Rocket Launching: A Universal and Efficient Framework for Training Well-performing Light Net

Models applied on real time response task, like click-through rate (CTR) prediction model, require high accuracy and rigorous response time. Therefore, top-performing deep models of high depth and complexity are not well suited for these applications with the limitations on the inference time. In order to further improve the neural networks' performance given the time and computational limitations, we propose an approach that exploits a cumbersome net to help train the lightweight net for prediction. We dub the whole process rocket launching, where the cumbersome booster net is used to guide the learning of the target light net throughout the whole training process. We analyze different loss functions aiming at pushing the light net to behave similarly to the booster net, and adopt the loss with best performance in our experiments. We use one technique called gradient block to improve the performance of the light net and booster net further. Experiments on benchmark datasets and real-life industrial advertisement data present that our light model can get performance only previously achievable with more complex models.Comment: 10 pages, AAAI201

Deep Interest Evolution Network for Click-Through Rate Prediction

Click-through rate~(CTR) prediction, whose goal is to estimate the probability of the user clicks, has become one of the core tasks in advertising systems. For CTR prediction model, it is necessary to capture the latent user interest behind the user behavior data. Besides, considering the changing of the external environment and the internal cognition, user interest evolves over time dynamically. There are several CTR prediction methods for interest modeling, while most of them regard the representation of behavior as the interest directly, and lack specially modeling for latent interest behind the concrete behavior. Moreover, few work consider the changing trend of interest. In this paper, we propose a novel model, named Deep Interest Evolution Network~(DIEN), for CTR prediction. Specifically, we design interest extractor layer to capture temporal interests from history behavior sequence. At this layer, we introduce an auxiliary loss to supervise interest extracting at each step. As user interests are diverse, especially in the e-commerce system, we propose interest evolving layer to capture interest evolving process that is relative to the target item. At interest evolving layer, attention mechanism is embedded into the sequential structure novelly, and the effects of relative interests are strengthened during interest evolution. In the experiments on both public and industrial datasets, DIEN significantly outperforms the state-of-the-art solutions. Notably, DIEN has been deployed in the display advertisement system of Taobao, and obtained 20.7\% improvement on CTR.Comment: 9 pages. Accepted by AAAI 201

Identification of a novel regulatory mechanism involved in inhibition of transcription of suvivin mRNA in breast cancer cells via p21cip–mediated regulation

Purpose: To evaluate the effect of p21Cip1 on survivin transcription levels in breast carcinoma, and to investigate the potential mechanisms.Methods: Epirubicin, a p21Cip1 activator, was used to treat MCF7 cells. Under the action of normal biological functions of p53, pEGFP-C2-p21 was transfected into MCF7 cells by lipofectamine and positive clones were screened out with G418. The expression levels of p21cip1, p53 and survivin mRNA were quantitated by real-time fluorescent polymerase chain reaction (RQ-PCR). MTT assay was utilized to measure cellular viability and proliferation after transfection. Flow cytometry was employed to determine the cell cycle. Hoechst 33342 staining was carried out to assess cell apoptosis. Lastly, several transcription factor sites located at the promoter region of survivin gene, such as, sp1 site, E2F site and p300/CBP, were measured by p21 overexpression using RT-PCR.Results: Following epirubicin treatment, within 24 h, the expression levels of endogenous p21cip1 and p53 were up-regulated, whereas that of survivin was down-regulated. After transfection treatment, p21 inhibited the proliferation of MCF7 cells on days 3 and 4, and MCF7 cells overexpressed p21 mRNA, whereas the level of survivin mRNA in MCF7-p21 groups was markedly down-regulated relative to control group, but overexpression of p21 was not sufficient to cause changes in p53 gene expression. The overexpressed p21 resulted in G1/G0 phase arrest based on cell cycle analysis, but apoptosis was not induced. In addition, co-transcription factors E2F-1, sp1 and p300/CBP mRNA levels decreased significantly compared with normal p21 expression groups.Conclusion: P21cip1 may down-regulate the expression of survivin gene partially by inhibiting the expression level of HAT.Keywords: Cyclin-dependent kinase inhibitor 1, Phosphoprotein p53, Survivin, Breast carcinoma, G1/G0 phase arrest, Epirubicin, Lipofectamin

Międzynarodowy Ranking Uniwersytetów (Academic Ranking of World Universities)- metodologia i problemy

The Institute of Higher Education at Shanghai Jiao Tong University has published the Academic Ranking of World Universities on the Internet. The ranking has drawn wide attention worldwide. Within the ranking institutions are ranked according to their academic or research performance. Ranking indicators include the alumni and staff winning major International awards, highly cited researchers in major research fields, articles published in selected top journals and articles indexed by major citation indexes, as well as performance per capita. Methodological problems discussed in the article include quantitative versus qualitative evaluation, evaluation of research versus education, variety of institutions, language of publications, selection of awards and studying and working experience of award winners. The article also discusses technical problems such as definition of institutions, name expression of institutions, merging and splitting of institutions, searching and attribution of publications.Instytut Szkolnictwa Wyższego (Institute of Higher Education), działający w ramach Shanghai Jiao Tong University, opublikował w Internecie międzynarodowy ranking uniwersytetów (Academic Ranking of World Universities), który odbił się szerokim echem na całym świecie. W rankingu tym szkoły wyższe szereguje się według wyników działalności dydaktycznej i badawczej. Wśród wskaźników stosowanych w rankingu znajdują się m.in. liczba absolwentów oraz pracowników zdobywających prestiżowe nagrody międzynarodowe, często cytowanych badaczy w ważniejszych dziedzinach badań, liczba artykułów publikowanych w wybranych, przodujących czasopismach oraz artykułów uwzględnianych w najważniejszych indeksach cytowań, a także efektywność działania ujęta w przeliczeniu na jedną osobę {performance per capita). Problemy metodologiczne omawiane w niniejszym artykule to m.in. ocena ilościowa i jakościowa, ocena działalności badawczej uczelni oraz oferowanego przez nie kształcenia, różnorodność instytucji szkolnictwa wyższego, język publikacji, kryteria wyboru nagród oraz doświadczenia edukacyjne i zawodowe osób uhonorowanych nagrodami. W artykule omówiono także zagadnienia natury technicznej, takie jak definicja szkoły wyższej, sposób formułowania nazw poszczególnych szkół, kwestia ich fuzji i podziałów, poszukiwanie oraz przypisywanie publikacji do autorów (instytucji)

Clincal Observation of Grouping Responsibility Model of Immersion foot nursing In Maternity Ward

目的：责任制护理是一种以病人为中心，在护理过程中运用医学、护理、心理、生理、社会等学科的知识，观察分析病人的全面健康情况，进行有计划和系统的护理，从而提高护理质量和护理人员的素质。引入浸足1号进行整体护理，观察其临床效果。方法：在产科实施分组责任制护理，可以使护士为病人提供连续、全程、无缝隙的护理服务。引入浸足1号护理分为试验组和对照组，使试验组患者增加了家的感觉，并促进了产妇体质的尽快恢复。结果：在实施过程中，我们改变了原来的排班模式，使病人在住院期间有固定的责任护士，增强了护士的责任心，调动了护士的积极性，加强了护患沟通，减少了护理差错和纠纷，提高了护理质量，同时把护士的被动服务变为了主动服务，大大提高了护理质量，促进了产妇康复进程，试验组与对照组比较，护理质量明显提高，统计学比较有显著差异，P<0.05。结论：引入浸足1号护理提高了病人、医生的满意度，提高了护士的自身价值。Objective: Nursing responsibility system is patient centered system, using medicine, nursing, psychology, social and other disciplines of knowledge in the process of nursing, observing and comprehensively analyzing the health condition of patient, proceeding with a systematic nursing plan, so as to improve the quality of nursing and nursing staff quality. Introduction of immersion foot 1 of holistic nursing care, to observe its clinical effect. Methods:The implementation of the system of grouping responsibility nursing in obstetrics, can enable nurses to provide continuous, full, and non-breaking nursing service for patients . Introduction of immersion foot 1 nurses were divided into experimental group and control group, the experimental group increases the feeling of home, which promote maternal physical recovery. Results:In the process of implementation, we changed the original scheduling model, so as to make the patient had the fixed nurses during hospitalization, to strengthen the responsibility of nurses, to arouse the enthusiasm of nurses, to strengthen communication between nurses and patients, to reduce nursing errors and disputes, to improve the quality of care. Meanwhile the nurses change passive service in order to active service, which greatly improved the quality of nursing and promoted maternal rehabilitation process. Compare the experimental group with control group, and significantly improved the quality of nursing, there was statistical significant difference between the groups P<0.05. Conclusion: Introduction of immersion foot 1 care improves patient, physician satisfaction, and the nurses' value

Analysis of gut microbiota and immune-related genes during sea cucumber (<em>Apostichopus japonicus</em>) response to dietary supplementation with <em>Codonopsis pilosula</em>

The gut microbiota composition of sea cucumber (Apostichopus japonicas) was investigated using high-throughput sequencing techniques. The mRNA expression of complement component 3 and lysozyme genes was evaluated using quantitative fluorescence PCR. Sea cucumbers were fed with a basal diet (control group) and an experimental diet supplemented with Codonopsis pilosula (experimental group) for 30 days. The results showed that the alpha diversity of the gut microbiota was changed in different indices, including Chao1, the abundance-based coverage estimator, the Shannon index, and Good's coverage. Dietary C. pilosula promoted the proliferation of the Flavobacteriaceae family of the Proteobacteria phylum and reduced the relative abundance of the Verrucomicrobiaceae family of the Verrucomicrobia phylum. We concluded that dietary C. pilosula supplementation could alter the network interactions among different microbial functional groups by changing the ecological network's microbial community composition and biological evolution. A positive effect on A. japonicus immune responses in the gut was seen via increasing the mRNA expression of the complement component 3 and lysozyme genes. It seems to happen via modulating the balance in gut microbiota

Parallel symbolic state-space exploration is difficult, but what is the alternative?

State-space exploration is an essential step in many modeling and analysis problems. Its goal is to find the states reachable from the initial state of a discrete-state model described. The state space can used to answer important questions, e.g., "Is there a dead state?" and "Can N become negative?", or as a starting point for sophisticated investigations expressed in temporal logic. Unfortunately, the state space is often so large that ordinary explicit data structures and sequential algorithms cannot cope, prompting the exploration of (1) parallel approaches using multiple processors, from simple workstation networks to shared-memory supercomputers, to satisfy large memory and runtime requirements and (2) symbolic approaches using decision diagrams to encode the large structured sets and relations manipulated during state-space generation. Both approaches have merits and limitations. Parallel explicit state-space generation is challenging, but almost linear speedup can be achieved; however, the analysis is ultimately limited by the memory and processors available. Symbolic methods are a heuristic that can efficiently encode many, but not all, functions over a structured and exponentially large domain; here the pitfalls are subtler: their performance varies widely depending on the class of decision diagram chosen, the state variable order, and obscure algorithmic parameters. As symbolic approaches are often much more efficient than explicit ones for many practical models, we argue for the need to parallelize symbolic state-space generation algorithms, so that we can realize the advantage of both approaches. This is a challenging endeavor, as the most efficient symbolic algorithm, Saturation, is inherently sequential. We conclude by discussing challenges, efforts, and promising directions toward this goal

SR-BI as a target of natural products and its significance in cancer

Scavenger receptor class B type I (SR-BI) protein is an integral membrane glycoprotein. SR-BI is emerging as a multifunctional protein, which regulates autophagy, efferocytosis, cell survival and inflammation. It is well known that SR-BI plays a critical role in lipoprotein metabolism by mediating cholesteryl esters selective uptake and the bi-directional flux of free cholesterol. Recently, SR-BI has also been identified as a potential marker for cancer diagnosis, prognosis, or even a treatment target. Natural products are a promising source for the discovery of new drug leads. Multiple natural products were identified to regulate SR-BI protein expression. There are still a number of challenges in modulating SR-BI expression in cancer and in using natural products for modulation of such protein expression. In this review, our purpose is to discuss the relationship between SR-BI protein and cancer, and the molecular mechanisms regulating SR-BI expression, as well as to provide an overview of natural products that regulate SR-BI expression