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The purpose of this chapter is to review how well walking interventions have increased and sustained walking, and to provide suggestions for improving future walking interventions. A scoping review was conducted of walking interventions for adults that emphasised walking as a primary intervention strategy and/or included a walking outcome measure. Interventions conducted at the individual, community, and policy levels between 1990 and 2015 were included, with greater emphasis on recent interventions. Walking tends to increase early in interventions and then gradually declines. Results suggest that increased walking, and environmental-change activities to support walking are more likely to be sustained when they are immediately followed by greater economic benefits/time-savings, social approval, and/or physical/emotional well-being. Adaptive interventions that adjust intervention procedures to match dynamically changing environmental circumstances also hold promise for sustaining increased walking. Interventions that incorporate automated technology, durable built environment changes, and civic engagement, may increase cost-efficiency. Variations in outcome measures, study duration, seasons, participant characteristics, and possible measurement reactivity preclude causal inferences about the differential effectiveness of specific intervention procedures for increasing and sustaining walking. This review synthesises the effects of diverse walking interventions on increasing and sustaining walking over a 25-year period. Suggestions are provided to guide future development of more effective, sustainable walking interventions at the population level.

Considerable progress has been made in connection with the scientific survey now being undertaken as a preliminary to the consideration of improved methods of treatment and prevention of the ever increasing menace of grain pests, of which there are some seventy varieties. The survey is being made by the Stored Products Laboratory, of the Imperial College of Science and Technology, under the direction of the Department of Scientific and Industrial Research, and is being conducted by Professor Munro, assisted by a staff of experienced entomologists. At the commencement of the survey a research committee was appointed under the chairmanship of Dr. E. J. Butler, C.M.G., C.I.E., the Secretary of the Agricultural Research Council, to supervise the survey, consider its results, and report to the Department. Membership of the Research Committee includes, in addition to representation from Government Departments, Mr. W. P. Henderson, the Chief Chemist of the L.M.S. Railway, and Mr. W. McAuley Gracie, M.B.E., M.Inst.T., Chairman of the Standing Conference on Pest Infestation set up by the Department of Scientific and Industrial Research. At a recent meeting of the Research Committee, Professor Munro submitted a progress report dealing with the scientific survey, and on the convincing evidence contained in the report the Department of Scientific and Industrial Research sought the opinion of the Standing Conference on Pest Infestation as to whether consideration of control and remedial measures should be undertaken forthwith. The Standing Conference, whose membership comprises representatives of Government Departments, trading authorities and associations, including the Ministry of Agriculture, the four main line railway companies, the Port of London Authority, the Association of Master Lightermen and Barge Owners, the Research Association of British Flour Millers, the National Federation of Corn Trade Associations, the National Association of Corn and Agricultural Merchants, the National Farmers' Union, the Brewers' Society and the Maltsters' Association, took unanimous resolutions desiring the Department to secure immediate consideration of control and remedial action appropriate to the varying circumstances, and to extend the constitution of the Conference to bring into contributing membership interests outside the grain trade, but who are concerned with other produce susceptible to pest infestation, inasmuch as they would derive benefit from this stage of the work. The Chairman was authorised to negotiate with the Department accordingly and standing orders were suspended to enable him to admit into membership such bodies as furnished the requisite proof of interest. The Conference also urged that the Department of Scientific and Industrial Research should consult immediately with other appropriate public departments to secure adequate arrangements being made for the complete treatment of the problems of prevention and cure. The cost of such treatment, however, has to be met largely by industrial contributions, but it is understood that there is indication that generous contribution may be made from public funds towards the cost of the immediate remedial stage, providing that substantial industrial financial backing is forthcoming. Promises of further financial support have already been secured, but more money is required before negotiation can be entered into with the Department to obtain help from public funds. The co‐operation of all industrial organisations faced with the problem of infestation, by taking up contributory membership to support the conference in its national work, is urgently required. The problems of infestation can only be successfully combated if the complete co‐operation of all sections of industry in any way affected is secured. Full details and information regarding membership of the Conference can readily be obtained on application to the Chairman of the Standing Conference on Pest Infestation at the Department of Scientific and Industrial Research, 16, Old Queen Street, London, S.W.1.

Within the existing health care system, a significant percentage of Americans over the age of 65 will have need of extended health care. Yet the extended care industry has little information as to how consumers will make a choice among placement options. The results of this study describe both the need recognition and pre‐selection search stages of the decision process and the impact of need recognition on subsequent search activity. The information obtained from an influential person as the problem is being defined appears to have a complex relationship with pre‐selection search, with initial information leading to less search but additional information increasing search activity. Contrary to previous studies, pre‐selection search was found to be fairly extensive, increasing with time availability.

This paper describes the development and implementation of a joint protocol for the investigation of crimes against vulnerable adults. The protocol was piloted in Northern Ireland by the Police Service and Homefirst Community Health and Social Services Trust. The paper explains the aims of the protocol, examines the training involved in implementing it and explains the operational arrangements with special attention to capacity and consent, joint investigation, liaison points and review methods. It concludes with an examination of potential future developments.

The behavioral decision-making of digital-self is one of the important research contents of the network of crowd intelligence. The factors and mechanisms that affect decision-making have attracted the attention of many researchers. Among the factors that influence decision-making, the mind of digital-self plays an important role. Exploring the influence mechanism of digital-selfs’ mind on decision-making is helpful to understand the behaviors of the crowd intelligence network and improve the transaction efficiency in the network of CrowdIntell.

In this paper, the authors use behavioral pattern perception layer, multi-aspect perception layer and memory network enhancement layer to adaptively explore the mind of a digital-self and generate the mental representation of a digital-self from three aspects including external behavior, multi-aspect factors of the mind and memory units. The authors use the mental representations to assist behavioral decision-making.

The evaluation in real-world open data sets shows that the proposed method can model the mind and verify the influence of the mind on the behavioral decisions, and its performance is better than the universal baseline methods for modeling user interest.

In general, the authors use the behaviors of the digital-self to mine and explore its mind, which is used to assist the digital-self to make decisions and promote the transaction in the network of CrowdIntell. This work is one of the early attempts, which uses neural networks to model the mental representation of digital-self.

Many higher education institutions (HEIs) have constructed their internal evaluation systems to secure teaching quality. This paper aims to analyze teaching quality, HEIs use students to evaluate their professors as they have direct contact with the professors during the whole semester. The authorities hope to receive valuable information, which can be used for many administrative purposes. The bias in the evaluation toward professors’ gender and attractiveness has already been proven. However, there is only limited evidence whether students give higher value to teaching quality over the professors’ personality.

In this paper, the authors go further in the gender-attractiveness evidence and put the evaluation in contrast with professors’ experience, age, etc.

The results indicate that the effect of experience predominates the effect of gender and in some areas also the effect of age. What is more, a semester in which a course is taken also influences the evaluation as different professors’ abilities are required in teaching in a different semester. On the other hand, the results do not fully confirm the effect of gender on the evaluation.

The results reveal that it is important to consider the course structure to assign professors to the right courses.

The purpose of this paper is to present a method that addresses the data sparsity problem in points of interest (POI) recommendation by introducing spatiotemporal context features based on location-based social network (LBSN) data. The objective is to improve the accuracy and effectiveness of POI recommendations by considering both spatial and temporal aspects.

To achieve this, the paper introduces a model that integrates the spatiotemporal context of POI records and spatiotemporal transition learning. The model uses graph convolutional embedding to embed spatiotemporal context information into feature vectors. Additionally, a recurrent neural network is used to represent the transitions of spatiotemporal context, effectively capturing the user’s spatiotemporal context and its changing trends. The proposed method combines long-term user preferences modeling with spatiotemporal context modeling to achieve POI recommendations based on a joint representation and transition of spatiotemporal context.

Experimental results demonstrate that the proposed method outperforms existing methods. By incorporating spatiotemporal context features, the approach addresses the issue of incomplete modeling of spatiotemporal context features in POI recommendations. This leads to improved recommendation accuracy and alleviation of the data sparsity problem.

The research has practical implications for enhancing the recommendation systems used in various location-based applications. By incorporating spatiotemporal context, the proposed method can provide more relevant and personalized recommendations, improving the user experience and satisfaction.

The paper’s contribution lies in the incorporation of spatiotemporal context features into POI records, considering the joint representation and transition of spatiotemporal context. This novel approach fills the gap left by existing methods that typically separate spatial and temporal modeling. The research provides valuable insights into improving the effectiveness of POI recommendation systems by leveraging spatiotemporal information.

This paper aims to address the following issues: (1) most existing methods are based on recurrent network, which is time-consuming to train long sequences due to not allowing for full parallelism; (2) personalized preference generally are not considered reasonably; (3) existing methods rarely systematically studied how to efficiently utilize various auxiliary information (e.g. user ID and time stamp) in trajectory data and the spatiotemporal relations among nonconsecutive locations.

The authors propose a novel self-attention network–based model named SanMove to predict the next location via capturing the long- and short-term mobility patterns of users. Specifically, SanMove uses a self-attention module to capture each user's long-term preference, which can represent her personalized location preference. Meanwhile, the authors use a spatial-temporal guided noninvasive self-attention (STNOVA) module to exploit auxiliary information in the trajectory data to learn the user's short-term preference.

The authors evaluate SanMove on two real-world datasets. The experimental results demonstrate that SanMove is not only faster than the state-of-the-art recurrent neural network (RNN) based predict model but also outperforms the baselines for next location prediction.

The authors propose a self-attention-based sequential model named SanMove to predict the user's trajectory, which comprised long-term and short-term preference learning modules. SanMove allows full parallel processing of trajectories to improve processing efficiency. They propose an STNOVA module to capture the sequential transitions of current trajectories. Moreover, the self-attention module is used to process historical trajectory sequences in order to capture the personalized location preference of each user. The authors conduct extensive experiments on two check-in datasets. The experimental results demonstrate that the model has a fast training speed and excellent performance compared with the existing RNN-based methods for next location prediction.

With the objective of encouraging the use of standard processes for exploring offenders' narratives two complementary procedures are discussed. One is a development of McAdams explorations with highly effective individuals, describing their life as if it were a book. This is a structured interview protocol that has been specifically produced for use with offenders, in which they describe their life as a film (LAAF). A number of studies with male and female incarcerated individuals as well as those without convictions have revealed important differences between people in how they give a free account of their past and future lives. This allows the differentiation of LAAF narratives and reveals the existence of dominant narrative forms in offenders' responses. These relate to those initially elaborated by Frye (1957) for fiction, namely tragedy, comedy, adventure and romance. The second method is the Narrative Role Questionnaire (NRQ) which elicits the inherent role that offenders saw themselves as playing during specific crimes. Completion of the NRQ by various samples reveals important differences between offences in the narratives that provide the agency for their criminal actions. The roles central to these narratives have also been found to embody distinct emotional components that maintain offending. Taken together the NRQ and the LAAF provide a framework for examining offence narratives which enables the main narratives of relevance to criminality to be identified and their implications for theory and practice to be elaborated.