Miracle-dz/UniFAR-FTUs huggingface dataset:
Appraisal of excess Kurtosis through outlier-modified GARCH-type models

Abstract The aim of this paper is to appraise if there is any improvement subtracting the effects of outliers from existing heteroscedastic models and whether this improvement makes difference with the existing models in achieving efficiency in capturing excess kurtosis in the returns series. The study employed both existing and outlier modified autoregressive conditional heteroscedastic (ARCH), generalized autoregressive conditional heteroscedastic (GARCH), exponential GARCH (EGARCH), Glosten, Jagnnathan and Runkle GARCH (GJR-GARCH) models with respect to normal and student-t distributions to assess the portion of excess kurtosis of the returns series expressed compare to the theoretical value of kurtosis. The data applied were the share prices of Union bank of Nigeria and Unity bank from January 3, 2006 to November 24, 2016, comprising 2690 observations and were obtained from Nigerian Stock Exchange. The results obtained revealed that the Outlier Modified GARCH-type models chosen were adequate and sufficiently reducing the value of excess kurtosis in close proximity to the theoretical value. Therefore, the modification of existing GARCH-type models by subtracting the effects of outliers seems to show a substantive improvement in the portion of excess kurtosis captured and thus proves that the Outlier Modified GARCH-type models make difference with the existing ones.
The case for establishing a blockchain research and development program at an academic medical center

Objective To develop a research and development program to study factors that will support research, education and innovation using blockchain technology for health in an effective and sustainable manner. We proposed to conduct qualitative research to generate insights for developing a market strategy to build a research lab for the promotion of blockchain technologies in health in academic environments. The team aimed to identify the key barriers and opportunities for developing a sustainable research lab that generates research, education, and application of blockchain in healthcare at an academic medical institution and test those strategies in a real-world scenario. Methods The research team identified potential customers and stakeholders through interviews and snowball sampling. The team conducted semi-structured interviews with 4 faculty researchers, 10 industry leaders, and 6 students from a variety of disciplines and organizations. The findings of these research activities informed our understanding of the needs of stratified customers and helped identify key assets and activities the lab will have to offer to meet those needs. Results The research insights from data analysis were used to build the business model for establishing a blockchain in health impact lab. This systematic study of areas where blockchain technology can impact health will guide the future development of research agenda for the researchers on campus. Conclusion Based on our learnings, we hope to design a Blockchain in Health Impact Lab to serve as a platform for students and faculty to come together with industry partners and explore current challenges of blockchain in healthcare. The academic medical center’s partnership with other healthcare providers will help create real-world opportunities to demonstrate and implement new technologies.
Knowing Ahead Mathematical Determinant of Bank Customers Credit Worthiness: A Safe Strategy for Funding Loan in a Critical Economy

The study was carried out to identify relevant attributes that signals the capacity of borrower to pay back the loan and determine the fit of mathematical scoring model to evaluate credit worthiness of a potential borrower. The data was taken from primary and secondary sources which was through the use of questionnaires (primary source) while the secondary source was collection of data from all the financial statements of selected business owners in Ekpoma, Edo State credits history of these business owners as well. The descriptive research and the explanatory research designs were employed in this study. Two research questions were raised while one hypothesis was formulated to guide the study. Thirty five (35) business owners were randomly selected from Ekpoma metropolis of Edo state for this study based on loan applications and business capacity. The data collected were analyzed using Altman Z-scores, frequencies and percentages while the Pearson Product Moment Correlation Co-efficient was used to determine the relationship between Mathematical Scoring model and credits worthiness. The result showed that credit scores developed from borrower financial and non-financial records and history such as turnover, assets, previous loan repayment rate and trading capital perfectly classified them into five risk classes of A (Worthy and very able to payback), B (worthy and less able to pay back) and D (not worthy at all). The result revealed that credit score can safe award banks and creditors against credit risk default and loss of money. It was therefore recommended among others, that banks and credit facilities handlers should adopt mathematical credit scoring techniques to avoid loss of their money.
Nonequilibrium Reaction Kinetics in Molecular Solids

We explore the possibility of nonstatistical chemical reactions in condensed-phase energetic materials via reactive molecular dynamics (MD) simulations. We characterize the response of nitromethane [CH3NO2], HMX [cyclic (CH2-NNO2)4], and PETN [C-(CH2-ONO2)4] to different types of insults: electric fields of various frequencies and strengths and direct heating at various rates. We find that nonequilibrium states can be created for short time scales when energy input targets specific vibrations through the electric fields and that equilibration eventually occurs even while the insults remain present. Interestingly, for strong fields these relaxation time scales are comparable to those of the initial chemical decomposition of the molecules. NM decomposes predominantly via bimolecular reactions, and while insults targeting specific modes lead to strong nonequilibrium states, they do not affect the kinetics associated with decomposition. PETN decomposes via the unimolecular formation of NO2 and, quite interest.
Characterization of the Nucleocytoplasmic Transport of the Cutaneous HPV8 E7 Protein

Characterization of the Nucleocytoplasmic Transport of the Cutaneous HPV8 E7 Protein Zeynep Onder Thesis Advisor: Prof. Junona Moroianu, Ph.D Some non melanoma skin cancers (NMSC) have been associated with human papillomavirus (HPV) pathogenesis, like epidermodysplasia verruciformis (EV) and squamous cell carcinoma (SCC) (3, 31, 34, 35, 102). EV is a genetically inherited skin disease that develops when the individuals are infected with cutaneous HPV types belonging to the β-genus, especially types 5 and 8 (3, 11, 30, 65). Transgenic mouse lineages expressing all early genes of cutaneous HPV8 develop papillomas, dysplasias and SCC after UV irradiation and this correlates with enhanced HPV8 oncogenes expression (3, 28, 80, 102). We have previously discovered that the nuclear localization of mucosal HPV16 E7 and HPV11 E7 proteins is mediated by their zinc-binding domain via a Randependent pathway and independent of nuclear import receptors and that a patch of hydrophobic residues within the zinc-binding domain of HPV16 E7 and HPV11 E7 proteins is responsible for their nuclear import via hydrophobic interactions with FG nucleoporins (5, 26, 43, 57, 75). Here we investigated the nucleocytoplasmic traffic of cutaneous HPV8 E7 protein using confocal microscopy to analyze the intracellular localization of EGFP-8E7, its subdomains and its mutants after transient transfections. We also investigated the nuclear import ability of GST-8E7, its subdomains and mutants using in vitro nuclear import assays in digitonin-permeabilized HeLa cells. In addition, we performed isolation assays to study the direct interaction between HPV8 E7 and two FG nucleoporins, Nup62 and Nup153 or the nuclear export receptor, CRM1. We found that the nuclear import of cutaneous HPV8 E7 is mediated by a nuclear localization signal (NLS) located within its zinc-binding domain. Furthermore, we determined that the hydrophobic residues within the 65LRLFV69 patch are responsible for the nuclear import and nuclear localization of HPV8 E7 via direct hydrophobic interactions with FG nucleoporins, Nup62 and Nup153, whereas the positively charged arginine 66 plays no significant role in the function of the NLS. In addition, we examined the nuclear export mechanism of cutaneous HPV8 E7 protein and showed that it has a leucine-rich nuclear export signal (NES) in its Cterminal domain that is recognized by the CRM1 nuclear export receptor. These studies are essential for understanding the nucleocytoplasmic traffic of cutaneous HPV8 E7 protein.
Nephroprotective effect of Bryophyllum pinnatum‐mediated silver nanoparticles in ethylene glycol‐induced urolithiasis in rat

Abstract A large population is suffering from multifactorial urolithiasis worldwide with a reoccurrence rate of almost 70%–80% in males and 47%–60% in females. In the present study, the nephroprotective effect of silver nanoparticles (AgNPs) synthesised by Bryophyllum pinnatum was evaluated in ethylene glycol‐induced urolithiasis in rat. B. pinnatum‐mediated AgNPs which were found to be spherical and polydispersed particles with an average size of 32.65 nm determined by transmission electron microscopy analysis, and showing an absorption peak at 432 nm by the UV‐Vis spectrophotometric analysis, revealing the role of hydroxyl group in the synthesis by Fourier Transformed Infrared Spectroscopy analysis, with a zeta potential value of −15.7 mV. The crystalline nature and fcc structure was demonstrated based on X‐ray diffraction analysis. Animal study was performed on 36 male Wistar rats divided into six equal groups, which demonstrated significant increase in serum total protein, albumin and globulin and significant decrease in AST, ALT, creatinine, BUN, calcium and phosphorus in group V and VI when compared with group II and IV. No crystalluria was observed in rats given B. pinnatum AgNPs. Histopathological observations in group V and VI showed mild degenerative changes and restoration or maintenance of kidney parenchyma when compared with group II and IV rats. Thus, the authors conclude with the beneficial preventive and therapeutic nephroprotective effect of B. pinnatum‐mediated AgNPs against ethylene glycol‐induced urolithiasis in rats.
Boosting EFL Learners Critical Thinking through Guided Discovery: a Classroom- Oriented Research on First-Year Master Students

Critical thinking is widely recognized as a necessary skill for growth and intellectual development due to a variety of factors, including globalization, the revolution of information technology, modernity, and connectivity. EFL teachers can lay the groundwork for their students to attain critical thinking through various methods, models, and strategies. The present investigation suggests that the teacher could promote EFL learners’ critical thinking through guided discovery model of instruction. Henceforth, the current paper endeavors to enlighten the adequacy of applying guided discovery for developing learners’ critical thinking skills. It is an experimental research that investigates: how may guided discovery contribute to the development of EFL learners’ critical thinking? It attempts to examine the utility of discovery learning in teaching students how to process and think critically about the education they receive where information has become readily available and accessible. To this aim, 40 EFL Master students who took educational psychology courses were nominated from the university center of Naama, Algeria. The researcher selected Peter Honey Critical Thinking test and focus group discussions to attain data on students’ critical thinking skills. The test results demonstrated that the experimental group outperformed the control group. The students become more autonomous, reflect on their learning experiences, and identify the most useful strategies. Furthermore, the analysis of focus group interviews revealed that the experimental group participants hold positive attitudes toward discovery learning. They perceive it as a precious method that can enhance their awareness about the value of thinking critically.
CFPU: A Cell-Free Processing Unit for High-Throughput, Automated In Vitro Circuit Characterization in Steady-State Conditions

Forward engineering synthetic circuits is at the core of synthetic biology. Automated solutions will be required to facilitate circuit design and implementation. Circuit design is increasingly being automated with design software, but innovations in experimental automation are lagging behind. Microfluidic technologies made it possible to perform in vitro transcription-translation (tx-tl) reactions with increasing throughput and sophistication, enabling screening and characterization of individual circuit elements and complete circuit designs. Here we developed an automated microfluidic cell-free processing unit (CFPU) that extends high-throughput screening capabilities to a continuous reaction environment, which is essential for the implementation and analysis of more complex and dynamic circuits. The CFPU contains 280 chemostats that can be individually programmed with DNA circuits. Each chemostat is periodically supplied with tx-tl reagents, giving rise to sustained, long-term steady state conditions. Using microfluidic pulse width modulation (PWM) the device is able to generate tx-tl reagent compositions in real-time. The device has higher throughput, lower reagent consumption, and overall higher functionality than current chemostat devices. We applied this technology to map transcription factor based repression under equilibrium conditions and implemented dynamic gene circuits switchable by small molecules. We expect the CFPU to help bridge the gap between circuit design and experimental automation for in vitro development of synthetic gene circuits.
Comorbidity rates of Posttraumatic Stress Disorder in dementia: a systematic literature review

ABSTRACT Background: Post Traumatic Stress Disorder (PTSD) has been described as an independent risk factor for cognitive decline and dementia. At the same time, cognitive deterioration and increased loss experiences in dementia may increase liability for the reactivation of traumatic memories and thereby PTSD symptoms. Objective: In order to investigate co-occurrence of PTSD in dementia this systematic literature review summarizes all the available evidence on reported comorbidity rates of PTSD in patients with dementia. Method: PubMed, Embase, PsycINFO and CINAHL were searched for potential publications investigating the co-occurrence of PTSD in dementia until 25 November 2019. Cohort and cross-sectional studies were included. To assure current comorbidity of PTSD in dementia, only publications with a recent PTSD diagnosis (<2 years before onset of dementia) were selected. Results: Of the 860 identified abstracts, three studies (0.35%) met the eligibility criteria and were included. These three studies concerned only military veteran populations, and they comprised two cross-sectional cohort studies and one prospective cohort study. The estimated comorbidity rate of PTSD in veterans with dementia varied between 4.7% and 7.8%. Conclusions: The limited research available shows comorbidity rates only in military veterans, which were possibly dependent on investigated population with respect to dementia severity and possibly associated behavioural and psychiatric symptoms of dementia (BPSD). In dementia patients the comorbidity with PTSD may be high and we suggest that worldwide the impact of PTSD in dementia is high and probably underestimated. Research and care on this topic should improve urgently with the current expanding prevalence of dementia. A first step to improve quality of dementia research and care would be to develop a structured tool to diagnose PTSD in these patients.
A Deep Learning Model for the Thermospheric Nitric Oxide Emission

Nitric oxide (NO) infrared radiation is an essential cooling source for the thermosphere, especially during and after geomagnetic storms. An accurate representation of the three‐dimension (3‐D) morphology of NO emission in models is critical for predicting the thermosphere state. Recently, the deep‐learning neural network has been widely used in space weather prediction and forecast. Given that the 3‐D image of NO emission from the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) onboard the Thermosphere Ionosphere Energetics and Dynamics satellite contains a large amount of missing data which is unobserved, a context loss function is applied to extract the features from the incomplete SABER NO emission images. A 3‐D NO emission model (referred to as NOE3D) that is based on the convolutional neural network with a context loss function is developed to estimate the 3‐D distribution of NO emission. NOE3D can effectively extract features from incomplete SABER 3‐D images. Additionally, NOE3D has excellent performance not only for the training datasets but also for the test datasets. The NO emission climate variations associated with solar activities have been well reproduced by NOE3D. The comparison results suggest that NOE3D has better capability in predicting the NO emission than the Thermosphere‐Ionosphere Electrodynamics General Circulation Model. More importantly, NOE3D is capable of providing the variations of NO emission during extremely disturbed times.
Disease ecology of wild fish: opportunities and challenges for linking infection metrics with behaviour, condition, and survival

Surmounting evidence supports that infectious agents play a critical role in shaping fish physiology, behaviour, and survival. The exclusion of disease-causing agents from fisheries research has resulted in major knowledge gaps that may limit the predictive capacity of ecological models. A major barrier in wild fisheries epidemiology is the logistical constraints associated with observing disease and obtaining samples from free-ranging fish, restricting the vast majority of research to laboratory studies or aquaculture facilities. For fisheries ecologists, including infectious agents can provide greater insight into observed phenomena, particularly with respect to fish physiology (e.g., metabolism), movement (e.g., migration rates), behaviour (e.g., habitat selection), personality (e.g., bold versus shy), and survival. Here we provide a brief introduction to the current understanding of disease ecology in wild fish and describe technological advances in both epidemiology and fisheries and aquatic sciences that can be used in tandem to create comprehensive studies of disease ecology in wild fishes. Combining nonlethal sampling and molecular genetic-based identification methods with field studies creates vast opportunities for innovative study designs that have the potential to address the true complexity of aquatic ecosystems.
Autocorrelation of the Ground Vibrations Recorded by the SEIS‐InSight Seismometer on Mars

Since early February 2019, the SEIS (Seismic Experiment for Interior Structure) seismometer deployed at the surface of Mars in the framework of the InSight mission has been continuously recording the ground motion at Elysium Planitia. In this study, we take advantage of this exceptional data set to put constraints on the crustal properties of Mars using seismic interferometry (SI). To carry out this task, we first examine the continuous records from the very broadband seismometer. Several deterministic sources of environmental noise are identified and specific preprocessing strategies are presented to mitigate their influence. Applying the principles of SI to the single‐station configuration of InSight, we compute, for each Sol and each hour of the martian day, the diagonal elements of the time‐domain correlation tensor of random ambient vibrations recorded by SEIS. A similar computation is performed on the diffuse waveforms generated by more than a hundred Marsquakes. A careful signal‐to‐noise ratio analysis and an inter‐comparison between the two datasets suggest that the results from SI are most reliable in a narrow frequency band around 2.4 Hz, where an amplification of both ambient vibrations and seismic events is observed. The average autocorrelation functions (ACFs) contain well identifiable seismic arrivals, that are very consistent between the two datasets. Interpreting the vertical and horizontal ACFs as, respectively, the P‐ and S‐ seismic reflectivity below InSight, we propose a simple stratified velocity model of the crust, which is mostly compatible with previous results from receiver function analysis. Our results are discussed and compared to recent works from the literature.
Structural multi-objective topology optimization and application based on the criteria importance through intercriteria correlation method

A structural multi-objective topology optimization method integrating the solid isotropic material with penalization (SIMP) approach, compromise programming method and criteria importance through intercriteria correlation (CRITIC) method is proposed. The SIMP approach performs topology optimization. The compromise programming method builds a comprehensive objective function to handle the multi-objective optimization. The CRITIC method, which reflects the contrast intensity and conflicting character of objectives, is applied to determine the weight coefficients of objectives. The conceptual design of a vehicle shock tower is taken as a numerical example. Comparison of the original design and the optimized conceptual design indicates that the stiffness and frequency performance of the shock tower clearly improve as the total weight reduces. Meanwhile, comparison of the weight coefficients and corresponding optimization results produced by the subjective method, CRITIC method, grey comprehensive relational analysis and entropy weight method proves that the CRITIC method is feasible and superior in structural multi-objective topology optimization.
Study of Markers for Assessment of Insulin Resistance in Obese Children and Adolescents

Background: Valid and reliable methods are essential to assess the presence and the extent of insulin resistance, the associated risk factors and the effect of pharmacological and lifestyle interventions. The aim of this work was to evaluate Homeostatic model assessment of insulin resistance (HOMA-IR) for assessment of insulin resistance among obese children and adolescents. Methods: This case control study included 40 children and adolescent with ages of 6 to 16 years who were classified into: Group I: 20 obese children and adolescents (body mass index (BMI) > 95th percentile on Egyptian growth curves and Group II: 20 healthy children as a control group of matched age and sex to group 1 and who had normal BMI. All subjects underwent 1) Thorough history taking 2) Full clinical examination 3) Laboratory investigations: Fasting blood glucose, Fasting serum insulin level, HOMA-IR, HbA1c.and OGTT. Results: There is no significant statistical difference as regard age, height, sex and puberty staging in both groups. The mean for weight, BMI, waist circumference, hip circumference, waist/hip ratio and acanthosis nigricans were found to be significantly higher in patient group. FBG, fasting serum insulin, HbA1c and HOMA-IR were significantly higher in patient group than in control group (p <0.001). HOMA-IR was significantly correlated with HbA1c and OGTT in obese patients (p<0.001*). Original Research Article Shall et al.; JAMMR, 33(4): 89-95, 2021; Article no.JAMMR. 66407 90 Conclusions: HOMA-IR can be used in assessment of insulin resistance among obese children and adolescents.