Miracle-dz/UniFAR-FTUs huggingface dataset:
Five year clinical effect of coronary stenting and coronary artery bypass grafting in renal insufficient patients with multivessel coronary artery disease: insights from ARTS trial.

AIMS To compare coronary stent implantation and bypass surgery for multivessel coronary disease in patients with renal insufficiency. METHODS AND RESULTS In the ARTS trial, 142 moderate renal insufficient patients (Ccr<60 mL/min) with multivessel coronary disease were randomly assigned to stent implantation (n=69) or CABG (n=73). At 5 years, there was no significant difference between the two groups in terms of mortality (14.5% in the stent group vs. 12.3% in the CABG group, P=0.81), or combined endpoint of death, cerebrovascular accident (CVA), or myocardial infarction (MI) (30.4% in the stent group vs. 23.3% in the CABG group, P=0.35). Among patients who survived without CVA or MI, 18.8% in the stent group underwent a second revascularization procedure when compared with 8.2% in the surgery group (P=0.08). The event-free survival at 5 years was 50.7% in the stent group and 68.5% in the surgery group (P=0.04). CONCLUSION At 5 years, the differences in mortality and combined incidence of death, CVA, and MI between coronary stenting and surgery did not reach statistically significant level. However, the occurrence of MACCE in the stent group was higher than in the CABG group, mainly driven by the higher incidence of repeat revascularization in the stent group.
Renal and Hormonal Responses to Direct Renin Inhibition With Aliskiren in Healthy Humans

Background— Pharmacological interruption of the renin-angiotensin system focuses on optimization of blockade. As a measure of intrarenal renin activity, we have examined renal plasma flow (RPF) responses in a standardized protocol. Compared with responses with angiotensin-converting enzyme inhibition (rise in RPF ≈95 mL · min−1 · 1.73 m−2), greater renal vasodilation with angiotensin receptor blockers (≈145 mL · min−1 · 1.73 m−2) suggested more effective blockade. We predicted that blockade with the direct oral renin inhibitor aliskiren would produce renal vascular responses exceeding those induced by angiotensin-converting enzyme inhibitors and angiotensin receptor blockers. Methods and Results— Twenty healthy normotensive subjects were studied on a low-sodium (10 mmol/d) diet, receiving separate escalating doses of aliskiren. Six additional subjects received captopril 25 mg as a low-sodium comparison and also received aliskiren on a high-sodium (200 mmol/d) diet. RPF was measured by clearance of para-aminohippurate. Aliskiren induced a remarkable dose-related renal vasodilation in low-sodium balance. The RPF response was maximal at the 600-mg dose (197±27 mL · min−1 · 1.73 m−2) and exceeded responses to captopril (92±20 mL · min−1 · 1.73 m−2; P<0.01). Furthermore, significant residual vasodilation was observed 48 hours after each dose (P<0.01). The RPF response on a high-sodium diet was also higher than expected (47±17 mL · min−1 · 1.73 m−2). Plasma renin activity and angiotensin levels were reduced in a dose-related manner. As another functional index of the effect of aliskiren, we found significant natriuresis on both diets. Conclusions— Renal vasodilation in healthy people with the potent renin inhibitor aliskiren exceeded responses seen previously with angiotensin-converting enzyme inhibitors and angiotensin receptor blockers. The effects were longer lasting and were associated with significant natriuresis. These results indicate that aliskiren may provide more complete and thus more effective blockade of the renin-angiotensin system.
Using Semantic Information from Neural Networks to Detect Context-Sensitive Spelling Errors

This paper proposes a means of using the internal representations of an artificial neural network to represent the semantic contexts in which a word can appear. Once the network has been trained, its hidden layer activations are recorded as a representation of the average context in which a word can appear. This context can then be compared to the contexts in which a word appears in novel text to detect context-sensitive spelling errors. While no significant results are found in the trials described here, several modifications of the system are proposed that might prove promising in future
The Open Corporation: The three strategies of ‘permeability’ in the open Corporation

The Open Corporation, originally published in 2002, set out a blueprint for effective corporate self-regulation, offering practical strategies for managers, stakeholders and regulators to build successful self-regulation management systems. Christine Parker examined the conditions under which corporate self-regulation of social and legal responsibilities were likely to be effective, covering a wide range of areas - from consumer protection to sexual harassment to environmental compliance. Focusing on the features that make self-regulation or compliance management systems effective, Parker argued that law and regulators needed to focus much more on 'meta-regulating' corporate self-regulation if democratic control over corporate action was to be established.
A Survey of Classification Techniques in the Area of Big Data

Big Data concern large-volume, growing data sets that are complex and have multiple autonomous sources. Earlier technologies were not able to handle storage and processing of huge data thus Big Data concept comes into existence. This is a tedious job for users unstructured data. So, there should be some mechanism which classify unstructured data into organized form which helps user to easily access required data. Classification techniques over big transactional database provide required data to the users from large datasets more simple way. There are two main classification techniques, supervised and unsupervised. In this paper we focused on to study of different supervised classification techniques. Further this paper shows a advantages and limitations.
Intelligent system for vehicular accident detection and notification

Road accidents are a human tragedy. They involve high human suffering and monetary costs in terms of untimely deaths, injuries and loss of potential income. There are so many new techniques such as Antilock Breaking System (ABS), Adaptive Cruise Control (ACC), Anti Collision System (ACS) to avoid accidents and in spite of all this, such large number of accidents takes place. Hence this paper presents a system which gives an idea about what can be done to provide medical help and other facilities after accident as soon as possible. Accident can be detected using flex sensor and accelerometer, while location of accident will be informed to desired persons such as nearest hospital, police and owner of vehicle through sms sent using GSM modem containing co-ordinates obtained from GPS along with time of accident and vehicle number. Camera located inside vehicle will transmit real time video to see current situation of passengers inside vehicle. Thus this paper emphasizes on post-accident system for detecting and informing about it. Simulation result on hyper terminal is also presented in this paper.
Game Theoretical Models in New Product Development

In the past four decades, research of new product development has attracted attention from both academia and practitioners. The success of new product development has been regarded as one important source of firms’ competitive advantage (Krishnan & Ulrich, 2001; Luo, Kannan, Besharati, & Azarm, 2005). In order to guide decision making in product design, several consumerdriven methodologies, such as conjoint analysis, discrete choice model, etc, have been developed in the literature. These methods implicitly assume that the choice of product attribute should solely consider the market (consumer) needs. As a result, these methods seek to elicit “true” consumer preference without considering the strategic interactions among stakeholders in product design. Recently, another school of methods, which are mainly game-theoretically based, have emerged in the literature. These game theoretical models seek to open the “black box” of stakeholder interaction both between and within the organization and offer insights on how such strategic interaction will have an impact on product design. In this chapter, we are going to review some basic game theoretical modes as well as their applications in the product design literature. The methods and applications described in this chapter also have broad applicability in the research of innovation, project management and operations management. In the following sections, we will start with a brief overview of one particular type of consumerdriven product design methods, i.e., conjoint analysis. Providing a comprehensive review of conjoint analysis is clearly beyond the scope of this chapter. The purpose, instead, is to make a clear comparison between consumer-driven methods and game theoretical models, hence achieve a better understanding of how the game theoretical models are complementary to previous methods. Next, we will review game theoretical models in both strategic and extensive forms and discuss their applications in the literature. Thoughts for future research are concluded at the end.
Effects of an ad libitum, high carbohydrate diet and aerobic exercise training on insulin action and muscle metabolism in older men and women.

BACKGROUND Previous studies have demonstrated that aerobic exercise training and weight loss have independent effects on insulin-stimulated glucose disposal (ISGD). We hypothesized that ad libitum consumption of a high-carbohydrate diet would result in weight loss and improved ISGD, and that aerobic exercise training would facilitate greater improvements in ISGD compared with diet alone. METHODS Older participants (13 women, 9 men; age = 66 +/- 1 year) with impaired glucose tolerance were randomly assigned to an ad libitum diet alone (18% fat, 19% protein, 63% carbohydrate) or this diet plus aerobic exercise training (4 d/wk, 45 min/d, 80% VO(2peak)) for 12 weeks. ISGD, abdominal fat distribution, muscle glycogen, and glycogen synthase activity were assessed pre- and postintervention. RESULTS Consumption of the diet resulted in significant weight loss and an improvement in ISGD. Consumption of the diet plus exercise training also resulted in weight loss and increased ISGD, but results were not significantly different from those in the diet-alone group. Mean abdominal visceral and subcutaneous adipose tissue cross-sectional areas were smaller postintervention compared to baseline with no difference between groups. Exercise training and consumption of the diet increased muscle glycogen content (344.7 +/- 21.3 to 616.7 +/- 34.4 micromol.g(-1)) and decreased glycogen synthase activity (0.21 +/- 0.02 to 0.13 +/- 0.01) compared to the diet alone. CONCLUSIONS These results demonstrate that consumption of an ad libitum, high-carbohydrate diet alone or in combination with aerobic exercise training results in weight loss and improved insulin sensitivity. Furthermore, exercise combined with this diet appears to limit additional increases in insulin sensitivity due to muscle glycogen supercompensation with a concomitant adaptive response of glycogen synthase.
DCNS: An Adaptable High Throughput RFID Reader-to-Reader Anticollision Protocol

The reader-to-reader collision problem represents a research topic of great recent interest for the radio frequency identification (RFID) technology. Among the state-of-the-art anticollision protocols, the ones that provide high throughput often have special requirements, such as extra hardware. This study investigates new high throughput solutions for static RFID networks without additional requirements. In this paper, two contributions are presented: a new configuration, called Killer, and a new protocol, called distributed color noncooperative selection (DCNS). The proposed configuration generates selfish behavior, thereby increasing channel utilization and throughput. DCNS fully exploits the Killer configuration and provides new features, such as dynamic priority management, which modifies the performance of the RFID readers when it is requested. Simulations have been conducted in order to analyze the effects of the innovations proposed. The proposed approach is especially suitable for low-cost applications with a priority not uniformly distributed among readers. The experimental analysis has shown that DCNS provides a greater throughput than the state-of-the-art protocols, even those with additional requirements (e.g., 16 percent better than NFRA).
A data perturbation approach to sensitive classification rule hiding

This paper focuses on privacy preservation in classification rule mining. The subject at hand is approached through the proposition of a data perturbation approach for hiding sensitive classification rules in categorical datasets. Such a methodology is absolutely necessary in case the data needs to be published on the web so that it is amply available for public use as opposed to other approaches like output perturbation or cryptographic techniques that restrict the usability of the data in different ways. This methodology is based upon the unique characteristics of sequential covering classification algorithms. It modifies the tuples of sensitive rules of a dataset D in such a way that these are distributed to the "more important" non-sensitive rules. In addition it assures that the tuples belonging to the sensitive rules are assigned to the non-sensitive rules in proportion to their rank in the ruleset. In that way, it is ensured that not only the sensitive rules are hidden but also that the current structure of the ruleset, thus the information value of the dataset, is preserved. Moreover a modification of the basic method which exhibits an alternative distribution procedure is also presented. Finally, a series of experiments are executed in order to evaluate the validity and effectiveness of the proposed approaches against existing similar ones.
A Reliability Aware Flooding Algorithm (RAFA) in wireless multi-hop networks

Flooding is a mechanism that distributes packets to every node of the network. The flooding mechanism is frequently used in many operations in wireless multi-hop networks. Since flooding exploits hop-by-hop broadcasting that suffers from unreliable transmission and fading, it is hard to achieve the reliability in flooding. As unreliable flooding may lead to a coverage hole, it will have a negative effect upon upper layer protocols. In this paper, we introduce a reliability aware flooding algorithm (RAFA), which estimates the expected reliability using two-hop topology knowledge. The estimated reliability is used for deciding whether or not to retransmit a packet. Using NS-2 [19] simulator, we show that RAFA achieves the higher reliability than RBP [1] by adjusting the number of retransmissions considering the network topology, regardless of the network topologies, the node density or the number of bottlenecks.
Implicit Enumeration of Hyperpaths in a Nested Logit Model for Transit Networks

This paper investigates the application of a nested logit model to urban transit networks where every set of competitive transit lines is described by a particular graph structure called hyperpath. It shows that the nested logit model transcends the inherent limitations of the simple logit model while retaining the algorithmic advantages similar to that obtained with the ordinary logit model for private vehicle networks.
Nitrogen cycling in North Sea sediments: interaction of denitrification and nitrification in offshore and coastal areas

Benthlc nltrogen cycling was studled In different areas of the southeastern North Sea in August 1991 and February 1992 Main attention was focused on the coupling between nltrlficatlon and demtnfication Additionally, extensive measurements of sediment-water exchange of lnorganlc nitrogen compounds and of the penetration of oxygen Into the sediment were made Denltnfication rates ranged from 0 to 8 pm01 N m-' h' , whlle nitnfication rates ranged between 5 and 26 pm01 N m-2 h ' Although the oxic layer of the sedlrnent was thnne r in August, nltnfication was hlgher dunng that period, indicating the importance of ammonlum availabihty rather than oxygen penetration Except in the deposltlonal area in the German Blght, denitrlflcation was completely dependent on nitnfication In general, however, the coupllng between the 2 processes was incomplete On average, 3 and 25 % of the produced nitrate was denltr~fied In August and February respectively The bulk of the produced nltrate diffused upward (along the steepest concentratlon gradient) to the nitrate-depleted overlylng water and was unavailable for denitnficatlon, part~cularly in August It 1s postulated that the coupllng efficiency is indirectly influenced by the nitrate concentratlon in the overlylng water
Caspase-2 and the oxidative stress response

Caspase-2, one of the earliest discovered caspases, has emerged as a multifunctional enzyme with roles that are not limited to cell death. It acts as a tumor suppressor, prevents genetic instability, and protects against aging by playing a crucial role in sensing alterations in cellular redox status and activating the antioxidant defense system. These apparent non-apoptotic functions, only discovered recently, emphasize the importance of this often-neglected protease.
APPLYING REAL CODED GENETIC ALGORITHMS TO GABOR FILTER BANK DESIGN FOR SUPERVISED TEXTURE CLASSIFICATION AND SEGMENTATION

Supervised classification and segmentation of textured images find immense importance in image analysis applications and still continues to be an open research issue to the Computer Vision community. The high performance texture analysis capability of the human visual system have encouraged the researchers to model the characteristics of the receptive cells of the human eye suggesting a close resemblance to the functioning of Gabor Filter Bank for spatial frequency analysis. In this work, we focus on designing Gabor filter banks using real coded genetic algorithms with the objective of maximum discrimination of texture features.
Inter-Network Resource Sharing in IEEE 802.22 Networks

IEEE 802.22 is the first worldwide standard for Cognitive Networks (CNs) that exploits unused spectrum of the television broadcast service. An IEEE 802.22 network is also called Wireless Regional Area Network (WRAN). An open issue in cognitive 802.22 networks is represented by the resource distribution among WRANs. In this paper a protocol for radio resource management for CNs in a multichannel environment is presented and analysed. In particular, the contribution of this work is a resource sharing method to schedule the WRAN access to the available channels in a community made by two o more coexisting WRANs. The method adapts to the continuous changes of the spectrum availability due to necessity of vacating a channel in case of the incumbent primary users. Moreover, the introduced allocation scheme allows to divide the available band in a proportional way to the cognitive user spectrum demands, taking into account the issue of spatial diversity, i.e. the case where the channel coverage area is not uniform. The effectiveness of the proposed multichannel scheme is proved through simulations. The results compared favorably with other methods already known in literature and show that the proposed algorithm optimize the spectral efficiency, keeping high fairness as demonstrated computing the Jain’s index.
Spread co-citation relationship as a measure for document retrieval

This paper proposes a measure that uses a spread co-citation relationship for document retrieval. To clarify whether this proposed measure has potential for enhancing the search performance of co-citation searching, two retrieval methods are evaluated: one uses the relationship directly; the other incorporates the co-citation context. Experiments with a special test collection comprising about 152,000 documents are conducted. Results indicate that this relationship tends to be able to detect relevant documents which are undetectable using a traditional co-citation relationship, and that using context has a positive effect to reduce the number of noise documents.
General and Specific Genetic Polymorphism of Cytokines-Related Gene in AITD

Autoimmune thyroid disease (AITD) shows the highest incidence among organ-specific autoimmune diseases and is the most common thyroid disease in humans, including Graves' disease (GD) and Hashimoto's thyroiditis (HT). The susceptibility to autoimmune diseases is affected by increased autoantibody levels, susceptibility gene polymorphisms, environmental factors, and psychological factors, but the pathogenesis remains unclear. Various cytokines and related genes encoding them play important roles in the development and progression of AITD. CD152, an expression product of the CTLA-4 gene, downregulates T cell activation. The A/A genotype polymorphism in the CT60 locus may reduce the production of thyroid autoantibodies. The C1858T polymorphism of the PTNP22 gene reduces the expression of its encoded LYP, which increases the risk of GD and HT. GD is an organ-specific autoimmune disease involving increased secretion of thyroid hormone, whereas HT may be associated with the destruction of thyroid gland tissue and hypothyroidism. These two diseases exhibit similar pathogenesis but opposite trends in the clinical manifestations. In this review, we focus on the structure and function of these cytokines and related genes in AITD, as well as the association of polymorphisms with susceptibility to GD and HT, and attempt to describe their differences in pathogenesis and clinical manifestations.
Ineecient Delays in Strategic Trades

Ineecient delays in trades can sometimes be observed after the arrival of important public news. This paper explains these phenomena with a model in which agents defer trades in the fear that they may be taken advantaged of by better informed trading partners. Under certain conditions, delay is inevitable, yet total collapse of trade can be avoided.
A Wikipedia Guided Autonomous Label Assignment Method for Tables with Missing Column Names ∗ Technical Report

As the volume of information available on the internet is growing exponentially, it is clear that most of this information will have to be processed and digested by computers to produce useful information for human consumption. Unfortunately, most web contents are currently designed for direct human consumption in which it is assumed that a human will decipher the information presented to him in some context and will be able to connect the missing dots, if any. In particular, information presented in some tabular form often does not accompany descriptive titles or column names similar to attribute names in tables. While such omissions are not really an issue for humans, it is truly hard to extract information in autonomous systems in which a machine is expected to understand the meaning of the table presented and extract the right information in the context of the query. It is even more difficult when the information needed is distributed across the globe and involve semantic heterogeneity. In this paper, our goal is to address the issue of how to interpret tables with missing column names by developing a method for the assignment of attributes names in an arbitrary table extracted from the web in a fully autonomous manner. We propose a novel approach by leveraging Wikipedia for the first time for column name discovery for the purpose of table annotation. To improve accuracy of the assignment, we exploit the structural homogeneity of the column values and their co-location to weed out less likely candidates. We show that this leads to an improved likelihood of capturing the context and interpretation of the table accurately and producing a semantically meaningful query response.