An optimization study of estimating blood pressure models based on pulse arrival time for continuous monitoring

Continuous blood pressure (BP) monitoring has a significant meaning for the prevention and early diagnosis of cardiovascular disease. However, under different calibration methods, it is difficult to determine which model is better for estimating BP. This study was firstly designed to reveal a better BP estimation model by evaluating and optimizing different BP models under a justified and uniform criterion, i.e., the advanced point-to-point pairing method (PTP). Here, the physical trial in this study caused the BP increase largely. In addition, the PPG and ECG signals were collected while the cuff bps were measured for each subject. The validation was conducted on four popular vascular elasticity (VE) models (MK-EE, L-MK, MK-BH, and dMK-BH) and one representative elastic tube (ET) model, i.e., M-M. The results revealed that the VE models except for L-MK outperformed the ET model. The linear L-MK as a VE model had the largest estimated error, and the nonlinear M-M model had a weaker correlation between the estimated BP and the cuff BP than MK-EE, MK-BH, and dMK-BH models. Further, in contrast to L-MK, the dMK-BH model had the strongest correlation and the smallest difference between the estimated BP and the cuff BP including systolic blood pressure (SBP) and diastolic blood pressure (DBP) than others. In this study, the simple MK-EE model showed the best similarity to the dMK-BH model. There were no significant changes between MK-EE and dMK-BH models. These findings indicated that the nonlinear MK-EE model with low estimated error and simple mathematical expression was a good choice for application in wearable sensor devices for cuff-less BP monitoring compared to others

Effect of temperature on the accumulation of marine biogenic gels in the surface microlayer near the outlet of nuclear power plants and adjacent areas in the Daya Bay, China

The surface microlayer (SML) in marine systems is often characterized by an enrichment of biogenic, gel-like particles, such as the polysaccharide-containing transparent exopolymer particles (TEP) and the protein-containing Coomassie stainable particles (CSP). This study investigated the distribution of TEP and CSP, in the SML and underlying water, as well as their bio-physical controlling factors in Daya Bay, an area impacted by warm discharge from two Nuclear power plants (Npp’s) and aquaculture during a research cruise in July 2014. The SML had higher proportions of cyanobacteria and of pico-size Chl a contrast to the underlayer water, particularly at the nearest outlet station characterized by higher temperature. Diatoms, dinoflagellates and chlorophyll a were depleted in the SML. Both CSP and TEP abundance and total area were enriched in the SML relative to the underlying water, with enrichment factors (EFs) of 1.5–3.4 for CSP numbers and 1.32–3.2 for TEP numbers. Although TEP and CSP showed highest concentration in the region where high productivity and high nutrient concertation were observed, EFs of gels and of dissolved organic carbon (DOC) and dissolved acidic polysaccharide (> 1 kDa), exhibited higher values near the outlet of the Npp’s than in the adjacent waters. The positive relation between EF’s of gels and temperature and the enrichment of cyanobacteria in the SML may be indicative of future conditions in a warmer ocean, suggesting potential effects on adjusting phytoplankton community, biogenic element cycling and air-sea exchange processe

Identify submitochondria and subchloroplast locations with pseudo amino acid composition: Approach from the strategy of discrete wavelet transform feature extraction

AbstractIt is very challenging and complicated to predict protein locations at the sub-subcellular level. The key to enhancing the prediction quality for protein sub-subcellular locations is to grasp the core features of a protein that can discriminate among proteins with different subcompartment locations. In this study, a different formulation of pseudoamino acid composition by the approach of discrete wavelet transform feature extraction was developed to predict submitochondria and subchloroplast locations. As a result of jackknife cross-validation, with our method, it can efficiently distinguish mitochondrial proteins from chloroplast proteins with total accuracy of 98.8% and obtained a promising total accuracy of 93.38% for predicting submitochondria locations. Especially the predictive accuracy for mitochondrial outer membrane and chloroplast thylakoid lumen were 82.93% and 82.22%, respectively, showing an improvement of 4.88% and 27.22% when other existing methods were compared. The results indicated that the proposed method might be employed as a useful assistant technique for identifying sub-subcellular locations. We have implemented our algorithm as an online service called SubIdent (http://bioinfo.ncu.edu.cn/services.aspx)

SPOT: Scalable 3D Pre-training via Occupancy Prediction for Autonomous Driving

Annotating 3D LiDAR point clouds for perception tasks including 3D object detection and LiDAR semantic segmentation is notoriously time-and-energy-consuming. To alleviate the burden from labeling, it is promising to perform large-scale pre-training and fine-tune the pre-trained backbone on different downstream datasets as well as tasks. In this paper, we propose SPOT, namely Scalable Pre-training via Occupancy prediction for learning Transferable 3D representations, and demonstrate its effectiveness on various public datasets with different downstream tasks under the label-efficiency setting. Our contributions are threefold: (1) Occupancy prediction is shown to be promising for learning general representations, which is demonstrated by extensive experiments on plenty of datasets and tasks. (2) SPOT uses beam re-sampling technique for point cloud augmentation and applies class-balancing strategies to overcome the domain gap brought by various LiDAR sensors and annotation strategies in different datasets. (3) Scalable pre-training is observed, that is, the downstream performance across all the experiments gets better with more pre-training data. We believe that our findings can facilitate understanding of LiDAR point clouds and pave the way for future exploration in LiDAR pre-training. Codes and models will be released.Comment: 15 pages, 9 figure

2-[3-((Z)-2-{4-[Bis(2-chloro­eth­yl)amino]­phen­yl}ethen­yl)-5,5-dimethyl­cyclo­hex-2-en-1-yl­idene]propane­dinitrile

The highly conjugated title compound, C23H25Cl2N3, is nearly planar (the mean deviation from the plane being 0.049 Å), except for the –C(CH3)2 group on the cyclo­hexene ring and the two CH2Cl groups. The cyclo­hexene ring has an envelope configuration. In the crystal, the packing is stabilized by C—H⋯Cl inter­actions and C—H⋯π inter­actions involving the benzene ring

Timeline editing of objects in video

We present a video editing technique based on changing the timelines of individual objects in video, which leaves them in their original places but puts them at different times. This allows the production of object-level slow motion effects, fast motion effects, or even time reversal. This is more flexible than simply applying such effects to whole frames, as new relationships between objects can be created. As we restrict object interactions to the same spatial locations as in the original video, our approach can produce high-quality results using only coarse matting of video objects. Coarse matting can be done efficiently using automatic video object segmentation, avoiding tedious manual matting. To design the output, the user interactively indicates the desired new life spans of objects, and may also change the overall running time of the video. Our method rearranges the timelines of objects in the video whilst applying appropriate object interaction constraints. We demonstrate that, while this editing technique is somewhat restrictive, it still allows many interesting results

Protection Effect of Exogenous Fibroblast Growth Factor 21 on the Kidney Injury in Vascular Calcification Rats

Background: Chronic kidney disease (CKD) is closely related to the cardiovascular events in vascular calcification (VC). However, little has known about the characteristics of kidney injury caused by VC. Fibroblast growth factor 21 (FGF21) is an endocrine factor, which takes part in various metabolic actions with the potential to alleviate metabolic disorder diseases. Even FGF21 has been regarded as a biomarker in CKD, the role of FGF21 in CKD remains unclear. Therefore, in this study, we evaluate the FGF21 on the kidney injury in VC rats. Methods: The male Sprague-Dawley rats were divided into three groups: (1) control group, (2) Vitamin D3 plus nicotine (VDN)-induced VC group, (3) FGF21-treated VDN group. After 4 weeks, the rats were killed and the blood was collected for serum creatinine, urea nitrogen, calcium, and phosphate measurement. Moreover, the renal tissues were homogenized for alkaline phosphatases (ALPs) activity and calcium content. The levels of FGF21 protein were measured by radioimmunoassay. The levels of β-Klotho and FGF receptor 1 (FGFR1) protein were measured by enzyme-linked immunosorbent assay (ELISA). The structural damage and calcifications in aortas were stained by Alizarin-red S. Moreover, the structure of kidney was observed by hematoxylin and eosin staining. Results: The renal function impairment caused by VDN modeling was ameliorated by FGF21 treatment, inhibited the elevated serum creatinine and urea level by 20.5% (34.750 ± 4.334 μmol/L vs. 27.630 ± 2.387 μmol/L) and 4.0% (7.038 ± 0.590 mmol/L vs. 6.763 ± 0.374 mmol/L; P \u3c 0.01), respectively, together with the structural damages of glomerular atrophy and renal interstitial fibrosis. FGF21 treatment downregulated the ALP activity, calcium content in the kidney of VC rats by 42.1% (P \u3c 0.01) and 11.7% (P \u3c 0.05) as well as ameliorated the aortic injury and calcification as compared with VDN treatment alone group, indicating an ameliorative effect on VC. ELISA assays showed that the expression of β-Klotho, a component of FGF21 receptor system, was increased in VDN-treated VC rats by 37.4% (6.588 ± 0.957 pg/mg vs. 9.054 ± 0.963 pg/mg; P \u3c 0.01), indicating an FGF21-resistant state. Moreover, FGF21 treatment downregulated the level of β-Klotho in renal tissue by 16.7% (9.054 ± 0.963 pg/mg vs. 7.544 ± 1.362 pg/mg; P \u3c 0.05). However, the level of FGFR1, the receptor of FGF21, kept unchanged under VDN and VDN plus FGF21 administration (0.191 ± 0.0376 ng/mg vs. 0.189 ± 0.032 ng/mg vs. 0.181 ± 0.034 ng/mg; P \u3e 0.05). Conclusions: In the present study, FGF21 was observed to ameliorate the kidney injury in VDN-induced VC rats. FGF21 might be a potential therapeutic factor in CKD by cutting off the vicious circle between VC and kidney injury

A large area, high counting rate micromegas-based neutron detector for BNCT

Beam monitoring and evaluation are very important to boron neutron capture therapy (BNCT), and a variety of detectors have been developed for these applications. However, most of the detectors used in BNCT only have a small detection area, leading to the inconvenience of the full-scale 2-D measurement of the beam. Based on micromegas technology, we designed a neutron detector with large detection area and high counting rate. This detector has a detection area of 288 mm multiples 288 mm and can measure thermal, epithermal, and fast neutrons with different detector settings. The BNCT experiments demonstrated that this detector has a very good 2-D imaging performance for the thermal, epithermal, fast neutron and gamma components, a highest counting rate of 94 kHz/channel, and a good linearity response to the beam power. Additionally, the flux fraction of each component can be calculated based on the measurement results. The Am-Be neutron source experiment indicates that this detector has a spatial resolution of approximately 1.4 mm, meeting the requirements of applications in BNCT. It is evident that this micromegas-based neutron detector with a large area and high counting rate capability has great development prospects in BNCT beam monitoring and evaluation applications