bluuebunny/crossref_metadata_2025 huggingface dataset:
Test zur Einschätzung wissenschaftlicher Widersprüche (TEWI): Messung wissenschaftsbezogenen Reflexionsvermögens in der Sekundarstufe II
Authors: Kramer Jochen , Thomm Eva , Oschatz-Grant Kerstin , Wagner Wolfgang , Bromme Rainer
Published: December 2021

Wissenschaftspropädeutik gehört zu den drei zentralen Bildungszielen der gymnasialen Oberstufe. Aufgrund eines Mangels an geeigneten Untersuchungsinstrumenten, gibt es jedoch kaum Studien zur Erreichung dieses Bildungsziels oder seines Einflusses auf den Werdegang junger Menschen. Im vorliegenden Beitrag werden die theoretischen Ansätze zur Wissenschaftspropädeutik kurz erläutert, bestehende Strukturmodelle vorgestellt und als zentrale Elemente die fächerübergreifende Denkweise und die kritisch-reflexive Perspektive auf Wissenschaft herausgearbeitet. Wissenschaftsbezogene Reflexionskompetenz im Umgang mit Widersprüchen in der Wissenschaft wird als eine Kernkomponente von Wissenschaftspropädeutik skizziert. Sie bildet auch den Ausgangspunkt für die Entwicklung des Tests zur Einschätzung wissenschaftlicher Widersprüche (TEWI) für das nationale Bildungspanel (NEPS). Im empirischen Teil werden Befunde zur Entwicklung und Pilotierung des TEWI sowie eine Studie zur konvergenten Konstruktvalidierung (N = 394) des TEWI vorgestellt. Die Ergebnisse weisen den TEWI als reliables Instrument mit zufriedenstellenden Skalierungseigenschaften aus.
Rigid-Body Analysis of a Beveled Shape Structure in Regular Waves Using the Weakly Compressible Smoothed Particle Hydrodynamics (WCSPH) Method
Authors: Hikmatullah Sahib Siti Ayishah Thaminah , Ramli Muhammad Zahir , Azman Muhammad Afiq , Abd Rahman Muhammad Mazmirul , Miskon Mohd Fuad , Ariffin Effi Helmy , Jeofry Muhammad Hafeez , Yunus Kamaruzzaman
Published: December 2021

In many cases of wave structure interactions, three-dimensional models are used to demonstrate real-life complex environments in large domain scales. In the seakeeping context, predicting the motion responses in the interaction of a long body resembling a ship structure with regular waves is crucial and can be challenging. In this work, regular waves interacting with a rigid floating structure were simulated using the open-source code based on the weakly compressible smoothed particle hydrodynamics (WCSPH) method, and optimal parameters were suggested for different wave environments. Vertical displacements were computed, and their response amplitude operators (RAOs) were found to be in good agreement with experimental, numerical, and analytical results. Discrepancies of numerical and experimental RAOs tended to increase at low wave frequencies, particularly at amidships and near the bow. In addition, the instantaneous wave contours of the surrounding model were examined to reveal the effects of localized waves along the structure and wave dissipation. The results indicated that the motion response from the WCSPH responds well at the highest frequency range (ω > 5.235 rad/s).
Artificial Intelligence in Current Diabetes Management and Prediction
Authors: Nomura Akihiro , Noguchi Masahiro , Kometani Mitsuhiro , Furukawa Kenji , Yoneda Takashi
Published: December 2021

Purpose of Review

Artificial intelligence (AI) can make advanced inferences based on a large amount of data. The mainstream technologies of the AI boom in 2021 are machine learning (ML) and deep learning, which have made significant progress due to the increase in computational resources accompanied by the dramatic improvement in computer performance. In this review, we introduce AI/ML-based medical devices and prediction models regarding diabetes.

Recent Findings

In the field of diabetes, several AI-/ML-based medical devices and regarding automatic retinal screening, clinical diagnosis support, and patient self-management tool have already been approved by the US Food and Drug Administration. As for new-onset diabetes prediction using ML methods, its performance is not superior to conventional risk stratification models that use statistical approaches so far.

Despite the current situation, it is expected that the predictive performance of AI will soon be maximized by a large amount of organized data and abundant computational resources, which will contribute to a dramatic improvement in the accuracy of disease prediction models for diabetes.
Autoimmune Inflammation and Insulin Resistance: Hallmarks So Far and Yet So Close to Explain Diabetes Endotypes
Authors: Petrelli Alessandra , Giovenzana Anna , Insalaco Vittoria , Phillips Brett E. , Pietropaolo Massimo , Giannoukakis Nick
Published: December 2021

Purpose of Review

Diabetes mellitus can be categorized into two major variants, type 1 and type 2. A number of traits such as clinical phenotype, age at disease onset, genetic background, and underlying pathogenesis distinguish the two forms.

Recent Findings

Recent evidence indicates that type 1 diabetes can be accompanied by insulin resistance and type 2 diabetes exhibits self-reactivity. These two previously unknown conditions can influence the progression and outcome of the disease. Unlike most conventional considerations, diabetes appears to consist of a spectrum of intermediate phenotypes that includes monogenic and polygenic loci linked to inflammatory processes including autoimmunity, beta cell impairment, and insulin resistance.

Here we discuss why a shift of the classical bi-modal view of diabetes (autoimmune vs. non-autoimmune) is necessary in favor of a model of an immunological continuum of endotypes lying between the two extreme “insulin-resistant” and “autoimmune beta cell targeting,” shaped by environmental and genetic factors which contribute to determine specific immune-conditioned outcomes.
Older People in Germany During the COVID-19 Pandemic:The Least, the More, and the Most Affected
Authors: Horn Vincent , Semmler Malte , Schweppe Cornelia
Published: December 2021

Older people have been identified as a particularly vulnerable group during the COVID-19 pandemic. However, the question of how older people actually fared during the COVID-19 pandemic has only been sporadically addressed. This article aims to partly fill this gap by classifying subgroups of older people using Latent Class Analysis. Indicators used are: risk perception, safety behavior, and well-being. To predict subgroup membership, age, gender, living arrangement, children, chronic illness, conflict, socioeconomic status, and migration history are controlled for. The data analyzed stem from a phone survey among 491 older people (75–100 years) in Germany conducted in September/October 2020. Results show that three subgroups of older people – the least, the more and the most affected – can be formed based on their risk perception, safety behavior, and well-being, indicating the usefulness of these three constructs for identifying and studying older people particularly affected by the COVID-19 pandemic and the measures taken to contain it.
The application of probabilistic linguistic CODAS method based on new score function in multi-criteria decision-making
Authors: Chen Liuxin , Gou Xiaoling
Published: December 2021

Probabilistic linguistic term sets (PLTSs) play an important role in multi-criteria decision-making(MCDM) problems because it can not only describe objects with several possible linguistic terms, but also represent the proportion of each linguistic term, which can effectively avoid the distortion of decision information to a greater extent and ensure the credibility of decision results. First, to compare PLTS more simply and reasonably, we define a new score function that takes into account partial deviations. Then considering the superiority of the classic combinative distance-based assessment (CODAS) method in the complete representation of information, it is extended to the probabilistic linguistic environment. Subsequently, we improved the classic CODAS method and proposed the PL-CODAS method. Finally, we apply the PL-CODAS method to a cases of venture investors choosing emerging companies, and we compare the proposed method with PL-TOPSIS method, PL-TODIM method and PL-MABAC method to verify its applicability and effectiveness.
P-adic L-functions in universal deformation families
Authors: Loeffler David
Published: December 2021

We construct examples of p-adic L-functions over universal deformation spaces for $${{\,\mathrm{GL}\,}}_2$$

GL

2

. We formulate a conjecture predicting that the natural parameter spaces for p-adic L-functions and Euler systems are not the usual eigenvarieties (parametrising nearly-ordinary families of automorphic representations), but other, larger spaces depending on a choice of a parabolic subgroup, which we call ‘big parabolic eigenvarieties’.
Scalable and distributed strategies for socially distanced human mobility
Authors: Roy Satyaki , Ghosh Preetam
Published: December 2021

COVID-19 is a global health crisis that has caused ripples in every aspect of human life. Amid widespread vaccinations testing, manufacture and distribution efforts, nations still rely on human mobility restrictions to mitigate infection and death tolls. New waves of infection in many nations, indecisiveness on the efficacy of existing vaccinations, and emerging strains of the virus call for intelligent mobility policies that utilize contact pattern and epidemiological data to check contagion. Our earlier work leveraged network science principles to design social distancing optimization approaches that show promise in slowing infection spread however, they prove to be computationally prohibitive and require complete knowledge of the social network. In this work, we present scalable and distributed versions of the optimization approaches based on Markov Chain Monte Carlo Gibbs sampling and grid-based spatial parallelization that tackle both the challenges faced by the optimization strategies. We perform extensive simulation experiments to show the ability of the proposed strategies to meet necessary network science measures and yield performance comparable to the optimal counterpart, while exhibiting significant speed-up. We study the scalability of the proposed strategies as well as their performance in realistic scenarios when a fraction of the population temporarily flouts the location recommendations.
Maximal regularity and a singular limit problem for the Patlak–Keller–Segel system in the scaling critical space involving BMO
Authors: Kurokiba Masaki , Ogawa Takayoshi
Published: December 2021

We consider a singular limit problem of the Cauchy problem for the Patlak–Keller–Segel equation in a scaling critical function space. It is shown that a solution to the Patlak–Keller–Segel system in a scaling critical function space involving the class of bounded mean oscillations converges to a solution to the drift-diffusion system of parabolic-elliptic type (simplified Keller–Segel model) strongly as the relaxation time parameter $$\tau \rightarrow \infty $$

τ
→
∞

. For the proof, we show generalized maximal regularity for the heat equation in the homogeneous Besov spaces and the class of bounded mean oscillations and we utilize them systematically as well as the continuous embeddings between the interpolation spaces $$\dot{B}^s_{q,\sigma }({\mathbb {R}}^n)$$

B
˙

q
,
σ

s

(

R

n

)

and $$\dot{F}^s_{q,\sigma }({\mathbb {R}}^n)$$

F
˙

q
,
σ

s

(

R

n

)

for the proof of the singular limit. In particular, end-point maximal regularity in BMO and space time modified class introduced by Koch–Tataru is utilized in our proof.
Multiple Attribute Decision-Making Method Based upon Intuitionistic Fuzzy Partitioned Dual Maclaurin Symmetric Mean Operators
Authors: Wang HongJuan , Liu Yi , Liu Fang , Lin Jun
Published: December 2021

We propound the idea of the partitioned dual Maclaurin symmetric mean (PDMSM) operator stimulated by the partitioned Maclaurin symmetric mean, suppose that we can partition overall attributes into some portions and the attributes are interrelated in the same portion, but the attributes are not interrelated in different portions. We can deal with decision-making issues using PDMSM operator in the intuitionistic fuzzy environment. We also analysis features and peculiar instance of the PDMSM operator. And, we extend the PDMSM operator to introduce the intuitionistic fuzzy partitioned dual Maclaurin symmetric mean operator and the weighted intuitionistic fuzzy partitioned dual Maclaurin symmetric mean operator. Then, we analysis several characteristics and peculiar instances of the developed operators. A new multiple attribute decision-making (MADM) approach grounded on the established weighted intuitionistic fuzzy partitioned dual Maclaurin symmetric mean operator is propounded; the MADM method is to choose the optimal alternative from several alternatives. Finally, we demonstrate the designed method is more general and effective than existing methods through comparative analysis.
A Bi-directional Fuzzy C-Means Clustering Ensemble Algorithm Considering Local Information
Authors: Ren Chunhua , Sun Linfu
Published: December 2021

The classic Fuzzy C-means (FCM) algorithm has limited clustering performance and is prone to misclassification of border points. This study offers a bi-directional FCM clustering ensemble approach that takes local information into account (LI_BIFCM) to overcome these challenges and increase clustering quality. First, various membership matrices are created after running FCM multiple times, based on the randomization of the initial cluster centers, and a vertical ensemble is performed using the maximum membership principle. Second, after each execution of FCM, multiple local membership matrices of the sample points are created using multiple K-nearest neighbors, and a horizontal ensemble is performed. Multiple horizontal ensembles can be created using multiple FCM clustering. Finally, the final clustering results are obtained by combining the vertical and horizontal clustering ensembles. Twelve data sets were chosen for testing from both synthetic and real data sources. The LI_BIFCM clustering performance outperformed four traditional clustering algorithms and three clustering ensemble algorithms in the experiments. Furthermore, the final clustering results has a weak correlation with the bi-directional cluster ensemble parameters, indicating that the suggested technique is robust.
Modeling of Passenger Transport Logistics Based on Intelligent Computational Techniques
Authors: Suraj Zbigniew , Olar Oksana , Bloshko Yurii
Published: December 2021

The paper describes the analysis of the application of classic and optimized triangular norms in the hierarchical structure of weighted fuzzy Petri nets on the example of passenger transport logistics. The research is presented in a scheme with several levels of tasks. Each task includes some knowledge sets which were previously given by the experts and set into tables of “Object–property” type. It leads to the creation of a hierarchical structure of weighted fuzzy Petri net model which includes 125 possible combinations of triples of functions for calculation processing. A classic triple of functions (ZtN, GtN, ZsN) is tested and compared with an optimized triple (ZtN, ZtN, LsN). Additional verification methods are applied to confirm the practical usefulness of these triples. These techniques imply the use of additional triples which can be associated with each other along with practically efficient mathematical calculations.
A Cooperative Coevolution Wingsuit Flying Search Algorithm with Spherical Evolution
Authors: Yang Jiaru , Zhang Yu , Wang Ziqian , Todo Yuki , Lu Bo , Gao Shangce
Published: December 2021

The algorithm wingsuit flying search (WFS) mimics the procedure of landing the vehicle. The outstanding feature of WFS is parameterless and of rapid convergence. However, WFS also has its shortcomings, sometimes it will inevitably be trapped into local optima, thereby yield inferior solutions owing to its relatively weak exploration ability. Spherical evolution (SE) adopts a novel spherical search pattern that takes aim at splendid search ability. Cooperative coevolution is a useful parallel structure for reconciling algorithmic performance. Considering the complementary strengths of both algorithms, we herein propose a new hybrid algorithm that is comprised of SE and WFS using cooperative coevolution. During the search for optimal solutions in WFS, we replaced the original search matrix and introduced the spherical mechanism of SE, in parallel with coevolution to enhance the competitiveness of the population. The two distinct search dynamics were combined in a parallel and coevolutionary way, thereby getting a good search performance. The resultant hybrid algorithm, CCWFSSE, was tested on the CEC2017 benchmark set and 22 CEC 2011 real-world problems. The experimental data obtained can verify that CCWFSSE outperforms other algorithms in aspects of effectiveness and robustness.
Some Inequalities for LR-$$\left({h}_{1}, {h}_{2}\right)$$-Convex Interval-Valued Functions by Means of Pseudo Order Relation
Authors: Khan Muhammad Bilal , Noor Muhammad Aslam , Noor Khalida Inayat , Nisar Kottakkaran Sooppy , Ismail Khadiga Ahmed , Elfasakhany Ashraf
Published: December 2021

In both theoretical and applied mathematics fields, integral inequalities play a critical role. Due to the behavior of the definition of convexity, both concepts convexity and integral inequality depend on each other. Therefore, the relationship between convexity and symmetry is strong. Whichever one we work on, we introduced the new class of generalized convex function is known as LR-$$\left({h}_{1}, {h}_{2}\right)$$h1,h2-convex interval-valued function (LR-$$\left({h}_{1}, {h}_{2}\right)$$h1,h2-IVF) by means of pseudo order relation. Then, we established its strong relationship between Hermite–Hadamard inequality (HH-inequality)) and their variant forms. Besides, we derive the Hermite–Hadamard–Fejér inequality (HH–Fejér inequality)) for LR-$$\left({h}_{1}, {h}_{2}\right)$$h1,h2-convex interval-valued functions. Several exceptional cases are also obtained which can be viewed as its applications of this new concept of convexity. Useful examples are given that verify the validity of the theory established in this research. This paper’s concepts and techniques may be the starting point for further research in this field.
Coupling Normalization with Moving Window in Backpropagation Neural Network (BNN) for Passive Microwave Soil Moisture Retrieval
Authors: Chai Soo See , Goh Kok Luong , Chang Yee Hui Robin , Sim Kwan Yong
Published: December 2021

A common practice to capture the non-stationary characteristics of the time series data in Artificial Neural Network (ANN) is by randomly dividing the whole set of available data into training, validation and testing, i.e. the data in validation and testing are represented in the training data. Consequently, the usability of the developed model on data not represented by the training data used during the network model development process is always doubtful. In this work, we present a back-propagation neural network (BNN) model trained using one-day history data to predict soil moisture data at 1 km resolution for two future dates. Specifically, high soil moisture values were observed in the training data while the testing data were characterized by drier conditions due to minimal or no rainfall. Our model uses separate mean and standard deviation statistics values from the training and testing data, respectively, to the z-normalized data. With data pre-processed using this method, the BNN model next uses a moving window of size 4 km × 4 km to capture the spatial variability of the soil moisture throughout the 40 km × 40 km study area. The coupling of the normalization and moving window method managed to achieve average soil moisture with Root Mean Square (RMSE) of 3.67% and correlation coefficient,R2of 0.89. By only using the suggested normalization without the moving window method, the BNN model managed to achieve an average RMSE of barely 5.82% withR2 = 0.83. When comparing with the normal practice of using the same mean and standard deviation statistics of the training data in the testing data, the retrieval accuracy of the BNN model deteriorates to 8.86% withR2 = 0.32. The experiment results demonstrated that the proposed coupling method performed better in terms of both RMSE and R2for soil moisture retrieval.
A Multi-Agent Linguistic-Style Large Group Decision-Making Method Considering Public Expectations
Authors: Zhu Gui-ju , Cai Chen-guang , Pan Bin , Wang Pei
Published: December 2021

Focusing on the characteristics of public participation and large group decision making of major livelihood projects, this paper proposes a multi-agent linguistic-style large group decision-making method with the consideration of public expectations. Firstly, based on the discrimination degree of evaluating information, the comprehensive weight of each attribute is calculated with the principle of maximum entropy. Secondly, the expert preference information for different alternatives is clustered and several aggregations are formed. Thirdly, the preference conflict level of experts' group for each alternative is calculated, and a conflict-oriented experts' aggregation weight optimization model is constructed to ensure the effectiveness of conflict resolution. Fourthly, the public group's satisfaction is determined with the expectation distribution of public’s and the expert group's preference, so as to obtain the sorting result of the decision alternatives. Finally, the effectiveness and applicability of the proposed method are verified by method comparison.
Computer-Aided Diagnosis for Pneumoconiosis Staging Based on Multi-scale Feature Mapping
Authors: Zhang Yuan
Published: December 2021

In this research, we explored a method of multi-scale feature mapping to pre-screen radiographs quickly and accurately in the aided diagnosis of pneumoconiosis staging. We utilized an open dataset and a self-collected dataset as research datasets. We proposed a multi-scale feature mapping model based on deep learning feature extraction technology for detecting pulmonary fibrosis and a discrimination method for pneumoconiosis staging. The diagnostic accuracy was evaluated using under the curve (AUC) of the receiver operating characteristic (ROC) curve. The AUC value of our model was 0.84, which showed the best performance compared with previous work on datasets. The diagnosis results indicated that our method was highly consistent with that of clinical experts on real patient. Furthermore, the AUC value obtained through categories I–IV on the testing dataset demonstrated that categories I (AUC = 0.86) and IV (AUC = 0.82) obtained the best performance and achieved the level of clinician categorization. Our research could be applied to the pre-screening and diagnosis of pneumoconiosis in the clinic.
Low Admission Immunoglobulin G Levels Predict Poor Outcome in Patients with Mild-to-Critical COVID-19: A Prospective, Single-Center Study
Authors: Vrettou Charikleia S. , Vassiliou Alice G. , Kakkas Ioannis , Jahaj Edison , Tsipilis Stamatios , Athanasiou Nikolaos , Zacharis Alexandros , Keskinidou Chrysi , Papageorgiou Aikaterini , Orfanos Stylianos E. , Kotanidou Anastasia , Dimopoulou Ioanna
Published: December 2021

Introduction

Immunoglobulins (Igs) comprise a critical part of the immune response. Little information exists on Ig serum levels in COVID-19 patients. We, therefore, investigated whether hospital admission Igs in patients with mild-to-critical disease are associated with clinical outcome.

Materials and Methods

This prospective, observational, single-center, cross-sectional study included 126 consecutive non-critically ill and critically ill and COVID-19 patients, in whom IgG, IgM, and IgA were measured on hospital admission.

Results

The cohort was divided in survivors and non-survivors, based on in-hospital mortality. Median IgG levels of survivors were significantly higher than non-survivors (p < 0.01). The cohort was subsequently divided in IgG deficient (< 690 mg/dl) and sufficient (≥ 690 mg/dl) patients. IgG-deficient patients had a higher mortality rate (p < 0.01). The multivariate logistic regression model showed that subnormal IgG was significantly associated with increased mortality risk (p < 0.01).

Conclusion

In our COVID-19 cohort, admission subnormal IgG levels might be independently associated with reduced survival.
The Tsunami of COVID-19 Infection Among Kidney Transplant Recipients: A Single-Center Study from Iran
Authors: Rahimzadeh Hormat , Tamehri Zadeh Seyed Saeed , Khajavi Alireza , Saatchi Mohammad , Reis Leonardo Oliveira , Guitynavard Fateme , Dehghani Sanaz , Soleimani Venus , Aghamir Seyed Mohammad Kazem
Published: December 2021

Background

Although most evidence supports the fact that kidney transplant (KT) recipients are at significant risk of morbidity and mortality, risk factors of accruing COVID-19 in this population have remained poorly defined.

Methods

All KT recipients who had been transplanted in Sina Hospital and were actively followed between March 1996 and January 2021 were enrolled in a retrospective manner. The demographic characteristics, immunosuppressive treatment before KT, and death were gathered by calling patients with a designed questionnaire.

Results

108 (about 21%) of 523 KT recipients were diagnosed with COVID-19. The mean age of COVID-19 patients was 46.9 ± 13.6, of whom 43% were women. In the multivariate model, body mass index (BMI) ≥ 30 independently increased the risk of COVID-19 incidence with OR 2.00 (95% CI 1.23, 3.26) (P = 0.00), and besides, having diabetes had a marginal association with COVID-19 incidence (OR 1.62 [95% CI 0.98, 2.66];P = 0.057). The mortality rate of COVID-19 was 15%. In the multivariate model, only pre-transplantation diabetes significantly increased the risk of death by COVID-19 with OR of 3.90 (95% CI 1.00–15.16) (P = 0.04).

Conclusion

Given the higher incidence rate in KT recipients with obesity and diabetes and higher mortality rate in KT recipients with diabetes as the cause of ESRD, more attention should be paid to KT recipients with these risk factors.
Riemann–Hilbert Problem Associated with the Fourth-Order Dispersive Nonlinear Schrödinger Equation in Optics and Magnetic Mechanics
Authors: Hu Beibei , Zhang Ling , Li Qinghong , Zhang Ning
Published: December 2021

In this paper, by using Fokas method, we study the initial-boundary value problems (IBVPs) of the fourth-order dispersive nonlinear Schrödinger (FODNLS) equation on the half-line, which can simulate the nonlinear transmission and interaction of ultrashort pulses in the high-speed optical fiber transmission system, and can also describe the nonlinear spin excitation phenomenon of one-dimensional Heisenberg ferromagnetic chain with eight poles and dipole interaction. By discussing the eigenfunctions of Lax pair of FODNLS equation and analyzing symmetry of the scattering matrix, we get a matrix Riemann–Hilbert (RH) problem from for the IBVPs of FODNLS equation. Moreover, we get the potential function solution u(x, t) of the FODNLS equation by solving this matrix RH problem. In addition, we also obtain that some spectral functions satisfy an important global relation.
Symmetry-Preserving Difference Models of Some High-Order Nonlinear Integrable Equations
Authors: Zhao Zhonglong
Published: December 2021

In this paper, a procedure for constructing the symmetry-preserving difference models by means of the potential systems is employed to investigate some kinds of integrable equations. The invariant difference models for the Benjamin–Ono equation and the nonlinear dispersive $$K\left( {m,n} \right)$$

K

m
,
n

equation are investigated. Four cases of $$K\left( {m,n} \right)$$

K

m
,
n

equations which yield compactons are studied. The invariant difference models preserving all the symmetries are obtained. Furthermore, some linear combinations of the symmetries are used to construct the invariant difference models. The invariant difference model of the Hunter–Saxton equation is constructed. The idea of this paper can be further extended to discrete some other high-order nonlinear integrable equations.
Dirac–Witten Operators and the Kastler–Kalau–Walze Type Theorem for Manifolds with Boundary
Authors: Wu Tong , Wang Jian , Wang Yong
Published: December 2021

In this paper, we obtain two Lichnerowicz type formulas for the Dirac–Witten operators. And we give the proof of Kastler–Kalau–Walze type theorems for the Dirac–Witten operators on 4-dimensional and 6-dimensional compact manifolds with (resp. without) boundary.
Cluster’s Number Free Bayes Prediction of General Framework on Mixture of Regression Models
Authors: Murayama Haruka , Saito Shota , Iikubo Yuji , Nakahara Yuta , Matsushima Toshiyasu
Published: December 2021

Prediction based on a single linear regression model is one of the most common way in various field of studies. It enables us to understand the structure of data, but might not be suitable to express the data whose structure is complex. To express the structure of data more accurately, we make assumption that the data can be divided in clusters, and has a linear regression model in each cluster. In this case, we can assume that each explanatory variable has their own role; explaining the assignment to the clusters, explaining the regression to the target variable, or being both of them. Introducing probabilistic structure to the data generating process, we derive the optimal prediction under Bayes criterion and the algorithm which calculates it sub-optimally with variational inference method. One of the advantages of our algorithm is that it automatically weights the probabilities of being each number of clusters in the process of the algorithm, therefore it solves the concern about selection of the number of clusters. Some experiments are performed on both synthetic and real data to demonstrate the above advantages and to discover some behaviors and tendencies of the algorithm.
From libertarian paternalism to liberalism: behavioural science and policy in an age of new technology
Authors: Krpan Dario , Urbaník Milan
Published: December 2021

Behavioural science has been effectively used by policy makers in various domains, from health to savings. However, interventions that behavioural scientists typically employ to change behaviour have been at the centre of an ethical debate, given that they include elements of paternalism that have implications for people's freedom of choice. In the present article, we argue that this ethical debate could be resolved in the future through implementation and advancement of new technologies. We propose that several technologies which are currently available and are rapidly evolving (i.e., virtual and augmented reality, social robotics, gamification, self-quantification, and behavioural informatics) have a potential to be integrated with various behavioural interventions in a non-paternalistic way. More specifically, people would decide themselves which behaviours they want to change and select the technologies they want to use for this purpose, and the role of policy makers would be to develop transparent behavioural interventions for these technologies. In that sense, behavioural science would move from libertarian paternalism to liberalism, given that people would freely choose how they want to change, and policy makers would create technological interventions that make this change possible.
Time to relapse of severe acute malnutrition and risk factors among under-five children treated in the health posts of Hadiya Zone, Southern Ethiopia
Authors: Lambebo Abera , Tamiru Dessalegn , Belachew Tefera
Published: December 2021

Relapse/repeated episodes are defined as the admission of a child with a diagnosis of severe acute malnutrition (SAM) after being discharged with a status of recovery. However, there is a lack of study that documented the time to relapse of SAM and its risk factors. The present study aimed to identify the time of relapse and its risk factor among under-five children discharged after undergoing treatment for SAM in health facilities of Hadiya Zone, South Ethiopia. An institution-based retrospective cohort study was carried out in the Hadiya Zone of Southern Ethiopia among under-five children. Data were collected from 760 cards of severe acute malnourished children over the past 5 years spanning from 2014/15 to 2019/20. Both first admission and relapse data were abstracted from the records of the SAM children from 1 August to 30 August 2020 and cards of children that were admitted to program by transferee with complete records were included. After checking all the assumptions, multivariable Cox Proportional Hazards model was fitted to isolate independent determinants of time to cure. All tests were two-sided and statistical significance at P-values < 0⋅05. The mean(±sd) time for relapse of SAM among under-five children was 22(±9⋅9) weeks from discharge to relapse time. On multivariable Cox Proportional Hazards model, the hazard of relapse for SAM was significantly higher for children who had oedema (AHR 2⋅02, 95 % CI 1⋅17, 3⋅50), age of 6–11 months (AHR 5⋅2, 95 % CI 1⋅95, 13⋅87) had discharge MUAC not cured (AHR12, 95% CI 7⋅90, 19⋅52). The finding showed that children discharged from SAM are likely to have relapse in 3 weeks time.
On the number of conjugacy classes of a primitive permutation group
Authors: Garzoni Daniele , Gill Nick
Published: December 2021

Let $G$ be a primitive permutation group of degree $n$ with nonabelian socle, and let $k(G)$ be the number of conjugacy classes of $G$. We prove that either $k(G)< n/2$ and $k(G)=o(n)$ as $n\rightarrow \infty$, or $G$ belongs to explicit families of examples.
Spreading speeds and traveling wave solutions of diffusive vector-borne disease models without monotonicity
Authors: Wang Xinjian , Lin Guo , Ruan Shigui
Published: December 2021

Vector-borne diseases, such as chikungunya, dengue, malaria, West Nile virus, yellow fever and Zika, pose a major global public health problem worldwide. In this paper we investigate the propagation dynamics of diffusive vector-borne disease models in the whole space, which characterize the spatial expansion of the infected hosts and infected vectors. Due to the lack of monotonicity, the comparison principle cannot be applied directly to this system. We determine the spreading speed and minimal wave speed when the basic reproduction number of the corresponding kinetic system is larger than one. The spreading speed is mainly estimated by the uniform persistence argument and generalized principal eigenvalue. We also show that solutions converge locally uniformly to the positive equilibrium by employing two auxiliary monotone systems. Moreover, it is proven that the spreading speed is the minimal wave speed of travelling wave solutions. In particular, the uniqueness and monotonicity of travelling waves are obtained. When the basic reproduction number of the corresponding kinetic system is not larger than one, it is shown that solutions approach to the disease-free equilibrium uniformly and there is no travelling wave solutions. Finally, numerical simulations are presented to illustrate the analytical results.
Liouville-type results for positive solutions of pseudo-relativistic Schrödinger system
Authors: Guo Yuxia , Peng Shaolong
Published: December 2021

In this paper, we are concerned with the physically engaging pseudo-relativistic Schrödinger system:
\[ \begin{cases} \left(-\Delta+m^{2}\right)^{s}u(x)=f(x,u,v,\nabla u) & \hbox{in } \Omega,\\ \left(-\Delta+m^{2}\right)^{t}v(x)=g(x,u,v,\nabla v) & \hbox{in } \Omega,\\ u>0,v>0 & \hbox{in } \Omega, \\ u=v\equiv 0 & \hbox{in } \mathbb{R}^{N}\setminus\Omega, \end{cases} \]where $s,t\in (0,1)$ and the mass $m>0.$ By using the direct method of moving plane, we prove the strict monotonicity, symmetry and uniqueness for positive solutions to the above system in a bounded domain, unbounded domain, $\mathbb {R}^{N}$, $\mathbb {R}^{N}_{+}$ and a coercive epigraph domain $\Omega$ in $\mathbb {R}^{N}$, respectively.
PROOF OF SOME CONJECTURAL CONGRUENCES OF DA SILVA AND SELLERS
Authors: SINGH AJIT , BARMAN RUPAM
Published: December 2021

Let
$p_{\{3, 3\}}(n)$
denote the number of
$3$
-regular partitions in three colours. Da Silva and Sellers [‘Arithmetic properties of 3-regular partitions in three colours’, Bull. Aust. Math. Soc.104(3) (2021), 415–423] conjectured four Ramanujan-like congruences modulo
$5$
satisfied by
$p_{\{3, 3\}}(n)$
. We confirm these conjectural congruences using the theory of modular forms.
Age-related hearing loss and mild cognitive impairment: a meta-analysis and systematic review of population-based studies
Authors: Lau K , Dimitriadis P A , Mitchell C , Martyn-St-James M , Hind D , Ray J
Published: December 2021

Background

The aim of this study was to identify any relationship between hearing loss and mild cognitive impairment.

Method

This was a systematic review and meta-analysis of randomised controlled trials conducted using Medline and the Cochrane Library up to 24 June 2020. Prospective, cohort and cross-sectional, and observational studies that reported on the relationship between mild cognitive impairment and hearing loss were included.

Results

A total of 34 studies reporting data on 48 017 participants were included. Twenty-three studies observed a significant association between hearing loss and mild cognitive impairment. The pooled risk ratio across all studies of prevalence of mild cognitive impairment in people with hearing loss was 1.44 (random-effects; 95 per cent CI = 1.27–1.64;p <0.00001; I2= 0 per cent). Significantly more people with mild cognitive impairment had peripheral hearing loss compared with those without (risk ratio, 1.40 random-effects; 95 per cent CI = 1.10–1.77;p =0.005; I2= 0 per cent). When the incidence was studied, significantly more people with peripheral hearing loss had mild cognitive impairment compared with those without (risk ratio = 2.06 random-effects; 95 per cent CI = 1.35–3.15;p =0.0008; I2= 97 per cent); however; a high level of statistical heterogeneity was evident.

Conclusion

Most of the studies included in this systematic review observed a significant association between hearing loss and mild cognitive impairment.
Metal accumulation in ecto- and endoparasites from the anadromous fish, the Pontic shad (Alosa immaculata)
Authors: Nachev M. , Rozdina D. , Michler-Kozma D. N. , Raikova G. , Sures B.
Published: December 2021

Among the parasitic taxa studied for their metal accumulation properties, especially Acanthocephala and Cestoda proved to be promising sentinels for metal pollution. However, studies on metal accumulation are still sparse for other parasite groups, mainly due to their small body size. In the present study, we collected the relatively large-sized monogenean Mazocraes alosae Hermann, 1782 from the gills of Pontic Shad (Alosa immaculata Bennet 1835) from its spawning region – the Danube River. The host tissues gills, muscle, intestine and liver, the monogeneans as well as the nematode Hysterothylacium aduncum (Rudolphi, 1802), in the cases of coinfected fish, were analysed for the elements As, Cd, Co, Cu, Fe, Mn, Pb, Se and Zn. All elements (except of As) were found in higher concentrations in monogeneans and nematodes compared to host muscle tissue. High bioconcentration factors were obtained for toxic elements such as Cd and Pb with concentrations being approximately 12 and 251 times higher in monogeneans and 773 and 33 in nematodes, respectively, as compared to host muscle tissue. In comparison to other host organs, however, some elements were found in similar or even lower concentrations in the parasites. Thus, monogeneans do not exhibit the high accumulation potential reported for other parasitic taxa. Physiological adaptations of the migratory host fish between freshwater and marine habitats with differences in uptake pathways and biological availability of elements can be discussed as a possible explanation for this divergent accumulation pattern.
Scanning electron microscopy of Quilonia renniei from Asian elephants revealing variation in coronal leaflet number
Authors: Chel Hla Myet , Bawm Saw , Htun Lat Lat , Masum Md. Abdul , Ichii Osamu , Nonaka Nariaki , Nakao Ryo , Katakura Ken
Published: December 2021

Although parasitic nematodes in the genera Murshidia and Quilonia (family Strongylidae) are recognized as major gastrointestinal parasites in Asian elephants, they have been poorly studied. Recently, light micrographs of these parasites in Myanmar have been presented, almost 100 years after the original drawings. However, the number of coronal leaflets, a key taxonomic feature of Quilonia species, has not been precisely determined based on light microscopy. The current study aimed to determine the exact number of coronal leaflets in Quilonia renniei specimens from Asian elephants in Myanmar. On the basis of scanning electron micrographs, leaflet number in females (19–20, average 19.7, n = 9) was significantly higher (P < 0.005) than that in males (16–19, average 18.1, n = 8). This compares with 18 coronal leaflets indicated in the original species description. Specimens bearing 19 coronal leaflets were most numerous, followed by those with 20 leaflets. Median-joining network analysis of mitochondrial cytochrome c oxidase subunit I gene sequences with 16 haplotypes from 19 individuals revealed no clear association between parasite populations and the number of coronal leaflets. These results highlight the importance of determining the number of coronal leaflets in the taxonomy of Q. renniei and other related Quilonia species infecting Asian elephants.
Alongside Slavery's Asides: Reverberations of Edward Young'sThe Revenge
Authors: Huang Amy B.
Published: December 2021

In an 1847 lecture before the Female Anti-Slavery Society of Salem, William Wells Brown stated: “Were I about to tell you the evils of Slavery, to represent to you the Slave in his lowest degradation, I should wish to take you, one at a time, and whisper it to you. Slavery has never been represented; Slavery never can be represented.” In these oft-cited lines, Wells Brown makes a strong claim for the absolute impossibility of representing slavery. But I wish to pause and stay with his earlier suggestion that it might just be possible to tell about slavery in a whisper. Breaking through the fastidiousness of the audience, a whisper can bring the condition of slavery close.
The burden of isolation to the individual: a comparison between isolation for COVID-19 and for other influenza-like illnesses in Japan
Authors: Tsuzuki Shinya , Ohmagari Norio , Beutels Philippe
Published: December 2021

At present, there is scarce evidence about the burden associated with the isolation of COVID-19 patients. We aimed to assess the differences between COVID-19 and other influenza-like illnesses (ILIs) in disease burden brought by isolation. We conducted an online survey of 302 respondents who had COVID-19 or other ILIs and compared the burden of isolation due to sickness with one-to-one propensity score matching. The primary outcomes are the duration and productivity losses associated with isolation, the secondary outcome is the health-related quality of life (HRQoL) valuation on the day of the survey. Acute symptoms of outpatient COVID-19 and other ILIs lasted 17 (interquartile range (IQR) 9–32) and 7 (IQR 4–10) days, respectively. The length of isolation due to COVID-19 was 18 (IQR 10–33) days and that due to other ILIs was 7 (IQR 4–11) days, respectively. The monetary productivity loss of isolation due to COVID-19 was 1424.3 (IQR 825.6–2545.5) USD and that due to other ILIs was 606.1 (IQR 297.0–1090.9) USD, respectively. HRQoL at the time of the survey was lower in the COVID-19 group than in the ‘other ILIs’ group (0.89 and 0.96, P = 0.001). COVID-19 infection imposes a substantial disease burden, even in patients with non-severe disease. This burden is larger for COVID-19 than other ILIs, mainly because the required isolation period is longer.
Seroepidemiological survey on pigs and cattle for novel K88 (F4)-like colonisation factor detected in human enterotoxigenic Escherichia coli
Authors: Tanimoto Yoshihiko , Inoue Miyoko , Komatsu Kana , Odani Atsuyuki , Wada Takayuki , Kage-Nakadai Eriko , Nishikawa Yoshikazu
Published: December 2021

Enterotoxigenic Escherichia coli (ETEC) strains that express various fimbrial or nonfimbrial colonisation factors (CFs) and enterotoxins are critical causes of diarrhoeal diseases. Human ETEC serotype O169:H41 (O169) has been a representative of epidemic ETEC worldwide; the organism shows massive adherence to HEp-2 cells similar to enteroaggregative E. coli. Previously, we determined the complete sequence of the unstable virulence plasmid, pEntYN10. The plasmid included a unique set of genes encoding a novel CF resembling K88 (F4) of porcine ETEC, in addition to CS6, a well-known representative CF of human ETEC, and another novel CF similar to CS8 (CFA/III) of human ETEC. In the present study, we focused on K88-like CF (hereafter, K88O169) that may allow the organisms to infect domestic livestock like original K88-harbouring strains that can cause diarrhoea in piglets. Samples were tested for antibodies against recombinant proteins of possible paralogous adhesins, FaeG1 and FaeG2, from K88O169 and the FaeG of typical K88 (F4). The seroepidemiological study using recombinant antigens (two paralogs FaeG1 and FaeG2 from K88O169) showed reactivity of porcine (18.0%) and bovine (17.1%) sera to K88O169 FaeG1 and/or FaeG2 antigens on indirect ELISA tests. These results suggest that E. coli with K88O169 adhesin can infect various hosts, including pigs and cattle. This is the first report of domestic livestock having antibodies to K88O169 of human ETEC. Although human ETEC had been thought to be distinguished from those of domestic animals based on CFs, zoonotic strains may conceal themselves among human ETEC organisms. The concept of One Health should be adopted to intervene in ETEC infections among animals and humans.
Olive oil and wine as source of multi-target agents in the prevention of Alzheimer disease
Authors: Silva Paula , Rodríguez-Pérez María , Gómez-Torres Óscar , Burgos-Ramos Emma
Published: December 2021

Olive oil and wine are consumed daily worldwide, and they constitute the fundamental pillars of the healthy Mediterranean diet. Polyphenolic compounds, naturally present in both olive oil and wine, are responsible for their beneficial properties. Current studies have shown the neuroprotective effects of polyphenols independently of their well-known antioxidant action. In this work, we have focused on reviewing the protective effect of polyphenols from extra virgin olive oil and wine in Alzheimer´s disease (AD), to emphasise that both foods could be a possible therapeutic tool. Beneficial effects have been described in β-aggregation, neurofibrillary tangles, autophagy and mitochondrial function, as well as in cerebral insulin resistance. Furthermore, to date, a harmful dose has not been described. Both pre-clinical and clinical works demonstrate that polyphenols act on neuropathological and cognitive disorders of AD, preventing or stopping the onset of this devastating disease. However, there are certain limitations in these studies, since it is very difficult to research diseases that lead to cognitive impairment. Although all the findings obtained are very encouraging, more studies should be carried out investigating the use of the polyphenols from olive oil and wine as therapeutic agents in the progression of AD. Therefore, more longitudinal studies in humans with a homogeneous cohort of patients are necessary to corroborate the efficacy of these nutraceuticals, as well as determine the most appropriate dose for this purpose.