Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy aware Secure Clustering in Mobile Ad hoc Networks

Mobile Ad hoc Networks (MANETs) suffer from security attacks and privacy issues, which dramatically impede their applications. In addition, the security measures applied in MANETs (like encryption and key distribution) have a number of negative effects on the network's performance. Cryptographic operations introduce a lot of both CPU and communication overhead. Therefore, routing protocols improvement is a challenge for researchers to overcome the negative effects of security measures. Clustering the MANET is a known technique to lower the routing over-head. It can also be utilized to distribute encryption keys and the authentication process. In this paper, a new protocol called Secure Clustering and Energy Saver Protocol “SCESP” is proposed. SCESP secures the Mobile Ad hoc Networks and increase its network lifetime. This system introduces a novel self-node clustering technique based on Ad-hoc On-demand Distance Vector “AODV” routing protocol. In addition, it eliminates the key distribution overhead using smart token or similar hardware which is used for authentication. The SCESP system succeeded to enhance the security level of MANETs and decrease the battery consumption of mobile nodes due to the transmitted and received route requests messages propagated to discover new routes in AODV routing protocol.
Counterfactual Evaluation and Learning for Search, Recommendation and Ad Placement

Online metrics measured through A/B tests have become the gold standard for many evaluation questions. But can we get the same results as A/B tests without actually fielding a new system? And can we train systems to optimize online metrics without subjecting users to an online learning algorithm? This tutorial summarizes and unifies the emerging body of methods on counterfactual evaluation and learning. These counterfactual techniques provide a well-founded way to evaluate and optimize online metrics by exploiting logs of past user interactions. In particular, the tutorial unifies the causal inference, information retrieval, and machine learning view of this problem, providing the basis for future research in this emerging area of great potential impact. Supplementary material and resources are available online at http://www.cs. cornell.edu/~adith/CfactSIGIR2016.
Effect of Pre-primary Experience in Numeracy and Literacy Skills on Primary Schools’ Performance in Mkuranga District

This study aimed at finding out the effect of pre-primary experience in numeracy and literacy skills on primary school performance in Mkuranga district. Specifically, the study was intended to determine extent to which pupils in Mkuranga have attended pre-primary education, assess the performance differences between pupils who have attended pre-primary education and those who have not attended in terms of numeracy and literacy as well as evaluate their teachers’ perception on the curriculum content coverage between pupils with pre-primary experience and those without. The study used quantitative approaches in which SPSS was used to analyze data. The study found that there is small difference between pupils with pre-primary experience and those without pre-primary experience in terms of their numbers. Where by 55% of the sample students were found to have pre-primary experience and 45% were found to have no pre-primary experience. In addition, pupils with pre-primary experience had high performance chances than those without pre-primary experience in both grade two and four. Furthermore, there is similar gaining between boys and girls with pre-primary experience. Pupils with pre-primary experience are perceived by teachers to have high ability of covering the curriculum than pupils than those without pre-primary experience. The study has concluded that pre-primary education enhances primary educational achievements. It was recommended that pre-primary school education should be encouraged by providing pre-primary educational facilities such as (classrooms, instructional materials, and equipments) needed for the success.
Drug delivery and drug resistance: EGFR-tyrosine kinase inhibitors in non-small cell lung cancer

The epidermal growth factor receptor (EGFR) pathway has emerged as an important target in the treatment of non-small cell lung cancer (NSCLC). Currently available EGFR inhibitors approved for the therapy of NSCLC include the small molecules erlotinib and gefitinib. They are administered orally and interfere with the intracellular tyrosine kinase domain. These agents appear most effective in patients with tumors which are highly dependent on the EGFR signaling pathway because of EGFR activating mutations or amplifications. The use of EGFR tyrosine kinase inhibitors prolongs survival in metastatic NSCLC. However, despite the dramatic initial responses to treatment in some cases, NSCLC eventually becomes resistant to EGFR-tyrosine kinase inhibitors (TKIs). Mechanisms of resistance include EGFR secondary mutations that interfere with drug binding. Besides, molecular cross-talk and redundancy between EGFR and other signaling pathways creates alternative pathways for tumor cell proliferation promoting resistance to EGFR inhibition such as the amplification of the receptor tyrosine kinases MET. Polymorphisms in EGFR and EGFR pathway- related genes, as well as in genes involved in drug metabolism and intake/efflux might also predict clinical outcome and toxicity. Therefore, understanding the mechanisms involved in the EGFR signalling and resistance to EGFR inhibition will provide new insights for the development of more effective targeted treatments against NSCLC.
Cajachalcone: An Antimalarial Compound from Cajanus cajan Leaf Extract

Cajanus cajan L, a member of the family Fabaceae, was identified from the Nigerian antimalarial ethnobotany as possessing antimalarial properties. The bioassay-guided fractionation of the crude methanol extract of C. cajan leaves was done in vitro using the multiresistant strain of Plasmodium falciparum (K1) in the parasite lactate dehydrogenase assay. Isolation of compound was achieved by a combination of chromatographic techniques, while the structure of the compound was elucidated by spectroscopy. This led to the identification of a cajachalcone, 2′,6′-dihydroxy-4-methoxy chalcone, as the biologically active constituent from the ethyl acetate fraction. Cajachalcone had an IC50 value of 2.0 μg/mL (7.4 μM) and could be a lead for anti-malarial drug discovery.
A Transmitter-Based Beamforming Scheme for the MIMO Downlink Employing Adaptive Channel Decomposition

An extension to decomposition based transmit beamforming is proposed for multiple input multiple output (MIMO) multiuser systems. In contrast to conventional beamforming which is constrained towards orthogonalizing the subchannels of the different users to yield groups of correlated antennas that belong to only one user, a more flexible orthogonalization approach is proposed which is targeted directly towards the optimization of the decision variables at the multi-antenna receivers of all users. The resulting groups of correlated antennas may consist of elements belonging to multiple users. Thus, the proposed beamforming has more degrees of freedom and therefore attains a more efficient performance optimization. The trade-off to the performance improvement is an increase in the precoding complexity imposed by the adaptive nature of the proposed beamforming. A suboptimal adaptive-decomposition beamforming scheme is therefore also proposed with a reduced complexity overhead. Comparative simulations of the proposed scheme to conventional beamforming show considerable error rate reductions that justify the increased complexity and verify the superiority of the proposed scheme.
An Adaptive Parameter Control Strategy for ACO

Ant colony optimization (ACO) has been proved to be one of the best performing algorithms for NP-hard problems as TSP. Many strategies for ACO have been studied, but fewer tuning methodologies have been done on ACO's parameters which influence the algorithm directly. The setting of ACO's parameters is considered as a combinational optimization problem in this paper. The particle swarm optimization (PSO) is introduced to solve this problem, and an adaptive parameter setting strategy is proposed. It's proved to be effective by the experiment based on TSPLIB test
Estrogenic activity of estradiol and its metabolites in the ER‐CALUX assay with human T47D breast cells Note

A number of metabolites of 17β‐estradiol were tested for their estrogenic activity using the ER‐CALUX assay based on the increased expression of luciferase in exposed T47D breast cancer cells. E2β and estrone showed similar potencies in the test, whereas E2α was 100 times less active. Incubation of cells with estrone (0.35 μM) resulted in the formation of E2β, whereas the reverse reaction was observed for E2β. The resulting equilibrium may explain the similar estrogenic potency of estrone in the test. The synthetic 17‐hydroxy benzoate ester of E2β was 3 times less active than the parent compound. The 17‐hydroxy palmitate and oleate esters of E2β, were respectively 25 and 200 times less active than the parent compound. The 2‐hydroxy metabolites of E2β and estrone showed a 5,000 to 10,000 fold lower activity. The 4‐hydroxy metabolites were more potent than the 2‐hydroxy metabolites, showing only a 20–200 times lower activity. The 2‐ and 4‐methoxyesters of estrone were 700 times less active. It is concluded that the estrogenic potency of metabolites formed in cattle after treatment with E2β, like estrone, E2α and especially the esters of E2β, may be significant with respect to the potential risk of the use of estradiol for growth promotion in domestic animals in certain countries.
Truncation of geometrically thin disks around massive black holes in galactic nuclei

The concept of an advection-dominated accretion ow (ADAF), with or without wind loss, was used to describe the spectra of the galactic center source SgrA*, low-luminosity AGN and nuclei of elliptical galaxies (including M 87). The spectral fits of various authors show that the transition from the geometrically thin disk to the hot ow occurs at quite different distances, apparently not uniquely related to the mass ow rate in the disk. We compare these results with the results of theoretical modeling where we determine the truncation of the thin outer disk from the efficiency of mass evaporation. The physics is the same as in the case of galactic black holes systems (Meyer et al. 2000b). For the observationally indicated mass ow rates our model predicts a truncation at 10(3) to 10(4) Schwarzschild radii. We discuss whether far inside this truncation an innermost cool thin disk could exist and affect the spectrum.
ZENA WERB AND

Previous studies have described the exchange of free cholesterol molecules of macrophage membranes with those of serum lipoproteins (1). Exchangeable cholesterol was found in two compartments. The rapidly exchanging compartment was identified as the plasma membrane, and the slowly exchanging compartment was associated with intracellular membranes (2). Cholesterol esters (CE's) 1 were not exchanged under these conditions, a finding which is in keeping with prior studies employing lipoprotein classes and erythrocytes (3). Under physiological and pathological conditions macrophages are exposed to other forms of both free cholesterol and CE's. Effete erythrocytes, tissue cells, and chylomicrons are taken up by phagocytosis (4-6), and subsequently are localized within cytoplasmic phagolysosomes. Many of their constituents are then degraded by acid hydrolases (7-9). Similar events take place under in vitro culture conditions and may lead to the formation of an intralysosomal compartment of free and esterified cholesterol, clearly distinct from the membrane-associated intracellular pool. The processing and fate of cholesterol and CE's within the digestive vacuole is poorly understood.
Learning discriminative MspLBP features based on Ada-LDA for multi-class pattern classification

This paper presents a novel approach for multi-class pattern classification - face detection and facial expression recognition, which is based on discriminative multi-scale and multi-position Local Binary Pattern (MspLBP) features selected by a boosting technique called the AdaBoost+LDA (Ada-LDA) method. From a large pool of MspLBP features within a face image, the most discriminative MspLBP features trained by two alternative LDA methods depending on the singularity of the within-class scatter matrix, are selected under the framework of AdaBoost. To verify the feasibility of our approach, we performed two extensive experiments on the famous face databases in terms of face detection and facial expression recognition. First, face detection, a typical example of two-class pattern classification, was carried out on the MIT-CBCL and MIT+CMU face test sets. Second, facial expression recognition, a typical problem of multi-class pattern classification, was performed on the JAFFE face database. Given the same number of features, the proposed face detector shows over 25% higher detection rate than the well-known Viola's detector at a given false positive rate of 10%. It can also provide real-time operation with over 10 frames per second rate. For facial expression recognition, our approach also shows a better performance over at least 21% recognition rates than other linear subspace-based methods such as PCA, DCV, and PCA+LDA. Our proposed approach provides a considerable performance improvement with only a small number of discriminative MspLBP features in the multi-class pattern classification problem.
Triangle Surface Mesh Watermarking Based on a Constrained Optimization Framework

A watermarking strategy for triangle surface meshes consists of modifying the vertex positions along the radial directions, in order to adjust the distribution of radial distances and thereby encode the desired payload. To guarantee that watermark embedding does not alter the center of mass, prior work formulated this task as a quadratic programming problem. In this paper, we contribute to the generalization of this formulation with: 1) integral reference primitives; 2) arbitrary relocation directions to alter the vertex positions; and 3) alternate distortion metrics to minimize the perceptual impact of the embedding process. These variants are benchmarked against a range of attacks and we report both improved robustness performances, in particular for simplification attacks, and improved control over the embedding distortion.
Impact of overweight and underweight on assisted reproduction treatment.

BACKGROUND Underweight and overweight may affect reproduction and interfere with treatment of infertility. The purpose of this report is to describe the independent effect of body weight on treatment with IVF and ICSI. METHODS Records of 5019 IVF or ICSI treatments in 2660 couples were reviewed. The influence of body mass index (BMI) on treatment outcome was examined, after accounting for differences in age and infertility diagnosis. RESULTS The cumulative live birth rate within three treatment cycles was 41.4% [95% confidence interval (CI) 32.1-50.7] in obese women with BMI > or =30 kg/m2 and 50.3 (95% CI 47.0-53.7) in normal weight women with BMI 18.5-24.9 kg/m2. Obesity was associated with an increased risk of early pregnancy loss occurring before 6 weeks gestation. Positive correlation between BMI and gonadotrophin requirement during stimulation and negative correlation between BMI and number of collected oocytes were observed. Underweight (BMI <18.5 kg/m2) was not related to an impaired outcome of IVF or ICSI. CONCLUSIONS Obesity is associated with lower chances for live birth after IVF and ICSI and with an impaired response to ovarian stimulation.
CAD-BASED ROBOT VISION FOR AUTONOMOUS MANIPULATION

Thispaperpresentssomefeaturesof avisionsystemfor autonomousmanipulationthatwearedevelopingin theframework of a project concerningunmannedspacemissions. Themaingoalis accurateestimationof therobotposeby3D scenereconstructionandmatchingagainstana priori CAD model of the environment. Resultsof someexperimental testson a “blocks world” arepresented.Theseresultsindicatethataccuraciesin theestimatedrobotpositionof the orderof 1/500of theviewing distanceareeasilyattainable, even with low-depthscenesandunoptimizedcameramotions.
Mining Emotional Features of Movies

In this paper, we present the algorithm designed for mining emotional features of movies. The algorithm dubbed Arousal-Valence Discriminant Preserving Embedding (AVDPE) is proposed to extract the intrinsic features embedded in movies that are essentially differentiating in both arousal and valence directions. After dimensionality reduction, we use the neural network and support vector regressor to make the final prediction. Experimental results show that the extracted features can capture most of the discriminant information in movie emotions.
Temporally coherent real-time labeling of dynamic scenes

The augmentation of objects by textual annotations provides a powerful means for visual data exploration. Especially in interactive scenarios, where the view on the objects and, thus, the preferred placement of annotations changes continually, efficient labeling procedures are required. As identified by a preliminary study for this paper, these procedures have to consider a number of requirements for achieving an optimal readability, e.g. cartographic principles, visual association and temporal coherence. In this paper, we present a force-based labeling algorithm for 2D and 3D scenes, which can compute the placements of annotations at very high speed and fulfills the identified requirements. The efficient labeling of several hundred annotations is achieved by computing their layout in parallel on the GPU. This allows for a real-time and collision-free arrangement of both dynamically changing and static information. We demonstrate that our method supports a large variety of applications, e.g. geographical information systems, automotive navigation systems, and scientific or information visualization systems. We conclude the paper with an expert study which confirms the enhancements brought by our algorithm with respect to visual association and readability.
Effects of the Positive Action programme on problem behaviours in elementary school students: A matched-pair randomised control trial in Chicago

This study examined the effects of the Positive Action (PA) programme in Chicago Public Schools on problem behaviours among a cohort of elementary school students from grade three through grade five. Using a matched-pair, randomised control design with 14 elementary schools, approximately 510 fifth-graders self-reported lifetime substance use, serious violence-related behaviour, and current bullying and disruptive behaviours. Three-level (i.e. students nested within schools within school pairs) overdispersed Poisson models were used to examine programme effects on the number of items endorsed for each of the four outcomes. Findings indicated that students in the intervention endorsed 31% fewer substance use behaviours (incidence rate ratio [IRR] = 0.69), 37% fewer violence-related behaviours (IRR = 0.63) and 41% fewer bullying behaviours (IRR = 0.59), respectively, compared to students in the control schools. Reduction in reported disruptive behaviours was of a similar magnitude (27%, IRR = 0.73), but was not statistically significant. These results replicate findings of an earlier randomised trial of the PA programme and extend evidence of its effectiveness to youth attending large urban school systems.
Hormonal control by A-factor of morphological development and secondary metabolism in Streptomyces

Streptomyces griseus, a well-known industrial producer of streptomycin, is a member of the genus Streptomyces, which shows a complex life cycle resembling that of fungi. A-factor, a C13γ-butyrolactone compound, was discovered as a self-regulatory factor or a bacterial hormone to induce morphological differentiation and production of secondary metabolites, including streptomycin, in this organism. Accumulating evidence has revealed an A-factor-triggered signal cascade, which is composed of several key steps or components. These include: (i) AfsA catalyzing a crucial step of A-factor biosynthesis, (ii) the A-factor-specific receptor (ArpA), which acts as a transcriptional repressor for adpA, (iii) adpA, a sole target of ArpA, which encodes a global transcriptional activator AdpA, and (iv) a variety of members of the AdpA regulon, a set of the genes regulated by AdpA. A-factor is biosynthesized via five reaction steps, in which AfsA catalyzes acyl transfer between a β-ketoacyl-acyl carrier protein and the hydroxyl group of dihydroxyacetone phosphate. The receptor ArpA, belonging to the TetR family, is a homodimer, each subunit of which contains a helix-turn-helix DNA-binding motif and an A-factor-binding pocket. The three-dimensional structure and conformational change upon binding A-factor are elucidated, on the basis of X-ray crystallography of CprB, an ArpA homologue. AdpA, belonging to the AraC/XylS transcriptional activator family, binds operators upstream from the promoters of a variety of the target genes and activates their transcription, thus forming the AdpA regulon. Members of the AdpA regulon includes the pathway-specific transcriptional activator gene strR that activates the whole streptomycin biosynthesis gene cluster, in addition to a number of genes that direct the multiple cellular functions required for cellular differentiation in a concerted manner. A variety of A-factor homologues as well as homologues of afsA/arpA are distributed widely among Streptomyces, indicating the significant role of this type of molecular signaling in the ecosystem and evolutional processes.
What Objective Does Self-paced Learning Indeed Optimize?

Self-paced learning (SPL) is a recently raised methodology designed through simulating the learning principle of humans/animals. A variety of SPL realization schemes have been designed for different computer vision and pattern recognition tasks, and empirically substantiated to be effective in these applications. However, the investigation on its theoretical insight is still a blank. To this issue, this study attempts to provide some new theoretical understanding under the SPL scheme. Specifically, we prove that the solving strategy on SPL accords with a majorization minimization algorithm implemented on a latent objective function. Furthermore, we find that the loss function contained in this latent objective has a similar configuration with non-convex regularized penalty (NSPR) known in statistics and machine learning. Such connection inspires us discovering more intrinsic relationship between SPL regimes and NSPR forms, like SCAD, LOG and EXP. The robustness insight under SPL can then be finely explained. We also analyze the capability of SPL on its easy loss prior embedding property, and provide an insightful interpretation to the effectiveness mechanism under previous SPL variations. Besides, we design a group-partial-order loss prior, which is especially useful to weakly labeled large-scale data processing tasks. Through applying SPL with this loss prior to the FCVID dataset, which is currently one of the biggest manually annotated video dataset, our method achieves state-of-the-art performance beyond previous methods, which further helps supports the proposed theoretical arguments.