Miracle-dz/UniFAR-FTUs huggingface dataset:
A dialogue of collaboration: cooperation in Canadian policing research today

Abstract Today, in Canadian policing research, unprecedented opportunities exist for university-based researchers to investigate various research questions with cooperation from police leadership. Given complexities in contemporary policing, it is recognized that transformational changes require contributions from external knowledge and scientific research – in furtherance of the movement toward evidence-based practices. This paper incorporates data originating from interviews with 20 Canadian police commanders and 20 Canadian policing research academics. It is clear that the majority of this study’s participants realize that more cooperative research arrangements are required to resolve long-standing issues around access, trust, and control of the research agenda. For academics, however, this does not extend to a policing research institute model for Canada (similar to that of the Scottish Institute for Police Research). In addressing these issues, this paper informs, and provides empirical context to, on-going international discussions across policing research and police communities – vis-à-vis ending the ‘dialogue of the deaf’.
A Diophantine model of routes in structured P2P overlays

An important problem in any structured Peer-to-Peer (P2P) overlay is what routes are available between peers. Understanding the structure of routes helps to solve challenging problems related to routing performance, security, and scalability. In this paper, we propose a theoretical approach for describing routes. It is based on a recent result in the linear Diophantine analysis and introduces a novel Diophantine model of P2P routes. Such a route aggregates several P2P paths that packets follow. A commutative context-free grammar describes the forwarding behavior of P2P nodes. Derivations in the grammar correspond to P2P routes. Initial and final strings of a derivation define packet sources and destinations, respectively. Based on that we construct a linear Diophantine equation system, where any solution counts forwarding actions in a route representing certain integral properties. Therefore, P2P paths and their composition into routes are described by a linear Diophantine systems; its solutions (basis) define a structure of P2P paths.
Scalable large margin online metric learning

We present a novel online metric learning model, called scalable large margin online metric learning (SLMOML). SLMOML belongs to the passive-aggressive family of learning models. In the formulation of SLMOML, we use the LogDet divergence to measure the closeness between two continuously learned matrices, which naturally ensures the positive semi-definiteness of the learned matrix at each iteration, provided the initial matrix is positive semi-definite. In addition, a hinge loss is used to maintain a large margin of distance between relatively dissimilar data. Using the Karush-Kuhn-Tucker (KKT) condition, the updating rule of SLMOML can be equivalently viewed as Bregman projections. Based on this fact, we have proved the global convergence of SLMOML. Extensive experiments on real world applications demonstrate the superiority of SLMOML over state-of-the-art metric learning and similarity learning approaches.
IITPSemEval: Sentiment Discovery from 140 Characters

This paper presents an overview of the system developed and submitted as a part of our participation to the SemEval-2015 Task 10 that deals with Sentiment Analysis in Twitter. We build a Support Vector Machine (SVM) based supervised learning model for Subtask A (term level task) and Subtask B (message level task). We also participate in Subtask E viz., determining degree of polarity, and build a very simple system by employing the available lexical resources. Experiments with the 2015 official datasets show F1 scores of 81.31% and 58.80% for Task A and Task B, respectively. For Subtask E, our model achieves a score of 0.413 on Kendal’s Tau metric.
Mining Commonsense Knowledge From Personal Stories in Internet Weblogs

Recent advances in automated knowledge base construction have created new opportunities to address one of the hardest challenges in Artificial Intelligence: automated commonsense reasoning. In this paper, we describe our recent efforts in mining commonsense knowledge from the personal stories that people write about their lives in their Internet weblogs. We summarize three preliminary investigations that involve the application of statistical natural language processing techniques to corpora of millions of weblog stories, and outline our current approach to solving a number of outstanding technical
ROBOG an autonomously navigating vehicle based on road detection for unstructured road

This research addresses the problem of navigating a robotic vehicle autonomously on unstructured roads where road information is not accurate. A real-time system for finding and tracking unstructured road in off-road conditions is proposed. The subsystems of autonomous navigation - road detection, steering, and obstacle avoidance are discussed in detail. This method has been integrated into a vehicle and driven successfully for both structured and unstructured road. An overview of vehicle performance in field is provided.
Performance of Statistical Tests for Single-Source Detection Using Random Matrix Theory

This paper introduces a unified framework for the detection of a single source with a sensor array in the context where the noise variance and the channel between the source and the sensors are unknown at the receiver. The Generalized Maximum Likelihood Test is studied and yields the analysis of the ratio between the maximum eigenvalue of the sampled covariance matrix and its normalized trace. Using recent results from random matrix theory, a practical way to evaluate the threshold and the p-value of the test is provided in the asymptotic regime where the number K of sensors and the number N of observations per sensor are large but have the same order of magnitude. The theoretical performance of the test is then analyzed in terms of Receiver Operating Characteristic (ROC) curve. It is, in particular, proved that both Type I and Type II error probabilities converge to zero exponentially as the dimensions increase at the same rate, and closed-form expressions are provided for the error exponents. These theoretical results rely on a precise description of the large deviations of the largest eigenvalue of spiked random matrix models, and establish that the presented test asymptotically outperforms the popular test based on the condition number of the sampled covariance matrix.
Puffer fish poisoning: a potentially life‐threatening condition

Puffer fish poisoning has been documented rarely in Australia. It results from ingesting tetrodoxtoxin found in the liver, ovaries, intestines and skin of the fish. Over a recent 16-month period, 11 cases of puffer fish poisoning were reported to the NSW Poisons Information Centre. Symptoms of poisoning may include paralysis, respiratory failure, numbness, paraesthesia, nausea and ataxia. Health professionals should be aware of the condition so as to institute early and appropriate management.
PENGARUH KUALITAS LAYANAN TERHADAP KEPUASAN KONSUMEN

The purpose of this research is to know the influence of services quality to consumerâ€™s satisfaction and also to know which variable that most dominant influence to the consumerâ€™s satisfaction at Hotel Sentosa Palembang. Â The data were collected by using interview and questionnaires. Â The sample are 60 respondences who are staying at Hotel Sentosa. Â The data were analyzed by using regression analysis follow by SPSS (Statistic Problem Solution Service) Version 11.5 software for windows. Â The result shows that the services quality, they are Tangible, Reliability, Responsiveness, Assurance, and Empathy affect to consumers satisfaction are 33,5% while the remaining influenced by other factors outside the study, one of which is an easily accessible location factor. Â Based on the t test (partial test), shows that there are three variables that influence of customers satisfaction partialy, they are responsiveness, assurance and empathy variable. Â However, the most dominant variable is responsiveness variable.
A NOVEL ALGORITHM FOR TRAINING POLYNOMIAL NETWORKS

Modern recognition systems require high-accuracy low-complexity methods. We explore a polynomial network approach to recognition problems. Traditionally, polynomial networks have been difficult to use for recognition because of either low accuracy or problems associated with large training sets. We detail a new training method that solves these problems. For identification, the method partitions the problem to dramatically reduce resources needed. For verification, the method conglomerates all anti-class data into a fixedsize background model. We illustrate the method by applying it to the problem of speaker recognition using voice.
P300 and Decision Making under Risk and Ambiguity

Our study aims to contrast the neural temporal features of early stage of decision making in the context of risk and ambiguity. In monetary gambles under ambiguous or risky conditions, 12 participants were asked to make a decision to bet or not, with the event-related potentials (ERPs) recorded meantime. The proportion of choosing to bet in ambiguous condition was significantly lower than that in risky condition. An ERP component identified as P300 was found. The P300 amplitude elicited in risky condition was significantly larger than that in ambiguous condition. The lower bet rate in ambiguous condition and the smaller P300 amplitude elicited by ambiguous stimuli revealed that people showed much more aversion in the ambiguous condition than in the risky condition. The ERP results may suggest that decision making under ambiguity occupies higher working memory and recalls more past experience while decision making under risk mainly mobilizes attentional resources to calculate current information. These findings extended the current understanding of underlying mechanism for early assessment stage of decision making and explored the difference between the decision making under risk and ambiguity.
X-ray beaming caused by resonance scattering in the accretion column of magnetic cataclysmic variables

Extremely strong ionized Fe emission lines, with equivalent widths reaching ∼4000 eV, were discovered by ASCA from a few Galactic compact objects, including AX J2315−0592, RX J1802.1+1804 and AX J1842.8−0423. These objects are thought to be binary systems containing magnetized white dwarfs (WDs). A possible interpretation of the strong Fe K line is the line-photon collimation in the WD accretion column, as a result of resonance scattering of line photons. The collimation occurs when the accretion column has a flat shape, and the effect is augmented by the vertical velocity gradient, which reduces the resonant trapping of resonant photons along the magnetic field lines. This effect was quantitatively confirmed with Monte Carlo simulations. Furthermore, with ASCA observations of the polar V834 Centauri, this collimation effect was clearly detected as a rotational modulation of the equivalent width of the Fe K emission line. The extremely strong emission lines mentioned above can be explained consistently by our interpretation. Combining this effect with other X-ray information, the geometry and plasma parameters in the accretion column were determined.
The relationship between gas content and star formation rate in spiral galaxies. Comparing the local field with the Virgo cluster

Context. Despite many studies of star formation in spiral galaxies, a complete and coherent understanding of the physical processes that regulate the birth of stars has not yet been achieved, nor has unanymous consensus been reached, despite the many attempts, on the effects of the environment on the star formation in galaxy members of rich clusters. Aims. We focus on the local and global Schmidt law and we investigate how cluster galaxies have their star formation activity perturbed. Methods. We collect multifrequency imaging for a sample of spiral galaxies, members of the Virgo cluster and of the local field; we compute the surface density profiles for the young and for the bulk of the stellar components, for the molecular and for the atomic gas. Results. Our analysis shows that the bulk of the star formation correlates with the molecular gas, but the atomic gas is important or even crucial in supporting the star formation activity in the outer part of the disks. Moreover, we show that cluster members that suffer from a moderate HI removal have their molecular component and their SFR quenched, while highly perturbed galaxies show an additional truncation in their star forming disks. Conclusions. Our results are consistent with a model in which the atomic hydrogen is the fundamental fuel for the star formation, either directly or indirectly through the molecular phase; therefore galaxies whose HI reservoirs have been depleted suffer from starvation or even from truncation of their star formation activity.
Interleukin-17A Gene Haplotypes Are Associated with Risk of Premature Coronary Artery Disease in Mexican Patients from the Genetics of Atherosclerotic Disease (GEA) Study

Aim The role of interleukin 17A (IL-17A) in the inflammatory process has caused interest in the potential significance of IL-17A as a biomarker for coronary artery disease (CAD). The aim of the present study was to evaluate the role of IL-17A gene polymorphisms as susceptibility markers for CAD in the Mexican population. Methods Four IL-17A gene polymorphisms (rs8193036, rs3819024, rs2275913 and rs8193037) were genotyped by 5’ exonuclease TaqMan assays in a group of 900 patients with premature CAD and 667 healthy controls (with negative calcium score by computed tomography), seeking associations with CAD and other metabolic and cardiovascular risk factors using logistic regression analyses. Results No single IL-17A polymorphism was associated with premature CAD, however two haplotypes (CAGG and TAGA) were significantly associated with increased risk of premature CAD (OR = 1.35, 95% CI: 1.00–1.84, P = 0.018 and OR = 2.09, 95% CI: 1.16–3.76, P = 0.003, respectively). Moreover, rs3819024 was associated with increased levels of visceral abdominal fat (P = 0.002) and rs8193036 was significantly associated with risk of central obesity (P = 0.020), hypertriglyceridemia (P = 0.027), and metabolic syndrome (P = 0.027) in the premature CAD group, under dominant models adjusted by age, gender, BMI, smoking history, alcohol consumption, and treatment. Conclusion The results suggest that IL-17A haplotypes are involved in the risk of developing premature CAD and some IL-17A polymorphisms are associated with cardiovascular risk factors in Mexican individuals with premature CAD.
Redifferentiation of human gastric cancer cells induced by ascorbic acid and sodium selenite.

OBJECTIVE To explore the effects and mechanisms of ascorbic acid (AA) and sodium selenite (SS) on growth inhibition and redifferentiation in human gastric cancer cells. METHODS In the present study, trypan blue dye exclusion method was used to determine the cell growth curve and mitotic index, cell electrophoresis and colonogenic potential were used as the indexes of redifferentiation. In order to find out the mechanisms of redifferentiation, the activities of superoxide dismutase (SOD), glutathione peroxidase (GPX) and catalase (CAT) were assayed, the content of malondialdehyde (MDA), reduced glutathione (GSH) and H2O2 were evaluated. RESULTS After treatment with AA 3 mol/L + SS 2 mu mol/L, the growth rate and mitotic index of human gastric cancer cells (MGc-803) decreased remarkably. The indexes related with cell malignancy were alleviated. For example, cell surface charge was obviously decreased, the electrophoresis rate was dropped from 2.21 to 1.15 mu m.s-1.V-1.cm-1. The indexes related with cell redifferentiation were promoted. For example, the colonogenic potential was decreased to 93.5%. These results indicated that redifferentiation of human gastric cancer cells was successfully induced by AA + SS. The activities of SOD and GPX were significantly higher, while the activity of CAT was slower in treated group than that in the control. The content of MDA was slightly decreased, GSH was sharply decreased, and H2O2 content was dramatically increased. CONCLUSION These results indicated that combination of ascorbic acid and sodium selenite may induce the redifferentiation of human gastric cancer cells and inhibit cell growth by virtue of enhancing the activities of antioxidative enzymes and inducing the formation of H2O2, and altering the cell redox status. Combination of ascorbic acid and sodium selenite may be a potent anticancer agent for human gastric cancer.
Zoom navigation exploring large information and application spaces

We present the concept of ZOOM NAVIGATION, a new interaction paradigm to cope with visualization and navigation problems as found in large information and application spaces. It is based on the pluggable zoom, an object-oriented component derived from the variable zoom fisheye algorithm.Working with a limited screen space we apply a Degree-of-interest (DOI) function to guide the level of detail used in presenting information. Furthermore we determine the user's information and navigation needs by analysing the interaction history. This leads to the definition of the aspect-of-interest (AOI) function. The AOI is evaluated in order to choose one of the several information aspects, under which an item can be studied. This allows us to change navigational affordance and thereby enhance navigation.In this paper we describe the ideas behind the pluggable zoom and the definition of DOI and AOI functions. The application of these functions is demonstrated within two case studies, the ZOOM ILLUSTRATOR and the ZOOM NAVIGATOR. We discuss our experience with these implemented systems.
The role of consequences of moral action in maximizing moral elevation

Abstract Moral elevation is described as a state of positive emotion that includes uplifting feelings, positive views of humanity and a desire to be a better person. Numerous empirical studies have demonstrated that elevation has powerful effects on people’s moral intention and behavior. The next step is to investigate how to maximize the emotion of elevation. According to the evolution of moral elevation research and the theory of moral disgust, we hypothesized that the consequences of moral action would influence moral elevation. The results of two studies in the present research (Study 1: N = 122, average age = 36.96 years; Study 2: N = 232, average age = 23.93 years) demonstrated that moral acts with good consequences were more effective in inducing moral elevation than moral acts with bad consequences. The implications for research and practice are discussed.
Disulfide Rearrangement Triggered by Translocon Assembly Controls Lipopolysaccharide Export

Get Ready, Assemble, Fold The outer membrane protein complex LptD/E is responsible for lipopolysaccharide export to the cell surface of Escherichia coli. LptD is an essential β-barrel protein that contains two disulfide bonds between nonconsecutive cysteines. Chng et al. (p. 1665, published online 30 August) describe the characterization of the oxidative folding and assembly pathway of LptD/E in living cells. A combination of steady-state and pulse-chase measurements was used to identify seven intermediates with different disulfide-bonded states, along the oxidative folding pathway. During folding and assembly, a non-native disulfide-bonded LptD intermediate accumulated and, triggered by β-barrel assembly and association with the lipoprotein LptE, rearranged to the native disulfide-bonded state required for lipopolysaccharide export. Thus, disulfide bond–dependent protein folding can involve the proper assembly of a two-protein complex in order to promote disulfide bond rearrangement. Protein-protein interactions promote oxidative protein folding during assembly of a bacterial lipopolysaccharide exporter. The presence of lipopolysaccharide (LPS) on the cell surface of Gram-negative bacteria is critical for viability. A conserved β-barrel membrane protein LptD (lipopolysaccharide transport protein D) translocates LPS from the periplasm across the outer membrane (OM). In Escherichia coli, this protein contains two disulfide bonds and forms the OM LPS translocon with the lipoprotein LptE. Here, we identified seven in vivo states on the oxidative-folding pathway of LptD. Proper assembly involved a nonfunctional intermediate containing non-native disulfides. Intermediate formation required the oxidase DsbA, and subsequent maturation to the active form with native disulfides was triggered by LptE. Thus, disulfide bond–dependent protein folding of LptD requires the proper assembly of a two-protein complex to promote disulfide bond rearrangement.
Minimization of Mutual Coupling Using Neutralization Line Technique for 2.4 GHz Wireless Applications

This paper presented a planar printed multiple-input-multiple-output MIMO antenna with a dimension of 100 x 45 mm2. It composed of two crescent shaped radiators placed symmetrically with respect to the ground plane. Neutralization line applied to suppress mutual coupling. The proposed antenna examined both theoretically and experimentally, which achieves an impedance bandwidth of 18.67% over 2.04-2.46 GHz with a reflection coefficient < -10 dB and mutual coupling minimization of < -20 dB. An evaluation of MIMO antennas is presented, with analysis of correlation coefficient, total active reflection coefficient TARC, capacity loss and channel capacity. These characteristics indicate that the proposed antenna suitable for some wireless applications.
Adaptive localization techniques in WiFi environments

Indoor localization of a mobile user can be performed by using the off-the-shelf 802.11 (WiFi) infrastructure. However most of the existing position estimators are based on a stationary environment assumption that turns out to be rarely true in practice. We analyze two different approaches for the simultaneous estimation of the position and of the signal statistical model. The first uses a discrete state approach and is based on the Expectation-Maximization (EM) algorithm; the second employs a continuous state space and Kalman or Particle Filtering methodology. Numerical simulations and implementation show the effectiveness of the latter for real-time applications in nonstationary environments.