TinyTracker: Ultra-Fast and Ultra-Low-Power Edge Vision In-Sensor for Gaze Estimation

Intelligent edge vision tasks encounter the critical challenge of ensuring power and latency efficiency due to the typically heavy computational load they impose on edge platforms.This work leverages one of the first "AI in sensor" vision platforms, IMX500 by Sony, to achieve ultra-fast and ultra-low-power end-to-end edge vision applications. We evaluate the IMX500 and compare it to other edge platforms, such as the Google Coral Dev Micro and Sony Spresense, by exploring gaze estimation as a case study. We propose TinyTracker, a highly efficient, fully quantized model for 2D gaze estimation designed to maximize the performance of the edge vision systems considered in this study. TinyTracker achieves a 41x size reduction (600Kb) compared to iTracker [1] without significant loss in gaze estimation accuracy (maximum of 0.16 cm when fully quantized). TinyTracker's deployment on the Sony IMX500 vision sensor results in end-to-end latency of around 19ms. The camera takes around 17.9ms to read, process and transmit the pixels to the accelerator. The inference time of the network is 0.86ms with an additional 0.24 ms for retrieving the results from the sensor. The overall energy consumption of the end-to-end system is 4.9 mJ, including 0.06 mJ for inference. The end-to-end study shows that IMX500 is 1.7x faster than CoralMicro (19ms vs 34.4ms) and 7x more power efficient (4.9mJ VS 34.2mJ

LinearCoFold and LinearCoPartition: Linear-Time Algorithms for Secondary Structure Prediction of Interacting RNA molecules

Many ncRNAs function through RNA-RNA interactions. Fast and reliable RNA structure prediction with consideration of RNA-RNA interaction is useful. Some existing tools are less accurate due to omitting the competing of intermolecular and intramolecular base pairs, or focus more on predicting the binding region rather than predicting the complete secondary structure of two interacting strands. Vienna RNAcofold, which reduces the problem into the classical single sequence folding by concatenating two strands, scales in cubic time against the combined sequence length, and is slow for long sequences. To address these issues, we present LinearCoFold, which predicts the complete minimum free energy structure of two strands in linear runtime, and LinearCoPartition, which calculates the cofolding partition function and base pairing probabilities in linear runtime. LinearCoFold and LinearCoPartition follows the concatenation strategy of RNAcofold, but are orders of magnitude faster than RNAcofold. For example, on a sequence pair with combined length of 26,190 nt, LinearCoFold is 86.8x faster than RNAcofold MFE mode (0.6 minutes vs. 52.1 minutes), and LinearCoPartition is 642.3x faster than RNAcofold partition function mode (1.8 minutes vs. 1156.2 minutes). Different from the local algorithms, LinearCoFold and LinearCoPartition are global cofolding algorithms without restriction on base pair length. Surprisingly, LinearCoFold and LinearCoPartition's predictions have higher PPV and sensitivity of intermolecular base pairs. Furthermore, we apply LinearCoFold to predict the RNA-RNA interaction between SARS-CoV-2 gRNA and human U4 snRNA, which has been experimentally studied, and observe that LinearCoFold's prediction correlates better to the wet lab results

Ultra-Efficient On-Device Object Detection on AI-Integrated Smart Glasses with TinyissimoYOLO

Smart glasses are rapidly gaining advanced functionality thanks to cutting-edge computing technologies, accelerated hardware architectures, and tiny AI algorithms. Integrating AI into smart glasses featuring a small form factor and limited battery capacity is still challenging when targeting full-day usage for a satisfactory user experience. This paper illustrates the design and implementation of tiny machine-learning algorithms exploiting novel low-power processors to enable prolonged continuous operation in smart glasses. We explore the energy- and latency-efficient of smart glasses in the case of real-time object detection. To this goal, we designed a smart glasses prototype as a research platform featuring two microcontrollers, including a novel milliwatt-power RISC-V parallel processor with a hardware accelerator for visual AI, and a Bluetooth low-power module for communication. The smart glasses integrate power cycling mechanisms, including image and audio sensing interfaces. Furthermore, we developed a family of novel tiny deep-learning models based on YOLO with sub-million parameters customized for microcontroller-based inference dubbed TinyissimoYOLO v1.3, v5, and v8, aiming at benchmarking object detection with smart glasses for energy and latency. Evaluations on the prototype of the smart glasses demonstrate TinyissimoYOLO's 17ms inference latency and 1.59mJ energy consumption per inference while ensuring acceptable detection accuracy. Further evaluation reveals an end-to-end latency from image capturing to the algorithm's prediction of 56ms or equivalently 18 fps, with a total power consumption of 62.9mW, equivalent to a 9.3 hours of continuous run time on a 154mAh battery. These results outperform MCUNet (TinyNAS+TinyEngine), which runs a simpler task (image classification) at just 7.3 fps per second

Association of n-3 polyunsaturated fatty acid intakes with juvenile myopia: A cross-sectional study based on the NHANES database

AimInflammation is involved in the development of myopia. n-3 polyunsaturated fatty acids (n-3 PUFAs) have vasodilating and anti-inflammatory effects, which may be involved in controlling myopia. It is of great significance to explore the relationship between n-3 PUFA intakes and juvenile myopia in order to control and alleviate myopia among teenagers through dietary intervention.MethodsSociodemographic data, information of nutrient intakes, cotinine, PUFAs, and eye refractive status of 1,128 juveniles were extracted from the National Health and Nutrition Examination Survey (NHANES) database in this cross-sectional study. PUFAs contained total polyunsaturated fatty acid (TPFAs), alpha-linolenic acid, octadecatetraenoic acid, eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA), and docosahexaenoic acid (DHA). Covariates were screened by comparison among groups of normal vision, low myopia, and high myopia. The association between n-3 PUFA intakes and the risk of juvenile myopia was evaluated using univariate and multivariate logistic regression analyses with odds ratios (ORs) and 95% confidence intervals (CIs).ResultsAmong the juveniles, 788 (70.68%) had normal vision, 299 (25.80%) had low myopia, and 41 (3.52%) had high myopia. There were significant differences in average EPA and DHA intakes among the three groups, and mean DPA and DHA intakes in the normal vision group were lower than those in the low myopia group (P < 0.05). After adjustment for age, gender, TPFAs, and cotinine, a high dietary intake of EPA (≥11 mg/1,000 kcal) in juveniles seemed to be associated with the risk of high myopia (OR = 0.39, 95% CI: 0.18–0.85), while no significant associations were identified between n-3 PUFA intakes and the risk of low myopia.ConclusionA high dietary intake of EPA may be associated with a decreased risk of high myopia among juveniles. A further prospective study is needed to validate this observation

CXCR4 Accelerates Osteoclastogenesis Induced by Non-Small Cell Lung Carcinoma Cells Through Self-Potentiation and VCAM1 Secretion

Background/Aims: Non-small cell lung carcinoma (NSCLC) metastasis to bone leads to skeletal-related events and a poor quality of life. Unravelling the mechanism of metastasis is crucial for improving survival. Previous work has implicated the role of CXCR4 in bone metastasis; however, the underlying mechanisms are unknown. Methods: The human bone metastasis tissue samples were obtained from lung cancer patients during surgery with consents. The patients were followed up and the overall survival curve was analysed. The expression of CXCR4, VCAM1, and ADAM17 was measured with real-time PCR, western blot and immunochemistry staining in human tissue or NSCLC cell lines. The effects of CXCR4, soluble VCAM1 and ADAM17 on NSCLC proliferation, migration and invasion were measured with CCK-8, monolayer scratch assay and transwell chamber, respectively. The amount of soluble VCAM1 in the conditioned medium was detected with ELISA. Tartrate-resistant acid phosphatasethe (TRAP) staining was performed to stain the multinucleated cells regarded as osteoclasts. Results: In this study, CXCR4 was found to be highly expressed in bone destruction area of metastatic NSCLC samples and related to poor survival in NSCLC patients with bone metastasis. CXCR4 potentiated NSCLC with enhanced proliferation and invasion abilities, while CXCR4 knockdown significantly suppressed the growth and invasion. Furthermore, CXCR4 promoted lung cancer-induced osteoclast differentiation with increased osteoclast formation. We also found that soluble VCAM1 (sVCAM1) secreted in NSCLC contributed to the osteoclastogenesis induced by CXCR4. The overexpression of CXCR4 increased sVCAM1, and the sVCAM1 secreted from CXCR4-overexpressing NSCLC cells recruited and arrested additional osteoclast progenitors to promote osteoclastogenesis. ADAM17 was confirmed to act as a downstream mediator of CXCR4. The chemical inhibition of ADAM17 with TAPI-2 decreased sVCAM1 secretion and the number of TRAP+ osteoclasts. Conclusion: Taken together, these results indicated that CXCR4 potentiated NSCLC and promoted osteoclastogenesis through sVCAM1, which was cleaved by ADAM17. These data support the pivotal role of the cross talk between CXCR4 and ADAM17-VCAM1 in NSCLC-induced bone metastasis

Impact of primary glaucoma on health-related quality of life in China: the handan eye study

Abstract Background We assessed health-related quality of life (HRQOL) and its determinants among rural glaucoma participants compared to age-matched normal controls in the population-based Handan Eye Study (HES), in rural Yongnian County, northern China. Methods We enrolled 99 adults with glaucoma (mean age 63.0 ± 11.0 years), including primary open-angle glaucoma (POAG, n = 67) and primary angle-closure glaucoma (PACG, n = 32) and 102 controls (mean age 58.5 ± 5.3 years) with normal visual acuity and visual field and no history of glaucoma. Results of ophthalmic examinations and socioeconomic data were recorded. HRQOL was measured using the EQ-5D (converted to utility valves, UVs), and visual function (VF) and vision-related quality of life (VRQOL) were evaluated using the visual function-quality of life (VF-QOL) instrument. Primary and secondary outcome measures EQ-5D and VF-QOL scores. Results The mean UVs, VF, and VRQOL scores for glaucoma cases were 0.98 ± 0.04, 87.9 ± 15.2, and 95.5 ± 12.8, respectively, significantly worse than VF (94.4 ± 4.4) and VRQOL (100.0 ± 0.0) among controls, even after adjusting for age, gender, educational level, and family income (P = 0.015, P = 0.033). UVs were significantly lower among glaucoma participants with impaired VRQOL (55.4 ± 11.5) compared to those with normal VRQOL scores (99.1 ± 2.8) (UVs: 0.92 ± 0.08 vs. 0.99 ± 0.03, P = 0.036), also after adjustment for age and family income (P = 0.006). Participants with PACG had significantly lower VF and VRQOL scores compared to POAG (77.8 ± 21.4 vs. 92.9 ± 6.8, P < 0.001; 89.0 ± 18.1 vs. 98.7 ± 7.5, P < 0.001). Conclusion Participants with glaucoma have worse visual function and related quality of life compared to age-matched normal population controls. Participants with PACG have lower VF and VRQOL compared to those with POAG. UVs can be used for cost-effectiveness research and to support public health strategies for glaucoma in rural China

Association between Inflammatory Bowel Disease and Pancreatitis: A PRISMA-Compliant Systematic Review

Background/Objectives. This systematic review was conducted to investigate the association between pancreatitis and IBD. Methods. MEDLINE, Embase, and CENTRAL were systematically searched for correlative studies till 2 November 2019. RevMan5.3 was used to estimate relevance. Results. Three studies with 166008 participants were included. The risk of pancreatitis significantly increased in the patients with CD (OR, 3.40; 95% CI, 2.70-4.28; P<0.00001) and UC (OR, 2.49; 95% CI, 1.91-3.26; P<0.00001). Increased risks of CD (OR, 12.90; 95% CI, 5.15-32.50; P<0.00001) and UC (OR, 2.80; 95% CI, 1.00-7.86; P=0.05) were found in patients with chronic pancreatitis. As for patients with acute pancreatitis, there were significant association of CD (OR, 3.70; 95% CI, 1.90-7.60; P=0.0002), but were not UC. Conclusions. The evidence confirmed an association between pancreatitis and IBD. When pancreatitis patients have chronic diarrhea and mucus blood stool or IBD patients have repeated abdominal pain and weight loss, they should consult pancreatic and gastrointestinal specialists