Miracle-dz/UniFAR-FTUs huggingface dataset:
Double-EIT ground-state laser cooling without blue-sideband heating

We discuss a laser cooling scheme for trapped atoms or ions which is based on double electromagnetically induced transparency (EIT) and makes use of a four-level atom in tripod configuration. The additional fourth atomic state is coupled by a strong-coupling laser field to the upper state of the usual three-level setup of single-EIT cooling. This effectively allows to create two EIT structures in the absorption spectrum of the system to be cooled, which may be controlled by the coupling laser field parameters to cancel both the carrier- and the blue-sideband excitations. In leading order of the Lamb-Dicke expansion, this suppresses all heating processes. As a consequence, the double-EIT scheme can be used to lower the cooling limit by a factor of order of the Lamb-Dicke parameter squared as compared to single-EIT cooling.
Clustering using the fisher-rao distance

In this paper we consider the Fisher-Rao distance in the space of the multivariate diagonal Gaussian distributions for clustering methods. Centroids in this space are derived and used to introduce two clustering algorithms for diagonal Gaussian mixture models associated to this metric: the k-means and the hierarchical clustering. These algorithms allow to reduce the number of components of such mixture models in the context of image segmentation. The algorithms presented here are compared with the Bregman hard and hierarchical clustering algorithms regarding the advantages of each method in different situations.
Virtual interaction: Design factors affecting student satisfaction and perceived learning in asynchronous online courses

This paper looks at factors affecting student satisfaction with and perceived learning from asynchronous online learning. It reports on an empirical investigation that explored relationships between student perceptions and course design factors in 73 SUNY Learning Network courses in the Spring, 1999 semester. The study found that three general factors – clarity of design, interaction with instructors, and active discussion among course participants – significantly influenced students’ satisfaction and perceived learning. Such findings are related to various kinds of interactivity and a ‘community of inquiry’ model of online learning.
Cross-layer Design of CSMA/CA with Spectrum Sensing for Cognitive Radio Networks

We devise a cross-layer design (CLD) of carrier sensing multiple access with collision avoidance (CSMA/CA) at the medium access control (MAC) layer with spectrum sensing (SpSe) at the physical layer for cognitive radio networks (CRNs). The proposed CLD relies on a Markov chain model with a state pair containing both the SpSe and the CSMA/CA with exponential backoff from which we derive the transmission and collision probabilities. Due to the 2-dimensions of CSMA/CA model with exponential backoff, the resulted Markov chain is obtained with 3-dimensions. Simulation and numerical results are derived and illustrated highlighting the impact of SpSe in CSMA/CA with exponential backoff. The obtained results could be used as performance criteria to evaluate the performance of specific CRNs when they are deployed in a distributed coordination fashion that is prone to collisions. Keywords— cross-layer design, CSMA/CA, spectrum sensing, Markov chain, cognitive radio networks.
Dnmt1 Overexpression Causes Genomic Hypermethylation, Loss of Imprinting, and Embryonic Lethality

ABSTRACT Biallelic expression of Igf2 is frequently seen in cancers because Igf2 functions as a survival factor. In many tumors the activation of Igf2 expression has been correlated with de novo methylation of the imprinted region. We have compared the intrinsic susceptibilities of the imprinted region of Igf2 and H19, other imprinted genes, bulk genomic DNA, and repetitive retroviral sequences to Dnmt1 overexpression. At low Dnmt1 methyltransferase levels repetitive retroviral elements were methylated and silenced. The nonmethylated imprinted region of Igf2 and H19 was resistant to methylation at low Dnmt1 levels but became fully methylated when Dnmt1 was overexpressed from a bacterial artificial chromosome transgene. Methylation caused the activation of the silent Igf2 allele in wild-type and Dnmt1 knockout cells, leading to biallelic Igf2 expression. In contrast, the imprinted genes Igf2r, Peg3, Snrpn, and Grf1 were completely resistant to de novo methylation, even when Dnmt1 was overexpressed. Therefore, the intrinsic difference between the imprinted region of Igf2 and H19 and of other imprinted genes to postzygotic de novo methylation may be the molecular basis for the frequently observed de novo methylation and upregulation of Igf2 in neoplastic cells and tumors. Injection of Dnmt1-overexpressing embryonic stem cells in diploid or tetraploid blastocysts resulted in lethality of the embryo, which resembled embryonic lethality caused by Dnmt1 deficiency.
Churn Prediction in Mobile Social Games: Towards a Complete Assessment Using Survival Ensembles

Reducing user attrition, i.e. churn, is a broad challenge faced by several industries. In mobile social games, decreasing churn is decisive to increase player retention and rise revenues. Churn prediction models allow to understand player loyalty and to anticipate when they will stop playing a game. Thanks to these predictions, several initiatives can be taken to retain those players who are more likely to churn. Survival analysis focuses on predicting the time of occurrence of a certain event, churn in our case. Classical methods, like regressions, could be applied only when all players have left the game. The challenge arises for datasets with incomplete churning information for all players, as most of them still connect to the game. This is called a censored data problem and is in the nature of churn. Censoring is commonly dealt with survival analysis techniques, but due to the inflexibility of the survival statistical algorithms, the accuracy achieved is often poor. In contrast, novel ensemble learning techniques, increasingly popular in a variety of scientific fields, provide high-class prediction results. In this work, we develop, for the first time in the social games domain, a survival ensemble model which provides a comprehensive analysis together with an accurate prediction of churn. For each player, we predict the probability of churning as function of time, which permits to distinguish various levels of loyalty profiles. Additionally, we assess the risk factors that explain the predicted player survival times. Our results show that churn prediction by survival ensembles significantly improves the accuracy and robustness of traditional analyses, like Cox regression.
Seamless vertical handover management for VoIP over intermingled IEEE 802.11g and IEEE 802.16e

Heterogeneous wireless access networks will be deployed in many areas. IEEE802.11g and IEEE802.16e will become key technologies as means of providing wireless broadband access to mobile users. These two different wireless access technologies will co-exist while complementing each other in the near future; hence, a mobile node (MN) with dual interfaces will likely execute many handovers (HOs) between 802.11g and 802.16e networks with different IP subnets. In this paper, we propose an end-to-end vertical HO management (HM) for VoIP over the intermingled 802.11g and 802.16e networks considering the wireless link condition and congestion state of both wireless networks. The HM exploits RTS retries and RTT between an MN and an access point in an 802.11g interface as well as CINR level and MN queue length of an 802.16e interface as HO decision criteria. We then conducted simulation experiments to evaluate the effectiveness of our proposed vertical HM using Qualnet 4.5. Our simulation results show that our proposed HM can preserve VoIP quality during such HOs.
In Vitro Study of Stromal Cell Defects in Myelodysplastic Syndromes

haematologica/journal of hematology vol. 88(07):july 2003 827 in normal erythroid progenitors. This agent, with its four pyrrole rings, was more active than tallimustine2 or hydroxyurea, the drug currently used for HbF enhancement in β-thalassemia and sickle-cell disease.3 In addition to increasing γ-globin mRNA synthesis, this agent also increased β-globin mRNA, but only slightly increased α-globin mRNA. Since these DNA-binding molecules are cytotoxic,2 chemical modifications will be required to reduce their toxicity. In this respect, our study should be considered as a basis for further efforts to develop agents for hematologic diseases in which the induction of both γ-globin and β-globin genes could be clinically relevant.
Fixed-point DSP implementation of wavelet decomposition for image processing

Real time implementation of wavelet transformations is becoming of great importance, since it is one of the key elements of JPEG2000 and MPEG4 encoding operations. This paper details a dedicated wavelet decomposition implementation for ADSP-BF533 and ADSP-BF561 fixed-point DSPs, and reports experimental results on several test images.
Spatial filter subspace optimization based on mutual information

Discriminating EEG signals between different motor imagery states is an important application of brain computer interface (BCI). However, low signal-to-noise ratio and significant data variation of EEG make it very difficult for BCI to obtain reliable results. Spatial filtering is one of the most successful feature extraction methods, and many efforts have been made to construct spatial filters that are robust against the data nonstationarity. In this paper, we propose a novel spatial filter optimization method based on mutual information which is estimated by Gaussian functions instead of Parzen window. We analyze the relationship between the mutual information and feature distance using a simulation study to show that optimization based on mutual information can contribute to feature stationarity. Moreover, we also evaluate the proposed method on a real world motor imagery EEG data set recorded from 16 subjects performing motor imagery or staying in idle state. The experimental results validate the effectiveness of the proposed spatial filter optimization method as it outperforms both the common spatial pattern analysis and filter-bank common spatial pattern analysis.
On tuning of self-quotient ε-filter and support vector machine and its application to noise robust human detection

This paper introduces a tuning algorithm of self-quotient ε-filter (SQEF) and support vector machine (SVM), and its application to noise robust human detection combining SQEF, histograms of oriented gradients (HOG), and SVM. Although human detection combining HOG and SVM is a powerful approach, as it uses local intensity gradients, it is difficult to handle noise corrupted images. On the other hand, although human detection combining SQEF, HOG and SVM can realize noise robust human detection, SQEF requires manual parameter setting. Our aim is not only to set the parameter of self-quotient e-filter but also to train SVM by using numerous images without noise and a small amount of images with noise.
Fabrication and Characterization of an Integrated Microsystem for Protein Preconcentration and Sensing

We report on a fabrication and packaging process for a microsystem consisting of a mass-based protein detector and a fully integrated preconcentrator. Preconcentration of protein is achieved by means of a nanofluidic concentrator (NC), which takes advantage of fast nonlinear electroosmotic flow near a nanochannel-microchannel junction to concentrate charged molecules inside a volume of fluid on the order of 1 pL. Detection of preconcentrated protein samples is accomplished by passing them through a suspended microchannel resonator (SMR), which is a hollow resonant cantilever serially connected to the NC on the same device. The transit of a preconcentrated sample produces a transient shift in the cantilever's resonance frequency that is proportional to the density of the sample and, hence, the concentration of protein contained in it. A device containing both NC and SMR structures was produced using a novel fabrication process which simultaneously satisfies the separate packaging requirements of the two structures. The initial testing of this prototype device has demonstrated that the integrated SMR can accurately measure the concentration of a bovine serum albumin solution, that was preconcentrated using the integrated NC. Future improvements in the fabrication process will allow site-specific surface modification of the device and compatibility with separation methods, which will create opportunities for its application to immunoassays and universal detection.
Dexmedetomidine for sedation of patients undergoing elective surgery under regional anesthesia

Background Dexmedetomidine may be useful as a sedative agent. However, it has been reported that dexmedetomidine decreases systemic blood pressure, heart rate, and cardiac output in a dose-dependent manner. The purpose of this study was to determine the appropriate dose of intravenously administered dexmedetomidine for sedation. Methods Forty-five American Society of Anesthesiologists physical status I-II patients under spinal anesthesia received dexmedetomidine 1 µg/kg intravenously as a loading dose. The patients were randomly allocated to one of three groups for maintenance dose: Group A (0.25 µg/kg/hr), Group B (0.50 µg/kg/hr), and Group C (0.75 µg/kg/hr). The hemodynamic variables and the Ramsay Sedation Scale (RSS) score were recorded for all patients. The numbers of patients who developed hypotension, bradycardia, or inadequate sedation necessitating further drug treatment were also recorded. Results Systolic blood pressure, heart rate, and SpO2 were decreased, and RSS score was increased significantly at both 20 min and 40 min after injection of dexmedetomidine in the three study groups compared to baseline, without significant differences between the groups. The prevalence of hypotension, but not that of bradycardia or adjunctive midazolam administration, exhibited a positive correlation with the dose of dexmedetomidine. Conclusions Intravenous injection of dexmedetomidine 1 µg/kg followed by continuous administration at infusion rates of 0.25, 0.50, or 0.75 µg/kg/hr produced adequate levels of sedation. However, there was a tendency for the incidence of hypotension to increase as the dose increased. To minimize the risk of hemodynamic instability, a dose of 0.25 µg/kg/hr may be the most appropriate for continuous administration of dexmedetomidine.
Enforcing spatial constraints for mobile RBAC systems

Proposed models for spatially-aware extensions of role-based access control (RBAC) combine the administrative and security advantages of RBAC with the dynamic nature of mobile and pervasive computing systems. However, implementing systems that enforce these models poses a number of challenges. As a solution, we propose an architecture for designing such a system. The architecture is based on an enhanced RBAC model that supports location-based access control policies by incorporating spatial constraints. Enforcing spatially-aware RBAC policies in a mobile environment requires addressing several challenges. First, one must guarantee the integrity of a user's location during an access request. We adopt a proximity-based solution using Near-Field Communication (NFC) technology. The next challenge is to verify the user's position continuously satisfies the location constraints. To capture these policy restrictions, we incorporate elements of the UCON_ABC usage control model in our architecture. In this work, we also propose a number of protocols, describe our prototype implementation, report the performance of our prototype, and evaluate the security guarantees.
A Source Routing Interference-Aware Multi-Path Routing Protocol for Mobile Ad Hoc Networks

In the literature, several Interference-Aware Multi-path Protocols have been introduced for Mobile Ad hoc NETworks (MANETs) but they are either not highly efficient or have the computational complexity of NP-hard. To tackle the problems, in this paper, we propose a novel Source Routing Interference-Aware Multi-path Protocol (SR-IA-MPOLSR) for mobile ad hoc networks. Our protocol uses source routing mechanism, parallel transmission via the minimal interference paths and adapts quickly to the change of topology in MANETs. The other strong point of SR-IAMPOLSR is that it finds paths with the computational complexity in polynomial time instead of NP-hard of other protocols. We compare our protocol to two typical protocols AOMDV (multipath protocol) and DSR in terms of packet delivery fraction, end-to-end delay, and routing overhead when the RTS/CTS mechanism is alternatively enabled and disabled. From simulation results, we show that SR-IA-MPOLSR significantly improves the network performance. We also prove the the network performance is reduced when RTS/CTS mechanism is used.
Educational Leadership to Create Authentic Inclusive Schools: The Experiences of Principals in a Canadian Rural School District.

Inclusive education—based on the premise of social justice—advocates equal ac-cess to educational opportunities for all students. Thi s research provides insight into the inclusive experiences of school principals in a Canadian rural school dis-trict through quantitative and qualitative inquiries. A survey was administered to 16 school administrators, and following initial data analysis, individual inter-views with four school principals were carried out as part of a multi-perspective case study of students with special needs. Overall, inclusion was viewed in a posi-tive light and extended beyond classroom placement to meeting the needs of diverse groups of students within the regular classroom. The r esponsibilities and strategies of the principals that support inclusion are outlined and other factors that contribute to effe ctive inclusion identifie d. Key
Indoor localization in multi-floor environments with reduced effort

In pervasive computing, localizing a user in wireless indoor environments is an important yet challenging task. Among the state-of-art localization methods, fingerprinting is shown to be quite successful by statistically learning the signal to location relations. However, a major drawback for fingerprinting is that, it usually requires a lot of labeled data to train an accurate localization model. To establish a fingerprinting-based localization model in a building with many floors, we have to collect sufficient labeled data on each floor. This effort can be very burdensome. In this paper, we study how to reduce this calibration effort by only collecting the labeled data on one floor, while collecting unlabeled data on other floors. Our idea is inspired by the observation that, although the wireless signals can be quite different, the floor-plans in a building are similar. Therefore, if we co-embed these different floors' data in some common low-dimensional manifold, we are able to align the unlabeled data with the labeled data well so that we can then propagate the labels to the unlabeled data. We conduct empirical evaluations on real-world multi-floor data sets to validate our proposed method.
Predicted Structures and Dynamics for Agonists and Antagonists Bound to Serotonin 5-HT2B and 5-HT2C Receptors

Subtype 2 serotonin (5-hydroxytryptamine, 5-HT) receptors are major drug targets for schizophrenia, feeding disorders, perception, depression, migraines, hypertension, anxiety, hallucinogens, and gastrointestinal dysfunctions. (1) We report here the predicted structure of 5-HT2B and 5-HT2C receptors bound to highly potent and selective 5-HT2B antagonist PRX-08066 3, (pKi: 30 nM), including the key binding residues [V103 (2.53), L132 (3.29), V190 (4.60), and L347 (6.58)] determining the selectivity of binding to 5-HT2B over 5-HT2A. We also report structures of the endogenous agonist (5-HT) and a HT2B selective antagonist 2 (1-methyl-1-1,6,7,8-tetrahydro-pyrrolo[2,3-g]quinoline-5-carboxylic acid pyridine-3-ylamide). We examine the dynamics for the agonist- and antagonist-bound HT2B receptors in explicit membrane and water finding dramatically different patterns of water migration into the NPxxY motif and the binding site that correlates with the stability of ionic locks in the D(E)RY region.
Improvement of Heterogeneous Systems Efficiency Using Self-Configurable FPGA-based Computing

Computer systems performance is is being improved today using two major approaches: general-purpose computers computing power increase (creation of multicore processors, multiprocessor computer systems, supercomputers), and adaptation of the computer hardware to the executed algorithm (class of algorithms). Last approach often provides application of the ASIC-based and FPGA-based hardware accelerators, also called reconfigurable, and is characterized by better performance / power consumption ratio and lower cost as compared to the general-purpose computers of equivalent performance. However, such systems have typical problems. The ASIC-based accelerators: 1) are effective for certain classes of algorithms only and 2) algorithms and software require adaptation for effective application. The FPGA-based accelerators and reconfigurable computer systems (that use FPGAs as a processing unit): 1) in the process of writing require a special program to perform computing tasks balancing between the general-purpose computer and FPGAs; 2) require designing the application-specific processor soft-cores; and 3) are effective for certain classes of problems only, for which application-specific processor soft-cores were previously developed. In this paper, we consider an emerging type of high-performance computer systems called self-configurable FPGA-based computer systems, which are deprived of specified challenges. We have analyzed the background of self-configurable computer systems creation, presented current results of our research, and introduced some ongoing works. Self-configurable computer systems are being developed within the project entitled "Improvement of heterogeneous systems efficiency using self-configurable FPGA-based computing" that is the part of the NESUS Action.
Rendering geometry with relief textures

We propose to render geometry using an image based representation. Geometric information is encoded by a texture with depth and rendered by rasterizing the bounding box geometry. For each resulting fragment, a shader computes the intersection of the corresponding ray with the geometry using pre-computed information to accelerate the computation. Our method is almost always artifact free even when zoomed in or at grazing angles. We integrate our algorithm with reverse perspective projection to represent a larger class of shapes. The extra texture requirement is small and the rendering cost is output sensitive, so our representation can be used to model many parts of a 3D scene.