Miracle-dz/UniFAR-FTUs huggingface dataset:
The role of individuals in social movements: the rise of policy entrepreneurs in Bulgaria during the first Borisov Cabinet

ABSTRACT This article investigates the question of how policy entrepreneurs influence the behaviour of social movements. It does so by presenting a new framework for analyzing social movements or collective action that emphasises the important role of individuals. In particular, it offers a systematic study of social movement leaders using the literature of policy entrepreneurship. We identify five areas that should be considered when assessing how policy entrepreneurs can foster policy or political changes in their society: (1) the motivations of policy entrepreneurs, (2) variations in their goals, (3) the characteristics and abilities of policy entrepreneurs, (4) their strategies and (5) the potential outcomes. We then place these changes on a 6-point continuum ranging from least extreme to most extreme. In testing our theoretical framework using the case study of Bulgarian protests against the First Borisov Cabinet, we develop theoretical insights that could be generalised to other social movements worldwide.
IOTEML: An Internet of Things (IoT)-Based Enhanced Machine Learning Model for Tumour Investigation

In the current age of technology, various diseases in the body are also on the rise. Tumours that cause more discomfort in the body are set to increase the discomfort of most patients. Patients experience different effects depending on the tumour size and type. Future developments in the medical field are moving towards the development of tools based on IoT devices. These advances will in the future follow special features designed based on multiple machine learning developed by artificial intelligence. In that order, an improved algorithm named Internet of Things-based enhanced machine learning is proposed in this paper. What makes it special is that it involves separate functions to diagnose each type of tumour. It analyzes and calculates things like the size, shape, and location of the tumour. Cure from cancer is determined by the stage at which we find cancer. Early detection of cancer has the potential to cure quickly. At a saturation point, the proposed Internet of Things-based enhanced machine learning model achieved 94.56% of accuracy, 94.12% of precision, 94.98% of recall, 95.12% of F1-score, and 1856 ms of execution time. The simulation is conducted to test the efficacy of the model, and the results of the simulation show that the proposed Internet of Things-based enhanced machine learning obtains a higher rate of intelligence than other methods.
Nonparametric Bayesian Quantile Regression via Dirichlet Process Mixture Models

OF THE DISSERTATION Nonparametric Bayesian Quantile Regression via Dirichlet Process Mixture Models by Chao Chang Doctor of Philosophy in Mathematics, Washington University in St. Louis, 2015. Professor Nan Lin, Chair We propose new nonparametric Bayesian approaches to quantile regression using Dirichlet process mixture (DPM) models. All the existing quantile regression methods based on DPMs require the kernel density to satisfy the quantile constraint, hence the kernel densities are themselves usually in the form of mixtures. One innovation of our approaches is that we impose no constraint on the kernel, thus a wide range of densities can be chosen as the kernels of the DPM model. The quantile constraint is satisfied by a post-processing of the DPM by a suitable location shift. As a result, our proposed models use simpler kernels and yet possess great flexibility by mixing over both the location parameter and the scale parameter. The posterior consistency of our proposed model is studied carefully. And Markov chain Monte Carlo algorithms are provided for posterior inference. The performance of our approaches is evaluated using simulated data and real data. Moreover, we are able to incorporate random effects into our models such that our approaches can be extended to handle longitudinal data.
Computing energy density in one dimension

We study the problem of computing energy density in one-dimensional quantum systems. We show that the ground-state energy per site or per bond can be computed in time (i) independent of the system size and subexponential in the desired precision if the ground state satisfies area laws for the Renyi entanglement entropy (this is the first rigorous formulation of the folklore that area laws imply efficient matrix-product-state algorithms); (ii) independent of the system size and polynomial in the desired precision if the system is gapped. As a by-product, we prove that in the presence of area laws (or even an energy gap) the ground state can be approximated by a positive semidefinite matrix product operator of bond dimension independent of the system size and subpolynomial in the desired precision of local properties.
EFFECT OF SOME NITROGEN AND SULPHUR SOURCES ON PLANT GROWTH AND YIELD OF ONION (ALLIUM CEPA, L.)

Two field experiments were conducted at the Experimental Farm of the Faculty of Agriculture, Tanta during the winter seasons of 1995/96 and 1996/97, to study the effect of some nitrogen and sulphur sources on plant growth, yield and quality of onion. Nitrogen was supplied at level of 100 kg/fed. from four sources, i.e., urea, ammonium, sulphate, ammonium nitrate and calcium nitrate, while sulphur was supplied as a sulphur powder 50 and 100 kg/fed. or ammonium thiosulphate (ATS) 2 and 4 kg/fed. Results revealed that, ammonium nitrate increased average bulb weight while calcium nitrate increased the percentage of bolting plants. Addition of sulphur at 50 or 100 kg increased the yield of onion. Results showed also that NO 3 -N was more accumulated in green leaves of onion than in its bulbs. The NO 3 -N content in both bulbs and leaves was affected significantly by the nitrogen and sulphur sources. Ammonium sulphate as nitrogen source lead to less nitrate accumulation in onion plants followed by ammonium nitrate and urea, while calcium nitrate caused increasing accumulation of NO 3 -N in plants. Sulphur treatment decreased the NO 3 -N content of onion plants. Values of the interaction showed that ammonium sulphate was more effective on decreasing nitrate accumulation in the presence of sulphur treatments.
Topological phases and the quantum spin Hall effect in three dimensions

We show the existence of topological phases of Bloch insulators with time-reversal symmetry in three dimensions. These phases are characterized by topological ${Z}_{2}$ invariants whose stability is studied using band-touching arguments. Unlike insulators which break time-reveral symmetry, some of these topological phases are intrinsically three dimensional. The number of invariants (four) needed to specify the phase of these insulators also differs from the time-reversal-breaking case. The relation between these phases and the quantum spin Hall effect in three dimensions is investigated.
Topographic Gravity Waves Observed in the Martian Thermosphere: A Statistical Perspective From a 1‐D Full‐Wave Model

Gravity waves (GWs) are significant dynamical processes in planetary atmospheres due to their efficient transport of momentum and energy from the lower to the upper atmosphere. Recent observations from in‐situ measurements by spacecraft like Mars Atmosphere and Volatile Evolution (MAVEN) also reveal ubiquitous GW activity in the Martian thermosphere. As a critical parameter for characterizing GWs, the wavelength spectrum has been studied for years. However, most of the current observations for the Martian thermosphere can only determine the apparent GW wavelength because they usually take one‐dimensional measurements within a typical GW period. In this work, we adopt a full‐wave GW model to statistically investigate the upward propagation of the topographic‐generated GWs and how their wavelength spectrum apparently looks in the thermosphere when observed by a spacecraft like MAVEN. We find that the wind significantly modifies the vertical wavelengths of GWs in the Martian atmosphere. Considering the GWs generated from topographic sources, we calculate their wavelength distribution in the thermosphere, with a most probable apparent vertical wavelength of around 14 km, consisting with the MAVEN observation. However, our theoretical wavelength spectrum is mainly concentrated in the low wavelength part (10–20 km), while the observed result contains a long‐tailed component in the long wavelength part. The mismatch between our model and observations indicates that at least 72% of the observed GWs in the thermosphere are not generated from topographic sources.
Willingness to Test for Human Immunodeficiency Virus (HIV) Infection among First-Year Students of a Public University in the Volta Region of Ghana

Voluntary counselling and testing (VCT) is key in HIV prevention. Young people aged 15–24 years carry a significant burden of new infections globally, but VCT uptake is low in this population. The study assessed university freshmen’s willingness to test for HIV now, among others, in a cross-sectional study as university campuses are places of risky sexual behaviour. Structured questionnaires were used to collect data on age, sex, marital status, HIV/AIDS knowledge, previous history of testing, willingness to test now, and others. Summary statistics were reported while chi-square and logistic regression methods were used to assess the association between dependent and independent variables with p-values < 0.05 held significant. About 90% (374/412) of respondents had good HIV/AIDS knowledge based on criteria defined by the study, but only 23.3% (96/412) had ever tested and 66.3% (266/401) were willing to test now for HIV. Respondents’ sex, previous sexual intercourse, and whether respondents’ educational support was from parents or non-parents influenced willingness to test for HIV now. The study highlights what appears to be personal beliefs that can potentially hinder HIV testing and control efforts. Relevant stakeholders must address these gaps to improve testing. Further qualitative investigation will improve understanding of the dynamics informing willingness to test for HIV among young people generally.
Connecting to Nature through 360° Videos during COVID-19 Confinement: A Pilot Study of a Brief Psychological Intervention

Psychological interventions have been shown to be beneficial in mitigating stress related to COVID-19 confinement. According to theories of restorative environments, exposure to natural surroundings has positive effects on well-being and stress through its restorative qualities. With 360° video-based Virtual Reality (VR), people can be exposed to nature and so better manage the consequences associated with mobility restrictions during confinement. The main aim of this pilot study was to examine whether a 360° video-based VR intervention composed of five 13-minute sessions (once a day) has positive effects on affect, well-being, and stress. The sample was made up of 10 participants (4 men and 6 women; age : M = 46.5, SD = 11.7) who were confined at home (voluntarily or not) during the COVID-19 pandemic. Participants were instructed to watch a 360° video each day (of a “beach” or “lake” environment) using their smartphone and VR glasses sent to them by mail. Participants responded with several self-reports before and/or after each session (emotions and sense of presence) and before and/or after the intervention (affect, well-being, perceived stress, perceived restorativeness of nature, and the usefulness and acceptability of the intervention). Results showed a tendency to improve positive (e.g., happiness) and negative (e.g., anxiousness) emotions and experience a high sense of presence after each session. Moreover, perceived restorative qualities of the environment and their cognitive and behavioral effects were high. A significant decrease in negative affect was found after the intervention. Usefulness and acceptability were also high. This is the first study to show that an affordable and accessible technology can be used to overcome the negative consequences of confinement and counteract its harmful psychological effects.
Fungi on the Devonian thalloid plant Schuguria (Orestoviaceae)

Schuguria, an alga-like thalloid form from the Middle Devonian (Givetian) of the Pavlovsk Quarry, Voronezh Region, European Russia is heavily infested with spore-bearing and conidial structures that occur in the cortex cavities forming pseudothecia and acervuli. The fungal remains are assigned to new teleomorph and anamorph morphotaxa Speirascoma schuguriae gen. et sp. nov. and Setacervula schuguriae gen. et sp. nov., respectively. They supposedly represent an archaic group of ascomycete with a relatively massive helical structure (ascogonium? ) in the centrum of the fruiting body. Symbiotic relationships of the Ascophyllum- Mycosphaerella type is suggested for the cutinized thalloids and their associated fungi.
Residual Neural Networks for Gemstone Recognition and Classification

: For rapidly and accurately identifying and classifying different gemstones, a residual neural network-based gemstone classification and recognition model is presented using the image feature differences of 15 classes of gemstones. The gemstone image set is firstly established, then the image set is expanded using the data enhancement method, and afterwards the sample data set is obtained using the data cleaning method. The images are divided into training and test sets in the ratio of 8:1, and then the training set is trained using a residual neural network (ResNet 50). Finally, the correctness of the network is evaluated. The experimental results show that the average accuracy of this gem classification and identification algorithm reaches 93.46%, and basic engineering applications can be achieved.
PHOTOMETRIC STUDY AND PERIOD ANALYSIS OF THE CONTACT BINARY XZ LEONIS

We present multi-color CCD photometry of the neglected contact binary XZ Leo. Completely covered VRI band light curves and four times of minimum light were obtained. Combining the photometric and previously published radial-velocity data, a revised photometric analysis was carried out for the binary system by applying the Wilson–Devinney code. With a hot spot placed on the massive primary component near the neck region of the common envelope, the light curves were satisfactorily modeled. The photometric solution combined with the radial-velocity solution reveals that XZ Leo is an A-type contact binary with a degree of contact of 24(±1)%. The absolute parameters of the components were determined to be M1 = 1.74(±0.06)M⊙, M2 = 0.61(±0.02)M⊙, R1 = 1.69(±0.01)R⊙, R2 = 1.07(±0.01)R⊙, L1 = 6.73(±0.08) L⊙, and L2 = 2.40(±0.04)L⊙. Based on all the available data, the long-term orbital period behavior of the system was investigated. It indicates that the binary system was undergoing a continuous orbital period increase in the past three decades with a rate of dP / dt = + 6.12 × 10 − 8 days yr − 1 ? > , which suggests a probable mass transfer from the secondary to the primary component at a rate of dM / dt = 3.92 × 10 − 8 M ⊙ yr − 1 ? > . The binary system is expected to evolve into the broken-contact stage in 1.56 × 10 6 ? > years. This could be evidence supporting the thermal relaxation oscillation theory.
Vlasov Simulations of Kinetic Enhancement of Raman Backscatter in Laser Fusion Plasmas

Stimulated Raman scattering (SRS) is studied in plasmas relevant to inertial confinement fusion (ICF). The Eulerian Vlasov-Maxwell code ELVIS was developed and run for this purpose. Plasma waves are heavily Landau damped in the regimes of interest, and coupled-mode theory predicts back-scattered SRS is a convective instability. Simulations in a finite length, homogeneous plasma show electron trapping drastically elevates the reflected light over convective gain values (“kinetic enhancement”). Average reflectivities are ∼ 10%, while the instantaneous reflectivity is chaotic and does not reach a steady state. Trapping reduces the plasma-wave Landau damping and downshifts the observed frequencies from their linear values. Two longitudinal acoustic (ω ∝ k) features and light from possible stimulated electron acoustic scattering (SEAS) are present. The phase-matched SEAS plasmon lies on the observed acoustic mode with phase velocity 1.3(Te/me). As the pump laser intensity is increased or the electron temperature is decreased, SRS transitions sharply from the coupled-mode steady state to kinetically enhanced levels. Enhancement happens for different back SRS seed levels and monochromatic or broadband seeds. Simulations with a Krook relaxation operator to mimic speckle sideloss display enhancement when resonant electrons complete a bounce orbit before escaping, with a sharp onset as the relaxation rate varies. The sudden development of kinetic enhancement as parameters change suggests trapping makes SRS absolutely unstable. Simulations with mobile ions give kinetic enhancement until a burst of activity occurs near the laser entrance, after which back SRS is low. The burst contains several Brillouin and Raman re-scatters and subsequent Langmuir decay instability (LDI), although no LDI of back SRS is seen. SRS runs in a density gradient show kinetic enhancement for long scale lengths and coupledmode convective levels for shorter ones. The reflectivity is higher when the pump propagates toward higher, rather than lower, density. The amplitude of externally-driven plasma waves in a density gradient is also enhanced over linear levels and displays a similar directional asymmetry. These results imply kinetic enhancement of SRS may be a concern in hohlraum plasmas for ICF experiments such as the National Ignition Facility. Thesis Supervisor: Abraham Bers Title: Professor of Electrical Engineering and Computer Science
A survey on failure prediction methods of information systems

Through analyzing the process of failure of computer information systems and confirming the relation of fault, error, symptom and failure, this paper proposes the corresponding prediction methods of diagnosing, detecting, monitoring and tracking, the research and development of failure prediction methods of fault diagnosing, detected error reporting, undetected error evaluating, symptom monitoring and failure tracking are summarized. Finally, the realize principle and fundamental framework of failure prediction methods are given, the failure prediction methods of computer relevant application are analyzed and discussed, the advantages and disadvantages of failure prediction methods are also compared and discussed.
Developing a Competency Model for Outstanding Researchers in China

: Outstanding researchers are the first resource for national science and technology development, and competency is one of the important reasons affecting the performance of outstanding researchers. Currently, there is a lack of strong explanations for the competency of outstanding researchers in China. Therefore, this study uses grounded theory method to code biographies of 17 Chinese scientists layer by layer to construct the competency model for Chinese outstanding researchers. The results show that: the competency model of Chinese outstanding researchers includes five dimensions, including internal research motivation, research knowledge reserve, creative consciousness and thinking ability, research quality, research skills and self-development, and 32 competencies, including research interest, research work ambition and enterprise, etc. The model is of great significance for establishing and improving the long-term mechanism of training, selection, evaluation and professional development of outstanding researchers in China.
Nanoscale superconducting-gap variations and lack of phase separation in optimally doped BaFe1.86Co0.14As2

We present tunneling data from superconducting BaFe1.86Co0. 14As2 and its parent compound, BaFe2As2. In the superconductor, clear coherencelike peaks are seen across the whole field of view, and their analysis reveals nanoscale variations in the superconducting gap value, Δ. The average peak-to-peak separation gives a 2Δ of ∼7.4kBTc, which exceeds the BCS weak coupling value for either s- or d-wave superconductivity. The characteristic length scales of the deviations from the average gap value and of anticorrelations observed between the gap magnitude and both the zero-bias conductance and coherence peak strength match well with the average separation between the Co dopant ions in the superconducting FeAs planes.
Immunoaffinity Cleanup and Isotope Dilution-Based Liquid Chromatography Tandem Mass Spectrometry for the Determination of Six Major Mycotoxins in Feed and Feedstuff

In this study, a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for simultaneous determination of deoxynivalenol, aflatoxin B1, zearalenone, ochratoxin A, T-2 toxin and fumonisin B1 in feed and feedstuff was established. The sample was extracted with an acetonitrile–water mixture (60:40, v/v), purified by an immunoaffinity column, eluted with a methanol–acetic acid mixture (98:2, v/v), and reconstituted with a methanol–water mixture (50:50, v/v) after drying with nitrogen. Finally, the reconstituted solution was detected by LC-MS/MS and quantified by isotope internal standard method. The six mycotoxins had a good linear relationship in a certain concentration range, the correlation coefficients were all greater than 0.99, the limits of detection were between 0.075 and 1.5 µg·kg−1, and the limits of quantification were between 0.5 and 5 µg·kg−1. The average spike recoveries in the four feed matrices ranged from 84.2% to 117.1% with relative standard deviations less than 11.6%. Thirty-six actual feed samples were analyzed for mycotoxins, and at least one mycotoxin was detected in each sample. The proposed method is reliable and suitable for detecting common mycotoxins in feed samples.
Factors Affecting Accounting Students' Interest in Online Learning in the Pandemic Period from the Perspective of Planned Behavior

This study aims to examine the factors that influence accounting students' interest in online learning with the concept of planned behavior theory. The research variables consisted of attitudes, regulations, perceptions of control and interest in online learning. The research sample consisted of 150 accounting students in the city of Semarang, the data collection technique was using purposive sampling technique. Hypothesis test using multiple regression test and t test. The study's results accept the three hypotheses proposed and prove that the variables of attitude, regulation, and perception of control positively affect interest in online learning. The results of this study also strengthen that the theory of planned behavior can be used as an approach to explain the factors that influence individual interest in doing something.