Miracle-dz/UniFAR-FTUs huggingface dataset:
An efficient proactive route maintenance process for reliable data transmissions in sensor networks

For industrial wireless sensor networks, maintaining the routing path for a high packet delivery ratio is one of the key objectives in network operations. It is important to both provide the high data delivery rate at the sink node and guarantee a timely delivery of the data packet at the sink node. Most proactive routing protocols for sensor networks are based on simple periodic updates to distribute the routing information. A faulty link causes packet loss and retransmission at the source until periodic route update packets are issued and the link has been identified as broken. We propose a new proactive route maintenance process where periodic update is backed-up with a secondary layer of local updates repeating with shorter periods for timely discovery of broken links. Proposed route maintenance scheme improves reliability of the network by decreasing the packet loss due to delayed identification of broken links. We show by simulation that proposed mechanism behaves better than the existing popular routing protocols (AODV, AOMDV and DSDV) in terms of end-to-end delay, routing overhead, packet reception ratio.
Dendritic spine density of prefrontal layer 6 pyramidal neurons in relation to apical dendrite sculpting by nicotinic acetylcholine receptors

Prefrontal layer 6 (L6) pyramidal neurons play an important role in the adult control of attention, facilitated by their strong activation by nicotinic acetylcholine receptors. These neurons in mouse association cortex are distinctive morphologically when compared to L6 neurons in primary cortical regions. Roughly equal proportions of the prefrontal L6 neurons have apical dendrites that are “long” (reaching to the pial surface) vs. “short” (terminating in the deep layers, as in primary cortical regions). This distinct prefrontal morphological pattern is established in the post-juvenile period and appears dependent on nicotinic receptors. Here, we examine dendritic spine densities in these two subgroups of prefrontal L6 pyramidal neurons under control conditions as well as after perturbation of nicotinic acetylcholine receptors. In control mice, the long neurons have significantly greater apical and basal dendritic spine density compared to the short neurons. Furthermore, manipulations of nicotinic receptors (chrna5 deletion or chronic developmental nicotine exposure) have distinct effects on these two subgroups of L6 neurons: apical spine density is significantly reduced in long neurons, and basal spine density is significantly increased in short neurons. These changes appear dependent on the α5 nicotinic subunit encoded by chrna5. Overall, the two subgroups of prefrontal L6 neurons appear positioned to integrate information either across cortex (long neurons) or within the deep layers (short neurons), and nicotinic perturbations differently alter spine density within each subgroup.
FEA1, FEA2, and FRE1, Encoding Two Homologous Secreted Proteins and a Candidate Ferrireductase, Are Expressed Coordinately with FOX1 and FTR1 in Iron-Deficient Chlamydomonas reinhardtii

ABSTRACT Previously, we had identified FOX1 and FTR1 as iron deficiency-inducible components of a high-affinity copper-dependent iron uptake pathway in Chlamydomonas. In this work, we survey the version 3.0 draft genome to identify a ferrireductase, FRE1, and two ZIP family proteins, IRT1 and IRT2, as candidate ferrous transporters based on their increased expression in iron-deficient versus iron-replete cells. In a parallel proteomic approach, we identified FEA1 and FEA2 as the major proteins secreted by iron-deficient Chlamydomonas reinhardtii. The recovery of FEA1 and FEA2 from the medium of Chlamydomonas strain CC425 cultures is strictly correlated with iron nutrition status, and the accumulation of the corresponding mRNAs parallels that of the Chlamydomonas FOX1 and FTR1 mRNAs, although the magnitude of regulation is more dramatic for the FEA genes. Like the FOX1 and FTR1 genes, the FEA genes do not respond to copper, zinc, or manganese deficiency. The 5′ flanking untranscribed sequences from the FEA1, FTR1, and FOX1 genes confer iron deficiency-dependent expression of ARS2, suggesting that the iron assimilation pathway is under transcriptional control by iron nutrition. Genetic analysis suggests that the secreted proteins FEA1 and FEA2 facilitate high-affinity iron uptake, perhaps by concentrating iron in the vicinity of the cell. Homologues of FEA1 and FRE1 were identified previously as high-CO2-responsive genes, HCR1 and HCR2, in Chlorococcum littorale, suggesting that components of the iron assimilation pathway are responsive to carbon nutrition. These iron response components are placed in a proposed iron assimilation pathway for Chlamydomonas.
Analysing automatic descriptions of intonation with ICARUS

We present ICARUS for intonation ‐ a graphical tool which allows to access automatically derived F0 features in an intuitive and user-friendly way. It can be used for data exploration and search. Tonal features can be accessed together with information from other linguistic levels; this is exemplified in two search queries where we combine the search for a specific tonal contour with a) coreference annotations and b) automatically derived syntactic annotations. Thereby we demonstrate how ICARUS for intonation bridges the gap between manual/semiautomatic analysis of relatively small, manually annotated data sets and automatic analysis of larger corpora with automatically derived features. Index Terms: Intonation, parametric F0 analysis, multi-level annotations, syntax interface, semantic interface
A Comparison of Subjective Experiences and Responses to Austerity of UK and Greek Youth

Following previous research carried out by Chalari (2014; 2015), this qualitative study explores the ways in which the younger generation in Greece and UK has been affected by austerity policy measures. These two countries have been at the forefront of intense social, political and economic transformations that have impacted particularly on young people’s current and future lives. This study aims to explore similarities and differences in young people’s subjective experiences and responses, as from this it may be possible to discern whether there is a general, long-term negative effect of austerity across Europe. The data shows that there are some similarities in the two cohorts’ subjective experiences and responses, but perhaps more interestingly some significant differences. The study discusses what the implications of these differences might be for young people and society in these countries, in terms of their impact on the abilities of the younger generation, in a way that has the potential to destabilize their personal and professional lives now and in the future.
On-Line Models for Use in Automated Fault Detection and Diagnosis for HVAC & R Equipment

To improve overall fault detection and diagnostic (FDD) performance, many of the techniques proposed for automated FDD rely on the use of steady-state models for expected values of operating states under normal operating conditions. Furthermore, on-line measurements and models for overall performance (e.g., EER) are useful in evaluating whether faults are serious enough for service to be performed. This paper presents a modeling approach for operating temperatures that combines a low-order polynomial with a general regression neural network (GRNN) to achieve both good interpolating and extrapolating performance. Using experimental data for a rooftop air conditioner, the performance of this modeling approach was evaluated and compared with several other black-box modeling approaches, including simple polynomials, pure general regression neural networks (GRNN), back-propagation neural networks, and radial-basis functions. This approach was further validated using data collected from a field site at Purdue University. In addition, a simple method for estimating cooling capacity, power consumption, and EER using low-cost measurements is presented and evaluated.
Prudence, Personality, Cognitive Ability and Emotional State

We report an experiment to consider the emotional correlates of prudent decision making. In the experiment, we present subjects with lotteries and measure their emotional response with facial recognition software. They then make binary choices between risky lotteries that distinguish prudent from imprudent individuals. They also perform tasks to measure their cognitive ability and a number of personality characteristics. We find that a more negative emotional state correlates with greater prudence. Higher cognitive ability and less conscientiousness is also associated with greater prudence.
Game balancing with ecosystem mechanism

To adapt game difficulty upon game character's strength, Dynamic Difficulty Adjustment (DDA) and some other learning strategies have been applied in commercial game designs. However, most of the existing approaches could not ensure diversity in results, and rarely attempted to coordinate content generation and behaviour control together. This paper suggests a solution that is based on multi-level swarm model and ecosystem mechanism, in order to provide a more flexible way of game balance control.
Path planning simulation for 3D ultrasound guided needle biopsy system

We propose a path planning simulation system for 3D ultrasound guided needle biopsy, this system is designed to accurately take a 3D biopsy specimen from an abdominal focal lesion without puncturing a blood vessel or pass through ribs, the introduced system traces the 3D position of the biopsy needle and visualizes the needle in 3D and 2D in real time format, this new designed system gives the physician the optimal pathway to get a biopsy before puncturing the patient and visualizes this pathway in real time during the flythrough movement. Real time visualization of the needle in MPR and 3D volume of interest is performed. Experimental results on an in-vitro phantoms and after path phantoms showed promising results of this system
Robust engine speed control based on nonlinear Takagi-Sugeno fuzzy systems with time-delay

In this study, the engine speed control algorithm is developed. The system augmented method based on the local linearized dynamic internal combustion engine model is presented for design of feedback controller without steady-state error. For multi-operating points local linearization of engine model the Takagi-Sugeno (T-S) fuzzy models with time-delay are presented, and the stability conditions are derived using Lyapunov-Krasovskii approach. The stabilizing fuzzy state feedback controllers are presented for time-delay fuzzy systems with disturbance, and the property of robust Hinfin disturbance attenuation is introduced. Finally, simulations attest to the properties of these methods.
Layer Design of Semiconductor Disk Lasers 41 Layer Design of Highly Efficient Optically Pumped Semiconductor Disk Lasers

Optically pumped semiconductor disk lasers (OPSDLs) with extended cavities are surfaceemitting laser devices which efficiently convert the low-beam-quality emission of a pump laser to a high-beam-quality circular non-astigmatic laser emission. Furthermore, the extended cavity can be utilized for intra-cavity second harmonic generation by insertion of nonlinear optical crystals. By that way, the range of usable wavelengths is drastically expanded from the near infrared to the visible range of the optical spectrum [1–5].
International Journal of Nanomedicine Dovepress Preparation, Characterization and Relative Bioavailability of Oral Elemene O/w Microemulsion

The objective was to develop an elemene oil/water (o/w) microemulsion and evaluate its characteristics and oral relative bioavailability in rats. Elemene was used as the oil phase and drug, polysorbate 80 as a surfactant along with ethanol, propylene glycol, and glycerol as the cosurfactants. The microemulsion was prepared by mixing method, or ultrasonication method in an ultrasonic bath. Its three-dimensional response surface diagram was drawn by Mathcad software. The microemulsion was characterized by visual observation, cross-polarized microscopy, size, zeta potential, acidity, viscosity, and surface tension measurement. The drug content and entrapment efficiency were determined by ultra fast liquid chromatography (UFLC) and liquid surface method. Blood was drawn from rats at different time points after oral administration of an elemene microemulsion or a commercial elemene emulsion for measurement of the drug in plasma by UFLC to establish the pharmacokinetic parameters and relative bioavail-ability. The elemene microemulsion as a clarified and isotropic system containing 1% elemene (w/v), 5% ethanol (v/v), 15% propylene glycol (v/v), 15% glycerol (v/v), and 5% polysorbate 80 (w/v), was characterized as (57. in surface tension, (8.273 ± 0.018) mg⋅mL-1 in content of β-elemene, and (99.81 ± 0.24)% in average entrapment efficiency. The area under the concentration-time curves from 0 h to 24 h (AUC 0→24h) of the elemene microemulsion and commercial elemene emulsion were integrated to be 3.092 mg⋅h⋅L-1 and 1.896 mg⋅h⋅L-1 respectively, yielding a relative bioavailability of 163.1%. The present study demonstrates the elemene microemulsion as a new formulation with ease of preparation, high entrapment efficiency, excellent clarity, good stability, and improved bioavailability.
Using Edge Histogram Models to solve Flow shop Scheduling Problems with Probabilistic Model-Building Genetic Algorithms

In evolutionary algorithms based on probabilistic modeling, the offspring population is generated according to the estimated probability density model of the parent instead of using recombination and mutation operators. In this chapter, we have proposed a probabilistic model-building genetic algorithms (PMBGAs) for solving flow shop scheduling problems using edge histogram based sampling algorithms (EHBSAs). The effectiveness of introducing the tag node (TN) in a string representation is also discussed.
The Importance of Repressor-Activator Balance in Various Models of Repression for Circadian Clocks

To understand protein networks, scientists use mathematical models to simulate the various molecules and their interactions. These mathematical models are differential equations for the concentrations of molecules over time. When constructing a model, it is important to choose a level of abstraction that makes models as simple as possible, without losing their key robustness properties. For oscillating systems, the ability to maintain oscillations is key. In a recent publication Kim and Forger (2012) discuss the relationship between the ratio of repressor and activator proteins and the robustness of a systems oscillations and conclude that a 1:1 ratio is best. Here, we examine three additional models of circadian processes (Leloup and Goldbeter, 2003; Mirsky et al., 2009; and Ueda et al. 2001) and seek to determine which model structures lead to the situation in which a 1:1 repressor to activator ratio gives rise to a more robust system. For each of the models, we modify the mode of repression using three different levels of abstraction: explicit sequestration, implicit sequestration, and direct Hill repression.
Optimizing rectangular partitions of histograms

The problem of partitioning isothetic polygons into rectangles, where the goal is to minimise the total length of the partition, has some applications in VLSIcircuit design and construction. If these polygons have holes inside, the problem becomes NP-hard, instead, in the case of hole-free polygons, an optimal partition can be computed in O(n4) exploiting dynamic programming. In this thesis, I focus my attention on rectangular partitions of histograms, which are special cases of hole-free isothetic polygons, using the fact it's possible to partition them into histograms in linear time. I've used dynamic programming in order to produce optimal partitions and a parameterised approximation algorithm, a variant of the so called thickest first" algorithm. Then, I've compared experimentally these two algorithms to check theoretical bounds and to evaluate the goodness of the approximation algorithm, especially on some interesting histogram shapes like staircase and staircase united with its mirror image. In parallel, an interactive tool has been implemented, with a graphical representation, which can help users to visualise the differences between these methods. The implementation of the algorithms, the auxiliary structures and the GUI of the tool have been implemented with C++ and Qt graphics libraries.
Three Dimensional Broadcast Protocol forWireless Networks

We present three dimensional broadcast (3DB) a wireless protocol designed for communication among nodes in three dimensional space. 3DB can be used for a large variety of applications, with static or mobile nodes. However, in this paper we apply 3DB for communications among airplanes, to show that the protocol performs very good even in such difficult conditions. On the other hand, communications among aeroplanes is an important application. In this scenario, 3DB enables the broadcast of emergency and surveillance information such as real time video over the network even in presence of adverse conditions, such as coordinated terrorist attacks, which might have disrupted other communication ways. 3DB is very robust. 3DB minimizes the number of retransmissions and therefore reduce the collisions, which could considerably delay transmissions and disrupt the communications during emergency situations. 3DB performs very well in highly dynamic ad hoc networks of airplane. We have evaluated 3DB through analysis and ns-2 simulations.
Immune Based Clustering for Medical Diagnostic Systems

It has recently been shown that Artificial Immune Systems (AIS) can be successfully implemented as biologically inspired systems. The Artificial Immune Network (AIN) is one of the computationally intelligent systems that are inspired by the processes of the immune system. Many algorithms are used to exploit the immune system's characteristics of learning and memory. The aiNet is one of such AIS algorithms with excellent performance on elementary clustering tasks. This paper proposes the use of two clustering techniques (DBSCAN and K-MEANS) in combination with aiNet algorithm for medical diagnosis. Two standard data sets are used to evaluate the clustering performance. The results indicate that both clustering techniques produced closely related outcomes under the usage of aiNet algorithm. However, K-means showed higher accuracy and better percentage of total clustering than DBSCAN for both data sets.
Joint diagonalization: Is non-orthogonal always preferable to orthogonal?

This paper deals with the efficiency of orthogonal versus non-orthogonal joint diagonalization techniques for blind source separation. The question is: are non-orthogonal algorithms always preferable to orthogonal ones in practical noisy conditions? The two techniques are compared in terms of separation performance through numerical simulations with different levels of additive noise and numbers of samples. Both fourth-order and second-order blind source separation contexts are investigated.
A data mining approach for dyslipidemia disease prediction using carotid arterial feature vectors

In this paper, we proposed a useful methodology for the diagnosis of dyslipidemia disease by using novel various features of carotid arterial wall thickness. We measured and tested intima-media thickness of carotid arteries and used them as diagnostic feature vectors. In order to evaluate extracted various features, we tested on five classification methods and evaluated performance of classifiers. As a result, SVM and Neural Network algorithms (about 92%–98% goodness of fit) outperformed the other classifiers on those selected features.
Impact of the spatial context on human communication activity

Technology development produces terabytes of data generated by human activity in space and time. This enormous amount of data often called big data becomes crucial for delivering new insights to decision makers. It contains behavioral information on different types of human activity influenced by many external factors such as geographic information and weather forecast. Early recognition and prediction of those human behaviors are of great importance in many societal applications like health-care, risk management and urban planning, etc. In this paper, we investigate relevant geographical areas based on their categories of human activities (i.e., working and shopping) in order to understand human-environmental relationships. We use spectral clustering approach followed by k-means algorithm based on TF/IDF cosine similarity metric. We evaluate the quality of the relevant area clusters with a use of silhouette coefficients which are estimated based on the similarities of the mobile communication activity temporal patterns. The area clusters are further used to explain typical or exceptional communication activities. We demonstrate our study using a real dataset containing 1 million Call Detailed Records. This type of analysis and application is important for discovering hidden relationships and unknown correlations.
Catheter–tissue contact force for pulmonary veins isolation: a pilot multicentre study on effect on procedure and fluoroscopy time

Aims Catheter–tissue contact is critical for effective lesion creation in radiofrequency catheter ablation (RFCA). In a multicentre prospective study, we assessed the effect of direct contact force (CF) measurement on acute procedural parameters during RFCA of atrial fibrillation (AF). Methods and results A new open-irrigated tip catheter with CF sensing (SmartTouch™, Biosense Webster Inc.) was used. All the patients underwent the first ablation procedure for paroxysmal AF with antral pulmonary vein (PV) isolation, aiming at entry and exit conduction block in all PVs. Ninety-five patients were enroled in nine centres and successfully underwent ablation. Overall procedure time, fluoroscopy time, and ablation time were 138.0 ± 67.0, 14.3 ± 11.2, and 33.8 ± 19.4 min, respectively. The mean CF value during ablation was 12.2 ± 3.9 g. Force time integral (FTI) analysis showed that patients achieving a value below the median of 543.0gs required longer procedural (158.0 ± 74.0 vs. 117.0 ± 52.0 min, P = 0.004) and fluoroscopy (17.5 ± 13.0 vs. 11.0 ± 7.7 min, P = 0.007) times as compared with those in whom FTI was above this value. Patients in whom the mean CF during ablation was >20 g required shorter procedural time (92.0 ± 23.0 vs. 160.0 ± 67.0 min, P = 0.01) as compared with patients in whom this value was <10 g. Four groin haematomas were the only complications observed. Conclusion Contact force during RFCA for PV isolation affects procedural parameters, in particular procedural and fluoroscopy times, without increasing complications.
Intra and extravascular transmembrane signalling of angiopoietin-1-Tie2 receptor in health and disease

• Introduction • Background, structural characteristics and distribution of Tie2 • Background, structural characteristics and distribution of Ang‐1 • Regulation of Tie2 signalling • Physiological roles • Pathophysiological role ‐ Ang‐1‐Tie2R and rheumatoid arthritis ‐ Ang‐1‐Tie2 and cancer ‐ Ang‐1‐Tie2R and asthma ‐ Therapeutic implications • Conclusion
Texture Analysis of Smoke for Real-Time Fire Detection

Since the texture is an important feature of smoke, a novel method of texture analysis is proposed for real-time fire smoke detection. The texture analysis is based on gray level co-occurrence matrices (GLCM) and can distinguish smoke features from other none fire disturbances. For the realization of real-time fire detection, block processing technique is adopted and the computation of texture features is done to every block of image. Neural network is used to classify smoke texture features from none-smoke features and the fire alarm trigger is set according to the total smoke blocks in one frame. The accuracy of the method is discussed as a function of frames in the end.