A New IEEE 802.15.4 Simulation Model for OMNeT++ / INET

This paper introduces a new IEEE 802.15.4 simulation model for OMNeT++ / INET. 802.15.4 is an important underlying standard for wireless sensor networks and Internet of Things scenarios. The presented implementation is designed to be compatible with OMNeT++ 4.x and INET 2.x and laid-out to be expandable for newer revisions of the 802.15.4 standard. The source code is available online https://github.com/michaelkirsche/IEEE802154INET-StandaloneComment: Published in: A. F\"orster, C. Sommer, T. Steinbach, M. W\"ahlisch (Eds.), Proc. of 1st OMNeT++ Community Summit, Hamburg, Germany, September 2, 2014, arXiv:1409.0093, 201

Milasauskis, Albert oral history interview

Born 1915 in Nashua, N.H. Parents had come from Lithuania and settled in Lewiston in 1916, working in mills. He too worked in the mill before marrying in 1939 and going to work in Portland shipyard

Exploring and pushing the boundaries of tunable and waveguide-based high harmonic sources

Current HHG experiments often face at least one of the following problems: low photon flux, long integration times, and a fixed harmonic comb structure that may not cover all desired photon energies. Tunable HHG sources have been developed, but suffer from moderate photon flux, incomplete spectral coverage, high complexity and low tuning speed, or a combination of these. This work addresses all these challenges by demonstrating a state-of-the-art photon flux between 50 eV and 70 eV, and 80 eV and 120 eV. The presented EUV source achieves full tunability with low losses and allows fast tuning by adjusting the pulse energy of the driving laser. By deliberately changing the pulse energy, both dispersion and plasma-induced effects can be used to change the instantaneous wavelength of the laser pulse and thus the generated EUV radiation. The experiments showed that managing the heat generated by the high average power of the driving laser is challenging and affects the efficiency of the HHG at high repetition rates. The experimental design already included active cooling of the fiber mount and a fluorine-doped cladding structure to direct stray light away from the required gas seals. However, ionization of the gas in the interaction zone caused significant heating of the gas, which reduced particle density, disturbed phase matching, and degraded the sealing rubbers. To address the heat-induced problems, the work proposes two strategies: active cooling of the fiber or a side-slit fiber geometry. To reduce reabsorption, the fiber core diameter can be increased or an axially drilled fiber can be used. All of these strategies have been investigated in gas flow, phase-matching, or temperature-based simulations and shown to be potentially promising. With existing fiber laser systems capable of delivering more than 1 kW of average power with mJ and fs pulses, this work represents an important step toward the generation of higher power from waveguide-based HHG sources

Rivard, Martha oral history interview

Born 1911 in Canada, one of 14 children. Came to Lewiston with parents in 1923. Left school at age 11, and began working in shoe shop at age 15. Married at age 29

Computational Methods for Structural Variation Analysis in Populations

Recent advances in long-read sequencing have given us an unprecedented view of structural variants (SVs). However, much of their role in disease and evolution remains unknown due to a number of technical and biological challenges, including the high error rate of most long-read sequencing data, the additional complexity of aligning around large variants, and biological differences in how the same SV can manifest in different individuals. In this thesis we introduce novel methods for structural variant analysis and demonstrate how they overcome many of these obstacles. First, we apply recent advances in data structures to the substring search problem and show how learned index structures can enable accelerated alignment of genomic reads. Next, we present an optimized SV calling pipeline that integrates improvements to existing software alongside two novel SV-processing methods, Iris and Jasmine, which improve the accuracy of SV breakpoints and sequences in individual samples and compare and integrate SV calls from multiple samples. Finally, we show how the introduction of CHM13, the first gap-free telomere-to-telomere human reference genome, enables for the first time variant calling in over 100 Mbp of newly resolved sequence and mitigates long-standing issues in variant calling that were attributed to gaps, errors, and minor alleles in the prior GRCh38 reference. We demonstrate the broad applicability of our advancements in SV inference by uncovering novel associations with gene expression in 444 human individuals from the 1000 Genomes Project, by detecting SVs in the tomato genome which affect fruit size and yield, and by comparing SVs between tumor and normal cells in organoids derived from the SKBR3 breast cancer cell line

Introduction of electric vehicle charging stations to university campuses : A case study for the university of Georgia from 2014 to 2017

Electric vehicles (EVs) are becoming increasingly popular in the United States of America (USA). EVs attract buyers with benefits including energy efficiency and environmental friendliness. As EV usage grows, more public spaces are installing EV charging stations. This paper presents a comprehensive analysis of EV charging station usage at the University of Georgia (UGA) in Athens, Georgia. Three ChargePoint EV charging stations at UGA were used to collect data about each of 3204 charging events that occurred from 10 April 2014 to 20 June 2017. The charging event data included start date, start time, length of parking time, length of charging time, amount of energy delivered, and the postal code entered by the user during ChargePoint account registration. Analytical methods were proposed to obtain information about EV charging behavior, charging station occupancy, and geolocation of charging station users. The methodology presented here was time- and cost-effective, as well as scalable to other organizations that own charging stations. Because this study took place at a university, the results presented here can be used as a reference for EV charging station usage in other college towns in the USA that do not have EV charging stations but are planning to develop EV infrastructure

Label‑free multiphoton microscopy enables histopathological assessment of colorectal liver metastases and supports automated classifcation of neoplastic tissue

As the state of resection margins is an important prognostic factor after extirpation of colorectal liver metastases, surgeons aim to obtain negative margins, sometimes elaborated by resections of the positive resection plane after intraoperative frozen sections. However, this is time consuming and results sometimes remain unclear during surgery. Label-free multimodal multiphoton microscopy (MPM) is an optical technique that retrieves morpho-chemical information avoiding all staining and that can potentially be performed in real-time. Here, we investigated colorectal liver metastases and hepatic tissue using a combination of three endogenous nonlinear signals, namely: coherent anti-Stokes Raman scattering (CARS) to visualize lipids, two-photon excited fluorescence (TPEF) to visualize cellular patterns, and second harmonic generation (SHG) to visualize collagen fibers. We acquired and analyzed over forty thousand MPM images of metastatic and normal liver tissue of 106 patients. The morphological information with biochemical specificity produced by MPM allowed discriminating normal liver from metastatic tissue and discerning the tumor borders on cryosections as well as formalin-fixed bulk tissue. Furthermore, automated tissue type classification with a correct rate close to 95% was possible using a simple approach based on discriminant analysis of texture parameters. Therefore, MPM has the potential to increase the precision of resection margins in hepatic surgery of metastases without prolonging surgical intervention

CCTC final report: care leavers' transitions to adulthood in the context of COVID-19

The Care Leavers, COVID-19 and Transitions from Care (CCTC) study was funded by the Economic and Social Research Council (ESRC), as part of UK Research and Innovation’s rapid response to COVID-19 (ES/V016245/1). The research explored care leavers’ experience of the pandemic. Analysis of local authority management information system data on over 1300 young people from 10 local authorities and over 60 interviews with young people and professionals informed the study. As part of the study care experienced adults, leaving care workers and operational managers came together to form a Networked Learning Community (NLC). Over a series of sessions the NLC supported the research team to interpret the findings, develop recommendations and tools for practic

CCTC final report: care leavers' transitions to adulthood in the context of COVID-19

The Care Leavers, COVID-19 and Transitions from Care (CCTC) study was funded by the Economic and Social Research Council (ESRC), as part of UK Research and Innovation’s rapid response to COVID-19 (ES/V016245/1). The research explored care leavers’ experience of the pandemic. Analysis of local authority management information system data on over 1300 young people from 10 local authorities and over 60 interviews with young people and professionals informed the study. As part of the study care experienced adults, leaving care workers and operational managers came together to form a Networked Learning Community (NLC). Over a series of sessions the NLC supported the research team to interpret the findings, develop recommendations and tools for practic