Miracle-dz/UniFAR-FTUs huggingface dataset:
Behavioral Modeling and Predistortion of Power Amplifiers Under Sparsity Hypothesis

A simple and flexible technique for improving the modeling and predistortion of power amplifiers is presented. The technique, which relies on the sparsity assumption for the kernel coefficients of the full Volterra (FV) behavioral model, combines a greedy algorithm for the selection of the active coefficients, a maximum likelihood method for their estimation and an information criterion for determining the best model. The approach has been applied to the design of reduced-parameters FV-based digital predistorters for three power amplifiers driven with orthogonal frequency division multiplexing signals, following the LTE and DVB-T2 standards, and a multichannel wideband code-division multiple access signal. Results show that the proposed linearizers meet the spectral masks and error vector magnitude constraints of the referred standards and provide a reduction better than 45% in the number of parameters, compared to the FV predistorters.
Influence of Environmental Factors on Phage–Bacteria Interaction and on the Efficacy and Infectivity of Phage P100

When using bacteriophages to control food-borne bacteria in food production plants and processed food, it is crucial to consider that environmental conditions influence their stability. These conditions can also affect the physiological state of bacteria and consequently host–virus interaction and the effectiveness of the phage ability to reduce bacteria numbers. In this study we investigated the stability, binding, and replication capability of phage P100 and its efficacy to control Listeria monocytogenes under conditions typically encountered in dairy plants. The influences of SDS, Lutensol AO 7, salt, smear water, and different temperatures were investigated. Results indicate that phage P100 is stable and able to bind to the host under most conditions tested. Replication was dependent upon the growth of L. monocytogenes and efficacy was higher when bacterial growth was reduced by certain environmental conditions. In long-term experiments at different temperatures phages were initially able to reduce bacteria up to seven log10 units after 2 weeks at 4°C. However, thereafter, re-growth and development of phage-resistant L. monocytogenes isolates were encountered.
DNA adducts and carcinogenicity of nitro-polycyclic aromatic hydrocarbons.

We have been interested in the structure-activity relationships of nitro-polycyclic aromatic hydrocarbons (nitro-PAHs), and have focused on the correlation of structural and electronic features with biological activities, including mutagenicity and tumorigenicity. In our studies, we have emphasized 1-, 2-, 3-, and 6-nitrobenzo[a]pyrenes (nitro-B[a]Ps) and related compounds, all of which are derived from the potent carcinogen benzo[a]pyrene. While 1-, 2-, and 3-nitro-B[a]P are potent mutagens in Salmonella, 6-nitro-B[a]P is a weak mutagen. In vitro metabolism of 1- and 3-nitro-B[a]P has been found to generate multiple pathways for mutagenic activation. The formation of the corresponding trans-7,8-dihydrodiols and 7,8,9,10-tetrahydrotetrols suggests that 1- and 3-nitro-B[a]P trans-7,8-diol-9,10-epoxides are ultimate metabolites of the parent nitro-B[a]Ps. We have isolated a DNA adduct from the reaction between 3-nitro-B[a]P trans-7,8-diol-anti9,10-epoxide and calf thymus DNA, and identified it as 10-(deoxyguanosin-N2-yl)-7,8,9-trihydroxy-7,8,9,10-tetrahydro-3-ni tro-B[a]P . The same adduct was identified from in vitro metabolism of [3H]3-nitro-B[a]P by rat liver microsomes in the presence of calf thymus DNA. A DNA adduct of 3-nitro-B[a]P formed from reaction of N-hydroxy-3-amino-B[a]P, prepared in situ with calf thymus DNA was also isolated. This adduct was identified as 6-(deoxyguanosin-N2-yl)-3-amino-B[a]P. The same adduct was obtained from incubating DNA with 3-nitro-B[a]P in the presence of the mammalian nitroeductase, xanthine oxidase, and hypoxanthine. (ABSTRACT TRUNCATED AT 250 WORDS)
Hardware oriented re-design and matrix approximation analysis for transform in High Efficiency Video Coding (HEVC)

In this paper, we propose an adaptive truncate k-bit re-configurable approximation (aTra) method which can achieve similar video coding efficiency as the original transform but substitute all low efficient multiplication by conformed shifting and addition operations, lifting the utilization of the hardware implementation and making simple hardware implementation and high efficiency pipeline design possible. Also, we may be the first to propose three mathematical constraints for the hardware matrix approximation to make the final performance controllable. The proposed method can achieve regular data flow and massive operation reduction balancing the rate distortion (RD) performance and data throughput. Particularly for the current secondary transform, rotational transform (ROT), we obtain the hardware friendly ROT through our proposed method based on one of the constraints. The simulation results implemented in the HEVC reference software HM1.0 present the validity of our method. Our method achieves similar performance when compared with the original one but it is much better than the simple hardware implementation.
Reverse Engineering of Gene Regulatory Networks: A Comparative Study

Reverse engineering of gene regulatory networks has been an intensively studied topic in bioinformatics since it constitutes an intermediate step from explorative to causative gene expression analysis. Many methods have been proposed through recent years leading to a wide range of mathematical approaches. In practice, different mathematical approaches will generate different resulting network structures, thus, it is very important for users to assess the performance of these algorithms. We have conducted a comparative study with six different reverse engineering methods, including relevance networks, neural networks, and Bayesian networks. Our approach consists of the generation of defined benchmark data, the analysis of these data with the different methods, and the assessment of algorithmic performances by statistical analyses. Performance was judged by network size and noise levels. The results of the comparative study highlight the neural network approach as best performing method among those under study.
Studies on Immune Clonal Selection Algorithm and Application of Bioinformatics

Immune algorithms (IAs) are microscopic view of evolutionary algorithms (EAs) and applied in combi- natorial optimization problems. This paper addresses to a clonal selection algorithm (CSA) that is one of the most representative IA and was applied into the protein structure prediction (PSP) on AB off-lattice model, in which the memory B cells of the CSA was innovated by employing different strategies: local search and global search in the phase of the mutation. And the CSA was further improved by adding aging operator to combat the premature con- vergence. However the pure aging operator didn't achieve effective results and sometimes the optimum solution was eliminated. To resolve this problem, the current best solution was reserved by an antibody and it was not eliminated when its age reached its life span. In our experiments the improved algorithm was compared with the standard CSA and the pure aging CSA, which of the results demonstrated that the improved strategy with the memory B cells and long life aging was very effective to overcome premature convergence and to avoid trapped in the local-best solution, and it was also effective in keeping the diversity of the small size population. On the other hand, one novel hybrid algorithm Quantum Immune(QI), which combines Quantum Algorithm (QA) and Immune Clonal Selection(ICS) Al- gorithm, has been presented for dealing with multi-extremum and multi-parameter problem based on AB off-lattice model in the predicting 2D protein folding structure. Clonal Selection Algorithm was introduced into the hypermuta- tion operators in the Quantum Algorithm to improve the local search ability, and double chains quantum coded was designed to enlarge the probability of the global optimization solution. It showed that the solution mostly trap into the local optimum, to escape the local best solution the aging operator is introduced to improve the performance of the algorithm. Experimental results showed that the lowest energies and computing-time of the improved Quantum Clonal Selection(QCS) algorithm were better than that of the previous methods, and the QCS was further improved by adding aging operator to combat the premature convergence. Compared with previous approaches, the improved QCS algorithm remarkably enhanced the convergence performance and the search efficiency of the immune optimization algorithm.
Multimodal multi-user human-robot interface for virtual collaboration

We present a intuitive teleoperation scheme by using human gesture and multimodal multi-user human-robot interface. Further, in order to deal with the dynamic daily environment, we apply haptic point cloud rendering and virtual collaboration and all these functions are achieved by portable hardwares which is called “mobile iSpace”. First, a surrounding environment of a teleoperated robot is captured and reconstructed as the 3D point cloud using a depth camera. Virtual world is then generated from the 3D point cloud, and a virtual teleoperated robot model is placed in there. An user uses their own whole body gesture to teleoperate the humanoid type robot. The gesture is captured by the depth camera placed in user-side in real time. And the user has the visual and vibrotactile feedback at the same time by using a head mounted display and a vibrotactile glove. All these system components e.g. the human user, the teleoperated robot and the feedback devices are connected with the Internet-based virtual collaboration system to support a flexible accessibility. So eventually, this makes possible that users can access the remote placed robot whenever and wherever they want.
Cellular Source-Specific Effects of Apolipoprotein (Apo) E4 on Dendrite Arborization and Dendritic Spine Development

Apolipoprotein (apo) E4 is the leading genetic risk factor for Alzheimer’s disease (AD), and it has a gene dose-dependent effect on the risk and age of onset of AD. Although apoE4 is primarily produced by astrocytes in the brain, neurons can also produce apoE4 under stress conditions. ApoE4 is known to inhibit neurite outgrowth and spine development in vitro and in vivo, but the potential influence of apoE4’s cellular source on dendritic arborization and spine development has not yet been investigated. In this study, we report impairments in dendritic arborization and a loss of spines, especially thin (learning) and mushroom (memory) spines, in the hippocampus and entorhinal cortex of 19–21-month-old female neuron-specific-enolase (NSE)-apoE4 and apoE4-knockin (KI) mice compared to their respective apoE3-expressing counterparts. In general, NSE-apoE4 mice had more severe and widespread deficits in dendritic arborization as well as spine density and morphology than apoE4-KI mice. The loss of dendritic spines, especially mushroom spines, occurred in NSE-apoE4 mice as early as 7–8 months of age. In contrast, glial fibrillary acidic protein (GFAP)-apoE4 mice, which express apoE4 solely in astrocytes, did not have impairments in their dendrite arborization or spine density and morphology compared to GFAP-apoE3 mice at both ages. These results indicate that the effects of apoE4 on dendrite arborization, spine density, and spine morphology depend critically on its cellular source, with neuronal apoE4 having more detrimental effects than astrocytic apoE4.
Feature weighting for case-based reasoning software project effort estimation

Background: Software effort estimation is one of the most important activities in software development process. Unfortunately, estimates are often substantially wrong and specifically most projects encounter effort overruns. Numerous methods have been proposed including Case based reasoning (CBR). Existing research shows that feature subset selection (FSS) is an important aspect of CBR, however, searching for the optimal feature weights is a combinatorial problem and therefore NP-hard. Objective: To develop and evaluate efficient algorithms to generalise FSS into an effective feature weighting approach that can improve accuracy further, since not all features contribute equally to solving the problem. Method: Use various search algorithms e.g., forward sequential weighting (FSW) and random mutation hill climbing (RMHC) to assign weight to features in order to improve the estimation accuracy. We will extend an existing CBR java shell ArchANGEL. We will perform experiments based on repeated measures design on real world datasets to evaluate these algorithms. Limitations of the proposed research: Dataset quality cannot be assured therefore our findings could be influenced by noisy data. Older datasets may be misrepresenting current software development approaches and technologies. CBR could be sensitive to the choice of distance metric; however, we will only use standardised Euclidean distance.
Fuzzy rules of sound speed influence on ultrasonic sensing in outdoor environments

The sound speed is affected by changes in the air properties, such as temperature, pressure, humidity, gas composition, and air turbulence. It has direct influence on the accuracy of distance measuring and the sound wavelength. For many indoor applications, the sound speed in air is considered as constant. For outdoor environments, a constant sound speed generates important errors of distance estimation. Also, for low temperature values, the real distance is smaller than measured distance, and this can be a dangerous situation. The pressure influence on sound speed can be neglected, and the sound speed depends on temperature and relative humidity. In this paper, variations in the speed of sound as a function of air properties are studied, along with their influence on the accuracy of ultrasonic sensing. In addition, fuzzy rules are generated for sound speed values used in outdoor applications.
Echocardiographic tissue deformation imaging of right ventricular systolic function in endurance athletes.

AIMS To investigate the physiological adaptation of the right ventricle (RV) in response to endurance training and to define reference values for regional deformation in the RV in endurance athletes. METHODS AND RESULTS Healthy controls (n = 61), athletes (n = 58), and elite athletes (n = 63) were prospectively enrolled with a training intensity of 2.2 +/- 1.6, 12.5 +/- 2.3 and 24.2 +/- 5.7 h/week, respectively (P < 0.001). Conventional echocardiographic parameters, tissue Doppler imaging (TDI), and 2D strain echo (2DSE)-derived velocity, strain, and strain rate (SR) were calculated in three RV segments. Left ventricular and RV dimensions were significantly increased (P < 0.001) in both groups of athletes compared with controls. Right ventricular systolic velocities and displacement were not different between the groups. Right ventricular strain and SR values were reduced in the RV basal and mid-segment in athletes. Athletes with marked RV dilatation showed lower strain and SR values in the basal (-20.9 +/- 4.7 vs. -24.5 +/- 4.9%, P < 0.001 and -1.23 +/- 0.31 vs. -1.50 +/- 0.33 s(-1), P < 0.001) and mid (-29.3 +/- 5.4 vs. -32.1 +/- 5.3%, P = 0.017 and -1.58 +/- 0.41 vs. -1.82 +/- 0.42 s(-1), P = 0.009) segment, whereas athletes without RV dilatation showed no significant difference compared with the controls. CONCLUSION Regional deformation and deformation rates (TDI and 2DSE) are reduced in the basal RV segment in athletes. This phenomenon is most pronounced in athletes with RV dilatation and should be interpreted as normal when evaluating athletes suspected for RV pathology.
Contribution à la continuité des flux d'informations et de connaissances dans le lien conception-production

Dans un contexte de la revolution de l'information numerique, les entreprises doivent proposer dans un temps court un systeme innovant de qualite et a moindre cout, et ce defi ne peut etre releve qu'avec des acteurs qui soient motives et qui collaborent ensemble. Les presents travaux de recherche visent donc a faciliter cette collaboration et le travail a valeur ajoutee, en contribuant a la continuite des flux d'informations et de connaissances. Au sein du LISMMA, nous avons decline ces travaux sur trois axes. Le premier axe vise a assurer les flux par l'interoperabilite des systemes d'information par la mediation et l'unification a base de standards. Le deuxieme axe se focalise sur la gestion des connaissances permettant aux flux d'etre compris et interpretes par les acteurs. Enfin, nous avons propose l'utilisation des ontologies pour assurer la coherence des informations transitant dans les flux. Ces travaux ont donne lieu au developpement de demonstrateurs, testes sur des cas industriels et/ou in-situ dans une entreprise.
A Markov-based framework for handover optimization in HetNets

The deployment of small cells in Heterogeneous Networks (HetNets) raises new challenges in relation to the Handover process and the mobility management. In fact, the performance of a mobile user within a HetNet scenario highly depends on the setting of the handover parameters in relation to other context parameters, such as the channel conditions and the user position and speed. In this paper, we derive a general theoretical analysis to characterize the user performance as a function of the mobility model, the power profile received from the neighboring cells, and the handover parameters. More in detail, we propose a Markov-based framework to model the user state during the handover process and, based on such model, we derive an optimal context-dependent handover criterion. The mathematical model is validated by means of simulations, showing that our strategy outperforms conventional handover optimization techniques by exploiting the context information.
Realistic Models of Neurons and Neuronal Networks

integrate and fire model#rate model#conductance models#synaptic model#multicompartment model integrate and fire model leaky integrate and fire model rate model synaptic input to the integrate and fire model conductance models kinetic models of ionic channels synaptic input to conductance models models of synaptic modification multicompartmental models This is an article that describes realistic models of neurons. The models range in complexity from the perfect integrate and fire model to conductance models in which the ionic currents are computed from the kinetics of the underlying gating particles.
Current Indications for Surgical Repair in Patients with Bicuspid Aortic Valve and Ascending Aortic Ectasia

Preventive surgical repair of the moderately dilated ascending aorta/aortic root in patients with bicuspid aortic valve (BAV) is controversial. Most international reference centers are currently proposing a proactive approach for BAV patients with a maximum ascending aortic/root diameter of 45 mm since the risk of dissection/rupture raises significantly with an aneurysm diameter >50 mm. Current guidelines of the European Society of Cardiology (ESC) and the joint guidelines of the American College of Cardiology (ACC)/American Heart Association (AHA) recommend elective repair in symptomatic patients with dysfunctional BAV (aortic diameter ≥45 mm). In asymptomatic patients with a well-functioning BAV, elective repair is recommended for diameters ≥50 mm, or if the aneurysm is rapidly progressing (rate of 5 mm/year), or in case of a strong family history of dissection/rupture/sudden death, or with planned pregnancy. As diameter is likely not the most reliable predictor of rupture and dissection and the majority of BAV patients may never experience an aortic catastrophe at small diameters, an overly aggressive approach almost certainly will put some patients with BAV unnecessarily at risk of operative and early mortality. This paper discusses the indications for preventive, elective repair of the aortic root, and ascending aorta in patients with a BAV and a moderately dilated—or ectatic—ascending aorta.
Implementation of a threaded dataflow multiprocessor using FPGAs

This paper presents the FPGA implementation and evaluation of the prototype for a Data-Driven Multithreading Chip-Multiprocessor. In particular, we study the implementation of a Thread Synchronization Unit (TSU) on FPGA, a hardware unit that enables thread execution using dataflow rules on a chip multiprocessor. Threads are scheduled for execution based on data availability, i.e. a thread is fired only if its input data is available. This model of execution is called the non-blocking Data-Driven Multithreading (DDM) model of execution. Due to its dataflow characteristics, this model exploits parallelism and tolerates latency. The DDM model has been evaluated using an execution driven simulator and showed and average speedup of 26 on a 32-node system. For evaluation purposes, implementation on Xilinx Virtex-5 FPGA using the Microblaze processors as execution cores has been performed. Experimental results show that the TSU can be implemented with a moderate hardware budget, and that delays incurred by the operation of the TSU can be tolerated. Furthermore, hardware complexity evaluation shows that the TSU size scales very well with the number of processors in the MPSoC.
Integration of interventional MRI with computer‐assisted surgery

Interventional MRI (IMRI) has entered into a new stage in which computer‐based techniques play an increasing role in planning, monitoring, and controlling the procedures. The use of interactive imaging, navigational image guidance techniques, and image processing methods is demonstrated in various applications. The integration of intraoperative MRI guidance and computer‐assisted surgery will greatly accelerate the clinical utility of image‐guided therapy in general and interventional MRI in particular. J. Magn. Reson. Imaging 2001;13:69–77. © 2001 Wiley‐Liss, Inc.
Precrash Dipping Nose (PCDN) Needs Pedestrian Recognition

This paper investigates the effect of vehicle front height lowering operation of precrash dipping nose (PCDN) on pedestrians. Although PCDN was developed for vehicle-vehicle side crashes, there is a possibility that the range sensor for crash detection will fail to distinguish a group of pedestrians from a side-faced vehicle. For simulation-based investigation, a vehicle model, an air spring with PCDN actuator, a pedestrian, and active hood system (AHS) were modeled. Two vehicle models were made for a sedan and a sport utility vehicle (SUV), respectively. In all crash situations (frontal crash without AHS, frontal crash with AHS, and side crash without AHS), a falsely operated PCDN is expected to cause worse pedestrian injury. As a conclusion, we insist that PCDN should incorporate a pedestrian-recognition capability into its crash detection system to reduce the improper activation of its actuator. In addition, as AHS showed a good performance even in improper activation, we propose a complementary method that activates AHS when PCDN is activated. It is noteworthy that the increasing importance of pedestrian protection seems to enforce even a system developed for vehicle-vehicle crashes to be investigated from the perspective of pedestrian safety.