Non-adiabatic holonomic quantum computation

We develop a non-adiabatic generalization of holonomic quantum computation in which high-speed universal quantum gates can be realized by using non-Abelian geometric phases. We show how a set of non-adiabatic holonomic one- and two-qubit gates can be implemented by utilizing optical transitions in a generic three-level $\Lambda$ configuration. Our scheme opens up for universal holonomic quantum computation on qubits characterized by short coherence times.Comment: Some changes, journal reference adde

Pembuatan dan Pengembangan Account E-Commerce pada “Waroeng Bali Tani”

Perkembangan teknologi informasi di Indonesia mengalami peningkatan di setiap harinya. Tentu saja perkembangan positif ini dapat kita manfaatkan untuk membantu masyarakat sekitar kita, seperti melakukan perdagangan tanpa perlu bertatap muka, terlebih di masa pandemi Covid-19 ini dampak teknologi sangatlah besar. Dimana UMKM pastinya mengalami penurunan omset penjualan, dikarenakan menurunnya intensitas pembeli yang datang karena tidak berani keluar rumah, sekarang konsumen cenderung membeli segala sesuatu menggunakan e-commerce. Kegiatan pengabdian masyarakat ini kami lakukan untuk memberikan media penjualan secara online melalui e-commerce berupa account Shopee dan cara pengembangannya kepada Waroeng Bali Tani yang merupakan UMKM produk pertanian. Pengabdian ini menggunakan metode Participatory Action Research (PAR), dengan terlibat secara langsung dalam penggalian informasi yang dibutuhkan oleh narasumber. Berdasarkan metode PAR, kami mengambil 3 tahapan metode dalam pengabdian ini yakni metode pendekatan, metode pengenalan, dan metode pengembangan. Hasil dari pengabdian adalah berupa account e-commerce dan pelatihan pengembangan account tersebut, agar nantinya UMKM ini dapat berkembang dengan adanya bantuan teknologi

Glasgow Coma Scale score at intensive care unit discharge predicts the 1-year outcome of patients with severe traumatic brain injury

OBJECTIVE: To analyse the association between the Glasgow Coma Scale (GCS) score at intensive care unit (ICU) discharge and the 1-year outcome of patients with severe traumatic brain injury (TBI). DESIGN: Retrospective analysis of prospectively collected observational data. PATIENTS: Between 01/2001 and 12/2005, 13 European centres enrolled 1,172 patients with severe TBI. Data on accident, treatment and outcomes were collected. According to the GCS score at ICU discharge, survivors were classified into four groups: GCS scores 3–6, 7–9, 10–12 and 13–15. Using the Glasgow Outcome Scale (GOS), 1-year outcomes were classified as “favourable” (scores 5, 4) or “unfavourable” (scores <4). Factors that may have contributed to outcomes were compared between groups and for favourable versus unfavourable outcomes within each group. MAIN RESULTS: Of the 538 patients analysed, 308 (57 %) had GCS scores 13–15, 101 (19 %) had scores 10–12, 46 (9 %) had scores 7–9 and 83 (15 %) had scores 3–6 at ICU discharge. Factors significantly associated with these GCS scores included age, severity of trauma, neurological status (GCS, pupils) at admission and patency of the basal cisterns on the first computed tomography (CT) scan. Favourable outcome was achieved in 74 % of all patients; the rates were significantly different between GCS groups (93, 83, 37 and 10 %, respectively). Within each of the GCS groups, significant differences regarding age and trauma severity were found between patients with favourable versus unfavourable outcomes; neurological status at admission and CT findings were not relevant. CONCLUSION: The GCS score at ICU discharge is a good predictor of 1-year outcome. Patients with a GCS score <10 at ICU discharge have a poor chance of favourable outcome

Autoencoder-based cleaning in probabilistic databases

In the field of data integration, data quality problems are often encountered when extracting, combining, and merging data. The probabilistic data integration approach represents information about such problems as uncertainties in a probabilistic database. In this paper, we propose a data-cleaning autoencoder capable of near-automatic data quality improvement. It learns the structure and dependencies in the data to identify and correct doubtful values. A theoretical framework is provided, and experiments show that it can remove significant amounts of noise from categorical and numeric probabilistic data. Our method does not require clean data. We do, however, show that manually cleaning a small fraction of the data significantly improves performance.Comment: Submitted to ACM Journal of Data and Information Quality, Special Issue on Deep Learning for Data Qualit

Rona Awal Makrobentos Di Perairan Tapak Pltn Muria

Rona Awal Makrobentos di Perairan Tapak PLTN Muria. Rencana pembangunan PLTN diperkirakan mempunyai potensi menimbulkan dampak negatif terhadap ekosistem perairan. Besaran dampak akan sangat tergantung pada kondisi rona awal dibandingkan dengan kondisi setelah terjadi Perubahan lingkungan akibat kegiatan proyek. Makrobentos merupakan organisme yang penting dalam rantai makanan. Metode yang digunakan untuk penelitian ini adalah sampling acak. Pengambilan sampel sedimen menggunakan Ekman grab sampler. Identifikasi dilakukan dengan mikroskop; individu yang berukuran cukup besar diidentifikasi dengan binokular. Kelimpahan dan indeks keanekaragaman spesies dilakukan berdasarkan rumus Shannon. Hewan makrobentos yang dijumpai di tapak PLTN pada ekosistem laut adalah Bivalvia, Polychaeta, Anguilla, Echinodermata dan Capitella

Performance of IMPACT, CRASH and Nijmegen models in predicting six month outcome of patients with severe or moderate TBI: An external validation study

Background: External validation on different TBI populations is important in order to assess the generalizability of prognostic models to different settings. We aimed to externally validate recently developed models for prediction of six month unfavourable outcome and six month mortality. Methods: The International Neurotrauma Research Organization - Prehospital dataset (INRO-PH) was collected within an observational study between 2009-2012 in Austria and includes 778 patients with TBI of GCS < = 12. Three sets of prognostic models were externally validated: the IMPACT core and extended models, CRASH basic models and the Nijmegen models developed by Jacobs et al - all for prediction of six month unfavourable outcome and six month mortality. The external validity of the models was assessed by discrimination (Area Under the receiver operating characteristic Curve, AUC) and calibration (calibration statistics and plots). Results: Median age in the validation cohort was 50 years and 44% had an admission GSC motor score of 1-3. Six-month mortality was 27%. Mortality could better be predicted (AUCs around 0.85) than unfavourable outcome (AUCs around 0.80). Calibration plots showed that the o

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