Miracle-dz/UniFAR-FTUs huggingface dataset:
Electrical tree growth in epoxy resin under DC voltages

This work investigates electrical tree propagation in a glassy epoxy resin under constant DC voltages of +60 kV and -60 kV, using samples with classical needle-plane electrodes but having small AC trees (henceforth called `initial trees') incepted prior to the DC tests. The characteristics of DC trees propagating from an initial tree is analysed via a sequence of 2-D projections of trees captured using a CCD camera during the test. The experimental results suggest that DC tree growth rate is polarity dependent even when initiated by the presence of an initial AC tree. The shape of the initial AC tree does not have a profound influence on the shape of the DC tree. The length of the initial tree, however, may have a determinant influence on the growth of DC tree. DC treeing exhibits a runway propagation and statistical analysis suggests that tree growth starts to accelerate after reaching a certain distance across the insulation.
Alternative passive maps in the Brayton-Moser framework: Implications on control and optimization

In the recent years, passivity theory has gained renewed attention because of its advantages and practicality in modeling of multi-domain systems and constructive control techniques. Unlike Lyapunov theory, passivity theory takes a behavioral approach in its control design methodologies. Hence, it provides solutions, which not only achieve the control objectives, but are also easily interpretable in the standard engineering parlance. The fundamental idea in passivity based control (PBC) methodologies is to find a controller that renders the closed-loop system passive. It is well known that, the PBC methodologies that rely on power-conjugate port-variables do not work for control objectives that require bounded power and unbounded energy. This is commonly known as the dissipation obstacle. One possible alternative that has been well explored, in the case of finite dimensional systems, is Brayton-Moser formulation. However, designing controllers in this framework leads to various difficulties, such as, solving for partial differential equations and finding storage functions satisfying a gradient structure.
Computerized comprehensive data analysis of lung imaging database consortium (LIDC).

PURPOSE Lung Image Database Consortium (LIDC) is the largest public CT image database of lung nodules. In this study, the authors present a comprehensive and the most updated analysis of this dynamically growing database under the help of a computerized tool, aiming to assist researchers to optimally use this database for lung cancer related investigations. METHODS The authors developed a computer scheme to automatically match the nodule outlines marked manually by radiologists on CT images. A large variety of characteristics regarding the annotated nodules in the database including volume, spiculation level, elongation, interobserver variability, as well as the intersection of delineated nodule voxels and overlapping ratio between the same nodules marked by different radiologists are automatically calculated and summarized. The scheme was applied to analyze all 157 examinations with complete annotation data currently available in LIDC dataset. RESULTS The scheme summarizes the statistical distributions of the abovementioned geometric and diagnosis features. Among the 391 nodules, (1) 365 (93.35%) have principal axis length < or =20 mm; (2) 120, 75, 76, and 120 were marked by one, two, three, and four radiologists, respectively; and (3) 122 (32.48%) have the maximum volume overlapping ratios -80% for the delineations of two radiologists, while 198 (50.64%) have the maximum volume overlapping ratios <60%. The results also showed that 72.89% of the nodules were assessed with malignancy score between 2 and 4, and only 7.93% of these nodules were considered as severely malignant (malignancy > or =4). CONCLUSIONS This study demonstrates that LIDC contains examinations covering a diverse distribution of nodule characteristics and it can be a useful resource to assess the performance of the nodule detection and/or segmentation schemes.
Personalization in Mobile Activity Recognition System Using K-Medoids Clustering Algorithm

Nowadays mobile activity recognition (AR) has been creating great potentials in many applications including mobile healthcare and context-aware systems. Human activities could be detected based on sensory data that are available on today’s smart phone. In this study, we consider mobile phones as an independent device since sending the data to central server can generate privacy issues. Furthermore, applying AR on mobile phone does not only require an effective accuracy rate but also the lowest power consumption. Normally, an AR model learnt from acceleration data of a specific person is distributed to other people to recognize the same activities instead of generating different models individually. This work often cannot create accurate results on the prediction in broad range of participants. Moreover, such AR model also has to allow each user to update his new activities independently. Therefore, we propose an algorithm that integrates Support Vector Machine classifier and -medoids clustering method to resolve completely the demand.
Biocompatible micelles based on comb-like PEG derivates: formation, characterization, and photo-responsiveness.

A novel comb-like derivative CPEG-g-DNQ was prepared by incorporating light responsive 2-diazo-1,2-naphthoquinone (DNQ) groups into the structure of comb-like poly(ethylene glycol) (CPEG). DLS and TEM results showed that CPEG-g-DNQ self-assembled into spherical micelles with an average size of about 135 nm in water. Upon exposure to light, the micelles could be disrupted because of the conversion of hydrophobic DNQ to hydrophilic 3-indenecarboylic acid. Additionally, hydrophobic coumarin 102 was successfully loaded into the micelles and photo-induced ON-OFF release was demonstrated by fluorescence spectroscopy. MTT assay revealed that the micelles are biocompatible. These photo-responsive micelles might have great potential for controlled release of hydrophobic drugs.
Fragmentation and matrix contrast favor understory plants through negative cascading effects on a strong competitor palm.

Understanding the patterns and processes driving biodiversity maintenance in fragmented tropical forests is urgently needed for conservation planning, especially in species-rich forest reserves. Of particular concern are the effects that habitat modifications at the landscape scale may have on forest regeneration and ecosystem functioning: a topic that has received limited attention. Here, we assessed the effects of landscape structure (i.e., forest cover, open area matrices, forest fragmentation, and mean inter-patch isolation distance) on understory plant assemblages in the Los Tuxtlas Biosphere Reserve, Mexico. Previous studies suggest that the demographic burst of the strong competitor palm Astrocaryum mexicanum in the core area of this reserve limits plant recruitment and imperils biodiversity conservation within this protected area. Yet, the local and landscape predictors of this palm, and its impact on tree recruitment at a regional scale are unknown. Thus, we used structural equation modeling to assess the direct and cascading effects of landscape structure on stem and species density in the understory of 20 forest sites distributed across this biodiversity hotspot. Indirect paths included the effect of landscape structure on tree basal area (a proxy of local disturbance), and the effects of these variables on A. mexicanum. Density of A. mexicanum mainly increased with decreasing both fragmentation and open areas in the matrix (matrix contrast, hereafter), and such an increase in palm density negatively affected stem and species density in the understory. The negative direct effect of matrix contrast on stem density was overridden by the indirect positive effects (i.e., through negative cascading effects on A. mexicanum), resulting in a weak effect of matrix contrast on stem density. These findings suggest that dispersal limitation and negative edge effects in more fragmented landscapes dominated by open areas prevent the proliferation of this palm species, enhancing the diversity and abundance of understory trees. This "positive" news adds to an increasing line of evidence suggesting that fragmentation may have some positive effects on biodiversity, in this case by preventing the proliferation of species that can jeopardize biodiversity conservation within tropical reserves.
Twenty-Four Poetic Moods: Poetry and Personality in Chinese Aesthetics

This article identifies certain universal characteristics of creativity and shows how along these general themes the Chinese culture marks its variations. Textual analysis centers on one of the most important texts of literary thought in Chinese poetics, The Twenty-Four Categories of Poetry by Ssu-k'ung T'u (837-908). This text is particularly suited for the present purposes because of its dual referentiality to poetry and personality at once. Thematic analysis reveals that the Chinese prototype of creativity consists of most of the essential ingredients of the creative personality as identified in the research literature, such as autonomy and its related traits, the nonconformist dimension of openness to experience, and intrinsic motivation. It also shows how Chinese poetics is unique in its high degree of self-reflexivity and its extensive use of the dialectical principles of complementarity. Furthermore, it shows how the Chinese personality profile of creativity contains the basic traits of psychoticism as identified by Eysenck (1993, 1995) and others, but with important cultural variations.
Augmenting Locomotion in an Anthropomorphic System

A powered orthosis has applications ranging from assisting the elderly to augmenting astronauts. An assistive control scheme is developed that uses the force from a slave actuator to augment the force of a master actuator. This can be used to augment a closed-loop control scheme applied to the master actuator. Initially, actuator augmentation is explored both theoretically and experimentally using a simple mechanical system. The control scheme is then applied to a scale model of human lower limbs on a stationary bicycle to investigate the feasibility of a powered orthosis using pneumatic muscle actuators.
Sharing the Incomati waters: cooperation and competition in the balance

The water resources of the Incomati river basin, shared between South Africa, Swaziland and Mozambique, are intensively used. Moreover, the basin is situated in a part of Africa that over the last 40 years has experienced a dynamic, sometimes turbulent and volatile, political history. Both ingredients might have been sufficient for the emergence of confrontations over water. Tensions between Mozambique, South Africa and Swaziland over Incomati waters existed but never escalated. This case study attempts to explain why cooperation prevailed, by presenting information about the natural characteristics of the basin, its political history, water developments and the negotiations that took place during the period 1967-2002. The paper provides four explanations why tensions did not escalate and cooperation prevailed. It is concluded that the developments in the Incomati basin support the hypothesis that water drives peoples and countries towards cooperation. Increased water use has indeed led to rising cooperation. When the next drought comes and Mozambique, South Africa and Swaziland enforce their recently concluded agreement, and voluntarily decrease those water uses deemed less essential, then the hypothesis has to be accepted.
A scalability test of Gaussian bare-bones differential evolution on high-dimensional optimization problems

Gaussian bare-bones differential evolution (GBDE) is a new differential evolution (DE) variant, which has shown good search abilities on low-dimensional optimization problems. In this paper, we present a scalability test of GBDE on high-dimensional optimization problems with dimensions 100, 200, 500, and 1000. Experimental results show that GBDE achieves promising results on the majority of test functions.
Highly Sensitive and Quantitative Detection of the H 274 Y Oseltamivir Resistance Mutation in Seasonal A / H 1 N 1 Influenza Virus

A C-to-T transition mutation in the neuraminidase gene from seasonal A/H1N1 causes a His-to-Tyr mutation at amino acid position 275 (H274Y, universal N2 numbering), conferring resistance against oseltamivir (Tamiflu). This mutation was first detected in clinical samples in Europe during the 2007-2008 influenza season. Viruses with this mutation reached a prevalence of 11% by the end of the season in North American isolates tested by the CDC. We developed a highly sensitive and specific quantitative real-time reverse transcriptase PCR assay to detect the H274Y mutation. This assay utilizes a 5 -methyl-isocytosine (isoC) residue and fluorescent reporters on genotype-specific primers. During PCR, a quencher coupled to isoguanine (isoG) is site-specifically incorporated complementary to the isoC/dye, resulting in loss of fluorescence. Optimization of primers and assay conditions produced a limit of detection of 100 gene copies per reaction for both wild-type and H274Y genotypes. In samples with mixed populations, it can reliably detect as little as a 1% wild-type or 0.1% H274Y component. This high sensitivity makes the assay usable on samples with viral loads too low for dideoxy or pyrosequencing analysis. Additionally, the assay distinguishes seasonal A/H1N1 from A/H3N2, influenza B, or 2009 pandemic A/H1N1, making it useful for influenza virus subtyping as well as for drug resistance detection. We probed seasonal A/H1N1 samples from the 2005-2006, 2006-2007, and 2007-2008 influenza seasons. Data from the new assay closely matched available drug resistance genotype data previously determined by dideoxy sequencing. The H274Y mutation was only found in samples from the 2007-2008 season.
Black-start scheme based on EV's intelligent integrated station

With electric power network getting larger and more complex, it is unprecedented vulnerable and modern society is faced with higher blackout risk The stable and reliable operation of a power system is necessary after major emergencies (or blackouts) following a major system event. The intelligent integrated station (IIS), providing energy and changing batteries for EVs, has the ability to separate and isolate itself from the power grid seamlessly with little or no disruption to loads in the station. Then, when the utility grid returns to normal, the IIS resynchronizes and reconnects itself to the grid in an equally seamless manner. According to conventional system restoration after a black-out, the control principles of black-start for intelligent integrated station are put forward. The build-up strategy is used to restore power system with IIS, which includes the process of restoring separated parts (islands) in the power system and interconnecting them afterwards. The control of IIS with energy storage system will deal with building isolated network, forming and operating island, and connecting island and re-synchronization with upstream network or grid system. A model based on the black-start principle proposed above is developed and the model is applied in a regional power grid.
A novel 2DEGFET model based on the parabolic velocity-field curve approximation

A new model for selectively doped heterostructure two-dimensional electron gas (2DEG) FET's has been proposed. In order to take into account the strong field dependence of the 2DEG mobility, a parabolic approximation is employed for a velocity-field curve below a velocity saturation field. The nonlinear field dependence of parasitic resistances has also been considered, which is of great importance for a more accurate description of actual FET characteristics. The proposed FET model is very useful for a digital IC design, since it has fewer fitting parameters and gives a smooth fit to measured data. Good agreement between the calculated drain current-voltage characteristics and the experimental characteristics, both for short-gate FET's and for long-gate FET's, demonstrates the validity of the present model. In addition, it has been recently found from the analysis that a transconductance compression is possible caused by a current limitation, due to hot electrons in the source-to-gate region, even though the n-(AlGa)As layer is totally depleted.
4D cone-beam computed tomography (CBCT) using a moving blocker for simultaneous radiation dose reduction and scatter correction

Four-dimensional (4D) x-ray cone-beam computed tomography (CBCT) is important for a precise radiation therapy for lung cancer. Due to the repeated use and 4D acquisition over a course of radiotherapy, the radiation dose becomes a concern. Meanwhile, the scatter contamination in CBCT deteriorates image quality for treatment tasks. In this work, we propose the use of a moving blocker (MB) during the 4D CBCT acquisition (‘4D MB’) and to combine motion-compensated reconstruction to address these two issues simultaneously. In 4D MB CBCT, the moving blocker reduces the x-ray flux passing through the patient and collects the scatter information in the blocked region at the same time. The scatter signal is estimated from the blocked region for correction. Even though the number of projection views and projection data in each view are not complete for conventional reconstruction, 4D reconstruction with a total-variation (TV) constraint and a motion-compensated temporal constraint can utilize both spatial gradient sparsity and temporal correlations among different phases to overcome the missing data problem. The feasibility simulation studies using the 4D NCAT phantom showed that 4D MB with motion-compensated reconstruction with 1/3 imaging dose reduction could produce satisfactory images and achieve 37% improvement on structural similarity (SSIM) index and 55% improvement on root mean square error (RMSE), compared to 4D reconstruction at the regular imaging dose without scatter correction. For the same 4D MB data, 4D reconstruction outperformed 3D TV reconstruction by 28% on SSIM and 34% on RMSE. A study of synthetic patient data also demonstrated the potential of 4D MB to reduce the radiation dose by 1/3 without compromising the image quality. This work paves the way for more comprehensive studies to investigate the dose reduction limit offered by this novel 4D MB method using physical phantom experiments and real patient data based on clinical relevant metrics.
Magnetotactic Bacteria Optimization Algorithm Based on Best Moments 2

Magnetotactic bacteria optimization algorithm(MBOA) is an optimization algorithm based on the characteristics of magnetotactic bacteria, which is a kind of polyphyletic group of prokaryotes with the characteristics of magnetotaxis that make them orient and swim along geomagnetic field lines. In this paper, an improved MBOA is proposed. At first, it generates moments based on the interaction energy of cells. Then, the moments of cells are regulated based on the best cell. Some cells have chance to move towards the best one. At last, some worse cells will be replaced by randomly generated solutions in order to keep diversity. Thus, it can find optimum solution. It is tested on ten standard function problems and compared with many popular optimization algorithms, including CLPSO, LeDE and ABC. Experiment results show that the improved MBOA is very effective in optimization problems and has superior performance to the compared methods on many benchmark functions.
Active Learning of Multi-Class Classifiers with Auxiliary Probabilistic Information

Our ability to learn accurate classification models from data is often limited by the number of available data instances. This limitation is of particular concern when data instances need to be labeled by humans and when the labeling process carries a significant cost. Recent years witnessed increased research interest in developing methods capable of learning models from a smaller number of examples. One such direction is active learning. Another, more recent direction showing a great promise utilizes auxiliary probabilistic information in addition to class labels. However, this direction has been applied and tested only in binary classification settings. In this work we first develop a multi-class variant of the auxiliary probabilistic approach, and after that embed it within an active learning framework, effectively combining two strategies for reducing the dependency of multi-class classification learning on the number of labeled examples. We demonstrate the effectiveness of our new approach on both simulated and real-world datasets.
Cytochrome P450 2C11 5′-Flanking Region and Promoter Mediate in Vivo Suppression by 3-Methylcholanthrene

Aromatic hydrocarbons such as 3-methylcholanthrene (MC) elicit toxic and adaptive responses through the aryl hydrocarbon receptor (AHR). Aromatic hydrocarbons act via an unknown mechanism to suppress the transcription of CYP2C11, a growth hormone-regulated gene encoding the male-specific rat hepatic cytochrome P450 2C11. We hypothesize that suppression of CYP2C11 by aromatic hydrocarbons is mediated by the gene's promoter and 5′-flank. Using hydrodynamics-based injections to deliver plasmid DNA to the liver of live rats, we studied the MC responsiveness of luciferase constructs containing 10.1, 5.6, and 2.4 kilobases (kb) of the CYP2C11 5′-flank. MC suppressed CYP2C11-luciferase activity of the 10.1- and 5.6-kb constructs to less than 50% of vehicle levels by 24 and 72 h. Luciferase activity of the 2.4-kb CYP2C11 construct was decreased to 63% of vehicle levels 24 h after MC treatment, but no suppression was detected by 72 h. Negative regulatory element(s) responsible for CYP2C11 reporter suppression by MC exist in the proximal 2.4 kb of the 5′-flank; however, additional cis-acting elements located between –5.6 and –2.4 kb mediate persistent reporter suppression. As a positive control for AHR activation, MC dramatically induced the luciferase activity of a Cyp1a1-driven luciferase plasmid under AHR control. Modulation of reporter gene activity by MC was accompanied by induction of endogenous CYP1A1 and suppression of endogenous CYP2C11 mRNA/protein. This is the first demonstration of aromatic hydrocarbon-mediated suppression of a CYP2C11-luciferase construct, and this finding suggests that the 5′-flanking region and promoter mediate down-regulation of this gene in the intact rat.
Using Boruta-Selected Spectroscopic Wavebands for the Asymptomatic Detection of Fusarium Circinatum Stress

High spectral resolution multitemporal data were used to model asymptomatic stress caused by Fusarium circinatum in 3-month old Pinus radiata seedlings. The objectives of the study were: 1) to identify an optimal subset of wavebands that could model asymptomatic stress in P. radiata seedlings and 2) to develop a robust classification model for discriminating healthy and stressed seedlings. To achieve these objectives, spectral data were collected for healthy, infected, and damaged seedlings using a hand-held field spectroradiometer. The data were analyzed, first for combined classes and then for class pairs using the Boruta algorithm. Results indicated that the best discrimination was possible at week three for all classes, with a KHAT value of 0.79 and an out of bag error of 14.00% (CV error = 16.00%), using a subset of 107 wavebands. A closer examination of the class pairs, namely healthy-infected (H-I) and infected-damaged (I-D), showed improved discrimination with KHAT values of 0.82 and 0.84, respectively. The H-I class pair was classified using a subset of just 38 wavebands, whereas the I-D class pair was classified using a subset of just 40 wavebands. Overall, this study demonstrated that it is more difficult to discriminate asymptomatic stress when additional stress related classes are present. Nonetheless, the methodology developed in this study has the potential to be operationalized within a nursery environment for the early detection of F. circinatum-induced stress in P. radiata seedlings.