Conceptual Model for Smart Cities: Irrigation and Highway Lamps using IoT

Keeping in mind the need to preserve energy as well as utilize the available at its best the need was felt to develop a module that would be able to sort out the problem where resources such as water and electricity were wasted, in urban as well as rural area. Resource (electricity) was wasted as beside the point operation of Highway & High Mast Lamp; while wastage of water followed by improper trends and methodologies imparted for watering of city park, road side plantation and highway plantation. Thus as per Energy survey statistics of a City (Lucknow, India) it was found that major portion of resources (water and electricity) were being wasted due to negligent activities of officials who were in charge of resource management. So to facilitate energy saving trends and to completely modernize it to autonomous system, module below is proposed which incorporates modern technological peripheral and has its base ingrained in IoT (Internet of Things) which when put into consideration would result in large scale resource and energy saving.This developed module incorporates the peripherals such as Arduino, Texas Instruments ultra low power kits etc. in accordance with software technology including Lab View which help to monitor as well as control the various operation from the base station, located far away from the site. Lab View Interface interacts with all the module located at various city parks, subways and highway lighting modules. Later below in several section a detailed pattern and application frame has been put up

Incremental Hierarchical Clustering driven Automatic Annotations for Unifying IoT Streaming Data

In the Internet of Things (IoT), Cyber-Physical Systems (CPS), and sensor technologies huge and variety of streaming sensor data is generated. The unification of streaming sensor data is a challenging problem. Moreover, the huge amount of raw data has implied the insufficiency of manual and semi-automatic annotation and leads to an increase of the research of automatic semantic annotation. However, many of the existing semantic annotation mechanisms require many joint conditions that could generate redundant processing of transitional results for annotating the sensor data using SPARQL queries. In this paper, we present an Incremental Clustering Driven Automatic Annotation for IoT Streaming Data (IHC-AA-IoTSD) using SPARQL to improve the annotation efficiency. The processes and corresponding algorithms of the incremental hierarchical clustering driven automatic annotation mechanism are presented in detail, including data classification, incremental hierarchical clustering, querying the extracted data, semantic data annotation, and semantic data integration. The IHCAA-IoTSD has been implemented and experimented on three healthcare datasets and compared with leading approaches namely- Agent-based Text Labelling and Automatic Selection (ATLAS), Fuzzy-based Automatic Semantic Annotation Method (FBASAM), and an Ontology-based Semantic Annotation Approach (OBSAA), yielding encouraging results with Accuracy of 86.67%, Precision of 87.36%, Recall of 85.48%, and F-score of 85.92% at 100k triple data

Beta-frequency electrophysiological bursts: BOLD correlates and relationships with psychotic illness

AIMS: To identify the BOLD (blood oxygenation level dependent) correlates of bursts of beta frequency band electrophysiological activity, and to compare BOLD responses between healthy controls and patients with psychotic illness. The post movement beta rebound (PMBR) is a transient increase in power in the beta frequency band (13-30 Hz), recorded with methods such as electroencephalography (EEG), following the completion of a movement. PMBR size is reduced in patients with schizophrenia and inversely correlated with severity of illness. PMBR size is inversely correlated with measures of schizotypy in non-clinical groups. Therefore, beta-band activity may reflect a fundamental neural process whose disruption plays an important role in the pathophysiology of schizophrenia. Recent work has found that changes in beta power reflect changes in the probability-of-occurrence of transient bursts of beta-frequency activity. Understanding the generators of beta bursts could help unravel the pathophysiology of psychotic illness and thus identify novel treatment targets. METHOD: EEG data were recorded simultaneously with BOLD data measured with 3T functional magnetic resonance imaging (fMRI), whilst participants performed an n-back working memory task. We included seventy-eight participants – 32 patients with schizophrenia, 16 with bipolar disorder and 30 healthy controls. Beta bursts were identified in the EEG data using a thresholding method and burst timings were used as markers in an event-related fMRI design convolved with a conventional haemodynamic response function. A region of interest analysis compared beta-event-related BOLD activity between patients and controls. RESULT: Beta bursts phasically activated brain regions implicated in coding task-relevant content (specifically, regions involved in the phonological representation of letter stimuli, as well as areas representing motor responses). Further, bursts were associated with suppression of tonically-active regions. In the EEG, PMBR was greater in controls than patients, and, in patients, PMBR size was positively correlated with Global Assessment of Functioning scores, and negatively correlated with persisting symptoms of disorganisation and performance on a digit symbol substition test. Despite this, patients showed greater, more extensive, burst-related BOLD activation than controls. CONCLUSION: Our findings are consistent with a recent model in which beta bursts serve to reactivate latently-maintained, task-relevant, sensorimotor information. The increased BOLD response associated with bursts in patients, despite reduced PMBR, could reflect inefficiency of burst-mediated cortical synchrony, or it may suggest that the sensorimotor information reactivated by beta bursts is less precisely specified in psychosis. We propose that dysfunction of the mechanisms by which beta bursts reactivate task-relevant content can manifest as disorganisation and working memory deficits, and may contribute to persisting symptoms and impairment in psychosis

Time lagged information theoretic approaches to the reverse engineering of gene regulatory networks

Background: A number of models and algorithms have been proposed in the past for gene regulatory network (GRN) inference; however, none of them address the effects of the size of time-series microarray expression data in terms of the number of time-points. In this paper, we study this problem by analyzing the behaviour of three algorithms based on information theory and dynamic Bayesian network (DBN) models. These algorithms were implemented on different sizes of data generated by synthetic networks. Experiments show that the inference accuracy of these algorithms reaches a saturation point after a specific data size brought about by a saturation in the pair-wise mutual information (MI) metric; hence there is a theoretical limit on the inference accuracy of information theory based schemes that depends on the number of time points of micro-array data used to infer GRNs. This illustrates the fact that MI might not be the best metric to use for GRN inference algorithms. To circumvent the limitations of the MI metric, we introduce a new method of computing time lags between any pair of genes and present the pair-wise time lagged Mutual Information (TLMI) and time lagged Conditional Mutual Information (TLCMI) metrics. Next we use these new metrics to propose novel GRN inference schemes which provides higher inference accuracy based on the precision and recall parameters. Results: It was observed that beyond a certain number of time-points (i.e., a specific size) of micro-array data, the performance of the algorithms measured in terms of the recall-to-precision ratio saturated due to the saturation in the calculated pair-wise MI metric with increasing data size. The proposed algorithms were compared to existing approaches on four different biological networks. The resulting networks were evaluated based on the benchmark precision and recall metrics and the results favour our approach. Conclusions: To alleviate the effects of data size on information theory based GRN inference algorithms, novel time lag based information theoretic approaches to infer gene regulatory networks have been proposed. The results show that the time lags of regulatory effects between any pair of genes play an important role in GRN inference schemes

Regional Brain Correlates of Beta Bursts in Health and Psychosis: A Concurrent Electroencephalography and Functional Magnetic Resonance Imaging Study

Background: There is emerging evidence for abnormal beta oscillations in psychosis. Beta-oscillations are likely to play a key role in the coordination of sensorimotor information, crucial to healthy mental function. Growing evidence suggests that beta oscillations typically manifest as transient “beta-bursts” that increase in probability following a motor response, observable as Post-Movement Beta Rebound (PMBR). Evidence indicates that PMBR is attenuated in psychosis, with greater attenuation associated with greater symptom severity and impairment. Delineating the functional role of beta-bursts may therefore be key to understanding the mechanisms underlying persistent psychotic illness.Methods: We used concurrent EEG and fMRI to identify BOLD correlates of beta-bursts during the N-back working memory task and intervening rest periods in healthy participants (N = 30) and patients with psychosis (N = 48). Results: During both task-blocks and intervening rest periods, beta-bursts phasically activated regions implicated in task-relevant content, while suppressing currently tonically active regions. Patients showed attenuated PMBR that was associated with persisting Disorganisation symptoms, as well as impairments in cognition and role function. Patients also showed greater task-related reductions in overall beta-burst rate, and greater, more extensive, beta-burst-related BOLD activation.Conclusions: Our evidence supports a model in which beta-bursts reactivate latently maintained sensorimotor information and are dysregulated and inefficient in psychosis. We propose that abnormalities in the mechanisms by which beta-bursts coordinate reactivation of contextually appropriate content can manifest as Disorganisation, working memory deficits and inaccurate forward models, and may underlie a “core deficit” associated with persisting symptoms and impairment

A comparison of in vitro nucleosome positioning mapped with chicken, frog and a variety of yeast core histones

AbstractUsing high-throughput sequencing, we have mapped sequence-directed nucleosome positioning in vitro on four plasmid DNAs containing DNA fragments derived from the genomes of sheep, drosophila, human and yeast. Chromatins were prepared by reconstitution using chicken, frog and yeast core histones. We also assembled yeast chromatin in which histone H3 was replaced by the centromere-specific histone variant, Cse4. The positions occupied by recombinant frog and native chicken histones were found to be very similar. In contrast, nucleosomes containing the canonical yeast octamer or, in particular, the Cse4 octamer were assembled at distinct populations of locations, a property that was more apparent on particular genomic DNA fragments. The factors that may contribute to this variation in nucleosome positioning and the implications of the behavior are discussed

The chromatin remodelling enzymes SNF2H and SNF2L position nucleosomes adjacent to CTCF and other transcription

Within the genomes of metazoans, nucleosomes are highly organised adjacent to the binding sites for a subset of transcription factors. Here we have sought to investigate which chromatin remodelling enzymes are responsible for this. We find that the ATP-dependent chromatin remodelling enzyme SNF2H plays a major role organising arrays of nucleosomes adjacent to the binding sites for the architectural transcription factor CTCF sites and acts to promote CTCF binding. At many other factor binding sites SNF2H and the related enzyme SNF2L contribute to nucleosome organisation. The action of SNF2H at CTCF sites is functionally important as depletion of CTCF or SNF2H affects transcription of a common group of genes. This suggests that chromatin remodelling ATPase's most closely related to the Drosophila ISWI protein contribute to the function of many human gene regulatory elements

Co-Administration of IL-1+IL-6+TNF-α with Mycobacterium tuberculosis Infected Macrophages Vaccine Induces Better Protective T Cell Memory than BCG

BCG has been administered globally for more than 75 years, yet tuberculosis (TB) continues to kill more than 2 million people annually. Further, BCG protects childhood TB but is quite inefficient in adults. This indicates that BCG fails to induce long-term protection. Hence there is a need to explore alternative vaccination strategies that can stimulate enduring T cell memory response. Dendritic cell based vaccination has attained extensive popularity following their success in various malignancies. In our previous study, we have established a novel and unique vaccination strategy against Mycobacterium tuberculosis (M. tb) and Salmonella typhimurium by utilizing infected macrophages (IM). In short-term experiments (30 days), substantial degree of protection was observed. However, remarkable difference was not observed in long-term studies (240 days) due to failure of the vaccine to generate long-lasting memory T cells. Hence, in the present study we employed T cell memory augmenting cytokines IL-1+IL-6+TNF-α and IL-7+IL-15 for the induction of the enhancement of long-term protection by the vaccine. We co-administered the M. tb infected macrophages vaccine with IL-1+IL-6+TNF-α (IM-1.6.α) and IL-7+IL-15 (IM-7.15). The mice were then rested for a reasonably large period (240 days) to study the bona fide T cell memory response before exposing them to aerosolized M. tb. IM-1.6.α but not IM-7.15 significantly improved memory T cell response against M. tb, as evidenced by recall responses of memory T cells, expansion of both central as well as effector memory CD4 and CD8 T cell pools, elicitation of mainly Th1 memory response, reduction in the mycobacterial load and alleviated lung pathology. Importantly, the protection induced by IM-1.6.α was significantly better than BCG. Thus, this study demonstrates that not only antigen-pulsed DCs can be successfully employed as vaccines against cancer and infectious diseases but also macrophages infected with M. tb can be utilized with great efficacy especially in protection against TB