Giant Intra-Articular Extrasynovial Osteochondroma of the Knee: A Report of Two Cases

We report two cases of a giant extrasynovial osteochondroma of the knee located in the infrapatellar fat pad region, in two females who were 58 and 71 years old respectively. Both patients had noticed the mass many years before our first clinical observation. In both patients, at physical examination a solid, firm and hard mass was palpable in the anterior part of the knee in Hoffa’s fat pad region, and the range of motion of the knee was severely restricted and painful. CT scan examination with 3D-reconstruction showed two large, calcified neoformations behind the patellar tendon, between the apex of the patella and the proximal third of the tibia. In both cases, the mass was completely resected surgically through an anterior longitudinal approach. At histological examination, the excised masses consisted of an outer layer of hyaline cartilage without significant chondrocyte atypia and an inner region of bone trabeculae formed by endochondral ossification. At follow-up, 8 and 4 years after the operation, both patients were pain-free, with complete recovery of the range of motion of the knee and without any clinical or radiographic evidence of recurrence. The authors believe that intra-articular extrasynovial osteochondroma of the knee is a primary metaplasia of Hoffa’s fat pad. Usually, the tumor develops slowly and asymptomatically over many years. The treatment of choice is a marginal resection of the mass, although a biopsy should be considered in some cases. Recurrences are extremely rare

Age and distraction are determinants of performance on a novel visual search task in aged Beagle dogs

Aging has been shown to disrupt performance on tasks that require intact visual search and discrimination abilities in human studies. The goal of the present study was to determine if canines show age-related decline in their ability to perform a novel simultaneous visual search task. Three groups of canines were included: a young group (N = 10; 3 to 4.5 years), an old group (N = 10; 8 to 9.5 years), and a senior group (N = 8; 11 to 15.3 years). Subjects were first tested for their ability to learn a simple two-choice discrimination task, followed by the visual search task. Attentional demands in the task were manipulated by varying the number of distracter items; dogs received an equal number of trials with either zero, one, two, or three distracters. Performance on the two-choice discrimination task varied with age, with senior canines making significantly more errors than the young. Performance accuracy on the visual search task also varied with age; senior animals were significantly impaired compared to both the young and old, and old canines were intermediate in performance between young and senior. Accuracy decreased significantly with added distracters in all age groups. These results suggest that aging impairs the ability of canines to discriminate between task-relevant and -irrelevant stimuli. This is likely to be derived from impairments in cognitive domains such as visual memory and learning and selective attention

Recommender Systems

The ongoing rapid expansion of the Internet greatly increases the necessity of effective recommender systems for filtering the abundant information. Extensive research for recommender systems is conducted by a broad range of communities including social and computer scientists, physicists, and interdisciplinary researchers. Despite substantial theoretical and practical achievements, unification and comparison of different approaches are lacking, which impedes further advances. In this article, we review recent developments in recommender systems and discuss the major challenges. We compare and evaluate available algorithms and examine their roles in the future developments. In addition to algorithms, physical aspects are described to illustrate macroscopic behavior of recommender systems. Potential impacts and future directions are discussed. We emphasize that recommendation has a great scientific depth and combines diverse research fields which makes it of interests for physicists as well as interdisciplinary researchers.Comment: 97 pages, 20 figures (To appear in Physics Reports

Structuring effect of tools conceptualized through initial goal fixedness for work activity

Analysis of work activities in nuclear industry has highlighted a new psycho-cognitive phenomenon: the structuring effect of tools (SET) sometimes leading to unexpected operating deviations; the subject is unable to perform a task concerning object A using or adapting a tool designed and presented to perform the same task concerning object B when object A is expected by the subject. Conditions to isolate and identify the SET were determined and reproduced in experiments for further analysis. Students and seven professional categories of adults (N = 77) were involved in three experimental conditions (control group, group with prior warning, group with final control) while individually performing a task with similar characteristics compared to real operating conditions and under moderate time-pressure. The results were: (1) highest performance with prior warning and (2) demonstration that academic and professional training favor the SET. After discussing different cognitive processes potentially related to the SET, we described (3) the psycho-cognitive process underlying the SET: Initial Goal Fixedness (IGF), a combination of the anchoring of the initial goal of the activity with a focus on the features of the initial goal favored by an Einstellung effect. This suggested coping with the negative effect of the SET by impeding the IGF rather than trying to increase the subjects’ awareness at the expense of their health. Extensions to other high-risk industries were discussed

Facilitating Organisational Fluidity with Computational Social Matching

Striving to operate in increasingly dynamic environments, organisations can be seen as fluid and communicative entities where traditional boundaries fade away and collaborations emerge ad hoc. To enhance fluidity, we conceptualise computational social matching as a research area investigating how to digitally support the development of mutually suitable compositions of collaborative ties in organisations. In practice, it refers to the use of data analytics and digital methods to identify features of individuals and the structures of existing social networks and to offer automated recommendations for matching actors. In this chapter, we outline an interdisciplinary theoretical space that provides perspectives on how interaction can be practically enhanced by computational social matching, both on the societal and organisational levels. We derive and describe three strategies for professional social matching: social exploration, network theory-based recommendations, and machine learning-based recommendations.Striving to operate in increasingly dynamic environments, organisations can be seen as fluid and communicative entities where traditional boundaries fade away and collaborations emerge ad hoc. To enhance fluidity, we conceptualise computational social matching as a research area investigating how to digitally support the development of mutually suitable compositions of collaborative ties in organisations. In practice, it refers to the use of data analytics and digital methods to identify features of individuals and the structures of existing social networks and to offer automated recommendations for matching actors. In this chapter, we outline an interdisciplinary theoretical space that provides perspectives on how interaction can be practically enhanced by computational social matching, both on the societal and organisational levels. We derive and describe three strategies for professional social matching: social exploration, network theory-based recommendations, and machine learning-based recommendations.Peer reviewe