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WE ARE INDEBTED to Mr. J. K. Vose of Metropolitan‐Vickers Electrical Co. Ltd., (Motor Engineering Department), for the identification of the early oil‐release method mentioned in the paper ‘Grease Bleeding’ by E. G. Ellis in our September issue. This method actually appeared in the first revision of the Company's Purchasing Specification for Grease of October, 1935, and the relevant clause read as follows :—

A RECENT CONTRIBUTION to Scientific Lubrication has drawn attention to early work done by Metropolitan‐Vickers Electrical Company Limited in the field of grease‐testing. In his paper ‘The Mechanical Evaluation of Lubricating Greases’ J. H. Harris has referred to the M‐V.E. Co's recent work on the practical rig testing of greases for the lubrication of Rolling Bearings. It may be asked why a firm manufacturing electrical equipment should shew such interest in a subject apparently far removed from its normal activities. In this article an attempt is made to give the basic reasons for the interest displayed, and to describe some of the work which has been done.

Drawing on the slavery history of the United States, the theoretical framework of the post-traumatic slave syndrome is used to understand the influences and challenges of contemporary assessment and counseling issues of African American offenders.

Through a qualitative review of the literature, supporting evidence is given from an investigation of slavery’s historical laws, practices, experiences, and beliefs’ and its influences on contemporary assessment and counseling issues concerning African American offenders and the challenges met by counselors.

The laws, the practices, the experiences, and the beliefs during slavery have had a profound influence on contemporary issues of assessment and counseling African American offenders. The transgenerational adaptations associated with previous traumas during and after slavery influenced counselors’ ability to effectively assess and counsel African American offenders. Moreover, transgenerational adaptations are equally present among white counselors, which have contributed to challenges with assessments and counseling of African American offenders.

Understanding history that is theoretically framed out of the post-traumatic slave syndrome builds knowledge in understanding present challenges and barriers to effective counseling of African American offenders in three ways: (1) it makes the connection between slavery and contemporary issues concerning assessment and counseling of African American offenders; (2) it explains how race might complicate counseling and assessment process; and (3) it sheds light on significant counseling concepts related to rehabilitation or sanctions of African American offenders.

Purpose – This chapter gives an overview of the impact that the COVID-19 pandemic has had on institutional corrections in the United States and the responses correctional institutions have taken to lessen those impacts.

Methodology/Approach – A review of the extant literature was conducted to gather information on COVID-19 and the institutional corrections systems within the United States.

Findings – The impacts of the COVID-19 pandemic on correctional institutions within the United States were more pronounced due to the demographic characteristics of inmates and facility challenges. Responses to outbreaks or potential outbreaks in jails and prisons in the United States included screening measures, restricted inmate movement and visitation, and decarceration efforts.

Originality/Value – This chapter builds upon literature by discussing the challenges posed to correctional institutions in the United States in the face of the COVID-19 pandemic and summarizing the measures taken to reduce the impact of COVID-19 on inmates, institutional staff, and community members alike.

This study aims to advance the existing analytic model to include staff allocation information at the district level. Maintaining adequate size of staff is essential to law enforcement agencies' ability to ensure social order, fight crime and, increasingly, deliver a widening range of social services. Review of the scientific literature on police size of force and staffing calculation models indicates that this line of inquiry (i.e. manpower analysis) is attentive to population size and workload demands but generally inattentive to how service demands are affected by community-level variables. Current staffing calculation models specify number of staff needed for a jurisdiction but do not inform the allocation of personnel across districts within the jurisdiction.

To address this problem, the current study illustrates an enhanced analytic model to provide law enforcement staffing recommendations for a southern coastal county. An integrated per capita-workload manpower analysis model first factors the minimum number of law enforcement deputies needed per population size served and recent history workload demands and then executes the six-step workload model process. This study enhances staffing analysis by adding an additional seventh arithmetical step indicating the staffing needs by districts across a jurisdiction.

The results from the integrated per capita-workload analysis indicate the need to hire additional deputies to meet current and future demands.

Discussion centers on the need to include drivers of police services identified but not measured in this study's application of the hybrid manpower analysis model and its replication potential.

The purpose of this paper is to establish a version of a theorem that originated from population genetics and has been later adopted in evolutionary computation theory that will lead to novel Monte‐Carlo sampling algorithms that provably increase the AI potential.

In the current paper the authors set up a mathematical framework, state and prove a version of a Geiringer‐like theorem that is very well‐suited for the development of Mote‐Carlo sampling algorithms to cope with randomness and incomplete information to make decisions.

This work establishes an important theoretical link between classical population genetics, evolutionary computation theory and model free reinforcement learning methodology. Not only may the theory explain the success of the currently existing Monte‐Carlo tree sampling methodology, but it also leads to the development of novel Monte‐Carlo sampling techniques guided by rigorous mathematical foundation.

The theoretical foundations established in the current work provide guidance for the design of powerful Monte‐Carlo sampling algorithms in model free reinforcement learning, to tackle numerous problems in computational intelligence.

Establishing a Geiringer‐like theorem with non‐homologous recombination was a long‐standing open problem in evolutionary computation theory. Apart from overcoming this challenge, in a mathematically elegant fashion and establishing a rather general and powerful version of the theorem, this work leads directly to the development of novel provably powerful algorithms for decision making in the environment involving randomness, hidden or incomplete information.

Climate change is a massive multidimensional shift. Temperature shifts, in particular, have important implications for urbanization, agriculture, health, productivity, and poverty, among other things. While much research has documented rising mean temperature levels, the authors also examine range-based measures of daily temperature volatility. Specifically, using data for select US cities over the past half-century, the authors compare the evolving time series dynamics of the average daily temperature (AVG) and the diurnal temperature range (DTR; the difference between the daily maximum and minimum temperatures). The authors characterize trend and seasonality in these two series using linear models with time-varying coefficients. These straightforward yet flexible approximations provide evidence of evolving DTR seasonality and stable AVG seasonality.

In 1967 Aslib Research and Development Department published a note describing experimental work on computer‐aided typesetting, and announcing that further research was planned. The proposed programme of work was carried out by the authors of the present paper, during their sojourns as members of the Department. The results are here reported.

The essence of finance has become essential in the sustainability discussion in recent times as a result of the capital intensive nature of sustainable projects. This has motivated financial experts and institutions to develop various financial instruments and mechanisms to further advance the course of protecting the environment, and decreasing the release of excess carbon and GreenHouse Gases. This is to also provide the opportunity for funding Green or sustainable infrastructure development. This chapter advances a discourse on matters relating to sustainable financing of infrastructure projects. The fundamentals of sustainable or green funding of infrastructure projects, and sustainable schemes of financing green infrastructure projects are discussed.

This study aims to show how cost savings can be achieved through optimizing the scheduling of e-commerce enablements. The University of California is one of the largest, most prestigious public education and research systems in the world, yet diminished state support is driving the search for system-wide cost savings.

This study documents the preparation for and rollout of an e-procurement system across a subset of campuses. A math programing tool was developed for prioritizing the gradual rollout to generate the greatest expected savings subject to resource constraints.

The authors conclude by summarizing the results of the rollout, discussing lessons learned and their benefit to decision-makers at other public institutions.

The pilot program comprising three campuses has been predicted to yield $1.2m in savings over a one-year period; additional sensitivity analysis with respect to savings, project timelines and other rollout decisions illustrate the robustness of these findings.