DESIGN AND CHARACTERIZATION OF PHOTONIC CRYSTAL FIBER FOR SENSING APPLICATIONS

A simple structure of Photonic Crystal Fiber (PCF) for gas sensing and chemical sensing has been proposed in this paper. Index guiding properties of proposed PCF have been numerically investigated by using finite element method (FEM). From the numerical result, it is shown that the relative sensitivity and confinement loss depend on geomatrical parameters and wavelength. The relative sensitivity is increased by a increase of the diameters of central hollow core and innermost ring holes and confinement loss is decreased with a increase of the diameters of outermost cladding holes. By optimize the parmeters, the relative sensitivity is improved to the value of 20.10%. In this case, the confinement loss of the fiber is 1.09×10-3 dB/m

Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future

The upcoming 5th Generation (5G) of wireless networks is expected to lay a foundation of intelligent networks with the provision of some isolated Artificial Intelligence (AI) operations. However, fully-intelligent network orchestration and management for providing innovative services will only be realized in Beyond 5G (B5G) networks. To this end, we envisage that the 6th Generation (6G) of wireless networks will be driven by on-demand self-reconfiguration to ensure a many-fold increase in the network performanceandservicetypes.Theincreasinglystringentperformancerequirementsofemergingnetworks may finally trigger the deployment of some interesting new technologies such as large intelligent surfaces, electromagnetic-orbital angular momentum, visible light communications and cell-free communications – tonameafew.Ourvisionfor6Gis–amassivelyconnectedcomplexnetworkcapableofrapidlyresponding to the users’ service calls through real-time learning of the network state as described by the network-edge (e.g., base-station locations, cache contents, etc.), air interface (e.g., radio spectrum, propagation channel, etc.), and the user-side (e.g., battery-life, locations, etc.). The multi-state, multi-dimensional nature of the network state, requiring real-time knowledge, can be viewed as a quantum uncertainty problem. In this regard, the emerging paradigms of Machine Learning (ML), Quantum Computing (QC), and Quantum ML (QML) and their synergies with communication networks can be considered as core 6G enablers. Considering these potentials, starting with the 5G target services and enabling technologies, we provide a comprehensivereviewoftherelatedstate-of-the-artinthedomainsofML(includingdeeplearning),QCand QML, and identify their potential benefits, issues and use cases for their applications in the B5G networks. Subsequently,weproposeanovelQC-assistedandQML-basedframeworkfor6Gcommunicationnetworks whilearticulatingitschallengesandpotentialenablingtechnologiesatthenetwork-infrastructure,networkedge, air interface and user-end. Finally, some promising future research directions for the quantum- and QML-assisted B5G networks are identified and discussed

Design and Optimization of Highly Sensitive Photonic Crystal Fiber with Low Confinement Loss for Ethanol Detection

In this paper, two highly sensitive photonic crystal fiber (PCF) structures with microstructure core and cladding have been demonstrated for Ethanol sensing. The microstructure core of both proposed PCFs is designed with supplementary holes in an octagonal formation. We have investigated the relative sensitivity and the confinement loss of the proposed PCF structures employing a full vectorial finite element method (FEM). The proposed PCFs work at a wide transmission band covering 0.8 µm to 2 µm and exhibit high sensitivity and low confinement loss simultaneously. The numerical analysis shows that the circular shape of air holes in the first ring is a more salient attribute for increasing sensitivity and the presence of the square shape of air holes in the first ring shows better performance to reduce confinement loss

Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic

Introduction Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality. Methods Prospective cohort study in 109 institutions in 41 countries. Inclusion criteria: children <18 years who were newly diagnosed with or undergoing active treatment for acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, retinoblastoma, Wilms tumour, glioma, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, medulloblastoma and neuroblastoma. Of 2327 cases, 2118 patients were included in the study. The primary outcome measure was all-cause mortality at 30 days, 90 days and 12 months. Results All-cause mortality was 3.4% (n=71/2084) at 30-day follow-up, 5.7% (n=113/1969) at 90-day follow-up and 13.0% (n=206/1581) at 12-month follow-up. The median time from diagnosis to multidisciplinary team (MDT) plan was longest in low-income countries (7 days, IQR 3-11). Multivariable analysis revealed several factors associated with 12-month mortality, including low-income (OR 6.99 (95% CI 2.49 to 19.68); p<0.001), lower middle income (OR 3.32 (95% CI 1.96 to 5.61); p<0.001) and upper middle income (OR 3.49 (95% CI 2.02 to 6.03); p<0.001) country status and chemotherapy (OR 0.55 (95% CI 0.36 to 0.86); p=0.008) and immunotherapy (OR 0.27 (95% CI 0.08 to 0.91); p=0.035) within 30 days from MDT plan. Multivariable analysis revealed laboratory-confirmed SARS-CoV-2 infection (OR 5.33 (95% CI 1.19 to 23.84); p=0.029) was associated with 30-day mortality. Conclusions Children with cancer are more likely to die within 30 days if infected with SARS-CoV-2. However, timely treatment reduced odds of death. This report provides crucial information to balance the benefits of providing anticancer therapy against the risks of SARS-CoV-2 infection in children with cancer

Proposal of a gas sensor with high sensitivity, birefringence and nonlinearity for air pollution monitoring

Flammable or poisonous gasses in the air are capable of destroying a geographical area of causing a fire, fulmination, and venomous exposure. This paper presents a micro-cored photonic crystal fiber based gas sensor for detecting colorless or toxic gasses and monitoring air pollution by measuring gas condensate components in production facilities. The numerical investigation of the proposed PCF takes place using the finite element method (FEM). The geometrical parameters of proposed PCF are varied to optimize and observe the dependence of guiding properties on them. According to simulated results, the high relative sensitivity of 53.07% is obtained at 1.33 μm wavelength for optimum parameters. In addition, high birefringence of the order 6.9 × 10−3; lower confinement loss of 3.21 × 10−6 dB/m is also gained at the same wavelength. Moreover, nonlinear coefficient, effective area, splice loss, V parameters and beat length are reported briefly. Keywords: Gas sensor, Air pollution sensing, Birefringence, Nonlinear coefficient, Sensitivity, Photonic crystal fibe

Design of a porous cored hexagonal photonic crystal fiber based optical sensor with high relative sensitivity for lower operating wavelength

Abstract In this article, highly sensitive and low confinement loss enriching micro structured photonic crystal fiber (PCF) has been suggested as an optical sensor. The proposed PCF is porous cored hexagonal (P-HPCF) where cladding contains five layers with circular air holes and core vicinity is formed by two layered elliptical air holes. Two fundamental propagation characteristics such as the relative sensitivity and confinement loss of the proposed P-HPCF have been numerically scrutinized by the full vectorial finite element method (FEM) simulation procedure. The optimized values are modified with different geometrical parameters like diameters of circular or elliptical air holes, pitches of the core, and cladding region over a spacious assortment of wavelength from 0.8 µm to 1.8 µm. All pretending results exhibit that the relative sensitivity is enlarged according to decrement of wavelength of the transmission band (O+E+S+C+L+U). In addition, all useable liquids reveal the maximum sensitivity of 57.00%, 57.18%, and 57.27% for n=1.33, 1.354, and 1.366 respectively by lower band. Moreover, effective area, nonlinear coefficient, frequency, propagation constant, total electric energy, total magnetic energy, and wave number in free space of the proposed P-HPCF have been reported recently

Investigation of highly birefringent and highly nonlinear Hexa Sectored PCF with low confinement loss

A novel design of Hexa Sectored Photonic Crystal Fiber (HS-PCF) with high nonlinearity and high birefringence has been revealed in this paper where core is slotted and filled with Gallium Phosphide (GaP). Finite Element Method has been used for numerical investigation of the proposed PCF along with finer mesh. Different optical parameters like nonlinearity, effective area, power fraction, birefringence, confinement loss and Numerical Aperture (NA) have been explored by proper tuning of Geometrical variables. The investigation shows that, proposed PCF exhibits high nonlinearity of 9.47 × 104 W−1Km−1 at the operating wavelength of 1.4 µm along with high birefringence of 0.259, Numerical aperture of 0.8774 and very low confinement loss of 5.78 × 10−9 dB/m at the optical wavelength of 2.0 µm. Therefore, it is expected that this proposed PCF could be a strong candidate in biomedical imaging, super continuum generation and sensing applications considering polarized light. Keywords: Photonic crystal fiber, Birefringence, Low confinement loss, Nonlinearity, GaP strips, Slotted cor

Folded cladding porous shaped photonic crystal fiber with high sensitivity in optical sensing applications: Design and analysis

A micro structure folded cladding porous shaped with circular air hole photonic crystal fiber (FP-PCF) is proposed and numerically investigated in a broader wavelength range from 1.4 µm to 1.64 µm (E+S+C+L+U) for chemical sensing purposes. Employing finite element method (FEM) with anisotropic perfectly matched layer (PML) various properties of the proposed FP-PCF are numerically inquired. Filling the hole of core with aqueous analyte ethanol (n = 1.354) and tuning different geometric parameters of the fiber, the sensitivity order of 64.19% and the confinement loss of 2.07 × 10-5 dB/m are attained at 1.48 µm wavelength in S band. The investigated numerical simulation result strongly focuses on sensing purposes; because this fiber attained higher sensitivity with lower confinement loss over the operating wavelength. Measuring time of sensitivity, simultaneously confinement loss also inquired. It reflects that confinement loss is highly dependable on PML depth but not for sensitivity. Beside above properties numerical aperture (NA), nonlinearity, and effective area are also computed. This FP-PCF also performed as sensor for other alcohol series (methanol, propanol, butanol, pentanol). Optimized FP-PCF shows higher sensitivity and low confinement loss carrying high impact in the area of chemical as well as gas sensing purposes. Surely it is clear that install such type of sensor will flourish technology massively.         Keywords: Confinement loss, Effective area, Index guiding FP-PCF, Numerical aperture, Nonlinear coefficient, Sensitivit