bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

AbstractThe 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

AbstractIn 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

AbstractA 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

AbstractFocusing 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

AbstractIn 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

Abstract
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

AbstractBackgroundAlthough 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.MethodsAll 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.Results108 (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).ConclusionGiven 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

AbstractIn 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

AbstractIn 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

AbstractIn 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

AbstractPrediction 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

AbstractBehavioural 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

Abstract
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.
PROOF OF SOME CONJECTURAL CONGRUENCES OF DA SILVA AND SELLERS
Authors: SINGH AJIT , BARMAN RUPAM 
Published: December 2021

AbstractLet
$p_{\{3, 3\}}(n)$
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

AbstractBackgroundThe aim of this study was to identify any relationship between hearing loss and mild cognitive impairment.MethodThis 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.ResultsA 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.ConclusionMost 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

AbstractAmong 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

AbstractAlthough 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.