Miracle-dz/UniFAR-FTUs huggingface dataset:
Functionalised optical fibre devices with embedded electrodes for nonlinear photonics

In this thesis are reported progresses in the development of a technique known as thermal poling of silica fibres, which allows for the creation of an effective second order nonlinearity in materials, such as glasses, which naturally lack any second order susceptibility. The main part of the thesis work was devoted to the exploration of new experimental methods as well as numerical simulations to overcome some of the apparently intrinsic limits shown by the thermal poling technique so far, such as for example the length of the nonlinear devices and the complexity of the geometrical structure of microstructured optical fibres, both solid and hollow-core. A new poling method, based on electrostatic induction, was developed and numerically modelled which allows for poling an optical fibre without any physical contact between the source of the electric potential and the electrode embedded into the fibre. Furthermore different kinds of materials (both metallic and non-metallic) have been used to create the embedded electrodes, and in particular a new method for poling metre-long optical fibres by means of aqueous solutions used as electrodes was developed. Using together both the induction poling method with liquid embedded electrodes could allow for poling metre-long fibres and microstructured fibres of very complex geometry which could raise the second harmonic efficiency up to a value of four order of magnitude higher than the one obtained in common step-index doped fibres. Part of this thesis was dedicated to the functionalisation of different kinds of silica fibres (including microstructured hollow core fibres) by means of deposition of thin layers of semiconductors (such as silicon, germanium or zinc selenide), with the aim of exploiting their intrinsic nonlinearities to increase the whole effective second order nonlinearity of an all- fibre nonlinear device.
The Role of Deformation and Microchemistry in the Corrosion Processes of Type 304 Stainless Steel in Simulated Pressurized Water Reactor Environments

xviii CHAPTER 1: Introduction . 1 1.1 Background . 1 1.2 Current work . 1 1.3 Thesis structure . 1 CHAPTER 2: Type 304 SS in Aqueous Environments: Literature Review . 3 2.1 Type 304 SS in nuclear reactors . 3 2.2 Commercial nuclear reactor environments . 4 2.3 Surface corrosion in high temperature aqueous environments . 5 2.3. 1 Methods of identifying corrosion products . 5 2.3. 2 Corrosion in oxygenated water . 5 2.3. 3 Corrosion in deoxygenated water . 6 2.3. 4 Oxide phase stability and chemistry . 6 2.3. 5 Mechanisms and growth rates . 6 2.3. 6 Role of deformation . 7 2.3. 7 Unknowns . 8 2.4 Stress corrosion cracking in high temperature aqueous environments . 9 2.4. 1 Environment . 9 2.4. 2 Material . 10 2.4. 3 Stress . 13 2.4. 4 Crack growth mechanisms . 14
Artificial immune system-based music recommendation

This paper addresses the problem of recommendation with the context of one-class classification. Specifically, we employ the alternative machine learning framework of Artificial Immune Systems (AIS) in order to develop user-specific preference models. Our approach is based on the fact that users experience a major difficulty in articulating their music preferences while at the same time they are extremely reluctant in providing counter-examples of their music habits. Therefore, developing coherent user models on the grounds of both positive (desirable) and negative (non-desirable) training samples is not a feasible task since the class of non-favorable data patterns is severely under-represented. Our recommendation approach alleviates the need to collect negative feedback form the user by building recommendation models that exclusively rely on the presence of a limited number positive data items. Such models are built, however, by trying to efficiently cover the complementary space of non-desirable patterns. This is achieved through the utilization of V-Detector, an AIS-based one-class classification algorithm, which operates by developing a set of variable-sized detectors for the subspace of non-preferable music items. V-Detector, despite being exclusively fed with instances from the positive class, focuses on delivering an accurate model of the negative space. Based on this complementarity, our recommendation algorithm is able to implicitly model individual user preferences that span arbitrary-shaped and fragmented regions of the complete space of patterns. The proposed recommendation approach was experimentally evaluated in terms of its efficiency to correctly identify the user-defined classes of positive and negative preference. The obtained results justify its superiority against traditional one-class classification approaches.
High-Intensity Intermittent Exercise Increases Fat Oxidation Rate and Reduces Postprandial Triglyceride Concentrations

(1) Background: This study investigated the effect of acute barehanded whole body high-intensity intermittent exercise (HIIE) and moderate intensity and continuous exercise (MICE) at the same quantity of energy expenditure on postprandial triglyceride (TG) concentrations. (2) Methods: Nine healthy males completed three trials (HIIE, MICE and control (CON)) in a random order separated by at least 14 days. After each intervention, the participants rested for 12 h and consumed a high-fat test meal on the next day. The blood samples and respiratory exchange ratio were observed in the fasted state and for 4 h after consuming the test meal. (3) Results: The HIIE had a significantly higher area under the curve of postprandial fat oxidation rate than MICE (p = 0.027) and CON (p = 0.035) and exhibited significantly lower postprandial TG concentration than the MICE and CON at 2 and 4 h after the test meal. Moreover, the HIIE displayed a higher postprandial TG concentration area under the curve than MICE (p = 0.013) and CON (p = 0.048). (4) Conclusions: The present study concluded that acute barehanded whole body HIIE could significantly lower postprandial TG concentrations. It possibly can induce a rise in the postprandial fat oxidation rate.
Adaptive algorithm based on a new hyperbolic sine cost function

This paper introduces a stochastic gradient algorithm, which uses an exclusive hyperbolic sine objective function. The algorithm belongs to the variable step size (VSS) class. The algorithms in this class are shown to be very stable and effective in many applications, e.g., echo-cancellation, equalization, and others. In this algorithm, as opposed to other existing VSS algorithms, only one tuning parameter is needed. Experimental results show that with a sub-optimal selection of the tuning parameter, the algorithm provides very promising results in both stationary and tracking scenarios. Analytic convergence and steady state error performance analysis are provided to demonstrate the excellent performance. Also, an optimal solution, based on the least hyperbolic sine error, is derived to confirm the convergence of the proposed algorithm towards the Wiener solution.
Brain Electrical Activity Associated With Cognitive Processing During a Looking Version of the A-Not-B Task.

This work was designed to investigate individual differences in brain electrical activity during a looking version of the A-not-B task. It was proposed that this spatial task required the cognitive skills of working memory and inhibitory control, each associated with frontal lobe function. Electroencephalograms (EEGs) were recorded from 54 8-month-old infants during baseline and task. Only high performers on the looking task exhibited increases in 6- to 9-Hz EEG power from baseline to task. These task-related changes were evident at frontal and posterior scalp locations. High performers on the looking task exhibited lower EEG coherence values at right hemisphere frontal locations relative to the low performers. These lower coherence values were evident during baseline and task. All infants showed increased frontal-parietal coherence during the spatial working memory task relative to baseline values. These data confirm previous cognitive neuroscience work associating frontal lobe function with cognitive performance levels during infancy.
Characterization of lactococcin BZ produced by Lactococcus lactis subsp. lactis BZ isolated from boza

A bacterium isolated from boza produced in Turkey was identified, and the physico-chemical and microbiological properties of its inhibitory compound were characterized. The isolate was identified as Lactococcus lactis subsp. lactis, based on morphology, physiology, carbohydrate fermentation, the fatty acid profile, and 16S rDNA gene sequence homology. The antimicrobial compound produced by the microorganism, lactococcin BZ, was sensitive to papain, pepsin, trypsin, and b-mercaptoethanol, but was resistant to catalase, amylase, lipase, organic solvents (methanol, chloroform, etc.), detergents (SDS, urea, Tween-80, Triton X-100), and EDTA. Lactococcin BZ was active against several gram-positive and gram-negative foodborne pathogens and food spoilage bacteria. Lactococcin BZ maintained its activity after high-heat treatment (90 °C for 30 min), at acidic and neutral pHs (2.0-7.0), and after storage at -20 to -80 °C for 3 months in lyophilized form. Lactococcin BZ was produced at the maximum level in MRS broth with an inoculum volume of 0.1%, an initial pH of 7.0, and an incubation temperature of 25 °C. Bacteriocin production began during the logarithmic phase and reached the maximum level during the early stationary phase. Its mode of action against Listeria monocytogenes was bactericidal and its molecular weight was about 5500 Da, as determined using tricine SDS-PAGE. Lactococcus lactis subsp. lactis BZ or its bacteriocin, which has a wide inhibitory spectrum, has the potential for use as a biopreservative in food products.
Skeletal Bone Age Assessment - Research Directions

The work was motivated by the increasing awareness of the need for bone age assessment (BAA) schemes featuring an appropriate methodology for skeletal age estimation. The endocrinological problems in youngsters are already evident in many countries worldwide, varying in scale and intensity for different age groups and sexes. Change in lifestyles and eating habits of people also contribute to endocrine disorders, increasing the need for a system that predicts such problems well in advance. Skeletal bone age assessment is a procedure often used in the management and diagnosis of endocrine disorders. It also serves as an indication of the therapeutic effect of treatment. It is of much significance in pediatric medicine in the detection of hormonal growth or even genetic disorders. Bone age is assessed from the left-hand wrist radiograph and then compared with the chronological age. A discrepancy between the two indicates abnormalities. This paper consists of an overall review and technical assessments of various skeletal age assessment schemes in the literature. This review also recommends some research areas in this field and those leading to high efficiency are highlighted
Social account linking via weighted bipartite graph matching

Along with the increasing popularity of online social network (OSN), it is common that the same user holds many accounts among different OSNs (eg, Facebook, Twitter, WeChat, QQ). In this scenario, an interesting and challenging problem arises: how to link accounts among OSNs belonged to a natural person, which is also known as a graph matching problem. The solution helps understand user behaviors and offer better services. To solve the account linking problem, various techniques for OSNs have been proposed. However, most existing methods assume specific OSN features impractical in general OSNs and unscalable to large‐scale OSNs. To address these shortcomings, in this paper, we remodel the account linking problem into maximum matching on weighted bipartite graphs and utilize the Kuhn‐Munkres algorithm to solve it. In our solution, we capture user profile, user online time distribution, and user interest as features to describe user accounts and measure account similarity, which is used as weight of edge in bipartite graphs. Then, the maximum matching on weighted bipartite graphs is solved with the Kuhn‐Munkres algorithm. The experiments conducted on the real datasets show that our solution outperforms the baseline methods with 11%, 17%, and 29% on average in precision, recall, and F1 score, respectively.
Effects of rs7903146 Variation in the Tcf7l2 Gene in the Lipid Metabolism of Three Different Populations

Background TCF7L2 rs7903146 is an important genetic factor predicting type 2 diabetes (T2DM) which has also been linked to higher cardiovascular risk. To date, there is little information about the additional impact of this single nucleotide polymorphism (SNP) beyond glucose metabolism. Methodology/Principal Findings We studied whether rs7903146 influenced postprandial lipid metabolism in three different populations (healthy young men, metabolic syndrome (MetS) patients and elderly persons). Eighty-eight healthy males were submitted to a single saturated fatty acid-rich test meal. Additionally, 110 middle-aged MetS patients and 20 healthy elderly persons (≥65 years) were submitted to three different dietary models followed by test meals. Minor allele homozygotes for rs7903146 showed a worse postprandial lipemia profile in young males, as seen by a lower HDL-cholesterol and Apo A1 concentration during the postprandial lipemia and a trend towards higher triglycerides (TG), than the other genotypes. In healthy elderly persons, carriers of the minor allele showed higher total cholesterol, LDL-cholesterol, Apo B and TG in the fasting state, and a higher postprandial area under the curve for total cholesterol, Apo B, small-triglyceride rich lipoprotein (TRL) cholesterol and small-(TRL) triglycerides. These results were accompanied by differential changes in adipokines. We did not observe any influence of rs7903146 on the postprandium of MetS patients. Conclusions/Significance Healthy young males and elderly persons who are carriers of the mutant allele for rs7903146 have an impaired postprandial lipid metabolism that may be mediated by an alteration in adipokine regulation, and may be related to the higher cardiovascular risk observed in these persons. Trial Registration ClinicalTrials.gov NCT00429195
A Conceptual Framework for Learning Systems Evaluation

A conceptual framework for learning systems evaluation based on literature review is proposed. Learning systems are the most recent way to carry out distance education by distributing learning material and processes over the Internet. It’s anytime, and any place vision could be part of a winning strategy for particular needs, such as provide support for students. However, there are many problems in the process of developing learning systems, particularly on evaluation such as what to evaluate, how many samples should be used and how much time should take the interaction with the system. This study purpose some answers to these questions based on literature review and experts opinions. This work does not pretend to be a final solution to these problems; it tries to provide some standardization of aspects involved in experiment design for evaluating learning systems. The conceptual framework includes some factors to be assessed; also, it proposed some instruments to measure each factor and some reference numbers of sample and interaction time. The framework is scalable, and as future work, it was suggested to enhance it adding more factors, instruments and other experimental characteristics such as statistic hypothesis test for each factor.
Carbon Nanotube Capacitors 373 Carbon Nanotube Capacitors

Capacitors are important components in many integrated circuits. They serve numerous roles in analog and mixed signal circuits, including switched capacitor filters and sampleand-hold circuits. In addition, capacitors provide a vital role in the decoupling of microprocessors, digital signal processors, and microcontrollers from power supply variations. Traditional integrated circuit capacitors use a parallel plate structure. The capacitance of these parallel plate structures is fundamentally limited by the die area they consume and the thickness of the dielectric material between the parallel plates. However, increasing the capacitance of traditional parallel plate capacitors by increasing the die area (resulting in a more expensive component) or decreasing the dielectric thickness (resulting in a higher leakage current) contradicts two of the fundamental tenements of integrated circuit design (ITRS, 2008). Carbon nanotubes (CNTs) are nanotechnology materials that have been in prominence for the last several years. They are cylinders of graphene that can exhibit radii on the order of nanometers. CNTs exhibit a number of properties that make them attractive as potential horizontal and vertical interconnects in future integrated circuits (Naeemi et al., 2004, Naeemi et al., 2005, Raychowdhury & Roy, 2004). The same properties allow CNTs to be used to create a new capacitor structure suitable for use in future integrated circuits (Budnik et al., 2006). In this chapter we introduce these CNT capacitor structures and compare their capacitance per unit area with existing technologies. The chapter is organized as follows. Section 2 reviews the structure and limitations of traditional parallel plate capacitors in integrated circuits. Section 3 briefly introduces CNTs, their varieties, and how they can be manufactured. Section 4 reviews the electrical models that have been developed for CNTs for use in the development of a CNT capacitor model. Section 5 formally introduces CNT capacitor devices as an extrapolation of the currently proposed CNT interconnects. Three different CNT capacitor structures and their electrical models are presented in this section. Finally, the conclusions are presented in Section 6.
80-Gb/s OTDM System Analysis of a Vertical Microcavity-Based Saturable Absorber for the Enhancement of Pulse Pedestal Suppression

In future high-speed optical time-division-multiplexed (OTDM) systems, an important factor that needs to be considered for optical pulse generation schemes is the impact of pulse pedestals on the overall system performance. The results presented in this letter are two-fold; first, the impact due to the height of pulse pedestals in an 80-Gb/s OTDM system are established. Second, a solution is provided to overcome these high pedestal levels through the use of a vertical microcavity saturable absorber, which can significantly reduce the pulse pedestal level and give enhanced system performance
Efficient Zero-Forcing Precoder Design for Weighted Sum-Rate Maximization With Per-Antenna Power Constraint

This paper proposes an efficient (semi-closed-form) zero-forcing (ZF) precoder design for the weighted sum-rate maximization problem under per-antenna power constraint (PAPC). Existing approaches for this problem are based on either interior-point methods that do not favorably scale with the problem size or subgradient methods that are widely known to converge slowly. To address these shortcomings, our proposed method is derived from three elements: minimax duality, alternating optimization (AO), and successive convex approximation (SCA). Specifically, the minimax duality is invoked to transform the considered problem into an equivalent minimax problem, for which we then recruit AO and SCA to find a saddle point, which enables us to take advantages of closed-form expressions and hence achieve fast convergence rate. Moreover, the complexity of the proposed method scales linearly with the number of users, compared to cubically for the standard interior-point methods. We provide an analytical proof for the convergence of the proposed method and numerical results to demonstrate its superior performance over existing approaches. Our proposed method offers a powerful tool to characterize the achievable rate region of ZF schemes under PAPC for massive multiple-input multiple-output.
Physical-layer entity authentication scheme for mobile MIMO systems

Exploiting physical layer in achieving different security aspects in wireless communications has been widely encouraged. In this work, the authors propose an entity authentication scheme for mobile devices with multiple antennas, which is purely based on physical layer parameters. According to the proposed scheme, in order to authenticate a device, a number of predefined authentication signals should be detected at the receive antennas on the authenticator side. The transmitted signals are designed based on the instantaneous channel responses in order to deliver the authentication signals to the receiver. The proposed scheme works efficiently even for mobile users, which is considered a significant improvement over previous related works. Mathematical analysis of the different involved factors along with sufficient simulations show the high performance of the proposed authentication scheme.
Genome-Wide Association Studies of 11 Agronomic Traits in Cassava (Manihot esculenta Crantz)

Cassava (Manihot esculenta Crantz) is a major tuberous crop produced worldwide. In this study, we sequenced 158 diverse cassava varieties and identified 349,827 single-nucleotide polymorphisms (SNPs) and indels. In each chromosome, the number of SNPs and the physical length of the respective chromosome were in agreement. Population structure analysis indicated that this panel can be divided into three subgroups. Genetic diversity analysis indicated that the average nucleotide diversity of the panel was 1.21 × 10-4 for all sampled landraces. This average nucleotide diversity was 1.97 × 10-4, 1.01 × 10-4, and 1.89 × 10-4 for subgroups 1, 2, and 3, respectively. Genome-wide linkage disequilibrium (LD) analysis demonstrated that the average LD was about ∼8 kb. We evaluated 158 cassava varieties under 11 different environments. Finally, we identified 36 loci that were related to 11 agronomic traits by genome-wide association analyses. Four loci were associated with two traits, and 62 candidate genes were identified in the peak SNP sites. We found that 40 of these genes showed different expression profiles in different tissues. Of the candidate genes related to storage roots, Manes.13G023300, Manes.16G000800, Manes.02G154700, Manes.02G192500, and Manes.09G099100 had higher expression levels in storage roots than in leaf and stem; on the other hand, of the candidate genes related to leaves, Manes.05G164500, Manes.05G164600, Manes.04G057300, Manes.01G202000, and Manes.03G186500 had higher expression levels in leaves than in storage roots and stem. This study provides basis for research on genetics and the genetic improvement of cassava.
Pattern discrimination method with a boosting approach using hierarchical neural trees

This paper proposes a new pattern classification method using probabilistic neural networks based on a boosting approach. In this method, a log-linearized Gaussian mixture network is used as a weak classifier. The method proposed automatically constructs a suitable classification network from given data. Validity of the proposed method is shown by discrimination results of artificial data and hand shape. The application is confirmed of the proposed method to human interface controlling of home electric appliances using hand shapes.