bluuebunny/crossref_metadata_2025_split huggingface dataset:
Retention and impairment of neurocognitive functions in mild cognitive impairment and Alzheimer’s disease with a comprehensive neuropsychological test
Authors: Yao Lu , Aoyama Shinsuke , Ouchi Atushi , Yamamoto Yasuji , Sora Ichiro 
Published: March 2022

AbstractAimMATRICS Consensus Cognitive Battery was developed by the National Institute of Mental Health to establish acceptance criteria for measuring cognitive changes in schizophrenia and can be used to assess cognitive functions in other psychiatric disorders. We used a Japanese version of MATRICS Consensus Cognitive Battery to explore the changes in multiple cognitive functions in patients with mild cognitive impairment and mild Alzheimer's disease.MethodsWe administered the Japanese version of MATRICS Consensus Cognitive Battery to 11 patients with mild cognitive impairment (MCI), 11 patients with Alzheimer's disease, and 27 healthy controls. All Japanese versions of MATRICS Consensus Cognitive Battery domain scores were converted to t‐scores using sample means and standard deviations and were compared for significant performance differences among healthy control, MCI, and mild Alzheimer's disease groups.ResultsCompared with healthy controls, patients with MCI and mild Alzheimer's disease demonstrated the same degree of impairment to processing speed, verbal learning, and visual learning. Reasoning and problem‐solving showed significant impairments only in mild Alzheimer's disease. Verbal and visual abilities in working memory showed different performances in the MCI and mild Alzheimer's disease groups, with the Alzheimer's disease group demonstrating significantly more deficits in these domains. No significant difference was found among the groups in attention/vigilance and social cognition.ConclusionsThe Japanese version of MATRICS Consensus Cognitive Battery can be used to elucidate the characteristics of cognitive dysfunction of normal aging, MCI, and mild dementia in clinical practice.
Using multiple convolutional window scanning of convolutional neural network for an efficient prediction of ATP‐binding sites in transport proteins
Authors: Nguyen Trinh‐Trung‐Duong , Chen Syun , Ho Quang‐Thai , Ou Yu‐Yen 
Published: March 2022

AbstractProtein multiple sequence alignment information has long been important features to know about functions of proteins inferred from related sequences with known functions. It is therefore one of the underlying ideas of Alpha fold 2, a breakthrough study and model for the prediction of three‐dimensional structures of proteins from their primary sequence. Our study used protein multiple sequence alignment information in the form of position‐specific scoring matrices as input. We also refined the use of a convolutional neural network, a well‐known deep‐learning architecture with impressive achievement on image and image‐like data. Specifically, we revisited the study of prediction of adenosine triphosphate (ATP)‐binding sites with more efficient convolutional neural networks. We applied multiple convolutional window scanning filters of a convolutional neural network on position‐specific scoring matrices for as much as useful information as possible. Furthermore, only the most specific motifs are retained at each feature map output through the one‐max pooling layer before going to the next layer. We assumed that this way could help us retain the most conserved motifs which are discriminative information for prediction. Our experiment results show that a convolutional neural network with not too many convolutional layers can be enough to extract the conserved information of proteins, which leads to higher performance. Our best prediction models were obtained after examining them with different hyper‐parameters. Our experiment results showed that our models were superior to traditional use of convolutional neural networks on the same datasets as well as other machine‐learning classification algorithms.
Influence of different box preparations on creep performance of corrugated fibreboard boxes subject to constant and cycling relative humidity environments
Authors: Gray‐Stuart Eli M. , Wade Kelly , Redding Gabe P. , Parker Kate , Bronlund John E. 
Published: March 2022

AbstractTo understand the effect of load and relative humidity (RH) on box creep in cool storage conditions, standard tests are performed. However, these test conditions are oversimplified compared with actual shipping conditions. Our aim is to develop test conditions that more closely mimic those encountered during refrigerated conditions to investigate their influence on creep performance and box lifetime. We compared three box preparations: (i) empty boxes used as a control, (ii) filled boxes, and (iii) boxes with only two side panels exposed to the atmosphere. A controlled environment test facility was used to subject sets of 24 boxes to 30% of their ultimate failure load under different cyclic and constant relative humidity conditions. Results indicate that filled boxes had substantially reduced performance in terms of secondary creep rate and lifetime. The fill in the box contributed to out‐of‐plane displacement of the side panels which manifested earlier than in the control, resulting in a higher creep rate. Boxes with only two exposed panels had lower moisture uptake and performed substantially better than the control. These findings demonstrate how creep performance and box lifetime depend on the box conditions including fill and the area of the box that is exposed for moisture transfer. Alternative box preparations which mimic supply chain conditions are worthy of investigation in creep analysis as they will help predict more accurately box performance in the cold supply chain.
Multi‐variable quantitative feedback theory based controller using directional transfer ratio
Authors: Roy Prasanta 
Published: March 2022

AbstractThis article proposes a novel method, inspired from eigen decomposition technique, to design a quantitative feedback theory (QFT) based robust controller for a multiple input multiple output (MIMO) uncertain plant. The proposed method is a direct and sufficiently generalized one. Unlike existing practice, it does not require to transform a “” MIMO‐QFT based design problem into “n” sequential multiple input single output QFT based design problems. Apart from the frequency dependency, the frequency response of a MIMO system also has the spatial dependency. This makes the frequency domain analysis and design for a MIMO system, more challenging than its SISO counterpart. Three new concepts namely directional transfer ratio (DTR), output directionality (OD), and principle of control along characteristic vectors (PCCV) are introduced to take care of the complexities of the frequency response of a MIMO feedback system. The DTR, OD, PCCV and existing techniques of QFT are combined together to develop the proposed design method. A case study is presented considering a “” ill‐conditioned plant to illustrate the method. The proposed method is expected to open up new avenues in the area of MIMO‐QFT based design.
Tough and Highly Efficient Underwater Self‐Repairing Hydrogels for Soft Electronics
Authors: Fu Rumin , Guan Youjun , Xiao Cairong , Fan Lei , Wang Zhengao , Li Yangfan , Yu Peng , Tu Lingjie , Tan Guoxin , Zhai Jinxia , Zhou Lei , Ning Chengyun 
Published: March 2022

AbstractThe vulnerability of hydrogel electronic materials to mechanical damage due to their soft nature has necessitated the development of self‐repairing hydrogel electronics. However, the development of such material with underwater self‐repairing capability as well as excellent mechanical properties for application in aquatic environments is highly challenging and has not yet been fully realized. This study designs a tough and highly efficient underwater self‐repairing supramolecular hydrogel by synergistically combining weak hydrogen bonds (H‐bonds) and strong dipole–dipole interactions. The resultant hydrogel has high stretchability (up to 700%) and toughness (4.45 MJ m−3), and an almost 100% fast strain self‐recovery (10 min). The underwater healing process is rapid and autonomous (98% self‐repair efficiency after 1 h of healing). Supramolecular hydrogels can be developed as soft electronic sensors for physiological signal detection (gestures, breathing, microexpression, and vocalization) and real‐time underwater communication (Morse code). Importantly, the hydrogel sensor can function underwater after mechanical damage because of its highly efficient underwater self‐repairing capability.
From quantum‐derived principles underlying cysteine reactivity to combating the COVID‐19 pandemic
Authors: Mazmanian Karine , Chen Ting , Sargsyan Karen , Lim Carmay 
Published: March 2022

AbstractThe COVID‐19 pandemic poses a challenge in coming up with quick and effective means to counter its cause, the SARS‐CoV‐2. Here, we show how the key factors governing cysteine reactivity in proteins derived from combined quantum mechanical/continuum calculations led to a novel multi‐targeting strategy against SARS‐CoV‐2, in contrast to developing potent drugs/vaccines against a single viral target such as the spike protein. Specifically, they led to the discovery of reactive cysteines in evolutionary conserved Zn2+‐sites in several SARS‐CoV‐2 proteins that are crucial for viral polypeptide proteolysis as well as viral RNA synthesis, proofreading, and modification. These conserved, reactive cysteines, both free and Zn2+‐bound, can be targeted using the same Zn‐ejector drug (disulfiram/ebselen), which enables the use of broad‐spectrum anti‐virals that would otherwise be removed by the virus's proofreading mechanism. Our strategy of targeting multiple, conserved viral proteins that operate at different stages of the virus life cycle using a Zn‐ejector drug combined with other broad‐spectrum anti‐viral drug(s) could enhance the barrier to drug resistance and antiviral effects, as compared to each drug alone. Since these functionally important nonstructural proteins containing reactive cysteines are highly conserved among coronaviruses, our proposed strategy has the potential to tackle future coronaviruses.This article is categorized under:
Structure and Mechanism > Reaction Mechanisms and Catalysis
Structure and Mechanism > Computational Biochemistry and Biophysics
Electronic Structure Theory > Density Functional Theory
Inverse modeling of cancellous bone using artificial neural networks
Authors: Stieve Verena , Blaszczyk Mischa , Hackl Klaus 
Published: March 2022

AbstractArtificial neural networks are used to solve different tasks of daily life, engineering and medicine. In this work, we investigate its suitability for the examination of simulation results of cancellous bone with the aim to evaluate whether the bone is affected by osteoporosis. This bone disease is characterized by a reduction of the cortical bone phase, one of the two main components of the bone. The neural network predicts the simulated volume fraction in different parts of a cylinder, which models the bone. As a basis for its calculations, the neural network gets the information about the magnetic field inside the cylinder from finite element simulations. Examinations show that it is possible to train neural networks on solving that task with very high accuracies.
Food regulation and policing: innovative technology to close the regulatory gap in Australia
Authors: Lindley Jade 
Published: March 2022

AbstractInternationally, food regulations are centred on human health and safety to prevent health crises. In Australia, regulatory control over the health and safety of humans is sound, however from a criminological perspective, control over fraudulent activities within food supply chains lack. Food fraud knows no geographical boundaries and has endless reach, therefore should be prioritised by policymakers, regulators and law enforcement. Australia’s reputation for high-quality food is important domestically, but also for establishing and maintaining trust in international food trade relationships, therefore lack of enforcement over food could damage ‘Brand Australia’. Given the food industry’s vested interest in maintaining this reputation, it must also play a role to protect it. This research reviews regulatory landscape against food fraud in Australia and then, questions whether coupling informal controls to support existing formal regulatory controls may be the most appropriate and holistic way forward to protect the industry and consumers. It tests a regulatory pluralism framework to determine whether it can logically organize informal, innovative responses to contribute cohesively alongside formal controls at various points along the supply chain to prevent food fraud. Finally, it considers available informal, innovative technologies to: enhance testing regimes; prevent product and label tampering; and trace food supply chains adopted internationally show positive progress in responding to increasingly sophisticated and organized global food fraud. The research concludes adopting a regulatory pluralism framework, coupling existing regulatory controls and innovative technology could enhance and strengthen Australia’s regulatory response to fraud within its food industry.
Early reduction of SARS-CoV-2-replication in bronchial epithelium by kinin B2 receptor antagonism
Authors: Jakwerth Constanze A. , Feuerherd Martin , Guerth Ferdinand M. , Oelsner Madlen , Schellhammer Linda , Giglberger Johanna , Pechtold Lisa , Jerin Claudia , Kugler Luisa , Mogler Carolin , Haller Bernhard , Erb Anna , Wollenberg Barbara , Spinner Christoph D. , Buch Thorsten , Protzer Ulrike , Schmidt-Weber Carsten B. , Zissler Ulrich M. , Chaker Adam M. 
Published: March 2022

Abstract
SARS-CoV-2 has evolved to enter the host via the ACE2 receptor which is part of the kinin-kallikrein pathway. This complex pathway is only poorly understood in context of immune regulation but critical to control infection. This study examines SARS-CoV-2-infection and epithelial mechanisms of the kinin-kallikrein-system at the kinin B2 receptor level in SARS-CoV-2-infection that is of direct translational relevance. From acute SARS-CoV-2-positive study participants and -negative controls, transcriptomes of nasal curettages were analyzed. Primary airway epithelial cells (NHBEs) were infected with SARS-CoV-2 and treated with the approved B2R-antagonist icatibant. SARS-CoV-2 RNA RT-qPCR, cytotoxicity assays, plaque assays, and transcriptome analyses were performed. The treatment effect was further studied in a murine airway inflammation model in vivo. Here, we report a broad and strong upregulation of kallikreins and the kinin B2 receptor (B2R) in the nasal mucosa of acutely symptomatic SARS-CoV-2-positive study participants. A B2R-antagonist impeded SARS-CoV-2 replication and spread in NHBEs, as determined in plaque assays on Vero-E6 cells. B2R-antagonism reduced the expression of SARS-CoV-2 entry receptor ACE2, G protein–coupled receptor signaling, and ion transport in vitro and in a murine airway inflammation in vivo model. In summary, this study provides evidence that treatment with B2R-antagonists protects airway epithelial cells from SARS-CoV-2 by inhibiting its replication and spread, through the reduction of ACE2 levels and the interference with several cellular signaling processes. Future clinical studies need to shed light on the airway protection potential of approved B2R-antagonists, like icatibant, in the treatment of early-stage COVID-19.

Graphical Abstract

Key messages

Induction of kinin B2 receptor in the nose of SARS-CoV-2-positive patients.

Treatment with B2R-antagonist protects airway epithelial cells from SARS-CoV-2.

B2R-antagonist reduces ACE2 levels in vivo and ex vivo.

Protection by B2R-antagonist is mediated by inhibiting viral replication and spread.
Global Existence for the N Body Euler–Poisson System
Authors: Parmeshwar Shrish 
Published: March 2022

AbstractIn this paper we investigate the problem of multiple expanding Newtonian stars that interact via their gravitational effect on each other. It is clear physically that if two stars at rest are separated initially, and start expanding as well as moving according to the laws of Newtonian gravity, they may eventually collide. Thus, one can ask whether each star can be given an initial position and velocity such that they can keep expanding without touching. We show that even with gravitational interaction between the bodies, a large class of initial positions and velocities give global-in-time solutions to the N Body Euler–Poisson system. To do this we use scaling mechanisms present in the compressible Euler system, shown in Parmeshwar (Quart Appl Math 79(2):273–334, 2021), gaining advantageous time weights and smallness in our estimates under the specific form of the Lagrangian flow maps, and assumption of small mass for each star, represented by a parameter $$\delta $$
δ
. This is combined with a careful analysis of how the gravitational interaction between stars affects their dynamics.
Homogenization of the elastic-viscoplastic damage behavior of asphalt mixtures based on the mesomechanical Mori–Tanaka method
Authors: Du Cong , Liu Pengfei , Oeser Markus 
Published: March 2022

AbstractTo improve the efficiency and accuracy in characterizing the nonlinear behavior of multi-phased asphalt mixtures and to further facilitate asphalt pavement design based on the nonlinear properties, this study proposes a homogenized method for the elastic-viscoplastic-damage constitutive model. The Drucker–Prager-type yield surfaces and non-association flow rule were employed to describe the viscoplastic strain of asphalt materials. The continuum damage mechanics (CDM) were incorporated to characterize the evolutions of internal micro-cracks or micro-voids in structures. The mesomechanical Mori–Tanaka (MT) method was used to yield the homogenized nonlinear strain components within multi-phase structures. The proposed constitutive model was then implemented in finite element (FE) simulations based on a self-developed subroutine. Several case studies were conducted, in which composite structures with one inclusion were simulated under constant stress and strain loading rate. Amongst the composite structures, the inclusions with various volume contents and shapes were taken into account. In addition, the influence of air voids in structures was considered by defining the zero stiffness for inclusions. The results indicated that the nonlinear behavior of composite with single aggregate or air void can be effectively represented using the proposed method. Furthermore, by coupling the homogenized nonlinear constitutive relation into the locally homogenous model from previous work, not only was the viscoplastic-damage behavior of the composite with multiple inclusions effectively demonstrated by the definition of the nonlinear material, but the internal heterogeneous feature was also precisely represented by the local cells. Therefore, the proposed homogenized method can effectively predict the viscoplastic and damage behavior of asphalt mixtures with various inclusions by simply specifying the parameters in the FE simulations.
Predictive value of postoperative day 1 parathyroid hormone levels for early and late hypocalcaemia after thyroidectomy
Authors: Riordan Fiona , Brophy Catherine , Murphy Matthew S. , Sheahan Patrick 
Published: March 2022

Abstract
Purpose
Early parathyroid hormone (PTH) levels after total thyroidectomy can predict patients at low risk of hypocalcaemia who can be discharged early without calcium supplementation. For centres without facility to perform early PTH levels, PTH levels sent on the first postoperative day (POD1) may be an alternative. However, there is less data regarding optimal cut-off PTH levels for POD1 discharge.

Methods
Retrospective review of prospective database of thyroid operations between September 2009 and February 2020 at tertiary referral centre. Main outcome measure was symptomatic hypocalcaemia.

Results
Five hundred seventy patients undergoing total (521) or completion thyroidectomy with POD1 PTH levels available were included. Among patients with POD1 PTH levels ≥ 20 pg/ml and POD1 calcium ≥ 2.0 mmol/l, the incidence of symptomatic hypocalcaemia was 1% (3/300), and need for intravenous calcium 0.3% (1/300). For POD1 PTH levels 15–19 pg/ml and POD1 calcium ≥ 2.0 mmol/l, the incidence of symptomatic hypocalcaemia and need for intravenous calcium was 5.4% (3/55). For PTH levels 10–14 pg/ml and calcium ≥ 2.0 mmol/l, the incidence of symptomatic hypocalcaemia and need for intravenous calcium was 11.7% (7/60). The risk of permanent hypoparathyroidism was < 1% for POD1 PTH levels ≥ 15 pg/ml; 5.4% for levels 10–14 pg/ml; and 19.8% for levels < 10 pg/ml.

Conclusions
POD1 PTH levels ≥ 15 pg/ml along with calcium ≥ 2.0 mmol/l are associated with low risk of symptomatic hypocalcaemia, and represent a safe criterion for discharge of most patients without calcium supplementation. For certain patient groups, a higher threshold of 20 pg/ml could be considered.
Large deflection of composite beams by finite elements with node-dependent kinematics
Authors: Carrera E. , Pagani A. , Augello R. 
Published: March 2022

AbstractIn this paper, the use of the node-dependent kinematics concept for the geometrical nonlinear analysis of composite one-dimensional structures is proposed With the present approach, the kinematics can be independent in each element node. Therefore the theory of structures changes continuously over the structural domain, describing remarkable cross-section deformation with higher-order kinematics and giving a lower-order kinematic to those portion of the structure which does not require a refinement. In this way, the reliability of the simulation is ensured, keeping a reasonable computational cost. This is possible by Carrera unified formulation, which allows writing finite element nonlinear equilibrium and incremental equations in compact and recursive form. Compact and thin-walled composite structures are analyzed, with symmetric and unsymmetric loading conditions, to test the present approach when dealing with warping and torsion phenomena. Results show how finite element models with node-dependent behave as well as ones with uniform highly refined kinematic. In particular, zones which undergo remarkable deformations demand high-order theories of structures, whereas a lower-order theory can be employed if no local phenomena occur: this is easily accomplished by node-dependent kinematics analysis.