Mental workload plays a vital role in cognitive impairment. The impairment refers to a person’s difficulty in remembering, receiving new information, learning new things, concentrating, or making decisions that serio...Mental workload plays a vital role in cognitive impairment. The impairment refers to a person’s difficulty in remembering, receiving new information, learning new things, concentrating, or making decisions that seriously affect everyday life. In this paper, the simultaneous capacity (SIMKAP) experiment-based EEG workload analysis was presented using 45 subjects for multitasking mental workload estimation with subject wise attention loss calculation as well as short term memory loss measurement. Using an open access preprocessed EEG dataset, Discrete wavelet transforms (DWT) was utilized for feature extraction and Minimum redundancy and maximum relevancy (MRMR) technique was used to select most relevance features. Wavelet decomposition technique was also used for decomposing EEG signals into five sub bands. Fourteen statistical features were calculated from each sub band signal to form a 5 × 14 window size. The Neural Network (Narrow) classification algorithm was used to classify dataset for low and high workload conditions and comparison was made using some other machine learning models. The results show the classifier’s accuracy of 86.7%, precision of 84.4%, F1 score of 86.33%, and recall of 88.37% that crosses the state-of-the art methodologies in the literature. This prediction is expected to greatly facilitate the improved way in memory and attention loss impairments assessment.展开更多
In today’s world, there are many people suffering from mentalhealth problems such as depression and anxiety. If these conditions are notidentified and treated early, they can get worse quickly and have far-reachingne...In today’s world, there are many people suffering from mentalhealth problems such as depression and anxiety. If these conditions are notidentified and treated early, they can get worse quickly and have far-reachingnegative effects. Unfortunately, many people suffering from these conditions,especially depression and hypertension, are unaware of their existence until theconditions become chronic. Thus, this paper proposes a novel approach usingBi-directional Long Short-Term Memory (Bi-LSTM) algorithm and GlobalVector (GloVe) algorithm for the prediction and treatment of these conditions.Smartwatches and fitness bands can be equipped with these algorithms whichcan share data with a variety of IoT devices and smart systems to betterunderstand and analyze the user’s condition. We compared the accuracy andloss of the training dataset and the validation dataset of the two modelsnamely, Bi-LSTM without a global vector layer and with a global vector layer.It was observed that the model of Bi-LSTM without a global vector layer hadan accuracy of 83%,while Bi-LSTMwith a global vector layer had an accuracyof 86% with a precision of 86.4%, and an F1 score of 0.861. In addition toproviding basic therapies for the treatment of identified cases, our model alsohelps prevent the deterioration of associated conditions, making our methoda real-world solution.展开更多
The unloading relaxation caused by excavation for construction of high arch dams is an important factor influencing the foundation’s integrity and strength.To evaluate the degree of unloading relaxation,the long-shor...The unloading relaxation caused by excavation for construction of high arch dams is an important factor influencing the foundation’s integrity and strength.To evaluate the degree of unloading relaxation,the long-short term memory(LSTM)network was used to estimate the depth of unloading relaxation zones on the left bank foundation of the Baihetan Arch Dam.Principal component analysis indicates that rock charac-teristics,the structural plane,the protection layer,lithology,and time are the main factors.The LSTM network results demonstrate the unloading relaxation characteristics of the left bank,and the relationships with the factors were also analyzed.The structural plane has the most significant influence on the distribution of unloading relaxation zones.Compared with massive basalt,the columnar jointed basalt experiences a more significant unloading relaxation phenomenon with a clear time effect,with the average unloading relaxation period being 50 d.The protection layer can effectively reduce the unloading relaxation depth by approximately 20%.展开更多
Objective To evaluate whether the thermotaxis tracking model is suitable for assessing long-term memory (LTM) in the nematode Caenorhabditis elegans. Methods Animals were trained at 20℃ overnight in presence of foo...Objective To evaluate whether the thermotaxis tracking model is suitable for assessing long-term memory (LTM) in the nematode Caenorhabditis elegans. Methods Animals were trained at 20℃ overnight in presence of food. The percentage of animals performing isothermal tracking (IT) behavior was measured at different time intervals after the training. Results The percentage of animals performing IT behavior, the numbers of body bends inside and outside the training temperature, and the expression patterns of AFD and AIY neurons were similar to those in control animals at 36 and 48 h after training; whereas when extending to 60, 72, and 84 h, locomotory behavior defects were observed in the assayed animals, suggesting that this thermal tracking model is feasible for analyzing LTM at 36 and 48 h after training. Moreover, the percent-age of animals performing IT behavior was reduced at 18, 36, and 48 h after training in neuronal calcium sensor-1 gene (nsc-1) mutant animals compared with that in wild-type N2 animals. In addition, exposure to plumbum (Pb) significantly repressed the LTM at 18, 36, and 48 h after training in both wild-type N2 and ncs-1 mutant animals. Conclusion The thermotaxis tracking model is suitable for evaluating the LTM regulated by NCS-1, and can be employed for elucidating regulatory functions of specific genes or effects of stimuli on memory in C. elegans.展开更多
Objective To gain a better understanding of gene expression changes in the brain following microwave exposure in mice. This study hopes to reveal mechanisms contributing to microwave-induced learning and memory dysfun...Objective To gain a better understanding of gene expression changes in the brain following microwave exposure in mice. This study hopes to reveal mechanisms contributing to microwave-induced learning and memory dysfunction. Methods Mice were exposed to whole body 2100 MHz microwaves with specific absorption rates (SARs) of 0.45 W/kg, 1.8 W/kg, and 3.6 W/kg for 1 hour daily for 8 weeks. Differentially expressing genes in the brains were screened using high-density oligonucleotide arrays, with genes showing more significant differences further confirmed by RT-PCR. Results The gene chip results demonstrated that 41 genes (0.45 W/kg group), 29 genes (1.8 W/kg group), and 219 genes (3.6 W/kg group) were differentially expressed. GO analysis revealed that these differentially expressed genes were primarily involved in metabolic processes, cellular metabolic processes, regulation of biological processes, macromolecular metabolic processes, biosynthetic processes, cellular protein metabolic processes, transport, developmental processes, cellular component organization, etc. KEGG pathway analysis showed that these genes are mainly involved in pathways related to ribosome, Alzheimer's disease, Parkinson's disease, long-term potentiation, Huntington's disease, and Neurotrophin signaling. Construction of a protein interaction network identified several important regulatory genes including synbindin (sbdn), Crystallin (CryaB), PPP1CA, Ywhaq, Psap, Psmb1, Pcbp2, etc., which play important roles in the processes of learning and memory. Conclusion Long-term, low-level microwave exposure may inhibit learning and memory by affecting protein and energy metabolic processes and signaling pathways relating to neurological functions or diseases.展开更多
Activity-regulated cytoskeleton-associated protein (Arc/Arg3.1) was originally identified in patients with seizures. It is densely distributed in the hip-pocampus and amygdala in particular. Because the expression of ...Activity-regulated cytoskeleton-associated protein (Arc/Arg3.1) was originally identified in patients with seizures. It is densely distributed in the hip-pocampus and amygdala in particular. Because the expression of Arc/Arg3.1 is regulated by nerve in-puts, it is thought to be an immediate early gene. As shown both in vitro and in vivo, Arc/Arg3.1 is in-volved in synaptic consolidation and regulates some forms of learning and memory in rats and mice [1,2]. Furthermore, a recent study suggests that Arc/Arg3.1 may play a significant role in signal transmission via AMPA-type glutamate receptors [3-5]. Therefore, we conducted a detailed analysis of fear memory in Arc/Arg3.1-deficient mice. As previously reported, the knockout animals exhib-ited impaired fear memory in both contextual and cued test situations. Although Arc/Arg3.1-deficient mice showed almost the same performance as wild-type littermates 4 hr after a conditioning trial, their performance was impaired in the retention test after 24 hr or longer, either with or without reconsolidation. Immunohistochemical analyses showed an abnormal density of GluR1 in the hip-pocampus of Arc/Arg3.1-deficient mice;however, an application of AMPA potentiator did not improve memory performance in the mutant mice. Memory impairment in Arc/Arg3.1-deficient mice is so ro-bust that the mice provide a useful tool for devel-oping treatments for memory impairment.展开更多
This article examines the dynamics for stochastic plate equations with linear memory in the case of bounded domain. We investigate the existence of solutions and bounded absorbing set by using the uniform pullback att...This article examines the dynamics for stochastic plate equations with linear memory in the case of bounded domain. We investigate the existence of solutions and bounded absorbing set by using the uniform pullback attractors on the tails estimates, and the asymptotic compactness of the random dynamical system is proved by decomposition method, and then we obtain the existence of a random attractor.展开更多
We study the short-term memory capacity of ancient readers of the original New Testament written in Greek, of its translations to Latin and to modern languages. To model it, we consider the number of words between any...We study the short-term memory capacity of ancient readers of the original New Testament written in Greek, of its translations to Latin and to modern languages. To model it, we consider the number of words between any two contiguous interpunctions I<sub>p</sub>, because this parameter can model how the human mind memorizes “chunks” of information. Since I<sub>P</sub> can be calculated for any alphabetical text, we can perform experiments—otherwise impossible— with ancient readers by studying the literary works they used to read. The “experiments” compare the I<sub>P</sub> of texts of a language/translation to those of another language/translation by measuring the minimum average probability of finding joint readers (those who can read both texts because of similar short-term memory capacity) and by defining an “overlap index”. We also define the population of universal readers, people who can read any New Testament text in any language. Future work is vast, with many research tracks, because alphabetical literatures are very large and allow many experiments, such as comparing authors, translations or even texts written by artificial intelligence tools.展开更多
BACKGROUND: Brain injury patients often exhibit learning and memory functional deficits. Long-term potentiation (LTP) is a representative index for studying learning and memory cellular models; the LTP index correl...BACKGROUND: Brain injury patients often exhibit learning and memory functional deficits. Long-term potentiation (LTP) is a representative index for studying learning and memory cellular models; the LTP index correlates to neural plasticity. OBJECTIVE: This study was designed to investigate correlations of learning and memory functions to LTP in brain injury patients, and to summarize the research advancements in mechanisms underlying brain functional improvements after rehabilitation intervention. RETRIEVAL STRATEGY: Using the terms "brain injuries, rehabilitation, learning and memory, long-term potentiation", manuscripts that were published from 2000-2007 were retrieved from the PubMed database. At the same time, manuscripts published from 2000-2007 were also retrieved from the Database of Chinese Scientific and Technical Periodicals with the same terms in the Chinese language. A total of 64 manuscripts were obtained and primarily screened. Inclusion criteria: studies on learning and memory, as well as LTP in brain injury patients, and studies focused on the effects of rehabilitation intervention on the two indices; studies that were recently published or in high-impact journals. Exclusion criteria: repetitive studies. LITERATURE EVALUATION: The included manuscripts primarily focused on correlations between learning and memory and LTP, the effects of brain injury on learning and memory, as well as LTP, and the effects of rehabilitation intervention on learning and memory after brain injury. The included 39 manuscripts were clinical, basic experimental, or review studies. DATA SYNTHESIS: Learning and memory closely correlates to LTP. The neurobiological basis of learning and memory is central nervous system plasticity, which involves neural networks, neural circuits, and synaptic connections, in particular, synaptic plasticity. LTP is considered to be an ideal model for studying synaptic plasticity, and it is also a classic model for studying neural plasticity of learning and memory. Brain injury patients clinically present with various manifestations, such as paralysis and sensory disability, which closely correlate to injured regions. In addition, learning and memory abilities decrease in brain injury patients and LTP decreases following brain injury. Brain tissue injury will lead to brain functional deficits. Hippocampal LTP is very sensitive. Difficulties in LTP induction are apparent even prior to morphological changes in brain tissue. There are no specific treatments for learning and memory functional deficits following brain injury. At present, behavioral and compensative therapies are the typical forms of rehabilitation. These results indicate that rehabilitation promotes learning and memory functional recovery in brain injury patients by speeding up LTP formation in the hippocampal CA3 region. CONCLUSION: Rehabilitation intervention increases LTP formation in the hippocampal CA3 region and recovers learning and memory functions in brain injury patients.展开更多
In this paper, a new class of three term memory gradient method with non-monotone line search technique for unconstrained optimization is presented. Global convergence properties of the new methods are discussed. Comb...In this paper, a new class of three term memory gradient method with non-monotone line search technique for unconstrained optimization is presented. Global convergence properties of the new methods are discussed. Combining the quasi-Newton method with the new method, the former is modified to have global convergence property. Numerical results show that the new algorithm is efficient.展开更多
The healthy condition of the milling tool has a very high impact on the machining quality of the titanium components.Therefore,it is important to recognize the healthy condition of the tool and replace the damaged cut...The healthy condition of the milling tool has a very high impact on the machining quality of the titanium components.Therefore,it is important to recognize the healthy condition of the tool and replace the damaged cutter at the right time.In order to recognize the health condition of the milling cutter,a method based on the long short term memory(LSTM)was proposed to recognize tool health state in this paper.The various signals collected in the tool wear experiments were analyzed by time-domain statistics,and then the extracted data were generated by principal component analysis(PCA)method.The preprocessed data extracted by PCA is transmitted to the LSTM model for recognition.Compared with back propagation neural network(BPNN)and support vector machine(SVM),the proposed method can effectively utilize the time-domain regulation in the data to achieve higher recognition speed and accuracy.展开更多
In dense pedestrian tracking,frequent object occlusions and close distances between objects cause difficulty when accurately estimating object trajectories.In this study,a conditional random field tracking model is es...In dense pedestrian tracking,frequent object occlusions and close distances between objects cause difficulty when accurately estimating object trajectories.In this study,a conditional random field tracking model is established by using a visual long short term memory network in the three-dimensional(3D)space and the motion estimations jointly performed on object trajectory segments.Object visual field information is added to the long short term memory network to improve the accuracy of the motion related object pair selection and motion estimation.To address the uncertainty of the length and interval of trajectory segments,a multimode long short term memory network is proposed for the object motion estimation.The tracking performance is evaluated using the PETS2009 dataset.The experimental results show that the proposed method achieves better performance than the tracking methods based on the independent motion estimation.展开更多
In this paper,we study the blow-up of solutions to a semi-linear wave equation with a nonlinear memory term of derivative type.By using methods of an iteration argument and di erential inequalities,we obtain the blow-...In this paper,we study the blow-up of solutions to a semi-linear wave equation with a nonlinear memory term of derivative type.By using methods of an iteration argument and di erential inequalities,we obtain the blow-up result for the semi-linear wave equation when the exponent of p is under certain conditions.Meanwhile,we derive an upper bound of the lifespan of solutions to the Cauchy problem for the semi-linear wave equation.展开更多
Objective To explore the changes in spatial learning performance and long-term potentiation (LTP) which is recognized as a component of the cellular basis of learning and memory in normal and lead-exposed rats after...Objective To explore the changes in spatial learning performance and long-term potentiation (LTP) which is recognized as a component of the cellular basis of learning and memory in normal and lead-exposed rats after administration of melatonin (MT) for two months. Methods Experiment was performed in adult male Wistar rats (12 controls, 12 exposed to melatonin treatment, 10 exposed to lead and 10 exposed to lead and melatonin treatment). The lead-exposed rats received 0.2% lead acetate solution from their birth day while the control rats drank tap water. Melatonin (3 mg/kg) or vehicle was administered to the control and lead-exposed rats from the time of their weaning by gastric gavage each day for 60 days, depending on their groups. At the age of 81-90 days, all the animals were subjected to Morris water maze test and then used for extracellular recording of LTP in the dentate gyrus (DG) area of the hippocampus in vivo. Results Low dose of melatonin given from weaning for two months impaired LTP in the DG area of hippocampus and induced learning and memory deficit in the control rats. When melatonin was administered over a prolonged period to the lead-exposed rats, it exacerbated LTP impairment, learning and memory deficit induced by lead. Conclusion Melatonin is not suitable for normal and lead-exposed children.展开更多
A Long Short-Term Memory(LSTM) Recurrent Neural Network(RNN) has driven tremendous improvements on an acoustic model based on Gaussian Mixture Model(GMM). However, these models based on a hybrid method require a force...A Long Short-Term Memory(LSTM) Recurrent Neural Network(RNN) has driven tremendous improvements on an acoustic model based on Gaussian Mixture Model(GMM). However, these models based on a hybrid method require a forced aligned Hidden Markov Model(HMM) state sequence obtained from the GMM-based acoustic model. Therefore, it requires a long computation time for training both the GMM-based acoustic model and a deep learning-based acoustic model. In order to solve this problem, an acoustic model using CTC algorithm is proposed. CTC algorithm does not require the GMM-based acoustic model because it does not use the forced aligned HMM state sequence. However, previous works on a LSTM RNN-based acoustic model using CTC used a small-scale training corpus. In this paper, the LSTM RNN-based acoustic model using CTC is trained on a large-scale training corpus and its performance is evaluated. The implemented acoustic model has a performance of 6.18% and 15.01% in terms of Word Error Rate(WER) for clean speech and noisy speech, respectively. This is similar to a performance of the acoustic model based on the hybrid method.展开更多
Statistics of languages are usually calculated by counting characters, words, sentences, word rankings. Some of these random variables are also the main “ingredients” of classical readability formulae. Revisiting th...Statistics of languages are usually calculated by counting characters, words, sentences, word rankings. Some of these random variables are also the main “ingredients” of classical readability formulae. Revisiting the readability formula of Italian, known as GULPEASE, shows that of the two terms that determine the readability index G—the semantic index , proportional to the number of characters per word, and the syntactic index GF, proportional to the reciprocal of the number of words per sentence—GF is dominant because GC is, in practice, constant for any author throughout seven centuries of Italian Literature. Each author can modulate the length of sentences more freely than he can do with the length of words, and in different ways from author to author. For any author, any couple of text variables can be modelled by a linear relationship y = mx, but with different slope m from author to author, except for the relationship between characters and words, which is unique for all. The most important relationship found in the paper is that between the short-term memory capacity, described by Miller’s “7 ? 2 law” (i.e., the number of “chunks” that an average person can hold in the short-term memory ranges from 5 to 9), and the word interval, a new random variable defined as the average number of words between two successive punctuation marks. The word interval can be converted into a time interval through the average reading speed. The word interval spreads in the same range as Miller’s law, and the time interval is spread in the same range of short-term memory response times. The connection between the word interval (and time interval) and short-term memory appears, at least empirically, justified and natural, however, to be further investigated. Technical and scientific writings (papers, essays, etc.) ask more to their readers because words are on the average longer, the readability index G is lower, word and time intervals are longer. Future work done on ancient languages, such as the classical Greek and Latin Literatures (or modern languages Literatures), could bring us an insight into the short-term memory required to their well-educated ancient readers.展开更多
Objective: This study aimed to compare the cortical topographic mapping while performing cognitive activities of standardized short-term memory. Materials and Methods: The sample consisted of 30 individuals of both ge...Objective: This study aimed to compare the cortical topographic mapping while performing cognitive activities of standardized short-term memory. Materials and Methods: The sample consisted of 30 individuals of both gender. Each individual participant of the survey was subjected to a short-term memory test for each sense. To carry out the EEG record, we used an electroencephalograph with 20 electrodes. The stimulus for the acquisition of short-term memory has always been made up of five items from different semantic classes. Results: The posterior right quadrant had a higher percentage of gamma rhythm during the tests of most senses. Conclusion: It was concluded that the right back quadrant has a higher gamma rhythms percentage during tests which involve somesthetic, olfactory and gustatory memory. On the other hand, the predominance of a gamma rhythm percentage in any quadrant when the auditory and visual memory was stimulated was not observed in this study.展开更多
Short-term memory allows individuals to recall stimuli, such as numbers or words, for several seconds to several minutes without rehearsal. Although the capacity of short-term memory is considered to be 7 ±?2 ...Short-term memory allows individuals to recall stimuli, such as numbers or words, for several seconds to several minutes without rehearsal. Although the capacity of short-term memory is considered to be 7 ±?2 items, this can be increased through a process called chunking. For example, in Japan, 11-digit cellular phone numbers and 10-digit toll free numbers are chunked into three groups of three or four digits: 090-XXXX-XXXX and 0120-XXX-XXX, respectively. We use probability theory to predict that the most effective chunking involves groups of three or four items, such as in phone numbers. However, a 16-digit credit card number exceeds the capacity of short-term memory, even when chunked into groups of four digits, such as XXXX-XXXX-XXXX-XXXX. Based on these data, 16-digit credit card numbers should be sufficient for security purposes.展开更多
文摘Mental workload plays a vital role in cognitive impairment. The impairment refers to a person’s difficulty in remembering, receiving new information, learning new things, concentrating, or making decisions that seriously affect everyday life. In this paper, the simultaneous capacity (SIMKAP) experiment-based EEG workload analysis was presented using 45 subjects for multitasking mental workload estimation with subject wise attention loss calculation as well as short term memory loss measurement. Using an open access preprocessed EEG dataset, Discrete wavelet transforms (DWT) was utilized for feature extraction and Minimum redundancy and maximum relevancy (MRMR) technique was used to select most relevance features. Wavelet decomposition technique was also used for decomposing EEG signals into five sub bands. Fourteen statistical features were calculated from each sub band signal to form a 5 × 14 window size. The Neural Network (Narrow) classification algorithm was used to classify dataset for low and high workload conditions and comparison was made using some other machine learning models. The results show the classifier’s accuracy of 86.7%, precision of 84.4%, F1 score of 86.33%, and recall of 88.37% that crosses the state-of-the art methodologies in the literature. This prediction is expected to greatly facilitate the improved way in memory and attention loss impairments assessment.
基金This research is funded by Vellore Institute of Technology,Chennai,India.
文摘In today’s world, there are many people suffering from mentalhealth problems such as depression and anxiety. If these conditions are notidentified and treated early, they can get worse quickly and have far-reachingnegative effects. Unfortunately, many people suffering from these conditions,especially depression and hypertension, are unaware of their existence until theconditions become chronic. Thus, this paper proposes a novel approach usingBi-directional Long Short-Term Memory (Bi-LSTM) algorithm and GlobalVector (GloVe) algorithm for the prediction and treatment of these conditions.Smartwatches and fitness bands can be equipped with these algorithms whichcan share data with a variety of IoT devices and smart systems to betterunderstand and analyze the user’s condition. We compared the accuracy andloss of the training dataset and the validation dataset of the two modelsnamely, Bi-LSTM without a global vector layer and with a global vector layer.It was observed that the model of Bi-LSTM without a global vector layer hadan accuracy of 83%,while Bi-LSTMwith a global vector layer had an accuracyof 86% with a precision of 86.4%, and an F1 score of 0.861. In addition toproviding basic therapies for the treatment of identified cases, our model alsohelps prevent the deterioration of associated conditions, making our methoda real-world solution.
基金This work was supported by the National Key Research and Development Program of China(Grant No.2018YFC0407004)the Natural Science Foundation of China(Grants No.51939004 and 11772116).
文摘The unloading relaxation caused by excavation for construction of high arch dams is an important factor influencing the foundation’s integrity and strength.To evaluate the degree of unloading relaxation,the long-short term memory(LSTM)network was used to estimate the depth of unloading relaxation zones on the left bank foundation of the Baihetan Arch Dam.Principal component analysis indicates that rock charac-teristics,the structural plane,the protection layer,lithology,and time are the main factors.The LSTM network results demonstrate the unloading relaxation characteristics of the left bank,and the relationships with the factors were also analyzed.The structural plane has the most significant influence on the distribution of unloading relaxation zones.Compared with massive basalt,the columnar jointed basalt experiences a more significant unloading relaxation phenomenon with a clear time effect,with the average unloading relaxation period being 50 d.The protection layer can effectively reduce the unloading relaxation depth by approximately 20%.
文摘Objective To evaluate whether the thermotaxis tracking model is suitable for assessing long-term memory (LTM) in the nematode Caenorhabditis elegans. Methods Animals were trained at 20℃ overnight in presence of food. The percentage of animals performing isothermal tracking (IT) behavior was measured at different time intervals after the training. Results The percentage of animals performing IT behavior, the numbers of body bends inside and outside the training temperature, and the expression patterns of AFD and AIY neurons were similar to those in control animals at 36 and 48 h after training; whereas when extending to 60, 72, and 84 h, locomotory behavior defects were observed in the assayed animals, suggesting that this thermal tracking model is feasible for analyzing LTM at 36 and 48 h after training. Moreover, the percent-age of animals performing IT behavior was reduced at 18, 36, and 48 h after training in neuronal calcium sensor-1 gene (nsc-1) mutant animals compared with that in wild-type N2 animals. In addition, exposure to plumbum (Pb) significantly repressed the LTM at 18, 36, and 48 h after training in both wild-type N2 and ncs-1 mutant animals. Conclusion The thermotaxis tracking model is suitable for evaluating the LTM regulated by NCS-1, and can be employed for elucidating regulatory functions of specific genes or effects of stimuli on memory in C. elegans.
基金supported by the Foundation of Astronaut Research and Training Center of China(No.SN 02-3)
文摘Objective To gain a better understanding of gene expression changes in the brain following microwave exposure in mice. This study hopes to reveal mechanisms contributing to microwave-induced learning and memory dysfunction. Methods Mice were exposed to whole body 2100 MHz microwaves with specific absorption rates (SARs) of 0.45 W/kg, 1.8 W/kg, and 3.6 W/kg for 1 hour daily for 8 weeks. Differentially expressing genes in the brains were screened using high-density oligonucleotide arrays, with genes showing more significant differences further confirmed by RT-PCR. Results The gene chip results demonstrated that 41 genes (0.45 W/kg group), 29 genes (1.8 W/kg group), and 219 genes (3.6 W/kg group) were differentially expressed. GO analysis revealed that these differentially expressed genes were primarily involved in metabolic processes, cellular metabolic processes, regulation of biological processes, macromolecular metabolic processes, biosynthetic processes, cellular protein metabolic processes, transport, developmental processes, cellular component organization, etc. KEGG pathway analysis showed that these genes are mainly involved in pathways related to ribosome, Alzheimer's disease, Parkinson's disease, long-term potentiation, Huntington's disease, and Neurotrophin signaling. Construction of a protein interaction network identified several important regulatory genes including synbindin (sbdn), Crystallin (CryaB), PPP1CA, Ywhaq, Psap, Psmb1, Pcbp2, etc., which play important roles in the processes of learning and memory. Conclusion Long-term, low-level microwave exposure may inhibit learning and memory by affecting protein and energy metabolic processes and signaling pathways relating to neurological functions or diseases.
文摘Activity-regulated cytoskeleton-associated protein (Arc/Arg3.1) was originally identified in patients with seizures. It is densely distributed in the hip-pocampus and amygdala in particular. Because the expression of Arc/Arg3.1 is regulated by nerve in-puts, it is thought to be an immediate early gene. As shown both in vitro and in vivo, Arc/Arg3.1 is in-volved in synaptic consolidation and regulates some forms of learning and memory in rats and mice [1,2]. Furthermore, a recent study suggests that Arc/Arg3.1 may play a significant role in signal transmission via AMPA-type glutamate receptors [3-5]. Therefore, we conducted a detailed analysis of fear memory in Arc/Arg3.1-deficient mice. As previously reported, the knockout animals exhib-ited impaired fear memory in both contextual and cued test situations. Although Arc/Arg3.1-deficient mice showed almost the same performance as wild-type littermates 4 hr after a conditioning trial, their performance was impaired in the retention test after 24 hr or longer, either with or without reconsolidation. Immunohistochemical analyses showed an abnormal density of GluR1 in the hip-pocampus of Arc/Arg3.1-deficient mice;however, an application of AMPA potentiator did not improve memory performance in the mutant mice. Memory impairment in Arc/Arg3.1-deficient mice is so ro-bust that the mice provide a useful tool for devel-oping treatments for memory impairment.
文摘This article examines the dynamics for stochastic plate equations with linear memory in the case of bounded domain. We investigate the existence of solutions and bounded absorbing set by using the uniform pullback attractors on the tails estimates, and the asymptotic compactness of the random dynamical system is proved by decomposition method, and then we obtain the existence of a random attractor.
文摘We study the short-term memory capacity of ancient readers of the original New Testament written in Greek, of its translations to Latin and to modern languages. To model it, we consider the number of words between any two contiguous interpunctions I<sub>p</sub>, because this parameter can model how the human mind memorizes “chunks” of information. Since I<sub>P</sub> can be calculated for any alphabetical text, we can perform experiments—otherwise impossible— with ancient readers by studying the literary works they used to read. The “experiments” compare the I<sub>P</sub> of texts of a language/translation to those of another language/translation by measuring the minimum average probability of finding joint readers (those who can read both texts because of similar short-term memory capacity) and by defining an “overlap index”. We also define the population of universal readers, people who can read any New Testament text in any language. Future work is vast, with many research tracks, because alphabetical literatures are very large and allow many experiments, such as comparing authors, translations or even texts written by artificial intelligence tools.
基金the Grant from Science and Technology Foundation of Sichuan Province, No. 2002-20
文摘BACKGROUND: Brain injury patients often exhibit learning and memory functional deficits. Long-term potentiation (LTP) is a representative index for studying learning and memory cellular models; the LTP index correlates to neural plasticity. OBJECTIVE: This study was designed to investigate correlations of learning and memory functions to LTP in brain injury patients, and to summarize the research advancements in mechanisms underlying brain functional improvements after rehabilitation intervention. RETRIEVAL STRATEGY: Using the terms "brain injuries, rehabilitation, learning and memory, long-term potentiation", manuscripts that were published from 2000-2007 were retrieved from the PubMed database. At the same time, manuscripts published from 2000-2007 were also retrieved from the Database of Chinese Scientific and Technical Periodicals with the same terms in the Chinese language. A total of 64 manuscripts were obtained and primarily screened. Inclusion criteria: studies on learning and memory, as well as LTP in brain injury patients, and studies focused on the effects of rehabilitation intervention on the two indices; studies that were recently published or in high-impact journals. Exclusion criteria: repetitive studies. LITERATURE EVALUATION: The included manuscripts primarily focused on correlations between learning and memory and LTP, the effects of brain injury on learning and memory, as well as LTP, and the effects of rehabilitation intervention on learning and memory after brain injury. The included 39 manuscripts were clinical, basic experimental, or review studies. DATA SYNTHESIS: Learning and memory closely correlates to LTP. The neurobiological basis of learning and memory is central nervous system plasticity, which involves neural networks, neural circuits, and synaptic connections, in particular, synaptic plasticity. LTP is considered to be an ideal model for studying synaptic plasticity, and it is also a classic model for studying neural plasticity of learning and memory. Brain injury patients clinically present with various manifestations, such as paralysis and sensory disability, which closely correlate to injured regions. In addition, learning and memory abilities decrease in brain injury patients and LTP decreases following brain injury. Brain tissue injury will lead to brain functional deficits. Hippocampal LTP is very sensitive. Difficulties in LTP induction are apparent even prior to morphological changes in brain tissue. There are no specific treatments for learning and memory functional deficits following brain injury. At present, behavioral and compensative therapies are the typical forms of rehabilitation. These results indicate that rehabilitation promotes learning and memory functional recovery in brain injury patients by speeding up LTP formation in the hippocampal CA3 region. CONCLUSION: Rehabilitation intervention increases LTP formation in the hippocampal CA3 region and recovers learning and memory functions in brain injury patients.
文摘In this paper, a new class of three term memory gradient method with non-monotone line search technique for unconstrained optimization is presented. Global convergence properties of the new methods are discussed. Combining the quasi-Newton method with the new method, the former is modified to have global convergence property. Numerical results show that the new algorithm is efficient.
基金National Natural Science Foundation of China(No.51805079)Shanghai Natural Science Foundation,China(No.17ZR1400600)Fundamental Research Funds for the Central Universities,China(No.16D110309)
文摘The healthy condition of the milling tool has a very high impact on the machining quality of the titanium components.Therefore,it is important to recognize the healthy condition of the tool and replace the damaged cutter at the right time.In order to recognize the health condition of the milling cutter,a method based on the long short term memory(LSTM)was proposed to recognize tool health state in this paper.The various signals collected in the tool wear experiments were analyzed by time-domain statistics,and then the extracted data were generated by principal component analysis(PCA)method.The preprocessed data extracted by PCA is transmitted to the LSTM model for recognition.Compared with back propagation neural network(BPNN)and support vector machine(SVM),the proposed method can effectively utilize the time-domain regulation in the data to achieve higher recognition speed and accuracy.
文摘In dense pedestrian tracking,frequent object occlusions and close distances between objects cause difficulty when accurately estimating object trajectories.In this study,a conditional random field tracking model is established by using a visual long short term memory network in the three-dimensional(3D)space and the motion estimations jointly performed on object trajectory segments.Object visual field information is added to the long short term memory network to improve the accuracy of the motion related object pair selection and motion estimation.To address the uncertainty of the length and interval of trajectory segments,a multimode long short term memory network is proposed for the object motion estimation.The tracking performance is evaluated using the PETS2009 dataset.The experimental results show that the proposed method achieves better performance than the tracking methods based on the independent motion estimation.
基金Supported by the Natural Science Foundation of China(Grant No.11371175)Innovation Team Project in Colleges and Universities of Guangdong Province(Grant No.2020WCXTD008)+1 种基金Science Foundation of Huashang College Guangdong University of Finance&Economics(Grant No.2020HSDS01)Science Research Team Project in Guangzhou Huashang College(Grant No.2021HSKT01).
文摘In this paper,we study the blow-up of solutions to a semi-linear wave equation with a nonlinear memory term of derivative type.By using methods of an iteration argument and di erential inequalities,we obtain the blow-up result for the semi-linear wave equation when the exponent of p is under certain conditions.Meanwhile,we derive an upper bound of the lifespan of solutions to the Cauchy problem for the semi-linear wave equation.
基金supported by the National Basic Research Program of China(No.2002CB512907)the National Natural Science Foundation of China(No.30630057).
文摘Objective To explore the changes in spatial learning performance and long-term potentiation (LTP) which is recognized as a component of the cellular basis of learning and memory in normal and lead-exposed rats after administration of melatonin (MT) for two months. Methods Experiment was performed in adult male Wistar rats (12 controls, 12 exposed to melatonin treatment, 10 exposed to lead and 10 exposed to lead and melatonin treatment). The lead-exposed rats received 0.2% lead acetate solution from their birth day while the control rats drank tap water. Melatonin (3 mg/kg) or vehicle was administered to the control and lead-exposed rats from the time of their weaning by gastric gavage each day for 60 days, depending on their groups. At the age of 81-90 days, all the animals were subjected to Morris water maze test and then used for extracellular recording of LTP in the dentate gyrus (DG) area of the hippocampus in vivo. Results Low dose of melatonin given from weaning for two months impaired LTP in the DG area of hippocampus and induced learning and memory deficit in the control rats. When melatonin was administered over a prolonged period to the lead-exposed rats, it exacerbated LTP impairment, learning and memory deficit induced by lead. Conclusion Melatonin is not suitable for normal and lead-exposed children.
基金supported by the Ministry of Trade,Industry & Energy(MOTIE,Korea) under Industrial Technology Innovation Program (No.10063424,'development of distant speech recognition and multi-task dialog processing technologies for in-door conversational robots')
文摘A Long Short-Term Memory(LSTM) Recurrent Neural Network(RNN) has driven tremendous improvements on an acoustic model based on Gaussian Mixture Model(GMM). However, these models based on a hybrid method require a forced aligned Hidden Markov Model(HMM) state sequence obtained from the GMM-based acoustic model. Therefore, it requires a long computation time for training both the GMM-based acoustic model and a deep learning-based acoustic model. In order to solve this problem, an acoustic model using CTC algorithm is proposed. CTC algorithm does not require the GMM-based acoustic model because it does not use the forced aligned HMM state sequence. However, previous works on a LSTM RNN-based acoustic model using CTC used a small-scale training corpus. In this paper, the LSTM RNN-based acoustic model using CTC is trained on a large-scale training corpus and its performance is evaluated. The implemented acoustic model has a performance of 6.18% and 15.01% in terms of Word Error Rate(WER) for clean speech and noisy speech, respectively. This is similar to a performance of the acoustic model based on the hybrid method.
文摘Statistics of languages are usually calculated by counting characters, words, sentences, word rankings. Some of these random variables are also the main “ingredients” of classical readability formulae. Revisiting the readability formula of Italian, known as GULPEASE, shows that of the two terms that determine the readability index G—the semantic index , proportional to the number of characters per word, and the syntactic index GF, proportional to the reciprocal of the number of words per sentence—GF is dominant because GC is, in practice, constant for any author throughout seven centuries of Italian Literature. Each author can modulate the length of sentences more freely than he can do with the length of words, and in different ways from author to author. For any author, any couple of text variables can be modelled by a linear relationship y = mx, but with different slope m from author to author, except for the relationship between characters and words, which is unique for all. The most important relationship found in the paper is that between the short-term memory capacity, described by Miller’s “7 ? 2 law” (i.e., the number of “chunks” that an average person can hold in the short-term memory ranges from 5 to 9), and the word interval, a new random variable defined as the average number of words between two successive punctuation marks. The word interval can be converted into a time interval through the average reading speed. The word interval spreads in the same range as Miller’s law, and the time interval is spread in the same range of short-term memory response times. The connection between the word interval (and time interval) and short-term memory appears, at least empirically, justified and natural, however, to be further investigated. Technical and scientific writings (papers, essays, etc.) ask more to their readers because words are on the average longer, the readability index G is lower, word and time intervals are longer. Future work done on ancient languages, such as the classical Greek and Latin Literatures (or modern languages Literatures), could bring us an insight into the short-term memory required to their well-educated ancient readers.
文摘Objective: This study aimed to compare the cortical topographic mapping while performing cognitive activities of standardized short-term memory. Materials and Methods: The sample consisted of 30 individuals of both gender. Each individual participant of the survey was subjected to a short-term memory test for each sense. To carry out the EEG record, we used an electroencephalograph with 20 electrodes. The stimulus for the acquisition of short-term memory has always been made up of five items from different semantic classes. Results: The posterior right quadrant had a higher percentage of gamma rhythm during the tests of most senses. Conclusion: It was concluded that the right back quadrant has a higher gamma rhythms percentage during tests which involve somesthetic, olfactory and gustatory memory. On the other hand, the predominance of a gamma rhythm percentage in any quadrant when the auditory and visual memory was stimulated was not observed in this study.
文摘Short-term memory allows individuals to recall stimuli, such as numbers or words, for several seconds to several minutes without rehearsal. Although the capacity of short-term memory is considered to be 7 ±?2 items, this can be increased through a process called chunking. For example, in Japan, 11-digit cellular phone numbers and 10-digit toll free numbers are chunked into three groups of three or four digits: 090-XXXX-XXXX and 0120-XXX-XXX, respectively. We use probability theory to predict that the most effective chunking involves groups of three or four items, such as in phone numbers. However, a 16-digit credit card number exceeds the capacity of short-term memory, even when chunked into groups of four digits, such as XXXX-XXXX-XXXX-XXXX. Based on these data, 16-digit credit card numbers should be sufficient for security purposes.