On the Lp Gaussian Minkowski problem

Existence of symmetric (resp. asymmetric) solutions to the $L_p$ Gaussian Minkowski problem for $p\leq 0$ (resp. $p\geq 1$) will be provided. Moreover, existence and uniqueness of smooth solutions to the problem for $p>n$ will also be proved without the restriction that the Gaussian volumes of convex bodies are not less than one-second.Comment: arXiv admin note: text overlap with arXiv:2207.0693

DACH1 suppresses breast cancer as a negative regulator of CD44.

Dachshund homolog 1 (DACH1), a key cell fate determination factor, contributes to tumorigenesis, invasion, metastasis of human breast neoplasm. However, the exact molecular mechanisms for the anti-tumor roles of DACH1 in breast carcinoma are still lack of extensive understanding. Herein, we utilized immunohistochemistry (IHC) staining and public microarray data analysis showing that DACH1 was higher in normal breast, low-grade and luminal-type cancer in comparison with breast carcinoma, high-grade and basal-like tumors respectively. Additionally, both correlation analysis of public databases of human breast carcinoma and IHC analysis of mice xenograft tumors demonstrated that DACH1 inversely related to cancer stem cells (CSCs) markers, epithelial-mesenchymal transition (EMT) inducers and basal-enriched molecules, while cluster of differentiation 44 (CD44) behaved in an opposite manner. Furthermore, mice transplanted tumor model indicated that breast cancer cells Met-1 with up-regulation of DACH1 were endowed with remarkably reduced potential of tumorigenesis. Importantly, meta-analysis of 19 Gene Expression Omnibus (GEO) databases of breast cancer implicated that patients with higher DACH1 expression had prolonged time to death, recurrence and metastasis, while CD44 was a promising biomarker predicting worse overall survival (OS) and metastasis-free survival (MFS). Collectively, our study indicated that CD44 might be a novel target of DACH1 in breast carcinoma

Proximal Stochastic Recursive Momentum Methods for Nonconvex Composite Decentralized Optimization

Consider a network of $N$ decentralized computing agents collaboratively solving a nonconvex stochastic composite problem. In this work, we propose a single-loop algorithm, called DEEPSTORM, that achieves optimal sample complexity for this setting. Unlike double-loop algorithms that require a large batch size to compute the (stochastic) gradient once in a while, DEEPSTORM uses a small batch size, creating advantages in occasions such as streaming data and online learning. This is the first method achieving optimal sample complexity for decentralized nonconvex stochastic composite problems, requiring $\mathcal{O}(1)$ batch size. We conduct convergence analysis for DEEPSTORM with both constant and diminishing step sizes. Additionally, under proper initialization and a small enough desired solution error, we show that DEEPSTORM with a constant step size achieves a network-independent sample complexity, with an additional linear speed-up with respect to $N$ over centralized methods. All codes are made available at~\url{https://github.com/gmancino/DEEPSTORM}.Comment: AAAI 202

Increasing Coverage of Hepatitis B Vaccination in China: A Systematic Review of Interventions and Implementation Experiences.

This study used a system evaluation method to summarize China's experience on improving the coverage of hepatitis B vaccine, especially the strategies employed to improve the uptake of timely birth dosage. Identifying successful methods and strategies will provide strong evidence for policy makers and health workers in other countries with high hepatitis B prevalence.We conducted a literature review included English or Chinese literature carried out in mainland China, using PubMed, the Cochrane databases, Web of Knowledge, China National Knowledge Infrastructure, Wanfang data, and other relevant databases.Nineteen articles about the effectiveness and impact of interventions on improving the coverage of hepatitis B vaccine were included. Strong or moderate evidence showed that reinforcing health education, training and supervision, providing subsidies for facility birth, strengthening the coordination among health care providers, and using out-of-cold-chain storage for vaccines were all important to improving vaccination coverage.We found evidence that community education was the most commonly used intervention, and out-reach programs such as out-of-cold chain strategy were more effective in increasing the coverage of vaccination in remote areas where the facility birth rate was respectively low. The essential impact factors were found to be strong government commitment and the cooperation of the different government departments.Public interventions relying on basic health care systems combined with outreach care services were critical elements in improving the hepatitis B vaccination rate in China. This success could not have occurred without exceptional national commitment

Convolutional Neural Networks and Feature Fusion for Flow Pattern Identification of the Subsea Jumper

The gas–liquid two-phase flow patterns of subsea jumpers are identified in this work using a multi-sensor information fusion technique, simultaneously collecting vibration signals and electrical capacitance tomography of stratified flow, slug flow, annular flow, and bubbly flow. The samples are then processed to obtain the data set. Additionally, the samples are trained and learned using the convolutional neural network (CNN) and feature fusion model, which are built based on experimental data. Finally, the four kinds of flow pattern samples are identified. The overall identification accuracy of the model is 95.3% for four patterns of gas–liquid two-phase flow in the jumper. Through the research of flow profile identification, the disadvantages of single sensor testing angle and incomplete information are dramatically improved, which has a great significance on the subsea jumper’s operation safety.publishedVersio

P-Glycoprotein/MDR1 Regulates Pokemon Gene Transcription Through p53 Expression in Human Breast Cancer Cells

P-glycoprotein (Pgp), encoded by the multidrug resistance 1 (MDR1) gene, is an efflux transporter and plays an important role in pharmacokinetics. In this study, we demonstrated that the pokemon promoter activity, the pokemon mRNA and protein expression can be significantly inhibited by Pgp. Chromatin immunoprecipitation assay showed that Pgp can bind the pokemon prompter to repress pokemon transcription activity. Furthermore, Pgp regulated pokemon transcription activity through expression of p53 as seen by use of p53 siRNA transfected MCF-7 cells or p53 mutated MDA-MB-231 cells. Moreover, p53 was detected to bind with Pgp in vivo using immunoprecipitation assay. Taken together, we conclude that Pgp can regulate the expression of pokemon through the presence of p53, suggesting that Pgp is a potent regulator and may offer an effective novel target for cancer therapy

First-principles methodology for studying magnetotransport in narrow-gap semiconductors: an application to Zirconium Pentatelluride ZrTe5

The origin of anomalous resistivity peak and accompanied sign reversal of Hall resistivity of ZrTe$_5$ has been under debate for a long time. Although various theoretical models have been proposed to account for these intriguing transport properties, a systematic study from first principles view is still lacking. In this work, we present a first principles calculation combined with Boltzmann transport theory to investigate the transport properties in narrow-gap semiconductors at different temperatures and doping densities within the relaxation time approximation. Regarding the sensitive temperature-dependent chemical potential and relaxation time of semiconductors, we take proper approximation to simulate these two variables, and then comprehensively study the transport properties of ZrTe$_5$ both in the absence and presence of an applied magnetic field. Without introducing topological phases and correlation interactions, we qualitatively reproduced crucial features observed in experiments, including zero-field resistivity anomaly, nonlinear Hall resistivity with sign reversal, and non-saturating magnetoresistance at high temperatures. Our calculation allows a systematic interpretation of the observed properties in terms of multi-carrier and Fermi surface geometry. Our method can be extended to other narrow-gap semiconductors and further pave the way to explore interesting and novel transport properties of this field.Comment: 12 pages, 7 figure

Effects of different cooling methods on the carbon footprint of cooked rice

peer-reviewedGlobal warming has become a serious problem facing the international community. All countries strive to reduce greenhouse gas (GHG) emissions. The food system produces a large amount of GHGs, and thus study of the carbon footprint (CF) in the food industry has attracted the attention of researchers. Based on the lifecycle assessment (LCA) method, the present study calculated CFs of cooling of cooked rice, as a unit operation under different operational conditions. The results showed that the carbon footprints for cooling 200 g cooked rice were 54.36 ± 1.07 gCO2eq for refrigerator cooling at 0 °C, 66.05 ± 2.00 g CO2eq for refrigerator cooling at 8 °C, 741.55 ± 27.26 g CO2eq for vacuum cooling, 1914.10 ± 141.24 g CO2eq for air blast cooling at 0 °C, 2463.61 ± 221.21 g CO2eq for air blast cooling at 3 °C, and 3916.54 ± 202.28 g CO2eq for air blast cooling at 8 °C. In addition, the CF for the cooling process was positively correlated with the output power of equipment and the cooling time. The carbon emissions arising from electricity consumption contributed to most of the CF for the cooling process. Sensitivity analysis of the parameters for the CF for the cooling process revealed that the CF of cooling process was stable for the applied equipment emission factor, but sensitive to the efficiency of electricity use and the extent of load. Improving the efficiency of electricity use and increasing cooling load could reduce the final CF of a product

Prevalence and Correlates of Discomfort and Acceptability of Acupuncture among Outpatients in Chinese Acupuncture and Moxibustion Departments: A Cross-Sectional Study

Objective. This study aims to give a profile of discomfort and acceptability of acupuncture, including the prevalence and association with demographic and acupuncture-related factors. Methods. A cross-sectional study was conducted in Beijing, China. Outpatients of acupuncture and moxibustion departments were recruited using purposive sampling. 925 subjects were interviewed with an anonymous questionnaire. Multinomial and binary logistic regression were used to analyze factors affecting discomfort and acceptability of acupuncture. Results. The average VAS value of 925 subjects’ acupuncture discomfort was 2.66 ± 2.02, within the range of mild discomfort. Acupuncture was easily accepted by 81.1% of the subjects. Results of logistic regression were as follows: (1) subjects with a better knowledge of acupuncture, or a greater fear of pain or needles, experienced more “moderate to severe discomfort” and showed a decreased acupuncture acceptance (P<0.001 or P<0.01); (2) Acupuncture with less discomfort or implemented by a more qualified doctor was easy to be accepted (P<0.001); (3) subjects aged 20–29 preferred to report “moderate to severe discomfort” while those aged 40–59 preferred to report “slight discomfort” (P<0.001). Conclusion. Acupuncture is an acceptable therapy with less discomfort, which can be greatly affected by fear of pain or needles, age, knowledge of acupuncture, and professional title of acupuncturist