The training process： Planning for strength-power training in track and field. Part 2： Practical and applied aspects

Planning training programs for strength-power track and field athletes require an understanding of both training principles and training theory. The training principles are overload, variation, and specificity. Each of these principles must be incorporated into an appropriate system of training. Conceptually, periodization embraces training principles and offers advantages in planning, allowing for logical integration and manipulation of training variables such as exercise selection, intensification, and volume factors. The adaptation and progress of the athlete is to a large extent directly related to the ability of the coach/athlete to create and carry an efficient and efficacious training process. This ability includes： an understanding of how exercises affect physiological and performance adaptation （i.e., maximum force, rate of force development, power, etc.）, how to optimize transfer of training effect ensuring that training exercises have maximum potential for carryover to performance, and how to implement programs with variations at appropriate levels （macro, meso, and micro） such that fatigue management is enhanced and performance progress is optimized.

The training process： Planning for strength-power training in track and field. Part 1： Theoretical aspects

The process of strength-power training and the subsequent adaptation is a multi-factorial process. These factors range from the genetics and morphological characteristics of the athlete to how a coach selects, orders, and doses exercises and loading patterns. Consequently, adaptation from these training factors may largely relate to the mode of delivery, in other words, programming tactics. There is strong evidence that the manner and phases in which training is presented to the athlete can make a profound difference in performance outcome. This discussion deals primarily with block periodization concepts and associated methods of programming for strength-power training within track and field. 2015 Production and hosting by Elsevier B.V. on behalf of Shanghai University of Sport.

Past review,current progress,and challenges ahead on the cocktail party problem

The cocktail party problem,i.e.,tracing and recognizing the speech of a specific speaker when multiple speakers talk simultaneously,is one of the critical problems yet to be solved to enable the wide application of automatic speech recognition(ASR) systems.In this overview paper,we review the techniques proposed in the last two decades in attacking this problem.We focus our discussions on the speech separation problem given its central role in the cocktail party environment,and describe the conventional single-channel techniques such as computational auditory scene analysis(CASA),non-negative matrix factorization(NMF) and generative models,the conventional multi-channel techniques such as beamforming and multi-channel blind source separation,and the newly developed deep learning-based techniques,such as deep clustering(DPCL),the deep attractor network(DANet),and permutation invariant training(PIT).We also present techniques developed to improve ASR accuracy and speaker identification in the cocktail party environment.We argue effectively exploiting information in the microphone array,the acoustic training set,and the language itself using a more powerful model.Better optimization ob jective and techniques will be the approach to solving the cocktail party problem.