Picturing short-period diachronic phenomena in specialised corpora

Terminology ◽  
2011 ◽  
Vol 17 (1) ◽  
pp. 134-156 ◽  
Author(s):  
Aurélie Picton
Keyword(s):  
Original Description ◽  
Short Term ◽  
Knowledge Evolution ◽  
Linguistic Methodology ◽  
Subsequent Research ◽  
Short Period

This article presents a first description and a proposal for the classification of the evolution phenomena involved in short-term diachrony in the field of space. It is based on the principles of Textual Terminology and relies on a tool-based analysis of two diachronic corpora. The linguistic methodology is briefly described but the emphasis is on the list of evolution phenomena revealed through our analysis. These results present an original description of knowledge evolution: 17 types of evolution are listed, revealing the heterogeneity and richness of terminology dynamics and offering a descriptive basis to start new subsequent research that would complete this typology

scholarly journals Using AI-Based Classification Techniques to Process EEG Data Collected during the Visual Short-Term Memory Assessment

2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Milos Antonijevic ◽  
Miodrag Zivkovic ◽  
Sladjana Arsic ◽  
Aleksandar Jevremovic
Keyword(s):  
Visual Information ◽  
Short Term Memory ◽  
Support Vector ◽  
Short Term ◽  
Term Memory ◽  
Memory Assessment ◽  
Visual Short Term Memory ◽  
Eeg Data ◽  
Short Period

Visual short-term memory (VSTM) is defined as the ability to remember a small amount of visual information, such as colors and shapes, during a short period of time. VSTM is a part of short-term memory, which can hold information up to 30 seconds. In this paper, we present the results of research where we classified the data gathered by using an electroencephalogram (EEG) during a VSTM experiment. The experiment was performed with 12 participants that were required to remember as many details as possible from the two images, displayed for 1 minute. The first assessment was done in an isolated environment, while the second assessment was done in front of the other participants, in order to increase the stress of the examinee. The classification of the EEG data was done by using four algorithms: Naive Bayes, support vector, KNN, and random forest. The results obtained show that AI-based classification could be successfully used in the proposed way, since we were able to correctly classify the order of the images presented 90.12% of the time and type of the displayed image 90.51% of the time.

scholarly journals Effects of different returning method combined with decomposer on decomposition of organic components of straw and soil fertility

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiao Wang ◽  
Xuexin Wang ◽  
Peng Geng ◽  
Qian Yang ◽  
Kun Chen ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Fertility ◽  
Decomposition Rate ◽  
Microbial Biomass Carbon ◽  
No Tillage ◽  
Short Term ◽  
Straw Decomposition ◽  
Short Period ◽  
Straw Return ◽  
Forms Of Carbon

AbstractIn view of the problems of low straw decomposition rates and reduced soil fertility in southern Liaoning, China, we investigated the effects of no-tillage mode (NT), deep loosening + deep rotary tillage mode (PT), rotary tillage mode (RT) and the addition of decomposing agent (the next is called a decomposer) (NT + S, PT + S, RT + S) on the decomposition proportion of straw, respectively, by using the nylon net bag method in combination with 365-day field plot experiments. The decomposition rules of cellulose, hemicellulose and lignin as well as the dynamics of soil organic carbon (SOC), soil microbial biomass carbon (MBC) and soil dissolved organic carbon (DOC) in straw returned to the field for 15, 35, 55, 75, 95, 145 and 365 days were analyzed. The results showed that in the short term, the decomposition of straw was better in both the rotray tillage and deep loosening + deep rotary modes than in the no-tillage mode, and the addition of decomposer significantly promoted the decomposition of straw and the release of carbon from straw, among them, the RT + S treatment had the highest straw decomposition proportion and carbon release proportion in all sampling periods. After a one year experimental cycle, the RT + S treatment showed the highest proportion of cellulose, hemicellulose and lignin decomposition with 35.49%, 84.23% and 85.50%, respectively, and soil SOC, MBC and DOC contents were also higher than the other treatments with an increase of 2.30 g kg−1, 14.22 mg kg−1 and 25.10 mg kg−1, respectively, compared to the pre-experimental soil. Our results show that in the short term, to accelerate the decomposition rate of returned straw and increase the content of various forms of carbon in soil, rotary tillage can be used to return the straw to the field, while also spraying straw decomposer on its surface. This experiment used a new straw decomposer rich in a variety of microorganisms, combined with the comparison of a variety of straw return modes, and in-depth study of straw decomposition effects of cellulose, hemicellulose and lignin. Thus, a scheme that can effectively improve the decomposition rate of straw and the content of various forms of organic carbon in soil within a short period of time was explored to provide theoretical support for the southern Liaoning.

scholarly journals Pressure Algometry Evaluation of Two Occlusal Splint Designs in Bruxism Management-Randomized, Controlled Clinical Trial

2021 ◽  
Vol 10 (11) ◽  
pp. 2342
Author(s):  
Bartosz Dalewski ◽  
Agata Kamińska ◽  
Paweł Kiczmer ◽  
Krzysztof Węgrzyn ◽  
Łukasz Pałka ◽  
...  
Keyword(s):  
Pain Threshold ◽  
Pressure Pain Threshold ◽  
Controlled Clinical Trial ◽  
Randomized Controlled Clinical Trial ◽  
Occlusal Splint ◽  
Short Term ◽  
Randomized Controlled ◽  
Canine Guidance ◽  
Medical University

The aim of this pilot study was to evaluate the short-term effectiveness of two different occlusal devices and their impact on the pressure pain threshold (PPT) values among patients who reported to the Dental Prosthetics Outpatient Clinic of Pomeranian Medical University (Szczecin, Poland) and who were diagnosed with probable bruxism. Two groups were formed (A and B) to which patients were assigned randomly. Each group used a different occlusal splint for bruxism management. The occlusal appliance by Okeson, or the bimaxillary splint, was used overnight by each patient for 30 days of the study. The PPT was measured twice, at the first visit and after 30 days of using each occlusal device, with Wagner Paintest FPX 25 algometer. Bruxism was diagnosed based on data from the patient’s medical history and from the physical examination. Nocturnal Bruxism Criteria according to the International Classification of Sleep Disorders (Third Edition) was used for the patient’s evaluation. Results: similar pain factor (PF) reduction was observed in both the examined groups, regardless of the device used; canine guidance and no guidance were similarly effective in terms of increasing pain resilience.

scholarly journals Time-frequency time-space long short-term memory networks for image classification of histopathological tissue

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tuan D. Pham
Keyword(s):  
Image Analysis ◽  
Short Term Memory ◽  
Disease Diagnosis ◽  
Short Term ◽  
Term Memory ◽  
Time Frequency ◽  
Time Space ◽  
Histopathological Images ◽  
Long Short Term Memory

AbstractImage analysis in histopathology provides insights into the microscopic examination of tissue for disease diagnosis, prognosis, and biomarker discovery. Particularly for cancer research, precise classification of histopathological images is the ultimate objective of the image analysis. Here, the time-frequency time-space long short-term memory network (TF-TS LSTM) developed for classification of time series is applied for classifying histopathological images. The deep learning is empowered by the use of sequential time-frequency and time-space features extracted from the images. Furthermore, unlike conventional classification practice, a strategy for class modeling is designed to leverage the learning power of the TF-TS LSTM. Tests on several datasets of histopathological images of haematoxylin-and-eosin and immunohistochemistry stains demonstrate the strong capability of the artificial intelligence (AI)-based approach for producing very accurate classification results. The proposed approach has the potential to be an AI tool for robust classification of histopathological images.

EXPRESS: Short-term upper limb immobilization impairs grasp representation

2020 ◽  
pp. 174702182098552
Author(s):  
Lucette Toussaint ◽  
Aurore Meugnot ◽  
Christel Bidet-Ildei
Keyword(s):  
Response Times ◽  
Motor Program ◽  
Control Group ◽  
Short Term ◽  
Small Sphere ◽  
Large Sphere ◽  
Short Period ◽  
Limb Immobilization ◽  
Laterality Task ◽  
Sensorimotor Processes

The present experiment aimed to gain more information on the effect of limb nonuse on the cognitive level of actions and, more specifically, on the content of the motor program used for grasping an object. For that purpose, we used a hand-grasping laterality task that is known to contain concrete information on manipulation activity. Two groups participated in the experiment: an immobilized group, including participants whose right hand and arm were fixed with a rigid splint and an immobilization vest for 24 hours, and a control group, including participants who did not undergo the immobilization procedure. The main results confirmed a slowdown of sensorimotor processes, which is highlighted in the literature, with slower response times when the participants identified the laterality of hand images that corresponded to the immobilized hand. Importantly, the grip-precision effect, highlighted by slower response times for hands grasping a small sphere versus a large sphere, is impaired by 24 hours of limb nonuse. Overall, this study provided additional evidence of the disengagement of sensorimotor processes due to a short period of limb immobilization.

High Resolution Sequence Stratigraphic Frameworks Research in the XII Group of the Member III of Qing Shankou Formation in the Qian'an Oilfield

2013 ◽  
Vol 339 ◽  
pp. 728-731 ◽  
Author(s):  
Cun Lei Li ◽  
Lei Qin ◽  
Xue Li ◽  
Xi Long Zhang
Keyword(s):  
High Resolution ◽  
Stratigraphic Correlation ◽  
Short Term ◽  
Middle Term ◽  
Sequence Stratigraphic ◽  
Base Level ◽  
Mud Logging ◽  
High Resolution Sequence Stratigraphy ◽  
Symmetric Structures

With the instruction of the high resolution sequence stratigraphy and sedimentology theory, and the comprehensive application of 11 wells core, more than 800 mud logging and log data, high resolution sequence stratigraphic characteristics research in the XII Group of the Member III of Qing Shankou Formation in the Qianan oilfield has been finished. The results show that the study area can be divided into one middle-term base level cycle and five short-term base level cycles. The only sequence structure of middle term cycle is (B type) and the short term cycle mainly consists of B types meanwhile there are small mounts of upward deepening structures (A type) and symmetric structures (C type). Based on the classification of base-level cycles, fine stratigraphic correlation is conducted by using isochronous cycle correlations. In addition, 15 high resolution sequence stratigraphic frameworks are established which unify the study area and provide the solid geological basis for the sandstone distribution, the identification of mainly oil-bearing sand bodies and potential oil reservoirs.

Classification of Technological Development Trends Based on the Analysis of US Patent Time Series. An Empirical Approach

2021 ◽  
pp. 251-278
Author(s):  
Vladimir I. Karnyshev ◽  
◽  
Vladimir I. Avdzeyko ◽  
Evgenia S. Paskal ◽  
◽  
...  
Keyword(s):  
Time Series ◽  
New Technologies ◽  
Practical Interest ◽  
The United States ◽  
Direct Access ◽  
Investment Planning ◽  
Short Term ◽  
Development Trends ◽  
Technical Problems

The forecasting of development trends and the timely revealing of new technical (technological) fields are the key prerequisite for an effective development of modern economy. Only reliable results of technological analysis (forecast) allow identifying new technologies, understanding the evolution of entire industries, carrying out strategic investment planning at the state level, and also planning R&D correctly. The aim of this work is to justify one of the possible approaches to the classification of technical (technological) fields in terms of assessing their relevance, novelty and short-term prospects. This approach is based on patent analysis, in particular, on the study of the time series features of US invention patents (1976-2018) for more than seventy-three thousand main groups (subgroups) of the 17th edition of the International Patent Classification (IPC17). The United States Patent and Trademark Office (USPTO) has been selected as the primary source of information because it is one of the world’s largest and constantly updated patent resources, providing direct access to full-text descriptions. In the authors’ opinion, a feature analysis of the US patent issue dynamics at time intervals (1976-2015, 2009-2018 and 2016-2018) allows dividing the IPC groups (subgroups) into the following three main clusters: “unpromising”, “promising” and “breakthrough”. In terms of the timely revealing of new, previously unknown, technologies or solutions in the technical field, or of the steadily growing technological trends, the “breakthrough” and “promising” subgroups are of the greatest practical interest. The article presents the results of an empirical classification of 71,266 subgroups (with a non-zero number of the issued patents since 1976 to 2018) in eight sections of the IPC17. These data may be useful for developers, researchers and R&D planners in solving complex scientific and technical problems, as well as for making short-term forecast estimates of a specific technical (technological) field development.

THREATS TO NATIONAL SECURITY OF RUSSIA IN THE CONTEXT OF A HYBRID WAR

2021 ◽  
Vol 16 (3) ◽  
pp. 109-130
Author(s):  
A.S. MAKSIMOV ◽  
Keyword(s):  
Synergistic Effect ◽  
National Security ◽  
Negative Impact ◽  
Short Term ◽  
Economic Information ◽  
Hybrid Threats ◽  
Hybrid War ◽  
Political Economic ◽  
Verbal Model

This article is devoted to identifying and characterizing the threat to national security of Russian Federation in the context of a hybrid war. The main aim of the study is to assume that the huge problem for national security of Russia today is the threat of a hybrid nature. This paper proposes the author's classification of hybrid threats, which made it possible to distinguish five functional groups of threats («triads») ‒ in the spiritual and socio-cultural, military-political, economic, information and international legal spheres. The specificity of the «triads» is that each of the three elements of the «triad» is capable of producing the appearance of the second and third elements of the «triad» and maintaining their activity. A variant of ranking «triads» according to the level of their threat intensity is presented, the rates of their intensification in the short term were determined. According to the author's conclusions, the synchronous activity of the «triads» creates a synergistic effect, exerting a complicated negative impact on the state of national security of Russia. The novelty of the research, the results of which are presented in the article, are the classification of hybrid threats and the verbal model of the functioning of the «triads» of threats. The findings of the study can contribute to the development of effective techniques and strategies for countering hybrid threats to national security of Russia.

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