Brake Strategy Analysis for Industrial Normal-closed Brake Based on Rotational Inertia Test and Simulation

Industrial brakes pose the dilemma of weighing brake capability against brake impact since the brake torque cannot be adjusted. On the one hand, the brake torque may be insufficient to stop the movement within a limited distance or parking position. On the other hand, the brake torque may be so high it can damage the transmission chain. In this study, the traditional brake strategy and the field oriented control (FOC) brake strategy were compared through simulation and a rotational inertia test. The influence of the rated brake torque and the open-closed ratio were obtained. Based on the test and simulation results, a semi-empirical formula that defines the relationship between relative brake capability and open-closed ratio was developed. Additional simulations were performed to analyze the performance of the brake in a flexible transmission chain. As an industrial application example, the benefits and the cost of a 'smart brake' based on the FOC brake strategy were analyzed. The results indicate that the equivalent brake torque with the FOC brake strategy is a function of the real-time controllable input and open-closed ratio, which can be conducted during the braking procedure. This can be an efficient way to solve the above problems

IMP3 expression is associated with poor outcome and epigenetic deregulation in intrahepatic cholangiocarcinoma

IMP3 is a fetal protein not expressed in normal adult tissues. IMP3 is an oncoprotein and a useful biomarker for a variety of malignancies and is associated with reduced overall survival of a number of them. IMP3 expression and its prognostic value for patients with intrahepatic cholangiocarcinoma (ICC) have not been well investigated. The molecular mechanism underlying IMP3 expression in human cancer cells remains to be elucidated. Here we investigated IMP3 expression in ICC and adjacent nonneoplastic liver in 72 unifocal primary ICCs from a single institute by immunohistochemistry, immunoblotting, and real-time polymerase chain reaction. IMP3 was specifically expressed in cancer cells but not in the surrounding normal tissue, and 59 (82%) of 72 ICCs were IMP3 positive by immunohistochemistry. Among 35 cases with lymphovascular invasion, 26 (74%) showed IMP3 positivity in lymph node metastases. IMP3 expression was significantly correlated with tumor size, pathological grade, metastasis, and clinical stage. Kaplan-Meier analysis demonstrated an inverse correlation between IMP3 expression and overall survival rate. Multivariate analysis revealed that IMP3 was the only risk factor associated with survival. To further explore the mechanism of IMP3 expression in cancers, we identified 2 CpG islands at IMP3 proximal promoter. Interestingly, the IMP3 promoter was almost completely demethylated in ICCs in contrast to densely methylated promoter in normal liver tissues. IMP3 expression is a useful biomarker for ICCs and can provide an independent prognostic value for patients with ICC. To our knoweldge, this is the first direct evidence of epigenetic deregulation of IMP3 in human cancer. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved

User experience evaluation method based on online product reviews

Evaluating the quality of the user experience (UX) of existing products is important for new product development. Conventional UX evaluation methods, such as questionnaire, have the disadvantages of the great subjective influence of investigators and limited number of participants. Meanwhile, online product reviews on e-commerce platforms express user evaluations of product UX. Because the reviews objectively reflect the user opinions and contain a large amount of data, they have potential as an information source for UX evaluation. In this context, this study explores how to evaluate product UX through using online product reviews. A pilot study is conducted to define the key elements of a review. Then, a systematic method of product UX evaluation based on reviews is proposed. The method includes three parts: extraction of key elements, integration of key elements, and quantitative evaluation based on rough number. The effectiveness of the proposed method is demonstrated by a case study using reviews of a wireless vacuum cleaner. Based on the proposed method, designers can objectively evaluate the UX quality of existing products and obtain detailed suggestions for product improvement

Modeling pedestrian safety at roundabouts

This study proposes a method for using a human participant in a field experiment to model pedestrian safety at roundabouts in the United States. Studies show that roundabouts are safer for vehicles, but are inconclusive as to whether pedestrians are at greater risk at roundabouts than at signalized intersections. Recent simulations, including virtual reality, can model pedestrian vehicle interaction, but the proposed technique could use real-world data to calibrate these models. Eight hours of video was made to gather data at a signalized intersection and a roundabout. A physical simulation was used to assess the pedestrian’s cross/don’t cross decision. Standard walking pace was simulated at 3.5 feet per second and a disabled pedestrian at half that pace. This study focused on factors such as signalization, approach streams, exit vs. entrance lanes, pace and direction to provide a realistic picture of the cross vs. don’t cross decision. Data showed that slow pedestrians had a significantly higher rate of don’t cross decisions at the roundabout. Roundabouts are thought to be safer for pedestrians than signalized intersections due to a lower number of conflict points, but the confusing multiple streams of roundabout traffic converging on exit lanes and the frames of approaching traffic at roundabout entrances may mean that another concept may be needed to fully capture pedestrian risks. The data on ‘relevant traffic’ showed that pedestrians had to be attentive to almost six times as many approach streams of traffic in the roundabout as in the signalized intersection. The value of this study is four-fold: 1) Future studies could revisit the conflict point at the core of Traffic Conflict Analysis and consider conflict streams as well; 2) Future studies could consider the cross/don’t cross decision as an important data point with which to evaluate the safety of roundabout crossings; 3) Slow pedestrians fared worse in their ability to cross at the roundabout than at the signalized intersection; 4) The human participant in a field experiment method can be a valuable source of data for calibrating pedestrian safety simulation systems

Multipointer Coattention Recommendation with Gated Neural Fusion between ID Embedding and Reviews

Recently, the interaction information from reviews has been modeled to acquire representations between users and items and improve the sparsity problem in recommendation systems. Reviews are more responsive to information about users’ preferences for the different aspects and attributes of items. However, how to better construct the representation of users (items) still needs further research. Inspired by the interaction information from reviews, auxiliary ID embedding information is used to further enrich the word-level representation in the proposed model named MPCAR. In this paper, first, a multipointer learning scheme is adopted to extract the most informative reviews from user and item reviews and represent users (items) in a word-by-word manner. Then, users and items are embedded to extract the ID embedding that can reveal the identity of users (items). Finally, the review features and ID embedding are input to the gated neural network for effective fusion to obtain richer representations of users and items. We randomly select ten subcategory datasets from the Amazon dataset to evaluate our algorithm. The experimental results show that our algorithm can achieve the best results compared to other recommendation approaches

The role of miR-34a in the hepatoprotective effect of hydrogen sulfide on ischemia/reperfusion injury in young and old rats.

Hydrogen sulfide (H2S) can protect the liver against ischemia-reperfusion (I/R) injury. However, it is unknown whether H2S plays a role in the protection of hepatic I/R injury in both young and old patients. This study compared the protective effects of H2S in a rat model (young and old animals) of I/R injury and the mechanism underlying its effects. Young and old rats were assessed following an injection of NaHS. NaHS alone reduced hepatic I/R injury in the young rats by activating the nuclear erythroid-related factor 2 (Nrf2) signaling pathway, but it had little effect on the old rats. NaHS pretreatment decreased miR-34a expression in the hepatocytes of the young rats with hepatic I/R. Overexpression of miR-34a decreased Nrf-2 and its downstream target expression, impairing the hepatoprotective effect of H2S on the young rats. More importantly, downregulation of miR-34a expression increased Nrf-2 and the expression of its downstream targets, enhancing the effect of H2S on hepatic I/R injury in the old rats. This study reveals the different effects of H2S on hepatic I/R injury in young and old rats and sheds light on the involvement of H2S in miR-34a modulation of the Nrf-2 pathway

Multipointer Coattention Recommendation with Gated Neural Fusion between ID Embedding and Reviews

Recently, the interaction information from reviews has been modeled to acquire representations between users and items and improve the sparsity problem in recommendation systems. Reviews are more responsive to information about users’ preferences for the different aspects and attributes of items. However, how to better construct the representation of users (items) still needs further research. Inspired by the interaction information from reviews, auxiliary ID embedding information is used to further enrich the word-level representation in the proposed model named MPCAR. In this paper, first, a multipointer learning scheme is adopted to extract the most informative reviews from user and item reviews and represent users (items) in a word-by-word manner. Then, users and items are embedded to extract the ID embedding that can reveal the identity of users (items). Finally, the review features and ID embedding are input to the gated neural network for effective fusion to obtain richer representations of users and items. We randomly select ten subcategory datasets from the Amazon dataset to evaluate our algorithm. The experimental results show that our algorithm can achieve the best results compared to other recommendation approaches

Brake Strategy Analysis for Industrial Normal-closed Brake Based on Rotational Inertia Test and Simulation

Industrial brakes pose the dilemma of weighing brake capability against brake impact since the brake torque cannot be adjusted. On the one hand, the brake torque may be insufficient to stop the movement within a limited distance or parking position. On the other hand, the brake torque may be so high it can damage the transmission chain. In this study, the traditional brake strategy and the field oriented control (FOC) brake strategy were compared through simulation and a rotational inertia test. The influence of the rated brake torque and the open-closed ratio were obtained. Based on the test and simulation results, a semi-empirical formula that defines the relationship between relative brake capability and open-closed ratio was developed. Additional simulations were performed to analyze the performance of the brake in a flexible transmission chain. As an industrial application example, the benefits and the cost of a 'smart brake' based on the FOC brake strategy were analyzed. The results indicate that the equivalent brake torque with the FOC brake strategy is a function of the real-time controllable input and open-closed ratio, which can be conducted during the braking procedure. This can be an efficient way to solve the above problems