Miracle-dz/UniFAR-FTUs huggingface dataset:
Clumpy Outflows from Supercritical Accretion Flow

Significant fraction of matter in supercritical (or super-Eddington) accretion flow is blown away by radiation force, thus forming outflows, however, the properties of such radiation-driven outflows have been poorly understood. We have performed global two-dimensional radiaion-magnetohydrodynamic simulations of supercritical accretion flow onto a black hole with 10 or 10^8 solar masses in a large simulation box of 514 r_S x 514 r_S (with r_S being the Schwarzschild radius). We confirm that uncollimated outflows with velocities of 10 percents of the speed of light emerge from the innermost part of the accretion flow over wide angles of 10 - 50 degree from the disk rotation axis. Importantly, the outflows exhibit clumpy structure above heights of ~ 250 r_S. The typical size of the clumps is ~ 10 r_S, which corresponds to one optical depth, and their shapes are slightly elongated along the outflow direction. Since clumps start to form in the layer above which (upward) radiation force overcomes (downward) gravity force, Rayleigh-Taylor instability seems to be of primary cause. In addition, a radiation hydrodynamic instability, which arises when radiation funnels through radiation-pressure supported atmosphere, may also help forming clumps of one optical depth. Magnetic photon bubble instability seems not to be essential, since similar clumpy outflow structure is obtained in non-magnetic radiation-hydrodynamic simulations. Since the spatial covering factor of the clumps is estimated to be ~ 0.3 and since they are marginally optically thick, they will explain at least some of rapid light variations of active galactic nuclei. We further discuss a possibility of producing broad-line clouds by the clumpy outflow.
Digital Phenotyping in Health Using Machine Learning Approaches: Scoping Review

Background: Digital phenotyping is the real-time collection of individual-level active and passive data from users in naturalistic and free-living settings via personal digital devices, such as mobile phones and wearable devices. Given the novelty of research in this field, there is heterogeneity in the clinical use cases, types of data collected, modes of data collection, data analysis methods, and outcomes measured. Objective: The primary aim of this scoping review was to map the published research on digital phenotyping and to outline study characteristics, data collection and analysis methods, machine learning approaches, and future implications. Methods: We utilized an a priori approach for the literature search and data extraction and charting process, guided by the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-analyses Extension for Scoping Reviews). We identified relevant studies published in 2020, 2021, and 2022 on PubMed and Google Scholar using search terms related to digital phenotyping. The titles, abstracts, and keywords were screened during the first stage of the screening process, and the second stage involved screening the full texts of the shortlisted articles. We extracted and charted the descriptive characteristics of the final studies, which were countries of origin, study design, clinical areas, active and/or passive data collected, modes of data collection, data analysis approaches, and limitations. Results: A total of 454 articles on PubMed and Google Scholar were identified through search terms associated with digital phenotyping, and 46 articles were deemed eligible for inclusion in this scoping review. Most studies evaluated wearable data and originated from North America. The most dominant study design was observational, followed by randomized trials, and most studies focused on psychiatric disorders, mental health disorders, and neurological diseases. A total of 7 studies used machine learning approaches for data analysis, with random forest, logistic regression, and support vector machines being the most common. Conclusions: Our review provides foundational as well as application-oriented approaches toward digital phenotyping in health. Future work should focus on more prospective, longitudinal studies that include larger data sets from diverse populations, address privacy and ethical concerns around data collection from consumer technologies, and build “digital phenotypes” to personalize digital health interventions and treatment plans.
Non-Markovian stochastic dynamics of a two level system inmersed in a PBG material

Spontaneous emission of an atom in contact with the modified radiation field of a Photonic band gap (PBG) material is known to present a typically non-Markovian behavior. In addition, the presence of a gap of forbidden frequencies in the photonic density of states (DOS), produces residual population of the excited level, and population inversion when the atomic system is driven by an external laser field. It's our aim to study those effects using non-Markovian Stochastic Schroedinger equations (NMSSE). This formalism permit us to describe the evolution of the atom in terms of a wave function, |ψt(z)], which due to the presence of the radiation field depends on a stochastic variable zt. Having a singularity at the origin, the models of field correlation function usually found in literature, are not suitable to generate the corresponding zt. We have proposed a new correlation function that do not have this problem, and reproduces all the important physical phenomena of the system under study. The results obtained with NMSSE are compared with those of the master equation, since the ensemble average of stochastic trajectories gives the reduced density matrix of the system, ρs. In addition, we propose a new non-Markovian master equation derived from the stochastic formalism, which in contrast to the current models of master equation preserves positivity for the problem under study.
Analysis of Students’ Performance in Chemistry in the West African Senior School Certificate Examination (WASSCE) and National Examination Council (NECO) from 2015-2018

: The study analysed the students’ performance in Chemistry in the West African Senior School Certificate Examination (WASSCE) and National Examination Council (NECO) from 2015-2018. An expo-facto design of research type was used for the study. The population for this study comprised of all secondary schools who presented chemistry students for WASSCE and NECO in Ekiti State within 2015-2018. The sample size of six thousand and seventy-two (6072) from WASSCE 2015-2018 and five thousand and forty-three (5043) chemistry students from NECO 2015-2018 were used for the study. The instrument for data collection for the study was WASSCE and NECO 2015-2018 results of chemistry students in secondary schools in Ekiti State. The formulated hypotheses were tested using inferential statistics of t-test. The findings of the study revealed that there is significant difference in the performance of students that sat for chemistry in 2015 WASSCE and NECO; there is no significant difference in the performance of students that sat for chemistry in 2016 WASSCE and NECO; that there is no significant difference in the performance of students that sat for chemistry in 2017 WASSCE and NECO; there is significant difference in the performance of students that sat for chemistry in 2018 WASSCE and NECO; and there is significant gender difference in the performance of students that sat for chemistry WASSCE and NECO Examinations between 2015 and 2018. Hence, based on the findings, appropriate recommendations were made. balanced state non-adherence to rubrics; poor knowledge of basic chemical principles; poor communication skills; wrong spellings.
EFFECTS OF ADVANCE ORGANIZER ON SENIOR SCHOOL STUDENTS’ ACADEMIC ACHIEVEMENT IN CHEMISTRY IN EKITI STATE, NIGERIA

: This study investigated the effects of advance organizer on senior secondary school students’ achievement in Chemistry in Ekiti State, Nigeria. The research designed adopted for this study was non-randomized, non-equivalent pre-test and post-test control group design. The population consisted of all senior secondary class two (SSII) students taking Chemistry in Ikere – Ekiti while sample consisted of 97 senior secondary school two students were drawn from intact classes using purposive sampling technique. The instrument used for the study was Chemistry Achievement Test. The face and content validity as well as reliability of the research instrument were carried out and reliability coefficient of 0.86 was obtained. The results of the data collected from both pre-test and post-test were collated and analysed using statistical tools involving mean and standard deviation, graph t-test and Analysis of Variance (ANOVA) at 0.05 level of significance using). The findings of the study showed that students operate at moderate level performance in Chemistry before their exposure to expository advance organizer. However, the use of expository advance organizer improves the performance of students in Chemistry more than conventional method of instruction. It was therefore recommended that the use of advance organizer should be adopted for the teaching of Chemistry as innovative tools to facilitate effective teaching and learning in secondary schools. determined the effects of individual and collaborative concept mapping learning strategy on chemistry students' anxiety and academic achievement. The design of the study was quasi-experimental pre-test – post-test – delayed post-test control group design. The sample of 100 students was drawn from co-educational secondary schools in Taraba North senatorial district. The Chemistry Achievement Test for Students (CATS) and Chemistry Anxiety Scale (CAS) with the reliability of 0.79 and 0.86 respectively were the main instruments, Descriptive Statistics and Analysis of covariance were used to analyze the data collected. The findings revealed that the use of concept mapping had a positive effect on
Stochastic Models for Fractional Calculus

Preface: 1 Introduction 1.1 The traditional diffusion model 1.2 Fractional diffusion 2 Fractional Derivatives 2.1 The Grunwald formula 2.2 More fractional derivatives 2.3 The Caputo derivative 2.4 Time-fractional diffusion 3 Stable Limit Distributions 3.1 Infinitely divisible laws 3.2 Stable characteristic functions 3.3 Semigroups 3.4 Poisson approximation 3.5 Shifted Poisson approximation 3.6 Triangular arrays 3.7 One-sided stable limits 3.8 Two-sided stable limits 4 Continuous Time Random Walks 4.1 Regular variation 4.2 Stable Central Limit Theorem 4.3 Continuous time random walks 4.4 Convergence in Skorokhod space 4.5 CTRW governing equations 5 Computations in R 5.1 R codes for fractional diffusion 5.2 Sample path simulations 6 Vector Fractional Diffusion 6.1 Vector random walks 6.2 Vector random walks with heavy tails 6.3 Triangular arrays of random vectors 6.4 Stable random vectors 6.5 Vector fractional diffusion equation 6.6 Operator stable laws 6.7 Operator regular variation 6.8 Generalized domains of attraction 7 Applications and Extensions 7.1 LePage Series Representation 7.2 Tempered stable laws 7.3 Tempered fractional derivatives 7.4 Pearson Diffusion 7.5 Classification of Pearson diffusions 7.6 Spectral representations of the solutions of Kolmogorov equations 7.7 Fractional Brownian motion 7.8 Fractional random fields 7.9 Applications of fractional diffusion 7.10 Applications of.
Using of Recurrent Neural Networks (RNN) Process

Innumerable study assignments necessitate handling of orderly information. Picture captioning, speech creation, music production, and video game participation all necessitate that a simulation produces series of results. In alternative fields, like time sequences forecasting, video assessment, and music data recuperation, a simulation has to acquire knowledge from series of contributions. Consequently more interactive assignments, like native language translation, participating in conversation, and machine control, frequently ask for both. Recurrent Neural Networks or RNNs are a dominant group of connectionist representations that record time dynamics through phases in the chart. Contrary to feed forward neural networks, the RNNs may operate instances one at a time, keeping a state, or memory, which indicates a randomly lengthy context opening. Although such systems have always been tough to train and frequently consist of millions of boundaries, new progress in network architectures, maximization methods, and analogous computation have permitted widespread studying with RNNs. Through the last several years, networks founded on modern Long Short-Term Memory or LSTM and Bidirectional Recurrent Neural Network or BRNN designs have shown incomparable performance on assignments as different as picture captioning, handwriting identification, and language translation. In this work, we generate the contents of investigation that over the last thirty years has produced and diminished to practice such dominant simulations. When suitable, we resolve contradictory notation and nomenclature.
Disparities in Use of Patient Portals Among Adults in Family Medicine

Objective: This study examined patient portal utilization by analyzing the pattern of time and feature use of patients, and thus to identify functionalities of portal use and patient characteristics that may inform future strategies to enhance communication and care coordination through online portals. Methods: We conducted a retrospective study of patients at 18 family medicine clinics over a 5-year period using access log records in the electronic health record database. Dimensionality reduction analysis was applied to group portal functionalities into 4 underlying feature domains: messaging, health information management, billing/insurance, and resource/education. Negative binomial regression analysis was used to evaluate how patient and practice characteristics affected the use of each feature domain. Results: Patients with more chronic conditions, lab tests, or prescriptions generally showed greater patient portal usage. However, patients who were male, elderly, in minority groups, or living in rural areas persistently had lower portal usage. Individuals on public insurance were also less likely than those on commercial insurance to use patient portals, although Medicare patients showed greater portal usage on health information management features, and uninsured patients had greater usage on viewing resource/ education features. Having Internet access only affected the use of messaging features. Conclusion: Efforts to enroll patients in online portals do not guarantee patients will use the portals to manage their health. When considering the use of patient portals for improving telehealth, clinicians need to be aware of technological, socioeconomic, and cultural challenges faced by their patients. (
Quantitative Analysis of Sulfur Dioxide Emissions in the Yangtze River Economic Belt from 1997 to 2017, China

Economic development is responsible for excessive sulfur dioxide (SO2) emissions, environmental pressure increases, and human and environmental risks. This study used spatial autocorrelation, the Environmental Kuznets Curve (EKC), and the Logarithmic Mean Divisia Index model to study the spatiotemporal variation characteristics and influencing factors of SO2 emissions in the Yangtze River Economic Belt (YREB) from 1997 to 2017. Our results show that the total SO2 emissions in the YREB rose from 513.14 × 104 t to 974.00 × 104 t before dropping to 321.97 × 104 t. The SO2 emissions from 11 provinces first increased and then decreased, each with different turning points. For example, the emission trends changed in Yunnan in 2011 and in Anhui in 2015, while the other nine provinces saw their emission trends change during 2005–2006. Furthermore, the SO2 emissions in the YREB showed a significant agglomeration phenomenon, with a Moran index of approximately 0.233–0.987. Moreover, the EKC of SO2 emissions and per capita GDP in the YREB was N-shaped. The EKCs of eight of the 11 provinces were N-shaped (Shanghai, Zhejiang, Anhui, Jiangxi, Sichuan, Guizhou, Hunan, and Chongqing) and those of the other three were inverted U-shaped (Jiangsu, Yunnan, and Hubei). Thus, economic development can both promote and inhibit the emission of SO2. Finally, during the study period, the technical effect (approximately −1387.97 × 104–130.24 × 104 t) contributed the most, followed by the economic (approximately 27.81 × 104–1255.59 × 104 t), structural (approximately −56.45 × 104–343.90 × 104 t), and population effects (approximately 4.25 × 104–39.70 × 104 t). Technology was the dominant factor in SO2 emissions reduction, while economic growth played a major role in promoting SO2 emissions. Therefore, to promote SO2 emission reduction, technological innovations and advances should be the primary point of focus.
Actinobacteria as Effective Biocontrol Agents against Plant Pathogens, an Overview on Their Role in Eliciting Plant Defense

Pathogen suppression and induced systemic resistance are suitable alternative biocontrol strategies for integrated plant disease management and potentially comprise a sustainable alternative to agrochemicals. The use of Actinobacteria as biocontrol agents is accepted in practical sustainable agriculture, and a short overview on the plant-beneficial members of this phylum and recent updates on their biocontrol efficacies are the two topics of this review. Actinobacteria include a large portion of microbial rhizosphere communities and colonizers of plant tissues that not only produce pest-antagonistic secondary metabolites and enzymes but also stimulate plant growth. Non-pathogenic Actinobacteria can also induce systemic resistance against pathogens, but the mechanisms are still poorly described. In the absence of a pathogen, a mild defense response is elicited under jasmonic acid and salicylic acid signaling that involves pathogenesis-related proteins and secondary plant metabolites. Priming response partly includes the same compounds as the response to a sole actinobacterium, and the additional involvement of ethylene signaling has been suggested. Recent amplicon sequencing studies on bacterial communities suggest that future work may reveal how biocontrol active strains of Actinobacteria can be enriched in plant rhizosphere.
A Physics-Based Model for Mobile-Ionic Field-Effect Transistors With Steep Subthreshold Swing

A physics-based model and the corresponding simulation framework for the mobile-ionic field-effect transistor (MIFET) exhibiting the ferroelectric-like behaviors are innovatively proposed based on two-dimensional (2D) Poisson’s equation and non-equilibrium Green’s function (NEGF), coupling with ion drift-diffusion equations. The simulation framework captures the dynamic distribution of mobile ions’ concentrations within dielectric along the external electric field. TaN/amorphous-ZrO2/TaN capacitors are experimentally characterized for the model calibration. It is proved that the mobile ions dominate the ferroelectric-like behaviors in MIFETs. Sub-60 mV/decade can be achieved in MIFETs based on the proposed model, which is consistent with the experimental results.
Real and Simulated Microgravity: Focus on Mammalian Extracellular Matrix

The lack of gravitational loading is a pivotal risk factor during space flights. Biomedical studies indicate that because of the prolonged effect of microgravity, humans experience bone mass loss, muscle atrophy, cardiovascular insufficiency, and sensory motor coordination disorders. These findings demonstrate the essential role of gravity in human health quality. The physiological and pathophysiological mechanisms of an acute response to microgravity at various levels (molecular, cellular, tissue, and physiological) and subsequent adaptation are intensively studied. Under the permanent gravity of the Earth, multicellular organisms have developed a multi-component tissue mechanosensitive system which includes cellular (nucleo- and cytoskeleton) and extracellular (extracellular matrix, ECM) “mechanosensory” elements. These compartments are coordinated due to specialized integrin-based protein complexes, forming a distinctive mechanosensitive unit. Under the lack of continuous gravitational loading, this unit becomes a substrate for adaptation processes, acting as a gravisensitive unit. Since the space flight conditions limit large-scale research in space, simulation models on Earth are of particular importance for elucidating the mechanisms that provide a response to microgravity. This review describes current state of art concerning mammalian ECM as a gravisensitive unit component under real and simulated microgravity and discusses the directions of further research in this field.
Comparison of Different Adhesive Systems on Bond Strength of Resin Composite Posts Placed in Primary Teeth

Background This study evaluated the push-out bond strength of resin composite posts to the intracanal dentin in primary teeth using different adhesive systems. Materials and Methods In this experimental study, sixty-eight primary lateral incisors were randomly allocated in four groups (n = 17): Adper Single Bond 2 (ASB), Clearfil SE Bond 2 (CSE), G-Premio Bond in etch-and-rinse mode (GP-ER), and G-Premio Bond in the self-etch mode (GP-SE). The coronal one third of root canals was filled with resin composite. The push-out test was performed using a universal testing machine. ANOVA and LSD tests were used to analyze the data (P < 0.05). Results One-way ANOVA showed significant differences between the four groups in push-out bond strength (P = 0.002). The ASB and GP-SE groups showed lower and higher bond strengths, respectively. The failure mode distribution did not differ between the bonding agents used (P = 0.763). Adhesive and mixed failures were more frequent. Conclusion The GP-SE, GP-ER, and CSE exhibited significantly higher push-out bond strength than ASB. A universal adhesive system and 6th generation self-etch adhesives are recommended for use with resin composite posts in primary anterior teeth. Regarding the advantages of these bonding agents, such as fewer clinical steps, lower technical sensitivity, and easy application, they can be a good option for restoring primary teeth with short resin composite posts.
Compensation Strategy of Wideband Voltage Harmonics for Doubly-Fed Induction Generator

Compensating voltage harmonics is the advanced target for doubly-fed induction generator under the harmonically distorted grid, which is also an essential function in the process that wind power generation system evolves into supporting or regulating grid from adapting grid. To overcome the weakness of the existing methods that only can compensate harmonics with pre-known frequency, a modified derivation controller is designed to compensate the voltage harmonics with fixed and unfixed frequencies in this paper. This article firstly investigates the critical factors that affect the harmonics compensation capability of DFIG based on harmonic mechanism analysis. Then, the design thought and design procedure of the proposed control strategy are detailly presented. Further, the performance comparisons between the proposed control and the traditional control are analyzed to theoretically signify the superiority of the proposed strategy. Finally, the tests on the hardware in loop platform are done to verify the validity and effectiveness of the proposed control strategy.