bluuebunny/crossref_metadata_2025_split huggingface dataset:
The incidence and carrier frequency of Tay‐Sachs disease in the French‐Canadian population of Quebec based on retrospective data from 24 years, 1992–2015
Authors: Sillon Guillaume , Allard Pierre , Drury Stella , Rivière Jean‐Baptiste , De Bie Isabelle 
Published: April 2020

AbstractTay‐Sachs disease (TSD) is a hereditary neurodegenerative condition inherited through an autosomal recessive pattern. The incidence and carrier frequency of infantile TSD were found to be increased among French Canadians in specific areas of the province of Quebec or calculated from New England populations with French‐Canadian heritage. No accurate infantile TSD carrier frequency for the whole French‐Canadian population in Quebec has been published. In this study, we estimate the incidence and carrier frequency of infantile TSD in the Quebec French‐Canadian population. The number of TSD cases was ascertained during the 1992–2015 period, as well as the number of births to mothers whose language of use is French. Seven cases of TSD have been diagnosed in Quebec during the period of ascertainment. This corresponds to an incidence of 1/218,144, which in turn corresponds to a carrier frequency of 1/234. In the same 24‐year period, there are two French‐Canadian couples who had a fetus prenatally diagnosed with TSD. If these cases are included, the incidence of TSD in the French‐Canadian population of Quebec is 1/169,668 and the carrier frequency 1/206. These findings can be used for genetic counseling and policy decisions regarding carrier screening for TSD in populations of French‐Canadian descent.
A novel flow cytometry-based assay to measure compromised B cell receptor signaling as a prognostic factor in chronic lymphocytic leukemia
Authors: Heitmann Jonas S , Märklin Melanie , Truckenmüller Felicia M , Hinterleitner Clemens , Dörfel Daniela , Haap Michael , Kopp Hans-Georg , Wirths Stefan , Müller Martin R 
Published: April 2020

Abstract
Chronic lymphocytic leukemia (CLL) is the most common leukemia in adults. In the past years, new therapeutic approaches (e.g., ibrutinib or venetoclax) have been established and greatly improved treatment of CLL. However, complete control or cure of the disease have not been reached so far. Thus, reliable prognostic markers are an imperative for treatment decisions. Recent studies have revealed an essential role for B cell receptor (BCR) signaling in the pathogenesis, prognosis, and therapy of CLL. A heterogeneous response to receptor stimulation with anti-IgM treatment culminating in different calcium flux capabilities has been demonstrated by several authors. However, the methods employed have not reached clinical application. Here, we report on a flow cytometry-based assay to evaluate calcium flux capabilities in CLL and demonstrate that compromised BCR signaling with diminished calcium flux is associated with a significantly better clinical outcome and progression free survival. In summary, our data strongly support the role of compromised BCR signaling as an important prognostic marker in CLL and establish a novel diagnostic tool for its assessment in clinical settings.
Global climatology of synoptically‐forced downslope winds
Authors: Abatzoglou John T. , Hatchett Benjamin J. , Fox‐Hughes Paul , Gershunov Alexander , Nauslar Nicholas J. 
Published: April 2020

AbstractDownslope winds are mesoscale mountain meteorological phenomena that contribute to localized temperature extremes and contribute to numerous societal and environmental impacts. Whereas previous studies have examined local downslope winds, no known efforts have attempted to identify and characterize meso‐ to synoptic‐scale downslope winds globally using a common approach. We use a conceptual model for downslope winds that employs cross‐barrier wind speed, near‐mountain top static stability, and downward vertical velocity using thresholds guided by a chronology of local downslope winds and meta‐analysis of downslope wind case studies. This approach was applied to ERA‐5 reanalysis during 1979–2018 to develop a global atlas of downslope winds. Downslope winds adhered to distinct geographic and seasonal patterns, with peak occurrence in north–south oriented midlatitude mountains in the winter hemisphere associated with strong cross‐mountain winds and stability. However, we identify numerous locations from the tropics to the high‐latitudes where downslope winds occur at least 60 days a year as a byproduct of the general circulation and local‐scale circulation interacting with topography. The four‐decade‐long data set is also used to examine statistical relationships between the occurrence of downslope winds and El Niño‐Southern Oscillation as well as long‐term trends in downslope wind occurrence.
A Fragment Library of Natural Products and its Comparative Chemoinformatic Characterization
Authors: Chávez‐Hernández Ana L. , Sánchez‐Cruz Norberto , Medina‐Franco José L. 
Published: April 2020

AbstractWe report a comprehensive fragment library with 205,903 fragments derived from the recently published Collection of Open Natural Products (COCONUT) data set with more than 400,000 non‐redundant natural products. The natural products‐based fragment library was compared with other two fragment libraries herein generated from ChEMBL (biologically relevant compounds) and Enamine‐REAL (a large on‐demand collection of synthetic compounds), both used as reference data sets with relevance in drug discovery. It was found that there is a large diversity of unique fragments derived from natural products and that the entire structures and fragments derived from natural products are more diverse and structurally complex than the two reference compound collections. During this work we introduced a novel visual representation of the chemical space based on the recently published concept of statistical‐based database fingerprint. The compounds and fragments libraries from natural products generated and analyzed in this work are freely available.
Stage detection of mild cognitive impairment via fMRI using Hilbert Huang transform based classification framework
Authors: Shi Jiahao , Liu Baolin 
Published: April 2020

PurposeThis work aims to establish a classification framework for the diagnosis of mild cognitive impairment (MCI) at different stages (early MCI and late MCI) through direct analysis of resting‐state functional magnetic resonance imaging (rs‐fMRI) signals and using the accuracy (total correct rate), specificity (correct rate of late MCI) and sensitivity (correct rate of early MCI) to validate its classification performance.MethodsAll fMR images of subjects were parcellated into 116 regions of interest (ROIs) by applying the Anatomical Automatic Labeling (AAL) template, and the average rs‐fMRI signals of each ROI were extracted. The Hilbert‐Huang transform (HHT) was introduced into the framework to decompose each rs‐fMRI signal into a series of intrinsic mode functions (IMFs) and to analyze these nonstationary and nonlinear time‐series from the perspective of multiresolution. After obtaining the instantaneous frequencies and amplitudes of all IMFs of a signal, the Hilbert weighted frequencies (HWFs) were calculated and combined into a vector as the feature of the corresponding ROI. Support Vector Machine (SVM) was implemented to classify MCI at different stages. We used the independent two‐sample t‐test as the feature selection method and measured the classification performance through the leave‐one‐out cross‐validation (LOOCV) method.ResultsResults on 77 early MCI (eMCI) and 64 late MCI (lMCI) with baseline rs‐fMRI data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) yielded 87.94% classification accuracy. Some of the brain regions with significant differences found by previous studies have been confirmed in this work. We found that HWF characteristics exhibited a significant downward trend in all cerebellar regions. The rs‐fMRI signals in differential brain regions have not changed completely, but only altered in some narrow frequency bands. The analysis results showed that during the progress of MCI, the main changes of rs‐fMRI were concentrated in IMF3, while IMFs with other indexes also contained HWF features with high SVM weights, such as Orbitofrontal superior frontal gyrus in IMF2, Insula in IMF4, and Lobule Ⅲ of vermis in IMF5, indicating that other IMFs provide important information for the diagnosis of MCI as well.ConclusionsThis work confirmed the classification ability of HHT‐based classification framework in classification of at different stages of MCI. Through the analysis, we found that during the progress of MCI the main changes of rs‐fMRI were concentrated in IMF3, and HWF characteristics showed a significant downward trend in all cerebellar regions.
Temperature dependence of methanol and ethanol vapor sorption in polyhedral oligomeric silsesquioxane (POSS) containing methacrylate membranes
Authors: Moriizumi Yukiko , Fukuda Hajime , Tanaka Seiya , Tanaka Daisuke , Nagai Kazukiyo 
Published: April 2020

AbstractThis study aimed to determine the solubility and temperature dependence of methanol and ethanol vapor caused by the difference in the substituents of polyhedral oligomeric silsesquioxane (POSS)‐containing polymethacrylate membranes and the spacer length between the backbone and POSS backbone. Vapor sorption of methanol and ethanol was measured at 25°C, 35°C, and 45°C for three kinds of POSS‐containing polymer membranes, namely, poly(methacryl isobutyl POSS), poly(methacrylate isobutyl POSS), and poly(methacryl phenyl POSS). The primary structures of the three POSS‐containing polymer chains were columnar. The solubility of alcohol vapor on the POSS‐containing polymer membranes followed the mechanism of solid adsorption and not the general dissolution diffusion. The sorption amount at all three temperatures was related to the surface area of the cylindrical primary structure and the solid adsorption property of the alcohol molecule of the POSS substituent. The sorption amount increased because of the large surface area and adsorption property of alcohol molecules. Although a typical glassy polymer shows exothermic mixing and a rubbery polymer displays endothermic mixing, the sample with the POSS substituent of isobutyl group exhibited an unusual behavior of endothermic mixing despite being a glassy polymer.
An unanticipated use of the nasogastric feeding tube
Authors: Yanagisawa Satoru , Takashi Ohe 
Published: April 2020

Key messageIndeed, the nasogastric feeding (NGF) tube should be used only for the main intended purpose such as feeding, and the correct insertion of the NGF tube into the gastrointestinal tract is encouraged; however, an NGF tube aberrantly inserted into the lung might provide a valuable opportunity of obtaining samples from the lower respiratory tract.
Laparoscopic totally extraperitoneal vs robotic transabdominal preperitoneal inguinal hernia repair: Assessment of short‐ and long‐term outcomes
Authors: Aghayeva Afag , Benlice Cigdem , Bilgin Ismail A. , Bengur Fuat B. , Bas Mustafa , Kirbiyik Ebru , Aytac Erman , Baca Bilgi 
Published: April 2020

AbstractBackgroundIn this study, we aimed to compare short‐ and long‐term outcomes between laparoscopic totally extraperitoneal (L‐TEP) and robotic transabdominal preperitoneal (R‐TAPP) inguinal hernia repair.MethodsPatients were classified into two groups: L‐TEP and R‐TAPP. The groups were case‐matched in a 1:1 ratio based on age, gender, and body mass index (BMI).ResultsOut of 86 patients, 43 patients were matched in each group based on the study criteria. Demographics were comparable between the groups. Operative time was significantly longer for the R‐TAPP compared to L‐TEP (129.1 ± 47.2 min vs 92.5 ± 28.3 min; P < .001). VAS scores at 24 hours after surgery were significantly higher in the L‐TEP compared to R‐TAPP (36.8 ± 20.1 vs 20.3 ± 18.7; P < .001). Total hospital costs were 4778$ for R‐TAPP and 3852$ for L‐TEP.ConclusionThe current study demonstrates similar long‐term postoperative outcomes and recurrence rates between robotic and laparoscopic inguinal hernia repair in a case‐matched fashion.
Observer‐predictor feedback for consensus of discrete‐time multiagent systems with both state and input delays
Authors: Liu Qingsong 
Published: April 2020

SummaryThis article is concerned with the consensus problem for discrete‐time multiagent systems with both state and input delays. Single observer‐predictor‐based protocols and multiple observer‐predictors feedback protocols are simultaneously established to predict the future state such that the input delay that can be arbitrarily large yet bounded is completely compensated. It is shown that the consensus of the multiagent system can be achieved by the single/multiple observer‐predictors feedback protocol. Moreover, sufficient conditions guaranteeing the consensus of the multiagent system are provided in terms of the stability of some simple observer‐error systems, and the separation principle is discovered. Finally, a numerical example is worked out to illustrate the effectiveness of the proposed approaches.
Determination and validation of simultaneous derivatization and dispersive liquid‐liquid microextraction method for analysis of nitrate and nitrite contents as nitrate ions in onion and potato samples
Authors: Khodaei Hossein , Afshar Mogaddam Mohammad Reza , Hamidi Ali Asghar , Farajzadeh Mir Ali , Bavili Tabrizi Ahad , Ansarin Khalil , Nemati Mahboob 
Published: April 2020

AbstractA simple and rapid method has been developed for the extraction of nitrate and nitrite from potato and onion samples using derivatization dispersive liquid‐liquid microextraction coupled with high‐performance liquid chromatography with ultraviolet detection. In this process nitrate ions are derivatized to 2,4‐dimethyl‐6‐nitrophenol using 2,4‐dimethyl phenol (as a derivatization agent) and the derivatized compound is concentrated using the microextraction method. The nitrite in the samples is rapidly oxidized to nitrate with potassium permanganate. After derivatization of nitrate ions under an acidic medium, the derivatized compound is extracted into carbon tetrachloride (as an extraction solvent) in the presence of methanol (as a dispersive solvent). Under optimum conditions, calibration graph was linear in the range of 31–50 000 ng/mL with r2 = 0.9997. The limits of detection and quantification were 9.1 and 31 ng/g, respectively. Extraction recovery was found to be 90%. Lastly, some real samples were analyzed and nitrite and nitrate contents were successfully determined. The developed method was compared with ISO 3365 method and the results showed that the proposed method is more efficient than it.
Dietary recommendations for patients with dementia
Authors: Yerstein Oleg , Mendez Mario F. 
Published: April 2020

AbstractWith the emergence of support for diet in the maintenance of cognition, clinicians have been justifiably eager to promote diet recommendations for their older patients. But popular diets, such as the Mediterranean diet, Dietary Approaches to Stop Hypertension (DASH), and the Mediterranean‐DASH Intervention for Neurodegenerative Delay (MIND), have not been shown to benefit cognition among patients who already have dementia or cognitive decline. In our experience, promoting these restrictive diets can be detrimental to patients with dementia who are already prone to eating disturbance; vulnerable to malnutrition; and, if underweight, demonstrate increased mortality. Moreover, we have seen both patient and caregiver satisfaction negatively affected by dietary modification. Clinicians need to be aware that any dietary recommendations for patients with dementia should be mitigated by the lack of evidence for improvement in cognition, the risks for exacerbating poor nutrition, and the potential for further limiting their quality of life.
Deep Induction: Induction Rules for (Truly) Nested Types
Authors: Johann Patricia , Polonsky Andrew 
Published: April 2020

AbstractThis paper introducesdeep induction, and shows that it is the notion of induction most appropriate to nested types and other data types defined over, or mutually recursively with, (other) such types. Standard induction rules induct over only the top-level structure of data, leaving any data internal to the top-level structure untouched. By contrast, deep induction rules induct overallof the structured data present. We give a grammar generating a robust class of nested types (and thus ADTs), and develop a fundamental theory of deep induction for them using their recently defined semantics as fixed points of accessible functors on locally presentable categories. We then use our theory to derive deep induction rules for some common ADTs and nested types, and show how these rules specialize to give the standard structural induction rules for these types. We also show how deep induction specializes to solve the long-standing problem of deriving principled and practically useful structural induction rules for bushes and othertrulynested types. Overall, deep induction opens the way to making induction principles appropriate to richly structured data types available in programming languages and proof assistants. Agda implementations of our development and examples, including two extended case studies, are available.
Semantical Analysis of Contextual Types
Authors: Pientka Brigitte , Schöpp Ulrich 
Published: April 2020

AbstractWe describe a category-theoretic semantics for a simply typed variant of Cocon, a contextual modal type theory where the box modality mediates between the weak function space that is used to represent higher-order abstract syntax (HOAS) trees and the strong function space that describes (recursive) computations about them. What makes Cocon different from standard type theories is the presence of first-class contexts and contextual objects to describe syntax trees that are closed with respect to a given context of assumptions. Following M. Hofmann’s work, we use a presheaf model to characterise HOAS trees. Surprisingly, this model already provides the necessary structure to also model Cocon. In particular, we can capture the contextual objects of Cocon using a comonad $$\flat $$
♭
that restricts presheaves to their closed elements. This gives a simple semantic characterisation of the invariants of contextual types (e.g. substitution invariance) and identifies Cocon as a type-theoretic syntax of presheaf models. We express our category-theoretic constructions by using a modal internal type theory that is implemented in Agda-Flat.
Spinal Atomic Lambda-Calculus
Authors: Sherratt David , Heijltjes Willem , Gundersen Tom , Parigot Michel 
Published: April 2020

AbstractWe present the spinal atomic $$\lambda $$
λ
-calculus, a typed $$\lambda $$
λ
-calculus with explicit sharing and atomic duplication that achieves spinal full laziness: duplicating only the direct paths between a binder and bound variables is enough for beta reduction to proceed. We show this calculus is the result of a Curry–Howard style interpretation of a deep-inference proof system, and prove that it has natural properties with respect to the $$\lambda $$
λ
-calculus: confluence and preservation of strong normalisation.
Sharp Congruences Adequate with Temporal Logics Combining Weak and Strong Modalities
Authors: Lang Frédéric , Mateescu Radu , Mazzanti Franco 
Published: April 2020

AbstractWe showed in a recent paper that, when verifying a modal $$\mu $$-calculus formula, the actions of the system under verification can be partitioned into sets of so-called weak and strong actions, depending on the combination of weak and strong modalities occurring in the formula. In a compositional verification setting, where the system consists of processes executing in parallel, this partition allows us to decide whether each individual process can be minimized for either divergence-preserving branching (if the process contains only weak actions) or strong (otherwise) bisimilarity, while preserving the truth value of the formula. In this paper, we refine this idea by devising a family of bisimilarity relations, named sharp bisimilarities, parameterized by the set of strong actions. We show that these relations have all the nice properties necessary to be used for compositional verification, in particular congruence and adequacy with the logic. We also illustrate their practical utility on several examples and case-studies, and report about our success in the RERS 2019 model checking challenge.
How Many Bits Does it Take to Quantize Your Neural Network?
Authors: Giacobbe Mirco , Henzinger Thomas A. , Lechner Mathias 
Published: April 2020

AbstractQuantization converts neural networks into low-bit fixed-point computations which can be carried out by efficient integer-only hardware, and is standard practice for the deployment of neural networks on real-time embedded devices. However, like their real-numbered counterpart, quantized networks are not immune to malicious misclassification caused by adversarial attacks. We investigate how quantization affects a network’s robustness to adversarial attacks, which is a formal verification question. We show that neither robustness nor non-robustness are monotonic with changing the number of bits for the representation and, also, neither are preserved by quantization from a real-numbered network. For this reason, we introduce a verification method for quantized neural networks which, using SMT solving over bit-vectors, accounts for their exact, bit-precise semantics. We built a tool and analyzed the effect of quantization on a classifier for the MNIST dataset. We demonstrate that, compared to our method, existing methods for the analysis of real-numbered networks often derive false conclusions about their quantizations, both when determining robustness and when detecting attacks, and that existing methods for quantized networks often miss attacks. Furthermore, we applied our method beyond robustness, showing how the number of bits in quantization enlarges the gender bias of a predictor for students’ grades.
On a certain adaptive method of approximate integration and its stopping criterion
Authors: Wąsowicz Szymon 
Published: April 2020

AbstractWe introduce a new quadrature rule based on Chebyshev’s and Simpson’s rules. The corresponding composite rule induces the adaptive method of approximate integration. We propose a stopping criterion for this method and we prove that if it is satisfied for a function which is either 3-convex or 3-concave, then the integral is approximated with the prescribed tolerance. Nevertheless, we give an example of a function which does satisfy our criterion, but the approximation error exceeds the assumed tolerance. The numerical experiments (performed by a computer program created by the author) show that integration of 3-convex functions with our method requires considerably fewer steps than the adaptive Simpson’s method with a classical stopping criterion. As a tool in our investigations we present a certain inequality of Hermite–Hadamard type.