3, 2, 1 … Discovering Newton’s Laws

“For every action there is an equal and opposite reaction.” “Except when a bug hits your car window, the car must exert more force on the bug because Newton’s laws only apply in the physics classroom, right?” Students in our classrooms were able to pick out definitions as well as examples of Newton’s three laws; they could recite the laws and even solve for force, mass, and acceleration. However, when given “real world” questions, they would quickly revert to naive explanations. This frustration led to an examination of our approach to teaching Newton’s laws. Like many, we taught Newton’s laws in their numerical order—first, second, and then third. Students read about the laws, copied definitions, and became proficient with vocabulary before they applied the laws in a lab setting. This paper discusses how we transformed our teaching of Newton’s laws by flipping the order (3, 2, 1) and putting the activity before concept, as well as how these changes affected student outcomes

2005 Ruby Yearbook

A digitized copy of the 2005 Ruby, the Ursinus College yearbook.https://digitalcommons.ursinus.edu/ruby/1108/thumbnail.jp

2004 Ruby Yearbook

A digitized copy of the 2004 Ruby, the Ursinus College yearbook.https://digitalcommons.ursinus.edu/ruby/1107/thumbnail.jp

Bioflavoring by non-conventional yeasts in sequential beer fermentations

Non-conventional yeast species have great capacity for producing diverse flavor profiles in production of alcoholic beverages, but their potential for beer brewing, in particular in consecutive fermentations with Saccharomyces cerevisiae, has only poorly been explored. We have screened 17 non-conventional yeast species for production of an appealing profile of flavor esters and phenolics in the first phase of alcoholic fermentation, followed by inoculation with S.\ua0cerevisiae to complete the fermentation. For measurement of phenolic compoundsand their precursors we developed an improved and highly sensitive methodology. The results show that non-conventional yeast species possess promising potential for enhancement of desirable flavors in beer production. Notable examples are increasing isoamyl acetate (fruity, banana flavor) by application of P.\ua0kluyverii, augmenting ethyl phenolic compounds (spicy notes) with Brettanomycesspecies and enhancing 4-vinyl guaiacol (clove-like aroma) with T.\ua0delbrueckii. All Pichia strains also produced high levels of ethyl acetate (solvent-like flavor). This might be selectively counteracted by selection of an appropriate S.\ua0cerevisiae strain for the second fermentation phase, which lowers total ester profile. Hence, optimization of the process conditions and/or proper strain selection in sequentially inoculated fermentations are required to unlock the full potential for aroma improvement by the non-conventional yeast species

A comparison of welfare outcomes for weaner and mature Bos indicus bulls surgically or tension band castrated with or without analgesia: 1. Behavioural responses

Tension-band castration of cattle is gaining favour because it is relatively simple to perform and is promoted by retailers of the devices as a humane castration method. Furthermore, retailers encourage delaying castration to exploit the superior growth rates of bulls compared with steers. Two experiments were conducted, under tropical conditions, comparing tension banding and surgical castration of weaner (7-10 months old) and mature (22-25 months old) Bos indicus bulls with and without pain management (ketoprofen or saline injected intramuscularly immediately prior to castration). Welfare outcomes were assessed using a wide range of measures; this paper reports on the behavioural responses of the bulls and an accompanying paper reports on other measures. Behavioural data were collected at intervals by direct observation and continuously via data loggers on the hind leg of the bulls to 4 weeks post-castration. Tension-banded bulls performed less movement in the crush/chute than the surgically castrated bulls during the procedures (weaner: 2.63 vs. 5.69,

The Telehealth Enhancement of Adherence to Medication (TEAM) in pediatric IBD trial: Design and methodology

Medication nonadherence is a significant health care issue requiring regular behavioral treatment. Lack of sufficient health care resources and patient/family time commitment for weekly treatment are primary barriers to receiving appropriate self-management support. We describe the methodology of the Telehealth Enhancement of Adherence to Medication (TEAM) trial for medication nonadherence in pediatric inflammatory bowel disease (IBD). For this trial, participants 11–18 years of age will be recruited from seven pediatric hospitals and will complete an initial 4-week run in to assess adherence to a daily medication. Those who take less than 90% of their prescribed medication will be randomized. A total of 194 patients with IBD will be randomized to either a telehealth behavioral treatment (TBT) arm or education only (EO) arm. All treatment will be delivered via telehealth video conferencing. Patients will be assessed at baseline, post-treatment, 3-, 6-, and 12-months. We anticipate that participants in the TBT arm will demonstrate a statistically significant improvement at post-treatment and 3-, 6-, and 12-month follow-up compared to participants in the EO arm for both medication adherence and secondary outcomes (i.e., disease severity, patient quality of life, and health care utilization). If efficacious, the TEAM intervention could be disseminated broadly and reduce health care access barriers so that patients could receive much needed self-management intervention

Multiomics Longitudinal Modeling of Preeclamptic Pregnancies

Preeclampsia is a complex disease of pregnancy whose physiopathology remains unclear and that poses a threat to both mothers and infants. Specific complex changes in women\u27s physiology precede a diagnosis of preeclampsia. Understanding multiple aspects of such a complex changes at different levels of biology, can be enabled by simultaneous application of multiple assays. We developed prediction models for preeclampsia risk by analyzing six omics datasets from a longitudinal cohort of pregnant women. A machine learning-based multiomics model had high accuracy (area under the receiver operating characteristics curve (AUC) of 0.94, 95% confidence intervals (CI):[0.90, 0.99]). A prediction model using only ten urine metabolites provided an accuracy of the whole metabolomic dataset and was validated using an independent cohort of 16 women (AUC= 0.87, 95% CI:[0.76, 0.99]). Integration with clinical variables further improved prediction accuracy of the urine metabolome model (AUC= 0.90, 95% CI:[0.80, 0.99], urine metabolome, validated). We identified several biological pathways to be associated with preeclampsia. The findings derived from models were integrated with immune system cytometry data, confirming known physiological alterations associated with preeclampsia and suggesting novel associations between the immune and proteomic dynamics. While further validation in larger populations is necessary, these encouraging results will serve as a basis for a simple, early diagnostic test for preeclampsia

14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon

Chemistry and materials science are complex. Recently, there have been great successes in addressing this complexity using data-driven or computational techniques. Yet, the necessity of input structured in very specific forms and the fact that there is an ever-growing number of tools creates usability and accessibility challenges. Coupled with the reality that much data in these disciplines is unstructured, the effectiveness of these tools is limited. Motivated by recent works that indicated that large language models (LLMs) might help address some of these issues, we organized a hackathon event on the applications of LLMs in chemistry, materials science, and beyond. This article chronicles the projects built as part of this hackathon. Participants employed LLMs for various applications, including predicting properties of molecules and materials, designing novel interfaces for tools, extracting knowledge from unstructured data, and developing new educational applications. The diverse topics and the fact that working prototypes could be generated in less than two days highlight that LLMs will profoundly impact the future of our fields. The rich collection of ideas and projects also indicates that the applications of LLMs are not limited to materials science and chemistry but offer potential benefits to a wide range of scientific disciplines

Towards an Embodied Sociology of War

While sociology has historically not been a good interlocutor of war, this paper argues that the body has always known war, and that it is to the corporeal that we can turn in an attempt to develop a language to better speak of its myriad violences and its socially generative force. It argues that war is a crucible of social change that is prosecuted, lived and reproduced via the occupation and transformation of myriad bodies in numerous ways from exhilaration to mutilation. War and militarism need to be traced and analysed in terms of their fundamental, diverse and often brutal modes of embodied experience and apprehension. This paper thus invites sociology to extend its imaginative horizon to rethink the crucial and enduring social institution of war as a broad array of fundamentally embodied experiences, practices and regimes