Features of the choice of potato (Solanum tuberosum) varieties when growing two harvests in the temperate zone of Russia.

The development of potato plants during the cultivation of two crops occurs in a short period. At the same time, field conditions change and do not repeat over time. The formation of the crop during the cultivation of two crops in the Moscow region turns out to be in different growing conditions: the first crop falls on a long day and moderate temperatures, as well as sometimes returning frosts, the second crop falls on a short day and high temperatures, as well as a lack of moisture. The purpose of our research was to substantiate the choice of varieties for cultivation of two crops. Its solution is possible with a certain guaranteed efficiency based on the theory of statistical games. The research was carried out at the Vegetable Experimental Station of the Moscow State Agrarian University named after K.A. Timiryazev and at the Central Experimental Station of the Barybino Research Institute of Agrochemistry of the Moscow Region 2017-2022. The experiment was laid by the method of random placement of plots, the predecessor was a bow. The planting density is 47.6 thousand plants per 1 ha. Germinated tubers were used for planting during the first planting of a large fraction, during the second planting of an average fraction. The second landing was carried out on the vacant place after cleaning the first landing. The cultivation technology is standard. Cleaning was carried out in mid-July and at the end of September. Statistical game theory was used to determine the choice of a variety with a certain guaranteed efficiency. As a result of forecasting in critical climatic conditions, it is necessary to plant 1 crop - varieties Riviera and for 2 crops - varieties Luck.

Relative contribution of ankle and hip muscles in regulation of the human orthograde posture in a frontal plane.

It was investigated, whether the postural regulation in the frontal plane takes place mainly at the hip or at the ankle level. The elimination of ankle torque was achieved by providing a point support in the frontal plane. (Two boards were attached to subject feet, below each board a metal pipe 2 cm diameter was fixed, so, the subject stood on contrivances resembling 'skates'). The lateral displacements of breast and hip, the angle of 'skates' tilt and the characteristics of frontal stabilogram and electromyogram of two ankle muscles (m. peroneus and m. soleus) were compared in two situations: (1) during normal standing; (2) under the conditions of the exclusion of ankle torque from postural control. During normal standing the body behaved as two-link inverted pendulum. Transition from normal standing to standing on free 'skates' produced changes in the kinematics of body movement. Under the conditions of ankle torque exclusion (free 'skates') breast and hip of a subject moved in a frontal plane as a single unit (one-link inverted pendulum). During standing on free 'skates' the electromyographic activity of m. peroneus and m. soleus was the same as during normal standing (approximately 70-100 microV).

Postural instability enhances motor responses to transcranial magnetic stimulation in humans.

Does the state of postural instability require a high hierarchical level of posture control? Electromyographic (EMG) activity of leg muscles was recorded during transcranial magnetic stimulation (TMS) of the motor cortex and electrical stimulation of the tibial nerve (H-reflex) in healthy subjects standing on a rigid floor and on a rocking platform. In the soleus muscle, TMS-evoked EMG responses increased considerably (2.2+/-1.1 times) when balancing on the rocking platform, whilst the H-reflex tended to decrease. The effect of support instability was specific to the muscles participating in the posture control. The results suggest that postural instability might change the state and the role of the motor cortex in equilibrium maintenance.

A multi-step approach to time series analysis and gene expression clustering.

MOTIVATION: The huge growth in gene expression data calls for the implementation of automatic tools for data processing and interpretation. RESULTS: We present a new and comprehensive machine learning data mining framework consisting in a non-linear PCA neural network for feature extraction, and probabilistic principal surfaces combined with an agglomerative approach based on Negentropy aimed at clustering gene microarray data. The method, which provides a user-friendly visualization interface, can work on noisy data with missing points and represents an automatic procedure to get, with no a priori assumptions, the number of clusters present in the data. Cell-cycle dataset and a detailed analysis confirm the biological nature of the most significant clusters. AVAILABILITY: The software described here is a subpackage part of the ASTRONEURAL package and is available upon request from the corresponding author. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.