Background and aims: Calcium plays a fundamental role in biological processes. Ionized calcium (Ca2+), is the biologically active fraction, but in practice total or corrected calcium assays are routinely used to deter...
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Background and aims: Calcium plays a fundamental role in biological processes. Ionized calcium (Ca2+), is the biologically active fraction, but in practice total or corrected calcium assays are routinely used to determine calcium status. Materials and methods: We retrospectively compared total and corrected calcium to assess the calcium status, with ionized calcium which is considered for now like the best indicator. To compensate for their lack of performance we created a machine learning algorithm to predict calcium status. Results: Corrected calcium performed less well than total calcium with 58% and 74% agreement, respectively, in our population. Total calcium was especially good for hypocalcemic samples: 93% agreement versus 45% for normocalcemic and 54% for hypercalcemic samples. Corrected calcium was especially good for hypercalcemic and normocalcemic samples: 90% and 84% agreement respectively versus 40% for hypocalcemic samples. Corrected calcium is mainly faulty in hypoalbuminemia, acid-base disorders, renal insufficiency, hyper-phosphatemia, or inflammatory syndrome. With our ML algorithm, we obtained 81% correct classifications. Its main advantage is that its performance are not influenced by the variables studied or the calcium status. Conclusion: In many situations, corrected calcium should not be used. Our ML algorithm may make a better assessment of calcium status than total calcium. Finally, if doubt, an ionized calcium assay should be performed.
PurposeContinuous Glucose Monitoring (CGM) is a key tool for insulin-treated people with diabetes (PwD). CGM devices include both real-time CGM (rtCGM) and intermittently scanned CGM (isCGM), which are associated with...
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PurposeContinuous Glucose Monitoring (CGM) is a key tool for insulin-treated people with diabetes (PwD). CGM devices include both real-time CGM (rtCGM) and intermittently scanned CGM (isCGM), which are associated with an improvement of glucose control and less hypoglycemia in clinical trials of people with type 1 and type 2 *** is an expert position to update a previous algorithm on the most suitable choice of CGM for insulin-treated PwD in light of the recent evidence and clinical *** identified six different clinical scenarios, including type 1 diabetes, type 2 diabetes, pregnancy on intensive insulin therapy, regular physical exercise, new onset of diabetes, and frailty. The use of rtCGM or isCGM is suggested, on the basis of the predominant clinical issue, as suboptimal glucose control or disabling hypoglycemia, regardless of baseline HbA1c or individualized HbA1c *** present algorithm may help to select the best CGM device based on patients' clinical characteristics, needs and clinical context, offering a further opportunity of a "tailored" therapy for people with insulin-treated diabetes.
Recent developments in archeological research extend diverse technological methods for the geometric deciphering and cultural understanding of various historical building components. One of the emerging methods in thi...
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Recent developments in archeological research extend diverse technological methods for the geometric deciphering and cultural understanding of various historical building components. One of the emerging methods in this field is the development of generative algorithms to develop computational models for the comparative study of variation among different structures belonging to a common era, style, or region. In this study, we present a novel approach for the computational analysis and parametric modeling of muqarnas found among Anatolian Seljuk architecture in Kayseri and Sivas built in the 13th century. Using four different octagonal muqarnas structures, we outline common generative rules showing recursive stacking of geometric layers, fractal patterns and hierarchical branching of the axis of symmetry. A recursive algorithm is developed that can offer a generative study of muqarnas structures using proportions based on the 'silver ratio.' The development of the algorithm is presented through rules and variations that can offer a novel perspective for the geometric understanding and categorization of muqarnas in the region.
Polynomial system solving arises in many application areas to model non-linear geometric properties. In such settings, polyno-mial systems may come with degeneration which the end-user wants to exclude from the soluti...
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Polynomial system solving arises in many application areas to model non-linear geometric properties. In such settings, polyno-mial systems may come with degeneration which the end-user wants to exclude from the solution set. The nondegenerate locus of a polynomial system is the set of points where the codimension of the solution set matches the number of *** the nondegenerate locus is classically done through ideal-theoretic operations in commutative algebra such as satura-tion ideals or equidimensional decompositions to extract the com-ponent of maximal *** exploiting the algebraic features of signature-based Grobner ba-sis algorithms we design an algorithm which computes a Grobner basis of the equations describing the closure of the nondegenerate locus of a polynomial system, without computing first a Grobner basis for the whole polynomial system.(c) 2023 Elsevier Ltd. All rights reserved.
Exploratory and confirmatory factor analyses are commonly employed to identify and explore underlying factor structures. Unfortunately, when variable selection is involved, results often fluctuate across studies makin...
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Exploratory and confirmatory factor analyses are commonly employed to identify and explore underlying factor structures. Unfortunately, when variable selection is involved, results often fluctuate across studies making it difficult to determine the "best" and most replicable factor structure. This study proposes a new factor analysis variable selection algorithm called the Replicable Factor Analytic Solutions (RFAS) that incorporates sound statistical and psychometric practices when selecting the final factor structure, while simultaneously examining the observed variables and factor structures replicability. This article outlines the algorithm development and rationale for each decision in the algorithm's development. An example using simulated and empirical data is also provided to display the algorithm results and delineate the utility of these results for future analysts.
The existing truncated variable method to generate random variate cannot be applied when indeterminacy is presented in either the parameters or observations. This paper addresses the truncated variable simulation unde...
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The existing truncated variable method to generate random variate cannot be applied when indeterminacy is presented in either the parameters or observations. This paper addresses the truncated variable simulation under the indeterminate environment. The truncated variable simulation method will be introduced using the DUS-neutrosophic Weibull distribution. The algorithm to generate random variate will be presented and applied in random variate generation. Extensive simulation tables for various values of indeterminacy and truncated variables are presented. The proposed study for other neutrosophic statistical distribution can be extended as future research.
Objective. To evaluate the relation between mismatch repair (MMR) status and the risk of lymph node metas-tasis in endometrial cancer, and whether this additional data can be incorporated to current SLN (sentinel lymp...
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Objective. To evaluate the relation between mismatch repair (MMR) status and the risk of lymph node metas-tasis in endometrial cancer, and whether this additional data can be incorporated to current SLN (sentinel lymph node) ***. We included a series of 332 women that underwent SLN mapping +/- systematic lymphadenectomy from January 2013 to December 2021. Protein expressions of MLH1, MSH2, MSH6, PMS2 were examined by immuno-histochemistry and considered MMRd (deficient) when at least one protein was not ***. MMRd was noted in 20.8% of cases and correlated to grade 3 (p = 0.018) and presence of lymphovascular space invasion (p = 0.032). Moreover, MMRd was an independent risk factor for lymph node metastasis (OR 2.76, 95% CI 1.36-5.62). Notably, 21.7% (15/69) cases with MMRd had lymph node metastasis compared to 9.5% (25/263) of cases with MMRp (proficient) (p = 0.005). The overall and bilateral SLN detection rates were 91.9% and 75.9%, respectively. Of the 80 (24%) cases of non-bilateral SLN detection, 66.2% had low-grade tumors (G1/G2) and myometrial invasion <50%. Considering MMR status an independent prognostic factor for lymph node metastasis, a systematic lymphadenectomy (side specific or bilateral) would forgo in 53.7% (43/80) of cases with non-bilateral detection, representing 13% (43/332) of all endometroid tumors. Conclusion. MMR status was independently related to lymph node metastasis in endometrioid EC. Moreover, MMR status may help to select patients that can forgo systematic lymphadenectomy in case of undetected SLN.(c) 2022 Elsevier Inc. All rights reserved.
Polymeric nanocomposites are broadly used in the manufacturing of aircraft, space, optical, and biomedical components. It is mainly due to their exceptional physiomechanical performances. The carbon nanotube (CNTs) re...
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Polymeric nanocomposites are broadly used in the manufacturing of aircraft, space, optical, and biomedical components. It is mainly due to their exceptional physiomechanical performances. The carbon nanotube (CNTs) reinforced fibrous polymer composite significantly replaced the heavyweight metallic materials and their alloys. This work examines the Milling performances of polymer nanocomposite modified by Glass fiber and Multiwall carbon nanotube (MWCNT). The considered varying constraints, namely, Spindle speed (S), Feed rate (F), Depth of Cut (D), and weight % MWCNT (wt.%), have effectively controlled to acquire the desired value. The experimentation was planned according to Taguchi L-9 Orthogonal array (OA). The aggregation of responses, namely, Material removal rate (MRR), Cutting force (F-c), and Surface roughness (Ra), was achieved by the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The optimal combination of machining constraints is achieved using the Grasshopper optimization algorithm (GOA). GOA mitigates the bionic-inspired principles to search for the best target among the many solutions. The main feature of the GOA is the larval phase is slow drive and minor steps of the Grasshopper. This makes it unique from other algorithms in obtaining a global solution. The Scanning electron microscopy (SEM) results show the feasible machined surface and higher potential of the proposed algorithm in the manufacturing environment.
Let graph G(p, q) be a simple graph, if there is a positive integer k(1 {1,2 ..., k}, such that for any edge uv is an element of E(G) , when d(u) = d(v), S(u) = S(v) , where S(u) Sigma(uv is an element of E(G))f(uv) ...
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Let graph G(p, q) be a simple graph, if there is a positive integer k(1 <= k <= vertical bar E vertical bar) and the mapping f: E(G) -> {1,2 ..., k}, such that for any edge uv is an element of E(G) , when d(u) = d(v), S(u) = S(v) , where S(u) Sigma(uv is an element of E(G))f(uv) . d(u) represents the degree of point u , then f is the coloring of Adjacent Vertex Sum Reducible Edge of G. The maximum value k is called the Adjacent Vertex Sum Reducible Edge chromatic number of graph G, denoted as chi(Avsr)(G). Based on the existing graph coloring concepts and reducible concepts, this paper proposes a new concept of adjacent vertex sum reducible edge coloring combined with practical problems and designs a new type of adjacent vertex sum reducible edge coloring algorithm.
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