Accelerating 3D printing of pharmaceutical products using machine learning

[Abstract] Three-dimensional printing (3DP) has seen growing interest within the healthcare industry for its ability to fabricate personalized medicines and medical devices. However, it may be burdened by the lengthy empirical process of formulation development. Active research in pharmaceutical 3DP has led to a wealth of data that machine learning could utilize to provide predictions of formulation outcomes. A balanced dataset is critical for optimal predictive performance of machine learning (ML) models, but data available from published literature often only include positive results. In this study, in-house and literature-mined data on hot melt extrusion (HME) and fused deposition modeling (FDM) 3DP formulations were combined to give a more balanced dataset of 1594 formulations. The optimized ML models predicted the printability and filament mechanical characteristics with an accuracy of 84%, and predicted HME and FDM processing temperatures with a mean absolute error of 5.5 °C and 8.4 °C, respectively. The performance of these ML models was better than previous iterations with a smaller and a more imbalanced dataset, highlighting the importance of providing a structured and heterogeneous dataset for optimal ML performance. The optimized models were integrated in an updated web-application, M3DISEEN, that provides predictions on filament characteristics, printability, HME and FDM processing temperatures, and drug release profiles (https://m3diseen.com/predictionsFDM/). By simulating the workflow of preparing FDM-printed pharmaceutical products, the web-application expedites the otherwise empirical process of formulation development, facilitating higher pharmaceutical 3DP research throughput

The Faculty Notebook, September 2005

The Faculty Notebook is published periodically by the Office of the Provost at Gettysburg College to bring to the attention of the campus community accomplishments and activities of academic interest. Faculty are encouraged to submit materials for consideration for publication to the Associate Provost for Faculty Development. Copies of this publication are available at the Office of the Provost

Navigating AI in Personnel Selection: A Scenario-based Study on Applicants\u27 Perceptions

AI-based systems are increasingly deployed on organizational tasks, such as personnel selection decisions. As existing research indicates that applicants generally react negatively to the use of AI in personnel selection, this study examines how organizations can mitigate adverse reactions to fully exploit the benefits of AI. To obtain robust results, we recruited an online sample of German participants (N = 1,852) and presented them with various selection scenarios. Using a between-subject design, the process stage (pre-selection vs. interview) and the degree of process automation (augmented vs. automated) were manipulated. By employing a multidimensional conceptualization of transparency, we show that disclosure and accuracy positively impact procedural justice perceptions, a strong predictor of process quality assessment. This relationship is robust across selection contexts. Results indicate that applicants prefer AI for pre-selection and as human decision support, thus offering overall insights into design choices for AI in selection, optimizing applicant reactions

Beyond the Pale: Pedagogical Strategies for Analyzing Race and Whiteness

The roots of American sociology of race and ethnicity run deep, but a focus on whiteness has matured in recent decades. This body of research is diverse: Whiteness is understood as simultaneously omnipresent, ubiquitous, rigid and flexible. Moreover, students enrolled in courses on race and ethnicity have difficulty grasping the conflicting and ambiguous character of whiteness that is exacerbated by their own misconceptions and ideological baggage they carry into the classroom. To empirically identify common student misconceptions, and to illuminate effective pedagogical interventions, I analyze two different sociology of race and ethnicity courses, offered twelve times over an eight-year span, at two different University institutions. Based on in- and out-of-classroom exercises and assignments completed by students in these classes (N = 406), I outline four patterned interpretative dilemmas and concomitant pedagogical interventions to aid students’ understanding of whiteness. Results indicate that these four intervention exercises found overall success amidst a variety of classroom sizes, disparately ranked public universities, different US regions, and amongst classroom contexts high in racial diversity to majority-white student course enrollment

New Approaches to Legal Study

Most lawyers - be they practitioners, judges, or just plain academics - have a fairly clear idea of what it is they must do when studying law . Most lawyers, without giving the matter very much thought, concern themselves with interpreting statutes according to well-understood principles, analysing cases using time-honoured notions such as stare decisis, ratio decidendi, and obita dicta, and occasionally (very occasionally, with much trepidation and many disclaimers) venturing a policy suggestion or two. Not many have wanted to do much else, and few have suggested any virtue in trying anything new. But the winds of change appear to be upon us. The last decade or so has seen development of several apparently new approaches to consideration of the law. It is my purpose in this essay to examine two of the better-developed streams of development, in an attempt to fix their value and significance. I refer to jurimetrics\u27 - a term generally taken to refer to the use of electronic (computer) retrieval, quantitative methods, and symbolic logic in the study of law - and to the growing body of jurisprudential writings by philosophers, primarily moral philosophers, generally on topics of contemporary political interest, such as civil disobedience, abortion and euthanasia

The Confusion of Causes and Reasons in Forensic Psychology: Deconstructing Mens Rea and Other Mental Events

The public perception that criminal conduct is increasingly excused on psychological grounds, notwithstanding a markedly small statistical success rate of diminished capacity defenses, evinces misplaced frustration over a broader cultural reluctance or inability to assign moral blame. Psychology is seen as feeding a kind of determinism that rationalizes evil behavior and precludes retributive punishment as a matter of scientific principle. This perception is accurate to the degree that it reveals our legal system\u27s fundamental confusion of purposes in judging and explaining criminal behavior. This confusion is engendered by the indeterminacy of language, which entangles the verificationist mode and purpose of science with the aspirational mode and purpose of metaphysics. The difference between the two linguistic forms roughly corresponds to Ludwig Wittgenstein\u27s distinction between propositions expressive of logical necessity (what can be said) and ethical sensibilities expressive of transcendent value (what can only be shown). The entangling of these forms in forensic psychology becomes manifest as a merger of causes, which explain actions in impersonal verificationist terms, and reasons, which infuse meanings to actions through something akin to literary interpretation. These entangled concepts are discussed in Part II of this paper