Miracle-dz/UniFAR-FTUs huggingface dataset:
Nurses' Knowledge and Skills regarding Oxygen Administration Methods at Pediatric Teaching Hospitals in Mosul City

Objective: To assess knowledge and skills level regarding oxygen administration methods at pediatric teaching hospitals in Mosul City.Methodology: A descriptive study was applied at pediatric teaching hospitals (Al-Kansaa, and Ibn Al-Atheer) in Mosul City from 8 of October / 2018 till 29 of May / 2019. The selection of the sample was non- probability (Purposive). This sample involved of (52) nurses. The questionnaire was constructed which consists of three parts and provided for nurses. The questionnaire validity was carried out through a panel of experts. To evaluate statistically the reliability of instruments, the pilot study was applied through period from 20– till –31 of January / 2019. Non-randomly (6) nurses from Ibn Sina teaching hospitals, the correlation of Pearson's coefficient result are (r= 0.798) and are significant at p ≤ 0.05 level was used to approximation the scale (test – retest) by using SPSS version 25. The Result show statistical knowledge and skills results for nurse's in concerning the oxygen administration methods for pediatric, that knowledge results are 84.6% (44) of them at not acceptable level, and the skills results are 65.4 % (34) of them also at not acceptable level. There are not significant relationships between the knowledge, skills results and all the demographic variables except the skills results with training courses only there are significant relationships at p≤ 0.05. Recommendations: Training course and workshops for nurses of teaching hospitals regarding oxygen administration methods
Association of Biochemical and Hematological Parameters With Enteric Fever Infection at the Dschang Regional Annex Hospital, Cameroon: A Cross-Sectional Study

Background Enteric fever is a systemic infection in humans caused by the Gram-negative bacilliSalmonella enterica serovars Typhi and Paratyphi. Although the diagnosis typically involves the isolation of Salmonella enterica serovars, it is often determined based on laboratory findings and clinical observations. However, due to the wide variety and the non-specific character of clinical features, making a definitive diagnosis presents numerous challenges. Therefore, the aim of this study was to find the predictive hematological and biochemical parameters which would serve in the diagnosis, prognosis, and treatment of typhoid fever cases. Methodology A cross-sectional study was conducted from November 2020 to September 2021 on1076consented volunteerparticipants. Stool culture and identification tests enabled us to distinguish three groups including 423 Salmonella Typhi positive patients, 115 S. Paratyphi positive patients, and 538 Salmonella negative participants. Biochemical and hematological parameters were evaluated using standard methods from commercial kits and Sysmex KX-21N automated hematology analyzer, respectively. A multiple logistic regression analysis was performed to identify the validity of the hematological and biochemical characteristics for enteric fever diagnosis. Results Multiple logistic regression showed hyper creatininemia, hypoalbuminemia, hyper total proteinemia, hyper alkaline phosphatase (ALP), hyper alanine aminotransferase (ALT), hyper total bilirubinemia, hyper conjugated bilirubinemia, hyper triglyceridemia, hyper C-reactive protein (CRP), leukopenia, thrombocytopenia, lymphopenia, monocytopenia, low hemoglobin, low hematocrit, low mean corpuscular volume (MCV), low mean corpuscular hemoglobin (MCH), low platelet, low platelet crit level, high platelet distribution width (PDW) level, high erythrocyte sedimentation rate 1 (ESR1) level as significant biological abnormalities associated (odds ratio {OR} > 1; p < 0.05) with enteric fever infection. Similarly, hyper ESR2 was an independent predictor (OR > 1; p < 0.05) of S. Typhi infection. However, a negative and significant association (OR < 1; p < 0.05) was recorded between enteric fever infection and high mean platelet volume (MPV). Conclusion Overall the results of the biochemical and hematological profiles can serve as potential diagnostic markers for typhoid fever. These markers can also be useful in the appropriate management of those with enteric fever, preventing severity and limiting outcomes of mortality.
The Impact of Loneliness and Social Isolation on Cognitive Aging: A Narrative Review

Social concepts such as loneliness and social isolation are fairly new factors that have been recently gaining attention as to their involvement in changes in cognitive function and association with dementia. The primary aim of this narrative review was to describe the current understanding of how loneliness and social isolation influence cognitive aging and how they are linked to dementia. Studies have shown that there is an association between loneliness, social isolation, and reduced cognitive function, in older adults, across multiple cognitive domains, as well as a heightened risk of dementia. Numerous changes to underlying neural biomechanisms including cortisol secretion and brain volume alterations (e.g., white/grey matter, hippocampus) may contribute to these relationships. However, due to poor quality research, mixed and inconclusive findings, and issues accurately defining and measuring loneliness and social isolation, more consistent high-quality interventions are needed to determine whether studies addressing loneliness and social isolation can impact longer term risk of dementia. This is especially important given the long-term impact of the COVID-19 pandemic on social isolation in older people is yet to be fully understood.
Understanding the effect of measurement error on quantile regressions

The impact of measurement error in explanatory variables on quantile regression functions is investigated using a small variance approximation. The approximation shows how the error contaminated and error free quantile regression functions are related. A key factor is the distribution of the error free explanatory variable. Exact calculations probe the accuracy of the approximation. The order of the approximation error is unchanged if the density of the error free explanatory variable is replaced by the density of the error contaminated explanatory variable which is easily estimated. It is then possible to use the approximation to investigate the sensitivity of estimates to varying amounts of measurement error.
The influence of script-type cooperative learning model on student learning activities

This study aimed to determine the effect of the learning model Cooperative Type Script Against Student Learning Activities. The method used in this study is an experimental research method using a research design experiment that aims to determine the difference in the increase in student learning activities who learn to use the Learning Model Cooperative Type Script (experimental class) with students who do not use conventional learning models (control class) in economics subjects, observations are used to see teacher activities and. This study's results indicate differences in student learning activities between the experimental class and the control class after doing the treatment. The experimental class uses a script-type cooperative learning model, and the control class uses a conventional method. This is shown in the results of the analysis. It can be seen that the value of tcount is greater than ttable or 2.717 2.002. This is following the Asymp. Sig. value of 0.009 which is less than the value of 0.05. So there are differences in student learning activities after treatment in the experimental and control classes.
Fitness distributions in spatial populations undergoing clonal interference

Competition between independently arising beneficial mutations is enhanced in spatial populations due to the linear rather than exponential growth of the clones. Recent theoretical studies have pointed out that the resulting fitness dynamics is analogous to a surface growth process, where new layers nucleate and spread stochastically, leading to the build up of scale-invariant roughness. This scenario differs qualitatively from the standard view of adaptation in that the speed of adaptation becomes independent of population size while the fitness variance does not, in apparent violation of Fisher’s fundamental theorem. Here we exploit recent progress in the understanding of surface growth processes to obtain precise predictions for the universal, non-Gaussian shape of the fitness distribution for one-dimensional habitats, which are verified by simulations.
Matrix Partitions of Graphs: Algorithms and Complexity

Recently, there has been much interest in studying certain graph partitions that generalize graph colourings and homomorphisms. They are described by a pattern, usually viewed as a symmetric {0, 1, ∗}-matrix M . Existing results focus on recognition algorithms and characterization theorems for graphs that admit such M -partitions, or M -partitions in which vertices of the input graph G have lists of admissible parts. For (homomorphism) problems with costs, researchers have also investigated the approximability of the problem. In this thesis, we study the complexity of these matrix partition problems. First, we investigate the complexity of counting M -partitions. The complexity of counting problems for graph colourings and graph homomorphisms has been previously classified, and most turned out to be # P-complete, with only trivial exceptions. By contrast, we exhibit many M -partition problems with interesting non-trivial counting algorithms; moreover these algorithms appear to depend on highly combinatorial tools. In fact, our tools are sufficient to classify the complexity of counting M -partitions for all matrices M of size less than four. Then, we turn our attention to the homomorphism problems with costs. Previous results include partial classification of approximation complexity for doubly convex bipartite graphs. We complete these results and extend them to all digraphs. We prove that if H is a cocircular arc bigraph, then the minimum cost graph homomorphism problem to H admits a polynomial time constant ratio approximation algorithm. This solves a problem posed in an earlier paper. Our algorithm is obtained by derandomizing a two-phase randomized procedure. In the final third of the thesis, we present a partial dichotomy for the complexity of exact minimization of homomorphism costs, when the cost function is a constant across the vertices of the input graph. We show that the dichotomy is complete when the target graph is a tree.
A Case of Primary Lymphoepithelioma-Like Carcinoma of the Bladder With Review

Lymphoepithelioma-like carcinoma (LELC) was characterized by epithelial neoplastic cells developing in solid or incohesive sheets mixed with a noticeable lymphoid infiltration. Lymphoepithelioma-like carcinoma of the bladder (LELCB), which was first described by Zukerberg, is a rare variant of LELC. Here we reported a new case of LELCB occurring in a 70-year-old woman presenting with hematuria. Computed tomography (CT) and cystoscopy revealed a tumor on the left upper wall of the bladder. A partial cystectomy was finally performed. Pathological and immunohistochemical analysis revealed LELCB. After receiving systemic adjuvant chemotherapy, the patient conducted a 25-month follow-up without experiencing a recurrence.
Mathematical modeling and numerical methods for non-classical transport in correlated media

In this work, we investigate a new and non-classical linear transport equation for the transport of particles in correlated background media. We derive a time-dependent non-classical transport equation that is capable of reproducing arbitrary path length distributions, in contrast to the classical theory. This equation governs the distribution function of a microscopic particle game in the Boltzmann-Grad limit. This rigorous mathematical derivation is based on recent results on the periodic Lorentz gas, and it relies on an analytic expression for the distribution of free path lengths in the limit. The resulting equation has the distance s to the next collision as an additional independent variable, which makes it non-classical . A Monte-Carlo study of path length distributions in homogeneous but correlated media suggests that this equation is valid for a wider class of spatially correlated media. We discuss generalizations of the resulting equation, as well as the connection to another recently proposed non-classical steady state transport equation. In the following, we develop numerical methods for this non-classical steady state transport equation. Therefore, we investigate a variation of a standard nite volume HLL method for moment models of this equation. In a detailed numerical analysis we show that these schemes preserve the analytic asymptotic limit in a di usive scaling. Furthermore, the schemes preserve the convex set of admissible and realizable sets. A coupling of the initial value and the full solution strongly suggests to use an iterative solution method. The naive source iteration method is shown to become arbitrarily slow in the scattering dominated regime, therefore we adapt a Di usion Synthetic Acceleration method for the classical equation based on the di usion approximation for the non-classical equation. We investigate the contraction rates via a von Neumann analysis of the full equation and the corresponding moment models, which shows that they are signi cantly decreased by the acceleration method. Equipped with accurate and e cient numerical schemes, we present a method for the solution of inverse problems based on the non-classical steady state transport equation. We formulate the parameter estimation problem as an optimal control problem, and derive a rst order optimality system using a Lagrange formalism. This formalism is based on adjoint calculus, therefore we formally derive the adjoint equation of the non-classical steady state transport equation. Then we adapt the numerical schemes to discretize this rst order optimality system. We also show that these schemes are consistent with the underlying discrete optimality system. Numerical solutions of the optimality system are obtained using gradient based optimization methods and show that parameters can be reconstructed accurately at a reasonable computational cost.
Hypernasal Speech Analysis via Emperical Mode Decomposition and the Teager-Kasiser Energy Operator

In the area of speech science, one particular problem of importance has been to develop a clear method for detecting hypernasality in speech. For speech pathologists, hypernsality is a critical diagnostic used for judging the severity of velopharyngeal (nasal cavity/mouth separation) inadequacy in children with a cleft lip or cleft palate condition. For physicians and particularly neurologists, these same velopharyngeal inadequacies are believed to be linked to nervous system disorders such as Alzheimer’s disease and particularly Parkinson’s disease. One can therefore envision the need to not only find a reliable method for detecting hypernasality, but to also quantify the level (severity) of hypernasality as well. An integral component in the study of speech is the analysis of speech formants, i.e., vocal tract resonances. Traditional acoustical analysis methods of using a linear source model follow the premise that differences between normal and hypernasal speech can be distinguished by shifts or power changes in the formant frequencies and/or the widening (or narrowing) of the formant bandwidths. Such a premise,
A Broken Process – The Swedish Health Care System Asks for Expert Advice

This paper analyses the process in which expert reports on health care governance are commissioned, produced and received in a Swedish setting. Based on an empirical analysis of interviews with commissioners and producers of such reports, the paper argues that the typical process in which expert reports on health governance come about is fraught with quite deficient ways of producing expert knowledge. The analysis contributes to the literature on the role of expertise in governance and policymaking. In contrast to most other analyses in this field, the paper focuses not on the content of expert reports nor on their political uptake but on the process in which they are produced.
Hybrid Finite Element Methods for Non-linear and Non-smooth Problems in Solid Mechanics

In this thesis, several hybrid finite element methods are studied and applied to non-linear and non-smooth problems in solid mechanics. We consider non-conforming methods based on isogeometric elements and standard polynomial spaces. The potential of isogemetric mortar methods is presented with a vibroacoustical example, which includes material and geometry variations. For non-linear problems of Signorini-type, we provide optimal order a priori estimates for the trace and the flux.
Nonlinear dynamics of granular assemblies

In this work we investigate granular chains, which are one-dimensional systems of discrete macroscopic particles interacting via the intrinsically nonlinear Hertz law. Such systems support the propagation of solitary waves (SWs), which are non-dispersive, mobile bundles of energy. A comprehensive analysis into the dynamical behaviour of these systems and the properties of SW propagation is presented, and several interesting new results are obtained. First, we find that the transition to the quasi-equilibrium (QEQ) phase in granular chains can be manipulated by altering the material properties of the system. We further use these results to develop a novel shock absorption device with a predictable and tunable frequency response, making it useful also for energy harvesting applications. Second, we show for the first time that granular chains with various nonlinearities of the contact potential can achieve thermal equilibrium at sufficiently long times, and thus QEQ is an intermediate phase of these systems. We characterize the equilibrium phase by deriving approximate distribution functions for grain velocity and kinetic energy and system kinetic energy in a microcanonical ensemble of interacting particles. As a by-product, we derive the equilibrium specific heat, and a size-dependent correction term, for such systems. We also show how these ideas extend to heterogeneous systems such as diatomic, tapered, and random-mass chains. Furthermore, we look closely at the transition to equilibrium by using statistical tests to show that the long-term dynamics is ergodic, and by examining the behaviour of various correlation functions close to the onset of the transition. Third, we solve a highly nonlinear, fourth-order wave equation that models the continuum theory of long-wavelength pulses in weakly compressed, homogeneous granular chains with a general power-law contact interaction, to characterize all trav-
Exploring banking competition in Croatia by using the Panzar-Rosse model

The performance commercial banks in the Croatia have been widely studied, but there is little known about the examination of the nature of competition. For these reasons, it is important to investigate whether the banking sector in Croatia exerts monopoly or monopolistic behavior. This research empirically explores the nature of competition in the Croatian banking sector by covering 24 commercial banks between 2008 and 2018. In this vein, the panel data analysis was used along with H-Statistics. This study for Croatia and its findings confirms early findings of the existence of monopolistic competition in the most transition and developing countries. In fact, the findings obtained from this study reveals that the commercial banks in Croatia operate under monopolistic structure. Moreover, the results reveal that variable of RIETD, RLTA, RETA, and RDTA are statically significant. It indicates that banks operated in Croatia are focus more on traditional loans than other activities.
Delaunay Methods for Approximating Geometric Domains

The Delaunay triangulation is used extensively for representing geometric domains. Since its definition in 1934, researchers have applied it and its dual structure, the Voronoi diagram, to algorithms for surface reconstruction, mesh generation, simplification, and feature computation. Its universality can be explained by the mathematical properties it naturally optimizes, the provable guarantees it lends to algorithm analysis, and the design simplicity it provides for algorithms. We consider the use of the Delaunay triangulation to approximate three different domains. We begin by developing a technique for simplifying vector field datasets using Delaunay triangulations. Piecewise-linear interpolation over Delaunay triangulations gives good approximations for scalar fields, motivating our approach on vector-valued data. We remove vertices from the Delaunay triangulation using a local error metric which is biased to preserve critical points of the field and to prevent topological changes during simplification. Experimental results show the effectiveness of this technique on both two and three dimensional datasets. We next present an algorithm, DelIso, for building Delaunay meshes to approximate smooth surfaces defined by the isosurface of a volume datasets. DelIso employs a two stage algorithm which discards the need to maintain the full 3D Delaunay triangulation in the second stage. Implementation results have shown that by using this optimization we can obtain a 2-3 times speedup over its one stage counterpart.
Job Insecurity, Grit and Work Engagement in The Hospitality Industry During Covid-19

This research was conducted to identify the influence of job insecurity and grit toward work engagement on 276 hospitality employees during the COVID-19 pandemic. It consisted of 81 male respondents and 195 female respondents. The sampling technique used was the purposive sampling technique, which has specific criteria. Those criteria are hospitality workers in hotels, the food and beverage industry, administration, marketing, travel, transportation, and housekeeping companies in Jakarta. This research used three measurement tools, namely, the Utrecht Work Engagement Scale (17 items; a = .856), the Job Insecurity Scale (9 items; a = .887), and the Grit Scale (12 items; a = .797). Multiple linear regression was used as a data analysis method. The findings indicated that during the COVID-19 pandemic, job insecurity and grit had an impact on the level of work engagement among hospitality employees. Job insecurity and grit both significantly affect how motivated people are at work in the hospitality industry. Employees’ job insecurity and grit have a positive relationship that can raise the value of work engagement. Therefore, decreasing job insecurity calls for high levels of grit and work engagement to keep employee positions within the organization. The strongest correlation was found between the dimensions of grit (perseverance of effort) and work engagement (dedication). Unlike this research, which was conducted on hospitality workers, the previous research was conducted on general workers. They expected the best performance, including maintaining a friendly smile and offering the best service in all circumstances while the pandemic was ongoing.
α by Frame Theory

We obtian a short and new sharp proof for atomic decomposition for Fock space by using the frame theory. In fact we show that the Fock space F 2 α admit an atomic decomposition i.e every analytic function in this space can be presented as a linear combination of ”atoms ” defined using the normalized reproducing kernel of this space.