Cryogenics at the Extremely Large Telescope (ELT)

The European Southern Observatory (ESO) is building the Extremely Large Telescope (ELT), a 40-m class telescope to be installed on top of the 3046 m high mountain Cerro Armazones in the central part of Chile\u27s Atacama Desert. Once being operational around 2025, the ELT will be the largest optical/near-infrared telescope in the world, gathering 13 times more light than the largest optical telescopes existing today. “The world\u27s biggest eye on the sky” will vastly advance astrophysical knowledge by enabling detailed studies of planets around other stars, the first galaxies in the Universe, super-massive black holes, and the nature and distribution of dark matter and energy which dominate the Universe. Powerful facility instruments are under development that can deliver the science cases for the ELT. The first instrument roadmap is listing more than six scientific instruments, each of them in the 10 - 20 tons class. Three selected first-light instruments are currently in detailed design phase, a diffraction-limited near-infrared imager, a single-field near-infrared wide-band integral field spectrograph, and a mid-infrared imager and spectrometer. While the telescope optics operates at ambient temperature, the instrument optics and in particular the detectors will be cooled to cryogenic temperatures down to 4 Kelvin. ESO is aiming to implement proven technology and commercial off-the-shelf components to build the cryogenic infrastructure for the ELT instruments. A combination of Liquid Nitrogen cooling and low-vibration cryo-coolers will be installed to provide the required temperature levels and cooling capacities. I will present a brief status of the ELT construction and the planned instruments, and will give an overview of the cryogenic concept

Efficient Detectors for Telegram Splitting based Transmission in Low Power Wide Area Networks with Bursty Interference

Low Power Wide Area (LPWA) networks are known to be highly vulnerable to external in-band interference in terms of packet collisions which may substantially degrade the system performance. In order to enhance the performance in such cases, the telegram splitting (TS) method has been proposed recently. This approach exploits the typical burstiness of the interference via forward error correction (FEC) and offers a substantial performance improvement compared to other methods for packet transmissions in LPWA networks. While it has been already demonstrated that the TS method benefits from knowledge on the current interference state at the receiver side, corresponding practical receiver algorithms of high performance are still missing. The modeling of the bursty interference via Markov chains leads to the optimal detector in terms of a-posteriori symbol error probability. However, this solution requires a high computational complexity, assumes an a-priori knowledge on the interference characteristics and lacks flexibility. We propose a further developed scheme with increased flexibility and introduce an approach to reduce its complexity while maintaining a close-to-optimum performance. In particular, the proposed low complexity solution substantially outperforms existing practical methods in terms of packet error rate and therefore is highly beneficial for practical LPWA network scenarios.Comment: Accepted for publication in IEEE Transactions on Communication

Split Options for 5G Radio Access Networks

5G networks are supposed to offer a high flexibility in a several ways. In this regard, a twofold split of the processing in the radio access network is under discussion: A control plane / user plane split to support the software defined network-ing principle and a radio protocol stack layer based split to allow a flexible placement of processing functions between a central and one or more distributed units. In this work, the motivation and state of the art for both splits are described including a discussion of the advantages and disadvantages. It is followed by a description of a network architecture al-lowing a flexible implementation of these splits. This especially focuses on the required interfaces between control and user plane

Validation of computerized wheeze detection in young infants during the first months of life

Background Several respiratory diseases are associated with specific respiratory sounds. In contrast to auscultation, computerized lung sound analysis is objective and can be performed continuously over an extended period. Moreover, audio recordings can be stored. Computerized lung sounds have rarely been assessed in neonates during the first year of life. This study was designed to determine and validate optimal cut-off values for computerized wheeze detection, based on the assessment by trained clinicians of stored records of lung sounds, in infants aged <1 year. Methods Lung sounds in 120 sleeping infants, of median (interquartile range) postmenstrual age of 51 (44.5–67.5) weeks, were recorded on 144 test occasions by an automatic wheeze detection device (PulmoTrack®). The records were retrospectively evaluated by three trained clinicians blinded to the results. Optimal cut-off values for the automatically determined relative durations of inspiratory and expiratory wheezing were determined by receiver operating curve analysis, and sensitivity and specificity were calculated. Results The optimal cut-off values for the automatically detected durations of inspiratory and expiratory wheezing were 2% and 3%, respectively. These cutoffs had a sensitivity and specificity of 85.7% and 80.7%, respectively, for inspiratory wheezing and 84.6% and 82.5%, respectively, for expiratory wheezing. Inter-observer reliability among the experts was moderate, with a Fleiss’ Kappa (95% confidence interval) of 0.59 (0.57-0.62) for inspiratory and 0.54 (0.52 - 0.57) for expiratory wheezing. Conclusion Computerized wheeze detection is feasible during the first year of life. This method is more objective and can be more readily standardized than subjective auscultation, providing quantitative and noninvasive information about the extent of wheezing

SIGLEC-1 in Systemic Sclerosis: A Useful Biomarker for Differential Diagnosis

Systemic Sclerosis (SSc) is a clinically heterogeneous disease that includes an upregulation of type I interferons (IFNs). The aim of this observational study was to investigate the IFN-regulated protein Sialic Acid–Binding Ig-like Lectin 1 (SIGLEC-1) as a biomarker for disease phenotype, therapeutic response, and differential diagnosis in SSc. Levels of SIGLEC-1 expression on monocytes of 203 SSc patients were determined in a cross-sectional and longitudinal analysis using multicolor flow cytometry, then compared to 119 patients with other rheumatic diseases and 13 healthy controls. SSc patients higher SIGLEC-1 expression on monocytes (2097.94 ± 2134.39) than HCs (1167.45 ± 380.93; p = 0.49), but significantly lower levels than SLE (8761.66 ± 8325.74; p < 0.001) and MCTD (6414.50 ± 1846.55; p < 0.001) patients. A positive SIGELC-1 signature was associated with reduced forced expiratory volume (p = 0.007); however, we were unable to find an association with fibrotic or vascular disease manifestations. SIGLEC-1 remained stable over time and was independent of changes in immunosuppressive therapy. However, SIGLEC-1 is suitable for differentiating SSc from other connective tissue diseases. SIGLEC-1 expression on monocytes can be useful in the differential diagnosis of connective tissue disease but not as a biomarker for SSc disease manifestations or activity

Machine-Learning-Based Detecting of Eyelid Closure and Smiling Using Surface Electromyography of Auricular Muscles in Patients with Postparalytic Facial Synkinesis: A Feasibility Study

Surface electromyography (EMG) allows reliable detection of muscle activity in all nine intrinsic and extrinsic ear muscles during facial muscle movements. The ear muscles are affected by synkinetic EMG activity in patients with postparalytic facial synkinesis (PFS). The aim of the present work was to establish a machine-learning-based algorithm to detect eyelid closure and smiling in patients with PFS by recording sEMG using surface electromyography of the auricular muscles. Sixteen patients (10 female, 6 male) with PFS were included. EMG acquisition of the anterior auricular muscle, superior auricular muscle, posterior auricular muscle, tragicus muscle, orbicularis oculi muscle, and orbicularis oris muscle was performed on both sides of the face during standardized eye closure and smiling tasks. Machine-learning EMG classification with a support vector machine allowed for the reliable detection of eye closure or smiling from the ear muscle recordings with clear distinction to other mimic expressions. These results show that the EMG of the auricular muscles in patients with PFS may contain enough information to detect facial expressions to trigger a future implant in a closed-loop system for electrostimulation to improve insufficient eye closure and smiling in patients with PFS

Nucleus basalis of Meynert predicts cognition after deep brain stimulation in Parkinson's disease

INTRODUCTION Subthalamic DBS in Parkinson's disease has been associated with cognitive decline in few cases. Volume reduction of the nucleus basalis of Meynert (NBM) seems to precede cognitive impairment in Parkinson's disease. In this retrospective study, we evaluated NBM volume as a predictor of cognitive outcome 1 year after subthalamic DBS. METHODS NBM volumes were calculated from preoperative MRIs using voxel-based morphometry. Cognitive outcome was defined as the relative change of MMSE or DemTect scores from pre-to 1 year postoperatively. A multiple linear regression analysis adjusted for the number of cognitive domains affected in the preoperative neuropsychological testing and UPDRS III was conducted. To account for other variables and potential non-linear effects, an additional machine learning analysis using random forests was applied. RESULTS 55 patients with Parkinson's disease (39 male, age 61.4 ± 7.5 years, disease duration 10.8 ± 4.7 years) who received bilateral subthalamic DBS electrodes at our center were included. Although overall cognition did not change significantly, individual change in cognitive abilities was variable. Cognitive outcome could be predicted based on NBM size (B = 208.98, p = 0.022*) in the regression model (F(3,49) = 2.869; R2 of 0.149; p = 0.046*). Using random forests with more variables, cognitive outcome could also be predicted (average root mean squared error between predicted and true cognitive change 11.28 ± 9.51, p = 0.039*). Also in this model, NBM volume was the most predictive variable. CONCLUSION NBM volume can be used as a simple non-invasive predictor for cognitive outcome after DBS in Parkinson's disease, especially when combined with other clinical parameters that are prognostically relevant

Policies for an Ageing Workforce Work-life balance, working conditions and equal opportunities 2019

At a time of rapid population ageing, a key means of sustaining current welfare states is to extend the length of working lives. In 2050, the share of people over the age of 75 years will be the same as the share over 65 years today. And just as not all are able to work to the age of 65 now, not everyone will be able to work to the age of 75 in 2050; even if future older workers will in all likelihood be healthier and have better working aids at their disposal. Extending average working lives by 10 years, and at the same time ensuring an adequate social safety net for those unable to work into their late 60s and 70s, is a major social policy challenge for the coming decades. And because people are much more likely to work late in life if they had stable careers before reaching 60, tackling this policy challenge means pulling on many more social policy levers than just pension policy. While being keenly aware of these issues and how they relate to the overall agenda of active ageing, Commissioner Thyssen also reminds us in her Foreword that marked increases in life expectancy – both past and in the future – represent enormous social progress. The Commissioner makes the point that older people too contribute to society. And more so with lifelong learning and investment in skills