327 research outputs found
Energy efficient resource allocation in 5G hybrid heterogeneous networks: A game theoretic approach
Millimeter wave (mmWave) technology integrated with heterogeneous networks (HetNets) has emerged as a new wave to overcome the thirst for higher data rates and severe shortage of spectrum. In this paper, we consider the uplink of a hybrid HetNet with femtocells overlaid on a macrocell, and formulate a two layer game theoretic framework to maximise the energy efficiency (EE) while optimising the network resources. The outer layer allows each femtocell access point (FAP) to maximise the data rate of its users by selecting the frequency band either from the sub-6 GHz and the mmWave. The solution to this non-cooperative game can be obtained by using pure strategy Nash equilibrium. The inner layer ensures the energy efficient user association method subject to the minimum rate and maximum transmission power constraints by using dual decomposition approach. Simulation results show that the proposed hybrid HetNet scheme exploiting the mmWave frequency band improves the sum-rate and EE in comparison to the scenario where all the networks operate at sub-6 GHz frequency band. The performance can further be enhanced by incorporating the power control mechanism
Computationally Intelligent Techniques for Resource Management in MmWave Small Cell Networks
Ultra densification in HetNets and the advent of mmWave technology for 5G networks have led researchers to redesign the existing resource management techniques. A salient feature of this activity is to accentuate the importance of CI resource allocation schemes offering less complexity and overhead. This article overviews the existing literature on resource management in mmWave-based Het- Nets with a special emphasis on CI techniques and further proposes frameworks that ensure quality of service requirements for all network entities. More specifically, HetNets with mmWave-based small cells pose different challenges compared to an all-microwave- based system. Similarly, various modes of small cell access policies and operations of base stations in dual mode, that is, operating both mmWave and microwave links simultaneously, offer unique challenges to resource allocation. Furthermore, the use of multi-slope path loss models becomes inevitable for analysis due to irregular cell patterns and blocking characteristics of mmWave communications. This article amalgamates the unique challenges posed because of the aforementioned recent developments and proposes various CI-based techniques, including game theory and optimization routines, to perform efficient resource management
Strengthening Food Security in Pakistan During the Covid-19 Pandemic
Pakistan is facing numerous socioeconomic impacts of the Covid-19 pandemic, including on food security. Food insecurity, which is a long-standing issue, has become more visible since the pandemic. Covid-19 Responses for Equity (CORE) partner the Sustainable Development Policy Institute (SDPI) – a leading policy research thinktank – has been supporting the Government of Pakistan to maintain essential economic activity and protect workers and small producers during the pandemic. One notable contribution has been the development of a Food Security Portal, which is being used by the government to better manage food security in the country. It is the first track and trace system from farm to fork for essential food items
TitrationAnalysis: a tool for high throughput binding kinetics data analysis for multiple label-free platforms [version 1; peer review: 3 approved]
Label-free techniques including Surface Plasmon Resonance (SPR) and Biolayer Interferometry (BLI) are biophysical tools widely used to collect binding kinetics data of bimolecular interactions. To efficiently analyze SPR and BLI binding kinetics data, we have built a new high throughput analysis tool named the TitrationAnalysis. It can be used as a package in the Mathematica scripting environment and ultilize the non-linear curve-fitting module of Mathematica for its core function. This tool can fit the binding time course data and estimate association and dissociation rate constants (ka and kd respectively) for determining apparent dissociation constant (KD) values. The high throughput fitting process is automatic, requires minimal knowledge on Mathematica scripting and can be applied to data from multiple label-free platforms. We demonstrate that the TitrationAnalysis is optimal to analyze antibody-antigen binding data acquired on Biacore T200 (SPR), Carterra LSA (SPR imaging) and ForteBio Octet Red384 (BLI) platforms. The ka, kd and KD values derived using TitrationAnalysis very closely matched the results from the commercial analysis software provided specifically for these instruments. Additionally, the TitrationAnalysis tool generates user-directed customizable results output that can be readily used in downstream Data Quality Control associated with Good Clinical Laboratory Practice operations. With the versatility in source of data input source and options of analysis result output, the TitrationAnalysis high throughput analysis tool offers investigators a powerful alternative in biomolecular interaction characterization
Assessing burned areas in wildfires and prescribed fires with spectral indices and SAR images in the Margalla Hills of Pakistan
The extent of wildfires cannot be easily mapped using field-based methods in areas with complex topography and in those areas, the use of remote sensing is an alternative. This study first obtained images from the Sentinel-2 satellites for the period 2015-2020 with the objective of applying multi-temporal spectral indices to assess areas burned in wildfires and prescribed fires in the Margalla Hills of Pakistan using Google Earth Engine (GEE). Using those images, the Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR), which are often used to assess the severity of fires, were calculated for wildfires and prescribed fires. For each satellite image scene, spectral indices values were extracted for the 5th, 20th, 40th, 60th, 80th and 95th percentiles of pixels of each burned area. Then, box plots representing the distribution of these values were plotted for each satellite image to identify whether the regeneration time subsequent to a fire, also known as the burn scar, and the severity of the fire differed between the autumn and summer wildfires, and with prescribed fires. A statistical test revealed no differences for the re-generation time amongst the three categories of fires, but that the severity of summer wildfires was significantly different from that of prescribed fire, and this, for both indices. Second, SAR images were obtained from the Sentinel-1 mission for the same period as that of the optical imagery. A visual interpretation of the 34 variables of SAR response revealed that the 95th percentile of the Normalized Signal Ratio (NSR p_95) is adequate to detect burned areas in the study area. Moreover, it was found that 95% of the plots analyzed by the 80th percentile NSR (NSR p_80) showed a good response to fires in comparison to the spectral indices
Gapless spinons and a field-induced soliton gap in the hyper-honeycomb Cu oxalate framework compound [(CH)NH]Cu(CO)
We report a detailed study of the specific heat and magnetic susceptibility
of single crystals of a spin liquid candidate: the hyper-honeycomb Cu oxalate
framework compound [(CH)NH]Cu(CO). The specific
heat shows no anomaly associated with a magnetic transition at low temperatures
down to 180 mK in zero magnetic field. We observe a large linear-in-
contribution to the specific heat , mK/mol K,
at low temperatures, indicative of the presence of fermionic excitations
despite the Mott insulating state. The low- specific heat is strongly
suppressed by applied magnetic fields , which induce an energy gap, , in the spin-excitation spectrum. We use the four-component relativistic
density-functional theory (DFT) to calculate the magnetic interactions,
including the Dzyaloshinskii-Moriya antisymmetric exchange, which causes an
effective staggered field acting on one copper sublattice. The magnitude and
field dependence of the field-induced gap, , are
accurately predicted by the soliton mass calculated from the sine-Gordon model
of weakly coupled antiferromagnetic Heisenberg chains with all parameters
determined by our DFT calculations. Thus our experiment and calculations are
entirely consistent with a model of
[(CH)NH]Cu(CO) in which anisotropic magnetic
exchange interactions due to Jahn-Teller distortion cause one copper sublattice
to dimerize, leaving a second sublattice of weakly coupled antiferromagnetic
chains. We also show that this model quantitatively accounts for the measured
temperature-dependent magnetic susceptibility. Thus
[(CH)NH]Cu(CO) is a canonical example of a
one-dimensional spin-1/2 Heisenberg antiferromagnet and not a
resonating-valence-bond quantum spin liquid, as previously proposed.Comment: 8 pages, 6 figure
Evolutionary Trajectories of Avian Avulaviruses and Vaccines Compatibilities in Poultry.
Newcastle disease virus (NDV) causes one of the highly infectious avian diseases in poultry leading to genuine financial misfortunes around the world. Recently, there has been an increasing trend in the number of ND-associated outbreaks in commercial Jordanian poultry flocks indicating a possible complex evolutionary dynamic of NDV infections in the country. To underpin the dynamics of circulating NDV strains and to assess the vaccine-escape potential, a total of 130 samples were collected from different poultry flocks in six Jordanian Governorates during 2019-2021. Twenty positive isolates, based on real-time reverse transcriptase PCR, were used for further genetic characterization and evolutionary analysis. Our results showed that there is a high evolutionary distance between the newly identified NDV strains (genotype VII.1.1) in this study and the commercially used vaccines (genotypes I and II), suggesting that circulating NDV field strains are under constant evolutionary pressure. These mutations may significantly affect flocks that have received vaccinations as well as flocks with insufficient immunity in terms of viral immunity and disease dynamics. To assess this further, we investigated the efficacy of the heterologous inactivated LaSota or homologous genotype VII.1.1 vaccine for their protection against virulent NDV in chicken. Vaccine-induced immunity was evaluated based on the serology, and protection efficacy was assessed based on clinical signs, survival rates, histopathology, and viral shedding. Chickens vaccinated with the inactivated genotype VII.1.1 based vaccine showed 100% protection with a significant reduction in virus shedding, and ameliorated histopathology lesions compared to LaSota vaccinated chicks that showed 60% protection. These results revealed that the usage of NDV inactivated vaccine from the circulating field strains can successfully ameliorate the clinical outcome and virus pathobiology in vaccinated chicks and will serve as an effective vaccine against the threat posed by commonly circulating NDV strains in the poultry industry
From mechatronics to the Cloud
At its conception mechatronics was viewed purely in terms of the ability to integrate the technologies of mechanical and electrical engineering with computer science to transfer functionality, and hence complexity, from the mechanical domain to the software domain. However, as technologies, and in particular computing technologies, have evolved so the nature of mechatronics has changed from being purely associated with essentially stand-alone systems such as robots to providing the smart objects and systems which are the building blocks for Cyber-Physical Systems, and hence for Internet of Things and Cloud-based systems. With the possible advent of a 4th Industrial Revolution structured around these systems level concepts, mechatronics must again adapt its world view, if not its underlying technologies, to meet this new challenge
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