Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic image annotation and object detection

We live in the midst of the information era, during which organising and indexing information more effectively is a matter of essential importance. With the fast development of digital imagery, how to search images - a rich form of information - more efficiently by their content has become one of the biggest challenges. Content-based image retrieval (CBIR) has been the traditional and dominant technique for searching images for decades. However, not until recently have researchers started to realise some vital problems existing in CBIR systems. One of the most important is perhaps what people call the \textit{semantic gap}, which refers to the gap between the information that can be extracted from images and the interpretation of the images for humans. As an attempt to bridge the semantic gap, automatic image annotation has been gaining more and more attentions in recent years. This thesis aims to explore a number of different approaches to automatic image annotation and some related issues. It begins with an introduction into different techniques for image description, which forms the foundation of the research on image auto-annotation. The thesis then goes on to give an in-depth examination of some of the quality issues of the data-set used for evaluating auto-annotation systems. A series of approaches to auto-annotation are presented in the follow-up chapters. Firstly, we describe an approach that incorporates the salient based image representation into a statistical model for better annotation performance. Secondly, we explore the use of non-negative matrix factorisation (NMF), a matrix decomposition tehcnique, for two tasks; object class detection and automatic annotation of images. The results imply that NMF is a promising sub-space technique for these purposes. Finally, we propose a model named the image based feature space (IBFS) model for linking image regions and keywords, and for image auto-annotation. Both image regions and keywords are mapped into the same space in which their relationships can be measured. The idea of multiple segmentations is then implemented in the model, and better results are achieved than using a single segmentation.
Prospects for Gold Nanorod Particles in Diagnostic and Therapeutic Applications

Abstract Rod-shaped gold nanoparticles (‘nanorods’) have recently attracted widespread attention due to their unique optical properties and facile synthesis. In particular, they can support a longitudinal surface plasmon, which results in suspensions of them having a strong extinction peak in the upper visible or near-infrared parts of the spectrum. The position of this peak can be readily tuned by controlling the shape of the rods. In addition, the surface of the nanorods can be functionalized by a very wide variety of molecules. This has led to interest in their use as selective biomarkers in biodiagnostics or for selective targeting in photothermal thearapeutics. Here, we review the recent advances in the use of gold nanorods in these applications. Additionally, the information available regarding their biocompatibility is discussed.
Cavity dumping of single 19 ps pulses from passively mode-locked quasi-continuously pumped highly doped Nd:YAG laser

The common approach for a picosecond laser source with output energy in millijoule level is a continuously pumped mode locked oscillator with single pulse selector followed by a regenerative amplifier. Systems can operate with repetition rates up to 100 kHz with single pulse duration around 10 ps. For many applications, as for example laser ranging, lasers operating at repetition rates below 1 kHz with longer pulse durations are more suitable. Such pulses can be obtained from passively mode-locked lasers with pulsed pumping, where the microjoule pulses are generated directly from oscillators and simple single or double pass amplifiers are sufficient for additional pulse amplification. Recently we reported about development of a 0.8 mJ laser with output pulse duration of 113 ps, where for passive mode-locking special semiconductor saturable absorbers with 100 quantum wells were used under Brewster angle in resonator in transmission mode [1].
Comparison of apical transportation between ProFile and ProTaper NiTi rotary instruments.

AIM To use a newly developed radiographic technique to compare apical transportation and loss of working length (WL) between.06 taper ProFile Series 29 and ProTaper nickel-titanium (NiTi) rotary instruments in vitro. METHODOLOGY Mesio-buccal canals of 40 extracted mandibular molars were randomly divided into two groups. Group 1 was instrumented with ProFile and group 2 with ProTaper instruments according to the manufacturers' directions. A specially constructed radiographic jig with a Schick digital radiographic system (Schick Technologies Inc., Long Island City, NY, USA) was used to take pre- and postoperative radiographs of the samples at predetermined angulations. Using AutoCAD 2000 (Autodesk Inc., San Rafael, CA, USA), the central axes of initial and final instruments were radiographically superimposed to determine the loss of WL and degree of transportation at D(0), D(1), D(2) and D(4) from the WL. Data were analysed using repeated-measures anova. RESULTS A statistically significant difference in apical transportation was found at the D(4) level between the two groups (P = 0.05). There was no statistical significance regarding postinstrumentation change in WL between groups. Spearman's Bivariate Correlation analysis indicated no statistically significant relationship between the radius of curvature and transportation. CONCLUSION The results indicate that both ProTaper and ProFile instruments are comparable to each other in regards to their ability to optimally enlarge root canal with minimal transportation and loss of WL in vitro.
Biodiversity of Bacillus subtilis group and beneficial traits of Bacillus species useful in plant protection

Biological control of plant pathogens and plant growth promotion by biological means is the late tendency in biotechnological approaches for agricultural improvement. Such an approach is considering the environmental protection issues without neglecting crop needs. In the present study, we are reviewing Bacillus spp. biocontrol and plant growth promoting activity. As Bacillus genus is a large bacterial taxon, with grate physiological biodiversity, we are describing some inter-grouping, differences and similarities between Bacillus species, especially related to Bacillus subtilis.
Hardware development of Voltage Source Inverter for Hybrid Electric Vehicle

The global desire to reduce the vehicle emissions and improve fuel economy accelerated the development of Hybrid Electric Vehicle (HEV). The technology advancements in the area of electric drive systems, battery technologies, fuel cells and the internal combustion engine (ICE) resulted in highly efficient HEV. In this paper the hardware details of three phase, 50Hz, 6KW, 180° conduction mode of Voltage Source Inverter (VSI) was explained. The output waveforms under various load conditions were presented and discussed.
RIDING ROLE AGENT VEHICLE PLACE ROLE AGENT VEHICLE PLACE VALUE MAN HORSE OUTSIDE VALUE DOG SKATEBOARD

We address the problem of recognizing situations in images. Given an image, the task is to predict the most salient verb (action), and fill its semantic roles such as who is performing the action, what is the source and target of the action, etc. Different verbs have different roles (e.g. attacking has weapon), and each role can take on many possible values (nouns). We propose a model based on Graph Neural Networks that allows us to efficiently capture joint dependencies between roles using neural networks defined on a graph. Experiments with different graph connectivities show that our approach that propagates information between roles significantly outperforms existing work, as well as multiple baselines. We obtain roughly 35% improvement over previous work in predicting the full situation. We also provide a thorough qualitative analysis of our model and influence of different roles in the verbs.
Memory for verbal information in individuals with HIV-associated dementia complex. HNRC Group.

Patterns of memory performance were examined for 9 participants with HIV-associated dementia (HAD), 15 HIV-seropositive participants without dementia, and 15 HIV-seronegative controls. Episodic and semantic memory were assessed using the California Verbal Learning Test, the Boston Naming Test, and Verbal Fluency tests. The HAD group showed deficits in episodic memory, with relative sparing of semantic memory. In addition, results suggest a retrieval deficit in HAD rather than a deficit in retention of information. This pattern is consistent with the presence of a subcortical dementing process and supports findings from previous neuropathological, neuroimaging, and neuropsychological studies suggesting that subcortical brain dysfunction is frequently associated with HIV disease (e.g., Navia, Jordan, & Price, 1986).
Low-temperature phonon-drag thermoelectric power in heterojunctions.

The phonon-drag contribution to the thermoelectric power is calculated at low temperatures in polar semiconductor heterostructures. Carriers are assumed to interact with longitudinal acoustic phonons through deformation potential and with both longitudinal and transverse acoustic phonons through piezoelectric field. The magnitude and the temperature dependence of the phonon-drag contribution calculated without any adjustable parameter agree reasonably well with recent data from Al/sub x/Ga/sub 1-//sub x/As/GaAs heterolayer. Both piezoelectric scattering and deformation potential scattering yield comparable contributions in the temperature range studied (i.e., below 10 K), although the former (latter) contribution becomes more important below (above) 3--4 K. Dielectric screening is found to reduce the phonon-drag thermopower significantly.
Satellite Imagery Classification Based on Deep Convolution Network

Satellite imagery classification is a challenging problem with many practical applications. In this paper, we designed a deep convolution neural network (DCNN) to classify the satellite imagery. The contributions of this paper are twofold — First, to cope with the large-scale variance in the satellite image, we introduced the inception module, which has multiple filters with different size at the same level, as the building block to build our DCNN model. Second, we proposed a genetic algorithm based method to efficiently search the best hyper-parameters of the DCNN in a large search space. The proposed method is evaluated on the benchmark database. The results of the proposed hyper-parameters search method show it will guide the search towards better regions of the parameter space. Based on the found hyper-parameters, we built our DCNN models, and evaluated its performance on satellite imagery classification, the results show the classification accuracy of proposed models outperform the state of the art method. Keywords—Satellite imagery classification, deep convolution network, genetic algorithm, hyper-parameter optimization.
Interventions to Improve CPAP Adherence and Outcomes: Role of Theory and Behavioral Change Techniques

Study Background: Low patient adherence to nasal Continuous Positive Airway Pressure (CPAP) limits treatment effectiveness. A wide variety of CPAP adherence intervention studies have been performed to date, with many showing some improvement in CPAP adherence. Better understanding of the theoretical foundations, specific behavioral change techniques, and modes of intervention delivery can help provide guidance for future interventional efforts and reflects efforts underway in the general treatment adherence literature. Methods: The CPAP adherence literature was reviewed to identify those studies that included a specific intervention designed to increase CPAP use. Twenty-nine studies were included in this review. Published coding schemes were used. Results: The average effect size of the CPAP adherence interventions in adults who are new users of CPAP was 0.52 (SD=0.42, range: 0-1.52). This moderate effect size did not appear to be related to the number of behavioral change techniques, use of theory, or to mode of delivery. Conclusion: Future research efforts should build on previous interventional studies, with the ultimate goal of identifying those techniques that can help improve CPAP adherence and patient outcomes
Small Cliques in Random Graphs

For d ≥ 1, a d-clique in a graph G is a complete d-vertex subgraph not contained in any larger complete subgraph of G. We investigate the limit distribution of the number of d-cliques in the binomial random graph G(n, p), p = p(n), n→∞.
Image Quality Enhancement for Single-Image Super Resolution Based on Local Similarities and Support Vector Regression

In reconstruction-based super resolution, a high-resolution image is estimated using multiple low-resolution images with sub-pixel misalignments. Therefore, when only one low-resolution image is available, it is generally difficult to obtain a favorable image. This letter proposes a method for overcoming this difficulty for single- image super resolution. In our method, after interpolating pixel values at sub-pixel locations on a patch-by-patch basis by support vector regression, in which learning samples are collected within the given image based on local similarities, we solve the regularized reconstruction problem with a sufficient number of constraints. Evaluation experiments were performed for artificial and natural images, and the obtained high-resolution images indicate the high-frequency components favorably along with improved PSNRs.
Attribute Reduction of Formal Context Based on Concept Lattice

The concept lattice is useful in knowledge processing and analyzing. And it has been used with a high intensity to knowledge reduction and data mining. This paper, from the viewpoint of concept extents, studies new and relatively reasonable formulas measuring attribute significance and proposes a theory for justifying whether an attribute set is a reduction on concept lattice, and then uses those formulas as heuristic information to design a novel and heuristic algorithm for attribute reduction on concept lattice. Finally, a real example is used to demonstrate both its feasibility and effectiveness.
High capacity lifepo4 battery model with consideration of nonlinear capacity effects

Lithium Ferro Phosphates (LiFePO4) batteries have high potential to be widely employed in the future due to its stability on chemical and thermal characteristics. Therefore, an accurate battery model of high capacity LiFePO4 battery is important for a circuit designer to handle and optimize battery usage. However, nonlinear capacity effects of the battery are usually not been considered. The ignorance of nonlinear capacity effects cause the existing battery models unable to perform accurately. In this paper, nonlinear capacity effects of high capacity battery are studied. A new battery model is developed with consideration of nonlinear capacity effects. Developed battery model is validated from the experimental results. Comparison between experimental and simulation results shows that the developed model is capable to capture nonlinear capacity effects of the high capacity battery.
Lipidomics reveals a remarkable diversity of lipids in human plasma1[S]

The focus of the present study was to define the human plasma lipidome and to establish novel analytical methodologies to quantify the large spectrum of plasma lipids. Partial lipid analysis is now a regular part of every patient's blood test and physicians readily and regularly prescribe drugs that alter the levels of major plasma lipids such as cholesterol and triglycerides. Plasma contains many thousands of distinct lipid molecular species that fall into six main categories including fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, sterols, and prenols. The physiological contributions of these diverse lipids and how their levels change in response to therapy remain largely unknown. As a first step toward answering these questions, we provide herein an in-depth lipidomics analysis of a pooled human plasma obtained from healthy individuals after overnight fasting and with a gender balance and an ethnic distribution that is representative of the US population. In total, we quantitatively assessed the levels of over 500 distinct molecular species distributed among the main lipid categories. As more information is obtained regarding the roles of individual lipids in health and disease, it seems likely that future blood tests will include an ever increasing number of these lipid molecules.
Enhanced chaotic spiral dynamic algorithm with application to controller design

This paper present an enhanced chaotic spiral dynamic algorithm (ECSDA) for optimization problems and their application in single link flexible manipulator system (SLFMS). The algorithm is developed by integrating logistic chaotic pattern into the original spiral dynamic algorithm (SDA). The artificial bee colony optimization (ABC) searching method is also adopted in ECSDA to increase its capability to find the best possible local optimum solution. This hybrid technique reduces the probability of ECSDA getting trapped at local optimum. ECSDA is used to optimize the PD controller parameters of a single link flexible manipulator system (SLFMS). The results show that the ECSDA outperforms the SDA with improved search capability and escaping local optima and is able to tune the PD controller of SLFMS for the desired output.
Behavioral influences of rectal diazepam in solution on dental patients with mentally and physically handicapping conditions.

The hypothesis of this study was to determine whether the use of rectal diazepam in solution would effectively modify the uncooperative behavior of patients with mentally and physically handicapping conditions during dental treatment. The sample consisted of 42 patients with mild to severe mentally handicapping conditions, 4 to 31 years old, who live in a homecare center. Supragingival and subgingival scaling and prophylaxis were attempted during a 5-minute period and the patient's behavior was assessed. Conscious sedation using a rectal solution of diazepam (Stesolid) was used for those patients with voluntary or involuntary uncooperative behavior that prevented treatment. Twenty-two subjects (52.4%) were treated without diazepam. The rectal solution of diazepam proved to be a significantly (P less than .01) effective agent for behavior modification permitting the successful treatment of 16 (80%) of the 20 remaining subjects. The following behaviors were significantly modified: places hand(s) or arm(s) in front of mouth (P less than .01); does not open mouth, lips held firmly together (P less than .05); turns head to one side or side to side (P less than .05); attempts to grab instruments (P less than .05). No relationship was found between the results and the variables of medical history, gender, age, weight, quantity of diazepam administered, routine medication, pulse rate, blood pressure, and respiration.
Effects of Interleukin-1 Receptor Antagonist Overexpression on Infection by Listeria monocytogenes

ABSTRACT Interleukin-1 receptor antagonist (IL-1ra) is a naturally occurring cytokine whose only known function is the inhibition of interleukin-1 (IL-1). Using a reverse genetic approach in mice, we previously showed that increasing IL-1ra gene dosage leads to reduced survival of a primary listerial infection. In this study, we characterize further the role of endogenously produced IL-1ra and, by inference, IL-1 in murine listeriosis. IL-1ra overexpression inhibits, but does not eliminate, primary immune responses, reducing survival and increasing bacterial loads in the target organs. We demonstrate that IL-1ra functions in the innate immune response to regulate the peak leukocyte levels in the blood, the accumulation of leukocytes at sites of infection, and the activation of macrophages during a primary infection. Reduced macrophage class II major histocompatibility complex expression was observed despite increased gamma interferon (IFN-γ) levels, suggesting that IL-1 activity is essential along with IFN-γ for macrophage activation in vivo. We also show that IL-1ra plays a more limited role during secondary listeriosis, blunting the strength of the delayed-type hypersensitivity response to listerial antigen while not significantly altering cellular immunity to a second infectious challenge. When these results are compared to those for other mutant mice, IL-1ra appears to be unique among the cytokines studied to date in its regulation of leukocyte migration during primary listeriosis.
c-ascending support vector machines for financial time series forecasting

This paper proposes a modified version of support vector machines (SVMs), called c-ascending support vector machines (c-ASVMs), to model non-stationary financial time series. c-ASVMS are obtained by a simple modification of the regularized risk function in SVMs whereby the recent /spl epsiv/-insensitive errors are penalized more heavily than the distant /spl epsiv/-insensitive errors. This procedure is based on the prior knowledge that in the non-stationary financial time series, the recent past data could provide more important information than the distant past data. In the experiment, c-ASVMS are tested using three real futures collected from the Chicago Mercantile Market. It is shown that the c-ASVMS with the actually ordered sample data consistently forecast better than the standard SVMs, with the worst performance when the reversely ordered sample data are used. Furthermore, the c-ASVMs use fewer support vectors than those of the standard SVMs, resulting in a sparser representation of solution.
Cluster observations of magnetic holes near the interplanetary current sheets at 1 AU

Linear Magnetic holes (LMHs) are magnetic field decreasing structures with little change in the field direction. Xiao et al. have studied the geometrical shape and occurrence rate of LMHs in the solar wind at 1 AU from the year 2001 to 2004 by using the magnetic field and plasma data provided by Cluster C1 [1]. In this work, we will investigate LMHs near the region of interplanetary current sheet. It is found that about 60% of LMHs accompanied with the small scale current sheets within 10min. This result may help us to study the formation mechanism of the LMHs in the solar wind.
Structural and catalytic roles of metal ions in RNA.

The discovery of ribozymes triggered a huge interest in the chemistry and biology of RNAs. Much of the recently made progress focusing on metal ions is addressed in Volume 9. This book, written by 28 internationally recognized experts, provides a most up-to-date view and it is thus of special relevance for colleagues teaching courses in biological inorganic chemistry and for researchers dealing, e.g., with nucleic acids, gene expression, and enzymology, but also for those in analytical and bioinorganic chemistry or biophysics. Structural and Catalytic Roles of Metal Ions in RNA describes metal ion-binding motives, methods to detect and characterize metal ion binding sites, and the role of metal ions in folding and catalysis. It deals with diffuse metal ion binding, RNA quadruplexes, the regulation of riboswitches, metal ions and ribozymes, including artificial ribozymes. The ribosome, ribozymes and redox cofactors, as well as the binding of kinetically inert metal ions to RNA are also considered.