Miracle-dz/UniFAR-FTUs huggingface dataset:
The Protective Effect of Bcl-xl Overexpression against Oxidative Stress-Induced Vascular Endothelial Cell Injury and the Role of the Akt/eNOS Pathway

Restenosis after intraluminal or open vascular reconstruction remains an important clinical problem. Vascular endothelial cell (EC) injury induced by oxidative stress plays an important role in the development of intimal hyperplasia. In this study, we sought to evaluate the protective effects of Bcl-xl overexpression in vitro on oxidative stress-induced EC injury and the role of the Akt/endothelial nitric oxide synthase (eNOS) pathway. Human umbilical vein endothelial cells (HUVECs) exposed to hydrogen peroxide (H2O2, 0.5 mM) were used as the experimental oxidative stress model. The Bcl-xl gene was transferred into HUVECs through recombinant adenovirus vector pAdxsi-GFP-Bcl-xl before oxidative treatment. Cell apoptosis was evaluated by Annexin V/propidium iodide and Hoechst staining, caspase-7 and PARP cleavage. Cell viability was assessed using the cell counting kit-8 assay, proliferating cell nuclear antigen (PCNA) immunocytochemical detection and the scratching assay. Expressions of Akt, phospho-Akt and eNOS were detected by Western blotting. Our results showed that H2O2 induced apoptosis and decreased the cell viability of HUVECs. Bcl-xl overexpression significantly protected cells from H2O2-induced cell damage and apoptosis and maintained the cell function. Furthermore, the level of phospho-Akt and eNOS protein expression was significantly elevated when pretreated with Bcl-xl gene transferring. These findings suggest that Bcl-xl overexpression exerts an anti-apoptotic and protective effect on EC function. The Akt/eNOS signaling pathway is probably involved in these processes.
The DLR lightweight robot: design and control concepts for robots in human environments

– The paper seeks to present a new generation of torque‐controlled light‐weight robots (LWR) developed at the Institute of Robotics and Mechatronics of the German Aerospace Center. , – An integrated mechatronic design approach for LWR is presented. Owing to the partially unknown properties of the environment, robustness of planning and control with respect to environmental variations is crucial. Robustness is achieved in this context through sensor redundancy and passivity‐based control. In the DLR root concept, joint torque sensing plays a central role. , – In order to act in unstructured environments and interact with humans, the robots have design features and control/software functionalities which distinguish them from classical robots, such as: load‐to‐weight ratio of 1:1, torque sensing in the joints, active vibration damping, sensitive collision detection, compliant control on joint and Cartesian level. , – The DLR robots are excellent research platforms for experimentation of advanced robotics algorithms. Space and medical robotics are further areas for which these robots were designed and hopefully will be applied within the next years. Potential industrial application fields are the fast automatic assembly as well as manufacturing activities done in cooperation with humans (industrial robot assistant). The described functionalities are of course highly relevant also for the potentially huge market of service robotics. The LWR technology was transferred to KUKA Roboter GmbH, which will bring the first arms on the market in the near future. , – This paper introduces a new type of LWR with torque sensing in each joint and describes a consistent approach for using these sensors for manipulation in human environments. To the best of one's knowledge, the first systematic experimental evaluation of possible injuries during robot‐human crashes using standardized testing facilities is presented.
Current Trends and the Future of Metamorphic Malware Detection

Dynamic binary obfuscation or metamorphism is a technique where a malware never keeps the same sequence of opcodes in the memory. This stealthy mutation technique helps a malware evade detection by today's signature-based anti-malware programs. This paper analyzes the current trends, provides future directions and reasons about some of the basic characteristics of a system for providing real-time detection of metamorphic malware. Our emphasis is on the most recent advancements and the potentials available in metamorphic malware detection, so we only cover some of the major academic research efforts carried out, including and after, the year 2006. The paper not only serves as a collection of recent references and information for easy comparison and analysis, but also as a motivation for improving the current and developing new techniques for metamorphic malware detection.
A Graph Transformation-Based Approach for Applying MDA to SOA

Although Model Driven Architecture has taken successful steps toward model-based software development, this approach still faces complex situations and ambiguous questions while applying to real world software systems. One of these questions - which has taken the most interest and focus - is how model transforms between different abstraction levels, MDA proposes. In this paper, we propose an approach based on Story Driven Modeling and Aspect Oriented Programming to ease these transformations. Service Oriented Architecture is taken as the target model to test the proposed mechanism in a functional system.
WSN and RFID integrated solution for advanced safety systems in industrial plants

The Smart Factory concept has been enabled in the last few years thanks to both Wireless Sensor Networks (WSNs) and Radio-Frequency IDentification (RFID) technologies. Although the two technologies have been adopted in isolation in factory automation applications, their partial integration start to be considered in different research fields. In this work, we propose a fully integrated approach between RFID and WSN targeted to develop an advanced safety system in industrial plants. By integrating RFID tags and readers in WSN nodes the developed system extends sensing capabilities, efficiency and pervasiveness of the WSN solutions already installed in the factory plant, while allowing a safety access to dangerous areas under the requirement that safety equipments are adopted. The paper presents both hardware and software solutions developed as well as performance evaluation results, in terms of system response time and energy consumption reduction, in a real testbed.
The Non-vanishing Cohomology of Orlik-Solomon Algebras

The cohomology on the complement of hyperplanes with the coefficients in the rank one local system associated to a generic weight vanishes except in the highest dimension. In this paper, we construct matroids or arrangements and its weights with non-vanishing cohomology of Orlik-Solomon algebras, using decomposable relations arising from Latin hypercubes.
Hierarchical multilabel classification for Indonesian news articles

Multilabel news classification is needed since numerous news could be labeled with two or more categories. This research is conducted in the account of Indonesian news, because researches in this area are still rare. The classification method used in this paper is called hierarchical multilabel classification and is used to decide the class and subclass of every single news using problem transformation approach. The aim of this study is to discover whether hierarchical multilabel classification is suitable to be implemented Indonesian news. Based on the experiment conducted, Naïve Bayes algorithm gives the best performance when it applied to construct the model.
Modeling Users' Dynamic Preference for Personalized Recommendation

Modeling the evolution of users' preference over time is essential for personalized recommendation. Traditional time-aware models like (1) time-window or recency based approaches ignore or deemphasize much potentially useful information, and (2) time-aware collaborative filtering (CF) approaches largely rely on the information of other users, thus failing to precisely and comprehensively profile individual users for personalization. In this paper, for implicit feedback data, we propose a personalized recommendation model to capture users' dynamic preference using Gaussian process. We first apply topic modeling to represent a user's temporal preference in an interaction as a topic distribution. By aggregating such topic distributions of the user's past interactions, we build her profile, where we treat each topic's values at different interactions as a time series. Gaussian process is then applied to predict the user's preference in the next interactions for top-N recommendation. Experiments conducted over two real datasets demonstrate that our approach outperforms the state-of-the-art recommendation models by at least 42:46% and 66:14% in terms of precision and Mean Reciprocal Rank respectively.
The sequential appearance of low- and high-molecular-weight forms of MAP2 in the developing cerebellum

Mammalian microtubule-associated protein 2 (MAP2) exists in high- molecular-weight (Mr approximately 280,000) and low-molecular-weight (Mr approximately 70,000) forms, with the latter protein being more abundant in embryonic brain homogenates than in preparations from mature brain (Riederer and Matus, 1985). In the current study, we have shown that avian MAP2 also exists as both high- (Mr approximately 260,000) and low-molecular-weight (Mr approximately 65,000) forms whose relative abundance changes during brain maturation, indicating a conserved function for these proteins during vertebrate neuronal morphogenesis. Using indirect immunohistochemistry, we have determined the cellular distribution of the high- and low-molecular-weight forms of MAP2 in the developing avian cerebellum. In the embryonic cerebellum, low-molecular-weight MAP2 is found in the external granular layer and in epithelial cells. High-molecular-weight MAP2 is found only in neurons that have commenced dendrogenesis, i.e., Purkinje cells and neurons within the internal granular layer. Thus, low-molecular-weight MAP2 is not only more abundant in embryonic nervous tissue than in the adult, but it also appears in glia and in differentiating neurons before the high-molecular-weight form. We have also shown that in the mature cerebellum high-molecular-weight MAP2 cannot be detected with monoclonal antibodies or polyclonal antisera in Purkinje cell dendrites. Polyclonal antisera against the regulatory subunit of the cAMP-dependent protein kinase, which is associated with MAP2 in the Purkinje cell dendrites of the rat, also fail to stain Purkinje cell dendrites in the mature quail cerebellum. This suggests that high- molecular-weight MAP2 may be necessary for the establishment of dendrites but is not necessary for the maintenance of dendritic form.
Review-oriented metadata enrichment: a case study

Book reviews contributed by readers in social sites contain valuable information on books' content, style and merit, many informative words in which can be used to enrich metadata of books in China-Us Million Book Digital Library. In this paper, we present a system for review-oriented metadata enrichment and propose an Book-Centric Diverse Random Walk algorithm on a four-partite graph containing three kinds of relations among authors, books, reviews and words, in order to produce highly relevant as well as diverse keywords for a book. Experimental results of a user study show that our approach significantly outperforms other methods in terms of relevance and diversity. The metadata generated by our approach also has a large overlap with popular social tags and brief introductions from DouBan for books in the coverage experiments.
A Five-Year Hedonic Price Breakdown for Desktop Personal Computer Attributes in Brazil

The purpose of this article is to identify the attributes that discriminate the prices of personal desktop computers. We employ the hedonic price method in evaluating such characteristics. This approach allows market prices to be expressed as a function, a set of attributes present in the products and services offered. Prices and characteristics of up to 3,779 desktop personal computers offered in the IT pages of one of the main Brazilian newspapers were collected from January 2003 to December 2007. Several specifications for the hedonic (multivariate) linear regression were tested. In this particular study, the main attributes were found to be hard drive capacity, screen technology, main board brand, random memory size, microprocessor brand, video board memory, digital video and compact disk recording devices, screen size and microprocessor speed. These results highlight the novel contribution of this study: the manner and means in which hedonic price indexes may be estimated in Brazil.
Use of body condition scores in clinical assessment of the provision of optimal nutrition.

T concept of providing optimal nutrition has been promoted by nutritionists and manufacturers of diets and feeds for a number of years. The nutrient profiles and feeding management that constitute optimal nutrition are ultimately determined by the productivity or outcome desired for each animal in a given situation. For example, running as fast as possible at maximum effort for a brief period versus running as fast as possible at less-than-maximum effort under inclement conditions for prolonged periods argues for 2 types of nutrient profiles and feeding strategies. Similarly, maximizing growth rate or milk production versus achieving more modest rates of growth or production and decreasing the risk of disease seemingly would affect nutrient profiles and feeding management. Finally, a particular disease or condition, its specific physiologic derangements, and severity of the problem can alter the nutrient profile or feeding management with regard to what is believed to be optimal. Attaining a specific performance goal is the quintessential determinant of whether optimal nutrition has been provided, but often an intermediate or preliminary assessment is desired prior to reaching a definitive end-point. Sometimes, end-products or intermediates of physiologic reactions that are affected by nutritional manipulations can be measured with relative ease. However, in all instances, the optimal nutrient profile and feeding strategy ultimately produces a characteristic body condition that is apparent during assessment. This should not be construed to mean that all optimal nutrient profiles and feeding strategies result in an optimal body condition. Based on the desired goal for production or performance of a specific animal, an optimal nutrient profile and feeding strategy may produce a body condition score (BCS) that is slightly more or slightly less than midscale BCS.
CrowdER: Crowdsourcing Entity Resolution

Entity resolution is central to data integration and data cleaning. Algorithmic approaches have been improving in quality, but remain far from perfect. Crowdsourcing platforms offer a more accurate but expensive (and slow) way to bring human insight into the process. Previous work has proposed batching verification tasks for presentation to human workers but even with batching, a human-only approach is infeasible for data sets of even moderate size, due to the large numbers of matches to be tested. Instead, we propose a hybrid human-machine approach in which machines are used to do an initial, coarse pass over all the data, and people are used to verify only the most likely matching pairs. We show that for such a hybrid system, generating the minimum number of verification tasks of a given size is NP-Hard, but we develop a novel two-tiered heuristic approach for creating batched tasks. We describe this method, and present the results of extensive experiments on real data sets using a popular crowdsourcing platform. The experiments show that our hybrid approach achieves both good efficiency and high accuracy compared to machine-only or human-only alternatives.
Design collaborative systems with multiple AF-relays for asynchronous frequency-selective fading channels

Distributed systems with multiple amplify-andforward (AF) relays are very appealing, due to their ease of implementing space diversity. Although their performance on synchronous flat-fading channels was well understood, the corresponding design and optimization in asynchronous frequency selective fading (AFSF) channels remains unsolved. In this paper, we tackle the problem in the information-theoretic framework, revealing that multi-relay amplify-and-forward (MR-AF) systems over AFSF channels can be better understood through the concept of virtual sub-channels. Each relay node virtually performs two functions, appropriately amplifying sub-channel signals on one hand and serving as a local switching center on the other. System design, therefore, reduces to the determination of optimal amplification factors, switching matrices, and power allocation among the source, relays and relevant sub-channels. The optimization is implemented in a layered structure. The effects of asynchronism and knowledge of channel information on mutual information are also investigated.
Modified Routing Algorithm for AODV in Constrained Conditions

On-demand routing protocol exhibits abnormal behavior during high mobility and multiple data streams sent to a common destination. This may decay the performance of adhoc on demand distance vector routing (AODV). The proposed work is aimed at performance improvement in Internet connectivity by applying local congestion methods in routing protocols. This method increases the packet delivery ratio of AODV even in constrained conditions to a satisfactory level, which has been major concern in the routing algorithm in mobile ad hoc networks. The results are also convincing in improvement in normalized routing load and end to end delay. The numerical results of this work are having improvement over existing algorithms upto 27%.
Uniwide WiFi based positioning system

Millions of people travel between countries and regions on a daily basis being exposed to unfamiliar environments. Knowing where you are and how to get to places within a restricted time can make people's lives easier. Today, WiFi access points (APs) are common everywhere, especially on university campuses, in hotels, hospitals, shopping centres, and city central business districts. This project, dubbed WiPos (WiFi-Positioning), had the objective to develop a positioning system using WiFi APs deployed across a university to locate one's position in a building under conditions where GPS could not be used. When relatively accurate user position is available, location based services (LBS) can be provided to users, including timetable of a lecture room, location of the nearest vending machine, and so on. This project involved developing a server and a client (running on the Android platform) to handle positioning and LBS transactions. Testing has shown that the university's WiFi network is sufficient to provide ‘room to room’ accuracy.
Experimental analysis of RSSI for distance and position estimation

In wireless sensor network (WSN), position awareness (localization) of the sensor nodes is necessary to exploit the communication and to provide the meaningful information about their surroundings. Here Received Signal Strength Indicator (RSSI) technique is used as it requires no extra hardware and can be used for both indoor and outdoor environment. RSSI is having limitations such as high randomness due to fading and shadowing. This makes difficulties in establishing exact relationship between RSSI value and distance. In this paper we propose the method of creating database by using Split Range Technique (SRT) to estimate the approximate distance between two nodes. Using this database, position estimation has been done. For this Adaptive n-Triangle algorithm is implemented. Present results of RSSI shows the approximate positioning of the sensor node with the error estimation of about 5–10%. The experiment can be extended to show the predicted path of a moving object which is being identified by sensors.
Why are normalization methods not interchangeable ?

SARTools is a R package associated with two R script templates which allow one to perform differential analysis with either DESeq2 [1] or edgeR [2], the normalization method employed being the one associated with the package used. The purpose of this additional file is to show that normalization methods are not interchangeable between statistical models without adequate transformation. Despite this has been recalled in [3] some users of R packages for differential expression are still not aware of that. This is an important issue as DESeq(2) and edgeR use normalization factors in two different ways : DESeq(2) integrates the size factors in the calculation of the mean of the Negative Binomial distribution used to model raw counts when edgeR normalizes library sizes and includes them as an offset in the statistical model for differential testing. Therefore, normalization factors should be computed and used with regard to the statistical test that follows.
Nonparametric Profile Monitoring by Mixed Effects Modeling

In some applications, the quality of a process is characterized by the functional relationship between a response variable and one or more explanatory variables. Profile monitoring is for checking the stability of this relationship over time. Control charts for monitoring nonparametric profiles are useful when the relationship is too complicated to be described parametrically. Most existing control charts in the literature are for monitoring parametric profiles. They require the assumption that within-profile measurements are independent of each other, which is often invalid in practice. This article focuses on nonparametric profile monitoring when within-profile data are correlated. A novel control chart is suggested, which incorporates local linear kernel smoothing into the exponentially weighted moving average (EWMA) control scheme. In this method, within-profile correlation is described by a nonparametric mixed-effects model. Our proposed control chart is fast to compute and convenient to use. Numerical examples show that it works well in various cases. Some technical details are provided in an Appendix available online as supplemental materials.
What Motivates Students to Learn? Applications for All Classroom Levels

The Deans for Impact (DFI) (2015) report posed the question "What motivates students to learn? ". This article examines strategies and interventions for each of the four cognitive principles presented in the report. Within this paper, applications of the cognitive principles will be discussed at the elementary, secondary and postsecondary levels. The techniques recommended in reference to belief about intelligence include collective goal writing, focus on ability to overcome setbacks, and reinforcing a growth mindset. Techniques for self-determined motivation reviewed include Project Based Learning, creating academic competition, and the use of letter grades in college courses. As teachers encourage students’ ability to monitor their own learning, this article reviews Socratic Seminar techniques, Question Answer Relationships, and reflective writing methods as possible strategies. Finally, this article includes interventions to reinforce belonging and acceptance through Writer’s Workshops, the wise feedback technique, and creating social-norming related to struggles with fitting in.