Miracle-dz/UniFAR-FTUs huggingface dataset:
Photoluminescence in polyamide/mica and polyethylene/ MgO nanocomposites induced by ultraviolet photons

Nature of electronic states in the energy band is investigated by means of optical absorption and photoluminescence induced by vacuum ultraviolet photons for polyamide-6/mica and low-density polyethylene/MgO nanocomposites. The nanofiller loading does not affect the absorption spectra of polyamide samples. Contrary to this, two absorption bands are induced at around 5.0 and 6.2 eV by the nanofiller loading in polyethylene samples, but they are due to absorption by the fillers. A luminescence band is observed at around 3.0 eV in polyamide samples, whereas three luminescence bands are observed at around 4.3, 3.7, and 2.9 eV in polyethylene samples. However, for all the luminescence bands, neither emission nor excitation energies change by the addition of nanofillers. Decay profiles of all the luminescence bands are essentially unchanged by the nanofiller loading. Moreover, no new PL bands are induced in the observed wavelength range. These results indicate that localized states, at least as far as the ones that can emit luminescence photons with intensities more than the sensitivity of the present research, are not induced by the nanofiller loading.
Phase contrast imaging (PCI) investigation for mouse kidney

[Abstract] Objective To evaluate the privilege of X-ray phase contrast imaging on the microstructure of mouse kidneys, and explore the imaging differences on kidney images obtained by DEI and in-line outline X-ray imaging (IOXI) with synchrotron radiation (SR) facility. Materials and Methods The SD mouse kidneys are taken as samples. DEI images were brought out at 4W1A beam line of BSRF and the in-line outline images were recorded at BL13W beam line of SSRF. Contrast of soft tissue and spatial resolution were selected mainly to evaluate the image quality. Results The kidney microstructures, which are usually hard to be visualized by conventional radiography, were recorded clearly with both of the imaging modalities. The kidney vessels of about 10μm in diameter were revealed, however more minute structures such as the renal glomeruli, were resolvable only in images taken with IOXI. Conclusion The phase contrast imaging has great potential to reveal the structures inside soft tissues which could achieve images of high quality for the tiny vessels without any administration of contrast media, and more microstructures of the mouse kidneys were demonstrated on IOXI. Due to the sample setup and fine images , the IOXI maybe well better manner in biological tissue imaging study.
Digital signal processing for doppler radar signals

In a pulsed-doppler radar system the return signal is naturally viewed as a sequence of samples of one or more complex sinusoids plus noise. We have studied several digital processing techniques for estimating a short-time spectral representation of such signals as well as digital techniques for estimating the frequency of a single dominant spectral component. Techniques considered include: (1) Discrete short-time Fourier analysis followed by peak-picking and median smoothing to remove errors. (2) Short-time maximum entropy spectrum estimation incorporating adaptive noise suppression. (3) A new recursive algorithm based on recursive computation of the short-time auto-correlation function. The relative merits of each technique are discussed and examples of performance are given.
Sélection simultanée d'index et de vues matérialisées

Indices and materialized views are physical structures that accelerate data access in data warehouses. However, these data structures generate some maintenance overhead. They also share the same storage space. The existing studies about index and materialized view selection consider these structures separately. In this paper, we adopt the opposite stance and couple index and materialized view selection to take into account the interactions between them and achieve an efficient storage space sharing. We develop cost models that evaluate the respective benefit of indexing and view materialization. These cost models are then exploited by a greedy algorithm to select a relevant configuration of indices and materialized views. Experimental results show that our strategy performs better than the independent selection of indices and materialized views.
Real-Time Estimation of Fundamental Frequency and Harmonics for Active Shunt Power Filters in Aircraft Electrical Systems

A novel algorithm for fundamental frequency and harmonic components detection is presented in this paper. The technique is based on a real-time implementation of discrete Fourier transform, and it allows fast and accurate estimation of fundamental frequency and harmonics of a distorted signal with variable fundamental frequency. It is suitable for active shunt filter applications, when fast and accurate tracking of the reference signal is required to achieve a good control performance. The main application for the algorithm is aircraft ac power systems, where the fundamental frequency can be either fixed on 400 Hz and its actual value fluctuates around the nominal value, or variable in the range 360-900 Hz. Hence, a real-time estimation of fundamental frequency is essential for active filter control. The proposed algorithm has been at first implemented in Matlab/Simulink for computer simulation, and it has been compared with a Phase Locked Loop (PLL) algorithm for frequency detection and the synchronous dq reference method for harmonic detection. Experimental tests have been carried out in order to validate the simulation results. The distorted current absorbed by a nonlinear load is analyzed and processed by means of a digital implementation of the algorithm running on the active shunt power filter control DSP, in order to calculate the active filter compensating current.
CSEPM - A Continuous Software Engineering Process Metamodel

Software engineers have to cope with uncertainties and changing requirements. Agile methods provide flexibility towards changes and the emergence of continuous delivery has made regular feedback loops possible. The abilities to maintain high code quality through reviews, to regularly release software, and to collect and prioritize user feedback, are necessary for continuous software engineering (CSE). However, there exists no software process metamodel that handles the continuous character of software engineering. In this paper, we describe an empirical process metamodel for continuous software engineering called CSEPM, which treats development activities as parallel running workflows and allows tailoring and customization. CSEPM includes static aspects that describe the relations between specific CSE concepts including reviews, releases, and feedback. It also describes the dynamic aspect of CSE, how development workflows are activated through change events. We show how CSEPM allows to instantiate linear, iterative, agile and continuous process models and how it enables tailoring and customization.
FUEL MOdELLInG And POTEnTIAL FIRE BEHAvIOR In TURKEy

Description of fuel characteristics is an essential input to fire behavior models that can provide decision-support for fire management. Fuel models describe fuel characteristics for fire modeling systems based on Rothermel’s fire spread model. In this study, fire behavior data collected in field experiments in different fuel complexes in Turkey is used in the process of fuel model development. Nine fuel models were built for low and tall maquis, Anatolian black pine (P. nigra J.F. Arnold subsp. nigra var. caramanica (Loudon) Rehder), litter, and slash variable in age and load. BehavePlus simulations of fire rate of spread, flame length and fireline intensity for typical summer weather conditions highlight the quite different fire potential between the studied fuel types. The difficulty in dealing with fuel complexes dominated by live fuels was evident from the simulations. On the contrary, the model correctly predicted the observed temporal decrease of fire behavior in slash. This study shows the crucial importance of experimental fire data to parameterize fuel models.
Development of Hairy Root Culture of Andrographis Paniculata for in Vitro Adrographollide Production

Development the hairy root culture of A. paniculata was conducted for growing the hairy roots and production of andrographollide. Different strains of Agrobacterium rhizogenes (R-1000, A4, ATCC 15834), different types of explants (cotyledons, hypocotyls, and leaves) and different infection time of A. rhizogenes (1, 2, 3 days) were tested to induce hairy roots of A. paniculata. The results indicated that the best strain, type of explants and infection time for hairy roots induction were found in strain ATCC 15834, the explants of cotyledon and the 2 days of infection, respectively. The best medium for growing the hairy roots was liquid half strength MS medium with the addition of 5.0 μM IBA. The highest amount of andrographollide was observed in the medium with the addition of 5.0 μM IBA on the week of two, as much as 0.54%. Integration of T-DNA of A. rhizogenes in hairy roots was confirmed by polymerase chain reaction (PCR) analysis with specific primer for rolA and rolC genes of the plasmid. Visualization of the PCR products on agarose gel electrophoresis showed two fragments with lengths of 248 bp and 490 bp which corresponds to rolA and rolC genes from Ri plasmids of ATCC 15834. 
LIDAR/MEMS IMU integrated navigation (SLAM) method for a small UAV in indoor environments

Simultaneous Localization and Mapping (SLAM) based on LIDAR and MEMS IMU is a kind of autonomous integrated navigation technology. It can provide attitude, velocity position for a small UAV in an indoor frame during the outage of GNSS. A method of integrating the measurements from a LIDAR and a MEMS IMU was proposed in the paper. LIDAR measurements are a set of ranges and scan angles. The angle rates and accelerations from MEMS IMU are used to drive the simplified strapdown INS equations. The first step of the method is environment features extracting from the measurements of LIDAR and constructing a feature map. Then, the model of errors of LIDAR measurement due to the change of the scan plane during the attitude manoeuver is established and compensated based on aiding information from MEMS INS and the assumption about the structural indoor environment. The relative position parameters derived from environmental features delay matching algorithm and the differences of measurements of LIDAR at adjacent times are used to estimate the error of MEMS INS and MEMS sensors by a Kaiman Filter. A LIDAR/MEMS IMU prototype was designed to verify the practicability of the integrated navigation system of LIDAR and MEMS IMU. Some experiments were carried out in a room and the results demonstrated the potential use of the LIDAR/MEMS IMU integration navigation system.
Community‐based Participatory Research: An Approach to Intervention Research With a Native American Community

Community-based participatory research (CBPR), with its emphasis on joining with the community as full and equal partners in all phases of the research process, makes it an appealing model for research with vulnerable populations. However, the CBPR approach is not without special challenges relating to ethical, cultural, and scientific issues. In this article, we describe how we managed the challenges we encountered while conducting a CBPR project with a Native American community. We also suggest criteria that will enable evaluation of the project.
Support vector machine fusion of idiolectal and acoustic speaker information in Spanish conversational speech

This paper proposes a support vector machine (SVM) based combining scheme that incorporates ideolectal and acoustic characteristics for speaker recognition. Two statistical model paradigms, namely GMM for acoustic modeling and bigrams for language modeling, provide multilevel speaker information that affords a better classification performance when SVM-based fusion is accomplished. This combining approach is useful for all speaker recognition tasks where a considerable amount of data is available. Motivated by the absence of Spanish databases that made feasible our research experiments, more than nine hours of Spanish conversational speech was collected and manually transcribed from broadcasted radio talk shows.
Effectiveness of Whey Protein Supplement in Resistance Trained Individuals

Athletes and recreationally resistance-trained individuals often use protein supplements in an attempt to maximize their training gains and performance. Because of the high bioavailability and solubility and its higher proportion of essential amino acids including Leucine, whey protein extract has been proposed as the best optimal form of protein for strength and power athletes. The objective of this review is to examine the current evidence for the efficacy of whey protein containing supplements to optimize strength training adaptation and outcomes for regular resistance training practitioners. A limited numbers of studies have reported positive effects of whey protein containing supplements (including those with carbohydrate and creatine) for optimizing the anabolic responses and adaptations process in resistancetrained individuals. In order to promote a more anabolic environment and maximize muscle protein synthesis along the day, an eating pattern behavior involving frequents meals (every 3 to 5 h) containing 17 to 20 g of high quality protein (200 to 250 mg/ kg) providing 8 to 10 g of EAA (90 to 110 mg/kg) and about 2 g of Leucine (20 to 25 mg/kg) have been recommended. Special attention should be given to the periworkout hours where the ingestion of whey proteins combined with carbohydrates, creatine monohydrate (0.1 g/kg/d) and other proteins sources such as casein before, during and after workout have been shown to improve training adaptations and enhance the recovery process. However, when considering that the training conditions (workout volume, organization, number of exercises) used in the available studies are substantially different than what athletes actually perform. Optimal whey protein supplementation protocols need to specifically be based on the regular resistance training workout organization and would probably need to consider other doses and timing strategies than what is currently recommended.
Safe and high speed navigation of a patrol robot in occluded dynamic obstacles

It is difficult to detect all dynamic obstacles around a robot due to the limitation of field of view. Visibility information is necessary in order to avoid collisions. In previous research, we proposed a path planning and speed control scheme that could be applied to a robot to avoid occluded dynamic obstacles. In this paper experimental verifications of the proposed scheme for various environments are presented. The path planning scheme is improved by considering the robot's moving direction. Experimental results show that the proposed high speed navigation of a patrol robot can be achieved together with safety.
The filterbank in MP3 and AAC encoders: A comparative analysis

MP3 and AAC both use the filterbank to convert audio signal from time domain to frequency domain, which plays an important role in the whole encoder processing. Analysis the application of the filterbank in MP3 and AAC will help to understand the difference of them in coding efficiency and audio quality better. Therefore, from three points, which are the components of filterbank, the selection of window shape and the type of the translation block, this paper analyses the filterbank in MP3 and AAC respectively, then explores the differences between them and gives some related experiments. The result shows that, compared with MP3, AAC shows a better coding efficiency and audio distortion control only in the filterbank module.
Optimal algorithms for recombination distance problem

Recombination of sequences is an important combinatorial optimization problem due to its applications in computational biology. It is related to the alignment with recombination which is an edit distance problem involved recombination, and reconstructing a history of recombination from a set of sequences, etc. Recently, Wu and Gu discussed a distance problem involved recombination consisting of single crossover. [S. Wu and X. Gu (2001). A Greedy algorithm for optimal recombination. Proceeding of COCOON2001, Lecture Notes in Computer Science 2108, pp. 86–90. ] 𝒜 and 𝒮 denote two collections of sequences where |𝒮| = 2. The goal is to generate 𝒜 from 𝒮 by a series of recombinations in minimum number of steps. They defined a special class 𝒜 of sequences called ‘tree’, and presented a greedy algorithm which was claimed optimal for finding the recombination distance from 𝒮 to 𝒜. In this paper, we revisit this result. We show that the greedy algorithm is not always optimal, and propose a revised algorithm which can solve the problem optimally. We further propose a new class 𝒜 of sequences called ‘chain’ and provide a polynomial time algorithm for finding the optimal recombination evolutionary history from 𝒮 to 𝒜. †chenting@math.zju. edu.cn
Automatic matching of marine sample types in marine survey

Marine survey is one of the most important methods for oceanic research. During the marine survey process, some collected samples will be distributed in-situ to scientists. In order to effectively manage the sample data, corresponding relations of sample type should be established between the actual distributed sample records and the prior sample applications. This matching result can provide the basis for subsequent data collection and analysis. This paper proposes a matching algorithm based on semantic similarity for marine sample type terms, which realizes automatic matching of marine sample types between records of samples distributed during the marine survey process and the prior sample applications. The approach first maps sample type terms to concepts in the ontology of marine sample type, and then calculates semantic similarity between sample type terms based on the domain ontology. Experimental result shows that the proposed method get a relatively high F1-measure ratio and has certain practical value.
Management of recurrent gastrointestinal stromal tumors

Recurrence after resection of primary gastrointestinal stromal tumor (GIST) is an unfortunately all‐too‐common phenomenon. The principal treatment for recurrent GIST is the first‐line tyrosine kinase inhibitor (TKI) imatinib mesylate. Those who progress on, or are intolerant of imatinib, are treated with second‐line TKI sunitinib malate. Cytoreductive surgery may be considered as an “adjuvant” therapy for patients with disease stabilized on imatinib, and, on an individual basis, sunitinib. J. Surg. Oncol. 2011; 104:915–920. © 2011 Wiley Periodicals, Inc.
Synthetic RORγ agonists regulate multiple pathways to enhance antitumor immunity

ABSTRACT RORγt is the key transcription factor controlling the development and function of CD4+ Th17 and CD8+ Tc17 cells. Across a range of human tumors, about 15% of the CD4+ T cell fraction in tumor-infiltrating lymphocytes are RORγ+ cells. To evaluate the role of RORγ in antitumor immunity, we have identified synthetic, small molecule agonists that selectively activate RORγ to a greater extent than the endogenous agonist desmosterol. These RORγ agonists enhance effector function of Type 17 cells by increasing the production of cytokines/chemokines such as IL-17A and GM-CSF, augmenting expression of co-stimulatory receptors like CD137, CD226, and improving survival and cytotoxic activity. RORγ agonists also attenuate immunosuppressive mechanisms by curtailing Treg formation, diminishing CD39 and CD73 expression, and decreasing levels of co-inhibitory receptors including PD-1 and TIGIT on tumor-reactive lymphocytes. The effects of RORγ agonists were not observed in RORγ−/− T cells, underscoring the selective on-target activity of the compounds. In vitro treatment of tumor-specific T cells with RORγ agonists, followed by adoptive transfer to tumor-bearing mice is highly effective at controlling tumor growth while improving T cell survival and maintaining enhanced IL-17A and reduced PD-1 in vivo. The in vitro effects of RORγ agonists translate into single agent, immune system-dependent, antitumor efficacy when compounds are administered orally in syngeneic tumor models. RORγ agonists integrate multiple antitumor mechanisms into a single therapeutic that both increases immune activation and decreases immune suppression resulting in robust inhibition of tumor growth. Thus, RORγ agonists represent a novel immunotherapy approach for cancer.
An Improved State Filter Algorithm for SIR Epidemic Forecasting

In epidemic modeling, state filtering is an excellent tool for enhancing the performance of traditional epidemic models. We introduce a novel state filter algorithm to further improve the performance of state-of-the-art approaches based on Susceptible-InfectedRecovered (SIR) models. The proposed algorithm merges two techniques, which are typically used separately: linear correction, as seen in the Ensemble Kalman Filter (EnKF), and resampling, as used in the Particle Filter (PF). We compare the inferential accuracy of our approach against the EnKF and the Ensemble Adjustment Kalman Filter (EAKF), using algorithms employing both an uncentered covariance matrix (UCM) and the standard column-centered covariance matrix (CCM). Our algorithm requires O(DN) more time than EnKF does, where D is the ensemble dimension and N denotes the ensemble size. We demonstrate empirically that our algorithm with UCM achieves the lowest root-mean-square-error (RMSE) and the highest correlation coefficient (CORR) amongst the selected methods, in 11 out of 14 major real-world scenarios. We show that the EnKF with UCM outperforms the EnKF with CCM, while the EAKF gains better accuracy with CCM in most scenarios.
Identifying Delegation in Congressional Bills

Theories of delegation abound in political science, economics, and public administration, but there have been few empirical tests of these theories. One major roadblock is the lack of a comprehensive data set on acts of delegation. I take a necessary first step toward testing these theories by training a neural network to classify whether sections of bills are delegating public authority to the bureaucracy. Using a convolutional neural network architecture, I achieve excellent performance that vastly improves over the baseline.
Towards Arabic Alphabet and Numbers Sign Language Recognition

-This paper proposes to develop a new Arabic sign language recognition using Restricted Boltzmann Machines and a direct use of tiny images. Restricted Boltzmann Machines are able to code images as a superposition of a limited number of features taken from a larger alphabet. Repeating this process in deep architecture (Deep Belief Networks) leads to an efficient sparse representation of the initial data in the feature space. A complex problem of classification in the input space is thus transformed into an easier one in the feature space. After appropriate coding, a softmax regression in the feature space must be sufficient to recognize a hand sign according to the input image. To our knowledge, this is the first attempt that tiny images feature extraction using deep architecture is a simpler alternative approach for Arabic sign language recognition that deserves to be considered and investigated