Miracle-dz/UniFAR-FTUs huggingface dataset:
Riding the storm: fiscal sustainability in the Caribbean

ABSTRACT Fiscal sustainability remains a paramount challenge for small economies with high debt and greater vulnerability to climate change. This paper applies the model-based fiscal sustainability test in 16 Caribbean countries during the period 1980–2018. The results indicate that the coefficient on lagged government debt is positive and statistically significant, implying that fiscal policy in the Caribbean takes corrective actions to counteract an increase in the debt-to-GDP ratio. Nonlinear estimations, however, show that the quadratic debt parameter is negative, which indicates that fiscal policy response is not adequate to ensure sustainability at higher levels of debt. We also find that the fiscal stance tends to be countercyclical on average during the sample period. These empirical results confirm that maintaining prudent fiscal policies and implementing growth-enhancing structural reforms are necessary to build fiscal buffers and ensure debt sustainability with high probability even when negative shocks occur over the long term.
Evaluation and Implementation of a Telepsychiatry Trial in the Emergency Department of a Metropolitan Public Hospital

ABSTRACT Telepsychiatry via video conferencing is not new to mental health but has been expanding at a rapid rate over recent years. Initially it was introduced for treatment in remote and rural communities, but it is now being utilized in larger health settings due to increasing patient demand and cost-effectiveness. Emergency departments are becoming increasingly burdened, as the workforce cannot keep pace with the rising demand of patient mental health needs. While telepsychiatry has been shown to have treatment efficacy, research is still relatively new, especially within the emergency department context.
On the Unified Design of Accelerated Gradient Descent

Nowadays, different kinds of problems such as modeling, optimal control, and machine learning can be formulated as an optimization problem. Gradient descent is the most popular method to solve such problem and many accelerated gradient descents have been designed to improve the performance. In this paper, we will analyze the basic gradient descent, momentum gradient descent, and Nesterov accelerated gradient descent from the system perspective and it is found that all of them can be formulated as a feedback control problem for tracking an extreme point. On this basis, a unified gradient descent design procedure is given, where a high order transfer function is considered. Furthermore, as an extension, both a fractional integrator and a general fractional transfer function are considered, which resulting in the fractional gradient descent. Due to the infinite-dimensional property of fractional order systems, numerical inverse Laplace transform and Matlab command stmcb() are used to realize a finite-order implementation for the fractional gradient descent. Besides the simplified design procedure, it is found that the convergence rate of fractional gradient descent is more robust to the step size by simulating results.
Economic Forecasting with an Agent-Based Model

We develop the first agent-based model (ABM) that can compete with benchmark VAR and DSGE models in out-of-sample forecasting of macro variables. Our ABM for a small open economy uses micro and macro data from national and sector accounts, input-output tables, government statistics, census and business demography data. The model incorporates all economic activities as classified by the European System of Accounts as heterogeneous agents. The detailed structure of the ABM allows for a breakdown into sector level forecasts. Potential applications of the model include stress-testing and predicting the effects of changes in monetary, fiscal, or other macroeconomic policies.
THE IMPLEMENTATION OF PERFORMANCE ASSESSMENT IN SOCIAL SCIENCE LEARNING

Purpose of the study: This study aims to determine the effect of the implementation of the performance assessment of the results of social studies with covariates social attitudes in fourth graders in District Jombang. Methodology: The research design uses archetypal, the Posttest Only Control Group with covariates social attitudes. Main Findings: There is a difference between students' social studies learning outcomes in learning with conventional performance appraisal and assessment, there are differences in the learning outcomes of social studies students who take conventional performance appraisal and assessment and there is a significant contribution between social attitudes towards social studies student learning outcomes of 12.9%. Applications of this study: Social studies with covariates social attitudes in fourth graders in District Jombang. Novelty/Originality of this study: Based on the above findings it can be concluded that the implementation of the performance assessment affects the students’ Social Sciences (IPS)learning achievement both before and after control.
Density Functional Theory Study of Water Adsorption on the CoO (100) and CoO (110) Surfaces

In this study, density functional theory was used to identify the optimum adsorption sites of H2O molecule on the CoO(100) and CoO(110) surfaces. The adsorption of H2O molecule is the first step in water molecule splitting on a catalytic surface. CoO bulk crystals were optimised by using generalised gradient approximation-Perdew–Burke–Ernzerhof functional methods through spin orbital interaction calculations. Band structure calculation results show that the indirect and direct bandgaps are 0.23 and 1.6 eV, respectively, which are similar to the reported experimental bandgap. The CoO(100) and CoO(110) surfaces were created from the optimised bulk structure. The CoO(100) surface contains 13 atoms Co vacancy, whereas the CoO(110) surface contains 15 atoms Co vacancy on the top layer surfaces. The adsorption energy of H2O on the CoO(100) and CoO(110) surfaces was calculated on the basis of eight configurations. The optimum adsorption energy (5.123 eV) of H2O on the CoO(100) surface is in Model 5. Meanwhile, the optimum adsorption energy (2.810 eV) of H2O on the CoO (110) surface is in Model 6. This result indicates that H2O is easier to absorb on CoO(110) than on CoO(100), and agree to the experiment result reported.
Cavitation Damage Detection Through Acoustic Emissions

Cavitation in hydraulic machinery is a common phenomenon with high potential for causing damage. Often it is not known whether the machinery is damaged by cavitation or cavitation occurs at all. With regard to predictive maintenance it would be advantageous not only to detect cavitation, but also to determine the current condition or damage of the hydraulic machinery. Knowing the current condition of the machinery, maintenance could be planned properly ahead and unnecessary downtime could be avoided. Since visual inspection of the current status i.e. state of cavitation and possible damage of the machinery is usually not possible due to missing optical access, acoustic inspection offers an alternative. In order to determine whether and how damage results in changes in acoustics, experiments in a controlled environment were conducted using a hydrofoil. The hydrofoil was placed in a cavitation-channel and exposed to strong cavitation for a defined period of time. Afterwards measurements of acoustic signals at different flow conditions with different cavitation conditions including no cavitation were conducted. The measurement procedure was repeated for several hundreds of times. So various measured acoustic signals of different cavitation damage states on the hydrofoil were captured. Since it was not known in which frequency region changes may occur due to cavitation damage, a broad frequency region reaching from several Hz up to 1MHz was investigated. The experiment shows promising results, such that cavitation damage at the hydrofoil results in significant changes in acoustics. Further different behavior in different frequency ranges and flow conditions can be observed.
A segmented generalized Markov regime-switching model with its application in financial time series data

ABSTRACT Movements of equity indices are very important information for an investment decision. Empirical studies illustrate that the movements switch among different regimes. The Markov regime-switching model has important applications to such analysis. However, parameters estimated under normality assumption might not be stable and the corresponding change-point detection algorithm might face some challenges when either the error distribution is heavy-tailed or observed data contain outliers. In this paper, we relax the normality assumption and propose a generalized Markov regime-switching (GMRS) model. We propose a GMRS model based change-point detection algorithm, which is tested on both simulation data and Hang Seng monthly index. Simulation studies show that this algorithm can improve the accuracy of identifying change-points when either the error distribution is heavy-tailed or observed data contain outliers. It is also evident that the identified change-points on Hang Seng monthly index data match the observed market behaviours.
Cost Optimization Estimation of Medical Institutions in Grading Diagnosis and Treatment based on System Dynamics Model

The grading diagnosis and treatment system in China is to improve the first-time diagnosis rate of patients in primary health care institutions, thereby increasing the proportion of people in primary health care institutions, thus achieving the goal of reducing costs. This study constructs a system dynamics model of the number of primary and higher-level visits—the cost of medical institutions, and simulates the effect of the increase in the proportion of patients attending the primary level on the cost of medical institutions. The study found that with the increase in the number of visits, the cost of primary medical institutions will increase, but the total cost of the entire medical system will be reduced significantly. Moreover, the higher the proportion of the number of people attending the primary level, the lower the total cost. If the proportion of primary care in 2017 increases by 15%, and this trend is maintained until 2021, the total cost saved by medical institutions in 2021 will be as high as 903.32
Deformation and Energy Absorption of Fiber Metal Laminates (FMLS) After Ballistic Impact Load

Estimated damage levels from ballistic impact zones provide valuable information to make bulletproof materials more effective. This study aims to determine the impact of ballistics including deformation and energy absorption in fiber metal laminates (FMLs) that collide with 9 mm FMJ caliber bullets at speeds of 426 m/s. Finite element method modeling is done using ANSYS 18.1 workbench software. The simulation results show that FMLs can hold the bullet rate with deformation on the back of the target (DOPIII) of 8,55 mm and total energy absorption of 426,59 J at 0,000095 s. The combination of two materials, Al 5083 in the outer layer and kevlar/epoxy as the core, results in faster energy absorption and maximum stress concentrations only occur in the kevlar/epoxy so there is no damage to the first and subsequent layers.
The Impact of Using a Robot Mannequin (RoMa) in Visual Merchandising

Social robots applications are becoming more and more popular in our daily life. Advertising, in this case, apparel advertising, is an area that humans must deal with every day. RoMa is a social robot mannequin that has been designed and developed as a mobile robot for use in the field of advertising and visual trading. In this paper, characteristics such as the interaction of people with RoMa, the impact of using a social robot on the sustainability of a storeâ€™s brand name for customers, the desire to revisit the store for another purchase, and the robot's structural features were measured in a Tehran retail store using various tools such as questionnaires, cameras, and a microphone. Finally, customer preferences for the process of selecting and buying clothes as well as an examination of the mannequinâ€™s display features have also been studied.
HEAVY METALS IN TOPSOILS OF THE REPUBLIC OF TATARSTAN, RUSSIA: MULTIVARIATE ANALYSIS AND POLLUTION EVALUATION

Background. The study is conducted to investigate the content and spatial distribution of Fe and eight heavy metals (Cd, Co, Cr, Cu, Mn, Ni, Pb, and Zn) in soils of the industrially developed region. Materials and methods. A total of 1,170 soil samples of different land use (natural, agricultural, urban) were collected from topsoils in the territory of the Republic of Tatarstan, Russia. Heavy metals concentrations in soil samples were determined using atomic absorption spectrometry after 5M HNO3 extraction. Multivariate and geostatistical analyses were used to investigate the current state of soil heavy metal contamination and to identify spatial patterns and possible sources of heavy metals on the regional scale. Results. Zonal soil types of a natural land use were used to assess the regional background values of the heavy metals: Cd – 0.44±0.24 mg/kg, Co – 10.4±3.6 mg/kg, Cr – 23.3±12.7 mg/kg, Cu – 16.4±7.8 mg/kg, Fe – 15275.4±5178.3 mg/kg, Mn – 652.4±228.4 mg/kg, Ni – 29.8±18.8 mg/kg, Pb – 11.5±3.2 mg/kg, Zn – 43.3±12.8 mg/kg. The results of the pollution evaluation showed the absence of regionalscale contamination directly related to agriculture. Urban soils were contaminated by Cu, Pb and Zn. Geostatistical analysis revealed several patterns of regional distribution of heavy metals and suggested an anthropogenic impact to the Cu, Pb and Zn distribution. Principal component analysis allowed distinguishing three regional geochemical groups of heavy metals and showed that at the regional scale the distribution of Cu, Mn and Ni is controlled by the element richness in soil parent material, overlayed by the soil forming factors; the distribution of the Co, Cr and Fe is controlled mainly by lithology; and the distribution of the Pb, Zn and Cd is strongly influenced by the anthropogenic sources. Conclusion. This case study demonstrates that a combination of multivariate statistics and geostatistical analysis together with the pollution assessment allows comprehensive characterizing heavy metals spatial distribution and determining their sources.
Pore‐Scale Modeling of Fluid‐Fluid Interfacial Area in Variably Saturated Porous Media Containing Microscale Surface Roughness

A pore‐scale model is developed to simulate fluid‐fluid interfacial area in variably saturated porous media, with a specific focus on incorporating the effects of solid‐surface roughness. The model is designed to quantify total (film and meniscus) fluid‐fluid interfacial area (Anw) over the full range of wetting‐phase fluid saturation (Sw) based on the inherent properties of the porous medium. The model employs a triangular pore space bundle‐of‐cylindrical‐capillaries framework, modified with three surface roughness‐related parameters. The first parameter (surface roughness factor) represents the overall magnitude of surface roughness, whereas the other two parameters (interface growth factor and critical adsorptive film thickness) reflect the microscale structure of surface roughness. A series of sensitivity analyses were conducted for the controlling variables, and the efficacy of the model was tested using air‐water interfacial area data measured for three natural porous media. The model produced good simulations of the measured Anw data over the full range of saturation. The results demonstrate that total interfacial areas for natural media are typically much larger than those for ideal media comprising smooth surfaces due to the substantial contribution of surface roughness to wetting‐film interfacial area. The degree to which fluid‐fluid interfacial area is influenced by roughness is a function of fluid‐retention characteristics and the nature of the rough surfaces. The full impact of roughness may be masked to some degree due to the formation of thick wetting films, which is explicitly quantified by the model. Application of the model provides insight into the importance of the interplay between pore‐scale distribution and configuration of wetting fluid and the surface properties of solids.
ON THE OPTIMAL COMBINATION OF ANNUITIES AND TONTINES

Abstract Tontines, retirement products constructed in such a way that the longevity risk is shared in a pool of policyholders, have recently gained vast attention from researchers and practitioners. Typically, these products are cheaper than annuities, but do not provide stable payments to policyholders. This raises the question whether, from the policyholders' viewpoint, the advantages of annuities and tontines can be combined to form a retirement plan which is cheaper than an annuity, but provides a less volatile retirement income than a tontine. In this article, we analyze and compare three approaches of combining annuities and tontines in an expected utility framework: the previously introduced “tonuity”, a product very similar to the tonuity which we call “antine” and a portfolio consisting of an annuity and a tontine. We show that the payoffs of a tonuity and an antine can be replicated by a portfolio consisting of an annuity and a tontine. Consequently, policyholders achieve higher expected utility levels when choosing the portfolio over the novel retirement products tonuity and antine. Further, we derive conditions on the premium loadings of annuities and tontines indicating when the optimal portfolio is investing a positive amount in both annuity and tontine, and when the optimal portfolio turns out to be a pure annuity or a pure tontine.
The ECF sigma factor PvdS regulates the type I-F CRISPR-Cas system in Pseudomonas aeruginosa

During infection, successful colonization of bacteria requires a fine-tuned supply of iron acquired via iron transport systems. However, the transport systems serve as phage attachment sites and entry portals for foreign nucleic acid. Most bacteria possess the CRISPR-Cas system, which targets and destroys foreign nucleic acids and prevents deleterious effects of horizontal gene transfer. To understand the regulation of the CRISPR-Cas system, we performed genome-wide random transposon mutagenesis which led to the identification of the Extracytoplasmic Function (ECF) Sigma factor, PvdS as a regulator of the Type I-F CRISPR-Cas system in P. aeruginosa. We show that under iron-depleted conditions PvdS induces the expression of the type I-F CRISPR-Cas system. This regulatory mechanism involves direct interaction of PvdS with specific binding sites in the promoter region of cas1. Furthermore, activation of the CRISPR-Cas system under iron-depleted conditions increases horizontal gene transfer (HGT) interference and adaptation. The PvdS activation of the CRISPR-Cas system under iron limitation highlights the versatility of the P. aeruginosa in multitasking its regulatory machinery to integrate multiple stress factors. Importance P. aeruginosa infects a wide range of host organisms and adapts to various environmental stress factors such as iron limitation due to its elaborate regulatory system. P aeruginosa possesses the type I-F CRISPR-Cas system as a defense mechanism against phages infection and HGT. This work highlights the ability of P. aeruginosa to multitask its iron regulatory system to control the CRISPR-Cas system under a physiologically relevant stress factor such as iron limitation where the bacteria are vulnerable to phage infection. It also adds to the knowledge of the regulation of the CRISPR-Cas system in bacteria and presents a possible target that could prevent the emergence of phage resistance via the CRISPR-Cas system during the development of phage therapy.
Biochemical Characterization of Human AlkBH7

Stony Brook University. SBU Graduate School in Molecular and Cellular Biology. Lawerence Martin (Dean of Graduate School), Daniel F. Bogenhagen, M.D. Professor, Department of Pharmacological Sciences Dissertation Advisor, Orlando Scharer, Ph.D. Associate Professor, Department of Pharmacological Sciences Chairman of Defense, Masaaki Moriya, Ph.D. Research Professor, Department of Pharmacological Sciences, Paul A. Fisher, MD, PhD Professor and Vice-Chairman, Department of Pharmacological Sciences.
Polymer-based porous microcarriers as cell delivery systems for applications in bone and cartilage tissue engineering

For tissue regeneration or repair, a suitable temporary scaffold needs to be constructed for delivering regenerative cells to damaged or diseased tissue. Scaffold types are currently categorised into 3D monolithic scaffolds, hydrogels, and microcarriers. Among these scaffolds, microcarrier systems offer an attractive method for cell amplification and enhancement of phenotype expression, and they have emerged as powerful injectable carriers to repair and reconstruct irregular defects in tissues and organs. In this article, several important issues related to polymeric porous microcarriers for tissue engineering are reviewed. The properties of porous microcarriers, including surface chemistry, pore structure, typical particle size, and specific density, and the corresponding effects on cell cultures are discussed. The fabrication techniques and biomaterials investigated for porous microcarriers are summarised, and their advantages and disadvantages are outlined. Recent advancements in the application of porous microcarriers, including bone and cartilage tissue engineering, are also presented.
The Binding Prediction Model of The Iron-responsive Element Binding Protein and Iron-responsive Elements

Iron is essential to fulfilling an indispensable role in the biological process in human physiology. Various proteins were known involved in iron metabolism. One of the proteins called iron-responsive element binding protein (IRP)which acts as master iron of cellular iron homeostasis. There are two IRP known to date, which is: IRP1 and IRP2. Previous studies showed IRP bind to iron-responsive elements (IRE) located in 5’-UTR of the transferrin receptor 1. The interaction of IRP/IRE is well studied through many years to find a better treatment for the cellular disorder in iron metabolism. However, the structural differences of both IRP and the binding prediction model of IRP/IRE remain unclear. This study provides a better understanding of the IRP structure and the IRP/IRE2 binding prediction model in a healthy condition. Several bioinformatic analyses were implemented in this study, such as molecular docking simulation, domain prediction, and structural similarity analysis. Structural analysis of IRP demonstrates a low root mean square deviation score that indicates both of IRP have high similarity in structure with different characteristics, such as binding site, and metabolic pathway. Interestingly, molecular docking simulation showed IRP has a preferably binding site when targeting specific IRE. Thus, this information could be beneficial in developing a drug for an iron-related disease.
A study on right iliac fossa mass

Mass in the right iliac fossa is not an uncommon entity in the surgical wards, whether detected clinically or as an Ultrasonography finding. Though we think of appendix more commonly in the right iliac fossa there are many other structures giving rise to a mass in the right iliac fossa. Thus preoperative diagnosis remains an enigmatic challenge and a reminder of art of surgical diagnosis. Patients with mass in the right iliac fossa may confront the surgeon, pediatrician or gynecologist. Thus, thorough understandings of the anatomy and pathological process that may occur within the abdomen are essential for an accurate diagnosis and plan of treatment. Some patients will require immediate surgical intervention whereas others will improve with conservative treatment. ABSTRACT