bluuebunny/crossref_metadata_2025 huggingface dataset:
Healthcare seeking outside healthcare facilities and antibiotic dispensing patterns in rural Burkina Faso: A mixed methods study
Authors: Valia Daniel , Kouanda Juste Stéphane , Ingelbeen Brecht , Derra Karim , Kaboré Bérenger , Kiemdé François , Rouamba Toussaint , Rouamba Eli , Hien Franck Sovi , Campbell Linda , Meudec Marie , Robert Annie , Tinto Halidou , van der Sande Marianne A. B. , Villalobos Hector Rodriguez
Published: March 2023

Objective

Optimising antibiotic use is important to limit increasing antibiotic resistance. In rural Burkina Faso, over‐the‐counter dispensing of antibiotics in community pharmacies and non‐licensed medicine retail outlets facilitates self‐medication. We investigated its extent, reasons and dispensing patterns.

Methods

In an exploratory mixed‐method design conducted between October 2020 and December 2021, this study first explored illness perceptions, the range of healthcare providers in communities, antibiotics knowledge and reasons for seeking healthcare outside healthcare facilities. Second, frequencies of illness and healthcare utilisation in the last 3 months were quantitatively measured.

Results

Participants distinguished between natural and magico‐religious illnesses, according to origins. For illnesses considered to be ‘natural’, healthcare was mainly sought at healthcare facilities, private pharmacies and informal drug outlets. For illnesses considered as magico‐religious, traditional healers were mainly visited. Antibiotics were perceived in the community as medicines similar to painkillers. Healthcare‐seeking outside healthcare facilities was reported by 660/1973 (33.5%) participants reporting symptoms, including 315 (47.7%) to informal vendors. Healthcare seeking outside facilities was less common for 0–4‐year‐olds (58/534, 10.9% vs. 379/850, 44.1% for ≥5‐year‐olds) and decreased with improving socio‐economic status (108/237, 45.6% in the lowest quintile; 96/418, 23.0% in the highest). Reported reasons included financial limitation, and also proximity to informal drug vendors, long waiting times at healthcare facilities, and health professionals' non‐empathetic attitudes towards their patients.

Conclusion

This study highlights the need to facilitate and promote access to healthcare facilities through universal health insurance and patient‐centred care including reducing patients' waiting time. Furthermore, community‐level antibiotic stewardship programmes should include community pharmacies and informal vendors.
The Effect of Health Communication on Reader Attitudes with Digital Media Literacy Antecedents
Authors: Putri Kinkin Yuliaty Subarsa , Istiyanto S Bekti , Prihantoro Edy , Setiawan Bramianto
Published: March 2023

The Coronavirus pandemic in Indonesia is increasing daily. Unfortunately, the implementation of lockdown is not enforced in some areas. Meanwhile, in these current pandemic conditions, health communication is needed. This research describes health communication concepts, readers’ attitudes, and digital media literacy. Furthermore, the digital media literacy antecedent focuses on understanding attitudes in handling hoax information and people infected with Coronavirus. A quantitative approach with the forecasting method was used in this research. It showed that Health Communication has a linear regression value of 0.49 with a significance of 0.000 on the reader's attitude variables. There is an influence between health communications on the reader's attitudes. Likewise, digital media has a regression result of 0.51 with a significant value of 0.000 on reader's attitudes indicating that digital media influences reader's attitudes. Subsequently, developing digital media literacy and reader attitudes in health communication is important. It is hoped that future research will be able to elaborate on health communication and digital media literacy in the wider community and use adapted methods.
Newly recognized blueschist-facies metamorphism (glaucophane-omphacite-garnet), Belvidere Mountain Complex, northern Appalachians
Authors: Honsberger Ian W.
Published: March 2023

An occurrence of blueschistfacies metamorphism in the Appalachian orogen is newly recognized in northwestern New England, United States. Inclusions of glaucophane and omphacite occur in a relict garnet core from a retrogressed garnetbarroisite amphibolite of the Belvidere Mountain Complex in Vermont. Pressuretemperature pseudosection and mineral composition isopleth calculations demonstrate that the Belvidere Mountain Complex blueschistfacies mineral assemblage of glaucophane–magnesio-hornblende–omphacite–chlorite–rutile–quartz–clinozoisite–garnet was stable at ~1.65–2.0 GPa and ~450–480 °C. Garnetabsent amphibolite with barroisite and chlorite inclusions in clinozoisite records highpressure epidote-amphibolite–facies metamorphism at ~1.0–1.4 GPa and ~515–550 °C. These new findings quantify deep subduction of the Belvidere Mountain Complex during the Cambrian to Ordovician Taconic orogenic cycle and suggest that more blueschistfacies mineral assemblages could be revealed in the Appalachians with detailed analysis of retrogressed rocks.
Differential attainment in specialty training recruitment in the UK: an observational analysis of the impact of psychometric testing assessment in Public Health postgraduate selection
Authors: Pinder Richard J , Bury Fran , Sathyamoorthy Ganesh , Majeed Azeem , Rao Mala
Published: March 2023

Objectives

To determine how current psychometric testing approaches used in selection of postgraduate training in UK Public Health are associated with socioeconomic and sociocultural background of applicants (including ethnicity).

Design

Observational study using contemporaneous data collected during recruitment and psychometric test scores.

Setting

Assessment centre of UK national Public Health recruitment for postgraduate Public Health training. The assessment centre element of selection comprises three psychometric assessments: Rust Advanced Numerical Reasoning, Watson-Glaser Critical Thinking Assessment II and Public Health situational judgement test.

Participants

629 applicants completed the assessment centre in 2021. 219 (34.8%) were UK medical graduates, 73 (11.6%) were international medical graduates and 337 (53.6%) were from backgrounds other than medicine.

Main outcome measure

Multivariable-adjusted progression statistics in the form of adjusted OR (aOR), accounting for age, sex, ethnicity, professional background and surrogate measures of familial socioeconomic and sociocultural status.

Results

357 (56.8%) candidates passed all three psychometric tests. Candidate characteristics negatively associated with progression were black ethnicity (aOR 0.19, 0.08 to 0.44), Asian ethnicity (aOR 0.35, 0.16 to 0.71) and coming from a non-UK medical graduate background (aOR 0.05, 0.03 to 0.12); similar differential attainment was observed in each of the psychometric tests. Even within the UK-trained medical cohort, candidates from white British backgrounds were more likely to progress than those from ethnic minorities (89.2% vs 75.0%, p=0.003).

Conclusion

Although perceived to mitigate the risks of conscious and unconscious bias in selection to medical postgraduate training, these psychometric tests demonstrate unexplained variation that suggests differential attainment. Other specialties should enhance their data collection to evaluate the impact of differential attainment on current selection processes and take forward opportunities to mitigate differential attainment where possible.
On effective birationality for sub-pairs
Authors: Han Jingjun , Liu Jihao
Published: March 2023

For [Formula: see text]-lc Fano-type varieties with fixed dimension, we show that [Formula: see text] defines a birational map for some positive integer [Formula: see text] depending only on [Formula: see text] and the dimension for any pair [Formula: see text] when vol[Formula: see text] and the coefficients of [Formula: see text] are bounded away from 0. When vol[Formula: see text] approaches to zero, we construct an example to show that the effective birationality fails even if [Formula: see text] is fixed, [Formula: see text] is [Formula: see text]-lc for some positive real number [Formula: see text], and the coefficients of [Formula: see text] belong to a descending chain condition (DCC) set. We also show the effective birationality holds for sub-pairs [Formula: see text] under certain conditions.
CAN THE NARROW AND BROAD MONEY SUPPLY GAP BE USED AS AN INVESTMENT INDICATOR FOR THE STOCK MARKET?
Authors: LEE YUAN-MING , WANG KUAN-MIN
Published: March 2023

This study uses the golden cross and death cross formed by the gap between the narrow and broad money growth rates as threshold variables to estimate the threshold model and test the causal relationship between money supply and stock prices in eight emerging market economies (EMEs) in Asia; the sample periods are from January 2000 to December 2020. The results show a high-positive, bi-directional relationship between the money supply and stock prices in the golden cross regime. On the other hand, the money supply has a negative, one-way causality on stock prices in the death cross regime. We also conducted a robustness test during the COVID-19 spread, and the result shows that the mechanism still applies, but the effectiveness is reduced. Thus, our contribution is discovering the golden cross and death cross information formed by narrow and broad money, informing stock market investment.
MONETARY POLICY AND ASSET PRICES: THE CASE OF PAKISTAN
Authors: MALIK WASIM SHAHID , MARIYAM SIDRA , SHAFIQ HINA
Published: March 2023

This paper sets the objective of estimating the mediating role of asset prices in the transmission of monetary policy. Vector autoregressive model comprising short-term interest rate, output, inflation and asset prices has been estimated using data of Pakistan economy for the period 2000m01 to 2019m06. We find significant role of asset prices in transmission of monetary policy to target variables, especially when individual asset prices are taken instead of asset price index. Stock prices are found important mediator of transmission from interest rate to output while exchange rate is so for inflation rate; role of house prices remains moderate.
Single-Inductor, Multiple-Input, Multiple-Output, DC–DC Converter Based on a New Software Zero-Current Switching Technique
Authors: Asgharzadeh-Bonab Akbar , Sheikhaei Samad
Published: March 2023

A single-inductor multiple-input multiple-output converter is proposed in this paper that can be used in low-power systems due to low output current and voltage. This converter is implemented discretely, and only one microcontroller is employed to control the system. The unique zero-current switching (ZCS) technique considered in this paper is such that only by reading the inductor’s left-side voltage the optimal value of the inductor discharge duty cycle is determined. This method can be generalized to low-power and high-power converters, whether implemented and designed as discrete or integrated. This converter works in discontinuous conduction mode. It uses pulse width modulation control and the time-multiplexing control method, which makes the system have high efficiency and makes the cross-regulation problem between the converter’s outputs tiny. The control algorithm considered in this converter is digital, which determines the optimal charge and discharge duty cycles. Also, the switching frequency of this converter is constant, relatively low, and equal to 5[Formula: see text]kHz. The efficiency of this converter has reached 91.6% by using the ZCS technique and other mentioned control methods.
Optimal Sparse Volterra Modeling for Transient Behavior of Turbofan Engines Based on Internet of Things
Authors: Ma Yidan , Cao Jianfu
Published: March 2023

In recent years, Internet of Things (IoT) technologies have been increasingly utilized to collect enormous volumes of performance data for intelligent analysis and modeling of aero-engines. This has aided in the development of numerous data-driven solutions so that a strong knowledge of the intricate operations within the equipment is no longer needed. To characterize the dynamic nonlinear transient behavior of turbofan engines, fast response changes have the possibility of being captured accurately through high-order, long-memory-length Volterra series. However, exponentially increasing coefficients are still challenging to be handled properly. For fast and reliable modeling of turbofan engines, an Optimal Sparse Volterra (OSV) model is developed in this paper by reconstructing sparse nonzero coefficients after a global selection through particle swarm optimization. The OSV model focuses on the optimal sparsity of the Volterra kernels while being insensitive to the signal length. Besides, noise reduction and the correlation analysis method are specifically designed for sensor measurements of low-bypass ratio turbofan engines. The OSV model, as well as retaining the powerful descriptive capability of the Volterra series for nonlinear characteristics, finds the most relevant sets of variables and the set of model parameters automatically under the minimum computing workload. According to the experimental results, when real test data are used for turbofan transient maneuvers, the OSV model ensures that the mean absolute error is less than [Formula: see text] for high-pressure rotor speed, thrust and exhaust temperature. Moreover, the nonzero identification coefficients produced by the OSV model in the experiments are less than 6% of the total coefficients. At the same time, the average running time required by the OSV model is less than 35% of that of traditional identification algorithms.
Deriving Thresholds of Object-Oriented Metrics to Predict Defect-Proneness of Classes: A Large-Scale Meta-Analysis
Authors: Mei Yuanqing , Rong Yi , Liu Shiran , Guo Zhaoqiang , Yang Yibiao , Lu Hongmin , Tang Yutian , Zhou Yuming
Published: March 2023

Many studies have explored the methods of deriving thresholds of object-oriented (i.e. OO) metrics. Unsupervised methods are mainly based on the distributions of metric values, while supervised methods principally rest on the relationships between metric values and defect-proneness of classes. The objective of this study is to empirically examine whether there are effective threshold values of OO metrics by analyzing existing threshold derivation methods with a large-scale meta-analysis. Based on five representative threshold derivation methods (i.e. VARL, ROC, BPP, MFM, and MGM) and 3268 releases from 65 Java projects, we first employ statistical meta-analysis and sensitivity analysis techniques to derive thresholds for 62 OO metrics on the training data. Then, we investigate the predictive performance of five candidate thresholds for each metric on the validation data to explore which of these candidate thresholds can be served as the threshold. Finally, we evaluate their predictive performance on the test data. The experimental results show that 26 of 62 metrics have the threshold effect and the derived thresholds by meta-analysis achieve promising results of GM values and significantly outperform almost all five representative (baseline) thresholds.
Multilevel domain uncertainty quantification in computational electromagnetics
Authors: Aylwin Rubén , Jerez-Hanckes Carlos , Schwab Christoph , Zech Jakob
Published: March 2023

We continue our study [R. Aylwin, C. Jerez-Hanckes, C. Schwab and J. Zech, Domain uncertainty quantification in computational electromagnetics, SIAM/ASA J. Uncertain. Quant. 8 (2020) 301–341] of the numerical approximation of time-harmonic electromagnetic fields for the Maxwell lossy cavity problem for uncertain geometries. We adopt the same affine-parametric shape parametrization framework, mapping the physical domains to a nominal polygonal domain with piecewise smooth maps. The regularity of the pullback solutions on the nominal domain is characterized in piecewise Sobolev spaces. We prove error convergence rates and optimize the algorithmic steering of parameters for edge-element discretizations in the nominal domain combined with: (a) multilevel Monte Carlo sampling, and (b) multilevel, sparse-grid quadrature for computing the expectation of the solutions with respect to uncertain domain ensembles. In addition, we analyze sparse-grid interpolation to compute surrogates of the domain-to-solution mappings. All calculations are performed on the polyhedral nominal domain, which enables the use of standard simplicial finite element meshes. We provide a rigorous fully discrete error analysis and show, in all cases, that dimension-independent algebraic convergence is achieved. For the multilevel sparse-grid quadrature methods, we prove higher order convergence rates free from the so-called curse of dimensionality. Numerical experiments confirm our theoretical results and verify the superiority of the sparse-grid methods.
Taylor–Couette flow with temperature fluctuations: Time periodic solutions
Authors: Feireisl Eduard , Kwon Young-Sam
Published: March 2023

We consider the motion of a viscous compressible and heat conducting fluid confined in the gap between two rotating cylinders (Taylor–Couette flow). The temperature of the cylinders is fixed but not necessarily constant. We show that the problem admits a time-periodic solution as soon as the ratio of the angular velocities of the two cylinders is a rational number.
Traveling waves for a Fisher-type reaction–diffusion equation with a flux in divergence form
Authors: Arias Margarita , Campos Juan
Published: March 2023

Analysis of the speed of propagation in parabolic operators is frequently carried out considering the minimal speed at which its traveling waves (TWs) move. This value depends on the solution concept being considered. We analyze an extensive class of Fisher-type reaction–diffusion equations with flows in divergence form. We work with regular flows, which may not meet the standard elliptical conditions, but without other types of singularities. We show that the range of speeds at which classic TWs move is an interval unbounded to the right. Contrary to classic examples, the infimum may not be reached. When the flow is elliptic or over-elliptic, the minimum speed of propagation is achieved. The classic TW speed threshold is complemented by another value by analyzing an extension of the first-order boundary value problem to which the classic case is reduced. This singular minimum speed can be justified as a viscous limit of classic minimal speeds in elliptic or over-elliptic flows. We construct a singular profile for each speed between the minimum singular speed and the speeds at which classic TWs move. Under additional assumptions, the constructed profile can be justified as that of a TW of the starting equation in the framework of bounded variation functions. We also show that saturated fronts verifying the Rankine–Hugoniot condition can appear for strictly lower speeds even in the framework of bounded variation functions.
Analysis of Hybridized Techniques with Class Imbalance Learning for Predicting Software Maintainability
Authors: Malhotra Ruchika , Lata Kusum
Published: March 2023

Software maintainability is a vital concern of organizations that develop and maintain large software products. The models that assess the maintainability of software systems at initial development stages play a significant role. In the Software Maintainability Prediction (SMP), a prevalent issue that needs to be taken care of is imbalanced data problem. For SMP, imbalanced data problem arises when the software classes that require high maintenance effort are less in number than classes that require low maintenance effort. In this paper, we dealt with the imbalanced data problem by the data resampling. With the imbalanced data, efficient machine learning algorithms are unable to predict the data points of both classes competently. Therefore, we examine the effectiveness of hybridized (HYB) techniques. The HYB techniques aid in finding an optimal solution for a problem by judging the goodness of multiple solutions. As per the results of the study, Adaptive synthetic minority oversampling technique (Adasyn) and Safe level synthetic minority oversampling technique (SafeSMOTE) are the best techniques of imbalanced data. Also, among the investigated HYB techniques, Fuzzy LogitBoost (GFS-LB) and Particle Swarm Optimization with Linear Discriminant Analysis (PSOLDA) emerged as the best techniques to predict maintainability.
Spectral studies and nonlinear optical properties of an organic crystal: Piperazine-1, 4-diiumbis (4-aminobenzenesulfonate)
Authors: Sathesh Kumar K. , Prakash S. M. , Srinivasan P. , Jayaprakash P.
Published: March 2023

FTIR, FT-Raman and NMR are studied to explore the functional groups, the vibration modes and its coupling interactions for the grown single crystal piperazine-1,4-diium bis (4-aminobenzenesulfonate) (PABS). The cut-off wavelength at 303 nm of UV–Visible spectrum exhibits great transmittance over the entire visible spectrum. Photoluminescence spectral study revealed the electron excitation notably in blue emission range. The range of susceptibility and nonlinear refractive index was obtained from second and third harmonic generations of PABS crystals. At various temperatures, the thermal stability of the crystal and the crystal dielectric characteristics had been studied in relation to frequency. The hardness of the crystal was obtained by microhardness measurements.
Study of enhanced sensitivity of nanosensors by using gold bowtie nanoparticles
Authors: Firoozi A. , Khordad R. , Rastegar Sedehi H. R.
Published: March 2023

A plasmonic nanosensor is proposed and investigated its sensitivity using the optical properties of plasmonic nanoparticles. To this end, we first consider the nanosensor consisting of bowtie nanoparticles. Then, the nanosensor performance is examined under different factors such as the refractive index of the background environment, the height, and length of the nanoparticles. The proposed bowtie nanoparticles, in this work, are made of gold. The boundary element method is used to simulate the nanosensor. The extinction cross-section is computed in terms of wavelength and the effect of various factors on the resonance wavelength of localized surface plasmon is investigated. It is shown that the nanosensor investigated in this research has a high sensitivity to the changes in the refractive index of the studied sample. The sensitivity of the nanosensor is obtained as 650[Formula: see text]nm/RIIU. In addition, the required spectral range can be arbitrarily adjusted by the type of nanoparticles.
Optical fibers to model pulses of ultrashort via generalized third-order nonlinear Schrödinger equation by using extended and modified rational expansion method
Authors: Nasreen Naila , Seadawy Aly R. , Lu Dianchen , Arshad Muhammad
Published: March 2023

In nonlinear Schrödinger equations (NLSEs), the third-order generalized NLSE is a significant sculpture which is utilized for modeling ultrashort pulses in fiber optics. In this study, we obtained wave and soliton solutions by using new extended and modified Rational expansion method to get several types of soliton such as bright solitons, dark solitons, perodic solitons and traveling waves. In three-dimensional and two-dimensional plots, we present graphical representations in dissimilar structures of some solutions to understand the phenomena physically. The development and achievements of computing show the power and effectiveness of current technology. In addition, we are able to resolve various other high-order NLSEs with the assistance of effortless and effectual technique.
Time-fractional Chen–Lee–Liu equation: Various optical solutions arising in optical fiber
Authors: Murad Muhammad Amin Sadiq , Hamasalh Faraidun Kadir , Ismael Hajar Farhan
Published: March 2023

In this paper, the extended simplest equation method is utilized to construct the novel exact optical solitons solutions of the perturbed time fractional Chen–Lee–Liu equation with conformable fractional derivative. The acquired optical solitons and other solutions are expressed via the rational functions, the trigonometric functions, and the hyperbolic functions; in addition to guaranteeing the existence of the acquired results, the constrain conditions are provided. Furthermore, to elucidate the magnitude of the proposed equation, various obtained solutions are plotted via two-dimensional (2D) and three-dimensional (3D) graphs using appropriate values of parameters. It is observed that the present technique is a powerful tool and efficient for finding the analytical solution for nonlinear differential equations of integer and fractional orders.
Stochastic averaging for a completely integrable Hamiltonian system with fractional Brownian motion
Authors: Wang Ruifang , Xu Yong , Pei Bin
Published: March 2023

This paper proposes an effective approximation result for the behavior of a small transversal perturbation to a completely integrable stochastic Hamiltonian system on a symplectic manifold. We derive an averaged stochastic differential equations (SDEs) in the action space for the action component of the perturbed system, where the averaged drift coefficient is characterized by the averages of that of the action component with respect to the invariant measure of the unperturbed system on the corresponding invariant manifolds. Then, the averaging principle is shown to be valid such that the action component of the perturbed system converges to the solution of averaged SDEs in the mean square sense.
Well-posedness of a system of SDEs driven by jump random measures
Authors: Jiao Ying , Kolliopoulos Nikolaos
Published: March 2023

We establish well-posedness for a class of systems of SDEs with non-Lipschitz coefficients in the diffusion and jump terms and with two sources of interdependence: a monotone function of all the components in the drift of each SDE and the correlation between the driving Brownian motions and jump random measures. Pathwise uniqueness is derived by employing some standard techniques. Then, we use a comparison theorem along with our uniqueness result to construct non-negative, [Formula: see text]-integrable càdlàg solutions as monotone limits of solutions to approximating SDEs, allowing for time-inhomogeneous drift terms to be included. Our approach allows also for a comparison property to be established for the solutions to the systems we investigate. The applicability of certain systems in financial modeling is also discussed.
Anti-Fraud Analysis during the COVID-19 Pandemic: A Global Perspective
Authors: Zhu Xiaoqian , Wang Yinghui , Chang Yanpeng , Chen Rongda , Li Jianping
Published: March 2023

The ongoing coronavirus disease 2019 (COVID-19) pandemic has brought unexpected economic downturns and accelerated digital transformation, leading to stronger financial fraud motives and more complicated fraud schemes. Although scholars, practitioners, and regulators have begun to focus on the new characteristics of financial fraud, a systematic and effective anti-fraud strategy during the pandemic still needs to be explored. This paper comprehensively analyzes the lessons of anti-fraud that we should learn from the COVID-19 pandemic. By exploring the complex motives and schemes of fraud, we summarize the characteristics of financial fraud activities and further analyze the regulatory challenges posed by financial fraud during the outbreak. To better cope with the fraudulent activities during the pandemic, policy proposals on how to improve the supervision of financial fraud activities are put forward. In particular, the panoramic data and graph-based techniques are powerful tools for future fraud detection.
Five-dimensional cylindrical anisotropic fluid in Einstein–Gauss–Bonnet gravity
Authors: Ghaemi Neda , Kaviani Kamran
Published: March 2023

In this paper, we present a static solution for the five-dimensional Einstein–Gauss–Bonnet (EGB) gravitational field equations with a cylindrical symmetry and an anisotropic fluid as a source. We consider whole set of equations in the interior space which sourced by static cylindrical anisotropic fluid and junction conditions required for smoothly matching with exterior space which is a cylindrical vacuum solution of five dimensional EGB equation. We achieve density and pressures as functions of cylindrical radial coordinate and give some graphically analysis under numerical solution.
Applications of some types of solitons within the framework of Kählerian spacetime manifolds
Authors: Dey Santu , Uddin Siraj
Published: March 2023

In this paper, we study applications of some certain types of solitons such as conformal Ricci soliton, conformal [Formula: see text]-Ricci–Yamabe soliton and [Formula: see text]-Ricci soliton on Kählerian spacetime manifolds. Further, we have developed the characteristics of conformal Ricci soliton and conformal [Formula: see text]-Ricci–Yamabe soliton on almost pseudo-symmetric Kählerian spacetime manifolds. Here, we have signalized the nature of solitons in terms of shrinking, steady or expanding and we have also presented the relationship between [Formula: see text] and [Formula: see text] in terms of conformal [Formula: see text]-Ricci–Yamabe soliton. Finally, we have embellished the classification of the potential function with respect to gradient [Formula: see text]-Ricci soliton on Kählerian spacetime manifolds.
Virtual Elements on polyhedra with a curved face
Authors: Brezzi Franco , Marini L. Donatella
Published: March 2023

We revisit classical Virtual Element approximations on polygonal and polyhedral decompositions. We also recall the treatment proposed for dealing with decompositions into polygons with curved edges. In the second part of the paper, we introduce a couple of new ideas for the construction of Virtual Element Method (VEM)-approximations on domains with curved boundary, both in two and three dimensions. The new approach looks promising, although sound numerical tests should be made to validate the efficiency of the method.
Coupon coloring of Kneser graph K(n,2)
Authors: Shadravan Mehrnoosh , Borzooei Rajab Ali
Published: March 2023

Chen et al. [On coupon coloring of graphs, Discrete Appl. Math. 193 (2015) 94–101] had introduced the concept of coupon coloring for any graph with no isolated vertex. A [Formula: see text]-coupon coloring of [Formula: see text] is an assignment of colors from [Formula: see text] to the vertices of [Formula: see text] such that the neighborhood of every vertex of [Formula: see text] contains vertices of all colors from [Formula: see text]. The maximum [Formula: see text] for which a [Formula: see text]-coupon coloring exists is called the coupon coloring number of [Formula: see text], and is denoted by [Formula: see text]. In this paper, we determine the coupon coloring number of Kneser graphs [Formula: see text].
A penalty decomposition algorithm for the extended mean–variance–CVaR portfolio optimization problem
Authors: Hamdi Abdelouahed , Khodamoradi Tahereh , Salahi Maziar
Published: March 2023

In this paper, we study mean–variance–Conditional Value-at-Risk (CVaR) portfolio optimization problem with short selling, cardinality constraint and transaction costs. To tackle its mixed-integer quadratic optimization model for large number of scenarios, we take advantage of the penalty decomposition method (PDM). It needs solving a quadratic optimization problem and a mixed-integer linear program at each iteration, where the later one has explicit optimal solution. The convergence of PDM to a partial minimum of original problem is proved. Finally, numerical experiments using the S&P index for 2020 are conducted to evaluate efficiency of the proposed algorithm in terms of return, variance and CVaR gaps and CPU times.
Design of an efficient graph-based traversing method for establishing authentication mechanism in cloud
Authors: Nagesh Puvvada , Srinivasu N.
Published: March 2023

With the broader development of networking, data acquired from IoT and big data have grown significantly in various real-time applications. It provides a transparent role of human life as it shows an extensive bond with data provisioning. On the other hand, it has some challenging issues like verification of authenticity of the enormous data over an un-trusted environment like cloud. It causes privacy leakage, delay, and unidentified data size by third-party. Thus, there is a need for a novel authentication to handle all these problems using a tree data structure for establishing authentication for privacy preservation. Here, a novel graph-based traversing algorithm (GTA) is proposed for realizing the data stream verification and validates the arrival of data streams. This model reduces the failure rate and improves the authentication mechanism and robustness. An integrity verification scheme is used to handle privacy leakage issues during third-party analysis. The simulation is performed in MATLAB 2016b environment to project the significance of the model, and the outcomes are more desirable for authentication and privacy preservation during practical examination. Here, metrics like path length, total verification time, and total insertion time are evaluated. The proposed model gives a better trade-off compared to existing approaches. The path length variation of GTA is 1.3, 1.4, and 1.5 for depth rates 6, 8, and 10, respectively. The total verification time with data size is 1, 2, 3, and 4[Formula: see text]GB, respectively. The total insertion time of GTA is 5, 10, 15, and 18[Formula: see text]s for 1, 2, 3, and 4[Formula: see text]GB, respectively. It is remarkably lesser than P-ATHAT and Merkle tree, respectively. The time needed for two successive data verification is 16, 23, 43, and 57[Formula: see text]s for data sizes of 1, 2, 3, and 4[Formula: see text]GB, respectively. The proposed model consumes 15, 28, 44, and 54[Formula: see text]s, respectively, for the data size from 1[Formula: see text]GB to 4[Formula: see text]GB.
Design of a novel masking-based deep convolutional neural network approach for accident classification
Authors: Kanakala V. Raviteja , Mohan K. Jagan , Reddy V. Krishna
Published: March 2023

This work presents a novel multi-class detection approach for predicting car damage due to accidents or other reasons. The proposed prediction model intends to extract the class information to analyze the objects over the frames. Here, a novel masking-based deep convolutional neural network (MD-CNN) is proposed to capture the car parts’ regions and the classification process. The proposed model works well compared to the various existing approaches. The computation is initiated with the acquisition of damaged images, and pre-processing is performed for data labeling, which is further divided into training and testing samples. The features are internally analyzed by the proposed MD-CNN model, where the internal feature extraction process is a significant advantage with the classification process. The simulation is done in MATLAB 2020a environment where various performance metrics like accuracy, precision, [Formula: see text]-measure, recall and detection rate are evaluated and compared with conventional learning approaches. The model gives an average precision of 94.5% and [Formula: see text]1-score of 91% which is higher than other approaches. The proposed model establishes a better trade-off among the prevailing approaches with superior prediction accuracy.
Croup disease classification using VGG19 and ResNet50 transfer learning method
Authors: Vetrimani E. , Arulselvi M.
Published: March 2023

Detection of any disease in the early stage can save a life. There are many medical imaging modalities like MRI, FMRI, ultrasound, CT, and X-ray used in the detection of disease. In the last decades, neural network-based methods are effective in detecting and classifying the disease based on abnormalities present in the medical images. Acute laryngotracheobronchitis (croup) is one of the common diseases seen in children among the 0.5–3 years age group which infects the respiratory system that can cause the larynx, trachea, and bronchi. Prior detection can lower the risk of spreading and can be treated accurately by a pediatrician. Commonly this infection can be diagnosed though physical examination. But due to the similarity of Covid-19 symptoms urges the physicians to get accurate detection of this disease using X-ray and CT images of the infant’s chest and throat. The proposed work aims to develop a croup diagnose system (CDS) which identify the Croup infection through post anterior (PA) view of pediatric X-ray using deep learning algorithm. We used the well-known transfer learning algorithm VGG19 and ResNet50. Data augmentation being adapted for reducing the overfitting and to improve the quantity of image samples. We show that the proposed transfer learning based CDS method can be used to classify the X-ray images into two classes namely, croup and normal. The experiment results confirm that VGG19 performs better than ResNet50 with promising classification accuracy (90.91%.). The results show that the proposed CDS models can be used for more pediatric medical image classification problem.
High recoverable energy storage density of Na0.5Bi0.5TiO3 lead-free ceramics modified by Bi(Mg0.5Hf0.5)O3
Authors: Wang Kaiyuan , Li Wenhua , Tang Xingui , Zhang Siyuan , Zhang Yansong , Hu Jia , Shen Zhihao , Jiang Yanping , Guo Xiaobin
Published: March 2023

Enhancing the availability and reliability of dielectric ceramic energy storage devices is of great importance. In this work, (1-[Formula: see text])[Formula: see text]–[Formula: see text]Bi([Formula: see text])[Formula: see text] (NBT–[Formula: see text]BMH) lead-free ceramics were created utilizing a solid-state reaction technique. All NBT–[Formula: see text]BMH ceramics have a single perovskite structure. With increasing BMH doping, the grain size shrinks drastically, which greatly enhances the breakdown electric field (310 kV/cm at [Formula: see text] = 0.25). Additionally, the relaxation behaviors of NBT–[Formula: see text]BMH ceramics with high BMH content are more remarkable. Among all designed components, the NBT–0.25BMH ceramic exhibits the best energy storage performance with a high [Formula: see text] of 4.63 J/[Formula: see text] and an [Formula: see text] of 75.1% at 310 kV/cm. The NBT–0.25BMH ceramic has exceptional resistance to fluctuations in both frequency (5–500 Hz) and temperature (30–100[Formula: see text]C). Charge–discharge test shows that the NBT–0.25BMH ceramic has a quick discharge rate ([Formula: see text] 110 ns). With these properties, the NBT–0.25BMH ceramic may have applications in microdevices as well as in ultra-high power electronic systems.
Humanitarian Organizational Network and Effectiveness of Disaster Response — A Theoretical Review
Authors: Masaba Ayub Kutosi , Ntayi Joseph M. , Amooti Vincent Bagire
Published: March 2023

In the humanitarian assistance sector, the primary objective of inter-organizational networks is to ensure that there are efficient and effective humanitarian response efforts that meet the needs of the affected population to the maximum extent possible (Drabek, 1987; Zhao et al., 2009). However, theoretical perspectives on humanitarian organizational networks and effective disaster response have remained relatively modest and confined to developing basic typologies of coordination arrangements and identifying the challenges encountered in the disaster management process. (Bennett, 1999) There also seems to be limited academic endeavor to use network, complexity, chaos and systems theories for disaster research not only for large-scale emergencies worldwide but also in developing countries. Most research works concentrate on an approach limited to a much smaller scale of nodes (organizational actors). In the preceding section, a review of relevant theories is presented in the context of humanitarian organizational network and disaster response.
Ready.gov
Authors: Mason Alicia , Bhati Sakshi
Published: March 2023

Nearly 20 years ago, the U.S. Department of Homeland Security launched Ready.gov, a national public service advertising campaign designed to educate and empower Americans to prepare for and respond to emergencies such as natural and technological disasters. To date, little is known about the accessibility and adaptability of this information for vulnerable populations including persons with disabilities (PwDs) and those with limited English proficiency (LEP). This computer-automated analysis seeks (1) to determine the general web, mobile and language accessibility of state websites which extend and/or amplify the Ready.gov national campaign goals, (2) to evaluate the document accessibility of downloadable emergency preparedness information, and, based on findings, (3) reflect upon improvement opportunities for disaster and emergency management preparedness messaging processes to vulnerable populations. An exploratory, quantitative content analysis relying on computer-automated software is used to assess the web, language, mobile and document accessibility of Ready.gov state-affiliated websites dedicated to providing public information for emergency preparedness and disaster response. Additional factors such as the use of CAPTCHA, adherence to the Matterhorn Protocol, disclosure of accessibility policy statements, and the presence of tailored information are evaluated. No significant differences among FEMA regions were found. The most frequent errors were likely to impact the POUR dimensions of perceivability and operability. In all, 76% of the Ready.gov state-affiliated websites had WCAG Level AA detectable accessibility failures on the home pages. Furthermore, 62% of the sites offered translational language formats for LEP users, while only 6% ([Formula: see text]) explicitly provided PwDs an option to report accessibility-related user experiences to the agency. Document accessibility was deemed to be poor with 80% of the websites disseminating downloadable .pdfs such as emergency planning guides and preparedness kits in inaccessible digital formats. These findings identify opportunities for improvement specifically, in the web, mobile and document accessibility of information associated with the Ready.gov national campaign. We argue that improvement and compliance is expected to reduce the likelihood of litigation, increase the resilience of vulnerable populations, and improve user experiences.
PDGes: An Interpretable Detection Model for Parkinson’s Disease Using Smartphones
Authors: Teng Fei , Chen Yanjiao , Cheng Yushi , Ji Xiaoyu , Zhou Boyang , Xu Wenyuan
Published: March 2023

Parkinson’s disease (PD) is a neurodegenerative disorder that severely affects the motor system of patients. Early PD detection will greatly improve the quality of lives. However, existing automatic PD detection systems either rely on customized sensors or require users to perform special activities, using machine learning models whose prediction process is not understandable by medical professionals. In this article, we develop a non-disruptive PD detection system on smartphones based on interpretable prediction models. We design an application named
PDGes
to passively collect touchscreen and Inertial Measurement Unit data of users’ tapping and swiping actions on smartphones. Meaningful features that reflect
finger dexterity
,
tremor
,
stiffness
, and
hand movement
are extracted to build the prediction model. To better comprehend the decisions made by the model, we conduct a systematic analysis of feature importance to help validate the conformity of the model with clinical PD diagnosis. We collected data from 108 volunteers to evaluate the performance of
PDGes
. The experiment results show that
PDGes
achieves a detection accuracy of more than 94.5% on different smartphones.
Compositional Timing Analysis of Asynchronized Distributed Cause-effect Chains
Authors: Günzel Mario , Chen Kuan-Hsun , Ueter Niklas , Brüggen Georg von der , Dürr Marco , Chen Jian-Jia
Published: March 2023

Real-time systems require the formal guarantee of timing constraints, not only for the individual tasks but also for the end-to-end latency of data flows. The data flow among multiple tasks, e.g., from sensors to actuators, is described by a cause-effect chain, independent from the priority order of the tasks. In this article, we provide an end-to-end timing-analysis for cause-effect chains on asynchronized distributed systems with periodic task activations, considering the maximum reaction time (MRT) (i.e., the duration of data processing) and the maximum data age (MDA) (i.e., the worst-case data freshness). We first provide an analysis of the end-to-end latency on one local electronic control unit (ECU) that has to consider only the jobs in a bounded time interval. We extend our analysis to globally asynchronized systems by exploiting a compositional property to combine the local results. Throughout synthesized data based on an automotive benchmark as well as on randomized parameters, we show that our analytical results improve the state-of-the-art.
Lower-limb resistance training reduces exertional dyspnea and intrinsic neuromuscular fatigability in individuals with chronic obstructive pulmonary disease
Authors: Brunton Nicole M. , Barbour David J. , Gelinas Jinelle C. , Yacyshyn Alexandra F. , Sasso John P. , Harper Megan I. , McNeil Chris J. , Melzer Bernie , Agar Gloria , Eves Neil D.
Published: March 2023

This study presents the novel finding that 4-wk resistance training (RT) focused specifically on the lower limbs can reduce exertional dyspnea during constant-load cycling, improve exercise tolerance, and reduce intrinsic fatigability of the quadriceps in individuals with COPD.
Acute interleukin-6 modulates key enzymes involved in prefrontal cortex and hippocampal amyloid precursor protein processing
Authors: Marko Daniel M. , Finch Michael S. , Yang Alex J. T. , Castellani Laura N. , Peppler Willem T. , Wright David C. , MacPherson Rebecca E. K.
Published: March 2023

It is becoming evident that exercise modulates APP processing and can reduce amyloid-beta (Aβ) peptide production. Our data help to explain this phenomenon by highlighting IL-6 as an exercise-induced factor that lowers pathological APP processing. These results also highlight brain regional differences in response to acute IL-6.
Inhibiting regional sweat evaporation modifies the ventilatory response to exercise: interactions between core and skin temperature
Authors: Foster Josh , Balmain Bryce N. , Wilhite Daniel P. , Watso Joseph C. , Babb Tony G. , Cramer Matthew N. , BelvaL Luke N. , Crandall Craig G.
Published: March 2023

Exercise in the heat increases the slope of the relation between minute ventilation and carbon dioxide elimination (V̇E/V̇co2 slope) in young healthy adults. An indispensable role for skin temperature in modulating the ventilatory response to exercise is noted, contradicting common belief that internal/core temperature acts independently as a controller of ventilation during hyperthermia.