ANALISIS TINGKAT KEPUASAN PENGGUNA TERHADAP APLIKASI TIERRA MENGGUNAKAN METODE PIECES FRAMEWORK

TIERRA is a community application for ornamental plant lovers that can be used by users to interact with each other and can share experiences and help about ornamental plants. To improve and develop the TIERRA application, it is necessary to know the level of satisfaction of the TIERRA application by using the PIECES (Performance, Information, Economy, Control, Efficiency, Service) method as a method of measuring the level of user satisfaction. Based on the variables of the PIECES method, namely Performance, Information, Economy, Control, Efficiency and Service, the level of user satisfaction based on each variable is: Performance gets a value of 4.47, Information gets a value of 4.60, Economy gets a value of 4.24, Control gets a value of 4.31, Efficiency gets a value 4.46 and Service scored 4.37. Because each PIECES method variable is on a user satisfaction level scale of 3.4 – 4.91, then user satisfaction with the TIERRA application can be categorized as SATISFIED.TIERRA merupakan aplikasi komunitas pecinta tanaman hias yang dapat digunakan oleh pengguna untuk berinteraksi satu sama lain serta dapat berbagi pengalaman dan membantu seputar tanaman hias. Untuk memperbaiki dan pengembangan aplikasi TIERRA perlu diketahui tingkat kepuasan pengguna aplikasi TIERRA dengan menggunakan metode PIECES (Performance, Information, Economy, Control, Efficiency, Service) sebagai metode pengukuran tingkat kepuasan pengguna. Berdasarkan variabel dari metode PIECES yaitu Performance, Information, Economy, Control, Efficiency dan Service tingkat kepuasan pengguna berdasarkan masing-masing variabel yaitu : Performance memperoleh nilai 4.47, Information memperoleh nilai 4.60, Economy memperoleh nilai 4.24, Control memperoleh nilai 4.31, Efficiency memperoleh nilai 4.46 dan Service memperoleh nilai 4.37. Dikarenakan setiap variabel metode PIECES berada pada skala tingkat kepuasan pengguna 3.4 – 4.91, maka kepuasan pengguna terhadap aplikasi TIERRA dapat dikategorikan PUAS

Simulating effects of hydro-dam alteration on thermal regime and wild steelhead recruitment in a stable-flow Lake Michigan tributary

Hydroelectric dams may affect anadromous fish survival and recruitment by limiting access to upstream habitats and adversely affecting quality of downstream habitats. In the Manistee River, a tributary to Lake Michigan, two hydroelectric dams potentially limit recruitment of anadromous rainbow trout (steelhead) by increasing tailrace water temperatures to levels that significantly reduce survival of young-of-year (YOY) fish. The objectives of this study were to determine whether proposed restoration scenarios (dam removals or a bottom withdrawal retrofit) would alter the Manistee River thermal regime and, consequently, improve wild steelhead survival and recruitment. Physical process models were used to predict Manistee River thermal regimes following each dam alteration scenario. Empirical relationships were derived from historical field surveys to quantify the effect of temperature on YOY production and potential recruitment of Manistee River steelhead. Both dam alteration scenarios lowered summer temperatures and increased steelhead recruitment by between 59% and 129%, but total recruitments were still low compared to other Great Lakes tributaries. Considering only temperature effects, bottom withdrawal provides the greatest promise for increasing natural steelhead recruitment by decreasing the likelihood of year-class failures in the warmest summers. Results of this study may allow managers to evaluate mitigation alternatives for Manistee River dams during future relicensing negotiations, and illustrate the utility of physical process temperature models in groundwater-fed rivers. Copyright © 2004 John Wiley & Sons, Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/35294/1/746_ftp.pd

Performance of the Quasar Spectral Templates for the Dark Energy Spectroscopic Instrument

Millions of quasar spectra will be collected by the Dark Energy Spectroscopic Instrument (DESI), leading to a fourfold increase in the number of known quasars. High-accuracy quasar classification is essential to tighten constraints on cosmological parameters measured at the highest redshifts DESI observes (z > 2.0). We present spectral templates for identification and redshift estimation of quasars in the DESI Year 1 data release. The quasar templates are comprised of two quasar eigenspectra sets, trained on spectra from the Sloan Digital Sky Survey. The sets are specialized to reconstruct quasar spectral variation observed over separate yet overlapping redshift ranges and, together, are capable of identifying DESI quasars from 0.05 < z < 7.0. The new quasar templates show significant improvement over the previous DESI quasar templates regarding catastrophic failure rates, redshift precision and accuracy, quasar completeness, and the contamination fraction in the final quasar sample

Broad absorption line quasars in the Dark Energy Spectroscopic Instrument Early Data Release

Broad absorption line (BAL) quasars are characterized by gas clouds that absorb flux at the wavelength of common quasar spectral features, although blueshifted by velocities that can exceed 0.1c. BAL features are interesting as signatures of significant feedback, yet they can also compromise cosmological studies with quasars by distorting the shape of the most prominent quasar emission lines, impacting redshift accuracy and measurements of the matter density distribution traced by the Lyman α forest. We present a catalogue of BAL quasars discovered in the Dark Energy Spectroscopic Instrument (DESI) survey Early Data Release, which were observed as part of DESI Survey Validation, as well as the first two months of the main survey. We describe our method to automatically identify BAL quasars in DESI data, the quantities we measure for each BAL, and investigate the completeness and purity of this method with mock DESI observations. We mask the wavelengths of the BAL features and re-evaluate each BAL quasar redshift, finding new redshifts which are 243 km s−1 smaller on average for the BAL quasar sample. These new, more accurate redshifts are important to obtain the best measurements of quasar clustering, especially at small scales. Finally, we present some spectra of rarer classes of BALs that illustrate the potential of DESI data to identify such populations for further study

IT-Related Barriers and Facilitators to the Implementation of a New European eHealth Solution, the Digital Survivorship Passport (SurPass Version 2.0): Semistructured Digital Survey

Background: To overcome knowledge gaps and optimize long-term follow-up (LTFU) care for childhood cancer survivors, the concept of the Survivorship Passport (SurPass) has been invented. Within the European PanCareSurPass project, the semiautomated and interoperable SurPass (version 2.0) will be optimized, implemented, and evaluated at 6 LTFU care centers representing 6 European countries and 3 distinct health system scenarios: (1) national electronic health information systems (EHISs) in Austria and Lithuania, (2) regional or local EHISs in Italy and Spain, and (3) cancer registries or hospital-based EHISs in Belgium and Germany. Objective: We aimed to identify and describe barriers and facilitators for SurPass (version 2.0) implementation concerning semiautomation of data input, interoperability, data protection, privacy, and cybersecurity. Methods: IT specialists from the 6 LTFU care centers participated in a semistructured digital survey focusing on IT-related barriers and facilitators to SurPass (version 2.0) implementation. We used the fit-viability model to assess the compatibility and feasibility of integrating SurPass into existing EHISs. Results: In total, 13/20 (65%) invited IT specialists participated. The main barriers and facilitators in all 3 health system scenarios related to semiautomated data input and interoperability included unaligned EHIS infrastructure and the use of interoperability frameworks and international coding systems. The main barriers and facilitators related to data protection or privacy and cybersecurity included pseudonymization of personal health data and data retention. According to the fit-viability model, the first health system scenario provides the best fit for SurPass implementation, followed by the second and third scenarios. Conclusions: This study provides essential insights into the information and IT-related influencing factors that need to be considered when implementing the SurPass (version 2.0) in clinical practice. We recommend the adoption of Health Level Seven Fast Healthcare Interoperability Resources and data security measures such as encryption, pseudonymization, and multifactor authentication to protect personal health data where applicable. In sum, this study offers practical insights into integrating digital health solutions into existing EHISs