Deep learning-driven superresolution (SR) outperforms traditional techniques but also faces the challenge of high complexity and memory bandwidth. This challenge leads many accelerators to opt for ...simpler and shallow models like FSRCNN, compromising performance for real-time needs, especially for resource-limited edge devices. This paper proposes an energy-efficient SR accelerator, ACNPU, to tackle this challenge. The ACNPU enhances image quality by 0.34dB with a 27-layer model, but needs 36% less complexity than FSRCNN, while maintaining a similar model size, with the decoupled asymmetric convolution and split-bypass structure. The hardware-friendly 17K-parameter model enables holistic model fusion instead of localized layer fusion to remove external DRAM access of intermediate feature maps. The on-chip memory bandwidth is further reduced with the input stationary flow and parallel-layer execution to reduce power consumption. Hardware is regular and easy to control to support different layers by processing elements (PEs) clusters with reconfigurable input and uniform data flow. The implementation in the 40 nm CMOS process consumes 2333 K gate counts and 198Â KB SRAMs. The ACNPU achieves 31.7 FPS and 124.4 FPS for <inline-formula> <tex-math notation="LaTeX">\times 2 </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">\times 4 </tex-math></inline-formula> scales Full-HD generation, respectively, which attains 4.75 TOPS/W energy efficiency.
Human neurons are functional over an entire lifetime, yet the mechanisms that preserve function and protect against neurodegeneration during ageing are unknown. Here we show that induction of the ...repressor element 1-silencing transcription factor (REST; also known as neuron-restrictive silencer factor, NRSF) is a universal feature of normal ageing in human cortical and hippocampal neurons. REST is lost, however, in mild cognitive impairment and Alzheimer's disease. Chromatin immunoprecipitation with deep sequencing and expression analysis show that REST represses genes that promote cell death and Alzheimer's disease pathology, and induces the expression of stress response genes. Moreover, REST potently protects neurons from oxidative stress and amyloid β-protein toxicity, and conditional deletion of REST in the mouse brain leads to age-related neurodegeneration. A functional orthologue of REST, Caenorhabditis elegans SPR-4, also protects against oxidative stress and amyloid β-protein toxicity. During normal ageing, REST is induced in part by cell non-autonomous Wnt signalling. However, in Alzheimer's disease, frontotemporal dementia and dementia with Lewy bodies, REST is lost from the nucleus and appears in autophagosomes together with pathological misfolded proteins. Finally, REST levels during ageing are closely correlated with cognitive preservation and longevity. Thus, the activation state of REST may distinguish neuroprotection from neurodegeneration in the ageing brain.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The accurate identification and real-time detection of obstacles have been considered the premise to ensure the safe operation of coal mine driverless electric locomotives. The harsh coal mine ...roadway environment leads to low detection accuracy of obstacles based on traditional detection methods such as LiDAR and machine learning, and these traditional obstacle detection methods lead to slower detection speeds due to excessive computational reasoning. To address the above-mentioned problems, we propose a deep learning-based ODEL-YOLOv5s detection model based on the conventional YOLOv5s. In this work, several data augmentation methods are introduced to increase the diversity of obstacle features in the dataset images. An attention mechanism is introduced to the neck of the model to improve the focus of the model on obstacle features. The three-scale prediction of the model is increased to a four-scale prediction to improve the detection ability of the model for small obstacles. We also optimize the localization loss function and non-maximum suppression method of the model to improve the regression accuracy and reduce the redundancy of the prediction boxes. The experimental results show that the mean average precision (mAP) of the proposed ODEL-YOLOv5s model is increased from 95.2 to 98.9% compared to the conventional YOLOv5s, the average precision of small obstacle rock is increased from 89.2 to 97.9%, the detection speed of the model is 60.2 FPS, and it has better detection performance compared with other detection models, which can provide technical support for obstacle identification and real-time detection of coal mine driverless electric locomotives.
Abstract
We have previously reported the molecular signature of murine pathogenic T
H
17 cells that induce experimental autoimmune encephalomyelitis (EAE) in animals. Here we show that human ...peripheral blood IFN-γ
+
IL-17
+
(T
H
1/17) and IFN-γ
−
IL-17
+
(T
H
17) CD4
+
T cells display distinct transcriptional profiles in high-throughput transcription analyses. Compared to T
H
17 cells, T
H
1/17 cells have gene signatures with marked similarity to mouse pathogenic T
H
17 cells. Assessing 15 representative signature genes in patients with multiple sclerosis, we find that T
H
1/17 cells have elevated expression of
CXCR3
and reduced expression of
IFNG
,
CCL3
,
CLL4
,
GZMB
, and
IL10
compared to healthy controls. Moreover, higher expression of
IL10
in T
H
17 cells is found in clinically stable vs. active patients. Our results define the molecular signature of human pro-inflammatory T
H
17 cells, which can be used to both identify pathogenic T
H
17 cells and to measure the effect of treatment on T
H
17 cells in human autoimmune diseases.
Spousal clustering of diabetes merits attention. Whether old-age vulnerability or a shared family environment determines the concordance of diabetes is also uncertain. This study investigated the ...spousal concordance of diabetes and compared the risk of diabetes concordance between couples and noncouples by using nationally representative data.
A total of 22,572 individuals identified from the 2002-2013 National Health Insurance Research Database of Taiwan constituted 5,643 couples and 5,643 noncouples through 1:1 dual propensity score matching (PSM). Factors associated with concordance in both spouses with diabetes were analyzed at the individual level. The risk of diabetes concordance between couples and noncouples was compared at the couple level. Logistic regression was the main statistical method. Statistical data were analyzed using SAS 9.4. C&RT and Apriori of data mining conducted in IBM SPSS Modeler 13 served as a supplement to statistics.
High odds of the spousal concordance of diabetes were associated with old age, middle levels of urbanization, and high comorbidities (all P < 0.05). The dual PSM analysis revealed that the risk of diabetes concordance was significantly higher in couples (5.19%) than in noncouples (0.09%; OR = 61.743, P < 0.0001).
A high concordance rate of diabetes in couples may indicate the influences of assortative mating and shared environment. Diabetes in a spouse implicates its risk in the partner. Family-based diabetes care that emphasizes the screening of couples at risk of diabetes by using the identified risk factors is suggested in prospective clinical practice interventions.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
A central goal of biology is understanding and describing the molecular basis of plasticity: the sets of genes that are combinatorially selected by exogenous and endogenous environmental changes, and ...the relations among the genes. The most viable current approach to this problem consists of determining whether sets of genes are connected by some common theme, e.g. genes from the same pathway are overrepresented among those whose differential expression in response to a perturbation is most pronounced. There are many approaches to this problem, and the results they produce show a fair amount of dispersion, but they all fall within a common framework consisting of a few basic components. We critically review these components, suggest best practices for carrying out each step, and propose a voting method for meeting the challenge of assessing different methods on a large number of experimental data sets in the absence of a gold standard.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Papaya (
Carica papaya
L.) is an important economic crop. An efficient and low-cost propagation
ex vitro
process is required for commercial papaya plantlet production. In this study, a propagation ...process of papaya was established by minicutting and evaluating parameters affecting survival. Individual shoots (1.5 cm) were cut from papaya multiple shoots
in vitro
as the minicuttings. After dipping in 400.0 mg L
−1
indole-3-butyric acid (IBA), they were planted into the nursery pro trays with 104 holes containing vermiculite, perlite, and King Root® substrate at 1:1:1 ratio, and then covered with a lid to keep the ratio of humidity (RH) at 100% for root development. After a 3-wk treatment in a growth chamber (28°C), the rooting rate, root number, root length, and stem length were promoted to 91.1%, 2.9, 3.71 cm, and 1.88 cm, respectively. Combining the treatment with 400 mg L
−1
IBA and 1/2 Murashige and Skoog (MS) salt solution supplemented at the 14th day after cutting gives the best growth potential for papaya plantlets, especially increasing root length to 4.55 cm. It also effectively enhances the survival rate of plantlets to 93.3%. This process saves the rooting initiation medium and time cost and avoids the complicated procedure of cleaning medium from root surface, which results in root damage. Under this minicutting process, the papaya plantlets thrived and were optimally suited to field cultivation.
Researchers are continuously developing various energy-saving technologies to enhance the internal combustion engine efficiency. Among them, continuous variable valve timing and variable valve lift ...system is one potential technology. To achieve this ability, a new type of electric valve, known as magnetorheological valve train, was introduced, which is based on the magnetorheological fluid’s active behavior. In this study, gasoline engine models are established for dynamic simulations of an engine with the magnetorheological valve train. Volumetric efficiency and performance of the engine with different magnetorheological valve train valve lifts and valve timings at engine speeds between 2000 and 6000 r/min are also analyzed. Simulation results show that, at low engine speeds, the lift of the valve has little effect on the engine performance. However, under high and medium engine speeds, the lift of the valve significantly affects the performance; the smaller the valve lift, the smaller the volumetric efficiency. Likewise, an adjustment of valve opening angle timing to reduce the valve overlap angle effectively increased the engine volumetric efficiency at low engine speeds.
Underlying pathophysiological mechanisms drive excessive clustering of cardiometabolic risk factors, causing metabolic syndrome (MetS). MetS status may transform as adolescents transition to young ...adulthood. This study investigated the latent clustering structure and its stability for MetS during adolescence, and assessed the anthropometric and clinical metabolic determinants for MetS transformation. A community-based representative adolescent cohort (
= 1516) was evaluated for MetS using four diagnostic criteria, and was followed for 2.2 years to identify new-onset MetS. The clustering structure underlying cardiometabolic parameters was stable across adolescence; both comprised a fat-blood pressure (BP)-glucose three-factor structure (total variance explained: 68.8% and 69.7% at baseline and follow-up, respectively). Among adolescents with MetS-negative at baseline, 3.2-4.4% had incident MetS after 2.2 years. Among adolescents with MetS-positive at baseline, 52.0-61.9% experienced MetS remission, and 38.1-48.0% experienced MetS persistence. Increased systolic BP (SBP) was associated with a high MetS incidence risk, while decreased levels of SBP and glucose were associated with MetS remission. Compared with adolescents with a normal metabolic status at baseline, those with an initial abdominal obesity and increased triglycerides level had a 15.0- and 5.7-fold greater risk for persistent abnormality, respectively. Abdominal obesity and low high-density lipoprotein cholesterol are two abnormal MetS components that highly persist during adolescence, and are the intervention targets for reducing the future risk of cardiometabolic disorders.
In order to improve the detection accuracy of an algorithm in the complex environment of a coal mine, including low-illumination, motion-blur, occlusions, small-targets, and background-interference ...conditions; reduce the number of model parameters; improve the detection speed of the algorithm; and make it meet the real-time detection requirements of edge equipment, a real-time obstacle detection method in the driving of driverless rail locomotives based on DeblurGANv2 and improved YOLOv4 is proposed in this study. A blurred image was deblurred using DeblurGANv2. The improved design was based on YOLOv4, and the lightweight feature extraction network MobileNetv2 was used to replace the original CSPDarknet53 network to improve the detection speed of the algorithm. There was a high amount of background interference in the target detection of the coal mine scene. In order to strengthen the attention paid to the target, the SANet attention module was embedded in the Neck network to improve the detection accuracy of the algorithm under low-illumination, target-occlusion, small-target, and other conditions. To further improve the detection accuracy of the algorithm, the K-means++ algorithm was adopted to cluster prior frames, and the focal loss function was introduced to increase the weight loss of small-target samples. The experimental results show that the deblurring of the motion-blurred image can effectively improve the detection accuracy of obstacles and reduce missed detections. Compared with the original YOLOv4 algorithm, the improved YOLOv4 algorithm increases the detection speed by 65.85% to 68 FPS and the detection accuracy by 0.68% to 98.02%.
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