We propose an efficient method for compressing Vietnamese text using n-gram dictionaries. It has a significant compression ratio in comparison with those of state-of-the-art methods on the same dataset. Given a text, first, the proposed method splits it into n-grams and then encodes them based on n-gram dictionaries. In the encoding phase, we use a sliding window with a size that ranges from bigram to five grams to obtain the best encoding stream. Each n-gram is encoded by two to four bytes accordingly based on its corresponding n-gram dictionary. We collected 2.5 GB text corpus from some Vietnamese news agencies to build n-gram dictionaries from unigram to five grams and achieve dictionaries with a size of 12 GB in total. In order to evaluate our method, we collected a testing set of 10 different text files with different sizes. The experimental results indicate that our method achieves compression ratio around 90% and outperforms state-of-the-art methods.

• MeSH
• Algorithms * MeSH
• Asian People * MeSH
• Data Compression * MeSH
• Humans MeSH
• Vocabulary * MeSH
• Dictionaries as Topic * MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH

BACKGROUND AND PURPOSE: Diffusion tensor imaging (DTI) has previously been used as a biomarker of myelopathy in patients with degenerative cervical cord compression (DCCC). However, many factors may affect the diffusion properties of the spinal cord. This prospective study seeks to identify sources of variability in spinal cord DTI parameters in both DCCC patients and healthy subjects. METHODS: The study group included 130 patients with DCCC confirmed by magnetic resonance imaging and 71 control subjects without signs of DCCC. DTI data of the cervical spine were acquired in all subjects. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values were measured at different levels of the spinal cord (SCLs). Statistical data analysis was then used to determine diffusion parameters in terms of age, sex, SCL, and spinal cord compression. RESULTS: Significant variations in FA and ADC values emerged when several spinal cord levels were mutually compared in the control group. FA values correlated significantly with age in the DCCC group and sex had a significant influence on ADC values in both groups. The two diffusion parameters in the DCCC group differed significantly between patients with clinical signs of mild-to-moderate myelopathy compared with asymptomatic patients, and correlated with measurements of spinal canal morphology. CONCLUSIONS: Diffusion parameters of the cervical spinal cord were thus shown to respond significantly to spinal cord compression, but were subject to interaction with several other factors including sex, age, and SCL. These findings may be important to the interpretation of DTI measurements in individual patients.

• Keywords
• Magnetic resonance imaging, degenerative cervical cord compression, degenerative cervical myelopathy, diffusion tensor imaging,
• MeSH
• Spinal Cord Compression diagnostic imaging   MeSH
• Cervical Cord diagnostic imaging   MeSH
• Middle Aged MeSH
• Humans MeSH
• Prospective Studies MeSH
• Diffusion Tensor Imaging * MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

The utilization of computer vision in smart farming is becoming a trend in constructing an agricultural automation scheme. Deep learning (DL) is famous for the accurate approach to addressing the tasks in computer vision, such as object detection and image classification. The superiority of the deep learning model on the smart farming application, called Progressive Contextual Excitation Network (PCENet), has also been studied in our recent study to classify cocoa bean images. However, the assessment of the computational time on the PCENet model shows that the original model is only 0.101s or 9.9 FPS on the Jetson Nano as the edge platform. Therefore, this research demonstrates the compression technique to accelerate the PCENet model using pruning filters. From our experiment, we can accelerate the current model and achieve 16.7 FPS assessed in the Jetson Nano. Moreover, the accuracy of the compressed model can be maintained at 86.1%, while the original model is 86.8%. In addition, our approach is more accurate than ResNet18 as the state-of-the-art only reaches 82.7%. The assessment using the corn leaf disease dataset indicates that the compressed model can achieve an accuracy of 97.5%, while the accuracy of the original PCENet is 97.7%.

• Keywords
• deep learning, model compression, progressive contextual excitation, pruning filters,
• MeSH
• Automation MeSH
• Farms MeSH
• Physical Phenomena MeSH
• Data Compression * MeSH
• Agriculture * MeSH
• Publication type
• Journal Article MeSH

The performance of ECG signals compression is influenced by many things. However, there is not a single study primarily focused on the possible effects of ECG pathologies on the performance of compression algorithms. This study evaluates whether the pathologies present in ECG signals affect the efficiency and quality of compression. Single-cycle fractal-based compression algorithm and compression algorithm based on combination of wavelet transform and set partitioning in hierarchical trees are used to compress 125 15-leads ECG signals from CSE database. Rhythm and morphology of these signals are newly annotated as physiological or pathological. The compression performance results are statistically evaluated. Using both compression algorithms, physiological signals are compressed with better quality than pathological signals according to 8 and 9 out of 12 quality metrics, respectively. Moreover, it was statistically proven that pathological signals were compressed with lower efficiency than physiological signals. Signals with physiological rhythm and physiological morphology were compressed with the best quality. The worst results reported the group of signals with pathological rhythm and pathological morphology. This study is the first one which deals with effects of ECG pathologies on the performance of compression algorithms. Signal-by-signal rhythm and morphology annotations (physiological/pathological) for the CSE database are newly published.

• MeSH
• Algorithms MeSH
• Databases, Factual MeSH
• Electrocardiography methods   MeSH
• Fractals MeSH
• Data Compression methods   MeSH
• Humans MeSH
• Wavelet Analysis MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

OBJECTIVES: To update a previously established list of predictors for neurological cervical cord dysfunction in nonmyelopathic degenerative cervical cord compression (NMDCCC). MATERIAL AND METHODS: A prospective observational follow-up study was performed in a cohort of 112 consecutive NMDCCC subjects (55 women and 57 men; median age 59 years, range 40-79 years), either asymptomatic (40 subjects) or presenting with cervical radiculopathy or cervical pain (72 subjects), who had completed a follow-up of at least 2 years (median duration 3 years). Development of clinical signs of degenerative cervical myelopathy (DCM) as the main outcome was monitored and correlated with a large number of demographic, clinical, electrophysiological, and MRI parameters including diffusion tensor imaging characteristics (DTI) established at entry. RESULTS: Clinical evidence of the first signs and symptoms of DCM were found in 15 patients (13.4%). Development of DCM was associated with several parameters, including the clinical (radiculopathy, prolonged gait and run-time), electrophysiological (SEP, MEP and EMG signs of cervical cord dysfunction), and MRI (anteroposterior diameter of the cervical cord and cervical canal, cross-sectional area, compression ratio, type of compression, T2 hyperintensity). DTI parameters showed no significant predictive power. Multivariate analysis showed that radiculopathy, cross-sectional area (CSA) ≤ 70.1 mm2, and compression ratio (CR) ≤ 0.4 were the only independent significant predictors for progression into symptomatic myelopathy. CONCLUSIONS: In addition to previously described independent predictors of DCM development (radiculopathy and electrophysiological dysfunction of cervical cord), MRI parameters, namely CSA and CR, should also be considered as significant predictors for development of DCM.

• Keywords
• cervical radiculopathy, degenerative cervical myelopathy, magnetic resonance imaging, nonmyelopathic degenerative cervical cord compression, predictive model,
• MeSH
• Adult MeSH
• Physical Examination MeSH
• Spinal Cord Compression diagnosis   diagnostic imaging   physiopathology   MeSH
• Cervical Vertebrae diagnostic imaging   physiopathology   MeSH
• Middle Aged MeSH
• Humans MeSH
• Magnetic Resonance Imaging MeSH
• Follow-Up Studies MeSH
• Spinal Cord Diseases diagnosis   diagnostic imaging   physiopathology   MeSH
• Disease Progression MeSH
• Prospective Studies MeSH
• Aged MeSH
• Diffusion Tensor Imaging MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

The treatment of radicular pain is mainly empirical because there are only few experimental studies dealing with morphological changes during compression radiculopathy. The goal of the study was to investigate changes in the morphology of myelinated axons during spinal root compression and the influence of decompression in a new rat model. The number of myelinated axons and their diameter were measured at 1, 2, 5, and 8 weeks during compression of the dorsal spinal root. The same approach was applied for 1-week compression followed by decompression for 1 or 2 weeks and compression for 5 weeks followed by 3-week decompression. A decrease in the number of myelinated axons (particularly those of large diameters) occurred after compression for 1 week. Continued compression for up to 8 weeks resulted in centripetal increase in the number of myelinated axons and the persistence of a small fraction of large myelinated axons at the site of compression. After that time, a decreased number of axons and a reduced fraction of large myelinated axons occurred again. Decompression after 1-week compression caused a rapid increase in the number of both small and large myelinated axons within the spinal root including the site of compression. A small fraction of regenerated axons was found after 5-week compression followed by 3-week decompression. Finally, we investigated the time course of the temporary increase in the number of regenerated myelinated axons during dorsal root compression for up to 8 weeks. The efficacy of decompression was superior when applied one week after compression or after regress of the acute phase of aseptic inflammation associated with fragility of spinal root. The results of the study verify the need for early surgical decompression to prevent irreversible damage of the spinal roots.

• MeSH
• Time Factors MeSH
• Decompression, Surgical MeSH
• Rats MeSH
• Low Back Pain etiology   pathology   physiopathology   MeSH
• Spinal Nerve Roots injuries   pathology   physiopathology   MeSH
• Disease Models, Animal MeSH
• Nerve Fibers, Myelinated pathology   MeSH
• Cell Count MeSH
• Rats, Wistar MeSH
• Radiculopathy pathology   physiopathology   MeSH
• Nerve Regeneration physiology   MeSH
• Nerve Compression Syndromes pathology   physiopathology   surgery   MeSH
• Wallerian Degeneration etiology   pathology   physiopathology   MeSH
• Animals MeSH
• Check Tag
• Rats MeSH
• Female MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

STUDY DESIGN: We conducted a cohort study of clinically asymptomatic spondylotic cervical cord compression cases with the primary end point of the development of clinical signs of cervical myelopathy. OBJECTIVES: To investigate whether various demographic, clinical, radiologic, and electrophysiological parameters could predict progression from clinically asymptomatic (preclinical) spondylotic cervical cord compression to symptomatic myelopathy. SUMMARY OF BACKGROUND DATA: The data available on the prediction of the outcome in surgical and conservative treatment of spondylotic cervical myelopathy are controversial. Little is known about the clinical natural history of asymptomatic magnetic resonance image-detected spondylotic cervical cord compression and/or changes of signal intensity. METHODS: A group of 66 patients (32 women, 34 men, median age 50 years) with magnetic resonance signs of spondylotic cervical cord compression but without clear clinical signs of myelopathy was followed prospectively for at least 2 years (range, 2-8 years; median, 4 years). Various demographic, clinical, imaging, and electrophysiological parameters were correlated with clinical outcome. RESULTS: Clinical signs of myelopathy during the follow-up period were detected in 13 patients (19.7%). The only variables significantly associated with the development of clinically symptomatic spondylotic cervical myelopathy (SCM) were the presence of symptomatic cervical radiculopathy, electromyographic signs of anterior horn lesion, and abnormal somatosensory-evoked potentials. A multivariate logistic regression model based on these variables correctly classified 90% of cases into 2 subgroups: a group with development of symptomatic SCM and that without clinical manifestation of subclinical cervical cord compression. CONCLUSIONS: Electrophysiological abnormalities together with clinical signs of cervical radiculopathy could predict clinical manifestation of preclinical spondylotic cervical cord compression.

• MeSH
• Anterior Horn Cells physiology   MeSH
• Early Diagnosis MeSH
• Adult MeSH
• Electromyography MeSH
• Cohort Studies MeSH
• Spinal Cord Compression diagnostic imaging   etiology   physiopathology   MeSH
• Cervical Vertebrae * MeSH
• Middle Aged MeSH
• Humans MeSH
• Magnetic Resonance Imaging MeSH
• Evoked Potentials, Motor MeSH
• Follow-Up Studies MeSH
• Spinal Osteophytosis complications   diagnostic imaging   physiopathology   MeSH
• Disease Progression MeSH
• Prospective Studies MeSH
• Radiography MeSH
• Aged MeSH
• Evoked Potentials, Somatosensory MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

The heat shock protein 70 (HSP70) is a key component of the stress response induced by various noxious conditions such as heat, oxygen stress, trauma and infection. In present study we have assessed the consequences of the compression of lower lumbar and sacral nerve roots caused by a multiple cauda equina constrictions (MCEC) on HSP70 immunoreactivity (HSP70-IR) in the dog. Our data indicate that constriction of central processes evokes HSP70 up-regulation in the spinal cord (L7, S1-Co3) as well as in the corresponding dorsal root ganglion cells (DRGs) (L7-S1) two days following injury. A limited number of bipolar or triangular HSP-IR neurons were found in the lateral collateral pathway (LCP) as well as in the pericentral region (lamina X) of the spinal cord. In contrast, a high number of HSP70 exhibiting motoneurons with fine processes appeared in the ventral horn (laminae VIII-IX) of lumbosacral segments. Concomitantly, close to them a few lightly HSP70-positive neuronal somata or cell bodies lacking the HSP70-IR occurred. In the DRGs, HSP70 expression was mildly up-regulated in small and medium-sized neurons and in satellite cells. On the contrary, DRGs from intact or sham-operated dogs did not reveal HSP70 specific neuronal staining. In conclusion, we have demonstrated that the MCEC in dogs mimicking the cauda equina syndrome in clinical settings evokes expression of HSP70 synthesis in specific neurons of the lumbo-sacro-coccygeal spinal cord segments and in small and medium sized neurons of corresponding DRGs. This suggests that HSP70 may play an active role in neuroprotective processes partly by maintaining intracellular protein integrity and preventing the neuronal degeneration in this experimental paradigm.

• MeSH
• Cauda Equina injuries   metabolism   MeSH
• Disease Models, Animal MeSH
• Neurons metabolism   MeSH
• HSP70 Heat-Shock Proteins metabolism   MeSH
• Dogs MeSH
• Tissue Distribution MeSH
• Nerve Compression Syndromes metabolism   MeSH
• Animals MeSH
• Check Tag
• Male MeSH
• Dogs MeSH
• Female MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• HSP70 Heat-Shock Proteins MeSH

Electroencephalography (EEG) experiments typically generate vast amounts of data due to the high sampling rates and the use of multiple electrodes to capture brain activity. Consequently, storing and transmitting these large datasets is challenging, necessitating the creation of specialized compression techniques tailored to this data type. This study proposes one such method, which at its core uses an artificial neural network (specifically a convolutional autoencoder) to learn the latent representations of modelled EEG signals to perform lossy compression, which gets further improved with lossless corrections based on the user-defined threshold for the maximum tolerable amplitude loss, resulting in a flexible near-lossless compression scheme. To test the viability of our approach, a case study was performed on the 256-channel binocular rivalry dataset, which also describes mostly data-specific statistical analyses and preprocessing steps. Compression results, evaluation metrics, and comparisons with baseline general compression methods suggest that the proposed method can achieve substantial compression results and speed, making it one of the potential research topics for follow-up studies.

• Keywords
• Artificial neural networks, Data compression, Electroencephalography, Machine learning, Neuroinformatics,
• MeSH
• Adult MeSH
• Electroencephalography * methods   MeSH
• Data Compression * methods   MeSH
• Humans MeSH
• Neural Networks, Computer * MeSH
• Signal Processing, Computer-Assisted MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

Degenerative cervical myelopathy (DCM) is a severe consequence of degenerative cervical spinal cord (CSC) compression. The non-myelopathic stage of compression (NMDC) is highly prevalent and often progresses to disabling DCM. This study aims to disclose markers of progressive neurochemical alterations in NMDC and DCM by utilizing an approach based on state-of-the-art proton magnetic resonance spectroscopy (1H-MRS). Proton-MRS data were prospectively acquired from 73 participants with CSC compression and 47 healthy controls (HCs). The MRS voxel was centered at the C2 level. Compression-affected participants were clinically categorized as NMDC and DCM, radiologically as mild (MC) or severe (SC) compression. CSC volumes and neurochemical concentrations were compared between cohorts (HC vs. NMDC vs. DCM and HC vs. MC vs. SC) with general linear models adjusted for age and height (pFWE < 0.05) and correlated to stenosis severity, electrophysiology, and myelopathy symptoms (p < 0.05). Whereas the ratio of total creatine (tCr) to total N-acetylaspartate (tNAA) increased in NMDC (+11%) and in DCM (+26%) and SC (+21%), myo-inositol/tNAA, glutamate + glutamine/tNAA, and volumes changed only in DCM (+20%, +73%, and -14%) and SC (+12%, +46%, and -8%, respectively) relative to HCs. Both tCr/tNAA and myo-inositol/tNAA correlated with compression severity and volume (-0.376 < r < -0.259). Myo-inositol/tNAA correlated with myelopathy symptoms (r = -0.670), whereas CSC volume did not. Short-echo 1H-MRS provided neurochemical signatures of CSC impairment that reflected compression severity and clinical significance. Whereas volumetry only reflected clinically manifest myelopathy (DCM), MRS detected neurochemical changes already before the onset of myelopathy symptoms.

• Keywords
• cervical spinal cord, compression, degenerative, magnetic resonance, myelopathy, spectroscopy,
• MeSH
• Adult MeSH
• Inositol metabolism   MeSH
• Spinal Cord Compression metabolism   pathology   MeSH
• Cervical Cord * MeSH
• Cervical Vertebrae MeSH
• Creatine metabolism   MeSH
• Aspartic Acid analogs & derivatives   metabolism   MeSH
• Glutamic Acid metabolism   MeSH
• Middle Aged MeSH
• Humans MeSH
• Magnetic Resonance Spectroscopy * MeSH
• Aged MeSH
• Sensitivity and Specificity MeSH
• Case-Control Studies MeSH
• Severity of Illness Index MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH
• Names of Substances
• Inositol MeSH
• Creatine MeSH
• Aspartic Acid MeSH
• Glutamic Acid MeSH
• N-acetylaspartate MeSH Browser