Miracle-dz/UniFAR-FTUs huggingface dataset:
Saturation Throughput Analysis of IEEE 802.11b Wireless Local Area Networks under High Interference Considering Capture Effects

Distributed contention based Medium Access Control (MAC) protocols are the fundamental components for IEEE 802.11 based Wireless Local Area Networks (WLANs). Contention windows (CW) change dynamically to adapt to the current contention level, Upon each packet collision, a station doubles its CW to reduce further collision of packets. IEEE 802.11 Distributed Coordination Function (DCF) suffers from a common problem in erroneous channel. They cannot distinguish noise lost packets from collision lost packets. In both situations a station does not receive its ACK and doubles the CW to reduce further packet collisions. This increases backoff overhead unnecessarily in addition to the noise lost packets, reduces the throughput significantly. Furthermore, the aggregate throughput of a practical WLAN strongly depends on the channel conditions. In real radio environment, the received signal power at the access point from a station is subjected to deterministic path loss, shadowing and fast multipath fading. In this paper, we propose a new saturation throughput analysis for IEEE 802.11 DCF considering erroneous channel and capture effects. To alleviate the low performance of IEEE 802.11 DCF, we introduce a mechanism that greatly outperforms under noisy environment with low network traffic and compare their performances to the existing standards. We extend the multidimensional Markov chain model initially proposed by Bianchi(3) to characterize the behavior of DCF in order to account both real channel conditions and capture effects, especially in a high interference radio environment.
A Simple Feature Extraction Technique of a Pattern By HopfieldNetwork

Interest in the area of pattern recognition has been increasing rapidly due to emerging applications, which are not only challenging but also demanding. Feature extraction is a special form of dimensionality reduction in pattern recognition. Our goal is to introduce a simple feature extraction technique for pattern recognition. Pattern recognition is the study of how machines can observe the environment, learn to distinguish patterns of interest from their background and take reasonable decision about the categories of the patterns. During last 50 years of research, attempts have been made by different researchers to develop a general-purpose machine pattern recognizer depending on different algorithms like template matching, statistical approach, artificial neural network etc. In this paper an approach of scale and translation independent feature extraction technique has been presented and analyzed with the help of Hopfield network. This technique is very useful for extraction of feature of shape of an object. It can be applied in the area of image processing, synthetic aperture radar, robotics etc., where detection of shapes of a digitized image or video stream are required.
Incidence of and Factors Influencing Femoral Neck Shortening in Elderly Patients After Fracture Fixation with Multiple Cancellous Screws

Background To study the incidence of and factors influencing “neck shortening” in elderly patients treated for femoral neck fractures using multiple cancellous screws. Material/Methods Of the 197 femoral neck fracture cases treated via closed reduction and cancellous screws fixation from January 2006 to February 2010, 110 were followed up. Patient age, gender, operative time, implantation method, reduction quality, fracture type, bone mineral density, loading time, length of hospital stay, and Harris hip score 12 months after operation were recorded. The patients were divided into two groups (shortening and non-shortening) based on their X-ray performance during follow-up. The healing rates and Harris hip scores of the two groups were compared, and the influencing factors of femoral neck shortening were analyzed. Results Of the 110 cases followed up, 94.5% (104/110) were healed and neck shortening occurred in 41.8% (46/110) within 12.5 months (mean) after treatment. The Harris hip score of the shortening group was lower than that of the non-shortening group (78±17 vs. 86±23, p=0.048). The fracture healing rates of the two groups were not significantly different (p=0.068). The factors influencing neck shortening were significantly correlated with bone mineral density, patient age, gender, and type of fracture. Conclusions The incidence of neck shortening in elderly patients treated for femoral neck fracture using cancellous screws was high. Bone mineral density, patient age, gender, and type of fracture were the influencing factors of neck shortening.
A strategy for enabling forensic investigation in cloud IaaS

Cloud computing is a fast developing technology widely used across industry as well as academia. With the growing popularity of cloud services, the probability of attacks on cloud systems has also gone up drastically. As a result there is a growing demand for enabling cloud systems with forensic capabilities. But, existing digital forensic techniques cannot be directly applied to cloud environments. This paper identifies various challenges involved in adapting existing forensic models to cloud systems. We propose a strategy for performing forensic investigation on cloud taking its inherent features and characteristics into consideration.
DNA Methylation Biomarkers: Cancer and Beyond

Biomarkers are naturally-occurring characteristics by which a particular pathological process or disease can be identified or monitored. They can reflect past environmental exposures, predict disease onset or course, or determine a patient’s response to therapy. Epigenetic changes are such characteristics, with most epigenetic biomarkers discovered to date based on the epigenetic mark of DNA methylation. Many tissue types are suitable for the discovery of DNA methylation biomarkers including cell-based samples such as blood and tumor material and cell-free DNA samples such as plasma. DNA methylation biomarkers with diagnostic, prognostic and predictive power are already in clinical trials or in a clinical setting for cancer. Outside cancer, strong evidence that complex disease originates in early life is opening up exciting new avenues for the detection of DNA methylation biomarkers for adverse early life environment and for estimation of future disease risk. However, there are a number of limitations to overcome before such biomarkers reach the clinic. Nevertheless, DNA methylation biomarkers have great potential to contribute to personalized medicine throughout life. We review the current state of play for DNA methylation biomarkers, discuss the barriers that must be crossed on the way to implementation in a clinical setting, and predict their future use for human disease.
Designing Attention-Centric Notification Systems: Five HCI Challenges

Through an examination of the emerging domain of cognitive systems, with a focus on attention-centric cognitive systems used for notification, this document explores the human-computer interaction challenges that must be addressed for successful interface design. This document asserts that with compatible tools and methods, user notification requirements and interface usability can be abstracted, expressed, and compared with critical parameter ratings; that is, even novice designers can assess attention cost factors to determine target parameter levels for new system development. With a general understanding of the user tasks supported by the notification system, a designer can access the repository of design knowledge for appropriate information and interaction design techniques (e.g., use of color, audio features, animation, screen size, transition of states, etc), which have analytically and empirically derived ratings. Furthermore, usability evaluation methods, provided to designers as part of the integrated system, are adaptable to specific combinations of targeted parameter levels. User testing results can be conveniently added back into the design knowledge repository and compared to target parameter levels to determine design success and build reusable HCI knowledge. This approach is discussed in greater detail as we describe five HCI challenges relating to cognitive system development: (1) convenient access to basic research and guidelines, (2) requirements engineering methods for notification interfaces, (3) better and more usable predictive modeling for pre-attentive and dual-task interfaces, (4) standard empirical evaluation procedures for notification systems, and (5) conceptual frameworks for organizing reusable design and software components. This document also describes our initial work toward building infrastructure to overcome these five challenges, focused on notification system development. We described LINK-UP, a design environment grounded on years of theory and method development within HCI, providing a mechanism to integrate interdisciplinary expertise from the cognitive systems research community. Claims allow convenient access to basic research and guidelines, while modules parallel a lifecycle development iteration and provide a process for requirements engineering guided by this basic research. The activities carried out through LINK-UP provide access to and interaction with reusable design components organized based on our framework. We think that this approach may provide the scientific basis necessary for exciting interdisciplinary advancement through many fields of design, with notification systems serving as an initial model. A version of this document will appear as chapter 3 in the book Cognitive Systems: Human Cognitive Models in Systems Design edited by Chris Forsythe, Michael Bernard, and Timothy Goldsmith resulting from a workshop led by the editors in summer 2003. The authors are grateful for the input of the workshop organizers and conference attendees in the preparation of this document.
PcaK, a high-affinity permease for the aromatic compounds 4-hydroxybenzoate and protocatechuate from Pseudomonas putida

PcaK is a transporter and chemoreceptor protein from Pseudomonas putida that is encoded as part of the beta-ketoadipate pathway regulon for aromatic acid degradation. When expressed in Escherichia coli, PcaK was localized to the membrane and catalyzed the accumulation of two aromatic substrates, 4-hydroxybenzoate and protocatechuate, against a concentration gradient. Benzoate inhibited 4-hydroxybenzoate uptake but was not a substrate for PcaK-catalyzed transport. A P. putida pcaK mutant was defective in its ability to accumulate micromolar amounts of 4-hydroxybenzoate and protocatechuate. The mutant was also impaired in growth on millimolar concentrations of these aromatic acids. In contrast, the pcaK mutant grew at wild-type rates on benzoate. The Vmax for uptake of 4-hydroxybenzoate was at least 25 nmol/min/mg of protein, and the Km was 6 microM. PcaK-mediated transport is energized by the proton motive force. These results show that although aromatic acids in the undissociated (uncharged) form can diffuse across bacterial membranes, high-specificity active transport systems probably also contribute to the ability of bacteria to grow on the micromolar concentrations of these compounds that are typically present in soil. A variety of aromatic molecules, including naturally occurring lignin derivatives and xenobiotics, are metabolized by bacteria and may be substrates for transport proteins. The characterization of PcaK provides a foundation for understanding active transport as a critical step in the metabolism of aromatic carbon sources.
Perceptual speech modeling for noisy speech recognition

This paper proposes a perceptual modeling approach with a two-stage recognition to deal with the issues of recognition degradation in noisy environment. The auditory masking effect is used for speech enhancement and acoustic modeling in order to overcome the model inconsistencies between training speech and noisy input. In the two-stage recognition, the maximum a posteriori (MAP) based adaptation algorithm is used to incrementally adapt the noise model. In order to evaluate our proposed approach, a Mandarin keyword spotting system was constructed. The experimental results show our proposed method achieves a better recognition rate compared to the audible noise suppression (ANS) and parallel model combination (PMC) methods for both in 70km/hr (10.3dB) and 90km/hr (6.4dB) car environments.
Calmodulin-microtubule association in cultured mammalian cells

A Triton X-100-lysed cell system has been used to identify calmodulin on the cytoskeleton of 3T3 and transformed SV3T3 cells. By indirect immunofluorescence, calmodulin was found to be associated with both the cytoplasmic microtubule complex and the centrosomes. A number of cytoplasmic microtubules more resistant to disassembly upon either cold (0-4 degrees C) or hypotonic treatment, as well as following dilution have been identified. Most of the stable microtubules appeared to be associated with the centrosome at one end and with the plasma membrane at the other end. These microtubules could be induced to depolymerize, however, by micromolar Ca++ concentrations. These data suggest that, by interacting directly with the microtubule, calmodulin may influence microtubule assembly and ensure the Ca++-sensitivity of both mitotic and cytoplasmic microtubules.
Estimate DC Characteristics of OPAMP with Neural Networks

Abbreviation of Operational amplifiers is OPAMP. They are available in the form of collected circuit. These amplifiers have a high consistency and if you connect appropriate composition of external elements such as resistance, capacitor, diode to them, you can carry out all the kinds of linear and nonlinear operations. In this article, we try to model OPAMP in a novel method and present it practically. In this way, during the usage there is no need to precise information of the structure. That is, the internal circuit, which is relatively voluminous or bulky, in the device is modeled with a block box. At the end, the used method is compared with the current method in modeling the parts and its advantages are stated.
The association between students' use of an electronic voting system and their learning outcomes

This paper reports on the use of an electronic voting system (EVS) in a first-year computing science subject. Previous investigations suggest that students' use of an EVS would be positively associated with their learning outcomes. However, no research has established this relationship empirically. This study sought to establish whether there was an association between students' use of an EVS over one semester and their performance in the subject's assessment tasks. The results from two stages of analysis are broadly consistent in showing a positive association between EVS usage and learning outcomes for students who are, relative to their class, more correct in their EVS responses. Potential explanations for this finding are discussed as well as modifications and future directions of this program of research.
Neurolinguistic profiles of advanced readers with developmental dyslexia

Dyslexia is a specific learning disability characterized by severe problems with fast and / or accurate reading and / or spelling. Children from parents with dyslexia have a larger risk to develop dyslexia themselves. In this thesis it has been investigated how the reading skills of advanced readers with (a familial risk of) dyslexia can be characterized, predicted and explained. First of all, it has been found that dyslexia is a persistent disorder, that does not resolve in adolescence. When the grade 3 word reading score is known, a good prediction of grade 6 reading level can be made; for this prediction it does not matter whether or not a child has a familial risk. Children who have dyslexia in Dutch also have reading and spelling difficulties in English at secondary school. However, for children with dyslexia reading English words went better than expected based on their Dutch reading scores. Children with a familial risk without reading difficulties in Dutch did not have these difficulties in English either. Deficits in phonological and orthographic awareness, rapid naming and the visual attention span are often observed among children with dyslexia. However, not all children with dyslexia have the same deficits to the same extent. Therefore, there is no dyslexia-specific cognitive profile. In the brain, differences in the fast automatic visual processing of print were found among right-handed students with and without dyslexia. Among 12-year-old children such differences were not found, possibly because their brain is still developing.
P2P streaming: use of advertisements as incentives

Peer-to-Peer (P2P) streaming systems, such as PPLive, have become a popular service with the widespread deployment of broadband networks. However, P2P streaming systems still face free-riding problems, similar to those that have been observed in P2P file sharing systems. Thus, one important problem in providing streaming services is that of providing appropriate incentives for peers to contribute their upload capacity. To this end, we propose the use of advertisements as an incentive for peers to contribute upload capacity. In the proposed framework, peers enjoy the same quality of streamed media, with the difference in quality of service being achieved through different amounts of advertisements viewed, based on the resource contributions to the system. A simulation-based study is performed, which demonstrates that our approach provides appropriate incentives for peers to contribute their resources.
The Bitter Taste Receptor Agonist Quinine Reduces Calorie Intake and Increases the Postprandial Release of Cholecystokinin in Healthy Subjects

Background/Aims Bitter taste receptors are expressed throughout the digestive tract. Data on animals have suggested these receptors are involved in the gut hormone release, but no data are available in humans. Our aim is to assess whether bitter agonists influence food intake and gut hormone release in healthy subjects. Methods Twenty healthy volunteers were enrolled in a double-blind cross-over study. On 2 different days, each subject randomly received an acid-resistant capsule containing either placebo or 18 mg of hydrochloride (HCl) quinine. After 60 minutes, all subjects were allowed to eat an ad libitum meal until satiated. Plasma samples were obtained during the experiment in order to evaluate cholecystokinin (CCK) and ghrelin levels. Each subject was screened to determine phenylthiocarbamide (PTC) tasting status. Results Calorie intake was significantly lower when subjects received HCl quinine than placebo (514 ± 248 vs 596 ± 286 kcal; P = 0.007). Significantly higher CCK ΔT90 vs T0 and ΔT90 vs T60 were found when subjects received HCl quinine than placebo (0.70 ± 0.69 vs 0.10 ± 0.86 ng/mL, P = 0.026; 0.92 ± 0.75 vs 0.50 ± 0.55 ng/mL, P = 0.033, respectively). PTC tasters ingested a significantly lower amount of calories when they received HCl quinine compared to placebo (526 ± 275 vs 659 ± 320 kcal; P = 0.005), whereas no significant differences were found for PTC non-tasters (499 ± 227 vs 519 ± 231 kcal; P = 0.525). Conclusions This study showed that intra-duodenal release of a bitter compound is able to significantly affect calorie intake and CCK release after a standardized meal. Our results suggest that bitter taste receptor signaling may have a crucial role in the control of food intake.
Differentiating Intraday Seasonalities Through Wavelet Multi-Scaling Ramazan Gençay

It is well documented that strong intraday seasonalities may induce distortions in the estimation of volatility models. These periodicities are also the dominant source for the underlying missspecifications of the various volatility models. Therefore, an obvious route is to filter out the underlying intraday seasonalities from the data. In this paper, we propose a simple method for intraday seasonality extraction that is free of model selection parameters which may affect other intraday seasonality filtering methods. Our methodology is based on a wavelet multi-scaling approach which decomposes the data into its low and high frequency components through the application of a non-decimated discrete wavelet transform. It is simple to calculate, does not depend on a particular model selection criterion or model specific parameter choices. The proposed filtering method is translation invariant, has the ability to decompose an arbitrary length series without boundary adjustments, is associated with a zero-phase filter and is circular. Being circular helps to preserve the entire sample unlike other two-sided filters where data loss occurs from the beginning and the end of the studied sample. Corresponding author: Department of Economics, University of Windsor, Windsor, Ontario, N9B 3P4, Canada. Ramazan Gençay gratefully acknowledges financial support from the Natural Sciences and Engineering Research Council of Canada and the Social Sciences and Humanities Research Council of Canada. Department of Economics, Bilkent University, Bilkent 06533, Ankara, Turkey. Eurandom, P.O. Box 513, 5600 MB Eindhoven, The Netherlands.
A Numerical Exploration of the Dynamical Behaviour of q-Deformed Nonlinear Maps

In this paper we explore the dynamical behaviour of the qdeformed versions of widely studied 1D nonlinear map-the Gaussian map and another famous 2D nonlinear map-the Henon map. The Gaussian map is perhaps the only 1D nonlinear map which exhibits the co-existing attractors. In this study we particularly, compare the dynamical behaviour of the Gaussian map and q-deformed Gaussian map with a special attention on the regions of the parameter space, where these maps exhibit co-existing attarctors. We also generalize the q-deformation scheme of 1D nonlinear map to the 2D case and apply it to the widely studied 2D quadratic map-the Henon map which is the simplest nonlinear model exhibiting strange attractor.
Training Structured Prediction Models with Extrinsic Loss Functions

We present an online learning algorithm for training structured prediction models with extrinsic loss functions. This allows us to extend a standard supervised learning objective with additional loss-functions, either based on intrinsic or taskspecific extrinsic measures of quality. We present experiments with sequence models on part-of-speech tagging and named entity recognition tasks, and with syntactic parsers on dependency parsing and machine translation reordering tasks.
The financial impact of student loans

Interest in student loan debt heightened in the early 1990s when the average tuition fees jumped by 10% two years in a row. While the rate of tuition increase subsequently fell back to single digits, between 1989/1990 and 2008/2009 tuition fees more than doubled in constant dollars (Chart A). 1 The rise in tuition fees in most provinces brought increased attention to levels of student borrowing and associated debt loads. One study found that between 1982 and 1995, the proportion of bachelor’s graduates with student loan debt rose from 45% to 47% for men and from 39% to 44% for women. Average loan amounts at graduation for those with a bachelor’s degree also rose during this period by 121% for men and 145% for women (Finnie 2002). The rise in average tuition fees is the result of a substantial shift in the funding of postsecondary education (PSE), a change requiring students to pay proportionally more while governments pay proportionally less (Schwartz and Finnie 2002). Between 1989 and 2009, average tuition fees as a percentage of total revenues for universities and colleges more than doubled, rising from 10% to 21% while funding from government fell from 72% to 55%. 2