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To interact efficiently with the visual environment, one perceptually integrates fragmented visual inputs into complete units. Another approach is to rely on previous experience to determine what should receive attention and what should be discarded. While both perceptual integration and learning experiences have been found to influence attentional selection, the interaction between these processes remains unexplored. The present study investigated whether perceptual integration modulates the effects of learning experiences on attentional selection using experiments, in which colors were associated either with a reward or a search target. During this association phase, stimuli featuring those colors either did or did not form a perceptually integrated object. We found that while stimuli that were previously associated with rewards impaired target processing, stimuli that were related to previous targets facilitated target search. Importantly, perceptual integration magnified the effects of reward-based and search history-based attention. Furthermore, the interaction between perceptual integration and experience-driven attention cannot be attributed solely to the fact that perceptual integration increases stimulus salience. We discuss specific mechanisms by which perceptual integration affects the dissociable components of experience-driven attention.

The engrossing account of how science-based forensics transformed the investigation of twentieth-century murders and in the process invented CSI. Crime scene investigation—or CSI—has captured the modern imagination. On television screens and in newspapers, we follow the exploits of forensic officers wearing protective suits and working behind police tape to identify and secure physical evidence for laboratory analysis. But where did this ensemble of investigative specialists and scientific techniques come from? In Murder and the Making of English CSI, Ian Burney and Neil Pemberton tell the engrossing history of how, in the first half of the twentieth century, novel routines, regulations, and techniques—from chain-of-custody procedures to the analysis of hair, blood, and fiber—fundamentally transformed the processing of murder scenes. Focusing on two iconic English investigations—the 1924 case of Emily Kaye, who was beaten and dismembered by her lover at a lonely beachfront holiday cottage, and the 1953 investigation into John Christie's serial murders in his dingy terraced home in London's West End—Burney and Pemberton chart the emergence of the crime scene as a new space of forensic activity. Drawing on fascinating source material ranging from how-to investigator handbooks and detective novels to crime journalism, police case reports, and courtroom transcripts, the book shows readers how, over time, the focus of murder inquiries shifted from a primarily medical and autopsy-based interest in the victim's body to one dominated by laboratory technicians laboring over minute trace evidence. Murder and the Making of English CSI reveals the compelling and untold story of how one of themost iconic features of our present-day forensic landscape came into being. It is a must-read for forensic scientists, historians, and true crime devotees alike.

Despite decades of research to better understand suicide risk and to develop detection and prevention methods, suicide is still one of the leading causes of death globally. While large-scale studies using real-world evidence from electronic health records can identify who is at risk, they have not been successful at pinpointing when someone is at risk. Personalized social media and online search history data, by contrast, could provide an ongoing real-world datastream revealing internal thoughts and personal states of mind. We conducted this study to determine the feasibility and acceptability of using personalized online information-seeking behavior in the identification of risk for suicide attempts. This was a cohort survey study to assess attitudes of participants with a prior suicide attempt about using web search data for suicide prevention purposes, dates of lifetime suicide attempts, and an optional one-time download of their past web searches on Google. The study was conducted at the University of Washington School of Medicine Psychiatry Research Offices. The main outcomes were participants' opinions on internet search data for suicide prediction and intervention and any potential change in online information-seeking behavior proximal to a suicide attempt. Individualized nonparametric association analysis was used to assess the magnitude of difference in web search data features derived from time periods proximal (7, 15, 30, and 60 days) to the suicide attempts versus the typical (baseline) search behavior of participants. A total of 62 participants who had attempted suicide in the past agreed to participate in the study. Internet search activity varied from person to person (median 2-24 searches per day). Changes in online search behavior proximal to suicide attempts were evident up to 60 days before attempt. For a subset of attempts (7/30, 23%) search features showed associations from 2 months to a week before the attempt. The top 3 search constructs associated with attempts were online searching patterns (9/30 attempts, 30%), semantic relatedness of search queries to suicide methods (7/30 attempts, 23%), and anger (7/30 attempts, 23%). Participants (40/59, 68%) indicated that use of this personalized web search data for prevention purposes was acceptable with noninvasive potential interventions such as connection to a real person (eg, friend, family member, or counselor); however, concerns were raised about detection accuracy, privacy, and the potential for overly invasive intervention. Changes in online search behavior may be a useful and acceptable means of detecting suicide risk. Personalized analysis of online information-seeking behavior showed notable changes in search behavior and search terms that are tied to early warning signs of suicide and are evident 2 months to 7 days before a suicide attempt.

Information Retrieval (IR) systems assist users in finding information from the myriad of information resources available on the Web. A traditional characteristic of IR systems is that if different users submit the same query, the system would yield the same list of results, regardless of the user. Personalised Information Retrieval (PIR) systems take a step further to better satisfy the user’s specific information needs by providing search results that are not only of relevance to the query but are also of particular relevance to the user who submitted the query. PIR has thereby attracted increasing research and commercial attention as information portals aim at achieving user loyalty by improving their performance in terms of effectiveness and user satisfaction. In order to provide a personalised service, a PIR system maintains information about the users and the history of their interactions with the system. This information is then used to adapt the users’ queries or the results so that information that is more relevant to the users is retrieved and presented. This survey paper features a critical review of PIR systems, with a focus on personalised search. The survey provides an insight into the stages involved in building and evaluating PIR systems, namely: information gathering, information representation, personalisation execution, and system evaluation. Moreover, the survey provides an analysis of PIR systems with respect to the scope of personalisation addressed. The survey proposes a classification of PIR systems into three scopes: individualised systems, community-based systems, and aggregate-level systems. Based on the conducted survey, the paper concludes by highlighting challenges and future research directions in the field of PIR.

Recently, nonrevisiting genetic algorithms have demonstrated superior capabilities compared with classic genetic algorithms and other single-objective evolutionary algorithms. However, the search efficiency of nonrevisiting genetic algorithms is currently low for some complex optimisation problems. This study proposes a nonrevisiting genetic algorithm with a multi-region guided search to improve the search efficiency. The search history is stored in a binary space partition (BSP) tree, where each searched solution is assigned to a leaf node and corresponds to a search region in the search space. To fully exploit the search history, several optimal solutions in the BSP tree are archived to represent the most potential search regions and estimate the fitness landscape in the search space. Except for the conventional genetic operations, the offspring can also be generated through multi-region guided search strategy, where the current solution is first navigated to one of the candidate search regions and is further updated towards the direction of the optimal solution in the search history to speedup convergence. Thus, multi-region guided search can reduce the possibility of getting trapped in local optima when solving problems with complex landscapes. The experimental results on different types of test suites reveal the competitiveness of the proposed algorithm in comparison with several state-of-the-art methods.

The variety and diversity of published content are currently expanding in all fields of scholarly communication. Yet, scientific knowledge graphs (SKG) provide only poor images of the varied directions of alternative scientific choices, and in particular scientific controversies, which are not currently identified and interpreted. We propose to use the rich variety of knowledge present in search histories to represent cliques modeling the main interpretable practices of information retrieval issued from the same “cognitive community”, identified by their use of keywords and by the search experience of the users sharing the same research question. Modeling typical cliques belonging to the same cognitive community is achieved through a new conceptual framework, based on user profiles, namely a bipartite geometric scientific knowledge graph, SKG GRAPHYP. Further studies of interpretation will test differences of documentary profiles and their meaning in various possible contexts which studies on “disagreements in scientific literature” have outlined. This final adjusted version of GRAPHYP optimizes the modeling of “Manifold Subnetworks of Cliques in Cognitive Communities” (MSCCC), captured from previous user experience in the same search domain. Cliques are built from graph grids of three parameters outlining the manifold of search experiences: mass of users; intensity of uses of items; and attention, identified as a ratio of “feature augmentation” by literature on information retrieval, its mean value allows calculation of an observed “steady” value of the user/item ratio or, conversely, a documentary behavior “deviating” from this mean value. An illustration of our approach is supplied in a positive first test, which stimulates further work on modeling subnetworks of users in search experience, that could help identify the varied alternative documentary sources of information retrieval, and in particular the scientific controversies and scholarly disputes.

Research has demonstrated that oculomotor visual search is guided by memory for which items or locations within a display have already been inspected. In the study reported here, we used a gaze-contingent search paradigm to examine properties of this memory. Data revealed a memory buffer for search history of three to four items. This buffer was effected in part by a space-based trace attached to a location independently of whether the object that had been seen at that position remained visible, and was subject to interference from other stimuli seen in the course of a trial.

A novel dynamic cooperative random drift particle swarm optimization algorithm based on entire search history decision (CRDPSO) is reported. At each iteration, the positions and the fitness values of the evaluated solutions in the algorithm are stored by a binary space partitioning tree structure archive, which leads to a fast fitness function approximation. The mutation is adaptive and parameter-less because of the fitness function approximation enhancing the mutation strategy. The dynamic cooperation between the particles by using the context vector increases the population diversity helps to improve the search ability of the swarm and cooperatively searches for the global optimum. The performance of CRDPSO is tested on standard benchmark problems including multimodal and unimodal functions. The empirical results show that CRDPSO outperforms other well-known stochastic optimization methods.

The modern law of search and seizure permits warrantless searches that ruin the citizenry's trust in law enforcement, harms minorities, and embraces an individualistic notion of the rights that it protects, ignoring essential roles that properly-conceived protections of privacy, mobility, and property play in uniting Americans. Many believe the Fourth Amendment is a poor bulwark against state tyrannies, particularly during the War on Terror. Historical amnesia has obscured the Fourth Amendment's positive aspects, and Andrew E. Taslitz rescues its forgotten history in Reconstructing the Fourth Amendment , which includes two novel arguments. First, that the original Fourth Amendment of 1791—born in political struggle between the English and the colonists—served important political functions, particularly in regulating expressive political violence. Second, that the Amendment’s meaning changed when the Fourteenth Amendment was created to give teeth to outlawing slavery, and its focus shifted from primary emphasis on individualistic privacy notions as central to a white democratic polis to enhanced protections for group privacy, individual mobility, and property in a multi-racial republic. With an understanding of the historical roots of the Fourth Amendment, suggests Taslitz, we can upend negative assumptions of modern search and seizure law, and create new institutional approaches that give political voice to citizens and safeguard against unnecessary humiliation and dehumanization at the hands of the police.

Launius points out that the emphasis on consensus in US national history has been present from the nation's beginnings, and there is, of course, considerable value in emphasizing the ideals that have brought Americans together as a people rather than focusing on the divisiveness in society. History might be viewed largely as a lesson in civics and a means of instilling in the nation's citizenry a sense of awe and reverence for the nation-state and its system of governance. The rise of the \"new social history\" in the 1960s, with its emphasis on race, ethnicity, class, gender, and the way groups have wielded power throughout the nation's past, offered a powerful counterweight to the consensus interpretation.