Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic isolation in an endemic African habitat specialist

The Chestnut‐banded Plover Charadrius pallidus is a Near‐Threatened shorebird species endemic to mainland Africa. We examined levels of genetic differentiation between its two morphologically and geographically distinct subspecies, C. p. pallidus in southern Africa (population size 11 000–16 000) and C. p. venustus in eastern Africa (population size 6500). In contrast to other plover species that maintain genetic connectivity over thousands of kilometres across continental Africa, we found profound genetic differences between remote sampling sites. Phylogenetic network analysis based on four nuclear and two mitochondrial gene regions, and population genetic structure analyses based on 11 microsatellite loci, indicated strong genetic divergence, with 2.36% mitochondrial sequence divergence between individuals sampled in Namibia (southern Africa) and those of Kenya and Tanzania (eastern Africa). This distinction between southern and eastern African populations was also supported by highly distinct genetic clusters based on microsatellite markers (global FST = 0.309, GST′ = 0.510, D = 0.182). Behavioural factors that may promote genetic differentiation in this species include habitat specialization, monogamous mating behaviour and sedentariness. Reliance on an extremely small number of saline lakes for breeding and limited dispersal between populations are likely to promote reproductive and genetic isolation between eastern and southern Africa. We suggest that the two Chestnut‐banded Plover subspecies may warrant elevation to full species status. To assess this distinction fully, additional sample collection will be needed, with analysis of genetic and phenotypic traits from across the species’ entire breeding range.
Capecitabine plus oxaliplatin (XELOX) versus 5-fluorouracil/folinic acid plus oxaliplatin (FOLFOX-4) as second-line therapy in metastatic colorectal cancer: a randomized phase III noninferiority study.

BACKGROUND To demonstrate the noninferiority of capecitabine plus oxaliplatin (XELOX) versus 5-fluorouracil/folinic acid and oxaliplatin (FOLFOX-4) as second-line therapy in patients with metastatic colorectal cancer after prior irinotecan-based chemotherapy. PATIENTS AND METHODS A total of 627 patients were randomly assigned to receive XELOX (n = 313) or FOLFOX-4 (n = 314) following disease progression/recurrence or intolerance to irinotecan-based chemotherapy. The primary end point was progression-free survival (PFS). RESULTS PFS for XELOX was noninferior to FOLFOX-4 [hazard ratio (HR) = 0.97; 95% confidence interval (CI) 0.83-1.14] in the intention-to-treat (ITT) population. Median PFS was 4.7 months with XELOX versus 4.8 months with FOLFOX-4. The robustness of the primary analysis was supported by multivariate and subgroup analyses. Median overall survival in the ITT population was 11.9 months with XELOX versus 12.5 months with FOLFOX-4 (HR = 1.02; 95% CI 0.86-1.21). Treatment-related grade 3/4 adverse events occurred in 50% of XELOX- and 65% of FOLFOX-4-treated patients. Whereas grade 3/4 neutropenia (35% versus 5% with XELOX) and febrile neutropenia (4% versus < 1%) were more common with FOLFOX-4, grade 3/4 diarrhea (19% versus 5% with FOLFOX-4) and grade 3 hand-foot syndrome (4% versus < 1%) were more common with XELOX. CONCLUSION XELOX is noninferior to FOLFOX-4 when administered as second-line treatment in patients with metastatic colorectal cancer.
Introducing progress testing in McMaster University's problem‐based medical curriculum: psychometric properties and effect on learning

BACKGROUND: The progress test (or Quarterly Profile Examination), invented concurrently by the University of Missouri-Kansas City School of Medicine and the University of Limburg, is used to provide useful summative and formative judgments about students' knowledge without distorting learning. All students in all classes sit the same examination at regular intervals through the year, and their individual progress is noted. This paper reports on four years' experience with a progress test, the Personal Progress Index (PPI), at the McMaster University Faculty of Health Sciences. METHOD: The PPI, a 180-item multiple-choice test with items drawn from all disciplines of medicine, is administered to medical students in all three classes three times per year. Individual feedback is provided, and accumulated student performance is determined for summative purposes. This paper examines extensive evidence of reliability, validity, and effect on student learning, using samples from the entering classes of 1992-1995 (a total of 400 students). RESULTS: Reliabilities across test administrations (within classes) ranged from . 46 to . 63. The PPI demonstrated strong construct validity, with highly significant statistical tests of differences between classes and changes within classes on successive administrations. The predictive validity of the PPI, i.e., whether it could predict performance on the licensing examination of the Medical Council of Canada, increased monotonically from a correlation of . 12 for the first test administration one month into medical school to a high of about . 60 for the cumulative score across all administrations three months prior to the examination. CONCLUSION: The PPI seems to be performing as intended, with students showing growth in performance across the three years of the MD program. Additional benefits are that many more students now self-refer for remediation (based on low PPI scores) and that the consistent relative performances of individual students across test administrations allow for the identification of students who have severe and persistent problems.
Evaluating Site-Specific and Generic Spatial Models of Aboveground Forest Biomass Based on Landsat Time-Series and LiDAR Strip Samples in the Eastern USA

Large-area assessment of aboveground tree biomass (AGB) to inform regional or national forest monitoring programs can be efficiently carried out by combining remotely sensed data and field sample measurements through a generic statistical model, in contrast to site-specific models. We integrated forest inventory plot data with spatial predictors from Landsat time-series imagery and LiDAR strip samples at four sites across the eastern USA—Minnesota (MN), Maine (ME), Pennsylvania-New Jersey (PANJ) and South Carolina (SC)—in statistical modeling frameworks to analyze the performance of generic (all sites combined) versus site-specific models. The major objective was to evaluate the prediction accuracy of generic and site-specific models when applied to particular sites. Pixel-level polynomial model fitting was applied to the time-series of near-anniversary date Landsat variables to obtain projected metrics in the target year 2014 for which LiDAR strip samples were available. Two forms of models based on ordinary least-squares multiple linear regressions (MLR) and the random forest (RF) machine learning approach were developed for each site and for the pooled (i.e., generic) reference data frame. The models were evaluated using national forest inventory (NFI) data for the USA. We observed stronger fit statistics with the MLR than with RF for both the site-specific and the generic models. The proportions of variances explained (adjusted R2) with the site-specific models were 0.86, 0.78, 0.82 and 0.92 for ME, MN, PANJ and SC, respectively while the generic model had adjusted R2 = 0.85. A test of statistical equivalence of observed and predicted AGB for the NFI locations did not reveal equivalence with any of the models, possibly due to the different resolutions of the observed and predicted data. In contrast, predictions by the generic and site-specific models were equivalent. We conclude that a generic model provides accuracies comparable to the site-specific models for large-area AGB assessment across our study sites in the eastern USA.
Risk-based intrusion response management in IDS using Bayesian decision networks

Nowadays, from information security perspective, detection methods are not enough solely. Intrusion Detection and Response Systems (IDRS), as a proactive solution, continuously monitor system health based on Intrusion Detection System (IDS) alerts, so that malicious activities can be handled effectively by applying appropriate countermeasures to prevent problems from worsening and return the system to a healthy state. In this paper, a novel IDRS is proposed which processes the generated alerts in real time, correlates the alerts, calculates the risk of correlated alerts and models the attack scenarios and their countermeasures using the concept of Bayesian decision networks (BDNs). The proposed framework has two modes: online and offline. In the offline mode, a BDN model is constructed. Then, in the online mode, using the generated BDN, the next probable intentions of attackers are predicted and the optimal sets of countermeasures are identified to prevent the attackers reaching their goals. The experimental results show that the proposed method effectively improves the security level of computer systems in terms of forecasting the multi-step attacks before they can compromise the network and determining the optimal security risk mitigation plans to prevent damages to the organizations assets.
Reinforcement learning for games: failures and successes

We apply CMA-ES, an evolution strategy with covariance matrix adaptation, and TDL (Temporal Difference Learning) to reinforcement learning tasks. In both cases these algorithms seek to optimize a neural network which provides the policy for playing a simple game (TicTacToe). Our contribution is to study the effect of varying learning conditions on learning speed and quality. Certain initial failures with wrong fitness functions lead to the development of new fitness functions, which allow fast learning. These new fitness functions in combination with CMA-ES reduce the number of required games needed for training to the same order of magnitude as TDL. The selection of suitable features is also of critical importance for the learning success. It could be shown that using the raw board position as an input feature is not very effective -- and it is orders of magnitudes slower than different feature sets which exploit the symmetry of the game. We develop a measure "feature set utility", FU, which allows to characterize a given feature set in advance. We show that the lower bound provided by FU is largely in accordance with the results from our repeated experiments for very different learning algorithms, CMA-ES and TDL.
The Prevalence of Descriptive Referring Expressions in News and Narrative

Generating referring expressions is a key step in Natural Language Generation. Researchers have focused almost exclusively on generating distinctive referring expressions, that is, referring expressions that uniquely identify their intended referent. While undoubtedly one of their most important functions, referring expressions can be more than distinctive. In particular, descriptive referring expressions -- those that provide additional information not required for distinction -- are critical to fluent, efficient, well-written text. We present a corpus analysis in which approximately one-fifth of 7,207 referring expressions in 24,422 words of news and narrative are descriptive. These data show that if we are ever to fully master natural language generation, especially for the genres of news and narrative, researchers will need to devote more attention to understanding how to generate descriptive, and not just distinctive, referring expressions.
The Volatility Research Based on the Except of Share Merger Reform

Based on the foreign research model, the expression of equilibrium price based on the expected full circulation is obtained in the text with consideration of the actual factors of the bond markets in China, and a volatility model is set up through the analysis of factors of equilibrium price as well. The study indicates that enterprises with less equity scale will encounter higher volatility, and the share merger reform will help to decrease the market volatility.
Genetic Diversity of the 2009 Pandemic Influenza A(H1N1) Viruses in Finland

Background In Finland, the first infections caused by the 2009 pandemic influenza A(H1N1) virus were identified on May 10. During the next three months almost all infections were found from patients who had recently traveled abroad. In September 2009 the pandemic virus started to spread in the general population, leading to localized outbreaks and peak epidemic activity was reached during weeks 43–48. Methods/Results The nucleotide sequences of the hemagglutinin (HA) and neuraminidase (NA) genes from viruses collected from 138 patients were determined. The analyzed viruses represented mild and severe infections and different geographic regions and time periods. Based on HA and NA gene sequences, the Finnish pandemic viruses clustered in four groups. Finnish epidemic viruses and A/California/07/2009 vaccine virus strain varied from 2–8 and 0–5 amino acids in HA and NA molecules, respectively, giving a respective maximal evolution speed of 1.4% and 1.1%. Most amino acid changes in HA and NA molecules accumulated on the surface of the molecule and were partly located in antigenic sites. Three severe infections were detected with a mutation at HA residue 222, in two viruses with a change D222G, and in one virus D222Y. Also viruses with change D222E were identified. All Finnish pandemic viruses were sensitive to oseltamivir having the amino acid histidine at residue 275 of the neuraminidase molecule. Conclusions The Finnish pandemic viruses were quite closely related to A/California/07/2009 vaccine virus. Neither in the HA nor in the NA were changes identified that may lead to the selection of a virus with increased epidemic potential or exceptionally high virulence. Continued laboratory-based surveillance of the 2009 pandemic influenza A(H1N1) is important in order to rapidly identify drug resistant viruses and/or virus variants with potential ability to cause severe forms of infection and an ability to circumvent vaccine-induced immunity.
Crowd computer interaction

HCI had moved from considering how individuals interact with computers to thinking about how groups collaborate using technology. While there has been research focused on large-scale on-line communities, little attention has been paid to large groups of collocated assemblies, namely crowds. The evidence from social psychology and sociology suggest that the social dynamics and behaviours of crowds are distinct from those of smaller group formations. In this workshop we want to think about new opportunities for designing crowd-centric technologies and explore the factors that will shape interaction design for large scale crowd computing. The workshop will explore themes related to crowd-centric computing through hands-on crowd-based exercises, position papers and discussion.
Frequency-domain identification of aircraft structural modes from short-duration flight tests

This article presents identification algorithms dedicated to the modal analysis of civil aircraft structures during in-flight flutter tests. This particular operational framework implies several specifications for the identification procedure. To comply with these requirements, the identification problem is formulated in the frequency domain as an output-error problem. Iterative identification methods based on structured matrix fraction descriptions are used to solve this problem and to identify a continuous-time model. These iterative methods are specifically designed to deal with experiments where short-duration tests with multiple-input excitations are used. These algorithms are first discussed and then evaluated through a simulation example illustrative of the in-flight modal analysis of a civil aircraft. Based on these evaluation results, an efficient iterative algorithm is suggested and applied to real flight-test data measured on board a military aircraft.
The Nature of Synergy between Tissue-Type and Single Chain Urokinase-Type Plasminogen Activators

Summary Enhancement of thrombolysis with combinations of tissue-type and single chain urokinase plasminogen activators (t-PA and scu-PA) has been demonstrated in vivo but has not been seen consistently in vitro. This study was designed to characterize interactions between t-PA and scu-PA with respect to rate of and extent of thrombolysis in vitro and to delineate mechanisms responsible. Combinations of t-PA and scu-PA at selected concentrations synergistically enhanced thrombolysis in vitro compared with thrombolysis induced by either activator alone. Enhanced thrombolysis did not occur at the expense of fibrin specificity since the extent of fibrinogenolysis and consumption of α2-antiplasmin were significantly less with synergistic combinations of t-PA and scu-PA compared with equi-effective concentrations of either activator alone. Attenuation of complex formation of t-PA and two chain u-PA (tcu-PA), formed from scu-PA, with plasma proteins did not appear to contribute to enhancement of thrombolysis as assessed by fibrin autography. Binding of 125I-t-PA to thrombi was increased by 27% at 1 hr and by 21% at 2 hr in the presence of scu-PA (p <0,001 for both). Conversion of scu-PA to tcu-PA was enhanced when thrombi were exposed to scu-PA in the presence of t-PA. Results of this study indicate that t-PA and scu-PA at selected concentrations enhance thrombolysis in vitro synergistically without compromising fibrin specificity. Enhanced binding of t-PA to thrombi in the presence of scu-PA and enhanced conversion of scu-PA to tcu-PA appear to contribute to synergy between t-PA and scu-PA for thrombolysis.
Administering of pregabalin and acetaminophen on management of postoperative pain in patients with nasal polyposis undergoing functional endoscopic sinus surgery

Abstract Background: Management of postoperative pain is a common problem in endoscopic sinus surgery. The objective of this study is the evaluation of pregabalin and acetaminophen effects on the management of postoperative pain in patients with nasal polyposis undergoing functional endoscopic sinus surgery (FESS). Materials and methods: In this clinical trial, double-blinded study, 70 patients with nasal polyposis who have indication of FESS were enrolled to this study. After operation, patients were divided randomly into pregabalin and acetaminophen therapy groups. The pregabalin group (n = 35) was treated under pregabalin 50 mg TDS and the acetaminophen group (n = 35) was treated under tablet acetaminophen 500 mg/6 h. Each group was administered for 3 d. The visual analogue scale (VAS) was measured in onset, 12, 24, 48 and 72 h after surgery. All data were entered into SPSS software (SPSS Inc., Chicago, IL) and appropriate statistical tests were assessed to every relation. Results: In this study, there was no significant difference between two groups according to VAS in onset (p = .37); however, VAS in 12, 24, 48 and 72 h after operation was significantly lower in the pregabalin group compared with the acetaminophen group (p < .0001, for every four). Also in the pregabalin group, adverse effects were significantly lower than the acetaminophen group (p < .03). Conclusions: Pregabalin has more effect, safely and usefully than acetaminophen on the management of postoperative pain in the patients with nasal polyposis undergoing functional endoscopic sinus surgery.
Performance of Weighted Fair Queuing System with Multi-class Jobs

This paper analyses the weighted fair queueing (WFQ) system subject to three classes of network applications. The arrival traffic flows follow Poisson processes. The service times is exponentially distributed. The system is modelled as a two-dimensional Markov chain and use matrix geometric technique to solve its stationary probabilities. The determination of the steady state probabilities can be used to compute the performance measures of the system, such as the mean queue length, the throughput and the mean response time. Numerical experiments corroborate the theoretical results are offered and make the developed model as an effective tool for examining the performance of WFQ systems.
Fault detection, identification, and reconstruction of faulty chemical gas sensors under drift conditions, using Principal Component Analysis and Multiscale-PCA

Statistical methods like Principal Components Analysis (PCA) or Partial Least Squares (PLS) and multiscale approaches, have been reported to be very useful in the task of fault diagnosis of malfunctioning sensors for several types of faults. In this work, we compare the performance of PCA and Multiscale-PCA on a fault based on a change of sensor sensitivity. This type of fault affects chemical gas sensors and it is one of the effects of the sensor poisoning. These two methods will be applied on a dataset composed by the signals of 17 conductive polymer gas sensors, measuring three analytes at several concentration levels during 10 months. Therefore, additionally to performance's comparison, both method's stability along the time will be tested. The comparison between both techniques will be made regarding three aspects; detection, identification of the faulty sensors and correction of faulty sensors response.
Robust Speech Hashing for Content Authentication

Robust hashing for multimedia authentication is an emerging research area. A novel key-dependent robust speech hashing based on speech production model is proposed in this letter. Robust hash is calculated based on linear spectrum frequencies (LSFs) which model the vocal tract. The correlation between LSFs is decoupled by discrete cosine transformation (DCT). A randomization scheme controlled by a secret key is applied in hash generation for random feature selection. The hash function is key-dependent and collision resistant. Meanwhile, it is highly robust to content preserving operations as well as having high accuracy of tampering localization.
Anything is possible: Managing feature creep in an innovation rich environment

This paper examines the inevitable product feature creep, also known as requirements creep, from an engineering project manager's perspective. Feature creep is often the wildcard a project manager has to balance against resources, cost and schedule. After first describing the nature and sources of feature creep, the paper delves into the detrimental aspects of feature creep, some of which are non-intuitive and affect a project in subtle ways. Finally, the paper describes methods to defend a project against the negative aspects of feature creep and incorporate change in a constructive way. This rigorous look at feature creep should help any engineering project manager balance the factors that affect a project, resulting in a successful product release.