Nourishing Yin and Promoting Blood Circulation of TCM to Treat Hemorheologic Disorder Induced by Diabetes Mellitus in Rats

Diabetes mellitus, DM, is commonly accompanied with various stages of hemorheologic disturbances that are the main causes of the development of chronic DM. In this study, simple Chinese material medica [yang-yin jiang-tang preparation (YYJT)] was given to alloxan-induced DM rats and analyzed to compare the changes of fasting blood glucose (FBG), fasting insulin (FINS), hemorheologic parameters and insulin-like growth factor II (IGF-II) before and after administration. The results suggested that YYJT can significantly downregulate FBG (P < 0.005), improve insulin resistance and beta-cell secretion (P < 0.05), decrease whole blood viscosity at low and high shear rates, gathering of blood index test (GIT) and fibrinogen (FIB) (P < 0.05), and enlarge the function of IGF-II (P < 0.05). We concluded that YYJT could prevent and treat hemorheologic disorder in DM rats by means of reducing glucose, improving insulin resistance and elevating IGF-II

Effects of polymer additives in the bulk of turbulent thermal convection

We present experimental evidence that a minute amount of polymer additives can significantly enhance heat transport in the bulk region of turbulent thermal convection. The effects of polymer additives are found to be the \textit{suppression} of turbulent background fluctuations that give rise to incoherent heat fluxes that make no net contribution to heat transport, and at the same time to \textit{increase} the coherency of temperature and velocity fields. The suppression of small-scale turbulent fluctuations leads to more coherent thermal plumes that result in the heat transport enhancement. The fact that polymer additives can increase the coherency of thermal plumes is supported by the measurements of a number of local quantities, such as the extracted plume amplitude and width, the velocity autocorrelation functions and the velocity-temperature cross-correlation coefficient. The results from local measurements also suggest the existence of a threshold value for the polymer concentration, only above which can significant modification of the plume coherent properties and enhancement of the local heat flux be observed. Estimation of the plume emission rate suggests that the second effect of polymer additives is to stabilize the thermal boundary layers.Comment: 8 figures, 11 page

Psychological characteristics and nursing intervention of adolescent patients with oral cavity

目的  通过对就诊病例的心理特点分析，总结适时的心理护理干预方法。方法  通过对121例青少年患者的心理定势、期待与满意等方面进行总结。结果与结论  充分了解正畸青少年患者的就诊心态，加强对患者心理护理的干预，以达到最佳治疗效果。Objective: Through the analysis of the psychological characteristics of patients with medical treatment, summarize the timely psychological nursing intervention. Methods: Summarize the mental set, expectation and satisfaction of 121 adolescent patients. Results and Conclusion: To fully understand the orthodontic patients of adolescent mentality，strengthen the psychological nursing of patients of intervention，in order to achieve the best therapeutic effect.

GitFL: Adaptive Asynchronous Federated Learning using Version Control

As a promising distributed machine learning paradigm that enables collaborative training without compromising data privacy, Federated Learning (FL) has been increasingly used in AIoT (Artificial Intelligence of Things) design. However, due to the lack of efficient management of straggling devices, existing FL methods greatly suffer from the problems of low inference accuracy and long training time. Things become even worse when taking various uncertain factors (e.g., network delays, performance variances caused by process variation) existing in AIoT scenarios into account. To address this issue, this paper proposes a novel asynchronous FL framework named GitFL, whose implementation is inspired by the famous version control system Git. Unlike traditional FL, the cloud server of GitFL maintains a master model (i.e., the global model) together with a set of branch models indicating the trained local models committed by selected devices, where the master model is updated based on both all the pushed branch models and their version information, and only the branch models after the pull operation are dispatched to devices. By using our proposed Reinforcement Learning (RL)-based device selection mechanism, a pulled branch model with an older version will be more likely to be dispatched to a faster and less frequently selected device for the next round of local training. In this way, GitFL enables both effective control of model staleness and adaptive load balance of versioned models among straggling devices, thus avoiding the performance deterioration. Comprehensive experimental results on well-known models and datasets show that, compared with state-of-the-art asynchronous FL methods, GitFL can achieve up to 2.64X training acceleration and 7.88% inference accuracy improvements in various uncertain scenarios

Diaqua­{6,6′-dimeth­oxy-2,2′-[ethane-1,2-diylbis(nitrilo­methyl­idyne)]diphenolato-κ2 O,N,N′,O′}manganese(III) perchlorate 18-crown-6 hemisolvate monohydrate

In the cation of the title compound, [Mn(C18H18N2O4)(H2O)2]ClO4·0.5C12H24O6·H2O, the MnIII ion is coordinated by two water O atoms, and two O atoms and two N atoms from the tetradentate 6,6′-dimeth­oxy-2,2′-[ethane-1,2-diylbis(nitrilo­methyl­idyne)]di­phenolate ligand, completing a distorted octa­hedral geometry. One O atom of the 18-crown-6-ether is disordered over two positions with occupancies of 0.70 (2) and 0.30 (2)

Did the nHZ Gravitational Waves Signatures Observed By NANOGrav Indicate Multiple Sector SUSY Breaking?

Discrete R symmetries always play an important role in low energy SUSY. The spontaneously broken of such discrete R symmetries, for example, by gaugino condensation, can lead to domain walls, which need to be either inflated away or collapse to avoid cosmic difficulties. We propose that explicitly R symmetry violation needed for collapse of domain walls can be the consequence of multiple sector SUSY breaking. The consistency constraints for the generation of non-problematic domain walls from gaugino condensation are discussed. We also study the emitted gravitational waves related to the collapse of domain walls. We find that, for SUSY breaking scale of order ${\cal O}(1)$ ${\rm GeV}$ in one of the sequestered sector (and also a low reheating temperature of order ${\rm MeV}$ if the reheating is not completed when the domain walls collapse), the peak frequency of gravitational waves emitted can lie at nHz. Such a low SUSY breaking scale can be consistency and natural in multiple sector SUSY breaking scenario. The GWs signal by NANOGrav could be a signal of such multiple sector SUSY breaking scenario and it may also indicate the existences of light goldstini at ${\rm eV}$ mass scale.Comment: 13 page

Axial Force Analysis and Roll Contour Configuration of Four-High CVC Mill

In order to analyze the influence of technical parameters on work roll axial force of four-high continuous variable crown (CVC) mill, the deformation analyzing model with top roll system and strip was established based on influence function method. Then a CVC work roll curve designing scheme was proposed and it was carried out on some cold rolling mill considering the requirement of comprehensive work roll axial force minimization. The status of comprehensive work roll axial force is improved considering the rolling schedule that is beneficial to the roller bearing. Corresponding to the newly designed work roll contour, the backup roll end chamfer was designed considering comprehensive performance of interroll stress concentration, comprehensive work roll axial force, and strip shape control ability. The distribution of roll wear with newly designed backup roll contour is more even according to the field application data. The newly established roll configuration scheme is beneficial to four-high CVC mill

APIS: accurate prediction of hot spots in protein interfaces by combining protrusion index with solvent accessibility

<p>Abstract</p> <p>Background</p> <p>It is well known that most of the binding free energy of protein interaction is contributed by a few key hot spot residues. These residues are crucial for understanding the function of proteins and studying their interactions. Experimental hot spots detection methods such as alanine scanning mutagenesis are not applicable on a large scale since they are time consuming and expensive. Therefore, reliable and efficient computational methods for identifying hot spots are greatly desired and urgently required.</p> <p>Results</p> <p>In this work, we introduce an efficient approach that uses support vector machine (SVM) to predict hot spot residues in protein interfaces. We systematically investigate a wide variety of 62 features from a combination of protein sequence and structure information. Then, to remove redundant and irrelevant features and improve the prediction performance, feature selection is employed using the F-score method. Based on the selected features, nine individual-feature based predictors are developed to identify hot spots using SVMs. Furthermore, a new ensemble classifier, namely APIS (A combined model based on Protrusion Index and Solvent accessibility), is developed to further improve the prediction accuracy. The results on two benchmark datasets, ASEdb and BID, show that this proposed method yields significantly better prediction accuracy than those previously published in the literature. In addition, we also demonstrate the predictive power of our proposed method by modelling two protein complexes: the calmodulin/myosin light chain kinase complex and the heat shock locus gene products U and V complex, which indicate that our method can identify more hot spots in these two complexes compared with other state-of-the-art methods.</p> <p>Conclusion</p> <p>We have developed an accurate prediction model for hot spot residues, given the structure of a protein complex. A major contribution of this study is to propose several new features based on the protrusion index of amino acid residues, which has been shown to significantly improve the prediction performance of hot spots. Moreover, we identify a compact and useful feature subset that has an important implication for identifying hot spot residues. Our results indicate that these features are more effective than the conventional evolutionary conservation, pairwise residue potentials and other traditional features considered previously, and that the combination of our and traditional features may support the creation of a discriminative feature set for efficient prediction of hot spot residues. The data and source code are available on web site <url>http://home.ustc.edu.cn/~jfxia/hotspot.html</url>.</p

TDP-43 Potentiates Alpha-synuclein Toxicity to Dopaminergic Neurons in Transgenic Mice

TDP-43 and α-synuclein are two disease proteins involved in a wide range of neurodegenerative diseases. While TDP-43 proteinopathy is considered a pathologic hallmark of sporadic amyotrophic lateral sclerosis and frontotemporal lobe degeneration, α-synuclein is a major component of Lewy body characteristic of Parkinson's disease. Intriguingly, TDP-43 proteinopathy also coexists with Lewy body and with synucleinopathy in certain disease conditions. Here we reported the effects of TDP-43 on α-synuclein neurotoxicity in transgenic mice. Overexpression of mutant TDP-43 (M337V substitution) in mice caused early death in transgenic founders, but overexpression of normal TDP-43 only induced a moderate loss of cortical neurons in the transgenic mice at advanced ages. Interestingly, concomitant overexpression of normal TDP-43 and mutant α-synuclein caused a more severe loss of dopaminergic neurons in the double transgenic mice as compared to single-gene transgenic mice. TDP-43 potentiated α-synuclein toxicity to dopaminergic neurons in living animals. Our finding provides in vivo evidence suggesting that disease proteins such as TDP-43 and α-synuclein may play a synergistic role in disease induction in neurodegenerative diseases

The mechanism of high contents of oil and oleic acid revealed by transcriptomic and lipidomic analysis during embryogenesis in Carya cathayensis Sarg.

Gene transcription in lipid synthesis. (XLSX 55 kb