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Those who carry the mutated gene will develop the fatal Huntington’s disease at some stage in life. The brain disease, which can be inherited across generations, begins slowly and makes it increasingly difficult for sufferes to regulate their feelings, thoughts, and eventually movements. There is still no treatment. However, Huntington researcher and psychiatrist Åsa Petersén is working hard at it
In anti-glomerular basement membrane (anti-GBM) disease, IgG class autoantibodies induce rapidly progressive glomerulonephritis. Regrettably, many patients are diagnosed at a late stage when even intensive conventional treatment fails to restore renal function The endopeptidase IdeS (Immunoglobulin G degrading enzyme of Streptococcus pyogenes) (imliflidase) rapidly cleaves all human IgG subclasses
BackgroundFor advanced pancreatic cancer, pulmonary metastases (PM) have been considered favorable factors compared to metastases of other sites, but it remains unknown whether the prognosis of patients with synchronous liver and lung metastases is better than that of non-PM.MethodsData was derived from a two-decade cohort and included 932 cases of pancreatic adenocarcinoma with synchronous liver
Massive Multiple-Input Multiple-Output (MIMO) communication systems are being investigated intensively for positioning services. Enhancing the accuracy on these services in terms of accurate positioning of users is an important goal to improve related applications in the future. Convolutional Neural Networks (CNNs) has been proposed to infer the position of a user from Channel State Information (C
The reactivity of the benzenedithiolate (bdt)-bridged complex [Fe2(CO)6(µ-bdt)] with arsine, stibine and phosphine ligands has been studied. The new mono- and disubstituted complexes [Fe2(CO)5(EPh3)(µ-bdt)] (E = As, 1; E = Sb 3) and [Fe2(CO)4(EPh3)2(µ-bdt)] (E = As, 2; E = Sb, 4) and the previously reported [Fe2(CO)4(PPh2H)2(µ-bdt)] (5) have been prepared by Me3NO-initiated carbonyl substitution r
We introduce rigorous theory for deriving first and second order backpropagation methods for Deep Neural Networks (DNN) whilst satisfying existing theory in DNN optimization. We begin by formally defining a neural network with its respective components and state the first and second order chain rule with respect to its partial derivatives. The partial derivatives in the chain rule formula are rela
