Miracle-dz/UniFAR-FTUs huggingface dataset:
An interactive framework for online image annotation

Image annotation plays a very important role in managing and retrieving abundant images over the internet nowadays. In this paper, we try to propose a Human-Computer interactive framework for online image annotation which fully considers the human judgments and all online-users' feedback. First, an interactive image annotation interface is demonstrated. It is utilized to interact with online-users and collect the original manual annotations. Second, an object-based image annotation framework is proposed to provide the automatic results for users. Then, the users' feedback can be recorded and integrated to help our system to achieve performance improvement. Third, a comprehensive method of annotation refinement is developed to remove the noisy keywords. Finally, experimental results demonstrate the effectiveness of our proposed system.
Bistatic synthetic aperture target detection and imaging with an AUV

The acoustic detection and classification of completely and partially buried objects in the multipath environment of the coastal ocean presents a major challenge to the mine countermeasures (MCM) community. However, the rapidly emerging autonomous underwater vehicle (AUV) technology provides the opportunity of exploring entirely new sonar concepts based on mono-, bi- or multi-static configurations. For example, the medium frequency regime (1-10 kHz) with its bottom penetration advantage may be explored using large synthetic apertures, where acoustic information is accumulated over a series of sonar pings. The performance of such approaches is highly dependent on accurate platform navigation and timing, which poses a significant challenge to AUV developers, particularly because the navigation procedures are themselves dependent on the complicated multipath acoustic environment. Data from the GOATS'98 experiment have been analyzed to investigate the feasibility of combining seabed scattering data from consecutive pings of a fixed parametric source to form a bistatic synthetic aperture for target localization and imaging with an AUV based receiving platform. The paper describes different levels of bistatic processing including both incoherent and coherent beamforming and very large aperture interferometric approaches, and the associated performance tradeoffs are discussed.
A smart way to play using brain machine interface (BMI)

Brain machine interfacing (BMI) devices have become popular in resent years because of their inexpensive tool and are comfortable to use due to which the BMI could reach out the research world and enter into the outer world including entertainment. In this paper we had put forward the concept of brain machine interface (BMI) system for gaming application both in real and virtual world. The proposed system have the ability to control gaming applications by means of neuro signals acquired from human brain using commercially available wireless EEG headset. The signal acquisition seizes the neural activity of brain which is then preprocessed to boost up the SNR (signal to noise ratio). The preprocessed signal is then feature extracted to pick the necessary information and finally the classification stage switch the picked features into control commands and relays them to gaming application.
Murine cytotoxic T lymphocytes induced following Chlamydia trachomatis intraperitoneal or genital tract infection respond to cells infected with multiple serovars

The obligate intracellular bacterium Chlamydia trachomatis is associated with human diseases ranging from blinding trachoma to sexually acquired genital infections and the systemic disease lymphogranuloma venereum (LGV). We have previously reported the isolation and culture of protective murine cytotoxic T lymphocytes (CTL) following intraperitoneal infection with C. trachomatis serovar L2, a serotype associated with human LGV. In this report, we now demonstrate that CTL can also be primed following introduction of C. trachomatis serovar L2 into the uterus or ovarian bursa of mice. We also describe Chlamydia-specific CTL lines isolated following murine infection with a typical human urogenital isolate of C. trachomatis (serovar D) and show that such CTL can be primed by intraperitoneal, intrauterine, or intrabursal infection. Last, we demonstrate that these murine CTL lines respond to multiple serovars, recognizing and lysing cells infected with C. trachomatis serovars B, C, D, F, J, K, L2, and L3, representative of organisms causing blinding trachoma, genital infection, and LGV.
000000000000000 Printed in the United Kingdom Scaling Up Classification Rule Induction Through Parallel Processing

The fast increase in the size and number of databases demands data mining approaches that are scalable to large amounts of data. This has led to the exploration of parallel computing technologies in order to perform data mining tasks concurrently using several processors. Parallelisation seems to be a natural and cost effective way to scale up data mining technologies. One of the most important of these data mining technologies is the classification of newly recorded data. This paper surveys advances in parallelisation in the field of classification rule induction.
Mobility prediction-based smartphone energy optimization for everyday location monitoring

Monitoring a user's mobility during daily life is an essential requirement in providing advanced mobile services. While extensive attempts have been made to monitor user mobility, previous work has rarely addressed issues with battery lifetime in real deployment. In this paper, we introduce SmartDC, a mobility prediction-based adaptive duty cycling scheme to provide contextual information about a user's mobility: time-resolved places and paths. Unlike previous approaches that focused on minimizing energy consumption for tracking raw coordinates, we propose efficient techniques to maximize the accuracy of monitoring meaningful places with a given energy constraint. SmartDC comprises unsupervised mobility learner, mobility predictor, and Markov decision process-based adaptive duty cycling. SmartDC estimates the regularity of individual mobility and predicts residence time at places to determine efficient sensing schedules. Our experiment results show that SmartDC consumes 81% less energy than the periodic sensing schemes, and 87% less energy than a scheme employing context-aware sensing, yet it still correctly monitors 80% of a user's location changes within a 160-second delay.
Deriving Association between Student's Comprehension and Facial expressions using Class Association Rule Mining

The scope of this study was to discover the association between facial expressions of students in an academic lecture and the level of comprehension shown by their expressions. This study focussed on finding the relationship between the specific elements of learner's behaviour for the different emotional states and the relevant expression that could be observed from individual students. The experimentation was done through surveying quantitative observations of the lecturers in the classroom in which the behaviour of students are recorded and were statistically analyzed. The main aim of this paper is to derive association rules that represent relationships between input conditions and results of domain experiments. Hence the relationship between the physical behaviors that are linked to emotional state with the student's comprehension is being formulated in the form of rules. We present Predictive Apriori algorithm that is able to find all valid class association rules with high accuracy. The rules derived by Predictive Apriori are pruned by objective and subjective measures.
Category Migration of Renal Cystic Masses with Use of Gadolinium-Enhanced Magnetic Resonance Imaging

The Bosniak renal cyst classification has been accepted by urologists and radiologists as a way of diagnosing cystic renal masses and determining the management approach. We report two cases of a renal cystic mass that showed a category change from category II on the basis of enhanced computed tomography to category IV after further gadolinium-enhanced magnetic resonance imaging. In both cases, the cysts were later confirmed as kidney cancer by pathology.
Evolution of fruit and seed characters in the Diervilla and Lonicera clades (Caprifoliaceae, Dipsacales).

BACKGROUND AND AIMS The Diervilla and Lonicera clades are members of the family Caprifoliaceae (Dipsacales sensu Donoghue et al., 2001, Harvard Papers in Botany 6: 459-479). So far, the intergeneric relationships of the Lonicera clade and the systematic position of Heptacodium remain equivocal. By studying fruit and seed morphology and anatomy, an attempt is made to clarify these issues. In addition, this study deals with the evolution of fruit and seed characters of the Diervilla and Lonicera clades with reference to allied taxa. METHODS Light and scanning electron microscopy were used for the morphological and anatomical investigations. Phylogenetic analyses were carried out by applying the parsimony and Bayesian inference optimality criteria. Character evolution was studied by means of parsimony optimization and stochastic character mapping. KEY RESULTS Diervilla and Weigela (Diervilla clade) are characterized by several unique traits in Dipsacales, including capsules with numerous seeds, seed coats without sclerified outer tangential exotestal cell walls, and dehiscent fruits. Seeds with completely sclerified exotestal cells and fleshy fruits characterize the Lonicera clade. Leycesteria and Lonicera have berries, ovaries without sterile carpels and several seeds per locule, whereas Symphoricarpos and Triosteum have drupes, ovaries with one or two sterile carpels and a single seed per locule. Heptacodium shares several characteristics with members of the Linnina clade, e.g. achenes, single-seeded fruits and a compressed, parenchymatous seed coat. CONCLUSIONS The results confirm the monophyly of the Diervilla and Lonicera clades and allow us to hypothesize a close relationship between Leycesteria and Lonicera and between Symphoricarpos and Triosteum. Fruit and seed morphology and anatomy point to a sister relationship of Heptacodium with the Linnina clade, rather than with the Lonicera clade.
A speech enhancement method using adaptive speech PDF

A speech enhancement algorithm by using MAP estimation with adaptive speech spectral amplitude probability density function (speech PDF) is presented in this paper. The proposed speech PDF has two adaptive shape parameters which affect the quality of enhanced speech. Noise can be efficiently suppressed when these parameters are properly estimated so that the adaptive speech PDF shape fits to the real-speech PDF one. We derive adaptive shape parameters from real-speech PDF in various narrow SNR intervals. The proposed speech enhancement algorithm with adaptive shape parameters is analyzed and compared to conventional algorithms. The evaluation results show that the proposed method is superior to the conventional algorithms.
Research on Kernel-Based Feature Fusion Algorithm in Multimodal Recognition

Ear and face based multimodal recognition could fully utilize their connection relationship, and implement recognizing people without their cooperation because of ear’s special physiological location and structure. In this paper akernel-based feature fusion algorithm is presented and applied to multimodal recognition based on fusing ear and face. With the algorithm, the associated feature vectors of ear and profile face are established for the following classification. The experimental results show that the method is efficient for feature fusion, and the multimodal recognition based on ear and profile face performs better than ear or profile face unimodal biometric recognition.
Cell proliferation and neuroblast differentiation in the dentate gyrus of high-fat diet-fed mice are increased after rosiglitazone treatment

In this study, we determined how rosiglitazone (RSG) differentially affected hippocampal neurogenesis in mice fed a low-fat diet (LFD) or high-fat diet (HFD; 60% fat). LFD and HFD were given to the mice for 8 weeks. Four weeks after initiating the LFD and HFD feeding, vehicle or RSG was administered orally once a day to both groups of mice. We measured cell proliferation and neuroblast differentiation in the subgranular zone of the dentate gyrus using Ki67 and doublecortin (DCX), respectively, as markers. In addition, we monitored the effects of RSG on the levels of DCX and brain-derived neurotrophic factor (BDNF) in hippocampal homogenates. At 8 weeks after the LFD feeding, the numbers of Ki67- and DCX-positive cells as well as hippocampal levels of DCX and BDNF were significantly decreased in the RSG-treated group compared to the vehicle-treated animals. In contrast, the numbers of Ki67- and DCX-positive cells along with hippocampal levels of DCX and BDNF in the HFD fed mice were significantly increased in the RSG-treated mice compared to the vehicle-treated group. Our data demonstrate that RSG can modulate the levels of BDNF, which could play a pivotal role in cell proliferation and neuroblast differentiation in the hippocampal dentate gyrus.
Postprocessing in block-based video coding based on a quantization noise model

In this paper, we propose a postprocessing method based on a quantization noise model with some assumptions in wavelet domain to reduce the blocking and ringing artifacts in block-coded video sequences. The quantization noise is considered as the sum of the blocking noise and the remainder noise including ringing noise. Since the one-dimensional (1-D) wavelet transform (WT) used in this paper represents a regularized differentiation, the blocking noise which is a gray level discontinuity at each block boundary appears as an impulse. We model the impulse as the blocking noise in wavelet domain and reduce it by estimating and weakening the strength of each blocking noise component that appears as an impulse at the block boundary in wavelet domain. The impulse strength estimation is performed using median filter, quantization parameter (QP), and local activity. The remainder noise, which is considered as a white Gaussian noise at non-edge pixels, then is reduced by soft-thresholding. Experimental results show that the proposed method yields better performance over verification model (VM) post-filter in MPEG-4 for all test sequences of various compression ratios.
ANALYSING CONSUMERS’ BEHAVIOUR TOWARDS GENETICALLY MODIFIED FOOD BY A VARIANCE-BASED STRUCTURAL EQUATION MODELLING METHOD

Applying gene technology in agricultural production, which results on the so-called genetically modified (GM) foods, is one of the most controversial scientific, political and social debates. In the EU, the underdevelopment of biotech crops is attributed to the social distrust in transgenic food. The potential consumers’ reactions towards Genetically Modified (GM) food influence the commercial feasibility and determine the economic agent decisions. This paper studies the underlying factors involved in determining consumers’ choice behaviour towards GM foods, examining the potential role of people literacy what is an issue barely studied by literature. The research is performed in Southern Spain using variance-Structural Equation Modelling, Partial Least Squares (PLS) technique. The results indicate that perceived risks and benefits from GM food act as antecedent of consumers’ purchase decisions and some differences are found in the patterns of behavioural intentions between scientific-technical literacy and social-humanistic literacy group.
Identifying the Source of a Humoral Factor of Remote (Pre)Conditioning Cardioprotection

Signalling pathways underlying the phenomenon of remote ischaemic preconditioning (RPc) cardioprotection are not completely understood. The existing evidence agrees that intact sensory innervation of the remote tissue/organ is required for the release into the systemic circulation of preconditioning factor(s) capable of protecting a transplanted or isolated heart. However, the source and molecular identities of these factors remain unknown. Since the efficacy of RPc cardioprotection is critically dependent upon vagal activity and muscarinic mechanisms, we hypothesized that the humoral RPc factor is produced by the internal organ(s), which receive rich parasympathetic innervation. In a rat model of myocardial ischaemia/reperfusion injury we determined the efficacy of limb RPc in establishing cardioprotection after denervation of various visceral organs by sectioning celiac, hepatic, anterior and posterior gastric branches of the vagus nerve. Electrical stimulation was applied to individually sectioned branches to determine whether enhanced vagal input to a particular target area is sufficient to establish cardioprotection. It was found that RPc cardioprotection is abolished in conditions of either total subdiaphragmatic vagotomy, gastric vagotomy or sectioning of the posterior gastric branch. The efficacy of RPc cardioprotection was preserved when hepatic, celiac or anterior gastric vagal branches were cut. In the absence of remote ischaemia/reperfusion, electrical stimulation of the posterior gastric branch reduced infarct size, mimicking the effect of RPc. These data suggest that the circulating factor (or factors) of RPc are produced and released into the systemic circulation by the visceral organ(s) innervated by the posterior gastric branch of the vagus nerve.
Removal of ovarian hormones from mature mice detrimentally affects muscle contractile function and myosin structural distribution.

The purposes of this study were to determine the effects of ovarian hormone removal on force-generating capacities and contractile proteins in soleus and extensor digitorum longus (EDL) muscles of mature female mice. Six-month-old female C57BL/6 mice were randomly assigned to either an ovariectomized (OVX; n = 13) or a sham-operated (sham; n = 13) group. In vitro contractile function of soleus and EDL muscles were determined 60 days postsurgery. Total protein and contractile protein contents were quantified, and electron paramagnetic resonance (EPR) spectroscopy was used to determine myosin structural distribution during contraction. OVX mice weighed 15% more than sham mice 60 days postsurgery, and soleus and EDL muscle masses were 19 and 15% greater in OVX mice, respectively (P < or = 0.032). Soleus and EDL muscles from OVX mice generated less maximal isometric force than did those from sham mice [soleus: 0.27 (SD 0.04) vs. 0.22 N.cm. mg(-1) (SD 0.04); EDL: 0.33 (SD 0.04) vs. 0.27 N.cm. mg(-1) (SD 0.04); P < or = 0.006]. Total and contractile protein contents of soleus and EDL muscles were not different between OVX and sham mice (P > or = 0.242), indicating that the quantity of contractile machinery was not affected by removing ovarian hormones. EPR spectroscopy showed that the fraction of strong-binding myosin during contraction was 15% lower in EDL muscles from OVX mice compared with shams [0.277 (SD 0.039) vs. 0.325 (SD 0.020); P = 0.004]. These results indicate that the loss of ovarian hormones has detrimental effects on skeletal muscle force-generating capacities that can be explained by altered actin-myosin interactions.
The seven lean years, elasticity traps, and intervention in grain markets in pre-industrial Europe

search on modern famines has shown that they can be provoked by a every small decrease in the supply of food. The important policy implication is that the food shortage is manageable, provided there is good government protecting the entitlements of the poor, and no speculative bubbles.2 This has led economic historians to similar conclusions on preindustrial Europe. This article shows that the policy implication is plausible but its premise is not: local harvest failures created large reductions in food supply because inventories, i.e. grain carried over from one harvest to the next, were small and high transport costs impeded inter-regional trade. The first part, sections I-IV, looks into the conflicting views of contemporary authors regarding the magnitude of output variations and then presents a series of new empirical assessments. In the second part, sections V-XI, it is argued that market failures and high costs and risks in transport and storage prevented the desired inter-temporal and inter-spatial redistribution of grain. Government intervention in the early modern period can be interpreted as a rational means of coping with the recurrent price shocks following temporary shortages.
Software Defined Networking-assisted routing in wireless mesh networks

Software-Defined Networking (SDN) is a recent model of networking architecture which splits the network control from data forwarding functions. Most SDN solutions have in their scope the wired networks, but more recently, some attempts have been made to adapt SDN architecture for the context of wireless mesh networks (WMNs). In the present paper, we examine whether the use of the SDN paradigm in WMNs can help overcome certain limitations of the classic routing algorithms. To that end, we propose a new deployment architecture which exploits the main benefits of this paradigm: faster routing convergence and optimal path identification and takes advantage of multiple communication interfaces that most wireless devices already possess to split the signalling and data transfer. We then propose an hybrid management scheme applicable which mixes our SDN approach with a conventional distributed protocol (OLSR in our case). Through NS3 simulations, an improvement of 20% in both packet delivery ratio and lost packets was observed. Therefore, we can claim that the SDN controller can positively assist the distributed routing protocol operations.
Mastrovito form of Karatsuba Multiplier for All Trinomials

We present a Matrix-vector form of Karatsuba multiplication over GF (2m) generated by an irreducible trinomial. Based on shifted polynomial basis (SPB), two Mastrovito matrices for different Karatsuba multiplication parts are studied. Then related multiplier architecture is proposed. This design effectively exploits the overlapped entries of the Mastrovito matrices to reduce the space complexity even further. We show that this new type of Karatsuba multiplier is only one TX slower than the fastest bit-parallel multiplier for all trinomials, where TX is the delay of one 2-input XOR gate. Meanwhile its space complexity is roughly reduced by O( 2 4 ) logic gates. Compared with previously proposed bit-parallel Karatsuba multipliers, it is the first time to achieve such time delay bound, while maintain nearly the same space complexity.
LiTPiC -- Light-trails and Photonic Integrated Circuits: Issues of Network Design and Performance

A recent advance in high-speed networks is the concept of Photonic Integrated Circuits (PICs) on an Indium Phosphide substrate, allowing miniaturization and integration of multiple OE and EO modules in a chip. PICs have the potential to do away with the opto-electronic bandwidth mismatch as well as result in severe cost reduction, hence questioning the need for all-optical networking. In this paper we analyze the impact of this digital optical networking concept by combining PIC technology with an all-optical solution - light-trails, resulting in a new solution called LiTPiC (Light-Trail Photonic Integrated Circuit). LiTPiCs offer the best of both digital and all-optical worlds. By enabling selective (and on-demand) regeneration of the signal, we are able to enhance the reach of all-optical light-trails. In addition, we are able to partition light-trail buses into multiple geographically disjoint sub-buses called PIC-Trails, thus for the first time introducing wavelength reuse within a light-trail. The LiTPiC concept gives PICs a new direction - that of being a technology enabler for next generation services using ROADM (Reconfigurable Optical Add-Drop Multiplexer) architecture and a complementary solution to the light-trail technology.