Preparation of Blood-Deficient Model and Research of Angelica Polysaccharide on Enriching Blood in Chickens

In this study cyclophosphamide was used to prepare the blood-deficient model. The red blood cell count and hemoglobin content were measured. The experimental chickens presented the symptoms of blood-deficient syndrome, dullness, shrinkinginto oneself, broken winded, loose feather, waxy eyelid, and pale tongue. At the same time, red blood cell count and hemoglobin content decreased significantly. Angelica polysaccharide as the effective component of Angelica Sinensis could significantly increase the red blood cell count and the hemoglobin content of blood-deficient chickens. The results indicated that cyclophosphamide could significantly reduce the red blood count and hemoglobin content, and make the ideal blood-deficient model successfully. Angelica polysaccharide had the function of enriching blood in different ways. On the one hand Angelica polysaccharide enriched he blood directly, increased the number of RBC and hemoglobin; on the other hand it regulated the hematopoietic factors, enriched the blood indirectly

Dynamic RACH Partition for Massive Access of Differentiated M2M Services

In machine-to-machine (M2M) networks, a key challenge is to overcome the overload problem caused by random access requests from massive machine-type communication (MTC) devices. When differentiated services coexist, such as delay-sensitive and delay-tolerant services, the problem becomes more complicated and challenging. This is because delay-sensitive services often use more aggressive policies, and thus, delay-tolerant services get much fewer chances to access the network. To conquer the problem, we propose an efficient mechanism for massive access control over differentiated M2M services, including delay-sensitive and delay-tolerant services. Specifically, based on the traffic loads of the two types of services, the proposed scheme dynamically partitions and allocates the random access channel (RACH) resource to each type of services. The RACH partition strategy is thoroughly optimized to increase the access performances of M2M networks. Analyses and simulation demonstrate the effectiveness of our design. The proposed scheme can outperform the baseline access class barring (ACB) scheme, which ignores service types in access control, in terms of access success probability and the average access delay

IL28B is associated with outcomes of chronic HBV infection

Purpose The role of IL28B gene variants and expression in hepatitis B virus (HBV) infections are not well understood. Here, we evaluated whether IL28B gene expression and rs12979860 variations are associated with HBV outcomes. Materials and Methods IL28B genetic variations (rs12979860) were genotyped by pyrosequencing of DNA samples from 137 individuals with chronic HBV infection [50 inactive carriers (IC), 34 chronic hepatitis B (CHB), 27 cirrhosis, 26 hepatocellular carcinoma (HCC)], and 19 healthy controls. IL28A/B mRNA expression in peripheral blood mononuclear cells was determined by qRT-PCR, and serum IL28B protein was measured by ELISA. Results Patients with IL28B C/C genotype had greater IL28A/B mRNA expression and higher IL28B protein levels than C/T patients. Within the various disease stages, compared to IC and healthy controls, IL28B expression was reduced in the CHB, cirrhosis, and HCC cohorts (CHB vs. IC, p=0.02; cirrhosis vs. IC, p=0.01; HCC vs. IC, p=0.001; CHB vs. controls, p&#60;0.01; cirrhosis vs. controls, p&#60;0.01; HCC vs. controls, p&#60;0.01). When stratified with respect to serum HBV markers in the IC and CHB cohorts, IL28B mRNA and protein levels were higher in HBeAg-positive than negative individuals (p=0.01). Logistic regression analysis revealed that factors associated with high IL28B protein levels were C/C versus C/T genotype [p=0.016, odds ratio (OR)=0.25, 95% confidence interval (CI)=0.08-0.78], high alanine aminotransferase values (p&#60;0.001, OR=8.02, 95% CI=2.64-24.4), and the IC stage of HBV infection (p&#60;0.001). Conclusion Our data suggest that IL28B genetic variations may play an important role in long-term development of disease in chronic HBV infections.</p

AutoMLP: Automated MLP for Sequential Recommendations

Sequential recommender systems aim to predict users' next interested item given their historical interactions. However, a long-standing issue is how to distinguish between users' long/short-term interests, which may be heterogeneous and contribute differently to the next recommendation. Existing approaches usually set pre-defined short-term interest length by exhaustive search or empirical experience, which is either highly inefficient or yields subpar results. The recent advanced transformer-based models can achieve state-of-the-art performances despite the aforementioned issue, but they have a quadratic computational complexity to the length of the input sequence. To this end, this paper proposes a novel sequential recommender system, AutoMLP, aiming for better modeling users' long/short-term interests from their historical interactions. In addition, we design an automated and adaptive search algorithm for preferable short-term interest length via end-to-end optimization. Through extensive experiments, we show that AutoMLP has competitive performance against state-of-the-art methods, while maintaining linear computational complexity.Comment: Accepted by WWW'2

FlowEval: A Consensus-Based Dialogue Evaluation Framework Using Segment Act Flows

Despite recent progress in open-domain dialogue evaluation, how to develop automatic metrics remains an open problem. We explore the potential of dialogue evaluation featuring dialog act information, which was hardly explicitly modeled in previous methods. However, defined at the utterance level in general, dialog act is of coarse granularity, as an utterance can contain multiple segments possessing different functions. Hence, we propose segment act, an extension of dialog act from utterance level to segment level, and crowdsource a large-scale dataset for it. To utilize segment act flows, sequences of segment acts, for evaluation, we develop the first consensus-based dialogue evaluation framework, FlowEval. This framework provides a reference-free approach for dialog evaluation by finding pseudo-references. Extensive experiments against strong baselines on three benchmark datasets demonstrate the effectiveness and other desirable characteristics of our FlowEval, pointing out a potential path for better dialogue evaluation.Comment: EMNLP 2022 camera-ready versio

Rethinking Sensors Modeling: Hierarchical Information Enhanced Traffic Forecasting

With the acceleration of urbanization, traffic forecasting has become an essential role in smart city construction. In the context of spatio-temporal prediction, the key lies in how to model the dependencies of sensors. However, existing works basically only consider the micro relationships between sensors, where the sensors are treated equally, and their macroscopic dependencies are neglected. In this paper, we argue to rethink the sensor's dependency modeling from two hierarchies: regional and global perspectives. Particularly, we merge original sensors with high intra-region correlation as a region node to preserve the inter-region dependency. Then, we generate representative and common spatio-temporal patterns as global nodes to reflect a global dependency between sensors and provide auxiliary information for spatio-temporal dependency learning. In pursuit of the generality and reality of node representations, we incorporate a Meta GCN to calibrate the regional and global nodes in the physical data space. Furthermore, we devise the cross-hierarchy graph convolution to propagate information from different hierarchies. In a nutshell, we propose a Hierarchical Information Enhanced Spatio-Temporal prediction method, HIEST, to create and utilize the regional dependency and common spatio-temporal patterns. Extensive experiments have verified the leading performance of our HIEST against state-of-the-art baselines. We publicize the code to ease reproducibility.Comment: 9 pages, accepted by CIKM'2

An efficient low-density grating setup for monochromatization of XUV ultrafast light sources

Ultrafast light sources have become an indispensable tool to access and understand transient phenomenon in material science. However, a simple and easy-to-implement method for harmonic selection, with high transmission efficiency and pulse duration conservation, is still a challenge. Here we showcase and compare two approaches for selecting the desired harmonic from a high harmonic generation source while achieving the above goals. The first approach is the combination of extreme ultraviolet spherical mirrors with transmission filters and the second approach uses a normal-incidence spherical grating. Both solutions target time- and angle-resolved photoemission spectroscopy with photon energies in the 10-20 eV range but are relevant for other experimental techniques as well. The two approaches for harmonic selection are characterized in terms of focusing quality, efficiency, and temporal broadening. It is demonstrated that a focusing grating is able to provide much higher transmission as compared to the mirror+filter approach (3.3 times higher for 10.8 eV and 12.9 times higher for 18.1 eV), with only a slight temporal broadening (6.8% increase) and a somewhat larger spot size (∼30% increase). Overall, our study establishes an experimental perspective on the trade-off between a single grating normal incidence monochromator design and the use of filters. As such, it provides a basis for selecting the most appropriate approach in various fields where an easy-to-implement harmonic selection from high harmonic generation is needed

Personality Counts More Than Appearance for Men Making Affective Judgments of Verbal Comments

Previous research has shown that that evaluative verbal information (praise and criticism) conveys different affective values: criticism is perceived as unpleasant while praise is generally considered pleasant. Here, using praise and criticism in Chinese, we investigated how affective value is modulated in men and women, depending on the particular attribute (personality vs. appearance) targeted by social comments. Results showed that whereas praise was rated as pleasant and criticism as unpleasant overall, criticizing personality reduced pleasantness more than criticizing appearance. In men, moreover, criticism of personality was deemed more unpleasant than criticism of appearance while personality-targeted praise was rated more pleasant than appearance-targeted praise. This effect was absent in women and consistent with men’s higher arousal ratings for personality- relative to appearance-targeted comments. Our findings suggest that men are more concerned about external perception of their personality than that of their appearance whereas women’s affective judgment is more balanced. These gender-specific results may have implications for topic selection in evaluative social communication