Clinical experience of functional electrical stimulation in complete paraplegia

In the Riordan (bridle) transfer, the posterior tibialis muscle as motor is routed through the interosseous membrane and anastomosed into a "bridle" formed by the distal tibialis anterior and peroneus longus muscles. In theory, the bridle provides inversion/eversion balance even if the transfer effects only tenodesis. However, the procedure has been criticized because its insertion is not into bone. This review analyzes the use of bridle transfer in flaccid paresis involving musculature innervated by the peroneal nerve. Surgery was performed 1 to 3 years after injury for patients with traumatic etiology. Ten patients are reviewed at 61 months' mean follow-up. Eight patients had traumatic peroneal nerve loss. Two had neuromuscular etiology. Evaluation included review of records, telephone interviews, and physical examinations. Data on functional status included walking barefoot running, need for bracing, return to duty, and patient satisfaction. Physical examination recorded ankle position and motions, gait findings, and results of static electromyograms. All patients were able to walk barefoot, but 6 of 10 had a mild to moderate limp. Five patients returned to running initially; only two were able to keep running. Nine patients were brace-free initially (polio sequela required bracing initially), and four others returned to bracing. Of these, two experienced an acute "tearing" and dorsiflexion loss, one sustained a prolonged gradual loss of dorsiflexion, and one sustained a contralateral cerebrovascular accident. Only three of seven patients returned to active duty, and one is on jump status. All patients were satisfied with their initial result. Only two patients had no detectable swing phase problems (both returned to active duty). Five patients had peroneal nerve exploration with repair or neurolysis; two of them sustained complete transections. Postoperative electromyograms showed insignificant, if any, nerve return. The Riordan transfer works well for neuromuscular flaccid paresis and in patients with peroneal nerve injuries with low demands. It may stretch out over time to the point of acute failure in patients with high demands. Concurrent peroneal nerve exploration and repair did not seem to be beneficial in this small study.     

Renal glomerular fibrosis in a cat

Renal glomerular fibrosis was observed in a 1-year-old spayed female Japanese domestic cat that showed clinically advanced renal failure. In the glomeruli, increased homogeneous materials were stained strongly with aniline blue by Masson's trichrome and positive for anti-type III collagen antibody by immunohistochemical staining, causing mesangial sclerosis and capillary collapse. By electron microscopy, randomly arranged fibrils were observed in the expanded subendothelial and mesangial areas, and the fibrils showed periodicity characteristic of collagen fibers in longitudinal sections. These findings of glomerular lesions closely resemble those of human "collagenofibrotic glomerulonephropathy," which has recently been described as a new type of glomerulonephropathy.     

Preconditioned iterative solver on the coarsest level of a multi-grid method for high frequency time harmonic electromagnetic field analyses

A multi-grid method is one of the most powerful linear solvers for finite element electromagnetic field analysis. However, as the discretized model has recently been enlarged, a solution process for a linear system arising on the coarsest level tends to be problematic in a complete multi-grid solution process. Whereas a linear system on the coarsest level is generally solved by a direct solver, we solve it here by means of an iterative solver to reduce the memory requirements. Since a conventional preconditioning technique is not effective for such a linear system, we introduce preconditioning techniques based on Arnold, Falk, and Winther’s and on Hiptmair’s smoothers. Numerical tests show that the newly installed preconditioning technique greatly improves the convergence rate.     

Vibration control of load for rotary crane system using neural network with GA-based training

A neuro-controller for vibration control of load in a rotary crane system is proposed involving the rotation about the vertical axis only. As in a nonholonomic system, the vibration control method using a static continuous state feedback cannot stabilize the load swing. It is necessary to design a time-varying feedback controller or a discontinuous feedback controller. We propose a simple three-layered neural network as a controller (NC) with genetic algorithm-based (GA-based) training in order to control load swing suppression for the rotary crane system. The NC is trained by a real-coded GA, which substantially simplifies the design of the controller. It appeared that a control scheme with performance comparable to conventional methods can be obtained by a relatively simple approach. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Learning commutative deterministic finite state automata in polynomial time

We consider the problem of learning the commutative subclass of regular languages in the on-line model of predicting {0,1∼-valued functions from examples and reinforcements due to Littlestone [7,4]. We show that the entire class of commutative deterministic finite state automata (CDFAs) of an arbitrary alphabet sizek is predictable inO(s ^k) time with the worst case number of mistakes bounded above byO(s ^kk logs), wheres is the number of states in the target DFA. As a corollary, this result implies that the class of CDFAs is also PAC-learnable from random labeled examples in timeO(s ^k) with sample complexity, using a different class of representations. The mistake bound of our algorithm is within a polynomial, for a fixed alphabet size, of the lower boundO(s+k) we obtain by calculating the VC-dimension of the class. Our result also implies the predictability of the class of finite sets of commutative DFAs representing the finite unions of the languages accepted by the respective DFAs. Part of this work was supported by the Office of Naval Research under contract number N00014-87-K-0401 while the author was at the Department of Computer and Information Science, University of Pennsylvania, and N0014-86-K-0454 while at the Department of Computer and Information Sciences, U.C. Santa Cruz. The author’s email address is abe@IBL.CL.nec.co.jp     

Effects of hematocrit variations on cerebral blood flow and oxygen transport in ischemic cerebrovascular disease

The contribution of hematocrit (Ht) changes on cerebral blood flow (CBF) and brain oxygenation in ischemic cerebrovascular disease is still controversial. In the present study, effects of Ht variations of CBF and oxygen delivery were investigated in patients with ischemic cerebrovascular disease. CBF was measured by the Xe-133 intracarotid injection method in 27 patients, whose diagnoses included completed stroke, reversible ischemic neurological deficit, and transient ischemic attack. Ht values in the patients ranged from 31 to 53%. There was a significant inverse correlation between CBF and Ht in these Ht ranges. Oxygen delivery, i.e., the product of arterial oxygen content and CBF, increased with Ht elevation and reached the maximum level in the Ht range of 40-45% and then declined. The CBF-Ht and oxygen transport-Ht relations observed in our study were similar to those in the glass-tube model studies by other workers rather than to those in intact animal experiments. From these results, it is conceivable that in ischemic cerebrovascular disease, the vasomotor adjustment was impaired in such a manner that the relations among Ht, CBF, and oxygen delivery were different from those in healthy subjects. Further, an "optimal hematocrit" for brain oxygenation was also discussed.     

Significant prognostic factors in breast cancer of Japanese women: special reference to nuclear grade and sinus histiocytosis

Progress of psychotherapy and of related behaviour sciences makes evident the importance of a better understanding of human relations. But psychoanalysis finds it hard to describe interpersonal processes without transference. In order to remain within the conceptional frame of metapsychology it has to see interaction between individuals as the oral, aggressive or sexual cathexis of an object or as satisfaction or denial of the subject by the object. The structure of the "ego", which--in analogy to medical thinking--is conceived as an organ with its functions, is considered to have no interpersonal activities. The "ego" of the classic psychoanalytic theory is chiefly occupied with itself. It has to care for its egoistical interests and to guarantee its self-preservation. As an auxiliary and meanwhile popular concept the "self" has been introduced to describe object-relations. This concept is not sharply defined. Due to its metapsychological implications it produces additional theoretical difficulties. Linguistic studies show that every inventory of words implies a certain insight into reality. For this reason the metapsychological machine-like concept of psychic structures does not permit new ideas about interpersonal relations. If we leave metapsychology and base on colloquial speech we see that the experience of "I" is much more related to persons than the rather autistic concept of the "ego" shows. Further we learn that self-preservation cannot be an egoistical interest; it depends on the attachment to others. All feelings of self-esteem depend much more on interpersonal relations than on "narcissistic regulations". From these experiences three conclusions are derived: a) One of the main qualities of the ego is the relatedness to persons. b) The concept of narcissistic regulation as a successor of primary narcissism is no longer useful. Narcissistic traits develop as the secundary compensations if the individual failed to build up satisfactory interpersonal relations. c) The revision of (a) ego-psychology and (b) theory of narcissism asks for modifications of the therapeutic technique, where now the interest is especially concentrated on interpersonal problems instead on the pathology of the ego.     

SiO2 thin film deposition on the inner surface of a poly(tetra-fluoroethylene) narrow tube by atmospheric-pressure glow microplasma

SiO₂ thin films were deposited on the inner surfaces of a commercial poly(tetrafluoroethylene) narrow tube with an inner diameter of 0.5 mm using tetraethoxysilane/O₂ feedstock gases and He carrier gas by atmospheric-pressure microplasma-enhanced chemical vapor deposition. A glow microplasma was generated inside the tube by radio frequency (RF) capacitively coupled discharge. X-ray photoelectron spectroscopy spectra showed that the tube inner surface was covered by a SiO₂ thin film. Transparent SiO₂ thin films were obtained with a deposition rate of 230 nm/min at an RF power of 6 W and substrate temperature of 100 °C. The wettability of the SiO₂-coated tube was about 3 times as large as that of an untreated sample tube.     

Calculations of impurity doping effects in CrO/sub 2/

The effects of impurity doping in CrO/sub 2/ have been calculated based on the Cr/sub 9/O/sub 40/ cluster using the method of DV-X /spl alpha/ molecular orbital calculation. Elements (Mo, W) belonging to the same family as Cr and the ones (Zr, Ru, Sn) whose dioxides have the same crystalline structure as the rutile were selected for impurity doping. The calculated results show the large enhancements of the magnetic moment and the Curie temperature by the doping of Zr and Ru, respectively.     

Dynamic cluster generation for a fuzzy classifier with ellipsoidalregions

In this paper, we discuss a fuzzy classifier with ellipsoidal regions that dynamically generates clusters. First, for the data belonging to a class we define a fuzzy rule with an ellipsoidal region. Namely, using the training data for each class, we calculate the center and the covariance matrix of the ellipsoidal region for the class. Then we tune the fuzzy rules, i.e., the slopes of the membership functions, successively until there is no improvement in the recognition rate of the training data. Then if the number of the data belonging to a class that are misclassified into another class exceeds a prescribed number, we define a new cluster to which those data belong and the associated fuzzy rule. Then we tune the newly defined fuzzy rules in the similar way as stated above, fixing the already obtained fuzzy rules. We iterate generation of clusters and tuning of the newly generated fuzzy rules until the number of the data belonging to a class that are misclassified into another class does not exceed the prescribed number. We evaluate our method using thyroid data, Japanese Hiragana data of vehicle license plates, and blood cell data. By dynamic cluster generation, the generalization ability of the classifier is improved and the recognition rate of the fuzzy classifier for the test data is the best among the neural network classifiers and other fuzzy classifiers if there are no discrete input variables