Employers perceive students are not qualified to enter the workforce. Students also feel unprepared to enter the workforce, resulting in a perceived skills gap between skills taught in schools and skills demanded by employers. My study examines the actual skills gap between skills taught in five Information Systems programs and skills demanded by employers in nine IT professions. In the scope of my analysis, I provide a discussion of my project methodology, answers for my research questions used to complete the gap analysis, and grounded recommendations to Information Systems programs on how to close the skills gap. Lastly, I also include future considerations that researchers may utilize to study my topic in greater detail. Students and schools can both use my analysis to improve their respective weaknesses and capitalize on their strengths in terms of hard skills required for the workforce.

The Star Planet Activity Research CubeSat (SPARCS) will be a 6U CubeSat devoted to photometric monitoring of M dwarfs in the far-ultraviolet (FUV) and near-ultraviolet (NUV) (160 and 280 nm respectively), measuring the time-dependent spectral slope, intensity and evolution of M dwarf stellar UV radiation. The delta-doped detectors baselined for SPARCS have demonstrated more than five times the in-band quantum efficiency of the detectors of GALEX. Given that red:UV photon emission from cool, low-mass stars can be million:one, UV observation of thes stars are susceptible to red light contamination. In addition to the high efficiency delta-doped detectors, SPARCS will include red-rejection filters to help minimize red leak. Even so, careful red-rejection and photometric calibration is needed. As was done for GALEX, white dwarfs are used for photometric calibration in the UV. We find that the use of white dwarfs to calibrate the observations of red stars leads to significant errors in the reported flux, due to the differences in white dwarf and red dwarf spectra. Here we discuss the planned SPARCS calibration model and the color correction, and demonstrate the importance of this correction when recording UV measurements of M stars taken by SPARCS.

Though schizophrenia was categorized as a mental illness over 100 years ago, there is a plethora of knowledge that continues to perplex the scientific and medical community alike. This tragic mental disorder affects approximately 1% of the general population, and many of these individuals are homeless if left untreated. Each schizophrenia patient has a different set of symptoms, so all of these patients experience a variety of positive and negative symptoms. Negative symptoms are called so as they are in absence, and some examples include apathy, anhedonia, lack of motivation, reduced social drive, and reduced cognitive functioning. Positive behavior, on the other hand, is a change in behavior or thoughts such as visual or auditory hallucinations, delusions, confused thoughts, disorganized speech, and trouble concentrating. Because schizophrenia patients do not share the exact same set of symptoms, research in schizophrenia requires a tremendous amount of medical resources. Over the last few years, new studies have started in the field of schizophrenia involving proteomics, or the study of proteins and their function. This new frontier gives doctors and scientists alike a new opportunity to improve the quality of life of schizophrenia patients by providing a potential method through which patients would receive individualized treatment based on their specific symptoms.