Miracle-dz/UniFAR-FTUs huggingface dataset:
Relative Efficiency of Bonds and Sukuk: A Case of Selected Islamic Countries

This study compares the efficiency of bonds and Sukuk through a comprehensive analysis using descriptive statistics and regression techniques. The dataset includes outstanding Sukuk and bonds issued between 1993 and 2023 in Malaysia, Indonesia, Pakistan, Turkey, and Saudi Arabia. Objectives focus on examining mean coupon rate and yield-to-maturity (YTM) differences, exploring yield variations, and assessing efficiency levels. The analysis employs t-tests and ordinary least squares (OLS) regression. Findings indicate that bonds and Sukuk are sold at a premium, with mean coupon rates exceeding YTMs. A separate analysis supports the hypothesis that Sukuk may have higher mean YTMs and coupon rates than bonds. Sukuk exhibits significantly higher YTMs, indicating greater returns compared to bonds across the selected countries. Sukuk also demonstrates higher efficiency, reflected by a positive and significant coefficient, implying a more efficient yield-to-tenure ratio. Policy implications highlight the need to enhance regulation quality and transparency in disclosing yield differentials and risks and promote Sukuk as an attractive investment option. Diversifying investment portfolios and improving market liquidity is also recommended. Limitations include limited data availability, preventing analysis of individual countries and segregation between corporate and sovereign issues within Sukuk. In conclusion, this study provides valuable insights into the efficiency of bonds and Sukuk, offering policy recommendations. Disparities in mean coupon rates, YTMs, and efficiency levels underscore the importance of informed decision-making. Policymakers and investors can utilize these findings to understand the potential benefits of Sukuk and implement strategies to foster a more efficient and robust market. Further research is necessary to address data limitations and explore specific country-level dynamics and Sukuk classifications.
Association between resilience promotion factors during childhood and risk of drug use disorder during adulthood

Few studies have been conducted on the relationship between “outside-residing” resilience characteristics and the risk of developing drug use disorder later in life. These characteristics include responsive and caring parenting, household routines involving regular family meals and bedtime routines, social support from peers, participation in organized activities, and religious service attendance. We quantified the association between these resilience promotion factors during childhood and the risk of developing criteria for drug use disorder during adulthood using data from a retrospective cohort study of 618 adults born in Massachusetts during 1969–1983, including those with adverse childhood experiences (ACEs). Self-administered questionnaires gathered information on criteria for drug use disorder, ACEs, and family and community resilience promotion factors. Compared to individuals with “low” numbers of resilience promotion factors, 30% (95% CI: 0.5–0.9) and 50% reductions (95% CI: 0.4–0.8) in the risk of developing one or more criteria for drug use disorder were observed among those with “moderate” and “high” numbers of resilience factors, respectively (p value for trend=0.003). Overall, family factors were associated with greater risk reductions than comparable numbers of community factors. Among individuals with ACEs, a “high” number of family factors but not community factors were associated with a reduction in risk (RR:0.6, 95% CI:0.4–1.0 for family factors, RR:1.0, 95% CI:0.5–1.8 for community factors). These results suggest that the risk of developing criteria for drug use disorder decreases in a dose-response fashion according to the number of “outside-residing” resilience promotion factors during childhood, and that family factors are associated with greater risk reductions than community factors, particularly among individuals with ACEs. Coordinated prevention efforts at the family and community level are recommended to reduce the risk of this important societal problem.
Mesoscale simulation of natural convection in an inclined square cavity

In this paper, a numerical method was applied to solve two dimensional, incompressible, thermal fluid flow problem. This study presents numerical prediction of natural convection heat transfer inside an inclined square cavity with perfectly conducting boundary conditions for the top and bottom walls. The mesoscale lattice Boltzmann scheme with uniform mesh resolution was applied a numerical research tool. The inclination angels were varied from 20° to 80° with 20° intervals. The results were presented in terms of streamlines and isotherms plots. We found that the flow structure together with the heat transfer mechanism are significantly dependence on the magnitude of the inclination angles. Good agreements were obtained when compared with the results published by other researchers in previous studies.
Identifying Risk Factors Associated With Lower Back Pain in Electronic Medical Record Free Text: Deep Learning Approach Using Clinical Note Annotations

Background Lower back pain is a common weakening condition that affects a large population. It is a leading cause of disability and lost productivity, and the associated medical costs and lost wages place a substantial burden on individuals and society. Recent advances in artificial intelligence and natural language processing have opened new opportunities for the identification and management of risk factors for lower back pain. In this paper, we propose and train a deep learning model on a data set of clinical notes that have been annotated with relevant risk factors, and we evaluate the model’s performance in identifying risk factors in new clinical notes. Objective The primary objective is to develop a novel deep learning approach to detect risk factors for underlying disease in patients presenting with lower back pain in clinical encounter notes. The secondary objective is to propose solutions to potential challenges of using deep learning and natural language processing techniques for identifying risk factors in electronic medical record free text and make practical recommendations for future research in this area. Methods We manually annotated clinical notes for the presence of six risk factors for severe underlying disease in patients presenting with lower back pain. Data were highly imbalanced, with only 12% (n=296) of the annotated notes having at least one risk factor. To address imbalanced data, a combination of semantic textual similarity and regular expressions was used to further capture notes for annotation. Further analysis was conducted to study the impact of downsampling, binary formulation of multi-label classification, and unsupervised pretraining on classification performance. Results Of 2749 labeled clinical notes, 347 exhibited at least one risk factor, while 2402 exhibited none. The initial analysis shows that downsampling the training set to equalize the ratio of clinical notes with and without risk factors improved the macro–area under the receiver operating characteristic curve (AUROC) by 2%. The Bidirectional Encoder Representations from Transformers (BERT) model improved the macro-AUROC by 15% over the traditional machine learning baseline. In experiment 2, the proposed BERT–convolutional neural network (CNN) model for longer texts improved (4% macro-AUROC) over the BERT baseline, and the multitask models are more stable for minority classes. In experiment 3, domain adaptation of BERTCNN using masked language modeling improved the macro-AUROC by 2%. Conclusions Primary care clinical notes are likely to require manipulation to perform meaningful free-text analysis. The application of BERT models for multi-label classification on downsampled annotated clinical notes is useful in detecting risk factors suggesting an indication for imaging for patients with lower back pain.
Rational Approximations to Power Expansions

There is a class of approximants to power expansions that possess remarkable analyti? cal and numerical properties but are not as widely known as they should be. The story begins in 1892 when Henri Pade considered the representation functions by rational functions in his thesis [1]. Nowadays, this work plays an important role in several branches of theoretical and applied researches. As an example, we mention the development of computational methods to represent transcendental functions with algorithms that converge quickly. Pade's method also makes it possible to obtain from a power series (converging or diverging) for a function a table of rational approximations to it [2]. The rational function representations of a power expansion are now known as Pade approximants. A recent extensive study on Pade approximants is [3]. We will briefly present the central results of Pade's work in modern notation and will show how to construct a Pade approximant given a power expansion.
Mathematical analysis on a diffusion model describing the compatibility between two types of tumor cells

Cancer caused by malignant tumor is a very common and serious disease which can lead to people towards death. However, sometimes, cancer may be controlled if the cancer cells can be infected and split by particular virus with weak pathogenicity. To give a better understanding on tumor dynamics, in this paper, we deal with a reaction–diffusion tumor model, which comes from the process of tumor therapy with oncolytic virus. Our main objective is to analyze the biological compatibility of uninfected and infected tumor cells. In addition, we are concerned with the long‐time behavior, stability, and a priori estimates for the model. The compatibility conditions show that under certain range of parameters control, the infected tumor cells can coexist with normal tumor cells or be eliminated by oncolytic virus as time goes on; in the elimination case, it implies that the organism's complete recovery is highly possible as a result of the attack of oncolytic virus. An indirect idea in calculating fixed point index is proposed; correspondingly, a new condition on coexistence is presented.
Single Tuned Filter Design for Mitigating Harmonic Distortion in (30 KV) ALTAHRER Substation

Nowadays, due to the fast growth of electronic devices, harmonic issues have become a main matter for current day electrical operators. Some of the causes of harmonics are: a) ripples in voltage waveform of machines, b) flux distortion in the synchronous machines, c) transformer magnetizing currents, d) non-linear loads such as static power converters, arc furnaces, and e) static-var compensators as suppliers of continuously variable var sources. The harmonic filtering is one of the solutions for preventing the worrying harmonics from entering the rest of the system. There are basically two types of filters: i) passive, where the filter components are passive elements such as resistor, inductor, and capacitor, and ii) active, where the filter has a controlled current or voltage source. This peper introduces a single-tuned passive filter to minimize the harmonic distortion of AL-TAHRER substation (30KV). The offered filter and studied system modeling are built by ETAP software. Results show the effectiveness of the proposed filter in mitigating total harmonic distortion of studied system
Treatment of Facioscapulohumeral Muscular Dystrophy (FSHD): A Systematic Review

Facioscapulohumeral muscular dystrophy (FSHD) is the third most common type of muscular dystrophy. This disease presents as a slowly progressive asymmetric muscle weakness that involves the facial, scapular, and upper arm muscles mainly. Currently, there is no established consensus on this disease treatment in terms of medications. We assessed the response to the treatment of the drugs utilized in clinical trials by performing a systematic literature review in English using the preferred reporting items for systematic reviews (PRISMA) and meta-analyses. We only used human clinical trials in patients diagnosed with FSHD that received consistent pharmacological treatment. We included 11 clinical trials that fulfilled our criteria. We concluded that albuterol had statistically significant results in three out of four clinical trials, with improved elbow flexors muscle strength. Vitamin C, vitamin E, zinc gluconate, and selenomethionine showed significant improvement in the maximal voluntary contraction and endurance limit time of quadriceps muscle. At the same time, diltiazem and MYO-029 demonstrate no improvement in function, strength, or muscle mass. Losmapimod, currently in phase I of the ReDUX4 trial, showed promising results. Peradventure, more clinical trials are still needed to address this subject. Nevertheless, this review provides a clear and concise update on the treatment for this disease.
The effect of star formation algorithms on the morphology of isolated galactic disc models

The effect of star formation algorithms on the morphology of isolated galactic disc models by Maan H Hani submitted on March 18, 2013: Structure is found in the Universe on various scales ranging from galaxies to galaxy clusters, super clusters. This structure is believed to have formed in a bottom-up hierarchical way. Computational techniques allow us to model structure formation and improve our understanding of structure formation. Moreover, cosmological simulations and simulations of galaxy formation and evolution have resolutions orders of magnitude higher than the scales at which stars form. Therefore, the application of a convergent flow criterion in galaxy formation simulations is debatable. Two isolated galactic discs (280,000 particles each) and two collapsing clouds (with a NFW dark matter density profile, 100,000 particles each) were simulated for 1.02Gyr and 4.4Gyr respectively. Each pair of simulations differed in the star formation conditions. One model allowed star formation in collapsing regions only (negative velocity divergence), while the other had no such condition. Although both models had similar star formation rates, the two models also showed significant morphological differences. With the removal of the velocity divergence criterion more stars were formed and a wider spread in the stellar spatial distribution in the potential well was detected.
Synchronization and anti-synchronization of fractional dynamical networks

The issue of synchronization between dynamical systems has attracted much attention, and the systems with integer-order dynamical networks have been well studied. The synchronous behavior of fractional-order dynamical systems is very interesting and importance, but has rarely been studied. In this paper, we studied the synchronization and anti-synchronization behavior between integer-order dynamical networks and fractional-order dynamical systems via a Takagi-Sugeno fuzzy model. Remarkably, there is synchronous behavior in such a system, and this is dramatically different from the behavior of integer-order dynamical networks. Moreover, we studied the impact of different coupling strengths on the dynamical process of synchronization and robustness of the designed controller to different coupling functions, different dimensions of dynamical equations and different fractional orders. Finally, we propose the theoretical analysis, which coincides well with the numerical simulations of five typical examples.
Standard 12-Core Transrectal Ultrasound-Guided Prostate Biopsy, a Useful Tool in Screening for Prostate Cancer: A Prospective Study in Uyo, Akwa Ibom State, Nigeria

Introduction: Guided prostate biopsy is still relevant in confirming the diagnosis of suspected prostate cancer. Objective: This study evaluated the role of Transrectal Ultrasound (TRUS) guided biopsy along with histopathological evaluation in the detection of prostate cancer on the basis of abnormal digital rectal examination (DRE) findings and elevated prostate specific antigen levels (PSA). Participants and Methods: This prospective study was undertaken among consenting men aged 40 years and above screened for prostate cancer at the University of Uyo Teaching Hospital using targeted, stepwise protocol including DRE, PSA and standard 12-core transrectal ultrasound guided biopsy technique. Biopsy samples were sent for histopathological evaluation. Findings were documented, analyzed and presented in tables and figures. Results: Among 437 participants, abnormal DRE findings, elevated PSA level above 4.0 ng/ml and abnormal TRUS findings were 17.2%, 21.1%, and 17.3% respectively. Of 44 participants who had prostate biopsies with histopathologic assessment, benign prostatic diseases were 24 cases (54.5%), slightly outnumbering malignant prostatic diseases seen in 20 (45.5%). The prostate cancer detection and prevalence rates were 45.5% and 4.6% respectively. Prostatic adenocarcinoma (45.5%), nodular hyperplasia (45.5%), basal cell hyperplasia (6.8%) and high grade prostatic intraepithelial neoplasia (2.2%) were identified histologic subtypes. Nodular hyperplasia was commonly associated with chronic prostatitis (80.0%). A significant association between DRE findings, outline of prostate, and tumour subtype was ascertained. Conclusion: Targeted screening protocol encompassing TRUS guided 12- core biopsy is a final arbiter in the diagnosis of prostate cancer and has a fairly high prostate cancer detection rate of 45.5%.
A numerical study of ponderomotive ion acceleration in a dense plasma driven by a circularly polarized high-intensity laser beam normally incident on thin foils

We use an Eulerian Vlasov code to study the efficient ion acceleration in dense targets by the ponderomotive force of a high-intensity circularly polarized laser beam, normally incident on a dense plasma. The code solves the one-dimensional relativistic Vlasov–Maxwell equations for both electrons and ions. We follow in details the mechanism of formation and evolution of a double-layer structure, where electrons are pushed steadily in the forward direction by the ponderomotive force of the laser beam, trapping an ion population, while an induced space charge electric field pulls ions behind them, forming a double-layer structure supported by the strong ponderomotive pressure of the intense laser beam. We consider the case of a high-density deuterium plasma with n/ncr= 100, where ncr is the critical density. Three cases are studied, by varying the width of the dense target and the intensity of the laser beam (with the normalized vector potential or quiver momentum a0= 50 and a0= 100), to follow the physical processes involved in the ion acceleration and the final formation of a neutral plasma jet ejected from the back of the target. We follow the transition from a situation where the laser pulse radiation pressure is acting on the double layer in the target, to a situation where below a given thickness a fraction of the laser energy is transmitted through the target. The absence of noise in the Eulerian Vlasov code allows us to follow accurately the evolution of the phase-space structures of the distribution functions.
Measurement Technique and Result Analysis of Helicopter Rotor Blade Structural Vibration Load

The measurement of helicopter rotor blade structural load amid flight has always been the difficulty in flight test. In this paper, the principle of the existing blade structural load measurement method (electrical measurement method) was analyzed, and the problem of physical decoupling in the use of this method was expounded. As a weak signal measurement, the electrical measurement method also has electromagnetic interference problems, which will affect the flight test period of blade structural load measurement. Therefore, a numerical decoupling measurement method based on fiber Bragg grating (FBG) was proposed. Then, the new method was applied and verified in the load equation modeling test and the flight test under the real atmospheric environment was carried out. Through comparing and analyzing the measured data of the new method and the electrical measurement one, the correctness of the FBG data decoupling method was validated. The results indicate that the method proposed in this paper can effectively improve the efficiency of blade load equation modeling engineering and has good application value.
An Improved Power System State Estimation Using A Dynamically Adapted JAYA Algorithm

State estimation is a central issue for power systems monitoring and control. Applying state estimation schemes ensures the accuracy of system real-time monitoring process. Due to the high nonlinearities and non-smoothness of the dynamic behavior of power systems, state estimation is getting more importance to lessen the error margins. In order to find the best estimate of the various variables of a power system, optimization-based and statistical techniques are applied. Classically, common metering devices are used to measure power system variables. Nevertheless, these devices are associated with errors, especially with the ongoing expansion of the power networks. These errors are linked to many issues related to operation and communication processes besides the errors caused by the metering device itself. The commonly applied technique to solve the power system state estimation problem is the Weighted Least-Squares (WLS) method. In this paper a dynamically adapted algorithm is introduced employing a WLS-based dynamic JAYA optimization technique. The algorithm was validated and applied on the well-known IEEE 14-bus network. The results proved the efficiency and advantages of the proposed algorithm when compared to other methods used for the state estimation problem.
How Race, Resentment, and Ideology Shape Attitudes About Native American Inherent Rights and Policy Issues

What shapes attitudes about Native American policy issues and inherent rights? Race and ethnicity are important in shaping US public opinion, but Native Americans have been almost entirely excluded from this research. We use data from an original survey and focus groups collected from the Reclaiming Native Truth project to examine the factors that shape attitudes toward Native American inherent rights and broader race conscious policy issues. We find high levels of support overall, but several factors influence lower levels of support. Many people have very low factual knowledge about Native American issues and rely heavily on partisan shortcuts in forming opinions, especially for policy issues. Overall, attitudes about inherent rights are less consistent as many people have very little knowledge about them. People of color tend to be more supportive than white people and white people tend to rely more on partisan shortcuts. Specifically, conservative whites are the least supportive across most issues. We also explore the effect of Native American resentment, finding there are people who hold overtly hostile views of Native Americans and are unsupportive of their rights and policies. Our findings contribute to growing literature on Indigenous resentment, settler colonialism and public attitudes toward Indigenous peoples.