Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of linear and nonlinear PCA to SAR ATR

This paper explores the use of Principal Component Analysis (PCA) techniques for the development of classification systems for Synthetic Aperture Radar (SAR) Images. The concept of Principal Component Analysis is centered on feature extraction and dimensionality reduction. Through the exploitation of spatial differences and variances between data points of a specific data domain, application of PCA techniques allows the reduction of datasets to representations consisting of principal components only. The effect hence forth being the reduction of dataset sizes, which translates to a reduction in processing time on these datasets, for almost any application the mathematical technique is applied to. Open literature provides examples of software computation domains to which PCA has been applied, examples being face recognition and geo-environmental forecasting applications. Both linear and nonlinear PCA forms are covered in this paper. Application of linear PCA to SAR based automatic target recognition has been covered extensively in open literature. This investigation therefore aims to improve on the performance achieved by linear PCA application, using non linear PCA. Three systems were developed for the purpose of the investigation, which were a linear PCA system, a nonlinear PCA system using a polynomial kernel, and a nonlinear PCA system using a Gaussian kernel. The systems were tested for how well they responded to a reduction in training dataset, as this is a real-world problem experienced in ATR systems. The performance of the systems in terms of their running times were also evaluated. As anticipated, the nonlinear PCA approach outperformed the linear PCA approach, and the performance of the polynomial kernel PCA system was observed to be the best of all the three systems.
SS+ tree: an improved index structure for similarity searches in a high-dimensional feature space

In this paper, we describe the SS+-tree, a tree structure for supporting similarity searches in a high- dimensional Euclidean space. Compared to the SS-tree, the tree uses a tighter bounding sphere for each node which is an approximation to the smallest enclosing sphere and it also makes a better use of the clustering property of the available data by using a variant of the k-means clustering algorithm as the split heuristic for its nodes. A local reorganization rule is also introduced during the tree building to reduce the overlapping between the nodes' bounding spheres.
Pratique de l’entretien dit ‘non-directif’

Conformement au projet qui sous-tend la publication de ce livre, ce chapitre sur l'entretien " non-directif " est resolument pratique et descriptif. Laissant de cote les questions d'ordre epistemologique, il vise a rendre compte de ce qui se passe lors d'un entretien de type " non-directif "2, en livrant des observations sur le role de l'enqueteur. Il s'agit de methodologie au sens le plus technique du terme (.).
LPS regulates proinflammatory gene expression in macrophages by altering histone deacetylase expression

Bacterial LPS triggers dramatic changes in gene expression in macrophages. We show here that LPS regulated several members of the histone deacetylase (HDAC) family at the mRNA level in murine bone marrow‐derived macrophages (BMM). LPS transiently repressed, then induced a number of HDACs (Hdac‐4, 5, 7) in BMM, whereas Hdac‐1 mRNA was induced more rapidly. Treatment of BMM with trichostatin A (TSA), an inhibitor of HDACs, enhanced LPS‐induced expression of the Cox‐2, Cxcl2, and Ifit2 genes. In the case of Cox‐2, this effect was also apparent at the promoter level. Overexpression of Hdac‐8 in RAW264 murine macrophages blocked the ability of LPS to induce Cox‐2 mRNA. Another class of LPS‐inducible genes, which included Ccl2, Ccl7, and Edn1, was suppressed by TSA, an effect most likely mediated by PU.1 degradation. Hence, HDACs act as potent and selective negative regulators of proinflammatory gene expression and act to prevent excessive inflammatory responses in macrophages. —Aung, H. T. , Schroder, K. , Himes, S. R. , Brion, K. , van Zuylen, W. , Trieu, A. , Suzuki, H. , Hayashizaki, Y. , Hume, D. A. , Sweet, M. J., Ravasi, T. LPS regulates proinflammatory gene expression in macrophages by altering histone deacetylase expression. FASEB J. 20, 1315–1327 (2006)
Reproductive biology of Aedes (S.) malayensis (Diptera: Culicidae).

The reproductive potential of Aedes malayensis and Ae. polynesiensis was studied. The average number of eggs per female for 18 Ae. polynesiensis and 17 Ae. malayensis during the 1st gonotrophic cycle was 99.8 and 53.6, respectively. The gonotrophic cycles of 15 Ae. malayensis females were followed for about 70 days and the average duration from blood meal to oviposition and from oviposition to blood meal was 5.6 and 1.2 clays, respectively. Most of the eggs were produced during the 1st 4 gonotrophic cycles; 2 females were able to oviposit up to 12 times. In a subsequent study, it was found that the number of ovipositing females decreased with an increase in the number of gonotrophic cycles, and that at the same time there was a decrease in egg production for each subsequent oviposition.
Q-Band pHEMT and mHEMT Subharmonic Gilbert Upconversion Mixers

This letter makes a comparison between Q-band 0.15 mum pseudomorphic high electron mobility transistor (pHEMT) and metamorphic high electron mobility transistor (mHEMT) stacked-LO subharmonic upconversion mixers in terms of gain, isolation and linearity. In general, a 0.15 mum mHEMT device has a higher transconductance and cutoff frequency than a 0.15 mum pHEMT does. Thus, the conversion gain of the mHEMT is higher than that of the pHEMT in the active Gilbert mixer design. The Q-band stacked-LO subharmonic upconversion mixers using the pHEMT and mHEMT technologies have conversion gain of -7.1 dB and -0.2 dB, respectively. The pHEMT upconversion mixer has an OIP3 of -12 dBm and an OP1 dB of -24 dBm, while the mHEMT one shows a 4 dB improvement on linearity for the difference between the OIP3 and OP1 dB. Both the chip sizes are the same at 1.3 mm times 0.9 mm.
Assessing the Verifiability of Attributions in News Text

When reporting the news, journalists rely on the statements of stakeholders, experts, and officials. The attribution of such a statement is verifiable if its fidelity to the source can be confirmed or denied. In this paper, we develop a new NLP task: determining the verifiability of an attribution based on linguistic cues. We operationalize the notion of verifiability as a score between 0 and 1 using human judgments in a comparison-based approach. Using crowdsourcing, we create a dataset of verifiability-scored attributions, and demonstrate a model that achieves an RMSE of 0.057 and Spearman’s rank correlation of 0.95 to human-generated scores. We discuss the application of this technique to the analysis of mass media.
An Improved Multi-View Convolutional Neural Network for 3D Object Retrieval

Learning robust and discriminative representations is essential for 3D object retrieval. In this paper, we present an improved Multi-view Convolutional Neural Network (MVCNN) for view-based 3D object representation learning. Our technical contributions are divided into two aspects. First, we propose to employ Group-view Similarity Learning (GSL) over the multi-view representations before the aggregation operation (i.e., max-pooling in MVCNN). We assume that the similarity information among the view groups of different 3D objects can provide an important cue but has been neglected more or less by previous methods. To enhance it, we add a branch to the original MVCNN architecture and learn to maintain such group-view similarity relationships. Second, we utilize an end-to-end metric learning loss function to improve the representation learning process. In particular, we propose an improved Triplet-Center Loss (TCL) named Adaptive Margin based Triplet-Center Loss (AMTCL). The original TCL assumes a fixed and common margin to control the relative distance relationship between a sample to its corresponding class center and to the nearest negative center. Though TCL has demonstrated its great capacity on the 3D object retrieval task, however, when considering the distinguishability between samples of one class and samples of another class, we assume that it would be more appropriate that the margin takes different values based on the distinguishability of samples of different classes. Therefore we propose to adaptively and dynamically adjust the margin hyperparameter based on the normalized confusion matrix which is obtained on the training set during the training process. Extensive experiments on several public 3D shape benchmarks show that our method, GSL + AMTCL, can learn more suitable representations for 3D object retrieval, obtaining superior performance against state-of-the-art methods.
One-Layer Rate-Splitting Multiple Access with Benefits over Power-Domain NOMA in Indoor Multi-Cell Visible Light Communication Networks

A conventional approach to tackle the inter-cell interference in multi-cell visible light communication (VLC) networks is based on non-orthogonal multiple access (NOMA) by allowing one user to fully decode the message of another user. Due to the ability of partially decoding the interference and partially treating it as noise, rate-splitting multiple access (RSMA) has been regarded as a more flexible interference management scheme that generalizes and outperforms NOMA. Motivated by the benefits of RSMA and its infancy in multi-cell VLC networks, this paper firstly introduces 1-layer RSMA into multi-cell VLC networks by considering the Lambertian radiation model of indoor visible-light channels. Afterwards, we develop a linear precoding containing 1-layer RSMA-VLC to achieve spectral efficiency having constrained the non-linear effect of a light-emitting diode (LED). Subsequently, the transmitted power allocation is constrained by the optical signal power. Finally, we perform a comparison between 1-layer RSMA and NOMA based on multi-cell VLC networks. Simulation results show the effectiveness of our proposal in system spectral efficiency and VLC constraints. Furthermore, key features guaranteeing the merits of 1-layer RSMA are analysed with respect to the number of users, user locations, and lighting deployment.
Dual Machine-Learning System to Aid Glaucoma Diagnosis Using Disc and Cup Feature Extraction

Glaucoma is a degenerative disease that affects vision, causing damage to the optic nerve that ends in vision loss. The classic techniques to detect it have undergone a great change since the intrusion of machine learning techniques into the processing of eye fundus images. Several works focus on training a convolutional neural network (CNN) by brute force, while others use segmentation and feature extraction techniques to detect glaucoma. In this work, a diagnostic aid tool to detect glaucoma using eye fundus images is developed, trained and tested. It consists of two subsystems that are independently trained and tested, combining their results to improve glaucoma detection. The first subsystem applies machine learning and segmentation techniques to detect optic disc and cup independently, combine them and extract their physical and positional features. The second one applies transfer learning techniques to a pre-trained CNN to detect glaucoma through the analysis of the complete eye fundus images. The results of both systems are combined to discriminate positive cases of glaucoma and improve final detection. The results show that this system achieves a higher classification rate than previous works. The system also provides information on the basis for the proposed diagnosis suggestion that can help the ophthalmologist to accept or modify it.
Conceptions of the Self and Others Across Time

People are full of plans, goals, hopes, and fears—future-oriented thoughts that constitute a significant part of the self-concept. But are representations of others similarly future oriented? Studies 1a and 1b demonstrate that the future is seen as a larger component of the self than of another person. Study 2 found that because self-identity is tied to an unrealized future, the self is thought to be less knowable than others in the present. Study 3 indicates that people believe that others need to know who they are striving to be in order to be understood—more so than they believe they need to know others' strivings to understand them. Studies 4a and 4b tested an important implication of these findings, that because so much of who they are is tied to the future, people believe they are further from their ideal selves than others are. Implications for judgment and decision making are discussed.
Studies to determine the critical control points in pork slaughter hazard analysis and critical control point systems

Aerobic mesophilic counts (AMC), coliform (CC) and coliform resuscitation counts (CRCs) were obtained by swabbing 50 cm areas at three sites (ham, belly and neck) on pig carcasses, after each of seven stages of the slaughter/dressing process (bleeding, scalding, dehairing, singeing, polishing, evisceration and chilling). In most cases, there were no statistical differences (P>0.05) among the counts derived by these three methods. Reductions in counts at individual sites were observed after scalding (3.5 log10 cfu cm ), and singeing (2.5 log10 cfu cm ). Increases in counts at individual sites were observed after dehairing (2.0 log10 cfu cm ) and polishing (1.5 log10 cfu cm ). The incidence of Salmonella on pig carcasses was also obtained by swabbing the outside surfaces of 100 half carcasses. Information on the incidence of Salmonella in scald tank water (108 samples) was also investigated. Carcass swabs and scald tank water were examined for the presence of Salmonella using standard enrichment methods. Salmonella were detected on 31% of carcasses immediately after bleeding, 7% of carcasses immediately after dehairing and evisceration, and 1% of carcasses immediately after scalding. Serovars included Salmonella Typhimurium, Salmonella Hadar, Salmonella Infantis and Salmonella Derby. No Salmonella were recovered from samples of scald tank water. The impact of pig slaughter/dressing processes on carcass microbiology and their potential use as critical control points (CCPs) during pork production are discussed. D 2003 Elsevier B.V. All rights reserved.
Joint Resource Allocation for NOMA-Assisted MEC Networks

Multi-access edge computing (MEC) is a promising technique to improve computation capabilities of mobile devices, and non-orthogonal multiple access (NOMA) can be combined with it to improve the spectral efficiency. This paper aims to minimize the energy consumption of a NOMA-assisted MEC system by optimizing the power allocation and task assignment. The original formulated problem is non-convex. To efficiently solve it, we decompose it into three stages, i.e., power allocation, time slot scheduling, and offloading task assignment, which are solved optimally by carefully studying their convexity and monotonicity. The optimal power expressions are obtained by solving the first problem. Subsequently, an additional time slot, which is occupied by OMA transmission, can be optimized by analyzing the monotonicity of the second problem. Finally, the offloading strategy coefficient, which decides the amount of data to be offloaded to the base station (BS) and the remaining data computed locally, is obtained optimally. The derived solution is optimal to the original problem by substituting the closed expressions obtained from those decomposed problems. Simulation results are provided to verify the superior performance of the proposed scheme compared with some benchmarks, i.e., OMA and the existing work.
Prey Size Selection of Insular Lizards by Two Sympatric Predatory Bird Species

Abstract. Size-related selection of insular lizards by two sympatric predatory bird species (Southern Grey Shrike and Eurasian Kestrel) was studied in an arid insular environment. The endemic lizard genus Gallotia was a key resource in the diet of both predators, constituting more than 50% of the total biomass. Shrikes captured smaller lizards than kestrels during all seasons (mean snout - vent length (SVL): 7.4 ±1.9 vs. 9.4 ± 2.1 cm respectively), presenting a sequential use of lizard sizes and avoiding potential competition. On the other hand, shrikes and kestrels showed the same seasonal variation pattern, capturing the largest lizards during their breeding periods (spring). Considering lizard availability, shrikes displayed less selective predation than kestrels in all seasons. Shrikes positively selected the medium lizard size (SVL: 5–10 cm) during the nestling period, but negatively selected the small lizard size (SVL: < 5 cm) in autumn and winter, probably due to an explosion of juvenile lizards. Lastly, kestrels appeared to be more selective, negatively choosing the small lizard size but positively selecting the largest ones all the year round (SVL: > 10 cm).
Selection of Reference Genes for Quantitative Real-time PCR Analysis in Canine Mammary Tumors Using the GeNorm Algorithm

Eleven reference genes (18s ribosomal ribonucleic acid [RNA], 28s ribosomal RNA, ubiquitin, beta-actin, glycerine aldehyde dehydrogenase, ATP-synthase subunit 5B, hydroxymethylbilane synthase, hypoxanthine-phosphoribosyl transferase, ribosomal protein L32, tryptophan 5monooxygenase activation protein (zeta polypeptide), and TATA-Box binding protein) were analyzed in use as references for gene expression profiling experiments using quantitative reverse transcription polymerase chain reaction (qRT-PCR) in canine mammary tumors. The transcription level of the candidates was measured in 22 histologically characterized excised tumor specimens from mammary gland tissue and 22 samples of non-neoplastic mammary tissue samples from the same individuals. Results were used to rank candidate reference genes using the GeNorm tool. It was determined that in samples of canine mammary gland tissue, a combination of hypoxanthine-phosphoribosyl transferase, ATP-synthase subunit 5B, ribosomal protein L32 and ubiquitin yields stable reference gene expression levels, whereas the use of glycerin aldehyde dehydrogenase or ribosomal RNA is unsuitable for normalization of qRT-PCR results in this tissue type.
Contribution à la modélisation du béton sous sollicitation de dynamique rapide. : La prise en compte de l'effet de vitesse par la viscoplasticité

Cette etude concerne la modelisation du beton sous sollicitation de dynamique rapide. Il s'agit de prendre en compte un phenomene important observe dans les essais experimentaux : l' effet de vitesse. La resistance apparente d'une eprouvette augmente lorsque la vitesse de sollicitation croit. Cette sensibilite a la vitesse de deformation est alors modelisee par une approche viscoplastique. Une viscosite de type Duvaut-Lions est introduite dans un modele plastique. La description de la compression et la traction repose sur la construction d'un critere compose de deux surfaces ; un Rankine pour la traction et un Drucker-Prager pour la compression. Par ailleurs, le comportement du materiau beton etant suppose decrire un regime adoucissant en phase de rupture, une etude est necessaire afin de verifier que le probleme est bien pose. La viscoplasticite joue le role de limiteur de localisation. Ainsi, on verifie que les equations qui regissent 1' equilibre preservent leur caractere hyperbolique a 1 'amorce de regime adoucissant. Les bases d'un modele de viscoplasticite etant posees, une validation du comportement statique est realisee sur plusieurs simulations de structures. Enfin, une analyse numerique de 1 'effet de vitesse par le biais de l'essai de compression a la technique des barres de Hopkinson fait l'objet d'une discussion. Et la simulation de plusieurs structures soumises a sollicitation de dynamique rapide permet de mettre en exergue les limites du modele. En fonction des points finis et des points faibles observes, une orientation sur les developpements a venir est proposee.
An Energy-Efficient Secure Scheme in Wireless Sensor Networks

We propose an energy-efficient security scheme in wireless sensor networks. The proposed scheme converts sensing data using TinyMD5, which is a variation of MD5, a one-way hash function, and can solve the collision problem of hash value that occurs when MD5 is modified. In addition, it strengthens security capabilities by transmitting data through multiple paths after conversion with TinyMD5 and divides the data to make decryption of the original data difficult. To show the superiority of the proposed algorithm, we compare it with the existing schemes through simulations. The performance evaluation results show that the proposed scheme maintains security better than the existing scheme, improving the communication cost and the network lifetime.
Skin from Feet of Museum Specimens as a Non-Destructive Source of DNA for Avian Genotyping

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Parental and environmental correlates of physical activity of children attending preschool.

OBJECTIVE To determine, using a social-cognitive framework and structural equation modeling, if parent-reported family physical activity (PA) variables are related to PA of young children. DESIGN Cross-sectional study. SETTING Children attending 23 preschools in and around Columbia, South Carolina. PARTICIPANTS Three hundred sixty-nine children (48.0% male and 50.4% black) and their parents. MAIN EXPOSURES Family variables were reported by parents and included parent PA, parent enjoyment of PA, importance to adults of child playing sports and being active, and family support. MAIN OUTCOME MEASURES Moderate to vigorous physical activity (MVPA) of children was modeled as a latent variable using PA from direct observation, accelerometers, and parent's perception of the child's athletic coordination. RESULTS A model of direct and indirect relations of family variables, preschool quality, home PA equipment, and child's enjoyment of PA had acceptable fit (root mean square error of approximation, 0.053; comparative fit index, 0.90). Parent PA, parent enjoyment of PA, and importance of child's PA were significantly related to family support. Family support, quality of preschool attended, home PA equipment, and child's enjoyment of PA were positively related to child's PA. However, there was no direct relationship between parent PA and the child's PA. CONCLUSION Although parent PA was not directly related to children's MVPA, results showed that parent PA indirectly affects preschool children's MVPA via its influence on family support for children's PA.