Tools for Assessing the Function of the Upper Extremity in Patients with Stroke: the Prognostic Role of Finger Extension

The purpose of the study was to determine the prognostic role of finger extension and to assess the function of the upper extremity in patients with stroke. Materials and methods. The study was performed on the basis of the Medical Center "Expert Health" and clinical units of Petro Mohyla Black Sea National University, Mykolaiv, Ukraine during 2020-2021. 89 patients who underwent acute cerebrovascular accident by ischemic type with paresis of the upper extremity were examined. All patients were examined in accordance with current clinical protocols in 3 and 6 months after undergoing stroke. Additionally, patients underwent a standard hand function test – Action Research Arm Test, as well as an extended test – Action Research Arm Test +in its own modification (IsoTren LTD). Statistical processing was performed by methods of analysis of variance and correlation using Statisica 13.0 software (TIBCO, USA). Results and discussion. When assessing the functional status of patients, the average values of Barthel Index were 65.4±1.4 points, which corresponded to 2.7±0.3 points by modified Rankin Scale. The main difficulties were observed in such skills as writing (d170), use of means of communication (landline and mobile phone, computer, gadgets – d360), fine motor movements (d440), cooking (d630), eating (d550), washing (d510), personal hygiene (d520) and toilet use (d530), etc. When evaluated according to the standard Action Research Arm Test 3 months after the stroke, the average score was 39.9±1.5, according to the subtest of the Extensors’ Function Assessment Test – 8.3±0.4 points, which corresponds to the overall score for Action Research Arm Test +of 48.1±1.4 points. After 6 months, the score of the Action Research Arm Test 3 months after the stroke, the average score was 43.4±1.2 points ( = +8.8%), according to the subtest of the Extensors’ Function Assessment Test – 9.9±0.4 points ( = +19.3%), which corresponds to the overall score on Action Research Arm Test +of 53.2±1.3 points ( = +10.6%). Correlation analysis showed that the results of the subtest of the Extensors’ Function Assessment Test and Action Research Arm Test significantly correlate with each other (r = 0.72 p <0.01). The developed original test to assess the function of extensors has a specificity of 95.6% with a sensitivity of 98.5% (J = 0.95). This estimate corresponds to LR += 24.75, which allows us to assess the prognostic value of finger extension as very high. When assessing the internal consistency of the standard test Action Research Arm Test and Action Research Arm Test +, it was found that Cronbach = 0.87, which indicates a high degree of consistency of the tests. Conclusion. It is advisable to use the extensor function assessment test together with the standard Action Research Arm Test (modified Action Research Arm Test +)

Deep ChaosNet for Action Recognition in Videos

Current methods of chaos-based action recognition in videos are limited to the artificial feature causing the low recognition accuracy. In this paper, we improve ChaosNet to the deep neural network and apply it to action recognition. First, we extend ChaosNet to deep ChaosNet for extracting action features. Then, we send the features to the low-level LSTM encoder and high-level LSTM encoder for obtaining low-level coding output and high-level coding results, respectively. The agent is a behavior recognizer for producing recognition results. The manager is a hidden layer, responsible for giving behavioral segmentation targets at the high level. Our experiments are executed on two standard action datasets: UCF101 and HMDB51. The experimental results show that the proposed algorithm outperforms the state of the art.

Positive Entropy Using Hecke Operators at a Single Place

We prove the following statement: let $X=\textrm{SL}_n({{\mathbb{Z}}})\backslash \textrm{SL}_n({{\mathbb{R}}})$ and consider the standard action of the diagonal group $A&lt;\textrm{SL}_n({{\mathbb{R}}})$ on it. Let $\mu $ be an $A$-invariant probability measure on $X$, which is a limit $$\begin{equation*} \mu=\lambda\lim_i|\phi_i|^2dx, \end{equation*}$$where $\phi _i$ are normalized eigenfunctions of the Hecke algebra at some fixed place $p$ and $\lambda&gt;0$ is some positive constant. Then any regular element $a\in A$ acts on $\mu $ with positive entropy on almost every ergodic component. We also prove a similar result for lattices coming from division algebras over ${{\mathbb{Q}}}$ and derive a quantum unique ergodicity result for the associated locally symmetric spaces. This generalizes a result of Brooks and Lindenstrauss [2].

Cyclic p-group actions on ℝℙ3

In this paper, we classify the smooth orientation preserving cyclic [Formula: see text]-group actions on the real projective space [Formula: see text] up equivalence, where two actions are equivalent if their images are conjugate in the group of self-diffeomorphisms. We view [Formula: see text] as the lens space [Formula: see text]. We show that any such action on [Formula: see text] is conjugate to a standard action explicitly defined, and we identify the quotient spaces of these actions. In addition, we enumerate the equivalence classes.

Learning Diverse Stochastic Human-Action Generators by Learning Smooth Latent Transitions

Human-motion generation is a long-standing challenging task due to the requirement of accurately modeling complex and diverse dynamic patterns. Most existing methods adopt sequence models such as RNN to directly model transitions in the original action space. Due to high dimensionality and potential noise, such modeling of action transitions is particularly challenging. In this paper, we focus on skeleton-based action generation and propose to model smooth and diverse transitions on a latent space of action sequences with much lower dimensionality. Conditioned on a latent sequence, actions are generated by a frame-wise decoder shared by all latent action-poses. Specifically, an implicit RNN is defined to model smooth latent sequences, whose randomness (diversity) is controlled by noise from the input. Different from standard action-prediction methods, our model can generate action sequences from pure noise without any conditional action poses. Remarkably, it can also generate unseen actions from mixed classes during training. Our model is learned with a bi-directional generative-adversarial-net framework, which can not only generate diverse action sequences of a particular class or mix classes, but also learns to classify action sequences within the same model. Experimental results show the superiority of our method in both diverse action-sequence generation and classification, relative to existing methods.

Further Understanding Videos through Adverbs: A New Video Task

Video understanding is a research hotspot of computer vision and significant progress has been made on video action recognition recently. However, the semantics information contained in actions is not rich enough to build powerful video understanding models. This paper first introduces a new video semantics: the Behavior Adverb (BA), which is a more expressive and difficult one covering subtle and inherent characteristics of human action behavior. To exhaustively decode this semantics, we construct the Videos with Action and Adverb Dataset (VAAD), which is a large-scale dataset with a semantically complete set of BAs. The dataset will be released to the public with this paper. We benchmark several representative video understanding methods (originally for action recognition) on BA and action recognition. The results show that BA recognition task is more challenging than conventional action recognition. Accordingly, we propose the BA Understanding Network (BAUN) to solve this problem and the experiments reveal that our BAUN is more suitable for BA recognition (11% better than I3D). Furthermore, we find these two semantics (action and BA) can propel each other forward to better performance: promoting action recognition results by 3.4% averagely on three standard action recognition datasets (UCF-101, HMDB-51, Kinetics).

A Comprehensive Review Article on Energy Efficiency Protocols in Wireless Sensor Networks

Several location-based programs depend on fine-grained checking of portable items that establish their particular places with feeling products like GPS receivers. For these items, power is just a really useful and restricted resource. A distance-based confirming project could be used to lessen the power they digest by giving place updates. But, the power necessary for place feeling hasn't been regarded in the past. In that report, we examine how a ensuing power usage from equally feeling and upgrade procedures could be paid off for distance-based reporting. We reveal that substantial savings are accomplished by giving place changes sooner than really required. For standard action, we get the small energy usage analytically. Eventually, two story on the web heuristics are planned that get a grip on the giving of place changes at runtime. Their efficiency is validated by considerable simulations.

Topological rigidity of quasitoric manifolds

Quasitoric manifolds are manifolds that admit an action of the torus that is locally the same as the standard action of $T^n$ on $\mathbb{C}^n$. It is known that the quotients of such actions are nice manifolds with corners. We prove that a class of locally standard manifolds, that contains the quasitoric manifolds, is equivariantly rigid, i.e., that any manifold that is $T^n$-homotopy equivalent to a quasitoric manifold is $T^n$-homeomorphic to it.

Divine Action in the Christian Life in Teresa of Avila

In this chapter, the author articulates and examines what Teresa of Avila claims about divine action and human action in the Christian life, or in her terms, the Christian soul. The author pays critical attention to her work The Interior Castle, which charts her journey in grace within the framework of the doctrinal and liturgical life of the church. He notes that there is little treatment of the standard action verbs latent in the tradition, like regeneration, justification, and baptism in the Spirit. This is due to the fact that she is relying not on theological inquiries for her work, but her own personal journey in the church with the help of confessors. Teresa thus expands the horizon of what God can do in the life of the church and in the individual believer.