Mechanisms of multiyear variations of Northern Australia wet-season rainfall

Northern Australia wet season (November–April) rainfall exhibits strong variability on multiyear timescales. In order to reveal the underlying mechanisms of this variability, we investigate observational records for the period 1900–2017. At multiyear timescales, the rainfall varies coherently across north-western Australia (NW) and north-eastern Australia (NE), but the variability in these two regions is largely independent. The variability in the NE appears to be primarily controlled by the remote influence of low frequency variations of El Niño-Southern Oscillation (ENSO). In contrast, multiyear variations in the NW appear to be largely driven locally and stem from a combination of rainfall-wind-evaporation feedback, whereby enhanced land-based rainfall is associated with westerly wind anomalies to the west that enhance local evaporation over the ocean to feed the enhanced land based rainfall, and soil moisture-rainfall feedback. Soil-moisture and associated evapotranspiration over northern Australia appear to act as sources of memory for sustaining multiyear wet and dry conditions in the NW. Our results imply that predictability of multiyear rainfall variations over the NW may derive from the initial soil moisture state and its memory, while predictability in the NE will be limited by the predictability of the low frequency variations of ENSO

EFFORT: Energy efficient framework for offload communication in mobile cloud computing

There is an abundant expansion in the race of technology, specifically in the production of data, because of the smart devices, such as mobile phones, smart cards, sensors, and Internet of Things (IoT). Smart phones and devices have undergone an enormous evolution in a way that they can be used. More and more new applications, such as face recognition, augmented reality, online interactive gaming, and natural language processing are emerging and attracting the users. Such applications are generally data intensive or compute intensive, which demands high resource and energy consumption. Mobile devices are known for the resource scarcity, having limited computational power and battery life. The tension between compute/data intensive application and resource constrained mobile devices hinders the successful adaption of emerging paradigms. In the said perspective, the objective of this paper is to study the role of computation offloading in mobile cloud computing to supplement mobile platforms ability in executing complex applications. This paper proposes a systematic approach (EFFORT) for offload communication in the cloud. The proposed approach provides a promising solution to partially solve energy consumption issue for communication-intensive applications in a smartphone. The experimental study shows that our proposed approach outperforms its counterparts in terms of energy consumption and fast processing of smartphone devices. The battery consumption was reduced to 19% and the data usage was reduced to 16%

The universe dynamics in the tachyon cosmology with non-minimal coupling to matter

Recently, the tachyon cosmology has been represented as dark energy model to support the current acceleration of the universe without phantom crossing. In this paper, we study the dynamics of the tachyon cosmology in which the field plays the role of tachyon field and also non--minimally coupled to the matter lagrangian. The model shows current universe acceleration and also phantom crossing in the future. Two cosmological tests are also performed to validate the model; the difference in the distance modulus and the model independent Cosmological Redshift Drift (CRD) test.Comment: 14 pages, 11 figure

Kinematic alpha effect in isotropic turbulence simulations

Using numerical simulations at moderate magnetic Reynolds numbers up to 220 it is shown that in the kinematic regime, isotropic helical turbulence leads to an alpha effect and a turbulent diffusivity whose values are independent of the magnetic Reynolds number, \Rm, provided \Rm exceeds unity. These turbulent coefficients are also consistent with expectations from the first order smoothing approximation. For small values of \Rm, alpha and turbulent diffusivity are proportional to \Rm. Over finite time intervals meaningful values of alpha and turbulent diffusivity can be obtained even when there is small-scale dynamo action that produces strong magnetic fluctuations. This suggests that small-scale dynamo-generated fields do not make a correlated contribution to the mean electromotive force.Comment: Accepted for publication in MNRAS Letter

Multi-criticality and field induced non-BEC transition in frustrated magnets

Frustrated spin-systems have traditionally proven challenging to understand, owing to a scarcity of controlled methods for their analyses. By contrast, under strong magnetic fields, certain aspects of spin systems admit simpler and universal description in terms of hardcore bosons. The bosonic formalism is anchored by the phenomenon of Bose-Einstein condensation (BEC), which has helped explain the behaviors of a wide range of magnetic compounds under applied magnetic fields. Here, we focus on the interplay between frustration and externally applied magnetic field to identify instances where the BEC paradigm is no longer applicable. As a representative example, we consider the antiferromagnetic $J_1 - J_2 - J_3$ model on the square lattice in the presence of a uniform external magnetic field, and demonstrate that the frustration-driven suppression of the N\'{e}el order leads to a Lifshitz transition for the hardcore bosons. In the vicinity of the Lifshitz point, the physics becomes unmoored from the BEC paradigm, and the behavior of the system, both at and below the saturation field, is controlled by a Lifshitz multicritical point. We obtain the resultant universal scaling behaviors, and provide strong evidence for the existence of a frustration and magnetic-field driven correlated bosonic liquid state along the entire phase boundary separating the N\'{e}el phase from other magnetically ordered states.Comment: 6 pages; 5 figures; v2) updated references, typos fixed, supplemental information added as ancillary fil

Reverse undercompressive shock structures in driven thin film flow

We show experimental evidence of a new structure involving an undercompressive and reverse undercompressive shock for draining films driven by a surface tension gradient against gravity. The reverse undercompressive shock is unstable to transverse perturbations while the leading undercompressive shock is stable. Depending on the pinch-off film thickness, as controlled by the meniscus, either a trailing rarefaction wave or a compressive shock separates from the reverse undercompressive shock

Generalized particle dynamics in anti de Sitter spaces: A source for dark energy

We consider the generalized particle dynamics, proposed by us, in brane world formalisms for an asymptotically anti de Sitter background. The present framework results in a new model that accounts for the late acceleration of the universe. An effective Dark Energy equation of state, exhibiting a phantom like behaviour, is generated. The model is derived by embedding the physical FRW universe in a $(4+1)$-dimensional effective space-time, induced by the generalized particle dynamics. We corroborate our results with present day observed cosmological parameters.Comment: 18 pages, 6 figures. Final version to appear in IJMP

A Deep Learning-Based Privacy-Preserving Model for Smart Healthcare in Internet of Medical Things Using Fog Computing

With the emergence of COVID-19, smart healthcare, the Internet of Medical Things, and big data-driven medical applications have become even more important. The biomedical data produced is highly confidential and private. Unfortunately, conventional health systems cannot support such a colossal amount of biomedical data. Hence, data is typically stored and shared through the cloud. The shared data is then used for different purposes, such as research and discovery of unprecedented facts. Typically, biomedical data appear in textual form (e.g., test reports, prescriptions, and diagnosis). Unfortunately, such data is prone to several security threats and attacks, for example, privacy and confidentiality breach. Although significant progress has been made on securing biomedical data, most existing approaches yield long delays and cannot accommodate real-time responses. This paper proposes a novel fog-enabled privacy-preserving model called [Formula: see text] sanitizer, which uses deep learning to improve the healthcare system. The proposed model is based on a Convolutional Neural Network with Bidirectional-LSTM and effectively performs Medical Entity Recognition. The experimental results show that [Formula: see text] sanitizer outperforms the state-of-the-art models with 91.14% recall, 92.63% in precision, and 92% F1-score. The sanitization model shows 28.77% improved utility preservation as compared to the state-of-the-art

Modeling two-photon calcium fluorescence of episodic V1 recordings using multifrequency analysis

The use of two-photon microscopy allows for imaging of deep neural tissue in vivo. This paper examines frequency-based analysis to two-photon calcium fluorescence images with the goal of deriving smooth tuning curves. We present a multifrequency analysis approach for improved extraction of calcium responses in episodic stimulation experiments, that is, when the stimulus is applied for a number of frames, then turned off for the next few frames, and so on. Episodic orientation stimulus was applied while recording from the primary visual cortex of an anesthetized mouse. The multifrequency model demonstrated improved tuning curve descriptions of the neurons. It also offers perspective regarding the characteristics of calcium fluorescence imaging of the brain.National Institutes of Health (U.S.) (Grant DP1-OD003646)National Institutes of Health (U.S.) (Grant R01-EB006385)National Institutes of Health (U.S.) (Grant EY07023)National Institutes of Health (U.S.) (Grant EY017098

Power-law corrections to entanglement entropy of horizons

We re-examine the idea that the origin of black-hole entropy may lie in the entanglement of quantum fields between inside and outside of the horizon. Motivated by the observation that certain modes of gravitational fluctuations in a black-hole background behave as scalar fields, we compute the entanglement entropy of such a field, by tracing over its degrees of freedom inside a sphere. We show that while this entropy is proportional to the area of the sphere when the field is in its ground state, a correction term proportional to a fractional power of area results when the field is in a superposition of ground and excited states. The area law is thus recovered for large areas. Further, we identify location of the degrees of freedom that give rise to the above entropy.Comment: 16 pages, 6 figures, to appear in Phys. Rev.