Target differentiation with simple infrared sensors using statistical pattern recognition techniques

This study compares the performances of various statistical pattern recognition techniques for the differentiation of commonly encountered features in indoor environments, possibly with different surface properties, using simple infrared (IR) sensors. The intensity measurements obtained from such sensors are highly dependent on the location, geometry, and surface properties of the reflecting feature in a way that cannot be represented by a simple analytical relationship, therefore complicating the differentiation process. We construct feature vectors based on the parameters of angular IR intensity scans from different targets to determine their geometry and/or surface type. Mixture of normals classifier with three components correctly differentiates three types of geometries with different surface properties, resulting in the best performance (100%) in geometry differentiation. Parametric differentiation correctly identifies six different surface types of the same planar geometry, resulting in the best surface differentiation rate (100%). However, this rate is not maintained with the inclusion of more surfaces. The results indicate that the geometrical properties of the targets are more distinctive than their surface properties, and surface recognition is the limiting factor in differentiation. The results demonstrate that simple IR sensors, when coupled with appropriate processing and recognition techniques, can be used to extract substantially more information than such devices are commonly employed for.     

Differentiation of Cancer Stem Cells by Using Synthetic Small Molecules: Toward New Therapeutic Strategies against Therapy Resistance

Despite the existing arsenal of anti-cancer drugs, 10 million people die each year worldwide due to cancers; this highlights the need to discover new therapies based on innovative modes of action against these pathologies. Current chemotherapies are based on the use of cytotoxic agents, targeted drugs, monoclonal antibodies or immunotherapies that are able to reduce or stop the proliferation of cancer cells. However, tumor eradication is often hampered by the presence of resistant cells called cancer stem-like cells or cancer stem cells (CSCs). Several strategies have been proposed to specifically target CSCs such as the use of CSC-specific antibodies, small molecules able to target CSC signaling pathways or drugs able to induce CSC differentiation rendering them sensitive to classical chemotherapy. These latter compounds are the focus of the present review, which aims to report recent advances in anticancer-differentiation strategies. This therapeutic approach was shown to be particularly promising for eradicating tumors in which CSCs are the main reason for therapeutic failure. This general view of the chemistry and mechanism of action of compounds inducing the differentiation of CSCs could be particularly useful for a broad range of researchers working in the field of anticancer therapies as the combination of compounds that induce differentiation with classical chemotherapy could represent a successful approach for future therapeutic applications.     

Chronically Elevated Exogenous Glucose Elicits Antipodal Effects on the Proteome Signature of Differentiating Human iPSC-Derived Pancreatic Progenitors

The past decade revealed that cell identity changes, such as dedifferentiation or transdifferentiation, accompany the insulin-producing β-cell decay in most diabetes conditions. Mapping and controlling the mechanisms governing these processes is, thus, extremely valuable for managing the disease progression. Extracellular glucose is known to influence cell identity by impacting the redox balance. Here, we use global proteomics and pathway analysis to map the response of differentiating human pancreatic progenitors to chronically increased in vitro glucose levels. We show that exogenous high glucose levels impact different protein subsets in a concentration-dependent manner. In contrast, regardless of concentration, glucose elicits an antipodal effect on the proteome landscape, inducing both beneficial and detrimental changes in regard to achieving the desired islet cell fingerprint. Furthermore, we identified that only a subgroup of these effects and pathways are regulated by changes in redox balance. Our study highlights a complex effect of exogenous glucose on differentiating pancreas progenitors characterized by a distinct proteome signature.     

Multi-tier service differentiation by coordinated learning-based resource provisioning and admission control

Multiple Internet applications are often hosted in one datacenter, sharing underlying virtualized server resources. It is important to provide differentiated treatment to co-hosted applications and to improve overall system performance by efficient use of shared resources. Challenges arise due to multi-tier service architecture, virtualized server infrastructure, and highly dynamic and bursty workloads. We propose a coordinated admission control and adaptive resource provisioning approach for multi-tier service differentiation and performance improvement in a shared virtualized platform. We develop new model-independent reinforcement learning based techniques for virtual machine (VM) auto-configuration and session based admission control. Adaptive VM auto-configuration provides proportional service differentiation between co-located applications and improves application response time simultaneously. Admission control improves session throughput of the applications and minimizes resource wastage due to aborted sessions. A shared reward actualizes coordination between the two learning modules. For system agility and scalability, we integrate the reinforcement learning approach with cascade neural networks. We have implemented the integrated approach in a virtualized blade server system hosting RUBiS benchmark applications. Experimental results demonstrate that the new approach meets differentiation targets accurately and achieves performance improvement of applications at the same time. It reacts to dynamic and bursty workloads in an agile and scalable manner.     

Thermal Explosions in the Early Evolution of the Earth

Exothermic regimes in the Earth's interior at an early stage of evolution are considered. Conditions are found that lead to selfaccelerating development of gravitational differentiation—separation of the heavier material forming the Earth's core from silicates in extended and heated local areas.     

多拓扑路由实现IP网络区分服务的优化算法*

在IP网络使用多拓扑技术对不同业务区分服务和路由优化的背景下,提出一种改进的链路权重优化启发式算法,在一定条件下以一定概率接受非可行解,从而引入松弛机制扩大候选解范围,避免搜索陷入局部最优。在仿真中将所提出的算法和已有算法进行了比较,结果证明该算法能够为每个高优先级需求的服务层协定（SLA）提供保证,有效降低全网总时延或提高网络吞吐量。     

Logistic模型的参数估计及人口预测

用数值微分和线性拟合化技术对Logistics模型进行了参数估计,由此检验了2005~2007年中国总人口数的误差情况,其中2007年用相关参考文献的等差参数估算方法所得结果的相对误差为5.58%,而本文参数估算所得结果的相对误差为0.114‰,预测取得了理想的效果.     

基于用户偏好的垂直搜索算法

提出并研究、实现了基于用户偏好的垂直搜索算法(PVSA)。以领域特征为基本出发点,PVSA借助领域主题偏好向量、领域元数据权重因子、检索名词差异化、行业词典库更新等4项策略,有效地挖掘、表征用户的领域个性化偏好,以此为基础构建基于用户偏好的垂直搜索算法。实验结果表明了PVSA算法的有效性和可行性。