Simplest Cubic Fields

Let $Q(\alpha)$ be the simplest cubic field, it is known that $Q(\alpha)$ can be generated by adjoining a root of the irreducible equation $x^{3}-kx^{2}+(k-3)x+1=0$, where $k$ belongs to $Q$. In this paper we have established a relationship between $\alpha$, $\alpha'$ and $k,k'$ where $\alpha$ is a root of the equation $x^{3}-kx^{2}+(k-3)x+1=0$ and $\alpha'$ is a root of the same equation with $k$ replaced by $k'$ and $Q(\alpha)=Q(\alpha')$

Analysis of Brain Imaging Data for the Detection of Early Age Autism Spectrum Disorder Using Transfer Learning Approaches for Internet of Things

In recent years, advanced magnetic resonance imaging (MRI) methods including functional magnetic resonance imaging (fMRI) and structural magnetic resonance imaging (sMRI) have indicated an increase in the prevalence of neuropsychiatric disorders such as autism spectrum disorder (ASD), effects one out of six children worldwide. Data driven techniques along with medical image analysis techniques, such as computer-assisted diagnosis (CAD), benefiting from deep learning. With the use of artificial intelligence (AI) and IoT-based intelligent approaches, it would be convenient to support autistic children to adopt the new atmospheres. In this paper, we classify and represent learning tasks of the most powerful deep learning network such as convolution neural network (CNN) and transfer learning algorithm on a combination of data from autism brain imaging data exchange (ABIDE I and ABIDE II) datasets. Due to their four-dimensional nature (three spatial dimensions and one temporal dimension), the resting state-fMRI (rs-fMRI) data can be used to develop diagnostic biomarkers for brain dysfunction. ABIDE is a collaboration of global scientists, where ABIDE-I and ABIDE-II consists of 1112 rs-fMRI datasets from 573 typical control (TC) and 539 autism individuals, and 1114 rs-fMRI from 521 autism and 593 typical control individuals respectively, which were collected from 17 different sites. Our proposed optimized version of CNN achieved 81.56% accuracy. This outperforms prior conventional approaches presented only on the ABIDE I datasets

Q-LEACH: A New Routing Protocol for WSNs

Wireless Sensor Networks (WSNs) with their dynamic applications gained a tremendous attention of researchers. Constant monitoring of critical situations attracted researchers to utilize WSNs at vast platforms. The main focus in WSNs is to enhance network life-time as much as one could, for efficient and optimal utilization of resources. Different approaches based upon clustering are proposed for optimum functionality. Network life-time is always related with energy of sensor nodes deployed at remote areas for constant and fault tolerant monitoring. In this work, we propose Quadrature-LEACH (Q-LEACH) for homogenous networks which enhances stability period, network life-time and throughput quiet significantly

Context-Aware Personalized Activity Modeling in Concurrent Environment

Activity recognition, having endemic impact on smart homes, faces one of the biggest challenges in learning a personalized activity model completely by using a generic model especially for parallel and interleaved activities. Furthermore, inhabitant’s mistaken object interaction may entail in another spurious activity at smart homes. Identifying and removing such spurious activities is another challenging task. Knowledge driven techniques used for recognizing activity models are static in nature, lack contextual representation and may not comprehend spurious actions for parallel/interleaved activities. In this paper, a novel approach for completing the personalized model specific to each inhabitant at smart homes using generic model (incomplete) is presented that can recognize the sequential, parallel, and interleaved activities dynamically while removing the spurious activities semantically. A comprehensive set of experiments and results based upon number of correct (true positivity) or incorrect (false negativity) recognition of activities assert effectiveness of presented approach within a smart hom

Exogenous application of polyamines improves germination and early seedling growth of hot pepper

Polyamines are low molecular weight organic compounds involved in diverse range of biological processes in all living organisms. Seed priming is a technique that improves seed performance by rapid and uniform germination with normal and vigorous seedlings. A laboratory study was performed to explore the benefits of seed priming with polyamines on seed germination and seedling growth of hot pepper (Capsicum annuum L.) Hot pepper seeds were primed in aerated solution of putrescine, spermine, or spermidine (25, 50, 75, and 100 mM) for 48 h at 25 ± 2 °C. Significant results (P < 0.05) were observed for different attributes of seed germination and early seedling growth. Polyamines priming resulted in earlier and synchronized germination via improving final germination percentage, time to 50% germination, mean germination time, germination energy, germination speed and germination index compared with control. Improvement in shoot and root length, seedling fresh and dry weight, seedling growth rate and seedling vigor index was clearly indicative of positive effects of seed priming with polyamines. Out of all polyamines, putrescine proved to be better at low concentrations (i.e. 25 and 50 mM) for most of the traits related to seed emergence and seedling growth

Modeling and simulation of VMD desalination process by ANN

YesIn this work, an artificial neural network (ANN) model based on the experimental data was developed to study the performance of vacuum membrane distillation (VMD) desalination process under different operating parameters such as the feed inlet temperature, the vacuum pressure, the feed flow rate and the feed salt concentration. The proposed model was found to be capable of predicting accurately the unseen data of the VMD desalination process. The correlation coefficient of the overall agreement between the ANN predictions and experimental data was found to be more than 0.994. The calculation value of the coefficient of variation (CV) was 0.02622, and there was coincident overlap between the target and the output data from the 3D generalization diagrams. The optimal operating conditions of the VMD process can be obtained from the performance analysis of the ANN model with a maximum permeate flux and an acceptable CV value based on the experiment

Coevolution of quantum and classical strategies on evolving random networks

We study the coevolution of quantum and classical strategies on weighted and directed random networks in the realm of the prisoner’s dilemma game. During the evolution, agents can break and rewire their links with the aim of maximizing payoffs, and they can also adjust the weights to indicate preferences, either positive or negative, towards their neighbors. The network structure itself is thus also subject to evolution. Importantly, the directionality of links does not affect the accumulation of payoffs nor the strategy transfers, but serves only to designate the owner of each particular link and with it the right to adjust the link as needed. We show that quantum strategies outperform classical strategies, and that the critical temptation to defect at which cooperative behavior can be maintained rises, if the network structure is updated frequently. Punishing neighbors by reducing the weights of their links also plays an important role in maintaining cooperation under adverse conditions. We find that the self-organization of the initially random network structure, driven by the evolutionary competition between quantum and classical strategies, leads to the spontaneous emergence of small average path length and a large clustering coefficient.Qiang Li, Azhar Iqbal, Matjaž Perc, Minyou Chen, Derek Abbot

N-player quantum games in an EPR setting

The $N$-player quantum game is analyzed in the context of an Einstein-Podolsky-Rosen (EPR) experiment. In this setting, a player's strategies are not unitary transformations as in alternate quantum game-theoretic frameworks, but a classical choice between two directions along which spin or polarization measurements are made. The players' strategies thus remain identical to their strategies in the mixed-strategy version of the classical game. In the EPR setting the quantum game reduces itself to the corresponding classical game when the shared quantum state reaches zero entanglement. We find the relations for the probability distribution for $N$-qubit GHZ and W-type states, subject to general measurement directions, from which the expressions for the mixed Nash equilibrium and the payoffs are determined. Players' payoffs are then defined with linear functions so that common two-player games can be easily extended to the $N$-player case and permit analytic expressions for the Nash equilibrium. As a specific example, we solve the Prisoners' Dilemma game for general $N \ge 2$. We find a new property for the game that for an even number of players the payoffs at the Nash equilibrium are equal, whereas for an odd number of players the cooperating players receive higher payoffs.Comment: 26 pages, 2 figure

INTRPERITONEAL INJECTION OF GABA B RECEPTOR ANTAGONIST (CGP 35348) FOLLOWING NEONATAL BRAIN DAMAGE AFFECTS THE BLOOD CHEMISTRY IN ALBINO MICE

ABSTRACT Aim of this study was to demonstrate the effect of GABA B receptor antagonists (CGP 35348) on hematological and serum biochemical profile of albino mouse injected for 12 days following neonatal hypoxic ischemic insult. Blood samples from 35 albino mice [CGP35348 treated (N = 19) and saline treated (N= 16)] were collected from direct cardiac puncture and various hematological [blood glucose, packed cell volume (PCV), total WBC count, total RBC count] and selected serum biochemical parameters (cholesterol, AST, ALT, HDL, LDL total protein, triglycerides) were determined. Glucose (P &lt; 0.001), TRBC (P &lt; 0.001), MCV (P &lt; 0.001), TWBC (P = 0.02) and PCV (P = 0.005) concentrations were significantly lower in CGP35348 treated as compared to saline treated albino mice. Gender based data analysis revealed that CGP 35348 had more drastic effects in blood chemistry of female than male albino mice as glucose (P = 0.002) and TRBC (P = 0.007) were the only significantly different parameters when compared between GABAB receptor antagonist and saline treated male albino mice while glucose (P = 0.01), TRBC (P = 0.01), TWBC (P = 0.01), PCV (P = 0.01) and MCV (P = 0.047) concentrations were significantly lower in CGP 35348 treated female albino mice than their respective control group indicating gender specific effect of hypoxic ischemic brain damage and CGP 35348 in albino mice

Substrate stiffness affects particle distribution pattern in a drying suspension droplet

The complexities involved in achieving a tailor-made evaporative deposition pattern have remained a challenge. Here, we show that the morphological pattern of drying suspension droplets can be altered by varying substrate elastic modulus E: We find that the particle spot diameter and spacing between the particles scale with substrate stiffness as ds E 0: 15 and s E 1: 23; respectively. We show that the larger spot diameter and spacing between particles on a softer substrate are attributed to a higher energy barrier U associated with stronger pinning of the contact line. The particle deposition pattern is characterized in terms of deposition index, Id; whose value is 0.75 for centralized (multilayer) and uniform (monolayer) deposition patterns observed for stiffer and softer substrates, respectively. The outcome of the present study may find applications in biochemical characterization and analysis of micro-/nanoparticles