Few-mode fibers and AO-assisted high resolution spectroscopy: coupling efficiency and modal noise mitigation

NIRPS (Near Infra-Red Planet Searcher) is an AO-assisted and fiber-fed spectrograph for high precision radial velocity measurements that will operate in the YJH-bands. While using an AO system in such instrument is generally considered to feed a single-mode fiber, NIRPS is following a different path by using a small multi-mode fiber (more specifically called "few-mode fiber"). This choice offers an excellent trade-off by allowing to design a compact cryogenic spectrograph, while maintaining a high coupling efficiency under bad seeing conditions and for faint stars. The main drawback resides in a much more important modal-noise, a problem that has to be tackled for allowing 1m/s precision radial velocity measurements. We study the impact of using an AO system to couple light into few-mode fibers. We focus on two aspects: the coupling efficiency into few-mode fibers and the question of modal noise and scrambling. We show first that NIRPS can reach coupling >= 50% up to magnitude I=12, and offer a gain of 1-2 magnitudes over a single-mode solution. We finally show that the best strategy to mitigate modal noise with the AO system is among the simplest: a continuous tip-tilt scanning of the fiber core.Comment: 10 pages, 5 figures. Proceeding of the AO4ELT5 conferenc

Metallization of cyanide-modified Pt(111) electrodes with copper

The support of the University of Aberdeen is gratefully acknowledged. CW acknowledges a summer studentship from the Carnegie Trust for the Universities of Scotland.Peer reviewedPostprin

PERAN BADAN PENGAWAS DALAM PENGAWASAN KOPERASI BERDASARKAN UNDANG-UNDANG NOMOR 25 TAHUN 1992 TENTANG PERKOPERASIAN

Penelitian ini dilakukan dengan tujuan untuk mengetahui bagaimana peran ataupun fungsi dari badan pengawas terhadap pengawasan koperasi dan bagaimana wewenang dan tanggung jawab badan pengawas terhadap koperasi. Dengan menggunakan metode penelitian yuridis normatif, disimpulkan: 1. Peran ataupun Fungsi dari badan pengawas terhadap koperasi secara garis besar yaitu pengawas secara aktif berperan dalam upaya mempertinggi kualitas kehidupan manusia dan masyarakat termasuk juga didalamnya pengawas berusaha untuk mewujudkan dan mengembangkan perekonomian nasional yang merupakan usaha bersama berdasar atas asas kekeluargaan dan demokrasi ekonomi. Keberadaan Lembaga Badan Pengawas pada struktur organisasi koperasi bukan merupakan sesuatu yang diwajibkan. Artinya pengawasan pada koperasi pada dasarnya dilakukan secara langsung oleh para anggota, tidak semua koperasi Lembaga khusus yang bertugas melakukan pengawasan. 2. Wewenang dan tanggung jawab dari pengawas koperasi secara garis besar meliputi pengawasan terhadap pengelolaan organisasi dan usaha koperasi secara umum, termasuk pemeriksaan terhadap kewajaran laporan keuangan koperasi. Sehubungan dengan pelaksanaan pengawasan tersebut, pengawas memiliki wewenang untuk meminta keterangan yang diperlukan dari pengurus koperasi atau pihak-pihak lain yang dianggap perlu. Selanjutnya pengawas wajib mempertanggung jawabkan laporan tersebut dengan membuat laporan tertulis mengenai pengawasan yang dilakukannya serta menyampaikan kepada rapat anggota.Kata kunci: Peran, Badan Pengawas, Koperas

PENGARUH RASIO KEUANGAN TERHADAP RETURN SAHAM (Studi Empiris pada Perusahaan Food and Beverages yang Terdaftar di BEI)

Penelitian ini untuk menguji pengaruh rasio keuangan terhadap return saham pada perusahaan food and beverages yang terdaftar di Bursa Efek Indonesia (BEI). Dalam penelitian ini likuiditas diukur menggunakan rumus Current Ratio (CR), Solvabilitas diukur dengan Debt to Equity Ratio (DER), Profitabilitas diukur dengan Return On Asset (ROA), Aktivitas diukur dengan Total Asset Turn Over (TATO), Nilai pasar diukur dengan Earning Per Share (EPS). Populasi dalam penelitian ini adalah perusahaan manufaktur sektor food and beverages yang terdaftar di Bursa Efek Indonesia (BEI). Teknik pengambilan sampel menggunakan purposive sampling dan diperoleh 11 sampel perusahaan dengan total pengamatan sebanyak 55 (11x5 tahun) perusahaan manufaktur sektor food and beverages yang terdaftar di Bursa Efek Indonesia (BEI) selama periode 2012-2016. Pengujian hipotesis penelitian ini menggunakan teknik analisis regresi berganda. Hasil penelitian ini menunjukkan bahwa nilai signifikansi Debt to Equity Ratio (DER) sebesar 0,034, Earning Per Share (EPS) sebesar 0,006 yang berarti nilai tersebut lebih kecil dari nilai signifikansi yang ditetapkan yaitu 0,05 atau 5% maka dari itu kedua rasio tersebut yaitu Debt to Equity Ratio (DER) dan Earning Per Share (EPS) berpengaruh positif terhadap return saham, sedangkan untuk nilai signifikansi Current Ratio (CR) sebesar 0,300, Return On Asset (ROA) sebesar 0,351, dan Total Asset Turn Over (TATO) sebesar 0,438 yang berarti nilai tersebut lebih besar dari nilai signifikansi yang ditetapkan yaitu 0,05 atau 5% maka ketiga rasio tersebut Current Ratio (CR), Return On Asset (ROA), Total Asset Turn Over (TATO) tidak berpengaruh terhadap return saham. Kata Kunci : Current Ratio, Debt to Equity Ratio, Return On Asset, Total Asset Turn Over, Earning Per Share, Return Saha

Optimal real-time filters for linear prediction problems

Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch)The classic model-based paradigm in time series analysis is rooted in the Wold decomposition of the data-generating process into an uncorrelated white noise process. By design, this universal decomposition is indifferent to particular features of a specific prediction problem (e. g., forecasting or signal extraction) – or features driven by the priorities of the data-users. A single optimization principle (one-step ahead forecast error minimization) is proposed by this classical paradigm to address a plethora of prediction problems. In contrast, this paper proposes to reconcile prediction problem structures, user priorities, and optimization principles into a general framework whose scope encompasses the classic approach. We introduce the linear prediction problem (LPP), which in turn yields an LPP objective function. Then one can fit models via LPP minimization, or one can directly optimize the linear filter corresponding to the LPP, yielding the Direct Filter Approach. We provide theoretical results and practical algorithms for both applications of the LPP, and discuss the merits and limitations of each. Our empirical illustrations focus on trend estimation (low-pass filtering) and seasonal adjustment in real-time, i. e., constructing filters that depend only on present and past data

Signal extraction revision variances as a goodness-of-fit measure

erworben im Rahmen der Schweizer Nationallizenzen (www.nationallizenzen.ch)Typically, model misspecification is addressed by statistics relying on model-residuals, i.e., on one-step ahead forecasting errors. In practice, however, users are often also interested in problems involving multi-step ahead forecasting performances, which are not explicitly addressed by traditional diagnostics. In this article, we consider the topic of misspecification from the perspective of signal extraction. More precisely, we emphasize the connection between models and real-time (concurrent) filter performances by analyzing revision errors instead of one-step ahead forecasting errors. In applications, real-time filters are important for computing trends, for performing seasonal adjustment or for inferring turning-points towards the current boundary of time series. Since revision errors of real-time filters generally rely on particular linear combinations of one- and multi-step ahead forecasts, we here address a generalization of traditional diagnostics. Formally, a hypothesis testing paradigm for the empirical revision measure is developed through theoretical calculations of the asymptotic distribution under the null hypothesis, and the method is assessed through real data studies as well as simulations. In particular, we analyze the effect of model misspecification with respect to unit roots, which are likely to determine multi-step ahead forecasting performances. We also show that this framework can be extended to general forecasting problems by defining suitable artificial signals

Reconstruction of a long-term recovery process from pasture to forest

We used space-for-time substitution to obtain a directed successional sequence for subalpine meadow vegetation in the Swiss National Park. Since human impacts (e.g., domestic animal grazing) ceased in 1914, the successional processes documented are assumed to be autogenic in nature. The data consist of 59 permanent plots spanning almost 90 years, and include many spatial replications. An initial inspection of the individual time series revealed the existence of a variety of response patterns, which are described in the literature as representing different successional types. However, a closer inspection suggested that many of these series can be superimposed, as they are part of a much longer deterministic series. Linking the individual time series proved to be challenging. A heuristic approach produced results that differed depending on initial starting conditions. We therefore derived a deterministic algorithm to produce a unique solution. The resulting sequence largely confirmed the heuristic interpretation, suggesting a trend from early successional (post-grazing) grassland to pine invasion spanning about 400 years. This timespan is valid only for the climatic conditions near the treeline, and for plant species specific to the study site. Our results suggest that the various species temporal response models described in the literature may be artifactual, representing portions of underlying Gaussian responses. The data also indicate that species assemblages may persist for several decades with only minor fluctuations, only to change suddenly for no apparent reason