Interior Materials and Applications: A Hands-On Project with First Presbyterian Church

Experiential learning is the philosophical term behind the idea of immersing oneself in a subject in order to learn. Aristotle wrote, "for the things we have to learn before we can do them, we learn by doing them". Being hands-on is especially important in the classroom because it allows students to engage in kinesthetic learning. 'Doing' helps them to gain a better understanding of the material. It allows students to experiment with trial and error, learn from their mistakes, and understand the potential gaps between theory and practice. It also provides educators with a unique opportunity to enrich the minds of their students in new and engaging ways. This project seeks to afford freshman design students the hands-on training, knowledge, skills and competencies needed in the workplace as they pursue their degree. In the spring 2022 approximately 50 freshman students from the IDES 115 Interior Materials and Applications, Sections 1 and 2 (a required course in the Interior Design major), taught by PI Alfaro and Co-PI Son, will align with a community partner, First Presbyterian Church of Muncie, to specify appropriate materials for a future youth room in their church, learn from qualified consultant’s appropriate application techniques, and then apply what they learn to actually refinish the space for the community partner. Students, using hands-on techniques, will gain an understanding of current materials and construction practices, and explore innovation in material application with guidance from guest consultants. The project addresses the production of specifications and schedules, cost analysis, project management, and applicable building codes

Applying Machine Learning to Neutron-Gamma Ray Discrimination from Scintillator Readout Using Wavelength Shifting Fibers

Advances in machine learning have found wide applications including radiation detection. In this work, machine learning is applied to neutron-gamma ray discrimination of an organic liquid scintillator (OLS) readout using wavelength shifting (WLS) fibers. The objective of using WLS fiber is to enable the transfer of the light signal from the scintillation medium, with almost any active volume geometry, to a low-profile photomultiplier. This is a common practice in high-energy physics research and has proven to be very effective for such applications. The drawback of this approach is the light pulses carried to the photomultiplier through the WLS fibers do not perfectly replicate the original OLS light pulses’ intensities or timing. This drawback causes traditional pulse shape discrimination algorithms applied to the degraded light pulses to fail to discriminate between neutron and gamma ray events. However, differences in the degraded light pulses for neutrons and gamma rays still exist and various machine learning algorithms can be applied to identify these differences. An experimental system was constructed to simultaneously capture part of the scintillation medium signal and the corresponding signal through the WLS fibers. Using the known neutron-gamma ray discrimination characteristics directly measured in the scintillation medium to provide the ground truth, supervised machine learning algorithms were applied to the corresponding light pulses carried to the photomultiplier through the WLS fibers. The results indicate that this approach will enable enhanced recovery of neutron-gamma ray discrimination information. This research effort will focus on two aspects of the OLS-WLS system: 1) developing an experimental system to create machine learning training data and 2) applying and evaluating various machine learning algorithms

Primordial Nucleosynthesis with CMB Inputs: Probing the Early Universe and Light Element Astrophysics

Cosmic microwave background (CMB) determinations of the baryon-to-photon ratio $\eta \propto \Omega_{\rm baryon} h^2$ will remove the last free parameter from (standard) big bang nucleosynthesis (BBN) calculations. This will make BBN a much sharper probe of early universe physics, for example, greatly refining the BBN measurement of the effective number of light neutrino species, $N_{\nu,eff}$. We show how the CMB can improve this limit, given current light element data. Moreover, it will become possible to constrain $N_{\nu,eff}$ independent of \he4, by using other elements, notably deuterium; this will allow for sharper limits and tests of systematics. For example, a 3% measurement of $\eta$, together with a 10% (3%) measurement of primordial D/H, can measure $N_{\nu,eff}$ to a 95% confidence level of \sigma_{95%}(N_\nu) = 1.8 (1.0) if $\eta \sim 6.0\times 10^{-10}$. If instead, one adopts the standard model value $N_{\nu,eff}=3$, then one can use $\eta$ (and its uncertainty) from the CMB to make accurate predictions for the primordial abundances. These determinations can in turn become key inputs in the nucleosynthesis history (chemical evolution) of galaxies thereby placing constraints on such models.Comment: 17 pages, 13 figures, plain LaTe

Structure-based discovery of opioid analgesics with reduced side effects

Morphine is an alkaloid from the opium poppy used to treat pain. The potentially lethal side effects of morphine and related opioids—which include fatal respiratory depression—are thought to be mediated by μ-opioid-receptor (μOR) signalling through the β-arrestin pathway or by actions at other receptors. Conversely, G-protein μOR signalling is thought to confer analgesia. Here we computationally dock over 3 million molecules against the μOR structure and identify new scaffolds unrelated to known opioids. Structure-based optimization yields PZM21—a potent Gi activator with exceptional selectivity for μOR and minimal β-arrestin-2 recruitment. Unlike morphine, PZM21 is more efficacious for the affective component of analgesia versus the reflexive component and is devoid of both respiratory depression and morphine-like reinforcing activity in mice at equi-analgesic doses. PZM21 thus serves as both a probe to disentangle μOR signalling and a therapeutic lead that is devoid of many of the side effects of current opioids

von der Transaktion zur Beziehung. Crossing Borders

StudieDie Swiss CRM Studie 2014 befasst sich mit dem Schwerpunktthema kooperatives CRM. Auch dieses Jahr umfasst die Studie den Status Quo sowie die Trends des CRM in der Schweiz

Introducing v0.5 of the AI Safety Benchmark from MLCommons

This paper introduces v0.5 of the AI Safety Benchmark, which has been created by the MLCommons AI Safety Working Group. The AI Safety Benchmark has been designed to assess the safety risks of AI systems that use chat-tuned language models. We introduce a principled approach to specifying and constructing the benchmark, which for v0.5 covers only a single use case (an adult chatting to a general-purpose assistant in English), and a limited set of personas (i.e., typical users, malicious users, and vulnerable users). We created a new taxonomy of 13 hazard categories, of which 7 have tests in the v0.5 benchmark. We plan to release version 1.0 of the AI Safety Benchmark by the end of 2024. The v1.0 benchmark will provide meaningful insights into the safety of AI systems. However, the v0.5 benchmark should not be used to assess the safety of AI systems. We have sought to fully document the limitations, flaws, and challenges of v0.5. This release of v0.5 of the AI Safety Benchmark includes (1) a principled approach to specifying and constructing the benchmark, which comprises use cases, types of systems under test (SUTs), language and context, personas, tests, and test items; (2) a taxonomy of 13 hazard categories with definitions and subcategories; (3) tests for seven of the hazard categories, each comprising a unique set of test items, i.e., prompts. There are 43,090 test items in total, which we created with templates; (4) a grading system for AI systems against the benchmark; (5) an openly available platform, and downloadable tool, called ModelBench that can be used to evaluate the safety of AI systems on the benchmark; (6) an example evaluation report which benchmarks the performance of over a dozen openly available chat-tuned language models; (7) a test specification for the benchmark

The Incidence of AIDS-Defining Illnesses at a Current CD4 Count ≥200 Cells/µL in the Post-Combination Antiretroviral Therapy Era

The incidence of AIDS was higher in patients with a current CD4 count of 500-749 cells/µL compared to 750-999 cells/µL, but did not decrease further at higher CD4 levels. Results were similar in those virologically suppressed on combination antiretroviral therapy, suggesting immune reconstitution is incomplete until CD4 >750/µ

Updated Nucleosynthesis Constraints on Unstable Relic Particles

We revisit the upper limits on the abundance of unstable massive relic particles provided by the success of Big-Bang Nucleosynthesis calculations. We use the cosmic microwave background data to constrain the baryon-to-photon ratio, and incorporate an extensively updated compilation of cross sections into a new calculation of the network of reactions induced by electromagnetic showers that create and destroy the light elements deuterium, he3, he4, li6 and li7. We derive analytic approximations that complement and check the full numerical calculations. Considerations of the abundances of he4 and li6 exclude exceptional regions of parameter space that would otherwise have been permitted by deuterium alone. We illustrate our results by applying them to massive gravitinos. If they weigh ~100 GeV, their primordial abundance should have been below about 10^{-13} of the total entropy. This would imply an upper limit on the reheating temperature of a few times 10^7 GeV, which could be a potential difficulty for some models of inflation. We discuss possible ways of evading this problem.Comment: 40 pages LaTeX, 18 eps figure

Evolution of structural, mechanical and tribological properties of Ni-P/MWCNT coatings as a function of annealing temperature

Collaborative research project Hardalt (Grant No. 606110) funded by the EU's seventh framework programme