoxide, and methyl radicals, in a Fenton reaction system, upon coordination of kaempferol to the redox-active Cu(II) ions, by 80% with respect to the free Cu(II) ions. A viscometric study revealed a better DNA-intercalating ability of the Cu-kaempferol complex than for free kaempferol, essential for conferring anticancer activity of these substances. The results of the viscometric measurements were compared with those from a DNA damage study of Cu-kaempferol complexes in a Fenton reaction system, using gel electrophoresis. At low concentrations of kaempferol (Cu–kaempferol ratios of 1:1 and 1:2), a very weak protective effect on DNA was noted, whereas when kaempferol was present in excess, a significant DNA-protective effect was found. This can be explained if the weakly intercalated kaempferol molecules present at the surface of DNA provide protection against attack by ROS that originate from the Fenton reaction involving intercalated Cu(II)-kaempferol complexes. Following the application of ROS scavengers, L-histidine, DMSO, and SOD, gel electrophoresis confirmed the formation of singlet oxygen, hydroxyl radicals, and superoxide radical anions, respectively. We propose that the prooxidant properties of Cu-kaempferol complexes may provide anticancer activity of these substances. When present in excess, kaempferol displays antioxidant properties under Cu-Fenton conditions. This suggests that kaempferol might prove a suitable candidate for the prevention or treatment of oxidative stress related medical conditions that involve a disturbed metabolism of redox metals such as copper, for example, Menkes disease, and neurological disorders, including Alzheimer’s disease. For the potential use of kaempferol in clinical practice, it will be necessary to optimize the dose size and critical age of the patient so that this flavonoid may be beneficial as a preventive drug against cancer and neurological disorders.     

Current Understandings on Magnesium Deficiency and Future Outlooks for Sustainable Agriculture

The productivity of agricultural produce is fairly dependent on the availability of nutrients and efficient use. Magnesium (Mg²⁺) is an essential macronutrient of living cells and is the second most prevalent free divalent cation in plants. Mg²⁺ plays a role in several physiological processes that support plant growth and development. However, it has been largely forgotten in fertilization management strategies to increase crop production, which leads to severe reductions in plant growth and yield. In this review, we discuss how the Mg²⁺ shortage induces several responses in plants at different levels: morphological, physiological, biochemical and molecular. Additionally, the Mg²⁺ uptake and transport mechanisms in different cellular organelles and the role of Mg²⁺ transporters in regulating Mg²⁺ homeostasis are also discussed. Overall, in this review, we critically summarize the available information about the responses of Mg deficiency on plant growth and development, which would facilitate plant scientists to create Mg²⁺-deficiency-resilient crops through agronomic and genetic biofortification.