A histological study on polyactive® for the prevention of peridural adhesions after spinal surgery: an experimental study in dogs with a 3 months follow-up

In the present study the potential of Polyactive^® bilayer sheets in the prevention of scar tissue formation after spinal surgery was investigated. Eight adult beagle dogs underwent 3 laminectomies at three levels (L2, L4 and L6). According to a randomized implantation schedule a Polyactive^® sheet or autogenous fat graft was placed in the defect. The third site served as a control without implant. After 4 or 12 weeks (4 dogs per period) the dogs were sacrificed and histological sections were prepared. The Polyactive^® treated defects showed partial closure by newly formed bone. The Polyactive^® was encapsuled by a thin fibrous tissue layer. Ventral to the defect, dense fibrous tissue was present which was separated from the dura by the Polyactive^® sheet in all cases. In some cases fibrous tissue was present between the implant capsule and the dura. In the fat graft group there were no signs of closure of the defect but most sites showed fibrous tissue at the edges of the graft, which was in 4 sites continous with the dura mater. Fibrosis and degeneration of the fat grafts were seen. All control defects showed partial closure by newly formed bone, and ventral to the defect extensive fibrous tissue, which was in 50% continous with the dura mater. Other sections showed loose connective tissue in contact with the dura mater. It is concluded that Polyactive^® has a potential as a mechanical barrier in the prevention of adhesions between the dorsal spinal muscles and the dura mater.     

A Dynamic Dictionary for Priced Information with Application

In this paper we design a dynamic dictionary for the priced information model initiated by Charikar et al. Assume that a set S consisting of n elements is given such that each element has an associated price, a positive real number. The cost of performing an operation on elements of S is a function of their prices. The cost of an algorithm is the sum of the costs of all operations it performs. The objective is to design algorithms which incur low cost. In this model we propose a dynamic dictionary, supporting search, insert and delete, for keys drawn from a linearly ordered set. As an application we show that the dictionary can be used in computing the trapezoidal map of a set of line segments, a fundamental problem in computational geometry.     

斯芬克司住宅，赫依曾，荷兰

5座斯芬克司住宅的每一栋各容纳了14间为了充分利用地段和阳光而组织起来的公寓。建筑的体量在背向水面的方向被斜切，从而使得从湖岸和公寓所能看到的湖景不被阻隔。当人在从楼里往上走时，公寓的数目逐层递减。结果产生了一种斯芬克司式的轮廓，面向太阳的屋顶退台置于这个神话中的怪兽的脊背上。每个建筑体量的雨篷设计是不同的，从而使其独特的头部产生一种韵律感——从连接新开拓地和现有大陆的stichtse桥上看去的一条激动人心的天际线。     

An optimal usage of NO x in a combined Pt/ceramic foam and a wall-flow monolith filter for an effective NO x -assisted soot oxidation

Topics in Catalysis - An NO2-assisted soot oxidation based filter candidate consists of Pt-coated ceramic foam in combination with a wall-flow monolith is proposed to acquire for an optimal usage...     

Application of reinforcement learning to the game of Othello

Operations research and management science are often confronted with sequential decision making problems with large state spaces. Standard methods that are used for solving such complex problems are associated with some difficulties. As we discuss in this article, these methods are plagued by the so-called curse of dimensionality and the curse of modelling. In this article, we discuss reinforcement learning, a machine learning technique for solving sequential decision making problems with large state spaces. We describe how reinforcement learning can be combined with a function approximation method to avoid both the curse of dimensionality and the curse of modelling. To illustrate the usefulness of this approach, we apply it to a problem with a huge state space—learning to play the game of Othello. We describe experiments in which reinforcement learning agents learn to play the game of Othello without the use of any knowledge provided by human experts. It turns out that the reinforcement learning agents learn to play the game of Othello better than players that use basic strategies.     

Effects of differences in office chair controls, seat and backrest angle design in relation to tasks

In this study the influence of chair characteristics on comfort, discomfort, adjustment time and seat interface pressure is investigated during VDU and non-VDU tasks: The two investigated office chairs, both designed according to European and Dutch standards are different regarding: 1) seat cushioning and shape, 2) backrest angle and 3) controls. Thirty subjects in total, both male and female, participated in two experiments: twenty in the first and ten in the second.Significant differences are found for ease of adjustment and adjustment time of controls, independent of the tasks. Related to tasks, a significant difference was found for the backrest range of motion. For non-VDU tasks a larger range of backrest motion was preferred by 70% of the subjects. The chair design differences were most clear for comfort and adjustment time of controls, followed by comfort of backrest angle. No differences are found between seat pan comfort and discomfort, first impressions and peak interface pressure.     

Office task effects on comfort and body dynamics in five dynamic office chairs

In the present study, we investigated the effect of office tasks on posture and movements in field settings, and the comfort rating for chair characteristics and correlation with type of task. The tasks studied were: computer work, telephoning, desk work and conversation. Postures, movements, chair part inclinations and comfort rating data were collected from 12 subjects. Computer work showed the lowest physical activity, together with upright trunk and head position and low backrest inclination. Conversation shows the highest activity of head legs and low back together with the highest cervical spine extension. In contrast, desk work provoked the most cervical spine flexion and showed the second lowest activity. The telephoning tasks showed medium activity and the highest kyphosis. Conversation showed the highest backrest inclination. Positive comfort relations were found for computer work and a "swing system" chair, for telephoning and an active longitudinal seat rotation, and for desk work and a chair with a three-dimensionally moveable seat.     

Moduli and canonical forms for linear dynamical systems II: The topological case

In this paper we study real linear dynamical systems \(\dot x = Fx + Gu,y = Hx,x \in R^n \) = state space,u ∈ R ^m = input space,y ∈ R ^p = output space, under the equivalence relation induced by base change in state space; or in other words we study triples of matrices with real coefficients (F, G, H) of sizesn × n, n × m, p × n respectively, under the action(F, G, H.) →(TFT ^?1,TG, HT ^?1) ofGL _n (R), the group of invertible realn × n matrices. One of the central questions studied is: “do there exist continuous canonical forms for this equivalence relation?”. After various trivial obstructions to the existence of such forms have been removed the answer is very roughly: no ifm ≥ 2, p ≥ 2, yes ifm = 1, orp = 1. For a precise statement cf. theorem 1.7. Existence or nonexistence of continuous canonical forms is related to the existence of a universal family of real linear dynamical systems. More precisely continuous canonical forms exist if such a universal family exists and if the underlying vector bundle of this family is the trivial vector bundle. In the case studied we show that a universal family in the appropriate sense does exist. The methods used are purely (differential) topological and in particular do not involve any algebraic geometry. There is a corresponding algebraic theory over any fieldk instead ofR which is the subject of part III of this series of papers.     

Generation of classes of robust periodic railway timetables

In this paper we discuss the problem of randomly sampling classes of fixed-interval railway timetables from a so-called timetable structure. Using a standard model for the timetable structure, we introduce a natural partitioning of the set of feasible timetables into classes. We then define a new probability distribution where the probability of each class depends on the robustness of the timetables in that class. Due to the difficulty of sampling directly from this distribution, we propose a heuristic sampling method and illustrate using practical data that our method indeed favors classes containing robust timetables over others.