Detecting stable locality-aware predicates

In a large-scale locality-driven network such as in modular robotics and wireless sensor networks, knowing the state of a local area is sometimes necessary due to either interactions being local and driven by neighborhood proximity or the users being interested in the state of a certain region. We define locality-aware predicates (LAP) that aim at detecting a predicate within a specified area. We model the area of interest as the set of processes that are within a breadth-first search tree (BFST) of height k$k$ rooted at the initiator process. Although a locality-aware predicate specifies a predicate only within a local area, observing the area consistently requires considering the entire system in a consistent manner. This raises the challenge of making the complexities of the corresponding predicate detection algorithms scale-free, i.e., independent of the size of the system. Since all existing algorithms for getting a consistent view of the system require either a global snapshot of the entire system or vector clocks of the size of the system, a new solution is needed. We focus on stable LAP, which are those LAP that remain true once they become true. We propose a scale-free algorithm to detect stable LAP within a k$k$-height BFST. Our algorithm can detect both stable conjunctive LAP and stable relational LAP. In the process of designing our algorithm, we also propose the first distributed algorithm for building a BFST within an area of interest in a graph, and the first distributed algorithm for recording a consistent sub-cut within the area of interest. This paper demonstrates that LAPs are a natural fit for detecting distributed properties in large-scale distributed systems, and stable LAPs can be practically detected at low cost.     

Fuzzy-HLSTM (Hierarchical Long Short-Term Memory) for Agricultural Based Information Mining

This research proposes a machine learning approach using fuzzy logic to build an information retrieval system for the next crop rotation. In case-based reasoning systems, case representation is critical, and thus, researchers have thoroughly investigated textual, attribute-value pair, and ontological representations. As big databases result in slow case retrieval, this research suggests a fast case retrieval strategy based on an associated representation, so that, cases are interrelated in both either similar or dissimilar cases. As soon as a new case is recorded, it is compared to prior data to find a relative match. The proposed method is worked on the number of cases and retrieval accuracy between the related case representation and conventional approaches. Hierarchical Long Short-Term Memory (HLSTM) is used to evaluate the efficiency, similarity of the models, and fuzzy rules are applied to predict the environmental condition and soil quality during a particular time of the year. Based on the results, the proposed approaches allows for rapid case retrieval with high accuracy.     

A domain decomposition strategy for alignment of multiple biological sequences on multiprocessor platforms

Multiple Sequences Alignment (MSA) of biological sequences is a fundamental problem in computational biology due to its critical significance in wide ranging applications including haplotype reconstruction, sequence homology, phylogenetic analysis, and prediction of evolutionary origins. The MSA problem is considered NP-hard and known heuristics for the problem do not scale well with increasing numbers of sequences. On the other hand, with the advent of a new breed of fast sequencing techniques it is now possible to generate thousands of sequences very quickly. For rapid sequence analysis, it is therefore desirable to develop fast MSA algorithms that scale well with an increase in the dataset size. In this paper, we present a novel domain decomposition based technique to solve the MSA problem on multiprocessing platforms. The domain decomposition based technique, in addition to yielding better quality, gives enormous advantages in terms of execution time and memory requirements. The proposed strategy allows one to decrease the time complexity of any known heuristic of O(N)^x$O{\left(N\right)}^x$ complexity by a factor of O(1/p)^x$O{(1/p)}^x$, where N$N$ is the number of sequences, x$x$ depends on the underlying heuristic approach, and p$p$ is the number of processing nodes. In particular, we propose a highly scalable algorithm, Sample-Align-D, for aligning biological sequences using Muscle system as the underlying heuristic. The proposed algorithm has been implemented on a cluster of workstations using the MPI library. Experimental results for different problem sizes are analyzed in terms of quality of alignment, execution time and speed-up.     

Multiple human tracking in high-density crowds

In this paper, we introduce a fully automatic algorithm to detect and track multiple humans in high-density crowds in the presence of extreme occlusion. Typical approaches such as background modeling and body part-based pedestrian detection fail when most of the scene is in motion and most body parts of most of the pedestrians are occluded. To overcome this problem, we integrate human detection and tracking into a single framework and introduce a confirmation-by-classification method for tracking that associates detections with tracks, tracks humans through occlusions, and eliminates false positive tracks. We use a Viola and Jones AdaBoost detection cascade, a particle filter for tracking, and color histograms for appearance modeling. To further reduce false detections due to dense features and shadows, we introduce a method for estimation and utilization of a 3D head plane that reduces false positives while preserving high detection rates. The algorithm learns the head plane from observations of human heads incrementally, without any a priori extrinsic camera calibration information, and only begins to utilize the head plane once confidence in the parameter estimates is sufficiently high. In an experimental evaluation, we show that confirmation-by-classification and head plane estimation together enable the construction of an excellent pedestrian tracker for dense crowds.     

Pivotal Role of Phytohormones and Their Responsive Genes in Plant Growth and Their Signaling and Transduction Pathway under Salt Stress in Cotton

The presence of phyto-hormones in plants at relatively low concentrations plays an indispensable role in regulating crop growth and yield. Salt stress is one of the major abiotic stresses limiting cotton production. It has been reported that exogenous phyto-hormones are involved in various plant defense systems against salt stress. Recently, different studies revealed the pivotal performance of hormones in regulating cotton growth and yield. However, a comprehensive understanding of these exogenous hormones, which regulate cotton growth and yield under salt stress, is lacking. In this review, we focused on new advances in elucidating the roles of exogenous hormones (gibberellin (GA) and salicylic acid (SA)) and their signaling and transduction pathways and the cross-talk between GA and SA in regulating crop growth and development under salt stress. In this review, we not only focused on the role of phyto-hormones but also identified the roles of GA and SA responsive genes to salt stress. Our aim is to provide a comprehensive review of the performance of GA and SA and their responsive genes under salt stress, assisting in the further elucidation of the mechanism that plant hormones use to regulate growth and yield under salt stress.     

Alternative approach to compute shear amplification in high‐rise reinforced concrete core wall buildings using uncoupled modal response history analysis procedure

The seismic response of the high‐rise reinforced concrete (RC) wall structures is really complicated as several vibration modes other than the fundamental mode normally contribute significantly to the response—commonly recognized as ‘higher mode effects’. Response spectrum analysis (RSA) procedure, which can account for higher mode effects, is usually employed to compute the seismic design demand for the high‐rise structures. Recent studies show that the inelastic seismic force demands obtained from the rigorous nonlinear response history analysis procedure are much larger than the seismic force design demands obtained from the code‐based RSA procedure for the high‐rise RC wall structures. Though, the nonlinear response history analysis procedure is widely accepted for its ability to provide the most accurate estimate of nonlinear seismic responses, the obtained responses are generally so complex that it is quite difficult for engineers to grasp the overall picture of the responses and gain some insight into them and use them to understand the cause of high seismic demands. Another important issue related to the nonlinear seismic response prediction of the high‐rise RC wall structures is the realistic and accurate numerical modeling of RC walls. In this study, a simplified but reasonably accurate procedure called the uncoupled modal response history analysis procedure is used to interpret the complex nonlinear behavior of high‐rise RC wall structures. Moreover, a finite element model based on modified compression field theory is employed for accurate numerical modeling of RC walls by incorporating the axial‐flexure‐shear interaction. This study, by making use of a better computer modeling approach and an in‐depth analysis by modal decomposition, aims to resolve some of the unanswered questions regarding realistic prediction of nonlinear seismic demands of high‐rise structures.     

Structural and magnetic properties of Pr–Ni substituted Ca0.5Ba0.5Fe12O19 hexa-ferrite nanoparticles

Effect of Pr–Ni substitution on structural and magnetic properties of Ca_0.5Ba_0.5−xPr_xNi_yFe_12−yO₁₉ (x=0.00–0.10 and y=0.00–1.00) prepared by the sol–gel auto combustion method were investigated. The XRD analysis confirmed the single phase M-type hexa-ferrite structure. The lattice parameters were found to increase as Pr–Ni content increases, which is attributed to the ionic size of the implicated cations. The Pr–Ni seems to be completely soluble in the lattice. Transmission electron microscopy reveals that the grain size decreases with increase of Pr–Ni substitution. The coercivity and remanent magnetization ranges from 1511 to 1925 (Oe) and 21.4 to 26.5 (emu/g), respectively. The coercivity values of all the samples fall in the range of M-type hexa-ferrites.     

Clozapine Increases Nestin Concentration in the Adult Male Rat Hippocampus: A Preliminary Study

Patients with schizophrenia, and rodent models of the disease, both exhibit suppressed neurogenesis, with antipsychotics possibly enhancing neurogenesis in pre-clinical models. Nestin, a cytoskeletal protein, is implicated in neuronal differentiation and adult neurogenesis. We hypothesized that schizophrenia pathogenesis involves nestin downregulation; however, few studies have related nestin to schizophrenia. We assessed nestin protein concentration, prepulse inhibition (PPI), and social interaction in the MK-801 model of schizophrenia, with or without antipsychotic (clozapine) treatment. Adult male Sprague–Dawley rats were intraperitoneally administered saline or MK-801 (0.1 mg/kg) to produce a schizophrenia-like phenotype, with concomitant subcutaneous injections of vehicle or clozapine (5 mg/kg). PPI was assessed on days 1, 8, and 15, and social interaction was assessed on day 4. Hippocampus tissue samples were dissected for Western blotting of nestin concentration. MK-801 alone did not alter nestin concentration, while clozapine alone enhanced hippocampal nestin concentration; this effect was not apparent in animals with MK-801 and clozapine co-administration. MK-801 also produced schizophrenia-like PPI disruptions, some of which were reversed by clozapine. Social interaction deficits were not detected in this model. This is the first report of clozapine-induced enhancements of hippocampal nestin concentration that might be mediated by NMDA receptors. Future studies will explore the impact of neurodevelopmental nestin concentration on symptom onset and antipsychotic treatment.