The Olfactory Nervous System Of Terrestrial And Aquatic Vertebrates

Animals in their natural milieu are surrounded by odors. These odors are rich source of information, and are perceived by sophisticated olfactory systems, that have evolved over time. The sense of smell helps species to localize prey, evade predators, explore food and recognize viable mates. In humans, memoirs, thoughts, emotions, and associations are more readily reached through the sense of smell than through any other channel. This suggests that olfactory processing is imperative and may differ fundamentally from processing in other sensory modalities. The molecular age in olfaction initiated in 1991 with the significant discovery of a large, multigene family of olfactory receptors in rat by Linda Buck and Richard Axel (Buck and Axel, 1991). The first cloned olfactory receptors consisted of a diverse repertoire of G-protein coupled receptors (GPCRs) with seven-trans membrane topology, and they were sparsely expressed in the olfactory epithelium. This Nobel Prize worthy pioneering discovery, together with availability of modern techniques and numerous completely sequenced genomes opened the way to characterize the gene families of olfactory receptors through exhaustive computational data mining in different species genome as well as by in vitro biology. In this review, I will explain about the two main model organism of olfactory perceptions, zebrafish and mouse

Metal complexes and their potential therapeutic role against COVID-19: recent developments in drug designing

COVID-19 is a global pandemic caused by severe acute respiratory syndromecoronavirus 2 (SARS-CoV-2). Being associated with high mortality rates, this pandemic has forced several countries worldwide to impose complete lockdowns to limit the spread of infection. Despite the development of various vaccines, there is still an urgent need to design novel treatments backed with safety data for fighting SARS-CoV-2 and its various mutants. Currently, scientists are putting their strenuous efforts into finding the best treatment option for COVID-19. In this regard, metal complexes beingactive antiviral agents and immunity enhancers have great potential against SARSCoV-2. Herein, metal complexes’ therapeutic role and significance against treating SARS-CoV-2 or any of its target proteins are discussed

Bulk Scheduling with the DIANA Scheduler

Results from the research and development of a Data Intensive and Network Aware (DIANA) scheduling engine, to be used primarily for data intensive sciences such as physics analysis, are described. In Grid analyses, tasks can involve thousands of computing, data handling, and network resources. The central problem in the scheduling of these resources is the coordinated management of computation and data at multiple locations and not just data replication or movement. However, this can prove to be a rather costly operation and efficient sing can be a challenge if compute and data resources are mapped without considering network costs. We have implemented an adaptive algorithm within the so-called DIANA Scheduler which takes into account data location and size, network performance and computation capability in order to enable efficient global scheduling. DIANA is a performance-aware and economy-guided Meta Scheduler. It iteratively allocates each job to the site that is most likely to produce the best performance as well as optimizing the global queue for any remaining jobs. Therefore it is equally suitable whether a single job is being submitted or bulk scheduling is being performed. Results indicate that considerable performance improvements can be gained by adopting the DIANA scheduling approach.Comment: 12 pages, 11 figures. To be published in the IEEE Transactions in Nuclear Science, IEEE Press. 200

A Fault Tolerant, Dynamic and Low Latency BDII Architecture for Grids

The current BDII model relies on information gathering from agents that run on each core node of a Grid. This information is then published into a Grid wide information resource known as Top BDII. The Top level BDIIs are updated typically in cycles of a few minutes each. A new BDDI architecture is proposed and described in this paper based on the hypothesis that only a few attribute values change in each BDDI information cycle and consequently it may not be necessary to update each parameter in a cycle. It has been demonstrated that significant performance gains can be achieved by exchanging only the information about records that changed during a cycle. Our investigations have led us to implement a low latency and fault tolerant BDII system that involves only minimal data transfer and facilitates secure transactions in a Grid environment.Comment: 18 pages; 10 figures; 4 table

A deep reinforcement learning based homeostatic system for unmanned position control

Deep Reinforcement Learning (DRL) has been proven to be capable of designing an optimal control theory by minimising the error in dynamic systems. However, in many of the real-world operations, the exact behaviour of the environment is unknown. In such environments, random changes cause the system to reach different states for the same action. Hence, application of DRL for unpredictable environments is difficult as the states of the world cannot be known for non-stationary transition and reward functions. In this paper, a mechanism to encapsulate the randomness of the environment is suggested using a novel bio-inspired homeostatic approach based on a hybrid of Receptor Density Algorithm (an artificial immune system based anomaly detection application) and a Plastic Spiking Neuronal model. DRL is then introduced to run in conjunction with the above hybrid model. The system is tested on a vehicle to autonomously re-position in an unpredictable environment. Our results show that the DRL based process control raised the accuracy of the hybrid model by 32%.N/

An Architecture for Integrated Intelligence in Urban Management using Cloud Computing

With the emergence of new methodologies and technologies it has now become possible to manage large amounts of environmental sensing data and apply new integrated computing models to acquire information intelligence. This paper advocates the application of cloud capacity to support the information, communication and decision making needs of a wide variety of stakeholders in the complex business of the management of urban and regional development. The complexity lies in the interactions and impacts embodied in the concept of the urban-ecosystem at various governance levels. This highlights the need for more effective integrated environmental management systems. This paper offers a user-orientated approach based on requirements for an effective management of the urban-ecosystem and the potential contributions that can be supported by the cloud computing community. Furthermore, the commonality of the influence of the drivers of change at the urban level offers the opportunity for the cloud computing community to develop generic solutions that can serve the needs of hundreds of cities from Europe and indeed globally.Comment: 6 pages, 3 figure

Towards In-Transit Analytics for Industry 4.0

Industry 4.0, or Digital Manufacturing, is a vision of inter-connected services to facilitate innovation in the manufacturing sector. A fundamental requirement of innovation is the ability to be able to visualise manufacturing data, in order to discover new insight for increased competitive advantage. This article describes the enabling technologies that facilitate In-Transit Analytics, which is a necessary precursor for Industrial Internet of Things (IIoT) visualisation.Comment: 8 pages, 10th IEEE International Conference on Internet of Things (iThings-2017), Exeter, UK, 201

Measuring Developer Experience of a Digital Platform

Smart city and smart transportation are concepts that have emerged as an enabling solution which facilitates the grassroots social innovations to mitigate the problems generated by rapid urbanization and population growth. The digital service platform has fostered a new paradigm of transportation by involving all key players to create a novel environment. It is concerned developer are also the user of the platform as they are using the system development tools and methods for further development, that is why developer experience over the platform plays a vital role. Delightful developer experience not only improving the platform performance but also invokes to introduce new innovations. In this research we off to measure developer experience and answering the research questions “how to measure developer experience on top of the digital service platform” and “how to analyse the developer experience”. In the state of measuring developer experience, an application has been developed over the digital service platform and a measurement procedure has been introduced by modifying System Usability Scale (SUS) to more suit the context of the developer. The SUS has been borrowed from UX measurement tools as developers are the user of system, system development tools and methods as well as SUS is a widely accepted tool by the usability researchers for measuring usability. The result of the proposed method showed superior experience from the developer’s perspective to develop the application over the living lab bus platform. The result is almost same when it is compared with another method, but it is arguable as it showed small discrepancy. Furthermore, it can be said that, this research provides a straight forward way to measure developer experience on a digital service platform. The answer of the research questions provides a detail guideline of the measurement process and analysing criteria of developer experience. Moreover, it comes out with few recommendations that can be helpful for the developers of the platform to improve the platform in future, so that it could ensure the delightful experience for the developers

The teleost taar family of olfactory receptors: From rapidly evolving receptor genes to ligand-induced behavior

Trace amine-associated receptors (TAARs) have recently been shown to function as olfactory receptors in mammals. In this current study, the taar gene family has been delineated in jawless, cartilaginous, and bony fish (zero, 2, and >100 genes, respectively). I conclude that the taar genes are evolutionary much younger than the related OR and ORA/V1R olfactory receptor families, which are present already in lamprey, a jawless vertebrate. The 2 cartilaginous fish genes appear to be ancestral for 2 taar classes, each with mammalian and bony fish (teleost) representatives. Unexpectedly, a whole new clade, class III, of taar genes originated even later, within the teleost lineage. Taar genes from all 3 classes are expressed in subsets of zebrafish olfactory receptor neurons, supporting their function as olfactory receptors. The highly conserved TAAR1 (shark,mammalian, and teleost orthologs) is not expressed in the olfactory epithelium and may constitute the sole remnant of a primordial, non olfactory function of this family. Class III comprises three-fourths of all teleost taar genes and is characterized by the complete loss of the aminergic ligand-binding motif, stringently conserved in all 25 genes of the other 2 classes. Two independent intron gains in class III taar genes represent extraordinary evolutionary dynamics, considering the virtual absence of intron gains during vertebrate evolution. The dN/dS analysis suggests both minimal global negative selection and an unparalleled degree of local positive selection as another hallmark of class III genes. The accelerated evolution of class III teleost taar genes conceivably might mark the birth of another olfactory receptor gene family. Ligands have only been identified for a handful of olfactory receptors of mammals and insects, while only a single teleost olfactory receptor have been deorphanized, a member of the OlfC family, OlfCa. Zebrafish TAAR olfactory receptors of classI are good candidates for having amines as possible ligands, due to the presence of the aminergic ligand binding motifs. This study identifies diamines as specific ligands for a taar receptor, DrTAAR13c. These diamines activate a sparse subset of olfactory sensory neurons, as indicated by c-Fos expression in olfactory epithelium. Diamines, putrescine and cadaverine, are foul-smelling aliphatic polycations that occur naturally as a result of bacterial decarboxylation of amino acids lysine and arginine, respectively. The 15 concentration of diamines in their environment is correlated to the degree of putrefication. In the behavioral assay, zebrafish exposed to even low concentration of diamines show dramatic, quantifiable aversion, while it shows attraction towards food stimulus and no response for water. The ligand spectrum of TAAR13c closely parallels the behavioral effectiveness of these diamines. This data is consistent with the existence of a defined neuronal microcircuit that elicits a characteristic behavior upon activation of a single olfactory receptor, a novum in the vertebrate sense of smell