Miracle-dz/UniFAR-FTUs huggingface dataset:
A new efficient and adaptive sclera recognition system

In this paper an efficient and adaptive biometric sclera recognition and verification system is proposed. Sclera segmentation was performed by Fuzzy C-means clustering. Since the sclera vessels are not prominent, in order to make them clearly visible image enhancement was required. Adaptive histogram equalization, followed by a bank of Discrete Meyer Wavelet was used to enhance the sclera vessel patterns. Feature extraction was performed by, Dense Local Directional Pattern (D-LDP). D-LDP patch descriptors of each training image are used to form a bag of features; further Spatial Pyramid Matching was used to produce the final training model. Support Vector Machines (SVMs) are used for classification. The UBIRIS version 1 dataset was used here for experimentation of the proposed system. To investigate regarding sclera patterns adaptively with respect to change in environmental condition, population, data accruing technique and time span two different session of the mention dataset are utilized. The images in two sessions are different in acquiring technique, representation, number of individual and they were captured in a gap of two weeks. An encouraging Equal Error Rate (EER) of 3.95% was achieved in the above mention investigation.
Effect of Antioxidant Supplementation on Exercise-Induced Cardiac Troponin Release in Cyclists: A Randomized Trial

Background Cardiac troponin is the biochemical gold standard to diagnose acute myocardial infarction. Interestingly however, elevated cardiac troponin concentrations are also frequently observed during and after endurance-type exercise. Oxidative stress associated with prolonged exercise has been proposed to contribute to cardiac troponin release. Therefore, the aim of this study was to assess the effect of 4 week astaxanthin supplementation (a potent cartenoid antioxidant) on antioxidant capacity and exercise-induced cardiac troponin release in cyclists. Methods Thirty-two well-trained male cyclists (age 25±5, weight 73±7 kg, maximum O2 uptake 60±5 mL·kg−1·min−1, Wmax 5.4±0.5 W·kg−1; mean ± SD) were repeatedly subjected to a laboratory based standardized exercise protocol before and after 4 weeks of astaxanthin (20 mg/day), or placebo supplementation in a double-blind randomized manner. Blood samples were obtained at baseline, at 60 min of cycling and immediately post-exercise (≈ 120 min). Results The pre-supplementation cycling trial induced a significant rise of median cardiac troponin T concentrations from 3.2 (IQR 3.0–4.2) to 4.7 ng/L (IQR 3.7–6.7), immediately post-exercise (p<0.001). Four weeks of astaxanthin supplementation significantly increased mean basal plasma astaxanthin concentrations from non-detectable values to 175±86 µg·kg−1. However, daily astaxanthin supplementation had no effect on exercise-induced cardiac troponin T release (p = 0.24), as measured by the incremental area under the curve. Furthermore, the elevation in basal plasma astaxanthin concentrations was not reflected in changes in antioxidant capacity markers (trolox equivalent antioxidant capacity, uric acid, and malondialdehyde). Markers of inflammation (high-sensitivity C-reactive protein) and exercise-induced skeletal muscle damage (creatine kinase) were equally unaffected by astaxanthin supplementation. Conclusion Despite substantial increases in plasma astaxanthin concentrations, astaxanthin supplementation did not improve antioxidant capacity in well-trained cyclists. Accordingly, exercise-induced cardiac troponin T concentrations were not affected by astaxanthin supplementation. Trial registration ClinicalTrials.gov NCT01241877
Gentle Robotic Handling Using Acceleration Compensation

Nowadays, robot manipulators are being widely used in the industrial and manufacturing sector, because of their high precision, speed, endurance and reliability. In the automotive industry, their typical applications include welding, painting, assembly of body, pick and place, etc. Normally, the main task is restricted to simple operations like moving a tool in different working locations. In the sector of logistics, they have to fulfill material handling and storage tasks like palletizing, depalletizing and transportation of goods. Without doubt, the main goal is to maximize the productivity. For this purpose, mostly the robotic manipulators are programmed to drive as fast as possible. But, reaching a time-optimal path does not mean the attainment of a perfect task performance. Since important aspects such as quality and safety should not be overlooked. Usually, most of the handling goods require a special and delicate treatment, due to the object's characteristic and complexity. Otherwise, quality degradations or damages to the transferring object may occur. In the process of material handling, it is common to encounter different kind of problems because of too high accelerated motions. For example: unexpected separation of the transferring object from its grasping tool, the spill-over of fluid materials in highly accelerated liquid containers, such as the transfer of hot molten steel or glass in a casting process, or dangerous collisions caused by swinging suspended objects in harbors or in construction areas, etc. To overcome the mentioned problems, new efficient approaches based on the so-called Acceleration Compensation Principle will be introduced in this chapter. The main idea is to modify the reference motion trajectory, in order to compensate undesirable disturbances. The position and the orientation of the robot's end-effector are adapted in such a way, that undesired acceleration side effects can be compensated and minimized. In addition, a derivation from the first proposed technique is introduced to compensate undesirable swinging oscillations. Gentle robotic handling and time optimized movements are considered as two main research objectives in the context of this work. Additionally, economic and complexity factor should be also taken into account. Beyond the achievement of optimal cycle time and the avoidance of collisions, the new algorithms are independent of the object's physical aspects and are evaluated with serial robot manipulators, as main part of the experimental test-bed, in order to verify the feasibility and effectiveness of the proposed approaches.
A model for the X-ray absorption in Compton-thin AGN

fraction of AGN with photoelectric absorption in the X-rays ranging from N H of 10 22 up to about 10 24 cm -2 (Compton-thin) appears observationally to be anticorrelated to their luminosity L,. This recently found evidence is used to investigate the location of the absorbing gas. The molecular torus invoked in the unified picture of AGN, while it can be regarded as confirmed on several grounds to explain the Compton. objects, do not conform to this new constraint, at least in its physical models as developed so far. In the frame of observationally based evidence that in Compton-thin sources the absorbing gas might be located far away from the X-ray source, it is shown that the gravitational effects of the black hole (BH) on the molecular gas in a disk, within 25-450 pc (depending on the BH mass, from 10 6 to 10 9 M ⊙ ), leads naturally to the observed anticorrelation, under the assumption of a statistical correlation between the BH mass and L,. Its normalization is also reproduced provided that the surface density, Σ, of this gas is larger than about 150-200 M ⊙ pc -2 , and assuming that the bolometric luminosity is one tenth of the Eddington limit. Interestingly, the required values are consistent with the value of the 300 pc molecular disk in our own galaxy, namely 500 M ⊙ pc -2 . In a sample of nearby galaxies from the BIMA SONG survey, it is found that half of the objects have central Σ larger than 150 M ⊙ pc -2 . Given the simplicity of the proposed model, this finding is very encouraging, waiting for future higher resolution surveys in CO on more distant galaxies.
A modular Fibonacci sequence in proteins

Protein-fragment seqlets typically feature about 10 amino acid residue positions that are fixed to within conservative substitutions but usually separated by a number of prescribed gaps with arbitrary residue content. By quantifying a general amino acid residue sequence in terms of the associated codon number sequence, we have found a precise modular Fibonacci sequence in a continuous gap-free 10-residue seqlet with either 3 or 4 conservative amino acid substitutions. This modular Fibonacci sequence is genuinely biophysical, for it occurs nine times in the SWISS-Prot/TrEMBL database of natural proteins.
Retinopathy of Prematurity Vessel and Ridge Parameters Measurement by Unsupervised Algorithm

The Retinopathy of Prematurity (ROP) is an ocular pathological disorder of the retinal blood vessels in premature infants and low birth weight infants. It is essential that those caring for premature infants should know who is at risk of ROP and their severity stage. It is also important that when screening must begin and how often these infants need to be examined otherwise the progression lead most severe stage and can cause blindness. The contrast stretching method has been utilized to enhance the ROP color image. Then an automatic method Isotropic Un-decimated Wavelet Transform (IUWT) has been proposed to extract the abnormal retinal blood vessel and measure its width and tortuosity. The ridge formation of this pathological disorder has also been obtained by the IUWT. The quantitative measurements of mean diameter, standard deviation, tortuosity, length of retinal blood vessel and ridge have been considered and computed the exact severity stage of ROP. The effectiveness of the proposed method has been verified through machine vision techniques and the results obtained are encouraged by experts. Automatic ROP screening system comprises several advantages, like a substantial time reduction of ophthalmologists in diagnosis, a non ophthalmologist can provide stage of ROP, improving the sensitivity of the test and a better accuracy in diagnosis.
A discrete optimization approach for SVD best truncation choice based on ROC curves

Truncated Singular Value Decomposition (SVD) has always been a key algorithm in modern machine learning. Scientists and researchers use this applied mathematics method in many fields. Despite a long history and prevalence, the issue of how to choose the best truncation level still remains an open challenge. In this paper, we describe a new algorithm, akin a the discrete optimization method, that relies on the Receiver Operating Characteristics (ROC) Areas Under the Curve (AUCs) computation. We explore a concrete application of the algorithm to a bioinformatics problem, i.e. the prediction of biomolecular annotations. We applied the algorithm to nine different datasets and the obtained results demonstrate the effectiveness of our technique.
Exploration and Combination: Randomized and Multi-Strategies Search in Satisﬁcing Planning

Heuristic (Informed) Search takes advantage of problemspecific knowledge beyond the definition of the problem itself to find solutions more efficiently than uninformed search, such as Breadth-First Search (BFS) and Depth-First Search (DFS). We design domain-dependent search algorithms to plan tasks. However, the domain-dependent design pattern cannot be applied to fully automatic domains, such as robots that need to plan unknown tasks. AI Planning, as a special case of heuristic search, emphasizes domainindependent approaches for solving such problems. Satisficing planning generally can handle harder problems than optimal planning. Solution optimality is not required in satisficing planning: finding a good suboptimal solution suffices. Recently, there has been great progress in satisficing planning: in the three last international planning competitions (IPC), top planners solved more than 90% of the tasks. Many problems are inspired by applications, such as oil industry, transportation and molecular biology. Considering that the top planners perform quite well over current IPC benchmarks, it is natural to check the scaling behavior of the current search algorithms as well as the reasons why the top planners do not perform well on these remaining unsolved problems. Most current state of the art satisficing planners use heuristic search techniques. During the past decades, the planning community spent a lot of effort in developing strong domain-independent heuristics to fit into the classical heuristic search algorithms. We now have many good domain-independent heuristics such as FF, causal graph (CG) and context-enhanced additive (CEA). However, because of the generality of domain-independent planning, it is hard to develop domain-independent heuristics as strong as domain-specific heuristics. It is not realistic to expect that all hard planning problems can be solved simply by combining domain-independent heuristics with classic search algorithms such as Hill-Climbing and Greedy Best First search. Since domain-independent heuristics might be uninformed or even ill-informed sometimes, we need more sophisticated search algorithms where heuristics are not reliable. Recently, more effort is spent in developing more powerful search algorithms, such as EHC (Hoffmann and Nebel 2001) and Random-Walk Planning (Nakhost and Müller 2009), as well as search enhancements such as preferred operators (Richter and Helmert 2009) and sophisticated explorative probes (Lipovetzky and Geffner 2011). There is still a lot of space to improve for current state of the art search algorithms. A typical algorithm is Greedy Best First Search (GBFS). GBFS always expands a node n that is closest to a goal state according to a heuristic h. Misleading or uninformative heuristics can massively increase the time and memory complexity of such searches. In this abstract, we are going to use GBFS as a typical example to talk about two problems closely related to my research, which also commonly exist in heuristic search algorithms: early mistakes and uninformative heuristic regions.
A robust weakly compressible SPH method and its comparison with an incompressible SPH

This paper presents a comparative study for the weakly compressible (WCSPH) and incompressible (ISPH) smoothed particle hydrodynamics methods by providing numerical solutions for fluid flows over an airfoil and a square obstacle. Improved WCSPH and ISPH techniques are used to solve these two bluff body flow problems. It is shown that both approaches can handle complex geometries using the multiple boundary tangents (MBT) method, and eliminate particle clustering‐induced instabilities with the implementation of a particle fracture repair procedure as well as the corrected SPH discretization scheme. WCSPH and ISPH simulation results are compared and validated with those of a finite element method (FEM). The quantitative comparisons of WCSPH, ISPH and FEM results in terms of Strouhal number for the square obstacle test case, and the pressure envelope, surface traction forces, and velocity gradients on the airfoil boundaries as well as the lift and drag values for the airfoil geometry indicate that the WCSPH method with the suggested implementation produces numerical results as accurate and reliable as those of the ISPH and FEM methods. Copyright © 2011 John Wiley & Sons, Ltd.
Cloning of Interleukin-10 from African Clawed Frog (Xenopus tropicalis), with the Finding of IL-19/20 Homologue in the IL-10 Locus

Interleukin-10 (IL-10) is a pleiotropic cytokine that plays an important role in immune system. In the present study, the IL-10 gene of African clawed frog (Xenopus tropicalis) was first cloned, and its expression pattern and 3D structure were also analyzed. The frog IL-10 mRNA encoded 172 amino acids which possessed several conserved features found in IL-10s from other species, including five-exon/four-intron genomic structure, conserved four cysteine residues, IL-10 family motif, and six α-helices. Real-time PCR showed that frog IL-10 mRNA was ubiquitous expressed in all examined tissues, highly in some immune related tissues including kidney, spleen, and intestine and lowly in heart, stomach, and liver. The frog IL-10 mRNA was upregulated at 24 h after LPS stimulation, indicating that it plays a part in the host immune response to bacterial infection. Another IL, termed as IL-20, was identified from the frog IL-10 locus, which might be the homologue of mammalian IL-19/20 according to the analysis results of the phylogenetic tree and the sequence identities.
Increases of Antibiotic Resistance in Excessive Use of Antibiotics in Smallholder Dairy Farms in Northern Thailand

Antibiotic resistance patterns of bacterial isolates from both quarter teat-tip swabs and their quarter milk samples were evaluated in smallholder dairy farms in northern Thailand with excessive use of antibiotics (HIGH) compared with normal use (NORM). Results from teat-tip swab samples showed that the percentage of Bacillus spp. resistance to overall antibiotics was significantly lower in the NORM group than that of the HIGH group, whereas, the resistance percentage of coagulase-negative staphylococci in the NORM group was higher than that of the HIGH one. The overall mastitis-causing bacteria isolated from milk samples were environmental streptococci (13.8%), coagulase-negative staphylococci (9.9%), Staphylococcus aureus (5.4%), and Corynebacterium bovis (4.5%). Both staphylococci and streptococci had significantly higher percentages of resistance to cloxacillin and oxacillin in the HIGH group when compared to the NORM one. An occurrence of vancomycin-resistant bacteria was also observed in the HIGH group. In conclusion, the smallholder dairy farms with excessive use of antibiotics had a higher probability of antibiotic-resistant pattern than the farms with normal use.
Distributed generalization of learned planning models in robot programming by demonstration

In Programming by Demonstration (PbD), one of the key problems for autonomous learning is to automatically extract the relevant features of a manipulation task, which has a significant impact on the generalization capabilities. In this paper, task features are encoded as constraints of a learned planning model. In order to extract the relevant constraints, the human teacher demonstrates a set of tests, e.g. a scene with different objects, and the robot tries to execute the planning model on each test using constrained motion planning. Based on statistics about which constraints failed during the planning process multiple hypotheses about a maximal subset of constraints, which allows to find a solution in all tests, are refined in parallel using an evolutionary algorithm. The algorithm was tested on 7 experiments and two robot systems.
Gold versus stock investment: An econometric analysis

It is important to have a portfolio in investment to diversify the investment to different kinds of instruments. Based on previous research, it is concluded that gold is a good portfolio diversifier, a hedge against stock and safe haven in extreme stock market condition. As an investment instrument, stock is exposed to macroeconomic risks and global stock market risks. In this research, we conduct a comparison between the stock investment and gold investment by using the probit econometric model and data from 1997 to 2011. The final result obtained from the model shows that the gold investment is more advantageous than the stock investment.
A Cooperative Spectrum Sensing Scheme Using Compressive Sampling

Cooperative spectrum sensing (CSS) schemes utilizing Compress Sampling (CS) enable efficient and reliable CSS for cognitive radio networks. Existing CSS schemes perform CS by random measurement matrixes, and thus suffer from a loss of efficiency. To counteract this drawback, this letter proposes a CS based CSS scheme using measurement matrix exploring the correlation of the primary spectrum. A reconstruction method with low complexity for CS is further investigated. Numerical results are provided to verify the effectiveness of the proposed scheme.
Exploiting Twitter for Border Security-Related Intelligence Gathering

Nowadays, an ever-growing amount of information is being transferred through web-based social media. In particular, Twitter emerged to be an important social medium providing most up-to-date information and comments on current events and topics of any kind. This led to a continuous growth of the interest of various security-related organizations in tools for real-time monitoring of Twitter streams to collect information there from. In this paper we present some initial explorations on how to exploit Twitter for border security-related intelligence gathering. To be more precise, we present techniques for: (a) retrieving and analyzing tweets posted in third countries, in which opinions and information are provided on migration to Europe or related issues (here we experimented with sentiment analysis for improving the retrieval performance), and (b) enhancing the information extracted from online news on border security-related events in third countries with information extracted from Twitter.
Gene Expression Based Cancer Classification Using Evolutionary and Non-evolutionary Methods

Recent advances in DNA microarray offer the ability to monitor and measure the expression levels of thousands of genes simultaneously in an organism. These experiments consist of monitoring each gene many times under different conditions or evaluating each gene under a single environment but in different types of tissues. The first one is useful for identification of functionally related genes while the second type of experiment is helpful in classification of different types of tissues and identification of those genes whose expression levels are good diagnostic indicators. Different machine learning approaches such as supervised and some unsupervised learning have been previously applied to classify different kinds of patient samples by identifying those genes responsible for different types of cancers. However, the main challenges in this task are the availability of a smaller number of samples compared to huge number of genes and the noisy nature of biological data. Moreover, many of these genes are irrelevant to distinction of different samples and have negative impact on acquired classification accuracy. In this paper, I provide a survey on gene expression based cancer classification using evolutionary and non-evolutionary methods.
Virtual Open Heart Surgery: Obtaining Models Suitable for Surgical Simulation

We present a pre-processing strategy including imaging, segmentation, and model reconstruction that is well suited for previously published GPU-accelerated techniques for surgical simulation. In particular we describe these modeling steps as a prerequisite for our virtual open heart surgery simulator. A short description including relevant references is presented for each of the steps.
An Effective Cache Algorithm for Heterogeneous Storage Systems

Modern storage environment is commonly composed of heterogeneous storage devices. However, traditional cache algorithms exhibit performance degradation in heterogeneous storage systems because they were not designed to work with the diverse performance characteristics. In this paper, we present a new cache algorithm called HCM for heterogeneous storage systems. The HCM algorithm partitions the cache among the disks and adopts an effective scheme to balance the work across the disks. Furthermore, it applies benefit-cost analysis to choose the best allocation of cache block to improve the performance. Conducting simulations with a variety of traces and a wide range of cache size, our experiments show that HCM significantly outperforms the existing state-of-the-art storage-aware cache algorithms.