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    Use "implex" in a sentence

    implex example sentences

    implex


    1. 'SimpleXmlElement was instantiated correctly


    2. Herpes Simplex: 1,000-3,000 mg per day is the usual daily dosage in the treatment or prevention of herpes I and


    3. A cold sore, sometimes called a fever blister is an infection with the Herpes Simplex I Virus (HSV-I)


    4. herpes virus, most often the herpes simplex 1 virus


    5. Genital herpes infection (usually caused by herpes simplex 2) is a related condition and potentially may be treated in much the same way as herpes


    6. The herpes simplex virus has a high requirement for the amino acid, arginine


    7. Although people with herpes simplex reportedly consume about the same amount of


    8. The amino acid, lysine, has been reported to reduce the recurrence rate of herpes simplex infections in both preliminary and double-blind trials


    9. Zinc preparations have been shown to inhibit the replication of herpes simplex in the test tube


    10. In one study, people with recurrent herpes simplex infections applied a zinc

    11. probably ineffective as a treatment for herpes simplex


    12. The proanthocyanidins in witch hazel have been shown to exert significant antiviral activity against herpes simplex 1 in the test tube


    13. John’s Wort and soapwort (Saponaria officinalis), has been found to inhibit the herpes simplex virus in the test tube


    14. The lesions filled with fluid caused by the herpes simplex virus can be really embarrassing and annoying


    15. There are studies which have revealed that the catechins along with flavenoids in green tea can inhibit influenza viruses, the herpes simplex virus, the human papillomavirus and even HIV


    16. Another trial has shown that the flavenoids and catechins can inhibit the herpes simplex virus


    17. There are also indications that these powerful chemical compounds can actually inhibit more dangerous viruses, such as herpes simplex and even HIV


    18. The Nelder-Mead method (also called the deformable polyhedron method, simplex search, or amoeba search method) has two modifications: original variant (based on rectilinear simplex) and advanced modification (which utilizes deformable simplex)


    19. Using the term “simplex” may be misleading to some extent since there is a widely known simplex method of linear programming developed to solve the problem of optimization with linear objective function and linear constraints that has nothing to do with the described method


    20. In the Nelder-Mead method the simplex represents the polyhedron in n-dimensional space with n+1 vertices

    21. The triangle is an example of the simplex in two-dimensional space


    22. Figuratively speaking, during optimization the simplex rolls over the parameters space, gradually approaching the extreme


    23. Having calculated the objective function values in the vertices of the simplex, we find the worst of them and move the simplex so that all other vertices stay at their places and the vertex with the worst value is substituted with the vertex that is symmetrical to the worst one relative to the simplex center


    24. This can be imagined visually in the two-dimensional case when the simplex (represented by the triangle) rolls over its side that is opposite to the worst apex


    25. By repeating such cycles, the simplex approaches the extreme until the objective function is no longer improved


    26. When the simplex is in the immediate vicinity of the extreme, so that the distance from its center to the extreme is less than the simplex side, it loses the capability to approach the extreme any closer


    27. In this case we can decrease the simplex size, while maintaining its initial shape and continue our search by repeating the size decrease each time when we lose the capability to get closer to the extreme, until the side length becomes smaller than the optimization step


    28. Select n+1 points of the initial simplex x1, x2


    29. In the two-dimensional case, when the simplex represents the triangle, it is sufficient that three points are not located on the same straight line


    30. Calculate point x0, which is the center of the figure whose vertices coincide with simplex vertices, except the worst one xn+1:

    31. If the objective function value at the reflected point is better than at the second-worst point xn, but is not better than at the best point x1, then the reflected point substitutes in the simplex the excluded worst point and the algorithm returns to step 2 (simplex rolls over from the worst point toward the point with a higher objective function value)


    32. The essence of this operation is the following: If the direction in which the objective function increases is established, the simplex should be expanded in this direction


    33. If the expansion point is better than the reflection point, the latter is substituted in the simplex by this expansion point and the simplex becomes expanded in this direction


    34. If the expansion point is not better than the reflected point, there is no sense in expansion, the reflected point is left in the simplex and its shape does not change


    35. As a result, the simplex contracts in this direction


    36. If the obtained point is worse than the worst point, it may testify to the fact that we are already in the immediate vicinity of the extreme, and to find it the simplex size has to be decreased


    37. Select three points of the initial simplex


    38. Assume that nodes with coordinates 12 and 105, 18 and 110, 18 and 100 are selected as simplex vertexes


    39. Calculate the values of the objective function for the three points of the initial simplex and find the node with the worst function value


    40. Since the objective function value in the reflected point is better than in all points of the initial simplex, the algorithm passes on to the expansion step

    41. It is found by doubling the distance between the simplex center and the second point


    42. 4) has a higher objective function value as compared to node number 2 and hence substitutes for the latter becoming the new vertex of the simplex


    43. Since the objective function value in the reflected point is lower than in the second-worst point of the previous simplex, the algorithm passes on to the contraction step


    44. Since this node is better than the worst one in the previous simplex, but is not the best, the algorithm passes on to the reflection step


    45. Since the objective function value in this node is lower than in all points of the previous simplex, the algorithm passes on to the contraction step


    46. Another, simpler approach consists in selecting the optimal solution among vertices of the last simplex (the one having the highest objective function value)


    47. Perhaps, the reason is that the initial conditions (the simplex size) and the values of its numerous coefficients (reflection, contraction, reduction, and expansion) should be thoroughly selected to implement this method effectively


    48. We selected the simplex size arbitrarily and applied commonly used values for the coefficients


    49. To obtain satisfactory results, we should probably define the coefficients more deliberately and select the initial simplex on the basis of some a priori assumptions about the optimization space properties


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