Miracle-dz/UniFAR-FTUs huggingface dataset:
Face Recognition Based on Nonlinear Feature Approach

Feature extraction techniques are widely used to reduce the complexity high dimensional data. Nonlinear feature extraction via Locally Linear Embedding (LLE) has attracted much attention due to their high performance. In this paper, we proposed a novel approach for face recognition to address the challenging task of recognition using integration of nonlinear dimensional reduction Locally Linear Embedding integrated with Local Fisher Discriminant Analysis (LFDA) to improve the discriminating power of the extracted features by maximize between-class while within-class local structure is preserved. Extensive experimentation performed on the CMU-PIE database indicates that the proposed methodology outperforms Benchmark methods such as Principal Component Analysis (PCA), Fisher Discrimination Analysis (FDA). The results showed that 95% of recognition rate could be obtained using our proposed method.
Pharmacokinetic and pharmacodynamic drug–drug interaction assessment between pradigastat and digoxin or warfarin

Pradigastat, a novel diacylglycerol acyltransferase‐1 inhibitor, was evaluated for both pharmacokinetic (PK) and pharmacodynamic (PD) drug–drug interactions when co‐administered with digoxin or warfarin in healthy subjects. This open‐label study included two parallel subject cohorts each with three sequential treatment periods. Forty subjects were enrolled in the study with 20 subjects allocated to each cohort. PK and PD (PT/INR for warfarin only) samples were collected in each period. The statistical analysis results showed that the 90% CIs of the geometric mean ratios of digoxin, R‐warfarin, and S‐warfarin PK parameters (AUC and Cmax) were all within 0.80–1.25 interval. The 90% CIs of the geometric mean ratios of pradigastat PK parameters (AUC and Cmax) were within 0.80–1.25 interval when co‐administered with warfarin; while co‐administration with digoxin slightly reduced pradigastat exposure (∼15%). The results also showed that 90% CIs of the geometric mean ratios of warfarin PD parameters (AUCPT, PTmax, AUCINR, and INRmax) were within 0.80–1.25 interval. Pradigastat and digoxin or warfarin had no relevant clinical PK or PD drug–drug interactions. Administration of pradigastat and warfarin or pradigastat and digoxin as a mono or combined treatment appears to be safe and tolerated.
Structural refinement and photocatalytic properties of CuWO4 crystals

In this chapter, we report the synthesis of copper tungstate (CuWO4) crystals by the co-precipitation/calcination method at 100, 200, 300, 400 and 500oC for 1 h. These crystals were structurally characterized by means of X-ray diffraction (XRD), Rietveld refinement and micro-Raman spectroscopy. XRD patterns indicated a structural evolution at long-range from amorphous to crystalline CuWO4 nanocrystals with the increase of calcination temperature. Structural refinement data and micro-Raman spectrum confirm that CuWO4 crystals calcinated at 500oC have a triclinic structure. Ultraviolet-visible (UV-vis) diffuse reflectance spectroscopy evidenced a decrease of optical band gap values (from 2.35 eV to 2.07 eV) with the raise of calcination temperature. Transmission electron microscopy (TEM) images showed that these CuWO4 crystals present a polydisperse particle size distribution in consequence of a predominant growth mechanism via aggregation of several nanocrystals. TEM and high resolution (HR)-TEM images indicate a predominantly amorphous material on the CuWO4 calcined at 100oC. From 200oC, a crystallization process was observed due to formation of small CuWO4 crystals (2 – 3 nm) on the amorphous CuWO4 aggregates. At 300oC, occurs a raise in crystal growth and formation of faceted nanocrystals with average crystals size of 50 nm. Moreover, thermal energy promotes an increase in the crystal growth. HR-TEM images indicate the presence of an amorphous layer on the crystal surface heat treated at 400oC. This amorphous layer was reduced on the CuWO4 crystals processed at 500oC. Finally, we have studied the photocatalytic properties of CuWO4 nanocrystals as a catalyst in the degradation of rhodamine B dye under UV light.
Consequences of a false-positive mammography result: drug consumption before and after screening

Abstract Background Previous research showed women experiencing false-positive mammograms to have greater anxiety about breast cancer than women with normal mammograms. To elucidate psychological effects of false-positive mammograms, we studied impact on drug intake. Methods We calculated the ratio of drug use for women with false-positive versus women with normal mammograms, before and after the event, using population-based registers, 1997–2006. The ratio of the ratios (RRR) assessed the impact. Results Before the test, 40.3% of women from the false-positive group versus 36.2% from the normal group used anxiolytic and antidepressant drugs. There was no difference in use of beta blockers. Hormone therapy was used more frequently by the false-positive, 36.6% versus 28.7%. The proportion of women using anxiolytic and antidepressant drugs increased with 19% from the before to the after period in the false-positive group, and with 16% in the normal group, resulting in an RRR of 1.02 (95% CI 0.92–1.14). RRR was 1.03 for beta blockers, 0.97 for hormone therapy. Conclusion(s) Drugs used to mitigate mood disorders were used more frequently by women with false-positive than by women with normal mammograms already before the screening event, while the changes from before to after screening were similar for both groups. The results point to the importance of control for potential selection in studies of screening effects.
Adaptive algorithm for sparse system identification using projections onto weighted ℓ1 balls

This paper presents a novel projection-based adaptive algorithm for sparse system identification. Sequentially observed data are used to generate an equivalent number of closed convex sets, namely hyperslabs, which quantify an associated cost criterion. Sparsity is exploited by the introduction of appropriately designed weighted ℓ1 balls. The algorithm uses only projections onto hyperslabs and weighted ℓ1 balls, and results into a computational complexity of order O(L) multiplications/additions and O(Llog2 L) sorting operations, where L is the length of the system to be estimated. Numerical results are also given to validate the proposed method against very recently developed sparse LMS and RLS type of algorithms, which are considered to belong to the same type of algorithmic family.
Physical inactivity in relation to self-rated eyesight: cross-sectional analysis from the English Longitudinal Study of Ageing

Background To assess the cross-sectional association between self-rated eyesight and physical activity behaviour in a large general population sample of older English adults. Methods Analyses of data from the English Longitudinal Study of Ageing. Participants provided information on self-rated eyesight (categorised as: excellent/very good/good/fair–poor) and their own physical activity levels (categorised as: inactive/moderate only at least 1/week, vigorous at least 1/week). Associations between self-rated eyesight and physical activity levels were examined using logistic regression. Results A total of 6634 participants (mean age 65.0±9.2 years) were included in the analyses. In adjusted logistic regression models, those with fair–poor and good eyesight were significantly more likely to be inactive than those who reported excellent eyesight (OR 2.07, 95% CI 1.58 to 2.72; OR 1.59, 1.27 to 1.99, respectively). Conclusion In this sample of older English adults, those with self-rated fair–poor vision were over twice as likely to be physically inactive than those who reported having excellent vision. When consistent data have emerged, interventions to increase physical activity in those who have poor eyesight are needed.
Stability of Stationary Distributions in Monotone Economies

This paper generalizes the sufficient conditions for stability of monotone economies and time series models due to Hopenhayn and Prescott (Econometrica, 60, p. 1387–1406, 1992). We introduce a new order-theoretic mixing condition and characterize stability for monotone economies satisfying this condition. We also provide a range of results that can be used to verify our mixing condition in applications, as well as the other components of our main stability theorem. Through this approach, we extend Hopenhayn and Prescott’s method to a significantly larger class of problems, and develop new perspectives on the causes of instability and stability.
GRiD: Gathering rich data from PubMed using one-class SVM

The Medical Subject Headings (MeSH) term search is typical data-gathering method in biomedical text mining. However, it has two problems: the allocation delay of the MeSH term and missing valuable literature sources. Since MeSH term allocation is performed by a human being, the allocation process has delay. In addition, even if a literature source was allocated with a MeSH term, there is a still the problem that valuable literature sources are missed during the data-gathering process. There are literature sources that are not indexed to the MeSH term of a keyword, even though it contains valuable information related to the MeSH term. The MeSH term search misses these valuable literature sources. In order to resolve these problems, we propose a novel method to gather rich data using a one-class support vector machine (SVM) and relevance rule. The term frequency-inverse document frequency (TF-IDF) and paragraph vector are examined as text vectorization methods with various parameters and relevance factors. We apply our method to lung cancer, prostate cancer, breast cancer, and Alzheimer's disease. As a result, up to 26% of keyword data and 35% of target data are gathered with high quality (a C-score of at least 0.948).
Efficient Computation of Shortest Path-Concavity for 3D Meshes

In the context of shape segmentation and retrieval object-wide distributions of measures are needed to accurately evaluate and compare local regions of shapes. Lien et al. [16] proposed two point-wise concavity measures in the context of Approximate Convex Decompositions of polygons measuring the distance from a point to the polygon's convex hull: an accurate Shortest Path-Concavity (SPC) measure and a Straight Line-Concavity (SLC) approximation of the same. While both are practicable on 2D shapes, the exponential costs of SPC in 3D makes it inhibitively expensive for a generalization to meshes [14]. In this paper we propose an efficient and straight forward approximation of the Shortest Path-Concavity measure to 3D meshes. Our approximation is based on discretizing the space between mesh and convex hull, thereby reducing the continuous Shortest Path search to an efficiently solvable graph problem. Our approach works out-of-the-box on complex mesh topologies and requires no complicated handling of genus. Besides presenting a rigorous evaluation of our method on a variety of input meshes, we also define an SPC-based Shape Descriptor and show its superior retrieval and runtime performance compared with the recently presented results on the Convexity Distribution by Lian et al. [12].
A Tunable Analog Conditioning Circuit Applied to Magnetoresistive Sensors

This paper presents an adaptive processing system based on analog-digital circuits to extend the linear range of angular position sensors compensating the temperature-dependent drift. System-level simulations give a sensor output improvement higher than 70%, which drastically reduces deviations due to temperature. The building block architecture characteristics make these circuits suitable for implementing the ldquosmartnessrdquo part of smart sensors in embedded systems.
Robustness and Uncertainty Aversion

Max-min expected utility theory uses multiple prior distributions to represent a decision maker’s uncertainty aversion. Robust control theory models a decision maker who fears that the data are generated by an unknown perturbation of his approximating model. We link the two approaches by interpreting the set of perturbations in robust control theory as the multiple priors of the max-min expected utility theory. Using a Brownian motion information structure, we construct recursive versions of max-min expected utility theory and robust control theory.
Characterization of a Functional Hydrogel Layer on a Silicon-Based Grating Waveguide for a Biochemical Sensor

We numerically demonstrated the characteristics of a functional hydrogel layer on a silicon-based grating waveguide for a simple, cost-effective refractive index (RI) biochemical sensor. The RI of the functional hydrogel layer changes when a specific biochemical interaction occurs between the hydrogel-linked receptors and injected ligand molecules. The transmission spectral profile of the grating waveguide shifts depends on the amount of RI change caused by the functional layer. Our characterization includes the effective RI change caused by the thickness, functional volume ratio, and functional strength of the hydrogel layer. The results confirm the feasibility of, and set design rules for, hydrogel-assisted silicon-based grating waveguides.
Assessing Psychometric Equivalence of Paper-and-Pencil and Interactive Voice Response (IVR) Modes of Administration for the EQ-5D and the QLQ-C30

Electronic data capture technologies, such as interactive voice response (IVR) systems, are emerging as important alternatives for collecting self-reported data. The purpose of this research was to assess the measurement equivalence between the original paper-based versions and the adapted interactive voice response (IVR) versions of the EQ-5D and the QLQ-C30. Furthermore, we examined the test-retest reliability of two consecutive administrations of the IVR versions of the EQ-5D and the QLQ-C30. The comparison of the paper and IVR versions of the EQ-5D was conducted utilizing a crossover design with subjects randomly assigned to one of two assessment orders: 1) paper then IVR or 2) IVR then paper. A convenience sample of in-treatment outpatient cancer clinic patients (n=139) were asked to complete each assessment two days apart. For the test-retest component, outpatient cancer clinic patients (n=127) were asked to complete the IVR-based EQ-5D twice, two days apart. The analyses tested for mean differences (paired t-test) and test-retest reliability (ICC). In the crossover analysis, ten of the fifteen mean differences analyzed for the scales and items of the QLQ-C30 were within the equivalence interval set a priori. The ICCs for the scales and items of the QLQ-C30 ranged from 0.698 to 0.899. Two of the items, insomnia and appetite loss, did not meet our threshold of being statistically different from an ICC of 0.70. The EQ-5D index score means were equivalent between paper and IVR, however the EQ VAS score differences were not wholly contained in the equivalence interval. The ICCs were above 0.890 for the index and the EQ VAS. In the test-retest analysis, the ICCs for the nine multi-item scales for the QLQ-C30 were all
Distributed under Creative Commons Cc-by 4.0 Are Mountain Habitats Becoming More Suitable for Generalist than Cold-adapted Lizards Thermoregulation?

Mountain lizards are highly vulnerable to climate change, and the continuous warming of their habitats could be seriously threatening their survival. We aim to compare the thermal ecology and microhabitat selection of a mountain lizard, Iberolacerta galani, and a widely distributed lizard, Podarcis bocagei, in a montane area. Both species are currently in close syntopy in the study area, at 1,400 m above the sea level. We determined the precision, accuracy and effectiveness of thermoregulation, and the thermal quality of habitat for both species. We also compared the selection of thermal microhabitats between both species. Results show that I. galani is a cold-adapted thermal specialist with a preferred temperature range of 27.9–29.7 • C, while P. bocagei would be a thermal generalist, with a broader and higher preferred temperature range (30.1–34.5 • C). In addition, I. galani selects rocky substrates while P. bocagei selects warmer soil and leaf litter substrates. The thermal quality of the habitat is higher for P. bocagei than for I. galani. Finally, P. bocagei achieves a significantly higher effectiveness of thermoregulation (0.87) than I. galani (0.80). Therefore, these mountain habitat conditions seem currently more suitable for performance of thermophilic generalist lizards than for cold-specialist lizards.
On the Design of a High-Efficiency Double-Beam Gyrotron

The gyrotron that operates with a double electron beam is designed and presented. The design of a 42-GHz 200-kW gyrotron at TE03 mode has been done and presented elsewhere. To enhance the RF power without losing the interaction efficiency of the 42-GHz gyrotron, double electron beams are launched into the cavity. The beam-wave interaction calculations and power and frequency growth estimation are performed and compared with the single-beam operation results. In the design of the gyrotron, in-house developed codes, GCOMS, MIGSYN, and MIGANS, as well as commercially available codes MAGIC and EGUN are used. The results show that more than 400 kW of power is not possible by single-beam operation while the double-beam operation shows this amount of power with the same mode. To achieve the double electron beams of the desired parameters at the cavity region, the double-beam magnetron injection gun (MIG) is designed. The results of the interaction cavity and MIG show the feasibility of the double-beam gyrotron for high-power and high-efficiency operation.
Modeling User Leniency and Product Popularity for Sentiment Classification

Classical approaches to sentiment classification exploit only textual features in a given review and are not aware of the personality of the user or the public sentiment toward the target product. In this paper, we propose a model that can accurately estimate the sentiment polarity by referring to the user leniency and product popularity computed during testing. For decoding with this model, we adopt an approximate strategy called “two-stage decoding. ” Preliminary experimental results on two realworld datasets show that our method significantly improves classification accuracy over existing state-of-the-art methods.
Implementation of Taguchi method to investigate the effect of electrophoretic deposition parameters of SnO2 on dye sensitised solar cell performance

ABSTRACT In the present work, photoanodes for dye-sensitised solar cell (DSSC) composed of SnO2 nanoparticles were developed by electrophoretic deposition (EPD) process . Taguchi experimental design was adopted to investigate the effect of EPD parameters into the physical and chemical properties of the deposited film. The deposited photoanodes were characterized by scanning electron microscopy (SEM) and optical microscope. Also, electrical measurements were conducted with the aim to evaluate the effect of the deposition parameters on the DSSC current density. The experimental results reveal that magnesium nitrate concentration has the most significant effect on the photocurrent densities followed by the time of deposition. It has been observed that the deposition parameters studied greatly influence the morphology of the obtained film. This indicates that the electrophoretic deposition process under a Taguchi design orthogonal array might be a cost efficient method to develop anodes for DSSC.
Task switching ability in mild cognitive impairment

There is growing evidence of executive function deficits in mild cognitive impairment (MCI) and task switching ability has been shown to predict MCI transition to Alzheimer's disease. We tested task switching ability using a cued task switching paradigm in 27 MCI patients. Sixteen patients could perfume the task (MCI-able) and 11 could not (MCI-unable). Neuropsychological, electrophysiological, neuroanatomical, genetic, demographic, health-related data are presented for the MCI sub-groups and normal controls. The most significant finding of this study is that task-switching ability can be a powerful tool in characterizing this heterogeneous population. We found that most MCI patients exhibit some form of task-switching deficits, but to vastly different degrees. On the one hand there are individuals closer to the normal aging end of the cognitive spectrum; these individuals may present with memory deficits relative to their normal age peers but can compensate these with quasi-intact executive functions and have a high probability of remaining dementia free as long as their executive functions remain adequate. On the other side of the spectrum, there are individuals who perfume poorly on executive tasks as well as having significant episodic memory deficits. These individuals appear to have a high probability of developing AD or dying within four years. iii
Physics-inspired topology changes for thin fluid features

We propose a mesh-based surface tracking method for fluid animation that both preserves fine surface details and robustly adjusts the topology of the surface in the presence of arbitrarily thin features like sheets and strands. We replace traditional re-sampling methods with a convex hull method for connecting surface features during topological changes. This technique permits arbitrarily thin fluid features with minimal re-sampling errors by reusing points from the original surface. We further reduce re-sampling artifacts with a subdivision-based mesh-stitching algorithm, and we use a higher order interpolating subdivision scheme to determine the location of any newly-created vertices. The resulting algorithm efficiently produces detailed fluid surfaces with arbitrarily thin features while maintaining a consistent topology with the underlying fluid simulation.
Fault Analysis using State-of-the-art Classifiers

Fault Analysis is the detection and diagnosis of malfunction in machine operation or process control. Early fault analysis techniques were reserved for high critical plants such as nuclear or chemical industries where abnormal event prevention is given utmost importance. The techniques developed were a result of decades of technical research and models based on extensive characterization of equipment behavior. This requires in-depth knowledge of the system and expert analysis to apply these methods for the application at hand. Since machine learning algorithms depend on past process data for creating a system model, a generic autonomous diagnostic system can be developed which can be used for application in common industrial setups. In this thesis, we look into some of the techniques used for fault detection and diagnosis multi-class and one-class classifiers. First we study Feature Selection techniques and the classifier performance is analyzed against the number of selected features. The aim of feature selection is to reduce the impact of irrelevant variables and to reduce computation burden on the learning algorithm. We introduce the feature selection algorithms as a literature survey. Only few algorithms are implemented to obtain the results. Fault data from a Radio Frequency (RF) generator is used to perform fault detection and diagnosis. Comparison between continuous and discrete fault data is conducted for the Support Vector Machines (SVM) and Radial Basis Function Network (RBF) classifiers. In the second part we look into one-class classification techniques and their application to fault detection. One-class techniques were primarily developed to identify one class of objects from all other possible objects. Since all fault occurrences in a system cannot be