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This paper is concerned with the application of systems analysis to problems of physical distribution. The principles of systems analysis and the concepts of the systems approach are outlined. Physical distribution is described as a set of major subsystems. The objective of this analysis is to provide a generalised framework for the solution of physical distribution problems. It may be noted that in the United Kingdom, systems analysis has come to be used in a narrower sense and to be concerned primarily with the design and specification of computer systems. In this paper, it is used in the wider sense, and for an appreciation the reader's attention is drawn to collections of papers by Emery, Opfner and Beishon and Peters. The use of a problem solving methodology is not unique to systems analysis except in the sense that systems analysis defines a particular process of problem solution. Similar processes are used in industrial engineering, method study, operational research, value analysis and management accounting. Other analyses of physical distribution systems are equally valid. That presented in this paper identifies a series of distribution units in the chain of distribution. It seeks to define the subsystems within each unit. The approach relies heavily on a series of diagrams which is intended to give a visual image of the relationships between elements in the chain.

Abstract
A common criticism of the use of algorithms in criminal justice is that algorithms and their determinations are in some sense "opaque"—that is, difficult or impossible to understand, whether because of their complexity or because of intellectual property protections. Scholars have noted some key problems with opacity, including that opacity can mask unfair treatment and threaten public accountability. In this paper, we explore a different but related concern with algorithmic opacity, which centers on the role of public trust in grounding the legitimacy of criminal justice institutions. We argue that algorithmic opacity threatens the trustworthiness of criminal justice institutions, which in turn threatens their legitimacy. We first offer an account of institutional trustworthiness before showing how opacity threatens to undermine an institution's trustworthiness. We then explore how threats to trustworthiness affect institutional legitimacy. Finally, we offer some policy recommendations to mitigate the threat to trustworthiness posed by the opacity problem.

The ability of both the non-credible score of the Rey Auditory Verbal Learning Test (RAVLT NC) and the recognition score of the RAVLT (RAVLT Recog) to predict credible versus non-credible neuropsychological test performance was examined. Credible versus non-credible group membership was determined according to diagnostic criteria with consideration of performance on two stand-alone performance validity tests. Findings from this retrospective data analysis of outpatients seen for neuropsychological testing within a Veterans Affairs Medical Center (N = 175) showed that RAVLT Recog demonstrated better classification accuracy than RAVLT NC in predicting credible versus non-credible neuropsychological test performance. Specifically, an RAVLT Recog cutoff of ≤9 resulted in reasonable sensitivity (48%) and acceptable specificity (91%) in predicting non-credible neuropsychological test performance. Implications for clinical practice are discussed. Note: The views contained here within are those of the authors and not representative of the institutions with which they are associated.