The CosmicWatch Desktop Muon Detector: a self-contained, pocket sized particle detector

The CosmicWatch Desktop Muon Detector is a self-contained, hand-held cosmic ray muon detector that is valuable for astro/particle physics research applications and outreach. The material cost of each detector is under $100 and it takes a novice student approximately four hours to build their first detector. The detectors are powered via a USB connection and the data can either be recorded directly to a computer or to a microSD card. Arduino- and Python-based software is provided to operate the detector and an online application to plot the data in real-time. In this paper, we describe the various design features, evaluate the performance, and illustrate the detectors capabilities by providing several example measurements.Comment: 11 pages, 8 figure

The Desktop Muon Detector: A simple, physics-motivated machine- and electronics-shop project for university students

This paper describes an undergraduate-level physics project that incorporates various aspects of machine- and electronics-shop technical development. The desktop muon detector is a self-contained apparatus that employs plastic scintillator as a detection medium and a silicon photomultiplier for light collection. These detectors can be used in conjunction with the provided software to make interesting physics measurements. The total cost of each counter is approximately $100.Comment: 29 pages, 14 figure

The Prediction of Recovery Rate of Covid 19 Case in Kabupaten Bandung Barat using Neural Network Algorithm

The COVID-19 pandemic that happens worldwide has affected not only human health, social activities, the economy, education but also the death rate caused by this pandemic. Although the death rate from COVID-19 worldwide is quite high, the recovery rate is also quite promising. Therefore, this study is conducted to predict the recovery rate of COVID-19 cases in Indonesia, specifically in Kabupaten Bandung Barat, which was analyzed using the Neural Network Algorithm. The method of this study is data mining, using the neural network algorithm that analyzed data, consisting of 2 attributes and 1 class attribute, namely: Daily Case that represent the daily new confirmed case in the observed location, Daily Death that represents the daily new number of confirmed deaths in observed location. The class attributes are using Daily Recovered, which represents the daily new number of confirmed recoveries in the observed location. The findings of this study indicate that the neural network models in this study have a Root Mean Square Error (RMSE) 102.168 to predict the recovery rate of COVID-19 cases in the observed location. Keywords: Recovery Rate, Covid 19, Neural Network Algorith

Expression of a catalytically inactive mutant form of glutathione peroxidase 4 (Gpx4) confers a dominant-negative effect in male fertility.

The selenoenzyme Gpx4 is essential for early embryogenesis and cell viability for its unique function to prevent phospholipid oxidation. Recently, the cytosolic form of Gpx4 was identified as an upstream regulator of a novel form of non-apoptotic cell death, called ferroptosis, whereas the mitochondrial isoform of Gpx4 (mGpx4) was previously shown to be crucial for male fertility. Here, we generated and analyzed mice with targeted mutation of the active site selenocysteine (Sec) of Gpx4 (Gpx4_U46S). Mice homozygous for Gpx4_U46S died at the same embryonic stage (E7.5) as Gpx4-/- embryos as expected. Surprisingly, male mice heterozygous for Gpx4_U46S presented subfertility. Subfertility was manifested in a reduced number of litters from heterozygous breedings and an impairment of spermatozoa to fertilize oocytes in vitro. Morphologically, sperm isolated from heterozygous Gpx4_U46S mice revealed many structural abnormalities particularly in the spermatozoan midpiece due to improper oxidation and polymerization of sperm capsular proteins and malformation of the mitochondrial capsule surrounding and stabilizing sperm mitochondria. These findings are reminiscent of sperm isolated from selenium-deprived rodents or from mice specifically lacking mGpx4. Due to a strongly facilitated incorporation of Ser in the polypeptide chain as compared to Sec at the UGA codon, expression of the catalytically inactive Gpx4_U46S was found to be strongly increased. Since the stability of the mitochondrial capsule of mature spermatozoa depends on the moonlighting function of Gpx4 both as an enzyme oxidizing capsular protein thiols and being a structural protein, tightly controlled expression of functional Gpx4 emerges being key for full male fertility

Global Analysis of Neutrino Data

In this talk I review the present status of neutrino masses and mixing and some of their implications for particle physics phenomenology. I first discuss the minimum extension of the Standard Model of particle physics required to accommodate neutrino masses and introduce the new parameters present in the model and in particular the possibility of leptonic mixing. I then describe the phenomenology of neutrino masses and mixing leading to flavour oscillations and present the existing evidence from solar, reactor, atmospheric and long-baseline neutrinos as well as the results from laboratory searches at short distances. I derive the allowed ranges for the mass and mixing parameters when the bulk of data is consistently analyzed in the framework of mixing between the three active neutrinos and obtain as a result the most up-to-date determination of the leptonic mixing matrix. Then I briefly summarize the status of some proposed phenomenological explanations to accommodate the LSND results: the role of sterile neutrinos and the violation of CPT. Finally I comment how within the present experimental precision it is possible to use the observation of oscillation patterns to impose severe constraints on the possible violation of fundamental symmetries in particle physics such as Lorentz invariance or the weak equivalence principle.Comment: Talk given at the Nobel Symposium on Neutrino Physics, Haga Slott, Enkoping, Swede

Synchronization reveals topological scales in complex networks

We study the relationship between topological scales and dynamic time scales in complex networks. The analysis is based on the full dynamics towards synchronization of a system of coupled oscillators. In the synchronization process, modular structures corresponding to well defined communities of nodes emerge in different time scales, ordered in a hierarchical way. The analysis also provides a useful connection between synchronization dynamics, complex networks topology and spectral graph analysis.Comment: 4 pages, 3 figure

The structural properties of the multi-layer graphene/4H-SiC(000-1) system as determined by Surface X-ray Diffraction

We present a structural analysis of the multi-layer graphene-4HSiC(000-1}) system using Surface X-Ray Reflectivity. We show for the first time that graphene films grown on the C-terminated (000-1}) surface have a graphene-substrate bond length that is very short (0.162nm). The measured distance rules out a weak Van der Waals interaction to the substrate and instead indicates a strong bond between the first graphene layer and the bulk as predicted by ab-initio calculations. The measurements also indicate that multi-layer graphene grows in a near turbostratic mode on this surface. This result may explain the lack of a broken graphene symmetry inferred from conduction measurements on this system [C. Berger et al., Science 312, 1191 (2006)].Comment: 9 pages with 6 figure