Perancangan Video Dokumenter Pulau Liukang Loe Di Kabupaten Bulukumba Provinsi Sulawesi Selatan

Indonesia memiliki potensi pariwisata yang besar meliputi wisata bahari, dimana berupa wilayah pantai dan alam laut untuk dikembangkan dan diperkenalkan kepada wisatawan nusantara dan mancanegara. Salah satu keindahan bahari yang dimiliki Indonesia berlokasi di Kabupaten Bulukumba Provinsi Sulawesi Selatan yaitu Pulau Liukang Loe dimana keindahan wisata baharinya masih alami. Kebanyakan masyarakat Indonesia belum mengetahui potensi-potensi keindahan alam yang ada di Indonesia. Perancangan video dokumenter ini dibuat untuk memperkenalkan potensi keindahan Pulau Liukang Loe di Kabupaten Bulukumba. Dalam perancangan ini melalui 3 tahapan diantaranya yaitu, tahap pra-produksi, tahap produksi, tahap pasca produksi dimana metode pengumpulan data menggunakan metode deskriptif kualitatif. Hasil dari perancangan video dokumenter ini berdurasi 10 - 15 menit dimana Pulau Liukang Loe diperkenalkan melalui media audio visual yang menyajikan informasi-informasi mengenai Pulau Liukang Loe yang akan membuat para penonton menikmati keindahan alam yang dimiliki pulau tersebut

Magnetothermodynamics of BPS baby skyrmions

The magnetothermodynamics of skyrmion type matter described by the gauged BPS baby Skyrme model at zero temperature is investigated. We prove that the BPS property of the model is preserved also for boundary conditions corresponding to an asymptotically constant magnetic field. The BPS bound and the corresponding BPS equations saturating the bound are found. Further, we show that one may introduce pressure in the gauged model by a redefinition of the superpotential. Interestingly, this is related to non-extremal type solutions in the so-called fake supersymmetry method. Finally, we compute the equation of state of magnetized BSP baby skyrmions inserted into an external constant magnetic field $H$ and under external pressure $P$, i.e., $V=V(P,H)$, where $V$ is the "volume" (area) occupied by the skyrmions. We show that the BPS baby skyrmions form a ferromagnetic medium.Comment: Latex, 39 pages, 14 figures. v2: New results and references added, physical interpretation partly change

Artificial gauge fields for the Bose-Hubbard model on a checkerboard superlattice and extended Bose-Hubbard model

We study the effects of an artificial gauge field on the ground-state phases of the Bose-Hubbard model on a checkerboard superlattice in two dimensions, including the superfluid phase and the Mott and alternating Mott insulators. First, we discuss the single-particle Hofstadter problem, and show that the presence of a checkerboard superlattice gives rise to a magnetic flux-independent energy gap in the excitation spectrum. Then, we consider the many-particle problem, and derive an analytical mean-field expression for the superfluid-Mott and superfluid--alternating-Mott insulator phase transition boundaries. Finally, since the phase diagram of the Bose-Hubbard model on a checkerboard superlattice is in many ways similar to that of the extended Bose-Hubbard model, we comment on the effects of magnetic field on the latter model, and derive an analytical mean-field expression for the superfluid-insulator phase transition boundaries as well.Comment: 8 pages, 5 figures and 1 table; to appear in EPJ

A novel method for measuring patients' adherence to insulin dosing guidelines: introducing indicators of adherence

<p>Abstract</p> <p>Background</p> <p>Diabetic type 1 patients are often advised to use dose adjustment guidelines to calculate their doses of insulin. Conventional methods of measuring patients' adherence are not applicable to these cases, because insulin doses are not determined in advance. We propose a method and a number of indicators to measure patients' conformance to these insulin dosing guidelines.</p> <p>Methods</p> <p>We used a database of logbooks of type 1 diabetic patients who participated in a summer camp. Patients used a guideline to calculate the doses of insulin lispro and glargine four times a day, and registered their injected doses in the database. We implemented the guideline in a computer system to calculate recommended doses. We then compared injected and recommended doses by using five indicators that we designed for this purpose: absolute agreement (AA): the two doses are the same; relative agreement (RA): there is a slight difference between them; extreme disagreement (ED): the administered and recommended doses are merely opposite; Under-treatment (UT) and over-treatment (OT): the injected dose is not enough or too high, respectively. We used weighted linear regression model to study the evolution of these indicators over time.</p> <p>Results</p> <p>We analyzed 1656 insulin doses injected by 28 patients during a three weeks camp. Overall indicator rates were AA = 45%, RA = 30%, ED = 2%, UT = 26% and OT = 30%. The highest rate of absolute agreement is obtained for insulin glargine (AA = 70%). One patient with alarming behavior (AA = 29%, RA = 24% and ED = 8%) was detected. The monitoring of these indicators over time revealed a crescendo curve of adherence rate which fitted well in a weighted linear model (slope = 0.85, significance = 0.002). This shows an improvement in the quality of therapeutic decision-making of patients during the camp.</p> <p>Conclusion</p> <p>Our method allowed the measurement of patients' adherence to their insulin adjustment guidelines. The indicators that we introduced were capable of providing quantitative data on the quality of patients' decision-making for the studied population as a whole, for each individual patient, for all injections, and for each time of injection separately. They can be implemented in monitoring systems to detect non-adherent patients.</p

Calibration of the charge and energy loss per unit length of the MicroBooNE liquid argon time projection chamber using muons and protons

We describe a method used to calibrate the position- and time-dependent response of the MicroBooNE liquid argon time projection chamber anode wires to ionization particle energy loss. The method makes use of crossing cosmic-ray muons to partially correct anode wire signals for multiple effects as a function of time and position, including cross-connected TPC wires, space charge effects, electron attachment to impurities, diffusion, and recombination. The overall energy scale is then determined using fully-contained beam-induced muons originating and stopping in the active region of the detector. Using this method, we obtain an absolute energy scale uncertainty of 2% in data. We use stopping protons to further refine the relation between the measured charge and the energy loss for highly-ionizing particles. This data-driven detector calibration improves both the measurement of total deposited energy and particle identification based on energy loss per unit length as a function of residual range. As an example, the proton selection efficiency is increased by 2% after detector calibration

Reconstruction and measurement of (100) MeV energy electromagnetic activity from π0 arrow γγ decays in the MicroBooNE LArTPC

We present results on the reconstruction of electromagnetic (EM) activity from photons produced in charged current νμ interactions with final state π0s. We employ a fully-automated reconstruction chain capable of identifying EM showers of (100) MeV energy, relying on a combination of traditional reconstruction techniques together with novel machine-learning approaches. These studies demonstrate good energy resolution, and good agreement between data and simulation, relying on the reconstructed invariant π0 mass and other photon distributions for validation. The reconstruction techniques developed are applied to a selection of νμ + Ar → μ + π0 + X candidate events to demonstrate the potential for calorimetric separation of photons from electrons and reconstruction of π0 kinematics

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector.

The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies

State sampling dependence of the Hopfield network inference

The fully connected Hopfield network is inferred based on observed magnetizations and pairwise correlations. We present the system in the glassy phase with low temperature and high memory load. We find that the inference error is very sensitive to the form of state sampling. When a single state is sampled to compute magnetizations and correlations, the inference error is almost indistinguishable irrespective of the sampled state. However, the error can be greatly reduced if the data is collected with state transitions. Our result holds for different disorder samples and accounts for the previously observed large fluctuations of inference error at low temperatures.Comment: 4 pages, 1 figure, further discussions added and relevant references adde