Miracle-dz/UniFAR-FTUs huggingface dataset:
Current effects on scattering of surface gravity waves by bottom topography

The scattering of random surface gravity waves by topography of small amplitude, and horizontal scales of the order of the wavelength, is investigated theoretically in the presence of a an almost uniform irrotational current. This problem is relevant to ocean waves propagation on shallow continental shelves where tidal currents are often significant. Defining the small scale bottom amplitude normalized by the mean water depth, � = h/H, a perturbation expansion of the wave action to order � 2 yields an evolution equation for the wave action spectrum. Based on numerical calculations for sinusoidal bars, a mixed surface-bottom bispectrum, that arises at order �, is unlikely to be significant in most oceanic conditions. Neglecting that term, the present theory yields a closed equation with a scattering source term that gives the rate of exchange of action between spectral wave components that have the same absolute frequency. This source term is proportional to the bottom elevation variance at the resonant wavenumbers, and thus represents a Bragg scattering approximation. With current, the source term formally combines a direct effect of the bottom topography with an indirect effect of the bottom through the modulation of the surface current and mean surface elevation. For Froude numbers of the order of 0.6 or less, the bottom topography effects dominate. For all Froude numbers, the reflection coefficients for the wave amplitudes that are inferred @�
Assisted network discovery for next generation wireless networks

IEEE 802.11 networks are the most popular option to have wireless access to the Internet. The popularity of these networks have raised a costly topology discovery and connection process, in which any device has to pass through an expensive scanning process of available Access Points. In order to improve the connection process, we propose a novel architecture for asynchronous assistance for topology discovery. We discuss the role of a Topology Manager that uses computational intelligence for generating optimal scanning sequences. Preliminary results show that this approach results in 30% to 70% improvements on AP discovery rate in chaotic deployments.
Fatty acid, protein and energy gain of broilers fed different dietary vegetable oils

The objective of this study was to assess energy, nitrogen, fat and fatty acid deposition in broilers fed diets containing different vegetable oil sources. Forty female broiler chickens were fed five diets, with different fats [coconut, palm, olive, soybean (SO) and linseed oil (LO)] at 10% from 30 to 50 days of age. The animals consuming the LO diet presented the lowest body fat content. There were no differences among treatments regarding nitrogen balance. The greater percentage of apparent metabolizable energy was obtained with the LO diet. All animals deposited more saturated and monounsaturated fatty acids than digested, however the amount of polyunsaturated fatty acids deposited in the SO and LO treatments was lower than the amount digested. These results indicate that chickens that consumed the highly polyunsaturated diets deposited less fat due to a lower gain of polyunsaturated fatty acids. Additional key words: chicken, energy balance, fatty acids, polyunsaturated fatty acids.
CD26/dipeptidylpeptidase IV—chemokine interactions: double‐edged regulation of inflammation and tumor biology

Post‐translational modification of chemokines is an essential regulatory mechanism to enhance or dampen the inflammatory response. CD26/dipeptidylpeptidase IV, ubiquitously expressed in tissues and blood, removes NH2‐terminal dipeptides from proteins with a penultimate Pro or Ala. A large number of human chemokines, including CXCL2, CXCL6, CXCL9, CXCL10, CXCL11, CXCL12, CCL3L1, CCL4, CCL5, CCL11, CCL14, and CCL22, are cleaved by CD26; however, the efficiency is clearly influenced by the amino acids surrounding the cleavage site and although not yet proven, potentially affected by the chemokine concentration and interactions with third molecules. NH2‐terminal cleavage of chemokines by CD26 has prominent effects on their receptor binding, signaling, and hence, in vitro and in vivo biologic activities. However, rather than having a similar result, the outcome of NH2‐terminal truncation is highly diverse. Either no difference in activity or drastic alterations in receptor recognition/specificity and hence, chemotactic activity are observed. Analogously, chemokine‐dependent inhibition of HIV infection is enhanced (for CCL3L1 and CCL5) or decreased (for CXCL12) by CD26 cleavage. The occurrence of CD26‐processed chemokine isoforms in plasma underscores the importance of the in vitro‐observed CD26 cleavages. Through modulation of chemokine activity, CD26 regulates leukocyte/tumor cell migration and progenitor cell release from the bone marrow, as shown by use of mice treated with CD26 inhibitors or CD26 knockout mice. As chemokine processing by CD26 has a significant impact on physiologic and pathologic processes, application of CD26 inhibitors to affect chemokine function is currently explored, e.g., as add‐on therapy in viral infection and cancer.
Profiles of College Drinkers Defined by Alcohol Behaviors at the Week Level: Replication Across Semesters and Prospective Associations With Hazardous Drinking and Dependence-Related Symptoms.

OBJECTIVE Types of college drinkers have been identified using traditional measures (e.g., 12-month drinking frequency). We used an alternative multidimensional approach based on daily reports of alcohol behaviors to identify college drinker statuses, each with a unique behavioral profile. The current study aimed to (a) identify drinker statuses at the week level across four semesters, (b) examine the predictive utility of drinker status by testing associations with senior-year hazardous drinking and dependence symptoms, and (c) identify concurrent predictors (gender, drinking motivations, hazardous drinking, any dependence symptoms) of senior-year drinker status. We also compared the week-level drinker statuses with drinker statuses identified using traditional measures. METHOD A multi-ethnic sample of U.S. college students completed 14-day bursts of daily web surveys across college (91%-96% completed ≥6 daily reports of the sampled week). Analyses focus on nine alcohol-related behaviors (including estimated blood alcohol concentration, pregaming, and drinking games) assessed daily in spring/sophomore year to fall/senior year and drinking motivations, hazardous drinking, and dependence symptoms assessed fall/senior year (n = 569; 56% women). RESULTS Four week-level drinker statuses were replicated across semesters: Nondrinker, Light Weekend, Heavy Weekend, and Heavy Frequent. Across semesters, drinker status was associated with senior-year hazardous drinking and any dependence symptoms. Senior-year fun/social motivations were also associated with senior-year drinker status. Differences in behavioral profiles between week-level drinker statuses and those identified using traditional measures were found. CONCLUSIONS Replicable week-level drinker statuses were identified, suggesting consistency in possible types of drinking weeks. Drinker statuses were predictive of senior-year hazardous drinking and dependence symptoms.
Delay-Tolerant Broadcasting

There are many asynchronous communication situations for which the prevalent continuous connectivity paradigm is not needed. Communication with a fair delay tolerance may instead be provided by intermittent store-and-forwarding between nodes. This paper proposes a design for an open, receiver-driven broadcasting system that relies on delay-tolerant forwarding of data chunks through mobility of wireless nodes. The system provides public broadcast channels, which may be openly used for both transmission and reception. We show by analysis and simulation under benchmark mobility models that a delay-tolerant broadcast channel has both a sufficiently high throughput and reach to be interesting as a competitive alternative to the regulated wireless broadcast channel. The analysis is based on a queuing model to study the interactions among the mobile nodes in a street. The simulations complement this analysis for mobile nodes moving on a square according to benchmark mobility models. Finally, we present the design of, and experiences with, a proof-of-concept prototype
ARABIDOPSIS TRITHORAX1 Dynamically Regulates FLOWERING LOCUS C Activation via Histone 3 Lysine 4 Trimethylation[W]

Trithorax function is essential for epigenetic maintenance of gene expression in animals, but little is known about trithorax homologs in plants. ARABIDOPSIS TRITHORAX1 (ATX1) was shown to be required for the expression of homeotic genes involved in flower organogenesis. Here, we report a novel function of ATX1, namely, the epigenetic regulation of the floral repressor FLOWERING LOCUS C (FLC). Downregulation of FLC accelerates the transition from vegetative to reproductive development in Arabidopsis thaliana. In the atx1 mutant, FLC levels are reduced and the FLC chromatin is depleted of trimethylated, but not dimethylated, histone 3 lysine 4, suggesting a specific trimethylation function of ATX1. In addition, we found that ATX1 directly binds the active FLC locus before flowering and that this interaction is released upon the transition to flowering. This dynamic process stands in contrast with the stable maintenance of homeotic gene expression mediated by trithorax group proteins in animals but resembles the dynamics of plant Polycomb group function.
p-Cresyl sulphate and indoxyl sulphate predict progression of chronic kidney disease

Background. Indoxyl sulphate (IS) and p-cresyl sulphate (PCS) are uraemic toxins that have similar protein binding, dialytic clearance and proinflammatory features. However, only a few prospective studies have evaluated possible associations between these two retained solutes and renal disease progression in chronic kidney disease (CKD) patients. Methods. This prospective observational study evaluated independent associations between serum total IS and PCS with renal progression in a selected cohort of patients having different stages of CKD. Baseline PCS and IS were correlated with renal progression [defined as decrements in estimated glomerular filtration rate (eGFR) > 50% from baseline or progression to end-stage renal disease (ESRD)] and death during a follow-up period of 24 months. Results. Of 268 patients, 35 (13.1%) had renal progression and 14 (5.2%) died after a mean follow-up of 21 ± 3 months. Univariate Cox regression analysis followed by multivariate analysis showed that high-serum PCS levels were associated with renal progression and all-cause mortality independent of age, gender, diabetes status, albumin levels, serum IS, serum creatinine, Ca × P product, intact parathyroid hormone, haemoglobin or high-sensitivity C-reactive protein level. Serum IS was only associated with renal progression; however, the predictive power of serum IS was weakened when serum PCS was also present in the analytical model. Conclusions. In addition to traditional and uraemia-related risk factors such as renal function, serum IS and PCS levels may help in predicting the risk of renal progression in patients having different stages of CKD.
Possible extrathymic development of nonfunctional T cells in a patient with complete DiGeorge syndrome.

Complete DiGeorge syndrome is characterized by the clinical triad of cardiac malformation, hypocalcemia, and T cell immunodeficiency due to congenital athymia. We describe an infant with complete DiGeorge syndrome who at presentation had no circulating T cells detectable by flow cytometry. The patient spontaneously developed circulating T cells but these cells did not proliferate in response to mitogens. The T cell receptor Vbeta repertoire was severely restricted. All T cells were host, not maternal, as assessed by fluorescent in situ hybridization evaluation of 22q11 hemizygosity. At autopsy, this patient had no grossly detectable thymus tissue and no microscopic evidence for thymopoiesis. These findings suggest that appearance of T cells in infants with complete DiGeorge syndrome may represent oligoclonal expansions of a small number of T cells that may have matured extrathymically and which do not respond in vitro to mitogen stimulation.
Intelligent Traffic System: Cooperation of MANET and Image Processing

In this paper is presented a new model for intelligent traffic systems, which is able to integrate a typical surveillance scenario and topology independent immediate data delivery. Surveillance part is based on image analysis, namely general foreground/background modeling scheme. Data delivery system ensures data transmission over mobile Ad-hoc network, by providing communication framework for this purpose. Experiments show all the potentialities of proposed approaches, in areas of real time execution and effectiveness.
Improving Performance of Mobile Interactive Data-Streaming Applications with Multiple Cloudlets

Improving performance of a mobile application by offloading its computation onto a cloudlet has become a prevalent paradigm. Among mobile applications, the category of interactive data-streaming applications is emerging while having not yet received sufficient attention. During computation offloading, the performance of this category of applications (including response time and throughput) depends on network latency and bandwidth between the mobile device and the cloudlet. Although a single cloudlet can provide satisfactory network latency, the bandwidth is always the bottleneck of the throughput. To address this issue, we propose to use multiple cloudlets for computation offloading so as to alleviate the bandwidth bottleneck. In addition, we propose to use multiple module instances to complete a module, enabling more fine-grained computation partitioning, since data processing in many modules of data-streaming applications could be highly parallelized. Specifically, at first we apply a fine-grained data-flow model to characterize mobile interactive data-streaming applications. Then we build a unified optimization framework that achieves maximization of the overall utilities of all mobile users, and design an efficient heuristic for the optimization problem, which is able to make trade-off between throughput and energy consumption at each mobile device. At the end we verify our algorithm with extensive simulation. The results show that the overall utility achieved by our heuristic is close to the precise optimum, and our multiple-cloudlet mechanism significantly outperforms the single-cloudlet mechanism.
A Novel Classification System to Address Financial Impact and Referral Decisions for Bile Duct Injury in Laparoscopic Cholecystectomy

Purpose. The study was undertaken to evaluate a novel classification system developed to estimate financial cost of bile duct injury (BDI) and to aid in decision making for referral. Study Design. A retrospective review of patients referred for BDI was performed. Grade I injuries involve the duct of Luschka or accessory right hepatic ducts, grade II includes all other biliary injuries, and grade III includes all vasculobiliary injuries. Groups were compared using standard statistical methods. Results. There were 14 grade I, 74 grade II, and 20 grade III injuries. There was a significant difference in the cost and mortality of grade I ($12,457, 0%), grade II ($46,481, 1.4%), and grade III ($69,368, 15%, P = 0.002 and P = 0.030, resp.) injuries. Grade II and III injuries were significantly more likely to require surgical repair (OR 27.7, P < 0.001). Conclusion. We have presented a simple classification system that is able to accurately predict cost and need for surgical repair.
Coordinated path following control of multiple wheeled mobile robots through decentralized speed adaptation

This paper addresses the problem of coordinated path following of multiple wheeled mobile robots while keeping a desired formation. The control laws proposed are categorized into two envelopes, one is steering individual robots to trace along predefined paths, and the other is ensuring tracked paths to be well defined in the formation, by means of decentralized speed adaption.Within this framework, geometric paths following are built on Lyapunov theory and backstepping techniques, while injecting helmsman like behavior into individual path following control. Speed adaption with minimum communication variable under the constraints of multi-robot communication topology, is elaborately designed without relative speeds between neighboring robots requested. The simple but effective controller design, enables multi-robot system to be coordinated and stabilized into an invariant manifold, and all speeds converge to desired profiles in addition. Simulation results illustrate the efficacy of the solution proposed.
Assessing and generating test sets in terms of behavioural adequacy

Identifying a finite test set that adequately captures the essential behaviour of a program such that all faults are identified is a well‐established problem. This is traditionally addressed with syntactic adequacy metrics (e.g. branch coverage), but these can be impractical and may be misleading even if they are satisfied. One intuitive notion of adequacy, which has been discussed in theoretical terms over the past three decades, is the idea of behavioural coverage: If it is possible to infer an accurate model of a system from its test executions, then the test set can be deemed to be adequate. Despite its intuitive basis, it has remained almost entirely in the theoretical domain because inferred models have been expected to be exact (generally an infeasible task) and have not allowed for any pragmatic interim measures of adequacy to guide test set generation. This paper presents a practical approach to incorporate behavioural coverage. Our BESTEST approach (1) enables the use of machine learning algorithms to augment standard syntactic testing approaches and (2) shows how search‐based testing techniques can be applied to generate test sets with respect to this criterion. An empirical study on a selection of Java units demonstrates that test sets with higher behavioural coverage significantly outperform current baseline test criteria in terms of detected faults. © 2015 The Authors. Software Testing, Verification and Reliability published by John Wiley & Sons, Ltd.
Towards a formal model for the network alarm correlation problem

In telecommunication networks, alarms are usually useful for identifying faults, and therefore solving them. However, for large systems the number of alarms produced is so large that the current management systems are overloaded. One way of overcoming this problem is to filter and reduce the number of alarms before the faults can be located. In this paper, we describe a new approach for fault recognition and classification in large telecommunication networks. We introduce a new model and present another way of understanding the alarm correlation problem.
Measurement with Minimal Theory

A central debate in applied macroeconomics is whether statistical tools that use minimal identifying assumptions are useful for isolating promising models within a broad class. In this paper, I extend the analysis of Chari, Kehoe, and McGrattan (2005) to compare four statistical methods---structural VARs, VARMAs, unrestricted state space methods, and restricted state space methods---all applied to data from the same business cycle model. The objective is to determine which, if any, of the methods can successfully uncover moments of the underlying economy. The methods differ in the amount of a priori theory that is imposed, with structural VARs imposing minimal assumptions and restricted state space methods imposing the maximal. The moments that I focus on are those typically reported in the business cycle literature. Preliminary results show that the identifying assumptions of structural VARs, VARMAs, and unrestricted state space methods are too minimal: they cannot robustly uncover many of the moments business cycle researchers are interested in measuring.
Improved audio event detection by use of contextual noise

This paper presents new approaches to improve the detection of two key audio events in a sport game (tennis) using contextual information. When analysing a tennis match using only audio information, the sound of the ball being struck and the occurrence of a line judge's shout can be obscured by players' grunts or shouts. Furthermore, if models of these two important events are trained from labelled training-data, there is often considerable audio mis-match with the test-data, which means that detection performance can be very poor. To handle this problem, we regard the players' grunts as useful contextual information that indicates the position of the events of interest. We show how to use an unsupervised learning method to build an improved model of the ball-hit event using grunt information. We can then use high-level information to distinguish grunts from line-judge shouts. This approach gives simultaneous improvements in detection of both ball-hits and line judge shouts, and is portable between different matches, unlike approaches based on the use of manually labelled training-data.
Be a computer scientist for a week the McGill “game programming guru” Summer Camp

Motivating high school students to consider Computer Science as their future field of study at the university level is a challenging endeavor. This paper describes the McGill computer science summer camp targeted at high school students from grade 10 to 11 (ages 15 to 17). We first motivate our choice of using computer games as the main camp theme, and then present the teaching methodology used throughout the camp. A day-by-day breakdown of the camp is provided, as to better illustrate the distribution of the material throughout the week and the evaluation methods used to track the progress of the students. We also present the game environment we developed in which the students exercise their problem solving skills during the lab sessions. We conclude by illustrating the positive effect of the camp, using a combination of code analysis and evaluation questionnaire filled out by the students and their parents.
Prediction of Atomic Web Services Reliability for QoS-Aware Recommendation

While constructing QoS-aware composite work-flows based on service oriented systems, it is necessary to assess nonfunctional properties of potential service selection candidates. In this paper, we present CLUS, a model for reliability prediction of atomic web services that estimates the reliability for an ongoing service invocation based on the data assembled from previous invocations. With the aim to improve the accuracy of the current state-of-the-art prediction models, we incorporate user-service-, and environment-specific parameters of the invocation context. To reduce the scalability issues present in the state-of-the-art approaches, we aggregate the past invocation data using K-means clustering algorithm. In order to evaluate different quality aspects of our model, we conducted experiments on services deployed in different regions of the Amazon cloud. The evaluation results confirm that our model produces more scalable and accurate predictions when compared to the current state-of-the-art approaches.