SupFusion: Supervised LiDAR-Camera Fusion for 3D Object Detection

In this paper, we propose a novel training strategy called SupFusion, which provides an auxiliary feature level supervision for effective LiDAR-Camera fusion and significantly boosts detection performance. Our strategy involves a data enhancement method named Polar Sampling, which densifies sparse objects and trains an assistant model to generate high-quality features as the supervision. These features are then used to train the LiDAR-Camera fusion model, where the fusion feature is optimized to simulate the generated high-quality features. Furthermore, we propose a simple yet effective deep fusion module, which contiguously gains superior performance compared with previous fusion methods with SupFusion strategy. In such a manner, our proposal shares the following advantages. Firstly, SupFusion introduces auxiliary feature-level supervision which could boost LiDAR-Camera detection performance without introducing extra inference costs. Secondly, the proposed deep fusion could continuously improve the detector's abilities. Our proposed SupFusion and deep fusion module is plug-and-play, we make extensive experiments to demonstrate its effectiveness. Specifically, we gain around 2% 3D mAP improvements on KITTI benchmark based on multiple LiDAR-Camera 3D detectors.Comment: Accepted to ICCV202

HIF-1α effects on angiogenic potential in human small cell lung carcinoma

<p>Abstract</p> <p>Background</p> <p>Hypoxia-inducible factor-1 alpha (HIF-1α) maybe an important regulatory factor for angiogenesis of small cell lung cancer (SCLC). Our study aimed to investigate the effect of HIF-1α on angiogenic potential of SCLC including two points: One is the effect of HIF-1α on the angiogenesis of SCLC <it>in vivo</it>. The other is the regulation of angiogenic genes by HIF-1α <it>in vitro </it>and <it>in vivo</it>.</p> <p>Methods</p> <p><it>In vivo </it>we used an alternative method to study the effect of HIF-1a on angiogenic potential of SCLC by buliding NCI-H446 cell transplantation tumor on the chick embryo chorioallantoic membrane (CAM) surface. <it>In vitro </it>we used microarray to screen out the angiogenic genes regulated by HIF-1a and tested their expression level in CAM transplantation tumor by RT-PCR and Western-blot analysis.</p> <p>Results</p> <p><it>In vivo </it>angiogenic response surrounding the SCLC transplantation tumors in chick embryo chorioallantoic membrane (CAM) was promoted after exogenous HIF-1α transduction (p < 0.05). <it>In vitro </it>the changes of angiogenic genes expression induced by HIF-1α in NCI-H446 cells were analyzed by cDNA microarray experiments. HIF-1α upregulated the expression of angiogenic genes VEGF-A, TNFAIP6, PDGFC, FN1, MMP28, MMP14 to 6.76-, 6.69-, 2.26-, 2.31-, 4.39-, 2.97- fold respectively and glycolytic genes GLUT1, GLUT2 to2.98-, 3.74- fold respectively. In addition, the expression of these angiogenic factors were also upregulated by HIF-1α in the transplantion tumors in CAM as RT-PCR and Western-blot analysis indicated.</p> <p>Conclusions</p> <p>These results indicated that HIF-1α may enhance the angiogenic potential of SCLC by regulating some angiogenic genes such as VEGF-A, MMP28 etc. Therefore, HIF-1α may be a potential target for the gene targeted therapy of SCLC.</p

Identification of special key genes for alcohol-related hepatocellular carcinoma through bioinformatic analysis

Background Alcohol-related hepatocellular carcinoma (HCC) was reported to be diagnosed at a later stage, but the mechanism was unknown. This study aimed to identify special key genes (SKGs) during alcohol-related HCC development and progression. Methods The mRNA data of 369 HCC patients and the clinical information were downloaded from the Cancer Genome Atlas project (TCGA). The 310 patients with certain HCC-related risk factors were included for analysis and divided into seven groups according to the risk factors. Survival analyses were applied for the HCC patients of different groups. The patients with hepatitis B virus or hepatitis C virus infection only were combined into the HCC-V group for further analysis. The differentially expressed genes (DEGs) between the HCCs with alcohol consumption only (HCC-A) and HCC-V tumors were identified through limma package in R with cutoff criteria│log2 fold change (logFC)|>1.0 and p 2.0 and adj.p < 0.05. The intersection of the two sets of DEGs was considered SKGs which were then investigated for their specificity through comparisons between HCC-A and other four HCC groups. The SKGs were analyzed for their correlations with HCC-A stage and grade and their prognostic power for HCC-A patients. The expressional differences of the SKGs in the HCCs in whole were also investigated through Gene Expression Profiling Interactive Analysis (GEPIA). The SKGs in HCC were validated through Oncomine database analysis. Results Pathological stage is an independent prognostic factor for HCC patients. HCC-A patients were diagnosed later than HCC patients with other risk factors. Ten SKGs were identified and nine of them were confirmed for their differences in paired samples of HCC-A patients. Three (SLC22A10, CD5L, and UROC1) and four (SLC22A10, UROC1, CSAG3, and CSMD1) confirmed genes were correlated with HCC-A stage and grade, respectively. SPP2 had a lower trend in HCC-A tumors and was negatively correlated with HCC-A stage and grade. The SKGs each was differentially expressed between HCC-A and at least one of other HCC groups. CD5L was identified to be favorable prognostic factor for overall survival while CSMD1 unfavorable prognostic factor for disease-free survival for HCC-A patients and HCC patients in whole. Through Oncomine database, the dysregulations of the SKGs in HCC and their clinical significance were confirmed. Conclusion The poor prognosis of HCC-A patients might be due to their later diagnosis. The SKGs, especially the four stage-correlated genes (CD5L, SLC22A10, UROC1, and SPP2) might play important roles in HCC development, especially alcohol-related HCC development and progression. CD5L might be useful for overall survival and CSMD1 for disease-free survival predication in HCC, especially alcohol-related HCC

Molecular Mechanisms of Ferroptosis and Its Role in Pulmonary Disease

Ferroptosis is a new mode of cell death that is characterized by the excessive accumulation of iron and lipid peroxides. It has unique morphological changes and disparate biochemical features and plays an intricate role in many pathophysiological processes. A great deal of researches confirms that ferroptosis can be regulated by numerous molecules through different mechanisms, supporting great potentials for novel pharmacological therapeutics. Recently, several studies reveal that ferroptosis is also closely associated with the initiation and development of respiratory disease. Understanding the specific mechanism, the molecular trait of ferroptosis and their relationship with pulmonary disease could provide significant references regarding effective treatment of these obstinate disease

Ample Evidence: Dehydroepiandrosterone (DHEA) Conversion into Activated Steroid Hormones Occurs in Adrenal and Ovary in Female Rat.

Dehydroepiandrosterone (DHEA) is important for human health, especially for women. All estrogens and practically half of androgens are synthesized from DHEA in peripheral tissues. However, the mechanism and exact target tissues of DHEA biotransformation in the female are not fully clear. The present study showed that maximal content of androstenedione (AD) and testosterone (T) were observed at 3h after DHEA administration in female rats, which was 264% and 8000% above the control, respectively. Estradiol (E2) content significantly increased at 6h after DHEA administration, which was 113% higher than that in control group. Gavage with DHEA could significantly reduce 3β-hydroxysteroid dehydrogenase (3β-HSD) mRNA level at 3-12h and 17β-hydroxysteroid dehydrogenase (17β-HSD) mRNA level at 12h in ovary, while increasing aromatase mRNA levels at 6, 24, and 48 h. It is interesting that administration of DHEA caused a significant increase of 17β-HSD, 3β-HSD and aromatase mRNA levels in adrenal. The AD and T contents also markedly increased by 537% and 2737% after DHEA administration in ovariectomised rats, in company with a significant increase in 17β-HSD and 3β-HSD mRNA levels and decreased aromatase mRNA level in adrenal. However, DHEA administration did not restore the decreased E2, estrone (E1), and progesterone (P) caused by the removal of the ovaries in females. These results clearly illustrated that exogenous DHEA is preferentially converted into androgens in adrenal, while its conversion to estrogens mainly happens in the ovary through steroidogenic enzyme in female rats

Three Versions of the Perceived Stress Scale: Psychometric Evaluation in a Nationally Representative Sample of Chinese Adults during the COVID-19 Pandemic

(1) Background: The COVID-19 outbreak has created pressure in people’s daily lives, further threatening public health. Thus, it is important to assess people’s perception of stress during COVID-19 for both research and practical purposes. The Perceived Stress Scale (PSS) is one of the most widely used instruments to measure perceived stress; however, previous validation studies focused on specific populations, possibly limiting the generalization of results. (2) Methods: This study tested the psychometric properties of three versions of the Chinese Perceived Stress Scale (CPSS-14, CPSS-10, and CPSS-4) in the Chinese general population during the COVID-19 pandemic. A commercial online survey was employed to construct a nationally representative sample of 1133 adults in Mainland China (548 males and 585 females) during a one-week period. (3) Results: The two-factor (positivity and negativity) solution for the three versions of the CPSS showed a good fit with the data. The CPSS-14 and CPSS-10 had very good reliability and the CPSS-4 showed acceptable reliability, supporting the concurrent validity of the CPSS. (4) Conclusions: All three versions of the CPSS appear to be appropriate for use in research with samples of adults in the Chinese general population under the COVID-19 crisis. The CPSS-10 and CPSS-14 both have strong psychometric properties, but the CPSS-10 would have more utility because it is shorter than the CPSS-14. However, the CPSS-4 is an acceptable alternative when administration time is limited

Application of GC/MS-Based Metabonomic Profiling in Studying the Therapeutic Effects of <i>Aconitum carmichaeli</i> with <i>Ampelopsis japonica</i> Extract on Collagen-Induced Arthritis in Rats

Aconitum carmichaeli with Ampelopsis japonica (AA) is a classical traditional Chinese medicine (TCM) formula. There are a lot of examples showing that AA can be used to treat rheumatoid arthritis, but its mechanism of action is still not completely clear. In this research, collagen-induced arthritis (CIA) was chosen as a rheumatoid arthritis (RA) model. Rats of treated groups were continuously administered Aconitum carmichaeli (AC), Ampelopsis japonica (AJ) and Aconitum carmichaeli + Ampelopsis japonica (AA) orally once a day from the day after the onset of arthritis (day 7) until day 42. The results showed that AA not only significantly reduced paw swelling, but also improved the levels of TNF-&#945; and IL-6 in serum. GC-MS-based urine metabonomics was established to analysis metabolic profiles and 21 biomarkers of RA rats were identified by the Partial Least Squares Discriminant Analysis (PLS-DA) and Support Vector Machine (SVM) methods. The prediction rate of the SVM method for the 21 biomarkers was 100%. Twenty of 21 biomarkers, including D-galactose, inositol and glycerol, gradually returned to normal levels after administration of AA. Metabolomic Pathway Analysis (MetPA) generated three related metabolic pathways&#8212;galactose metabolism, glycerolipid metabolism and inositol phosphate metabolism&#8212;which explain the mechanism of AA treatment of rheumatoid arthritis. This research provides a better understanding of the therapeutic effects and possible therapeutic mechanism of action of a complex TCM (AA) on rheumatoid arthritis

Analysis and Optimization Test of the Peanut Seeding Process with an Air-Suction Roller Dibbler

The air-suction roller dibbler for peanuts is the core component to realizing precision seeding on film; however, the seeds in the dibbler cannot accurately fall into the seed-guiding mechanism during the work. In this study, we stabilized the seed trajectory by adjusting the installation angles of the chock block (IACB) and installation angles of the dibbler cover (IADC). We studied the seed-movement characteristics under different IACB and dibbler covers using EDEM simulation software. The separation between the seed and the baffle was obtained for different installation conditions, which were contact separation and noncontact separation. We obtained the best seeding performance when the seed was released from the edge of the dibbler cover in contact with the baffle of the seed separation tray. In the bench test, we obtained the best seed-feeding performance at 48.28&deg; for the IACB, 12.29&deg; for the IADC, and 3.84 km/h for the machine. The seeding pass rate was 95.35%, the missed seeding rate was 2.52%, and the reseeding rate was 2.11%. The field verification test showed that the machine worked well with the combination, and the seeding pass rate was above 92%, which meets the requirements of the single-grain precision sowing of peanuts and substantially improves the operation performance

Research on a Dynamic Algorithm for Cow Weighing Based on an SVM and Empirical Wavelet Transform

Weight is an important indicator of the growth and development of dairy cows. The traditional static weighing methods require considerable human and financial resources, and the existing dynamic weighing algorithms do not consider the influence of the cow motion state on the weight curve. In this paper, a dynamic weighing algorithm for cows based on a support vector machine (SVM) and empirical wavelet transform (EWT) is proposed for classification and analysis. First, the dynamic weight curve is obtained by using a weighing device placed along a cow travel corridor. Next, the data are preprocessed through valid signal acquisition, feature extraction, and normalization, and the results are divided into three active degrees during motion for low, medium, and high grade using the SVM algorithm. Finally, a mean filtering algorithm, the EWT algorithm, and a combined periodic continuation-EWT algorithm are used to obtain the dynamic weight values. Weight data were collected for 910 cows, and the experimental results displayed a classification accuracy of 98.6928%. The three algorithms were used to calculate the dynamic weight values for comparison with real values, and the average error rates were 0.1838%, 0.6724%, and 0.9462%. This method can be widely used at farms and expand the current knowledgebase regarding the dynamic weighing of cows