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... Poster presentation link: https://docs.google.com/presentation/d/1ukISXtK25OS7x6FbwrVYal8rKn3LdVr0Uhy77umRYjg/edit?usp=sharing Intelligent interfaces (AI-driven interfaces) are a promising step for interface designing. These interfaces use intelligent machine learning AI that use user models and interactions provided by the user to accurately design an interface towards the users liking. There are risks and benefits behind these interfaces so its not the best option to choose now. Everything within interface design must be considered such as age, intellect, culture, skill, health, emotional status, and mental status to understand and connect properly with the user. Improvements in Computer Interfaces and User Experiences By Ryan Geissinger CS485:01 Comp Sci ResearchElainea Neville What makes a great user-focused interface? Understand human-to-computer interactions and human-to-human interactions. With the knowledge behind what a user does and anticipate what the user will do next (through AI) is what can help better interface design. Usability is one of the important parts Build newer designs off self-learning of creating a great interface. The interface will have to analyze a users needs and gather data taken from actions performed on the interface. Good feedback is another important part since it reflects to the user what they are doing. When an interface gives a response to feedback, itll give an approach (how to do a task), give motivation (encourage completion of the task), and create a connection with the user. systems and use the design structures for future designs. To achieve better functioning designs, the system of the interface will have to be interacted so many times, actions will have to be expressed thoroughly, and updates on the system will have to happen regularly.  ...

... A Molecular Dynamics Investigation of Ternary Phase Diagrams Names: William M. Ames, Benjamin Cunningham Department of Chemistry and Biochemistry, Juniata College. Introduction Discussion Conclusion and Future Work Determining the efficacy of molecular dynamics simulations holds promise for physical chemistry and for confirming the reliability of specific softwares in computational chemistry. (1) Prior work from Pivirotto and Harijanto at Juniata has shown that molecular-dynamics CHARMM36 force field results work well in providing qualitative results for virtual titrations that can be plotted on a ternary phase diagram and compared realistically with real lab titrations. Similarly, this work focuses on comparing CHARMM-GUI and GROMACS-made, virtual simulations with each other and with a set of real lab titrations in terms of each methods qualitative and quantitative results, giving glimpses into how well computer systems represent mixtures of miscible and immiscible compounds. CHARMM force field simulations have recognition among biological chemists as a tool for modeling proteins, fats, and other macromolecules in different solvents. This research expands from previous investigations to see if the CHARMM-GUI and/or GROMACS-based simulations are feasible. CHARMM-GUI seems to give micro-molecules results consistent with laboratory results. GROMACS tends to produce qualitative results when plotting the data from its production runs on a ternary phase diagram. This may be because the random-insertion method used to build the files used in the GROMACS simulations spaced the molecules in the virtual box unrealistically. Alternatively, the equilibration step involved in preparing the virtual boxes should have allowed the molecules simulated to coalesce in their proper phases but could also have trapped molecules arbitrarily throughout the box. GROMACS is a powerful tool that allows individuals to simulate various molecular interactions of immense scopes; its utility should not be doubted. Despite this, the accuracy of its simulations for these investigations varies between productions. GROMACS functions well with the accessible, online platform, CHARMM-GUI. CHARMM-GUI, requires less work to learn and operate than native GROMACS commands. Our results indicate that CHARMM force field molecular simulations do not consistently allow researchers to distinguish phases within those boxes based on the densities of the molecules involved; it can only serve as a qualitative basis for judging the miscibility of micro-molecules in solution. Though lab methods are imperfect, they continue to produce the data necessary to plot ternary-phase diagrams desirable for research. Mass Percent Data Figure 2: Water-- 44.23 Figure 3: Water-- 8.00 Figure 4: Water-- 37.14 Methods Heptane-- 16.73 1-Propanol-- 39.04 Heptane-- 70.30 1-Propanol-- 12.70 Heptane-- 16.64 1-Propanol-- 46.21 Solutions for the lab titrations On an analytical balance Weighed beaker, DI water massed; organic layer massed added stir-bar, covered with punctured parafilm Titrated with 1-propanol titrant into water/alkane mixture or water into alkane/1-propanol mixture Incrementally measured titrant used at approximately 1-5 ml intervals based on turbidity duration remained before reaching equivalence point. GROMACS files produced through gmx commands Generated *CRD, * PSF, and *PDB files for hexane, 1-propanol, and water on the CHARMM-GUI In GROMACS, minimized, equilibrated, and ran production runs with *.tpr files. Simulations were for 10 ns, 2 fs time step, at 300 K and 1 bar, with Nose-Hoover thermostat and Parrinello-Raham barostat Figure 2: Density of three phases throughout 50 slices--heterogenous simulation Future work could cater to the utilization of native, GROMACS commands over the CHARMM-GUI. Additionally, the simulations could run longer (100+ ns) to give the system more time to arrange molecules as accurately as possible. Also, the method of randomly inserting the molecules into the files used for the simulations could take a layered approach instead. An extension of the work here could use larger and smaller molecules in the organic and aqueous layers, and different titrants could be used, too. Lastly, the data could be analyzed differently; instead of considering the data across the whole simulation time, it could be gathered from only the last few nanoseconds of a simulation. Figure 3: Density of three phases throughout 50 slices--simulation with two developing phases Figure 4: Density of three phases throughout 50 slices--generally homogeneous simulation References Figure 5: Ternary Phase diagram of lab-produced miscibility of hexane in water with 1-propanol as a solvent 1) Brooks, B. R., et al. CHARMM: The Biomolecular Simulation Program. Journal of Computational Chemistry, vol. 30, no. 10, July 2009, pp. 1545614. DOI.org (Crossref), https://doi.org/10.1002/jcc.21287. Figure 1: Ternary Phase diagram of GROMACS simulated miscibility of hexane in water with 1-propanol as a solvent  ...

... Investigation of a Series of N-oxide Schiff-base Ligands Derived from 2-Pyridinecarboxaldehyde N-oxide and 1,2-Phenylenediamine, and Their Respective Metal Complexes Michael Delosh and Dr. Peter Baran Department of Chemistry and Biochemistry, Juniata College, Huntingdon, PA 16652, USA Background: Synthetic Pathways & Results: Organic ligands containing Schiff-base functionality have been of particular interest in coordination chemical studies. NH H 2N Industrial Catalysis Organic Chemical Transformations1 Biological Therapeutics Antibiotic, Anti-inflammatory, Antitumor Properties2 Photochemical Technology Development of OLED Displays3 Chemical Analysis Anion Receptors4 2-Pyridinecarboxaldehyde N-oxide OH N HO N O Salphen (Classical Tetradentate Schiff-base Ligand) N MeOH reflux O N MeOH N NH2 0.5 eq. Na2SO4 O N N N O N O O N Conclusions & Project Outlook: Poxpam Poxbim O MeOH reflux N2 Atmosphere Copper(II) Complex of Poxphen Cu(NO3)23H2O 20 C MeOH Cu(NO3)23H2O Methods & Results: MeOH 20 C O N Ar Atmosphere O O HN N Cu N O N NH REALITY O N O O EXPECTATION The following map outlines the series of synthetic pathways conducted to form various N-oxide Schiff-base ligands and coordination complexes: Reactions with dark blue reaction arrows represent a repetition of results obtained by previous students in our research group. Reactions with red reaction arrows yield theoretical products that were expected to result from specific transformations. Reactions with light blue reaction arrows represent the experimental products obtained in contrast to the theoretical products. Violet arrows from certain species point toward their corresponding structures determined by X-ray crystallography. Reagents, solvents, and conditions are listed near their respective reaction arrows. Certain reactions were conducted in inert atmospheres. All reported syntheses were conducted in air unless otherwise specified. All products obtained were characterized by X-ray crystallography, infrared spectroscopy, and melting point analysis (where applicable). Although the monomer of the tetradentate N-oxide analogue of salphen cannot be isolated, its dimer is synthesized through a carbon-carbon bond-forming reaction. Despite the inability to synthesize a copper(II) coordination complex with the tridentate poxpam ligand, a polymeric complex can be formed through formation of a different tridentate ligand in situ with bridging and chelating capabilities. Future endeavors could include further examining the formation of the carbon-carbon bond of the poxphen dimer, synthesizing complexes of the poxphen dimer, and exploring the synthesis and physicochemical properties of the newlyobtained polymeric complex with the novel tridentate ligand. EXPECTATION O O Poxphen Dimer (C-C BOND FORMATION) reflux Cu O O N NaOH N N O HN O N HN N N O MeOH 20 C Poxphen (N-oxide Analogue of Salphen) O N reflux Cu(NO3)23H2O O N Although inspired by salphen-type ligands, all ligands in the study are distinguished by their N-oxide functionality. Not much is known about the structures and properties of N-oxide Schiff-base ligands compared to the extensive research done on their phenolate counterparts. 1,2-Phenylenediamine MeOH O N N NH2 NaOH O N N O N O REALITY N O The ligands in this study take inspiration from tetradentate salphentype Schiff-base ligands, the complexes of which have applications in: N O N N N O O N N Poxphen (Cannot Isolate) O Acknowledgements: This project could not have been undertaken without the gracious assistance of Juniata College for the use of their research facilities, and for Dr. Milan Gembicky of the University of California San Diego for conducting X-ray crystallographic analyses. 2:1 Poxbim:Copper(II) Complex References: H 3C O O O N N O N N N N O N O O Cu N N O N NH2 O N O O N O N O N H 3C 1-Dimensional Polymeric Copper(II) Complex Formed through Chelation and Bridging O O N O O Cu O N O Cu N O O N Cu H 3C N O Copper(II) Complex of Poxpam (Cannot Isolate) (1) Jacobsen, E. N.; Zhang, W.; Muci, A. R.; Ecker, J. R.; Deng, L. Highly Enantioselective Epoxidation Catalysts Derived from 1,2Diaminocyclohexane. J. Am. Chem. Soc. 1991, 113 (18), 70637064. https://doi.org/10.1021/ja00018a068. (2) Hussain, A.; AlAjmi, M. F.; Rehman, M. T.; Amir, S.; Husain, F. M.; Alsalme, A.; Siddiqui, M. A.; AlKhedhairy, A. A.; Khan, R. A. Copper(II) Complexes as Potential Anticancer and Nonsteroidal AntiInflammatory Agents: In Vitro and in Vivo Studies. Scientific Reports 2019, 9 (1), 5237. https://doi.org/10.1038/s41598-019-41063-x. (3) Whiteoak, C. J.; Salassa, G.; Kleij, A. W. Recent Advances with -Conjugated Salen Systems. Chem. Soc. Rev. 2012, 41 (2), 622631. https://doi.org/10.1039/C1CS15170C. o (4) Cort, A. D.; Bernardin, P. D.; Forte, G.; Mihan, F. Y. Metal Salophen-Based Receptors for Anions. Chem. Soc. Rev. 2010, 39 (10), 38633874. https://doi.org/10.1039/B926222A.  ...

... Julian Jackson, Juniata College Conclusions Introduction The Advanced Physics Lab (PC 307) is one of the most important courses someone could take in the physics department. It teaches a lot of great techniques and lessons that will be used in the real world. Visual Basic, and experience with Excel are critical areas of expertise and will certainly land a job having any experience with this kind of software. Another great part about this course is an independent project. This project allows creativity to come alive. The software known as Autodesk Inventor made it possible to create anything imaginable. Being a mechanical engineer, this would be great to have experience with. Designing, and building anything one could possibly need. Materials Methods Autodesk Inventor is a software used to design and create pieces of the Rube Goldberg machine. PrusaSlicer is a software used that imports files from Inventor, into Prusa, Prusa then prints said files with varying PLA filaments. Assemble each part in a way that it can execute its assignment or make the next event in the chain reaction to occur. Attach magnetic strips along the faces of each piece will allow the prints to stay along that metal wall. After each step in the process occurs, it will end with turning on a very pretty neon light. Autodesk Inventor Software PrusaSlicer Software Original Prusa i3 MK3 3D Printer Neon Mood Light Magnetic Tape with Adhesives Metal wall PLA Filament This has been a great experience overall and will help all people who dream of being engineers. Obtaining a skill with software like this is so crucial with engineering and everyone should have the experience of learning how to 3D print. The final product, will have a lot of pieces working together for a small task of just turning on a neon sign. Results Literature cited Autodesk Inventor was used to design pieces for a Rube Goldberg project. Each print executes a different assignment. When it came to magnetizing each piece, magnetic strips was placed along a surface on piece in order to stick to the wall. Pieces are still being printed and will continue to grow in steps of the chain reaction. A marble has fallen onto a switch turning on a neon sign. Swartz, By Clay. How to Make a Rube Goldberg Machine. Scout Life Magazine, 4 Feb. 2022, scoutlife.org/hobbiesprojects/projects/159359/how-to-make-arube-goldberg-machine. Acknowledgments Must give thanks Dr. Mark Pearson for everything he did this semester. Also, a special thanks to Dr. Matt Beaky, for his help throughout this whole process. Further information Email: jacksjx19@juniata.edu Phone: 717-437-7282  ...

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... Going Nutty: Walnut Consumption Effects on Gut Microbiota and Cardiovascular Health Jillian Leister1,2, Mansi Chandra1,2, Alyssa M Tindall3, Christopher J McLimans2, Kristina S Petersen3, Penny M Kris-Etherton3, and Regina Lamendella1,2 1 Juniata College Biology Department, 2Wright Labs LLC, 3Department of Nutritional Sciences, The Pennsylvania State University Introduction Background An organisms gut microbiome has observable impact on its life history traits Microbes present within the gut are involved in extraction and metabolism of nutrients not fully digested in the small intestine1 Cardiovascular disease (CVD) is a leading cause of mortality globally and is highly impacted by diet1 Experimental Design Results (cont.) 1. Sample preparation Controlled-feeding study with 2-wk run-in on SWD followed by three 6-wk diet periods Fecal sample collection Store samples at -80C until extraction. 2. RNA extraction & Library preparation Extract RNA PCR amplification of V4 region of 16S rRNA Library preparation and dual index barcoding Assess quality of library and purify FIGURE 4. The average relative abundance of bacterial phyla in WD, WFMD and ORAD diets in individuals with increased CVD risk factors. Synthesize cDNA Figure 1. Etiology of cardiovascular risk in obesity due to microbiota shift2 Sequencing and Analysis The WD, WFMD and the ORAD diet showed enrichment of certain species of bacteria in the gut microbiome which play an important role in altering the gut environment. Walnuts contain ellagitannins which are metabolized by the bacteria to produce substances that provide cardiovascular benefits 5 These diets led to enrichment of bacterial species with positive effects on the gut epithelium, gut lining, and cardiovascular risk factors 6,7 Demonstrates that walnut consumption can alter the gut microbiota in a way that provides cardiovascular benefits and a stable gut environment. Results Metatranscriptomics is a method where functional genes and pathways are identified by isolating the mRNA of an organism Metabolizable energy from walnuts is overestimated by 21%, suggesting that walnut-derived nutrients are accessible to the gut microbiota3,4 Objectives 1. Analyze the effects on the gut microbiome of three different study diets: 1 containing walnuts and 2 containing different vegetable oil blends 2. Investigate how changes in the gut microbiome are related to CVD risk factors 3. Examine the chemical pathways being utilized and the subsequent impact on cardiovascular health Discussion Future Directions Acknowledgements Metatranscriptomic Analysis Gain a better understanding of what genes are turned on, rather than those that could be In-depth knowledge about which metabolic pathways are affected and altering the gut environment. References 1. 2. Figure 2. Relative abundance of the most prominent bacteria phyla in participants with overweight, obesity, and morbid obesity (n=42) FIGURE 3. Comparisons of enriched bacteria between walnut diet, walnut fatty acid matched diet, oleic acid replaces linolenic acid diet and the run-in diet in adults at increased cardiovascular risk (n=42) 3. 4. 5. 6. 7. David LA, Maurice CF, Carmody RN, Gootenberg DB, Button JE,Wolfe BE, Ling AV, Devlin AS, Varma Y, Fischbach MA, et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature 2014;505: 55963. Kasselman LJ, Vernice NA, DeLeon J, Reiss AB. The gut microbiome and elevated cardiovascular risk in obesity and autoimmunity. Atherosclerosis 2018;271: 203-213. Rajaram S. Health benefits of plant-derived -linolenic acid. Am J Clin Nutr 2014;100:443S8S. West SG, Krick AL, Klein LC, Zhao G, Wojtowicz TF, McGuiness M, Bagshaw DM, Wagner P, Ceballos RM, Holub BJ, et al. Effects of diets high in walnuts and flax oil on hemodynamic responses to stress and vascular endothelial function. J Am Coll Nutr 2010;29: 595603. Selma M V, Beltran D, Garca-Villalba R, Espin JC, Tomas-Barberan FA. Description of urolithin production capacity from ellagic acid of two human intestinal Gordonibacter species. Food Funct 2014;5: 177984. Chiang JYL. Bile acid metabolism and signaling. Compr Physiol 2013;3:1191. Ajouz H, Mukherji D, Shamseddine A. Secondary bile acids: an underrecognized cause of colon cancer. World J Surg Oncol 2014;12:164. Liberal Arts Symposium 2021  ...