scholarly journals Sentence Recall in Latent and Anomic Aphasia: An Exploratory Study of Semantics and Syntax

2021 ◽  
Vol 11 (2) ◽  
pp. 230
Author(s):  
Christos Salis ◽  
Nadine Martin ◽  
Laura Reinert
Keyword(s):  
Real Time ◽  
Short Term Memory ◽  
Recall Performance ◽  
Syntactic Complexity ◽  
Control Groups ◽  
Short Term ◽  
Sentence Recall ◽  
Semantic Plausibility ◽  
Verbatim Recall ◽  
And Control

We investigated whether semantic plausibility and syntactic complexity affect immediate sentence recall in people with latent and anomic aphasia. To date, these factors have not been explored in these types of aphasia. As with previous studies of sentence recall, we measured accuracy of verbatim recall and uniquely real-time speech measures. The results showed that accuracy did not distinguish performance between latent aphasia and neurotypical controls. However, some of the real-time speech measures distinguished performance between people with latent aphasia and neurotypical controls. There was some evidence, though not pervasive, that semantic plausibility and syntactic complexity influenced recall performance. There were no interactions between semantic plausibility and syntactic complexity. The speed of preparation of responses was slower in latent aphasia than controls; it was also slower in anomic aphasia than both latent and control groups. It appears that processing speed as indexed by temporal speech measures may be differentially compromised in latent and anomic aphasia. However, semantic plausibility and syntactic complexity did not show clear patterns of performance among the groups. Notwithstanding the absence of interactions, we advance an explanation based on conceptual short-term memory as to why semantically implausible sentences are typically more erroneous and possibly also slower in recall.

scholarly journals Real-Time Detection of Dictionary DGA Network Traffic Using Deep Learning

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
Kate Highnam ◽  
Domenic Puzio ◽  
Song Luo ◽  
Nicholas R. Jennings
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Real Time ◽  
Network Traffic ◽  
Short Term Memory ◽  
Domain Names ◽  
Control Networks ◽  
Detection Techniques ◽  
Lstm Network ◽  
And Control

AbstractBotnets and malware continue to avoid detection by static rule engines when using domain generation algorithms (DGAs) for callouts to unique, dynamically generated web addresses. Common DGA detection techniques fail to reliably detect DGA variants that combine random dictionary words to create domain names that closely mirror legitimate domains. To combat this, we created a novel hybrid neural network, Bilbo the “bagging” model, that analyses domains and scores the likelihood they are generated by such algorithms and therefore are potentially malicious. Bilbo is the first parallel usage of a convolutional neural network (CNN) and a long short-term memory (LSTM) network for DGA detection. Our unique architecture is found to be the most consistent in performance in terms of AUC, $$F_1$$ F 1 score, and accuracy when generalising across different dictionary DGA classification tasks compared to current state-of-the-art deep learning architectures. We validate using reverse-engineered dictionary DGA domains and detail our real-time implementation strategy for scoring real-world network logs within a large enterprise. In 4 h of actual network traffic, the model discovered at least five potential command-and-control networks that commercial vendor tools did not flag.

scholarly journals Reading comprehension on the last grades of cicles I and II of elementary school

CoDAS ◽  
2014 ◽  
Vol 26 (4) ◽  
pp. 276-285
Author(s):  
Eliane Mi Chang ◽  
Clara Regina Brandão de Avila
Keyword(s):  
Working Memory ◽  
Elementary School ◽  
Reading Comprehension ◽  
Research Groups ◽  
Control Groups ◽  
Short Term ◽  
Good Readers ◽  
Spearman Coefficient ◽  
Positive Correlations ◽  
And Control

PURPOSE: To characterize students' performance in Cycle I and II of the Elementary School (EF), in decoding, reading comprehension and underlying skills of reading, and investigate correlations between these variables, in the absence and presence of reading comprehension deficits, identified by their teachers.METHODS: 125 students from ES were grouped according to Cycle and presence or absence of reading comprehension impairments. Two Control (good readers from both Cycles) and two Research groups (poor readers from both Cycles) were established. Assessment involved: fluency and reading comprehension; oral comprehension; working and short-term phonological memory; grammar closure. It was compared (Mann-Whitney test): in intragroup study, both Control and Research groups; in intergroup study, Control and Research from different cycles, and Control I and Research II. Spearman coefficient investigated correlations.RESULTS: Analyzing reading comprehension, we observed better performance of Control Groups in all tasks in comparison to the respective Research Groups, and better performance of Control II in comparison to Control I. Research Groups had similar results in most tests. Positive correlations have been observed between most of the variables.CONCLUSION: Students without reading comprehension impairments showed better performance in reading in both Cycles. Working memory and oral comprehension did not differentiate students with and without complaints in Cycle I, differently from what was observed in Cycle II. Research II presented similar or better performance than Research I and similar or worse performance than Control I. Underlying skills showed different profiles of correlation with reading comprehension capacity, according to the group.

scholarly journals Efficient Deep Learning Models for DGA Domain Detection

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Juhong Namgung ◽  
Siwoon Son ◽  
Yang-Sae Moon
Keyword(s):  
Deep Learning ◽  
Short Term Memory ◽  
Ensemble Model ◽  
Learning Models ◽  
Short Term ◽  
Domain Names ◽  
Additional Information ◽  
Domain Sequence ◽  
Long Short Term Memory ◽  
And Control

In recent years, cyberattacks using command and control (C&C) servers have significantly increased. To hide their C&C servers, attackers often use a domain generation algorithm (DGA), which automatically generates domain names for the C&C servers. Accordingly, extensive research on DGA domain detection has been conducted. However, existing methods cannot accurately detect continuously generated DGA domains and can easily be evaded by an attacker. Recently, long short-term memory- (LSTM-) based deep learning models have been introduced to detect DGA domains in real time using only domain names without feature extraction or additional information. In this paper, we propose an efficient DGA domain detection method based on bidirectional LSTM (BiLSTM), which learns bidirectional information as opposed to unidirectional information learned by LSTM. We further maximize the detection performance with a convolutional neural network (CNN) + BiLSTM ensemble model using Attention mechanism, which allows the model to learn both local and global information in a domain sequence. Experimental results show that existing CNN and LSTM models achieved F1-scores of 0.9384 and 0.9597, respectively, while the proposed BiLSTM and ensemble models achieved higher F1-scores of 0.9618 and 0.9666, respectively. In addition, the ensemble model achieved the best performance for most DGA domain classes, enabling more accurate DGA domain detection than existing models.

Perceptual Organization and Grouping Factors: Age Related Effects

1994 ◽  
Vol 38 (2) ◽  
pp. 170-174
Author(s):  
Darryl G. Humphrey ◽  
Arthur F. Kramer ◽  
Sheryl S. Gore
Keyword(s):  
Older Adults ◽  
Perceptual Organization ◽  
Short Term Memory ◽  
Recall Performance ◽  
Partial Report ◽  
Visual Environment ◽  
Short Term ◽  
Visual Short Term Memory ◽  
Information Displays ◽  
Age Related

Older adults have evidenced a poorer ability to use grouping factors in such tasks as Embedded Figures, Incomplete Figures, and partial report. Difficulties in disambiguating the findings of these studies has left unanswered the cause of this age-related difference. By taking into account age-related differences in visual short-term memory, the results of the current study suggest that older adults maintain the ability to capitalize on the perceptual organization of the visual environment as a means of facilitating recall performance. These results have implications for the design of information displays, product labels, codes, and instructions.

High physiological levels of epinephrine do not enhance muscle glycogenolysis during tetanic stimulation

1994 ◽  
Vol 77 (2) ◽  
pp. 956-962 ◽  
Author(s):  
A. Chesley ◽  
D. J. Dyck ◽  
L. L. Spriet
Keyword(s):  
Tetanic Stimulation ◽  
Control Groups ◽  
Perfusion Medium ◽  
Short Term ◽  
Muscle Lactate ◽  
Rest Perfusion ◽  
Train Duration ◽  
Fast Twitch ◽  
And Control ◽  
White Gastrocnemius

This study examined whether high physiological concentrations of epinephrine (EPI) would enhance muscle glycogenolysis during intense muscular contractions. Muscles of the rat hindlimb were perfused for 12 min at rest and 45 s of tetanic stimulation (1.0-Hz train rate, 100-ms train duration at 80 Hz) without EPI (control) or with 15 or 35 nM EPI. In the EPI groups the muscles were perfused with EPI for the last 2 min of rest perfusion and throughout stimulation. Glycogenolysis in the white gastrocnemius, red gastrocnemius, plantaris, and soleus muscles during stimulation was unaffected by the presence of EPI in the perfusion medium. In addition, muscle lactate and hindlimb lactate efflux were similar in EPI and control groups. It is concluded that EPI is not important for enhancing glycogenolysis in rat muscles composed predominantly of fast-twitch fibers during intense short-term tetanic stimulation.

Decoding Movements from Cortical Ensemble Activity Using a Long Short-Term Memory Recurrent Network

2019 ◽  
Vol 31 (6) ◽  
pp. 1085-1113 ◽  
Author(s):  
Po-He Tseng ◽  
Núria Armengol Urpi ◽  
Mikhail Lebedev ◽  
Miguel Nicolelis
Keyword(s):  
Real Time ◽  
Short Term Memory ◽  
Unscented Kalman Filter ◽  
Bipedal Walking ◽  
Motor Tasks ◽  
Short Term ◽  
Term Memory ◽  
Cortical Areas ◽  
Long Short Term Memory ◽  
Ensemble Activity

Although many real-time neural decoding algorithms have been proposed for brain-machine interface (BMI) applications over the years, an optimal, consensual approach remains elusive. Recent advances in deep learning algorithms provide new opportunities for improving the design of BMI decoders, including the use of recurrent artificial neural networks to decode neuronal ensemble activity in real time. Here, we developed a long-short term memory (LSTM) decoder for extracting movement kinematics from the activity of large ( N = 134–402) populations of neurons, sampled simultaneously from multiple cortical areas, in rhesus monkeys performing motor tasks. Recorded regions included primary motor, dorsal premotor, supplementary motor, and primary somatosensory cortical areas. The LSTM's capacity to retain information for extended periods of time enabled accurate decoding for tasks that required both movements and periods of immobility. Our LSTM algorithm significantly outperformed the state-of-the-art unscented Kalman filter when applied to three tasks: center-out arm reaching, bimanual reaching, and bipedal walking on a treadmill. Notably, LSTM units exhibited a variety of well-known physiological features of cortical neuronal activity, such as directional tuning and neuronal dynamics across task epochs. LSTM modeled several key physiological attributes of cortical circuits involved in motor tasks. These findings suggest that LSTM-based approaches could yield a better algorithm strategy for neuroprostheses that employ BMIs to restore movement in severely disabled patients.

Subhypnotic dose of intravenous propofol stimulates appetite in cats with stress-induced anorexia

2020 ◽  
Vol 187 (8) ◽  
pp. e58-e58
Author(s):  
Victry Fredley ◽  
Rachael Kreisler ◽  
Kirk Miller
Keyword(s):  
Treatment Group ◽  
Control Groups ◽  
Short Term ◽  
Onset Of Action ◽  
Adverse Side Effects ◽  
Delayed Onset ◽  
Wilcoxon Rank Sum Test ◽  
And Control ◽  
Median Amount ◽  
Food Consumed

BackgroundStress-induced anorexia is common in cats. While medications are available to stimulate appetite, many require oral administration, have delayed onset-of-action or cause adverse side effects. The aim of this study was to determine whether cats diagnosed with stress-induced anorexia given a subhypnotic dose of intravenous propofol would have increased short-term appetite as compared to those given placebo.MethodsAnorexic shelter cats received either 1 mg/kg propofol or 1 mL saline placebo and then presented with various commercial cat foods. Grams of food consumed was measured at 15 and 30 min, and total grams compared between treatment and control groups using the Wilcoxon rank-sum test. 12 cats were enrolled, with six cats randomly assigned to each group.ResultsThe median amount consumed by the treatment group was 31 g (range: 0–72), with the median for the four cats (67 per cent) who consumed food being 45 g (range: 26–72), or 49 per cent of their daily maintenance calorie requirement. The median amount consumed by control cats was 0 g (range: 0–5), with one cat consuming food. Total grams consumed was different between treatment and control groups (P=0.05).ConclusionA subhypnotic dose of intravenous propofol increased appetite in cats with stress-induced anorexia for a 30 min period.

scholarly journals Inner speech is used to mediate short-term memory, but not planning, among intellectually high-functioning adults with autism spectrum disorder

2012 ◽  
Vol 24 (1) ◽  
pp. 225-239 ◽  
Author(s):  
David M. Williams ◽  
Dermot M. Bowler ◽  
Christopher Jarrold
Keyword(s):  
Autism Spectrum Disorder ◽  
Articulatory Suppression ◽  
Short Term Memory ◽  
Recall Performance ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Inner Speech ◽  
Short Term ◽  
Order Problem ◽  
Term Memory

AbstractEvidence regarding the use of inner speech by individuals with autism spectrum disorder (ASD) is equivocal. To clarify this issue, the current study employed multiple techniques and tasks used across several previous studies. In Experiment 1, participants with and without ASD showed highly similar patterns and levels of serial recall for visually presented stimuli. Both groups were significantly affected by the phonological similarity of items to be recalled, indicating that visual material was spontaneously recoded into a verbal form. Confirming that short-term memory is typically verbally mediated among the majority of people with ASD, recall performance among both groups declined substantially when inner speech use was prevented by the imposition of articulatory suppression during the presentation of stimuli. In Experiment 2, planning performance on a tower of London task was substantially detrimentally affected by articulatory suppression among comparison participants, but not among participants with ASD. This suggests that planning is not verbally mediated in ASD. It is important that the extent to which articulatory suppression affected planning among participants with ASD was uniquely associated with the degree of their observed and self-reported communication impairments. This confirms a link between interpersonal communication with others and intrapersonal communication with self as a means of higher order problem solving.

Sign in / Sign up

Export Citation Format

Share Document