Miracle-dz/UniFAR-FTUs huggingface dataset:
Health Belief of Elderly Women as Predictor of Health-Seeking Behavior to Breast Cancer Prevention in Kauru Local Government Area of Kaduna State, Nigeria

The study investigates the health belief of older women as predictors of health-seeking behaviors to breast cancer prevention in Kauru Local Government Area of Kaduna State. The study employed a descriptive cross-sectional survey. A Multi-stage sampling technique was used to select 394 elderly women in Kauru Local Government Area of Kaduna State. The demographic information and research question were analyzed using descriptive statistics while the research hypotheses were analyzed using Pearson Product Moment Correlation and Linear regression at 0.05 level of significance. The results showed 41.6% of the elderly women had average knowledge of breast cancer prevention, 46.7% high level of susceptibility to breast cancer, 35.5% perceived severity, 39.3% perceived barriers, 39.8% perceived benefits. There was a significant relationship between the health belief and behavioral skills on breast cancer prevention (r= 0.881, p< 0.05). The most significant predictors of breast cancer prevention among the Elderly women is perceived severity (ß = 0.157; t =2.543; p < 0.05). Next in terms of magnitude of predictor is perceived susceptibility (ß = 0.114; t = 2.542; p < 0.05), perceived benefits (ß = 0.127, t =1.139; p < 0.05) and perceived barriers (ß = 0.112, t =1.533; p < 0.05). Hence, the four health belief variables had significant contribution to breast cancer prevention. The study recommends that, government and non-governmental health agencies scale-up campaigns specifically tailored to change negative attitudinal barriers as well encourage Brest Self-Examination among women in the northern region of Nigeria. Healthy lifestyle is the best form of prevention of breast cancer prevention among women.
DATA-EFFICIENT REINFORCEMENT LEARNING

Data efficiency poses a major challenge for deep reinforcement learning. We approach this issue from the perspective of self-supervised representation learning, leveraging reward-free exploratory data to pretrain encoder networks. We employ a novel combination of latent dynamics modelling and goal-reaching objectives, which exploit the inherent structure of data in reinforcement learning. We demonstrate that our method scales well with network capacity and pretraining data. When evaluated on the Atari 100k data-efficiency benchmark, our approach significantly outperforms previous methods combining unsupervised pretraining with task-specific finetuning, and approaches human-level performance.
Test and Development of Pharmaceutical Pictorials

This study tests the comprehension ofa set of pharmaceutical pictorials from the U.S. Pharmacopoeia Convention. This research also documents the relatively unexplored area of pictorial redesign. Concepts not well communicated by the original pictorials were reworked with data collected from error analyses of participants' answers and drawings generated from focus group participants. Several redesigned pictorials have been developed for further testing. A set of preliminary guidelines for redesigning pictorials is offered.
A Survey of Computational Offloading in Cloud/Edge-based Architectures: Strategies, Optimization Models and Challenges

In recent years, mobile devices have become an essential part of daily life. More and more applications are being supported by mobile devices thanks to edge computing, which represents an emergent architecture that provides computing, storage, and networking capabilities for mobile devices. In edge computing, heavy tasks are offloaded to edge nodes to alleviate the computations on the mobile side. However, offloading computational tasks may incur extra energy consumption and delays due to network congestion and server queues. Therefore, it is necessary to optimize offloading decisions to minimize time, energy, and payment costs. In this article, different offloading models are examined to identify the offloading parameters that need to be optimized. The paper investigates and compares several optimization techniques used to optimize offloading decisions, specifically Swarm Intelligence (SI) models, since they are best suited to the distributed aspect of edge computing. Furthermore, based on the literature review, this study concludes that a Cuckoo Search Algorithm (CSA) in an edge-based architecture is a good solution for balancing energy consumption, time, and cost.
Liquid-Liquid Equilibrium Data for Fatty Systems Containing Monoacylglycerols and Diacylglycerols

Edible oils can be deacidified by solvent extraction, and the comprehension of liquid–liquid equilibrium is essential to the design process. Thus, this study aims to determine the data of liquid–liquid equilibrium for the fatty systems containing triacylglycerols (TAG) of refined oils (soybean, cottonseed, and rice bran) + commercial fatty acid (linoleic and oleic) + diacylglycerols (DAG) of commercial mixture of mono- and diacylglycerols + monoacylglycerols (MAG) of commercial mixture of mono- and diacylglycerols + anhydrous ethanol at different temperatures (303.15 K and 318.15 K). The high performance size exclusion chromatography (HPSEC) method was used for quantification of all components: TAG, DAG, MAG, fatty acids, and ethanol in both phases in equilibrium. The preference of fatty acids to solvent phase is consistent to previously reported data in literature. The mass fraction of MAG was more than 2 times greater in the solvent phase, and the DAG concentration is higher in the oil phase. The averag.
Term Structure of Equity and Bond Yields over Business Cycles

Recent findings on the term structure of equity and bond yields pose serious challenges to existing equilibrium asset pricing models. This paper presents a new equilibrium model to explain the joint historical dynamics of equity and bond yields (and their yield spreads). Equity/bond yields movements are mainly driven by subjective dividend/GDP growth expectation. Yields on short-term dividend claims are more volatile because the short-term dividend growth expectation is mean-reverting to its less volatile long-run counterpart. The procyclical slopes of spot and forward equity yields are due to the counter-cyclical slope of dividend growth expectations. Returns on long-term dividend claims have higher volatilities and co-move more strongly with the market, because of stronger belief revisions over long-term dividend growth. The correlation between equity returns/yields and nominal bond returns/yields switched from positive to negative after the late 1990s, owing to (1) procyclical inflation and (2) higher correlation between expectations of real GDP and of real dividend growth post-2000. The model is also consistent with the data in generating persistent and volatile price-dividend ratios, excess return volatility, and return predictability.
Towards a better understanding of the neuro-developmental role of autophagy in sickness and in health

Autophagy is a critical cellular process by which biomolecules and cellular organelles are degraded in an orderly manner inside lysosomes. This process is particularly important in neurons: these post-mitotic cells cannot divide or be easily replaced and are therefore especially sensitive to the accumulation of toxic proteins and damaged organelles. Dysregulation of neuronal autophagy is well documented in a range of neurodegenerative diseases. However, growing evidence indicates that autophagy also critically contributes to neurodevelopmental cellular processes, including neurogenesis, maintenance of neural stem cell homeostasis, differentiation, metabolic reprogramming, and synaptic remodelling. These findings implicate autophagy in neurodevelopmental disorders. In this review we discuss the current understanding of the role of autophagy in neurodevelopment and neurodevelopmental disorders, as well as currently available tools and techniques that can be used to further investigate this association.
Mean–variance optimization of discrete time discounted Markov decision processes

In this paper, we study a mean–variance optimization problem in an infinite horizon discrete time discounted Markov decision process (MDP). The objective is to minimize the variance of system rewards with the constraint ofmean performance. Different frommost ofworks in the literaturewhich require the mean performance already achieve optimum, we can let the discounted performance equal any constant. The difficulty of this problem is caused by the quadratic form of the variance function which makes the variance minimization problem not a standard MDP. By proving the decomposable structure of the feasible policy space, we transform this constrained variance minimization problem to an equivalent unconstrained MDP under a new discounted criterion and a new reward function. The difference of the variances of Markov chains under any two feasible policies is quantified by a difference formula. Based on the variance difference formula, a policy iteration algorithm is developed to find the optimal policy. We also prove the optimality of deterministic policy over the randomized policy generated in the meanconstrained policy space. Numerical experiments demonstrate the effectiveness of our approach. © 2017 Elsevier Ltd. All rights reserved.
Factors Affecting Digital Marketing in Tourism: An Empirical Analysis of the Nepal Tourism Sector

The goal of this analysis is to examine the various factors influencing the adoption of digital marketing (E-Marketing) by the tourism industry in Nepal. The research validates a methodological framework for the application of TAM and IDT models to clarify E-marketing acceptance using a qualitative methodology in which information is gathered on the basis of a survey method by questionnaires to answer various rates of the study. Advanced statistical methods and Structural equation models were used to examine the data collected. The results showed that the internal and external influences of the Nepalese tourism institutions have a significant impact on the implementation of E-Marketing by these organizations. Similarly, the results have verified that IT hypotheses (that is, TAM and IDT) are true in the example of e-Marketing adoption by the tourism sector in Nepal. The findings highlight the relevance of environmental conditions for the implementation of E-Marketing and contribute to the extremely limited number of empirical studies that have been performed to examine the acceptance of E-Marketing in emerging markets.
A Cascade Structure of Damped-SOGI to Identify Multimode Low-Frequency Oscillations

The on-line estimation of low-frequency oscillations in an interconnected power system has attracted much attention as this provides vital information about the stability condition of the power system. In this paper, a measurement-based structure for estimation of the frequency, magnitude, and damping of multimode oscillations is proposed. The method can be applied to the Phasor Measurement Unit (PMU) to extract further information about the power system. The proposed method is derived by applying modifications to the parallel structure of an existing method called Damped Second Order Generalized Integrator (DampedSOGI). The paper details the proposed cascade structure and presents simulation results to confirm the analytical derivations and the desired performance of the proposed method.
Clinical evaluation and nasoendoscopic scores of patients with chronic rhinosinusitis in Ilorin, Nigeria

Introduction chronic rhinosinusitis (CRS) is characterised by inflammation of the mucosal lining of the nose and paranasal sinuses for at least 12 weeks duration. Other than the diagnostic criteria that is based on clinical features; nasoendoscopy and/or computerized tomographic scan have been included in the diagnosis. This study seeks to outline the clinical evaluation and nasoendoscopic assessment of CRS patients. Methods a hospital-based analytical study carried out on 154 participants. Clinical assessment and nasoendoscopy were performed and scored according to the discharge, inflammation and polyps/oedema (DIP) scale. Statistical analysis was carried out and results were presented in charts and tables. Results of the 154 participants, 71 (46.1%) were males and 83 (53.9%) females with a male to female ratio of 1: 1.7. Nasal discharge and blockage were the commonest symptoms. Nasoendoscopy had higher yield in the examination of intranasal polyps (NPs) over anterior rhinoscopy. The prevalence of NPs was 26.6%. The result of DIP nasoendoscopic findings revealed more participants with moderate scores. There was a significant statistical difference between the presence of NPs on nasoendoscopy and DIP score. Conclusion nasoendoscopy is an important aspect in the diagnosis and evaluation of patients with CRS. It provides a better visualization of NPs; therefore, it should be made routine in the clinical assessment and treatment of patients with CRS. The nasal endoscopic scoring of CRS should be considered as a common practice in clinical setting as well.
Classification of MRI Images: A Review

With the rapid development of the medical science more and more medical images are generated rapidly like OMR, CT scan, X-ray etc. Due to that an efficient system is essential for the indexing, storing and analyzing such images. The analyzing cost of such images is very high. The analysis quality also differs and highly prone to errors. The classification of such images is a quite harder job. Hence it is essential to develop a strong system for classification of such images. In this paper we are presenting some techniques that are used to classify the X-ray images. Keywords— image classification, medical images, X-ray, medical image databases. ——————————  ——————————
6.06 Lithosphere Stress and Deformation

The advent of plate tectonics brought a new meaning and understanding to the mechanically defined lithosphere. Lithosphere became synonymous with the Earth’s outer thermal boundary, the mobile ‘plates’ of plate tectonics. Motion of the plates was soon understood to be the result of a balance of forces that both drove and resisted their movement. While convection in the Earth is the ultimate source of the energy to drive plate tectonics, large density inhomogeneities associated with plate subduction and generation of new oceanic lithosphere create the major driving forces. Other potentially important forces include viscous drag at the base of plates (either driving or resisting) as well as frictional resistance along plate boundaries. Lithospheric deformation, the ‘tectonics’ of plate tectonics, is a result of the stress state within the lithosphere. In this chapter we review the evidence for, and the implications of, field and laboratory data on the state of stress in the lithosphere and the forces acting upon and within it. Intensive investigation over the past few decades has revealed that the lithospheric state of stress is remarkably uniform both with depth and over vast regions of plate interiors. The broad uniformity of observed stress orientations and relative magnitudes, even across major bends in old orogenic belts, indicates that the lithospheric stress field is the result of present-day forces and is not due to residual stresses from past tectonic activity. Modeling has shown us that the same forces acting on and within the plates to drive plate motion are the same forces responsible for the state of stress in the lithosphere. Direct measurement of stress magnitudes at depth confirms a simple model in which stress differences in the crust are close to and limited by the frictional strength of the most well-oriented faults. In contrast to the relative uniformity of intraplate stress fields, deformation rates in plate interiors vary by about eight orders of magnitude. We show how knowledge of the stress field, combined with mechanical, thermal, and rheological properties, can be used to constrain both the rate and style of lithospheric deformational processes.
Polyurethane Binder for Aqueous Processing of Li-Ion Battery Electrodes

In this manuscript the investigation of the heat-curable polyurethane (PU)/carboxymethyl cellulose (CMC) mixture as binder for Li-ion battery electrodes is reported. The experimental results demonstrate the outstanding thermal and electrochemical stability of PU, as well as the good electrochemical performance of cathode (NMC) and anode (graphite) electrodes in which PU is used as binder. The most important ﬁnding is the ability of PU to prevent current collector corrosion usually occurring when an aqueous dispersion (slurry) of NMC is coated on aluminum foils. SEM investigation shows that PU encapsulates the positive active material particles preventing a pH raise in the slurry. Finally, the cycling performance of PU/CMC based anodes and cathodes are tested in half as well as full lithium-ion cell setups. the
Joint Monitoring of Process Mean and Variance Using Exponentially Weighted Moving Average Control Charts

The performances of control-charting schemes for thejoint monitoring of a process mean and a variance are evaluated and compared. Certain schemes are shown to be inadequate for this purpose, and the potential risk of using these schemes alone is discussed. A combined scheme consisting of a two-sided exponentially weighted moving average (EWMA) mean chart and a two-sided EWMA variance chart is found to perform well under several types of out-of-control situations. A simple method is provided for approximating the average run length and the percentage points of a run-length distribution of a combined EWMA scheme. A simple procedure is also proposed for the design of a combined EWMA scheme.
CHARTER: heatmap-based multi-type chart data extraction

The digital conversion of information stored in documents is a great source of knowledge. In contrast to the documents text, the conversion of the embedded documents graphics, such as charts and plots, has been much less explored. We present a method and a system for end-to-end conversion of document charts into machine readable tabular data format, which can be easily stored and analyzed in the digital domain. Our approach extracts and analyses charts along with their graphical elements and supporting structures such as legends, axes, titles, and captions. Our detection system is based on neural networks, trained solely on synthetic data, eliminating the limiting factor of data collection. As opposed to previous methods, which detect graphical elements using bounding-boxes, our networks feature auxiliary domain specific heatmaps prediction enabling the precise detection of pie charts, line and scatter plots which do not fit the rectangular bounding-box presumption. Qualitative and quantitative results show high robustness and precision, improving upon previous works on popular benchmarks
Impact of Graft Size Matching on the Early Post-Transplant Complications and Patients Survival in Children after Living Donor Liver Transplantations

We aimed to assess the impact of the graft-recipient weight ratio (GRWR) on early post-transplant complications and patient survival rates in children after living donor liver transplantation (LDLT). We retrospectively analyzed 321 patients who underwent LDLT from 2004 to 2019. The recipients were categorized into four groups: 37 patients had a GRWR ≤ 1.5% (Group A), 196 patients had a GRWR > 1.5% and ≤3.5% (Group B), 73 patients had a GRWR > 3.5% and <5% (Group C) and 15 patients had a GRWR ≥ 5% (Group D). Incidence of early surgical complications including vascular complications, biliary complications, postoperative bleedings, gastrointestinal perforations and graft loss were comparable among groups with a different GRWR. Delayed abdominal wound closure was more common in patients with a GRWR > 3.5%. Recipients with a GRWR < 5% had a significantly better prognosis concerning patients and graft survival. Using grafts with a GRWR < 5% allows us to expand the donor pool and decrease the risk of mortality while on the waiting list, when patients at the time of transplantation have less advanced liver disease. LDLT with a GRWR ≥ 5% is related to a higher risk of poor outcome, and thus should be an option for treating selected patients when the risk of a delayed transplantation is high and access to deceased donors is limited.
Postoperative analgesic effect of intraoperative loading dose of morphine in caesarean section

Objective: evaluate the effect of intraoperative morphine intravenous (IV) in addition to tramadol and NSAIDs on post-operative analgesia in cesarean sections. Methods: This is a prospective comparative study done at Baghdad teaching hospital & nursing house at medical city complex from January 2017 to January 2018, including 100 patients scheduled for elective cesarean section. Patients are divided into two groups, one group receives morphine intraoperatively, and the other group is control group. Postoperative pain was assessed at specific time interval using numerical analogue scale. Results: Effect of morphine on pain score at awakening and after 15 minutes show significant difference otherwise no significant difference in the later 16 hours. Time of recovery is significantly ANALYSIS 24(105), September October, 2020 Medical Science ISSN 2321–7359 EISSN 2321–7367
Genotype by Environment Interaction and Grain Yield Stability Analysis of Advanced TEF Genotypes for High Potential TEF Growing Areas of Ethiopia

Tef [ Eragrostis tef (Zucc.)Trotter]) is one of the most important cereal crops grown in Ethiopia; the first crop in terms of acreage, however, its production has been partly constrained by low grain yield and less stability of the released tef genotypes under cultivation. This study was conducted to estimate the extent of genotype by environment interactions and stability in tef genotypes in the highlands of Ethiopia. Eighteen promising recombinant inbred lines plus a standard and local check variety were evaluated at six environments under rain-fed conditions using the randomized complete block design with four replications. AMMI analysis showed that tef grain yield was highly significantly (p < 0.001) affected by environments (E), genotypes (G), and genotype × environment interaction (GEI) indicating the presence of genetic variation and possible selection of stable entries. Thus, 50.6% of the total sum of squares was justified by environmental fluctuations showing that the environments were diverse to cause large variation in grain yield across test locations. GEI was further partitioned by principal component analysis and the first two multiplicative axis terms (PCA1, and PCA2) explained 45.5% and 20.7% (66.2%) of GEI sum of squares, respectively. The mean grain yield value of tested genotypes averaged over environments indicated that G4 (HO-TF-1486 x DZ-01-2787(RIL No. 173) had the highest grain yield of 2827 kg ha -1 compared to the standard check variety Negus with 2565 kg ha -1 grain yield. In addition, this candidate variety proved stable across environments for grain yield during the varietal evaluation experiment. This genotype, therefore, will be verified and evaluated by the national variety release committee in 2021/22 main cropping season for approval and release for high potential tef growing environments to increase tef production and productivity.
The prognostic value of B-catenin, CD10 and p63 Immunohistochemical expression in urothelial carcinoma

Background: Detection of high-grade urothelial carcinoma is important for modification of therapy and improving the prognosis. We studied the prognostic value of β-catenin, CD10 and p63 immunohistochemical expression in urothelial carcinoma and correlated this expression with the tumor grade and stage to evaluate the prognostic value of those commonly used markers. Material and Methods: Eighty four cases of urinary bladder urothelial carcinoma were obtained from the pathology archive and reexamined ANALYSIS 24(105), September October, 2020 Medical Science ISSN 2321–7359 EISSN 2321–7367