The significant increase in the CO sub(2) levels as a result of combustion of hydrocarbons fuels resulted in global warming. The use of solar base technology may decrease CO sub(2) concentration but ...at the same time can be helpful in meeting energy demands. Moreover, most of the photocatalysts work in ultraviolet region of light. In the present work, a successful effort has been made to synthesize a photocatalyst which works in visible region of light. CoTe nanostructures with multiform architectures such as nanospheres, nanodisks, nanobelts, irregular nanoflakes and 3D layered nanostructures have been synthesized through a facile hydrothermal method. A series of well-ordered experiments demonstrated that shape and size of as-synthesized nanostructures can be adjusted effectively by directing reaction conditions such as alkalinity of reaction medium (concentration of KOH), reaction time and use of different surfactants. The X-ray diffraction (XRD) analysis confirmed the hexagonal phase of synthesized samples. UV-visible spectroscopic analysis was employed to evaluate the band gap value and to confirm the activity of nanostructures in visible region of electromagnetic radiations. Valence band position of synthesized CoTe nanostructures was determined by using X-ray photoelectron spectroscopy (XPS). The BET analysis has been employed to study the surface area of synthesized nanostructures. The photocatalytic activity has been studied for the photoreduction of carbon dioxide (CO sub(2)) into methane (CF sub(4)). The effects of different morphologies and particles size on the photocatalytic activity of synthesized nanostructures have been studied. The photocatalytic activity of present nanostructures is greater than most of single semiconductor photocatalysts reported earlier.
The recent work provides the numerical investigation of an unsteady viscous nanofluid flow between two porous plates under the effect of variable magnetic field and suction/injection. Navier Stokes ...equations are modeled to study the hydrothermal properties of four different nanoparticles copper
(
Cu
)
, silver
(
Ag
)
, aluminum oxide
(
A
l
2
O
3
)
, and titanium oxide
(
Ti
O
2
)
. The resultant nonlinear partial differential equations, governing the viscous fluid flow, are solved numerically using Crank–Nicolson scheme. The effect of important physical parameters such as volume fraction, magnetic strength, and porosity parameter are shown both graphically and in tabular form. It is found that due to the greatest thermal diffusivity for nanofluid
Ag
, comparatively the velocity increases more rapidly with the increasing value of volume fraction. Due to this effect, it is preferred to use nanofluid
Ag
for transportation purposes.
5G envisages a "hyper-connected society," where an enormous number of devices are inter-connected anywhere and at any time. Cloud-enabled radio access networks (RANs) where intelligence is placed in ...conjunction with the radio heads at the proximity of end users are a promising solution to fulfill the 5G expectations of sub-millisecond latency, huge traffic volumes, and higher data rates. Network functions virtualization (NFV) and software-defined networking (SDN) developments enable end users to access advanced features, such as configurability, automation, scalability, improved resource utilization, and multi tenancy over the cloud-enabled RANs. Management and orchestration techniques are the ultimate factor that determines the effectiveness of the novel SDN/NFV features being introduced. Our focus in this letter is the resource allocation in a realistic cloud-enabled RAN, taking into account the dynamics of ~100,000 persons movement in a crowded event, i.e., a football match. The proposed solution jointly orchestrates NFV and bandwidth resources, as one resource affects the other. Simulation results clearly verify the benefits of the proposed solution over traditional disjoint schemes.
Low‐dimensional materials and heterostructure photocatalysts are distinct research topics in artificial photocatalysis. The rational design of photocatalysts considering both aspects has established ...significant importance due to the fascinating advantages of superior charge carrier transport/transfer and photocatalytic performances. Graphitic carbon nitride (g‐C3N4), a captivating metal‐free and visible light‐active photocatalyst, has drawn interdisciplinary attention in the field of solar energy conversion and pollutant degradation because of its appropriate electronic band structure, excellent physicochemical stability, facile synthesis, and unique layered structure. The g‐C3N4‐based low‐dimensional heterostructures demonstrate various mechanisms for photogenerated charge carrier transfer including type I heterojunction, type II heterojunction, p–n heterojunction, Z‐scheme heterojunction, Schottky junction, and surface plasmon resonance (SPR) effect. Herein, the state‐of‐the‐art g‐C3N4‐based low‐dimensional heterostructure photocatalysts are analyzed to provide an insightful outlook with respect to doping and defect engineering, band structures tuning, and charged carrier dynamics to realize enhanced visible light absorption, improved photoinduced charge carrier transport/transfer, and spatially separated electron–hole pairs for improved photocatalytic performances. Furthermore, the potential application of g‐C3N4‐based low‐dimensional heterostructures for water splitting, CO2 reduction, and pollutant degradation is also presented. Finally, conclusion and invigorating perspective about challenges and opportunities for advanced design of g‐C3N4‐based low‐dimensional heterostructures are briefed.
Graphitic carbon nitride (g‐C3N4) constructs, state‐of‐the‐art low‐dimensional heterostructure photocatalysts modulated via doping and defect engineering, band structures tuning, and charge carrier dynamics to realize enhanced visible light absorption, improved photoinduced charge carrier transport/transfer, and spatially separated electron–hole pairs for improved photocatalytic performances are analyzed. The recent progress in g‐C3N4‐based low‐dimensional heterostructures for water splitting, CO2 reduction, and pollutant degradation is presented.
The thermophysical features of Casson fluid flow caused by a nonlinear permeable stretchable surface are assessed in the present study. The computational model of Casson fluid is used to define ...viscoelasticity, which is quantified rheologically in the momentum equation. Exothermic chemical reactions, heat absorption/generation, magnetic field and nonlinear volumetric thermal/mass expansion over the stretched surface are also considered. The proposed model equations are lessened by the similarity transformation to the dimensionless system of ODEs. The obtained set of differential equations are numerically computed through parametric continuation approach. The results are displayed and discussed via figures and tables. The outcomes of the proposed problem are compared to the existing literature and bvp4c package for the validity and accuracy purposes. It has been perceived that the energy and mass transition rate of Casson fluid increased with the flourishing trend of heat source parameter and chemical reaction respectively. Casson fluid velocity can be elevated by the rising effect of thermal, mass Grashof number and nonlinear thermal convection.
This research inspects the liquid film flow of the nanofluid in a permeable medium with the consequence of thermal radiation over a stretching sheet. The viscidness and thermal conduction of the ...nanofluid varies with temperature in such a manner that the thermal conductivity considered in direct relation while the viscosity considered inversely proportional to the temperature field. The invariable magnetic field applies vertically to the flow field in the existence of entropy generation. For the above-mentioned nanofluid study, Buongiorno’s model is used. The leading equations are changed into a set of third- and second-order nonlinear coupled differential equations. These nonlinear ordinary differential equations are solved using the optimal approach of homotopy analysis method. The physical appearance of the modelled parameters based on the liquid film thickness is mainly focused. Furthermore, the influence of embedded parameters like variable viscosity parameter
Λ
,
Prandtl number
Pr
,
Schmidt number
Sc
,
Brinkman number
Br
,
Brownian motion constraint
Nb
,
thermophoresis constraint
Nt
,
magnetic parameter
M
,
thermal radiation parameter
Nr
,
Reynolds number
Re
,
diffusion coefficient
λ
,
non-dimension temperature variation
χ
and non-dimension concentration variation
Ω
is observed on the velocity pitch, temperature gradient and concentration sketch. The consequence of parameters due to entropy generation and Bejan number has also been observed in this work. The important physically quantities of skin friction coefficient, the local Nusselt number and Sherwood number have also been studied. Residual error and optimal values have been calculated for the range of each physical parameter. The present work is compared with the published work and the comparison has been shown physically and numerically.
Detection of epileptic seizures on the basis of Electroencephalogram (EEG) recordings is a challenging task due to the complex, non-stationary and non-linear nature of these biomedical signals. In ...the existing literature, a number of automatic epileptic seizure detection methods have been proposed that extract useful features from EEG segments and classify them using machine learning algorithms. Some characterizing features of epileptic and non-epileptic EEG signals overlap; therefore, it requires that analysis of signals must be performed from diverse perspectives. Few studies analyzed these signals in diverse domains to identify distinguishing characteristics of epileptic EEG signals. To pose the challenge mentioned above, in this paper, a fuzzy-based epileptic seizure detection model is proposed that incorporates a novel feature extraction and selection method along with fuzzy classifiers. The proposed work extracts pattern features along with time-domain, frequency-domain, and non-linear analysis of signals. It applies a feature selection strategy on extracted features to get more discriminating features that build fuzzy machine learning classifiers for the detection of epileptic seizures. The empirical evaluation of the proposed model was conducted on the benchmark Bonn EEG dataset. It shows significant accuracy of 98% to 100% for normal vs. ictal classification cases while for three class classification of normal vs. inter-ictal vs. ictal accuracy reaches to above 97.5%. The obtained results for ten classification cases (including normal, seizure or ictal, and seizure-free or inter-ictal classes) prove the superior performance of proposed work as compared to other state-of-the-art counterparts.
Summary Background The excruciating pain of patients with renal colic on presentation to the emergency department requires effective analgesia to be administered in the shortest possible time. Trials ...comparing intramuscular non-steroidal anti-inflammatory drugs with intravenous opioids or paracetamol have been inconclusive because of the challenges associated with concealment of randomisation, small sample size, differences in outcome measures, and inadequate masking of participants and assessors. We did this trial to develop definitive evidence regarding the choice of initial analgesia and route of administration in participants presenting with renal colic to the emergency department. Methods In this three-treatment group, double-blind, randomised controlled trial, adult participants (aged 18–65 years) presenting to the emergency department of an academic, tertiary care hospital in Qatar, with moderate to severe renal colic (Numerical pain Rating Scale ≥4) were recruited. With the use of computer-generated block randomisation (block sizes of six and nine), participants were assigned (1:1:1) to receive diclofenac (75 mg/3 mL intramuscular), morphine (0·1 mg/kg intravenous), or paracetamol (1 g/100 mL intravenous). Participants, clinicians, and trial personnel were masked to treatment assignment. The primary outcome was the proportion of participants achieving at least a 50% reduction in initial pain score at 30 min after analgesia, assessed by intention-to-treat analysis and per-protocol analysis, which included patients where a calculus in the urinary tract was detected with imaging. This trial is registered with ClinicalTrials.gov , number NCT02187614. Findings Between Aug 5, 2014, and March 15, 2015, we randomly assigned 1645 participants, of whom 1644 were included in the intention-to-treat analysis (547 in the diclofenac group, 548 in the paracetemol group, and 549 in the morphine group). Ureteric calculi were detected in 1316 patients, who were analysed as the per-protocol population (438 in the diclofenac group, 435 in the paracetemol group, and 443 in the morphine group). The primary outcome was achieved in 371 (68%) patients in the diclofenac group, 364 (66%) in the paracetamol group, and 335 (61%) in the morphine group in the intention-to-treat population. Compared to morphine, diclofenac was significantly more effective in achieving the primary outcome (odds ratio OR 1·35, 95% CI 1·05–1·73, p=0·0187), whereas no difference was detected in the effectiveness of morphine compared with intravenous paracetamol (1·26, 0·99–1·62, p=0·0629). In the per-protocol population, diclofenac (OR 1·49, 95% CI 1·13–1·97, p=0·0046) and paracetamol (1·40, 1·06–1·85, p=0·0166) were more effective than morphine in achieving the primary outcome. Acute adverse events in the morphine group occurred in 19 (3%) participants. Significantly lower numbers of adverse events were recorded in the diclofenac group (7 1% participants, OR 0·31, 95% CI 0·12–0·78, p=0·0088) and paracetamol group (7 1% participants, 0·36, 0·15–0·87, p=0·0175) than in the morphine group. During the 2 week follow-up, no additional adverse events were noted in any group. Interpretation Intramuscular non-steroidal anti-inflammatory drugs offer the most effective sustained analgesia for renal colic in the emergency department and seem to have fewer side-effects. Funding Hamad Medical Corporation Medical Research Center, Doha, Qatar.
Cloud computing is the de facto platform for deploying resource- and data-intensive real-time applications due to the collaboration of large scale resources operating in cross-administrative domains. ...For example, real-time systems are generated by smart devices (e.g., sensors in smart homes that monitor surroundings in real-time, security cameras that produce video streams in real-time, cloud gaming, social media streams, etc.). Such low-end devices form a microgrid which has low computational and storage capacity and hence offload data unto the cloud for processing. Cloud computing still lacks mature time-oriented scheduling and resource allocation strategies which thoroughly deliberate stringent QoS. Traditional approaches are sufficient only when applications have real-time and data constraints, and cloud storage resources are located with computational resources where the data are locally available for task execution. Such approaches mainly focus on resource provision and latency, and are prone to missing deadlines during tasks execution due to the urgency of the tasks and limited user budget constraints. The timing and data requirements exacerbate the efficient task scheduling and resource allocation problems. To cope with the aforementioned gaps, we propose a time- and cost-efficient resource allocation strategy for smart systems that periodically offload computational and data-intensive load to the cloud. The proposed strategy minimizes the data files transfer overhead to computing resources by selecting appropriate pairs of computing and storage resources. The celebrated results show the effectiveness of the proposed technique in terms of resource selection and tasks processing within time and budget constraints when compared with the other counterparts.
The classical mathematical modeling of ultrasound acoustic bubble is so far using to improve the medical imaging quality. A clear and visible medical ultrasound image relies on bubble’s diameter, ...wavelength and intensity of the scattered sound. A bubble with diameter much smaller than the sound wavelength is regarded as highly efficient source of sound scattering. The dynamical equation for a medical ultrasound bubble is primarily modeled in classical integer-order differential equation. Then a reduction of order technique is used to convert the modeled dynamic equation for the bubble surface into a system of incommensurate fractional-orders. The incommensurate fractional-order values are calculated directly, by using Riemann stability region. On the basis of stability the convergence and accuracy of the numerical scheme is also discussed in detail. It has been found that the system will remain stable and chaotic for the incommensurate values α1<0.737 and α2<2.80, respectively.
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