Targeting S1PRs as a Therapeutic Strategy for Inflammatory Bone Loss Diseases—Beyond Regulating S1P Signaling

As G protein coupled receptors, sphingosine-1-phosphate receptors (S1PRs) have recently gained attention for their role in modulating inflammatory bone loss diseases. Notably, in murine studies inhibiting S1PR2 by its specific inhibitor, JTE013, alleviated osteoporosis induced by RANKL and attenuated periodontal alveolar bone loss induced by oral bacterial inflammation. Treatment with a multiple S1PRs modulator, FTY720, also suppressed ovariectomy-induced osteoporosis, collagen or adjuvant-induced arthritis, and apical periodontitis in mice. However, most previous studies and reviews have focused mainly on how S1PRs manipulate S1P signaling pathways, subsequently affecting various diseases. In this review, we summarize the underlying mechanisms associated with JTE013 and FTY720 in modulating inflammatory cytokine release, cell chemotaxis, and osteoclastogenesis, subsequently influencing inflammatory bone loss diseases. Studies from our group and from other labs indicate that S1PRs not only control S1P signaling, they also regulate signaling pathways induced by other stimuli, including bacteria, lipopolysaccharide (LPS), bile acid, receptor activator of nuclear factor κB ligand (RANKL), IL-6, and vitamin D. JTE013 and FTY720 alleviate inflammatory bone loss by decreasing the production of inflammatory cytokines and chemokines, reducing chemotaxis of inflammatory cells from blood circulation to bone and soft tissues, and suppressing RANKL-induced osteoclast formation.     

Discharge coefficient for vertical sluice gate under submerged condition using contraction and energy loss coefficients

A novel method is suggested for the determination of flow discharge in vertical sluice gates with considerably small bias. First, in order to derive an equation for the discharge coefficient, energy-momentum equations are implemented to define the physical realization of the phenomenon. Afterward, the discharge coefficient is presented in terms of contraction and energy loss coefficients. Subsequently, discharge coefficient, contraction, and energy loss coefficients were determined through an implicit optimization technique on the data. Data analysis illustrated that there is a meaningful power relationship between the contraction and energy loss coefficients. Thereafter, dimensional analysis is performed and an explicit best-fit regression equation is developed for defining the energy loss coefficient. The obtained equations for contraction and energy loss coefficients were then used in the computation of the discharge coefficient and determination of the flow discharge in the vertical sluice gate. The performance of the developed approach is validated against the selected benchmarks existing in the literature.     

Interval analysis of mode shapes to identify damage in beam structures

Various damage detection methods have been proposed by several researchers in the past few decades. Amongst them, the efficiency of mode shapes in detecting damage has been demonstrated by many researchers when further processed. In most cases, the processing involves expansion or reduction of the mode shape data. However, vital information that are damage-prints are often lost during processing of the mode shape data. In addition, most of these processes involve long and complex computation, thus, leading to inaccurate damage identification. In this study, a simple and fast damage identification technique is proposed to identify damage in beam structures. Interval analysis is applied to the mode shapes of a beam structure in the damaged and undamaged states. The interval situations of each of the beam's segment via mode shape are derived to obtain the upper and lower bounds and the derived bounds are compared. To establish a relationship for identify the damaged point, a possibility of damage existence is defined for each segment of the beam structure. The mode shape increment is defined as the increase in the mode shape value. Furthermore, a damage measure index that provide enhance damage information is obtained as the product of the possibility of damage existence and mode shape increment. A numerical model of a simply supported steel beam is applied to demonstrate this method by imposing damage through thickness reduction of elements in segments. In addition, a parametric analysis is carried out to evaluate noise effect by considering varying damage severities and different noise levels. The results showed that this method is simple and provides considerable accurate results.     

Performance assessment of gas crossover phenomenon and water transport mechanism in high pressure PEM electrolyzer

To improve proton exchange membrane (PEM) electrolyzes’ performance the voltage loss through them should be avoided. In this work, it is intended to analyze losses including of diffusion loss, ohmic loss due to electrode, bipolar plate (BP), and membrane resistances, and gas crossover associated with the water transferring mechanisms. All of the losses are associated with water transferring mechanisms, which is created due to electro-osmoic drag, pressure differential between the anode and cathode sides, and diffusion. Furthermore, the effect of membrane thickness, cathode pressure, and operating temperature on the hydrogen crossover is examined. In addition, the contribution of ohmic loss due to electrode bipolar plate (BP), and membrane resistances is studied and, the contribution of different losses on the cell performance is discussed. Results show that raising cathode pressure from 1 to 40 bar lead to the increment of anodic hydrogen content from 1.038% to 21% at the specific current density of 10,000 A/m2. Enhancing the thickness of membrane has considerable impact on decrementing anodic hydrogen content, but the mass transfer loss rises from 0.022 to 0.027 V with enhancing membrane thickness from 50 to 300 μm, respectively. Furthermore, the contribution of voltage losses, assigned to each of losses are equal to 85%, 3%, and 12% for activation, diffusion and ohmic losses, respectively. It is found that, from the reported contribution for ohmic loss, the contribution of electrode BP, and membrane resistances are 31% and 69%, respectively.     

基于多尺度双线性卷积神经网络的多角度下车型精细识别

针对多角度下车辆出现一定的尺度变化和形变导致很难被准确识别的问题，提出基于多尺度双线性卷积神经网络（MS-B-CNN）的车型精细识别模型。首先，对双线性卷积神经网络（B-CNN）算法进行改进，提出MS-B-CNN算法对不同卷积层的特征进行了多尺度融合，以提高特征表达能力；此外，还采用基于中心损失函数与Softmax损失函数联合学习的策略，在Softmax损失函数基础上分别对训练集每个类别在特征空间维护一个类中心，在训练过程中新增加样本时，网络会约束样本的分类中心距离，以提高多角度情况下的车型识别的能力。实验结果显示，该车型识别模型在CompCars数据集上的正确率达到了93.63%，验证了模型在多角度情况下的准确性和鲁棒性。     

基于时间延迟的多类型维修与经济生产批量联合优化研究

针对目前未能较好的综合考虑多维修类型与经济生产批量联合优化的问题，首先考虑多类型维修关系，基于时间延迟理论求出故障和缺陷次数的表达式；其次，在此基础上，综合考虑生产费用和维修费用的基础上，构建了多类型维修和经济生产批量联合优化模型，以单位时间内总费用最小为优化目标，获得最优检查间隔期和经济生产批量；最后，通过算例分析验证了模型的有效性，说明了第一类缺陷检查次数的多少对费用和经济生产批量影响不大。     

Extended vertical lists for temporal pattern mining from multivariate time series

In this paper, the problem of mining complex temporal patterns in the context of multivariate time series is considered. A new method called the Fast Temporal Pattern Mining with Extended Vertical Lists is introduced. The method is based on an extension of the level‐wise property, which requires a more complex pattern to start at positions within a record where all of the subpatterns of the pattern start. The approach is built around a novel data structure called the Extended Vertical List that tracks positions of the first state of the pattern inside records and links them to appropriate positions of a specific subpattern of the pattern called the prefix. Extensive computational results indicate that the new method performs significantly faster than the previous version of the algorithm for Temporal Pattern Mining; however, the increase in speed comes at the expense of increased memory usage.     

往复式活塞压缩机中间喷液制冷系统的(火用)分析

通过对往复式活塞压缩机进行改造，在单级活塞压缩系统的基础上搭建了一种中间喷液冷却的准两级压缩系统并在蒸发温度为-20 ℃的工况下进行实验测量，根据实验数据对单级活塞压缩系统和新型中间喷液冷却活塞压缩系统的COP、〖HT5”，7”〗火〖KG-*3〗用〖HT5”〗损失和〖HT5”，7”〗火〖KG-*3〗用〖HT5”〗效率进行计算。结果表明：加入中间喷液冷却系统后，系统的COP由1.27提升至1.36，单位制冷量由155.1 kJ/kg提升至176.7 kJ/kg；单级活塞压缩系统〖HT5”，7”〗火〖KG-*3〗用〖HT5”〗损失较大的部分是压缩机和膨胀阀，分别占压缩机输入〖HT5”，7”〗火〖KG-*3〗用〖HT5”〗的16.2%和14.8%，加入中间喷液冷却系统后压缩机部分的〖HT5”，7”〗火〖KG-*3〗用〖HT5”〗损失明显降低，仅占压缩机输入〖HT5”，7”〗火〖KG-*3〗用〖HT5”〗的3.6%，冷凝器及膨胀阀的〖HT5”，7”〗火〖KG-*3〗用〖HT5”〗损比也有所下降。     

油砂沥青质对油砂沥青中甲苯残留的影响

利用热重质谱联用仪（TG-MS）分析了三种油砂沥青（印尼油砂沥青、伊朗油砂沥青、加拿大油砂沥青）中的甲苯残留以及油砂沥青质含量对油砂沥青中甲苯残留的影响，并在此基础上，进一步研究了油砂沥青质中的甲苯残留。结果发现，不同油砂沥青中甲苯残留量存在一定差异，其中印尼油砂沥青中的甲苯残留量最多。进一步对沥青质质量分数分别为10%、19%、30%的油砂沥青样品进行热重质谱实验，发现随着油砂沥青中沥青质含量的增加，甲苯的残留量会成倍增加。以加拿大油砂沥青质为例，研究了油砂沥青质对溶剂残留的影响，发现油砂沥青质具有对甲苯分子的夹带能力，导致甲苯分子在超过自身沸点40℃以上才能从沥青质中分离出来。油砂沥青中其他组分的存在也会加剧沥青质对甲苯的夹带作用。此外，研究还发现，在350~650℃时，油砂沥青质可以热解产生甲苯，而且油砂沥青中的沥青质含量越高，热解生成的甲苯越多。     

基于翻领松量结构模型的翻折领结构设计方法

为解决翻领松量计算精准性及翻折领通用结构设计方法的问题,提出了一种基于翻领松量结构模型的翻折领结构设计方法。通过构建翻领松量结构模型确定了翻领松量计算系数,对6种不同状态下的翻领间隙量变化进行数据统计分析,依据翻领间隙回归系数模型确定了翻领松量计算给定常数,运用SPSS统计软件对实验数据进行了相关性分析、回归分析、配对样本T检验,并推导出翻领松量计算公式。实验结果表明:使用该公式计算的翻领松量提高了翻折领结构造型的准确性,基于翻领松量结构模型的翻折领结构设计方法可以满足不同翻折领领型结构设计要求。