Miracle-dz/UniFAR-FTUs huggingface dataset:
Modulo-lattice reduction in precoding schemes

This paper discusses the use of modulo arithmetics in the precoding scheme for N-dimensional data symbols. The transmission scheme employing modulo reduction mod-/spl Lambda/ precoding is an attractive strategy when transmitting over AWGN channels, which suffer from additive noise, and an additional interference term, which is already known at the transmitter side. The capacity of channels and the use of optimum lattice quantizers for minimum error entropy approach applying numerical optimization are also studied.
Natural regeneration of sessile oak under different light conditions

Different variants of regeneration felling or different light conditions (total site factor 15-95%) and weed control were evaluated in relation to the 4-year development of individuals of regenerated sessile oak. The regenera - tion density is not dependent on light conditions. The highest mortality occurs on the open area of clear felling. For a certain time in youth, it is possible to consider oak as a shade-tolerating species. With the increasing light intensity the diameter and height growth of oak seedlings increases proportionally, being the highest at 100% light intensity. However, to support at least medium-fast growth, the species requires minimally 50% light intensity (smaller closed clear-felled areas ). On the other hand, more extensive unprotected cleared areas appear to be quite unsuitable at the initial stages of regeneration. The positive effect of weed control on the success and growth of natural regeneration is questionable. We recommend developing the regenerated stand by means of a series of small-area (about ≤ 0.3 ha) two-stage felling with a medium-long regeneration period (15-20 years).
Polymer matrix composites (PMC ) in aerospace

The progress of PMC, especially ACM, for aircraft and spacecraft in the past 20 years is reviewed. Treated are the history of use of BFRP, CFRP and AFRP, and some problems that we faced to introduce those new materials into aerospace structural parts including design, fabrication, assembly, manufacture cost, repair, etc. New tough CFRP, which is possibly one of key technologies developed in the era, and perspectives of technological issues to be solved are also presented.
Assessing the Physical Service Setting

Objective: To determine the attributes of the physical setting that are important for developing a positive service climate within emergency departments and to validate a measure for assessing physical service design. Background: The design of the physical setting is an important and contributing factor for creating a service climate in organizations. Service climate is defined as employee perceptions of the practices, procedures, and behaviors that get rewarded, supported, and expected with regard to customer service and customer service quality. There has been research conducted which identifies antecedents within organization that promotes a positive service climate which in turn creates service-oriented behaviors by employees toward clients. The antecedent of the physical setting and its impact on perceptions of service climate has been less commonly explored. Methods: Using the concept of the physical service setting (which may be defined as aspects of the physical, built environment that facilitate the delivery of quality service), attributes of the physical setting and their relationship with service climate were explored by means of a quantitative paper survey distributed to emergency nurses (n = 180) throughout a province in Canada. Results: The results highlight the validity and reliability of six scales measuring the physical setting and its relation to service. Respondents gave low ratings to the physical setting of their departments, in addition to low ratings of service climate. Conclusions: Respondents feel that the design of the physical setting in the emergency departments where they work is not conducive to providing quality service to clients. Certain attributes of the physical setting were found to be significant in influencing perceptions of service climate, hence service quality, within the emergency department setting.
Effect of Process Parameters on Burrs Produced in Micromilling of a Thin Nitinol Foil

This paper examines the formation of burrs in micromilling of a thin nickel–titanium alloy (nitinol) foil used in implantable biomedical device applications. The paper analyzes the effects of key micromilling process parameters such as spindle speed, feed, tool wear, backing material, and adhesive used to attach the foil to the backing material on the burr height. It is found that burr height is larger on the downmilling side for grooves cut with a worn tool at high feeds, low spindle speeds with a softer backing material, and a weaker adhesive bond. Some important interaction effects of these factors are also studied. The study also shows that the mechanics of burr formation in such thin materials depends on whether the mode of cutting is dominated by tearing or chip formation, which is a function of the feed rate. A kinematic model to predict burr widths is developed and verified through experiments.
Estimating a Mean-Path from a set of 2-D curves

To perform many common industrial robotic tasks, e.g. deburring a work-piece, in small and medium size companies where a model of the work-piece may not be available, building a geometrical model of how to perform the task from a data set of human demonstrations is highly demanded. In many cases, however, the human demonstrations may be sub-optimal and noisy solutions to the problem of performing a task. For example, an expert may not completely remove the burrs that result in deburring residuals on the work-piece. Hence, we present an iterative algorithm to estimate a noise-free geometrical model of a work-piece from a given dataset of profiles with deburring residuals. In a case study, we compare the profiles obtained with the proposed method, nonlinear principal component analysis and Gaussian mixture model/Gaussian mixture regression. The comparison illustrates the effectiveness of the proposed method, in terms of accuracy, to compute a noise-free profile model of a task.
Moving improvement research closer to practice: the Researcher-in-Residence model

The traditional separation of the producers of research evidence in academia from the users of that evidence in healthcare organisations has not succeeded in closing the gap between what is known about the organisation and delivery of health services and what is actually done in practice. As a consequence, there is growing interest in alternative models of knowledge creation and mobilisation, ones which emphasise collaboration, active participation of all stakeholders, and a commitment to shared learning. Such models have robust historical, philosophical and methodological foundations but have not yet been embraced by many of the people working in the health sector. This paper presents an emerging model of participation, the Researcher-in-Residence. The model positions the researcher as a core member of a delivery team, actively negotiating a body of expertise which is different from, but complementary to, the expertise of managers and clinicians. Three examples of in-residence models are presented: an anthropologist working as a member of an executive team, operational researchers working in a front-line delivery team, and a Health Services Researcher working across an integrated care organisation. Each of these examples illustrates the contribution that an embedded researcher can make to a service-based team. They also highlight a number of unanswered questions about the model, including the required level of experience of the researcher and their areas of expertise, the institutional facilitators and barriers to embedding the model, and the risk that the independence of an embedded researcher might be compromised. The Researcher-in-Residence model has the potential to engage both academics and practitioners in the promotion of evidence-informed service improvement, but further evaluation is required before the model should be routinely used in practice.
Increased Endoplasmic Reticulum Stress in Atherosclerotic Plaques Associated With Acute Coronary Syndrome

Background— The endoplasmic reticulum (ER) responds to various stresses by upregulation of ER chaperones, but prolonged ER stress eventually causes apoptosis. Although apoptosis is considered to be essential for the progression and rupture of atherosclerotic plaques, the influence of ER stress and apoptosis on rupture of unstable coronary plaques remains unclear. Methods and Results— Coronary artery segments were obtained at autopsy from 71 patients, and atherectomy specimens were obtained from 40 patients. Smooth muscle cells and macrophages in the fibrous caps of thin-cap atheroma and ruptured plaques, but not in the fibrous caps of thick-cap atheroma and fibrous plaques, showed a marked increase of ER chaperone expression and apoptotic cells. ER chaperones also showed higher expression in atherectomy specimens from patients with unstable angina pectoris than in specimens from those with stable angina. Expression of 7-ketocholesterol was increased in the fibrous caps of thin-cap atheroma compared with thick-cap atheroma. Treatment of cultured coronary artery smooth muscle cells or THP-1 cells with 7-ketocholesterol induced upregulation of ER chaperones and apoptosis, whereas these changes were prevented by antioxidants. We also investigated possible signaling pathways for ER-initiated apoptosis and found that the CHOP (a transcription factor induced by ER stress)-dependent pathway was activated in unstable plaques. In addition, knockdown of CHOP expression by small interfering RNA decreased ER stress-dependent death of cultured coronary artery smooth muscle cells and THP-1 cells. Conclusions— Increased ER stress occurs in unstable plaques. Our findings suggest that ER stress-induced apoptosis of smooth muscle cells and macrophages may contribute to plaque vulnerability.
Efficient estimation of tail probabilities of the typical distance in preferential attachment models

The properties of random graphs provide insight into the behavior of real-world complex networks. One such property is the Typical Distance, which characterizes the time required to traverse the network. For example, the Typical Distance measures how fast a virus spreads through a population. The probability that the Typical Distance is large is difficult to estimate via crude Monte Carlo. We propose a new sequential importance sampling estimator that can find the probability of a large Typical Distance in preferential attachment models, with a computational complexity that is quadratic in the number of nodes. Numerical experiments indicate that the estimator is significantly more efficient than crude Monte Carlo.
From monaural to binaural speaker recognition for humanoid robots

This paper addresses speaker recognition in a binaural context. Such an auditory sensor is naturally well suited to humanoid robotics as it only requires two microphones embedded in artificial ears. But the state of the art shows that, contrary to monaural and multi-microphone approaches, binaural systems are not so much studied in the specific task of automatic speaker recognition. Indeed, these sensors are mostly used for speech recognition, or speaker localization. This study will then focus on the benefits of the binaural context in comparison with monaural techniques. The proposed approach is first evaluated in simulation through a HRTF database reproducing the head shadowing effect and with a 10-speakers database. Next, the method is assessed with an experimental binaural 15-speakers database recorded in our own almost-anechoic room for various SNR conditions. Results show that the speaker positions during the learning step of the proposed approach strongly influence the recognition rates.
Rationale of Using Dynamic Imaging for Characterization of Suspicious Lung Masses into Benign or Malignant on Contrast Enhanced Multi Detector Computed Tomography

Objectives: To assess the utility of dynamic imaging namely, wash-in and wash-out characteristics through multidetector contrast-enhanced computed tomography in differentiating benign and malignant pulmonary masses. Materials and Methods: Seventy-three patients who were suspected to have malignant pulmonary mass on the basis of clinical symptoms and chest radiograph were included in the study. All the patients underwent multidetector computed tomography scanning, and three series of images were obtained for each patient-noncontrast, early enhanced, and 15 min delayed enhanced scans. Computed tomography (CT) findings were assessed in terms of washin, absolute, and relative percentage washout of contrast. Biopsy of the mass was done and sent for histopathological evaluation. Sensitivity, specificity, and area under curve for diagnosing malignancy in the lung masses were calculated by considering both the wash-in and wash-out characteristics at dynamic CT and plotting the receiver operating curve after the final diagnosis which was obtained by histopathological evaluation. Results: Threshold net enhancement (washin) value of >22.5 HU had sensitivity, specificity, and diagnostic accuracy of 88.5%, 57.1%, and 82%, respectively, in predicting malignancy. Threshold relative percentage washout of <16.235% had 98.1%, 85.7%, and 94% sensitivity, specificity, and diagnostic accuracy, respectively, and threshold absolute percentage washout of <42.72% had 98.1%, 95.2%, and 95% sensitivity, specificity, and diagnostic accuracy, respectively, in predicting malignancy. Conclusion: Threshold net enhancement (washin), absolute and relative washout percentages can be used to predict malignancy with very high diagnostic yield, and possibly obviate the need of invasive procedures for diagnosis of bronchogenic carcinoma.
Optimal notch shapes for loaded plates

This paper presents design data defining optimal freeform notch shapes for use in tensile loading conditions for a range of geometries, notably the notch aspect ratio and plate widths. Here, an iterative two-dimensional finite element gradientless shape optimization procedure was used to obtain the optimal shapes, which offer the lowest possible stress concentration, subject to the geometric constraints. Precise non-dimensional coordinates are given, for a range of notch aspect ratios and plate widths, and are presented in a tabular form that allows them to be easily used by designers. All cases have been solved with a minimum radius of curvature constraint, which results in a ‘robust’ optimal shape that has no sharp corners. The optimal shapes were found to provide up to a 26 per cent reduction in local peak stress over circular shapes of the same aspect ratio. Optimal geometries are also given for limiting notches that provide a net section stress equal to unity, at a finite notch aspect ratio. The results obtained are applicable to both the initial design of notched components and the shape reworking of existing components to remove damage.
Association Rule Mining for Suspicious Email Detection: A Data Mining Approach

Email has been an efficient and popular communication mechanism as the number of Internet user's increase. In many security informatics applications it is important to detect deceptive communication in email. This paper proposes to apply Association Rule Mining for Suspected Email Detection. (Emails about Criminal activities). Deception theory suggests that deceptive writing is characterized by reduced frequency of first person pronouns and exclusive words and elevated frequency of negative emotion words and action verbs . We apply this model of deception to the set of Email dataset, then applied Apriori algorithm to generate the rules The rules generated are used to test the email as deceptive or not. In particular we are interested in detecting emails about criminal activities. After classification we must be able to differentiate the emails giving information about past criminal activities(Informative email) and those acting as alerts(warnings) for the future criminal activities. This differentiation is done using the features considering the tense used in the emails. Experimental results show that simple Associative classifier provides promising detection rates.
Temperate coliphages: classification and correlation with habitats

Temperate coliphages were recovered from sewage, mammalian feces, and lysogenic strains of Escherichia coli. A total of 32 phages of independent origin were divided into six groups by applying the criteria of host range, antigenic homology, and the ultraviolet inducibility of the prophage. The demonstration of genetic interactions in some cases has confirmed the classification scheme. Nine phages were assigned to the P2 family and 19 to the lambda family. The remaining four isolates may represent some novel phylogenetic types. Phages recovered from the lysogenic strains of E. coli were all found to be P2 related, whereas a majority of the phages recovered as cell-free plaque-forming units were assignable to the lambda family. It is proposed that the biological attributes of the phages belonging to the two principal families are reflected in the distribution patterns observed. The virions of phage HK256 show multiple tail fibers and may thus represent a "new" virion form among the temperate coliphages.
Confirmation for Deterministic Hypotheses 1 Running head : CONFIRMATION FOR DETERMINISTIC HYPOTHESES Seeking Confirmation is Rational for Deterministic Hypotheses

The tendency to test outcomes that are predicted by our current theory (the confirmation bias) is one of the best-known biases of human decision making. We prove that the confirmation bias is an optimal strategy for testing hypotheses when those hypotheses are deterministic, each making a single prediction about the next event in a sequence. Our proof applies for two normative standards commonly used for evaluating hypothesis testing: maximizing expected information gain and maximizing the probability of falsifying the current hypothesis. This analysis rests on two assumptions: (1) that people predict the next event in a sequence in a way that is consistent with Bayesian inference and (2) when testing hypotheses, people test the hypothesis that they assign highest posterior probability. We present four behavioral experiments that support these assumptions, showing that a simple Bayesian model can capture people’s predictions about numerical sequences (Experiments 1 and 2), and that we can alter the hypotheses that people choose to test by manipulating the prior probability of those hypotheses (Experiments 3 and 4). Confirmation for Deterministic Hypotheses 3 Seeking Confirmation is Rational for Deterministic Hypotheses
The SHH/Gli pathway is reactivated in reactive glia and drives proliferation in response to neurodegeneration‐induced lesions

In response to neurodegeneration, the adult mammalian brain activates a cellular cascade that results in reactive astrogliosis and microgliosis. The mechanism through which astrocytes become reactive and the physiological consequences of their activation in response to neurodegeneration is complex. While the activation and proliferation of astrocytes has been shown to occur during massive neuronal cell death, the functional relationship between these two events has not been clearly elucidated. Here we show that in response to kainic acid‐ (KA) induced neurodegeneration, the mitogen sonic hedgehog (SHH) is upregulated in reactive astrocytes. SHH activity peaks at 7 days and is accompanied by increased Gli activity and elevated proliferation in several cell types. To determine the functional role of SHH‐Gli signaling following KA lesions, we used a pharmacological approach to show that SHH secreted by astrocytes drives the activation and proliferation of astrocytes and microglia. The consequences of SHH‐Gli signaling in KA‐induced lesions appear to be independent of the severity of neurodegeneration. GLIA 2014;62:1595–1607
Improving the prediction accuracy of liver disorder disease with oversampling

The complexity of liver makes it easily affected by disease of disorder. So diagnosing liver disorder disease is a high interest to data miners, and decision trees have been useful data mining tools to diagnose the disease, but the accuracy of decision trees has been limited due to insufficient data. In order to generate more accurate decision trees for liver disorder disease this paper suggests a method based on over-sampling in minor classes to compensate the insufficiency of data effectively. Experiments were done with two representative algorithms of decision trees, C4.5 and CART, and a data set, 'BUPA liver disorder', and showed the validity of the method.
Effect of joint angle on EMG variables in leg and thigh muscles

It is the purpose of this article (a) to show the influence of electrode location on EMG amplitude and spectral variables for simulated and real signals for different muscles of the thigh and leg, (b) to investigate the relative movement of the muscle under the recording electrodes when the joint angle changes for the set of muscles most frequently investigated in gait analysis, and (c) to illustrate how different electrode locations may lead to different interpretations of the muscle activity investigated with amplitude and spectral analysis of the surface EMG signal. The study has been carried out on the following muscles of the leg and thigh: rectus femoris, vastus lateralis, vastus medialis, biceps femoris, semitendinosus, tibialis anterior, gastrocnemius lateralis, and gastrocnemius medialis.
Prediction of user app usage behavior from geo-spatial data

In the era of mobile Internet, a vast amount of geo-spatial data allows us to gain further insights into human activities, which is critical for Internet Services Providers (ISP) to provide better personalized services. With the pervasiveness of mobile Internet, much evidence show that human mobility has heavy impact on app usage behavior. In this paper, we propose a method based on machine learning to predict users' app usage behavior using several features of human mobility extracted from geo-spatial data in mobile Internet traces. The core idea of our method is selecting a set of mobility attributes (e.g. location, travel pattern, and mobility indicators) that have large impact on app usage behavior and inputting them into a classification model. We evaluate our method using real-world network traffic collected by our self-developed high-speed Traffic Monitoring System (TMS). Our prediction method achieves 90.3% accuracy in our experiment, which verifies the strong correlation between human mobility and app usage behavior. Our experimental results uncover a big potential of geo-spatial data extracted from mobile Internet.
Rewriting History to Exploit Gain Time

With modern processors and more dynamic application requirements it is becoming increasingly difficult to produce tight upper bounds on the worst-case execution time of real-time tasks. As a result, at run-time, considerable spare CPU capacity (termed gain time) becomes available that must be usefully employed if cost effective real-time systems are to be engineered. In this paper we introduce a scheme by which gain time is exploited by retrospectively reassigning execution time from a task’s own budget to the gain time that later become available. As a result of changing the system’s execution history, spare capacity is immediately reallocated and hence preserved. The proposed scheme is shown to work with fixed priority dispatching, the use of servers to provide temporal firewalls, and other capacity sharing approaches. Evaluations are provided via simulations.