Fundamental properties of light unavoidably impose features on images collected using fluorescence microscopes. Modeling these features is ever more important in quantitatively interpreting microscopy images collected...
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The recent Mamba model has shown remarkable adaptability for visual representation learning, including in medical imaging tasks. This study introduces MambaMIR, a Mamba-based model for medical image reconstruction, as...
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We develop a hybrid oscillator-qubit processor framework for quantum simulation of strongly correlated fermions and bosons that avoids the boson-to-qubit mapping overhead encountered in qubit hardware. This framework ...
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This paper discusses the use of federated learning as a method for optimizing decision-making in communication systems. Federated learning is a machine learning technique that enables the training of models on decentr...
This paper discusses the use of federated learning as a method for optimizing decision-making in communication systems. Federated learning is a machine learning technique that enables the training of models on decentralized data, allowing for the collection and analysis of data from multiple sources while maintaining the privacy and security of the data. This approach is particularly useful in communication systems, as it allows for the optimization of decision-making across a wide range of devices and networks. The paper examines the advantages of federated learning, including the ability to collect a large amount of data from a diverse range of devices, the protection of sensitive data, and the ability to adapt to changing conditions in real-time. The paper also provides specific examples of how federated learning can be used in the optimization of mobile networks and content delivery. The conclusion highlights the growing importance of federated learning in improving communication systems.
Energy monitoring is one of the important points of a Home Energy Management System (HEMS) and aims to perform itemized energy detection in order to extract information on the distribution of energy consumed. This tas...
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We demonstrate the integration of graphene with conventional flash memory technology. The structure allows for programmable memory by electrostatic doping in graphene. The device could also find applications in tunabl...
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We examine CP-violating effects on electroweak phase transition (EWPT) in the standard model with a complex singlet scalar focusing particularly on a scenario where additional scalars have masses close to 125 GeV. Suc...
We examine CP-violating effects on electroweak phase transition (EWPT) in the standard model with a complex singlet scalar focusing particularly on a scenario where additional scalars have masses close to 125 GeV. Such a high mass degeneracy makes collider signatures in the scenario standard model like, and current experimental data cannot distinguish them from the standard model predictions. We utilize a simplified scalar potential to understand impacts of CP violation on EWPT qualitatively. Then, one-loop effective potential with a thermal resummation is employed for full numerical evaluations. As a phenomenological consequence, gravitational waves from the first-order EWPT are also evaluated. We find that the strength of the first-order EWPT would get weaker as the CP-violating effect becomes larger. As a result, gravitational wave amplitudes are diminished by the size of the CP violation. Future gravitational wave experiments may shed light on CP violation in the singlet scalar sector as well as the experimental blind spot due to the high mass degeneracy.
The treatment of stormwater to remove and recover nutrients has received increasing interest. The objective of this study was to develop a novel adsorbent that is easy to handle, has good adsorption capacity, and is e...
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The aim of the paper is to present a design cycle regarding to the construction of an unmanned cargo aircraft with own weight up to 25 kg, operating range of up to 100 km and AGL operating ceiling of up to 1...
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In this work,methylammonium lead triiodide(CH3NH3PbI3)perovskite solar cells with efficiencies higher than 18%were achieved using a new nanocomposite hole transport layer(HTL)by doping poly(ethylenedioxythiophene):pol...
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In this work,methylammonium lead triiodide(CH3NH3PbI3)perovskite solar cells with efficiencies higher than 18%were achieved using a new nanocomposite hole transport layer(HTL)by doping poly(ethylenedioxythiophene):poly(styrene sulfonate)(PEDOT:PSS)with a mixed dopant of polyaniline(PANI)and graphene oxide(GO).A synergistic engineering between GO,PANI,and PEDOT:PSS was accomplished to introduce additional energy levels between perovskite and PEDOT:PSS and increase the conductivity of PEDOT:*** probe force microscope results confirmed that adding GO to PEDOT:PSS/PANI composite significantly reduced the average surface *** increased the open circuit voltage(Voc)to 1.05 V for the GO/PEDOT:PSS/PANI nanocomposite perovskite solar cells from the pristine PEDOT:PSS(Voc=0.95 V)and PEDOT:PSS/PANI(Voc=0.99 V).In addition,adding PANI to the HTLs substantially enhanced short circuit current density(Jsc).This was supported by the current sensing-atomic force microscopy(CS-AFM)and conductivity *** PANI doped films showed superior electrical conductivity compared with those without PANI as indicated by CS-AFM *** can fill the gaps between the microflakes of GO and give rise to more compact hole transport material(HTM)*** led to a higher Jsc after doping with PANI,which was consistent with the incident photon-to-current efficiency and electrochemical impedance spectroscopy *** results of X-ray diffraction(XRD)and AFM indicated the GO/PANI doped HTMs significantly improved the crystallinity,topography,and crystal size of the perovskite film grown on their surface.A higher efficiency of 18.12%for p-i-n perovskite solar cells has been obtained by adding the mixed dopant of GO,PANI,and PEDOT:PSS,demonstrating better stability than the pristine PEDOT:PSS cell.
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