Performance and flow dynamics studies of polymeric optofluidic sers sensors

We present a polymer-based optofluidic surface enhanced Raman scattering chip for biomolecule detection, serving as a disposable sensorchoice with cost-effective production. The SERS substrate is fabricated by using industrial roll-to-roll UV-nanoimprinting equipment andintegrated with adhesive-based polymeric microfluidics. The functioning of the SERS detection on-chip is confirmed and the effect of thepolymer lid on the obtainable Raman spectra is analysed. Rhodamine 6G is used as a model analyte to demonstrate continuous flowmeasurements on a planar SERS substrate in a microchannel. The relation between the temporal response of the sensors and sample flowdynamics is studied with varied flow velocities, using SERS and fluorescence detection. The response time of the surface-dependent SERSsignal is longer than the response time of the fluorescence signal of the bulk flow. This observation revealed the effect of convection on thetemporal SERS responses at 25 μl/min to 1000 μl/min flow velocities. The diffusion of analyte molecules from the bulk concentration intothe sensing surface induces about a 40-second lag time in the SERS detection. This lag time, and its rising trend with slower flow velocities, has to be taken into account in future trials of the optofluidic SERS sensor, with active analyte binding on the sensing surface

A portable methane sampling system for radiocarbon-based bioportion measurements and environmental CH4 sourcing studies

Radiocarbon measurements can be used to deduce the proportion of renewable to fossil carbon in materials. While these biofraction measurements are performed routinely on solid and liquid substances, measurements of gaseous samples, such as methane, are still scarce. As a pioneering effort, we have developed a field-capable sampling system for the selective capture of CH4 for radiocarbon-concentration measurements. The system allows for biofraction measurements of methane by accelerator mass spectrometry. In environmental research, radiocarbon measurements of methane can be used for fingerprinting different sources of methane emissions. In metrology and industry, biofraction measurements can be utilized to characterize biogas/natural gas mixtures within gas-line networks. In this work, the portable sampling system is described in detail and reference measurements of biofractions of gaseous fuel samples are presented. Low-concentration (1-ppm-CH4) sampling for environmental applications appears feasible but has not been fully tested at present. This development allows for multitude of future applications ranging from Arctic methane emissions to biogas insertion to gas networks. Published by AIP Publishing.Peer reviewe

Shape coexistence at the proton drip-line: First identification of excited states in 180Pb

Excited states in the extremely neutron-deficient nucleus, 180Pb, have been identified for the first time using the JUROGAM II array in conjunction with the RITU recoil separator at the Accelerator Laboratory of the University of Jyvaskyla. This study lies at the limit of what is presently achievable with in-beam spectroscopy, with an estimated cross-section of only 10 nb for the 92Mo(90Zr,2n)180Pb reaction. A continuation of the trend observed in 182Pb and 184Pb is seen, where the prolate minimum continues to rise beyond the N=104 mid-shell with respect to the spherical ground state. Beyond mean-field calculations are in reasonable correspondence with the trends deduced from experiment.Comment: 5 pages, 4 figures, submitted to Phys.Rev.

The power of coarse graining in biomolecular simulations

Computational modeling of biological systems is challenging because of the multitude of spatial and temporal scales involved. Replacing atomistic detail with lower resolution, coarse grained (CG), beads has opened the way to simulate large-scale biomolecular processes on time scales inaccessible to all-atom models. We provide an overview of some of the more popular CG models used in biomolecular applications to date, focusing on models that retain chemical specificity. A few state-of-the-art examples of protein folding, membrane protein gating and self-assembly, DNA hybridization, and modeling of carbohydrate fibers are used to illustrate the power and diversity of current CG modeling

First observation of excited states in 173Hg

The neutron-deficient nucleus 173Hg has been studied following fusion-evaporation reactions. The observation of gamma rays decaying from excited states are reported for the first time and a tentative level scheme is proposed. The proposed level scheme is discussed within the context of the systematics of neighbouring neutron-deficient Hg nuclei. In addition to the gamma-ray spectroscopy, the alpha decay of this nucleus has been measured yielding superior precision to earlier measurements.Comment: 5 pages, 4 figure

HybridDeepRx: Deep Learning Receiver for High-EVM Signals

In this paper, we propose a machine learning (ML) based physical layer receiver solution for demodulating OFDM signals that are subject to a high level of nonlinear distortion. Specifically, a novel deep learning based convolutional neural network receiver is devised, containing layers in both time- and frequency domains, allowing to demodulate and decode the transmitted bits reliably despite the high error vector magnitude (EVM) in the transmit signal. Extensive set of numerical results is provided, in the context of 5G NR uplink incorporating also measured terminal power amplifier characteristics. The obtained results show that the proposed receiver system is able to clearly outperform classical linear receivers as well as existing ML receiver approaches, especially when the EVM is high in comparison with modulation order. The proposed ML receiver can thus facilitate pushing the terminal power amplifier (PA) systems deeper into saturation, and thereon improve the terminal power-efficiency, radiated power and network coverage.Comment: To be presented in the 2021 IEEE International Symposium on Personal, Indoor and Mobile Radio Communication

Pediatric malignancies in neurofibromatosis type 1: A population‐based cohort study

Neurofibromatosis type 1 (NF1) is a cancer predisposition syndrome with an incidence of 1:2,000. Patients with NF1 have an increased cancer risk and mortality, but there are no population‐based cohort studies specifically investigating the risk of childhood malignancies. We used the Finnish NF1 cohort to analyze the incidence, risk and prognosis of malignancies in NF1 patients </p

Detection of dengue virus type 2 of Indian origin in acute febrile patients in rural Kenya

Dengue virus (DENV) has caused recent outbreaks in coastal cities of Kenya, but the epidemiological situation in other areas of Kenya is largely unknown. We investigated the role of DENV infection as a cause of acute febrile disease in non-epidemic settings in rural and urban study areas in Kenya. Altogether, 560 patients were sampled in 2016-2017 in rural Taita-Taveta County (n = 327) and urban slums of Kibera, Nairobi (n = 233). The samples were studied for DENV IgM, IgG, NS1 antigen and flaviviral RNA. IgG seroprevalence was found to be higher in Taita-Taveta (14%) than in Nairobi (3%). Five Taita-Taveta patients were positive for flaviviral RNA, all identified as DENV-2, cosmopolitan genotype. Local transmission in Taita-Taveta was suspected in a patient without travel history. The sequence analysis suggested that DENV-2 strains circulating in coastal and southern Kenya likely arose from a single introduction from India. The molecular clock analyses dated the most recent ancestor to the Kenyan strains a year before the large 2013 outbreak in Mombasa. After this, the virus has been detected in Kilifi in 2014, from our patients in Taita-Taveta in 2016, and in an outbreak in Malindi in 2017. The results highlight that silent transmission occurs between epidemics and also affects rural areas. More information is needed to understand the local epidemiological characteristics and future risks of dengue in Kenya. Author summary Dengue virus (DENV) is an emerging mosquito-borne global health threat in the tropics and subtropics. The majority of the world's population live in areas at risk of dengue that can cause a wide variety of symptoms from febrile illness to haemorrhagic fever. Information of DENV in Africa is limited and fragmented. In Kenya, dengue is a recognized disease in coastal cities that have experienced recent outbreaks. We investigated the role of DENV infection as a cause of acute febrile disease in non-epidemic settings in rural and urban study areas in Kenya. We found DENV-2 in five febrile patients from rural Taita-Taveta, where no dengue has been reported before. Genetic analysis of the virus suggests it to be most likely of Indian origin. This Indian origin DENV-2 was detected in the Mombasa outbreak in 2013, in Kilifi in 2014, in Taita-Taveta in 2016 (our study samples) and again in the Malindi outbreak in 2017. The results suggest that dengue is unrecognized in rural Kenya and more studies are needed for local risk assessment. Our findings of virus transmission between epidemics contribute to better understanding of the epidemiological situation and origins of DENV in Kenya.Peer reviewe