Miracle-dz/UniFAR-FTUs huggingface dataset:
IZA DP No . 1527 Aligning Ambition and Incentives

Aligning Ambition and Incentives In many economic situations several principals contract with the same agents sequentially. Asymmetric learning about agents' abilities provides the first principal with an informational advantage and has profound implications for the design of incentive contracts. We show that the principal always strategically distorts information revelation to future principals about the ability of her agents. The second main result is that she can limit her search for optimal incentive schemes to the class of relative performance contracts that cannot be replicated by contracts based on individual performance only. This provides a new rationale for the optimality of such compensation schemes. JEL Classification: D82, J33, L14
Volatile Anesthetics Influence Blood-Brain Barrier Integrity by Modulation of Tight Junction Protein Expression in Traumatic Brain Injury

Disruption of the blood-brain barrier (BBB) results in cerebral edema formation, which is a major cause for high mortality after traumatic brain injury (TBI). As anesthetic care is mandatory in patients suffering from severe TBI it may be important to elucidate the effect of different anesthetics on cerebral edema formation. Tight junction proteins (TJ) such as zonula occludens-1 (ZO-1) and claudin-5 (cl5) play a central role for BBB stability. First, the influence of the volatile anesthetics sevoflurane and isoflurane on in-vitro BBB integrity was investigated by quantification of the electrical resistance (TEER) in murine brain endothelial monolayers and neurovascular co-cultures of the BBB. Secondly brain edema and TJ expression of ZO-1 and cl5 were measured in-vivo after exposure towards volatile anesthetics in native mice and after controlled cortical impact (CCI). In in-vitro endothelial monocultures, both anesthetics significantly reduced TEER within 24 hours after exposure. In BBB co-cultures mimicking the neurovascular unit (NVU) volatile anesthetics had no impact on TEER. In healthy mice, anesthesia did not influence brain water content and TJ expression, while 24 hours after CCI brain water content increased significantly stronger with isoflurane compared to sevoflurane. In line with the brain edema data, ZO-1 expression was significantly higher in sevoflurane compared to isoflurane exposed CCI animals. Immunohistochemical analyses revealed disruption of ZO-1 at the cerebrovascular level, while cl5 was less affected in the pericontusional area. The study demonstrates that anesthetics influence brain edema formation after experimental TBI. This effect may be attributed to modulation of BBB permeability by differential TJ protein expression. Therefore, selection of anesthetics may influence the barrier function and introduce a strong bias in experimental research on pathophysiology of BBB dysfunction. Future research is required to investigate adverse or beneficial effects of volatile anesthetics on patients at risk for cerebral edema.
Kidney Function and Estimated Vascular Risk in Patients with Primary Dyslipidemia

Background: Chronic kidney disease (CKD) is associated with increased vascular risk. Some studies suggested that considering markers of CKD might improve the predictive accuracy of the Framingham risk equation. Aim: To evaluate the links between kidney function and risk stratification in patients with primary dyslipidemia. Methods: Dyslipidemic patients (n = 156; 83 men) who were non-smokers, did not have diabetes mellitus or evident vascular disease and were not on lipid-lowering or antihypertensive agents were recruited. Creatinine clearance (CrCl) was estimated using the Cockcroft-Gault equation. Estimated glomerular filtration rate (eGFR) was calculated using the Modification of Diet in Renal Disease (MDRD) equation. We estimated vascular risk using the Framingham equation. Results: In both men and women, there was a significant negative correlation between estimated Framingham risk and both eGFR and CrCl (p < 0.001 for all correlations). When men were divided according to creatinine tertiles, there were no significant differences in any parameter between groups. When men were divided according to either eGFR or CrCl tertiles, all estimated Framingham risks significantly increased as renal function declined (p<0.001 for all trends). When women were divided according to creatinine tertiles, all estimated Framingham risks except for stroke significantly increased as creatinine levels increased. When women were divided according to either eGFR or CrCl tertiles, all estimated Framingham risks significantly increased as renal function declined. Conclusions: Estimated vascular risk increases as renal function declines. The possibility that incorporating kidney function in the Framingham equation will improve risk stratification requires further evaluation.
A Human-Web Interaction Based Trust Model for Trustworthy Web Software Development

Web software systems provide information and service for end users through the Web interface. The interactive process between the user and the software is the process of software systems to perceive the environment and user, to adjust own configuration and provide appropriate services, monitor and eliminate untrustworthy factors, complete own evolvement and achieve trusted result finally. This paper aims to establishing the online trust evolution model and then building the corresponding trustworthy software framework during the human-Web interactive process. Our research will consider the human and software factors together and combine related methodologies and tools for developing trust model in a user-centric way. Our study can provide theoretical and technical support for developing trustworthy Web software systems.
Improved video-based vehicle detection methodology

Focusing on the problem that the detection accuracy of traffic detection system is sensitive to the changes of complex environments, this paper presents an improved method of vehicle detection. It builds and updates the background adaptively. Additionally, to improve the computation efficiency of shadow elimination, a fast algorithm of neighbor mean based on HSV model is proposed. As the occlusion is inevitable, a new solution is presented to deal with occlusion in this paper. First, a method based on Kalman filter is applied for occlusion identification. And then a search algorithm of template matching based on hierarchical pyramid is utilized for real-time segmentation. Experimental results have shown that the proposed method is effective and high real-time, and it can effectively improve the detection rate of video-based traffic detection system.
Licensed under Creative Commons Attribution Cc by an Efficient Prediction Based Clustering with Crcn

Vehicular Ad Hoc Networks (VANETs) are created by applying the principles of mobile ad hoc networks (MANETs)-the spontaneous creation of a wireless network for data exchange-to the domain of vehicles. Routing protocols are use to communicates between the nodes. After that we introduce the cognitive radio network. Cognitive radio is an intelligent radio that can be programmed and configured dynamically. Its transceiver is designed to use the best wireless channels in its vicinity. Such a radio automatically detects available channels in wireless spectrum, then accordingly changes its transmission or reception parameters to allow more concurrent wireless communications in a given spectrum band at one location. After it we introduce predictive clustering approach. The task of predictive clustering combines elements from both prediction and clustering. Than allocate the Channel for the transmission of message. Communication starts between the nodes. We will use DSR protocol for routing.
Identifying Comparable Corpora Using LDA

Parallel corpora have applications in many areas of Natural Language Processing, but are very expensive to produce. Much information can be gained from comparable texts, and we present an algorithm which, given any bodies of text in multiple languages, uses existing named entity recognition software and topic detection algorithm to generate pairs of comparable texts without requiring a parallel corpus training phase. We evaluate the system's performance firstly on data from the online newspaper domain, and secondly on Wikipedia cross-language links.
Using image sensor PUF as root of trust for birthmarking of perceptual image hash

The perceptual image hash has been widely used for integrity check of digital image content. Existing image hashes fail to identify the origin of image acquisition and non-repudiable authentication is contingent on the privacy of secret key. This paper presents a new and more secure image hashing scheme by exploiting the CMOS image sensor physical unclonable function (PUF) as a root of trust to imprint a birthmark into the image hash. The hash vector is generated directly by the CMOS image sensor based on the content-based features extracted from its captured image and the timestamp of the image without the need for a shared secret key for its authentication. Other than the ability to detect malicious tampering of image content from normal benign image processing operations, the use of CMOS image sensor PUF as a random one-way function to map the extracted feature and the timestamp to a hash vector provides a non-repudiable proof of the original image acquisition device and time of offence when the digital image content is to be presented as an evidence of a crime. As the hash vector can only be generated by the image sensor when it is powered on, it is inherently secure against invasive, data remanence and replay attacks, which are common threats to key-based perceptual image hashes. Our preliminary experimental results on 49 content-preserving and 5 wilfully tampered copies of an original image captured by a 64 × 64 image sensor PUF fabricated in 180 nm 3.3 V CMOS technology have demonstrated that the tampered images and their regions of alteration can be successfully detected from the hash vectors.
Analysis of the optimal trajectory in weightlifting in style "snatch"

The paper presents a comparative analysis of the data obtained from the vertical trajectory of the bar during weightlifting in the snatch mode, these amateur athletes will be compared to an elite athlete in weightlifting, in order to obtain velocities and accelerations for the evaluation of the technique used in each phase. The Lagrange interpolation method was used to obtain a mathematical representation a function of time describing the trajectory of the bar during the uprising in the snatch mode, to thereby obtain the speed and acceleration during the lifting of the bar at every phase.
Enterprise Systems Benefits: How Should They Be Assessed?

This paper proposes key points for the timing and scope of enterprise systems benefit assessment. Enterprise systems (ES) such as enterprise resource planning (ERP) systems support a wide range of enterprise processes influencing organizational management in various areas. Due to the complexity of the system design the learning curve is long, and with constant changes in technology and business needs the functionality and use of these systems are changing continuously throughout their lifetime. Assessing the benefits of enterprise-wide information systems, therefore, requires a longitudinal view on multi-dimensional aspects. The available methods of IS assessment can assist a good understanding of enterprise-wide system benefits of certain parts or for certain periods of time, but cannot address them in holistic and longitudinal terms. This study distinguishes ES from traditional information systems and forms propositions about ES benefit assessment. Through longitudinal case studies of four medium-sized Australian utility companies, this study suggests that the benefits from ES are likely to be realized at different rates for different core processes in each of the five dimensions, i.e. operational, managerial, strategic, IT infrastructure and organizational. It is hoped that the benefit differences between dimensions, different time periods and core processes will clarify conflicting perceptions of ES success, with the finding that the time point of the assessment and the range of ES benefit assessments can strongly affect the evaluation results.
Identification of Roads in Satellite Imagery Using Artificial Neural Networks: A Contextual Approach

Humans can fairly easily identify roads in remote sensing images, but this has turned out to be a difficult task for computers. Most previous work in this area has utilized statistical and rule-based techniques, which depended primarily upon spectral information. However, it appears that spectral information alone is insufficient to identify roads in Landsat Thematic Mapper satellite imagery, since soils have the same spectral signature in the data as roads, and that contextual information is required. In this application, artificial neural networks are found to be superior to several previous techniques due in part to their ability to incorporate both spectral and contextual information. However, a number of factors cause problems for the network, and further work must be done to include additional information; it is suggested that a hybrid system might alleviate most of these difficulties.
An analytical model of rate-adaptive wireless LAN and its simulative verification

We develop an analytical model of rate adaptive Wireless LAN and downlink traffic flows to randomly located users in the range of an access point. We first calculate the service time distribution of packets being served by the access point. Then, we show that the location of each user determines the throughput that all other users may achieve. Finally we verify our findings with simulations.
Automated discovery of product preferences in ubiquitous social media data: A case study of automobile market

Social media enables ubiquitous communication that allows users to disseminate and receive information anywhere and anytime. Among this increasingly vast pool of social media data reside opinionate messages that infer user experience on product usages. Knowledge extracted from such messages could prove to be useful to manufacturers and designers looking to develop next generation products that better meet the needs of the market. Recent developments in machine learning algorithms make it possible to analyze and automatically discover patterns existing within large scale social media networks. Though previous literature has shown that it is possible to extract customers' preferences on smartphones from Twitter data, doubts arise as whether the proposed algorithms could generalize to other product domains. In this paper, we illustrate that the methodology proposed in the previous literature could also be applied on automobile products, whose user-generated content in social media is quite limited, compared to more main stream products such as smartphones.
State of the art in infrared face recognition

Face recognition is an area that has attracted a lot of interest. Much of the research in this field was conducted using visible images. With visible cameras the recognition is prone to errors due to illumination changes. To avoid the problems encountered in the visible spectrum many authors have proposed the use of infrared. In this paper we give an overview of the state of the art in face recognition using infrared images. Emphasis is given to more recent works. A growing field in this area is multimodal fusion; work conducted in this field is also presented in this paper and publicly available Infrared face image databases are introduced.
Survey on Sensor Networks

The special constraints of sensor networks impose a number of technical challenges for employing them. In this survey, we study the issues and existing protocols in three areas: coverage, routing, and robustness. We present two types of coverage problems: to determine the minimum number of sensor nodes that need to perform active sensing in order to monitor a certain area; and to decide the quality of service that can be provided by a given sensor network. While most routing protocols in sensor networks are data-centric, there are other types of routing protocols as well, such as hierarchical, location-based, and QoS-aware. We describe and compare several protocols in each group. Robustness is an important topic in sensor networks since sensor nodes are prone to failure and wireless channels are unreliable. We present several multi-path routing protocols and single-path with local repair routing protocols, which are proposed for recovering from sensor node crashes. We also discuss some transport layer schemes for reliable data transmission in lossy wireless channels.
Outage Probability at Finite SNR by Cemal Akgaba

In this thesis, we present a technique to reduce the outage probability of a single user multiple input multiple output (MIMO) channel when a sub-optimal transceiver architecture is used. We show that in slow-fading scenarios, the outage probability can be improved by using unitary rotations combined with coding. We provide analysis and simulations supporting our approach. Thesis Supervisor: Lizhong Zheng Title: Assistant Professor
Activation of coherent lattice phonon following ultrafast molecular spin-state photo-switching: A molecule-to-lattice energy transfer

We combine ultrafast optical spectroscopy with femtosecond X-ray absorption to study the photo-switching dynamics of the [Fe(PM-AzA)2(NCS)2] spin-crossover molecular solid. The light-induced excited spin-state trapping process switches the molecules from low spin to high spin (HS) states on the sub-picosecond timescale. The change of the electronic state (<50 fs) induces a structural reorganization of the molecule within 160 fs. This transformation is accompanied by coherent molecular vibrations in the HS potential and especially a rapidly damped Fe-ligand breathing mode. The time-resolved studies evidence a delayed activation of coherent optical phonons of the lattice surrounding the photoexcited molecules.
Evolution with State-Dependent Mutations

Recent evolutionary models have introduced "small mutation rates" as a way of refining predictions of long-run behavior. We show that this refinement effect can only be obtained by restrictions on how the magnitude of the effect of mutation on evolution varies across states of the system. In particular, given any model of the effect of mutations, any invariant distribution of the "mutationless" process is close to an invariant distribution of the process with appropriately chosen small mutation rates.
Cell Recovery in Bronchoalveolar Lavage Fluid in Smokers Is Dependent on Cumulative Smoking History

Background Smoking is a risk factor for various lung diseases in which BAL may be used as a part of a clinical investigation. Interpretation of BAL fluid cellularity is however difficult due to high variability, in particular among smokers. In this study we aimed to evaluate the effect of smoking on BAL cellular components in asymptomatic smokers. The effects of smoking cessation, age and gender were also investigated in groups of smokers and exsmokers. Methods We performed a retrospective review of BAL findings, to our knowledge the largest single center investigation, in our department from 1999 to 2009. One hundred thirty two current smokers (48 males and 84 females) and 44 ex-smokers (16 males and 28 females) were included. A group of 295 (132 males and 163 females) never-smokers served as reference. Result The median [5–95 pctl] total number of cells and cell concentration in current smokers were 63.4 [28.6–132.1]×106 and 382.1 [189.7–864.3]×106/L respectively and correlated positively to the cumulative smoking history. Macrophages were the predominant cell type (96.7% [90.4–99.0]) followed by lymphocytes (2% [0.8–7.7]) and neutrophils (0.6% [0–2.9]). The concentration of all inflammatory cells was increased in smokers compared to never smokers and ex-smokers. BAL fluid recovery was negatively correlated with age (p<0.001). Smoking men had a lower BAL fluid recovery than smoking women. Conclusion Smoking has a profound effect on BAL fluid cellularity, which is dependent on smoking history. Our results performed on a large group of current smokers and ex-smokers in a well standardized way, can contribute to better interpretation of BAL fluid cellularity in clinical context.
Smart meter security : a survey

Europe’s smart metering initiative may be the largest engineering project ever undertaken in the region; it is significantly larger than the Channel Tunnel. The European Parliament mandated the replacement of electricity meters with new ‘smart’ meters by 2022, except in Member States who certify this year that it would be uneconomic. This project could cost over $100 billion, and will involve non-trivial engineering challenges, a number of which touch on security and privacy issues. In fact, it is a fascinating case study in security economics: systems are much harder to protect when incentives conflict, and smart metering exposes perverse incentives galore. Nonpayment is a major concern for the utilities, whose main goal is to move defaulting customers to prepayment remotely, rather than having to roll a truck. But prior experience from countries with widespread prepayment metering suggests that it may increase technical fraud. Second, fine-grained energy consumption data reveal a lot of information about house occupants’ behaviour, leading to serious privacy concerns. Third, the industry is worried that over-regulation could significantly increase the cost of the project, following negative experiences of regulatory mechanisms in smart grid projects to modernise transmission and distribution networks. Fourth, there is growing concern that centrally controllable electricity meters could be vulnerable to attack by a state-level or substate adversary. Fifth, there are serious conflicts of interest between the energy retailers who will operate the meters in most countries, the customers, and governments, which may undermine the goals of the project and which may be made worse by myopic architectural choices. Finally, the lack of a viable framework for communication between smart meters and appliances in the home will not merely lead to lack of interoperability, but could thwart competition and is likely to frustrate one of the main project goals: that future smart grids can provide demand response by tailoring the demand for energy rapidly to supply fluctuations. Without demand response, much less of our energy can come from fluctuating sources such as wind and solar. If we want to maximise the use of renewables, we will need a more incentive-compatible system architecture, and we discuss some possible first steps.
On the Iterative Solution of the Matrix Equation AX 2-1 = 0

It is clear that C is symmetric. However, in order to avoid the solution of two special eigenvalue problems, it is desirable to have a way of forming the transforming matrix A~* in terms of the known matrix A without a previous determination of the eigenvalues and eigenvectors of A. Indeed, this is possible by an iterative process, based on Newton's algorithm, for any matrix A with real positive eigenvalues. Newton's method. Two simple algorithms can be presented for the iterative solution of the scalar equation ax2 1 = 0 with a positive a ; these are