bluuebunny/crossref_metadata_2025 huggingface dataset:
Empirical formula for heavy cluster decay in the superheavy region
Authors: Prathapan K. , Biju R. K.
Published: December 2021

In this paper, an empirical formula to describe the heavy cluster decay with [Formula: see text] ([Formula: see text] is the charge number of the emitted cluster) from superheavy elements is proposed. The predictions of our formula are compared with the predictions of Coulomb and Proximity Potential Model (CPPM), the predictions of Analytical Super Asymmetric Fission (ASAF) model and the predictions by UDL formula of Qi et al. Excellent agreement is found between the predictions of CPPM and ASAF models and those of the present formula. Using our formula, we have calculated the decay half-lives of various heavy cluster emission from superheavy elements leading to doubly magic [Formula: see text]Pb and compared with the predictions of CPPM. The predictions of UDL formula deviate considerably from the predictions of this formula, CPPM and ASAF model, giving much lower decay half-lives, as the order of decay half-life increases. Possible heavy cluster emissions from [Formula: see text] and 122 nuclei leading to [Formula: see text]Pb and [Formula: see text]Bi are also predicted.
Non-existence of graded unital homomorphisms between Leavitt algebras and their Cuntz splices
Authors: Arnone Guido , Cortiñas Guillermo
Published: December 2021

Let [Formula: see text], let [Formula: see text] be the graph consisting of one vertex and [Formula: see text] loops and let [Formula: see text] be its Cuntz splice. Let [Formula: see text] and [Formula: see text] be the Leavitt path algebras over a unital ring [Formula: see text]. Let [Formula: see text] be the cyclic group on [Formula: see text] elements. Equip [Formula: see text] and [Formula: see text] with their natural [Formula: see text]-gradings. We show that under mild conditions on [Formula: see text], which are satisfied, for example, when [Formula: see text] is a field or a principal ideal domain, there are no unital [Formula: see text]-graded ring homomorphisms [Formula: see text] nor in the opposite direction.
Operator-valued positive definite kernels and differentiable universality
Authors: Guella J. C.
Published: December 2021

We present a characterization for a positive definite operator-valued kernel to be universal or [Formula: see text]-universal, and apply these characterizations to a family of operator-valued kernels that are shown to be well behaved. Later, we obtain a characterization for an operator-valued differentiable kernel to be [Formula: see text]-universal and [Formula: see text]-universal. In order to obtain such characterization and examples, we generalize some well-known results concerning the structure of differentiable kernels to the operator-valued context. On the examples is given an emphasis on the radial kernels on Euclidean spaces.
A Stable Node-Based Smoothed Finite Element Method with Transparent Boundary Conditions for the Elastic Wave Scattering by Obstacles
Authors: Wang Shiyao , Wang Yu , Yue Junhong , Niu Ruiping , Li Yan , Li Ming
Published: December 2021

In this work, a stable node-based smoothed finite element method with TBC (SNS-FEM-TBC) is proposed to solve the scattering of elastic plane waves by a two-dimensional (2D) homogeneous isotropic elastic medium. First, using Helmholtz decomposition, two scalar potential functions are introduced to divide the Navier equation into Helmholtz equations with the coupled boundary conditions for the elastic scattering problem. Second, based on the analytical solutions of Helmholtz equations, TBC operators are deduced. Then, the gradient Taylor expansion is used to construct the stability term to deal with the instability of the original NS-FEM, the gradient of the solution is expressed into a linear formulation through approximating the node-based smoothing domain as a circle. Finally, based on smoothed Galerkin weak formula, the SNS-FEM-TBC formula of linear algebraic system with linear smoothing gradient is derived. Numerical examples show that SNS-FEM can obtain more stable and accurate solutions than standard FEM. Moreover, the convergence rates of [Formula: see text] and [Formula: see text] semi-norm errors of SNS-FEM are faster.
A Nonintrusive Reduced-Order Model for Uncertainty Quantification in Numerical Solution of One-Dimensional Free-Surface Water Flows Over Stochastic Beds
Authors: Alghosoun Alia , Mocayd Nabil El , Seaid Mohammed
Published: December 2021

Free-surface water flows over stochastic beds are complex due to the uncertainties in topography profiles being highly heterogeneous and imprecisely measured. In this study, the propagation and influence of several uncertainty parameters are quantified in a class of numerical methods for one-dimensional free-surface flows. The governing equations consist of both single-layer and two-layer shallow water equations on either flat or nonflat topography. For this purpose, the free-surface profiles are computed for different realizations of the random variables when the bed is excited with sources whose statistics are well defined. Many research studies have been dedicated to the development of numerical methods to achieve some order of accuracy in free-surface flows. However, little concern was given to examine the performance of these numerical methods in the presence of uncertainty. This work addresses this specific area in computational hydraulics with regards to the uncertainty generated from bathymetric forces. As numerical solvers for the one-dimensional shallow water equations, we implement four finite volume methods. To reduce the required number of samples for uncertainty quantification, we combine the proper orthogonal decomposition method with the polynomial chaos expansions for efficient uncertainty quantifications of complex hydraulic problems with large number of random variables. Numerical results are shown for several test examples including dam-break problems for single-layer and two-layer shallow water flows. The problem of flow exchange through the Strait of Gibraltar is also solved in this study. The obtained results demonstrate that in some hydraulic applications, a highly accurate numerical method yields an increase in its uncertainty and makes it very demanding to use in an operational manner with measured data from the field. On the other hand, when the complexity of physics increases, these highly accurate numerical methods display less uncertainty compared to the low accurate methods.
On a submersion of generic submanifold of a nearly Kaehler manifold
Authors: Fatima Tanveer , Akyol Mehmet Akif , Alzulaibani Alaa Awad
Published: December 2021

The purpose of this paper is to study the submersions of a generic submanifold [Formula: see text] of a nearly Kaehler manifold [Formula: see text]. It is proved that the base space [Formula: see text] of such a submersion which is an almost Hermitian manifold, turns out to be nearly Kaehler. It is also shown under certain conditions that base [Formula: see text] becomes Kaehler. Further, we give some curvature relations; specifically, we derive the relation between the holomorphic sectional curvature of [Formula: see text] restricted to the horizontal distribution and that of [Formula: see text].
Cyclic Loading on Damaged AA7075-T6 Specimens: Numerical Modelling and Experimental Testing
Authors: Arcieri Emanuele Vincenzo , Baragetti Sergio
Published: December 2021

AA7075-T6 is widely used in the aviation and aerospace industries thanks to its interesting strength-to-weight ratio. The fatigue life of the structural components of aircrafts and rockets can be altered as a consequence of the impact of alien objects. This work investigates the fatigue behavior of an AA7075-T6 hourglass specimen induced by the impact of a steel ball at its minimum cross-section. The specimen is then tested with a rotating bending moment. The stress distributions after impact and during cyclic loading are estimated using the Finite Element (FE) method. The failure mechanism was clarified by the observation of the failed specimen surface.
Subcritical Neimark–Sacker bifurcation and hybrid control in a discrete-time Phytoplankton–Zooplankton model
Authors: Khan A. Q. , Javaid M. B.
Published: December 2021

In this paper, we explore the local dynamical behavior with different topological classifications around fixed points, Neimark–Sacker bifurcation and hybrid control in the discrete-time Phytoplankton–Zooplankton model. More precisely, we have investigated the local dynamical behavior with different topological classifications around trivial, semitrivial and interior fixed points of the two-dimensional Phytoplankton–Zooplankton model, respectively. The existence of possible bifurcations around fixed points is also investigated, and it is proved that there exists no flip bifurcation around trivial and semitrivial fixed points but around interior fixed point, the model undergoes Neimark–Sacker bifurcation only. Moreover, hybrid control strategy is utilized for controlling Neimark–Sacker bifurcation in the Phytoplankton–Zooplankton model. Lastly, theoretical results are verified numerically.
Comparative Analysis Between the Main 3D Scanning Techniques: Photogrammetry, Terrestrial Laser Scanner, and Structured Light Scanner in Religious Imagery: The Case of The Holy Christ of the Blood
Authors: Ruiz Rafael Melendreras , Torres Ma Teresa Marín , Allegue Paloma Sánchez
Published: December 2021

In recent years, three-dimensional (3D) scanning has become the main tool for recording, documenting, and preserving cultural heritage in the long term. It has become the “document” most in demand today by historians, curators, and art restorers to carry out their work based on a “digital twin,” that is, a totally reliable and accurate model of the object in question. Thanks to 3D scanning, we can preserve reliable models in digital format of the real state of our heritage, some of which are currently destroyed. The first step is to digitize our heritage with the highest possible quality and precision. To do this, it will be necessary to identify the most appropriate technique. In this article, we will show some of the main digitization techniques currently used in sculpture heritage and the workflows associated with them to obtain high-quality models. Finally, a complete comparative analysis will be made to show their main advantages and disadvantages.
Connected Histories of the BBC: Opening up the BBC Oral History Archive to the Digital Domain
Authors: Sichani Anna-Maria , Hendy David
Published: December 2021

This article describes the computational and data-related challenges of the “Connected Histories of the BBC” project, an interdisciplinary project aiming to bring into the public realm some of the hidden treasures of the BBC's own Oral History Archive through the creation of an openly accessible, fully searchable and interconnected digital catalogue of this archive. This project stands as an interesting case study on the tensions between “computational” and “archival”, by critically designing and employing computational approaches for an historical, complex Oral History collection of scattered analogue records of various forms with an archival pre-history. From data acquisition, modeling, structuring and enhancement, metadata, data analysis procedures, to web design and legal issues, this paper discusses the various computational challenges, processes and decisions made during this project, while showcasing the principles of (re)usability, accessibility, and collaboration throughout its course.
Clinical Features of Extragastrointestinal Stromal Tumor Compared with Gastrointestinal Stromal Tumor: A Retrospective, Multicenter, Real-World Study
Authors: Feng Huolun , Hu Weixian , Zheng Chengbin , Wang Wei , Zheng Guoliang , Feng Xingyu , Xiong Wenjun , Lin Guosheng , Zhou Yongjian , Zhao Yan , Li Yong
Published: December 2021

Importance. Extragastrointestinal stromal tumor (EGIST) is a rare tumor, and its diagnosis and treatment strategy lack clinical guideline and relative literature evidence. In clinical practice, EGIST only misuses the pattern of GIST of diagnosis and treatment. The study hopes to find evidence of the treatment pattern for EGIST. Objective. This study aimed to compare the tumor characteristics and long-term outcomes between EGIST and GIST. The confounding function was applied to improve the result credibility in the case of small sample size. Design, Setting, and Participants. This cohort study enrolled 55 patients with EGIST who underwent surgery and were selected from four high-volume hospitals in China and 221 GIST patients who were collected from one of the four hospitals between January 2006 and September 2017. We used propensity score matching (PSM) and subgroup analysis to compare EGIST with GIST in terms of prognosis. The confounding function was used for sensitivity analysis to reduce unmeasured confounding. Results. We matched 43 patients in each of the GIST and EGIST groups by PSM. We compared EGIST data with GIST data to explore the prognostic factors between them. In the multivariate Cox regression model, tumor location of EGIST was negatively correlated with overall survival (after PSM: HR, 4.32; 95% CI, 1.22–15.26) or disease-free survival (after PSM: HR, 9.79; 95% CI, 2.22–43.31), which was also intuitively shown in the Kaplan–Meier survival curves (all

P

values < 0.05). In the subgroup analysis, EGIST with high risk factors had a worse prognosis than GIST. In unmeasured confounding analysis, the overall curve tends to show all combinations of c(0) of c(1) up to 2.0, none of which would bring the corrected relative risk to 1 for OS and DFS. Conclusions and Relevance. EGIST was associated with worse prognosis compared with GIST patients, particularly in EGIST patients with high risk factors, while there was a similar prognosis without those high risk factors.
Construction of Smart City Street Landscape Big Data‐Driven Intelligent System Based on Industry 4.0
Authors: Li Zhe , He YuKun , Lu XinYi , Zhao HengYi , Zhou Zheng , Cao YinYin
Published: December 2021

With the application of engineering management in smart city construction under Industry 4.0, the intelligent design of urban street landscape has attracted extensive attention. Affected by the low intelligent level of traditional landscape design, the existing urban landscape composite system has difficulty in meeting the needs of smart city construction. Therefore, this paper proposes the construction of street landscape big data‐driven intelligent decision support system based on Industry 4.0. Based on the complex network theory, this paper analyzes the structure, links, nodes, driving forces, and functional requirements of urban street landscape and then puts forward the construction content and implementation method of urban street landscape intelligent decision support system. The system consists of four aspects: intelligent infrastructure, service, protection and maintenance, and management and evaluation system. Its implementation not only reflects the cooperation and effective application of intelligent technology in each stage of street landscape construction, but also provides reference for the application of engineering management in other fields under Industry 4.0.
Formulation and Pharmaceutical Assessment of Annona muricata Oral Capsules and Suspension as Antidiarrhea Dosage Forms
Authors: Owusu Frederick William Akuffo , Boakye-Gyasi Mariam El , Entsie Philomena , Osei-Asare Christina , Adi-Dako Ofosua , Bosuthe Grace Boakye , Antwi-Mensah Esther , Bayor Marcel Tunkumgnen
Published: December 2021

Annona muricata (Annonaceae) is a tropical plant widely known for its edible fruits. Recent scientific studies have confirmed the folkloric use of its seeds as an antidiarrheal agent. This study sought to formulate capsules and suspensions using the ethanolic extract from Annona muricata seeds. The dried ethanolic extract was formulated into granules and subsequently encapsulated. The suspension formulated was assessed for sedimentation rate, sedimentation volume, viscosity, dissolution, drug content, and flow rate, while pharmacopeia tests such as disintegration, dissolution, uniformity of weight, and drug content were carried out on the formulated capsules. The formulated suspension passed the drug content and in vitro release studies. Annona muricata suspension exhibited pseudoplastic flow with good sedimentation rate and sedimentation volume. The formulated capsules passed the in vitro dissolution studies, weight uniformity, disintegration, and drug content tests. The ethanolic extract of Annona muricata seeds was appropriately formulated into standardized solid and liquid oral dosage forms.
State of Health Estimation of Lithium-Ion Battery Using Time Convolution Memory Neural Network
Authors: Zhu Chunxiang , Zheng Bowen , He Zhiwei , Gao Mingyu , Sun Changcheng , Bao Zhengyi
Published: December 2021

The accurate state of health (SOH) estimation of lithium-ion batteries enables users to make wise replacement decision and reduce economic losses. SOH estimation accuracy is related to many factors, such as usage time, ambient temperature, charge and discharge rate, etc. Thus, proper extraction of features from the above factors becomes a great challenge. In order to extract battery’s features effectively and improve SOH estimation accuracy, this article proposes a time convolution memory neural network (TCMNN), combining convolutional neural networks (CNN) and long short-term memory (LSTM) by dropout regularization-based fully connected layer. In experiment, the terminal voltage and charging current of the battery during charging process are collected, and input and output data sets are sorted out from the experimental battery data. Due to the limited equipment in the laboratory, only one battery can be charged and discharged at a time; the amount of battery data collected is relatively small, which will affect the extraction of features during the training process. Data augmentation algorithms are applied to solve the problem. Furthermore, in order to improve the accuracy of estimation, exponential smoothing algorithm is used to optimize output data. The results show that the proposed method can well extract and learn the feature relationship of battery cycle charge and discharge process in a long time span. In addition, it has higher accuracy than that of CNN, LSTM, Backpropagation (BP) algorithm, and Grey model-based neural network. The maximum error is limited to 3.79%, and the average error is limited to 0.143%, while the input data dimension is 514.
A Systematic Review and Meta-Analysis of the Effects of Herbal Medicine Buyang Huanwu Tang in Patients with Poststroke Fatigue
Authors: Jin Chul , Kwon Seungwon , Cho Seung-Yeon , Park Seong-Uk , Jung Woo-Sang , Moon Sang-Kwan , Park Jung-Mi , Ko Chang-Nam , Cho Ki-Ho
Published: December 2021

Poststroke fatigue (PSF) is reported to occur in 30%–72% of all patients with stroke. PSF not only is a symptom of stroke but has also been reported to adversely affect the prognosis of patients with stroke. However, no treatment has had a significant effect on PSF. In East Asian countries, several herbal medicines have been used to treat stroke, with Buyang Huanwu Tang (BHT) being the most common. This review aimed to evaluate the efficacy and safety of BHT for PSF. A literature search was conducted on MEDLINE, CENTRAL, Scopus, CiNii, CNKI, OASIS, NDSL, and KTKP databases for randomized controlled trials that evaluated the effects and safety of BHT on PSF. Six studies (n = 427) were included. The overall methodological quality of these studies was relatively low. In the adjunctive BHT group, the meta-analysis indicated statistically significant improvements in the Fatigue Severity Scale score (mean difference −1.49, 95% CI [−2.25, −0.73]) and total clinical efficacy rate (risk ratio 0.11, 95% CI [0.03, 0.41]) compared to those in the nonherbal group. Adverse events were only reported in one study, and no serious adverse events occurred. BHT administration might be effective in the treatment of PSF. We were unable to draw definitive conclusions owing to the limitations of the included studies. The trial is registered with CRD42019130178 in PROSPERO.
Computer Vision-Enabled Character Recognition of Hand Gestures for Patients with Hearing and Speaking Disability
Authors: Juneja Sapna , Juneja Abhinav , Dhiman Gaurav , Jain Shashank , Dhankhar Anu , Kautish Sandeep
Published: December 2021

Hand gesture recognition is one of the most sought technologies in the field of machine learning and computer vision. There has been an unprecedented demand for applications through which one can detect the hand signs for deaf people and people who use sign language to communicate, thereby detecting hand signs and correspondingly predicting the next word or recommending the word that may be most appropriate, followed by producing the word that the deaf people and people who use sign language to communicate want to say. This article presents an approach to develop such a system by that we can determine the most appropriate character from the sign that is being shown by the user or the person to the system. To enable pattern recognition, various machine learning techniques have been explored and we have used the CNN networks as a reliable solution in our context. The creation of such a system involves several convolution layers through which features have been captured layer by layer. The gathered features from the image are further used for training the model. The trained model efficiently predicts the most appropriate character in response to the sign exposed to the model. Thereafter, the predicted character is used to predict further words from it according to the recommendation system used in this case. The proposed system attains a prediction accuracy of 91.07%.
Rolling Bearing Fault Vibration Signal Denoising Based on Adaptive Morphological Wavelet Perona–Malik Filter Algorithm
Authors: Li Hao , Tan Yifan , Pu Yun
Published: December 2021

This paper proposes an adaptive Perona–Malik filtering algorithm based on the morphological Haar wavelet, which is used for vibration signal denoising in rolling bearing fault diagnosis with strong noise. First, the morphological Haar wavelet operator is utilized to presmooth the noisy signal, and the gradient of the presmooth signal is estimated. Second, considering the uncertainty of gradient at the strong noise point, a strong noise point recognition operator is constructed to adaptively identify the strong noise point. Third, the two‐step gradient average value of the strong noise point in the same direction is used to substitute, and the second derivative is introduced into the diffusion coefficient. Finally, diffusion filtering is performed based on the improved Perona–Malik model. The simulation experiment result indicated that not only the algorithm can denoise effectively, but also the average gradient and second derivative in the same direction can effectively suppress the back diffusion of strong noise points to improve the denoising signal‐to‐noise ratio. The experimental results of rolling bearing show that the algorithm can adaptively filter out strong noise points and keep the information of peak in the signal well, which can improve the accuracy of rolling bearing fault diagnosis.
Highly Effective Crosslinker for Redox-Sensitive Gene Carriers
Authors: Lin Lin , Chen Jie , Hu Yingying , Fang Huapan , Wang Kui , Tian Huayu , Chen Xuesi
Published: December 2021

Polyethyleneimine (PEI) has been extensively used as a common gene carrier due to its high gene transfection efficiency. PEI1.8k shows significantly lower cytotoxicity than its high molecular weight counterparts. However, it also has the problem of low gene transfection efficiency. To address the dilemma, a highly effective crosslinker (DTME) was synthesized to react with PEI1.8k to obtain CS-PEI1.8k. The reaction showed several advantages, such as a fast process in room temperature within nine hours with the product which can directly complex with DNA after removing the solvent. The ability of CS-PEI1.8k to agglomerate with DNA was proven by particle size, zeta potential, and gel retardation assays. The cytotoxic in vitro transfection ability and cell internalization capacity of CS-PEI1.8k were tested to verify the transfection capacity of CS-PEI1.8k. Moreover, we also studied the mechanism of the relatively high level of gene transfection by this binary complex compared with PEI25k.
Diode Laser Surgery as a Conservative Management of Hairy Tongue Lesion Resistance to Treatment
Authors: Samiei Nazanin , Ghane Hadi Kaseb , Fekrazad Reza
Published: December 2021

Hairy tongue is a furry appearance on the dorsum surface of the tongue with variable colors. This lesion is due to defective shedding of filiform papillae. Various treatments are proposed for this condition like keratolytic agents, surgical procedure with a scalpel, or laser application. In this case study, we reported successful treatment of hairy tongue with a diode laser. The diode laser with wavelength 810 nm, power of 4 watts, a pulse width of 20 milliseconds, and an interval of 20 milliseconds by a 400-micron optical fiber was selected for treatment of this lesion. There was no bleeding during this minimally invasive surgery, and the patient experienced a low level of pain. Loss of taste function was completely resolved. Based on the result of this study, a diode laser can be a good alternative for minimally invasive surgical treatment of hairy tongue.
Using Hybrid Machine Learning Methods to Predict and Improve the Energy Consumption Efficiency in Oil and Gas Fields
Authors: Li Jun , Guo Yidong , Zhang Xiangyang , Fu Zhanbao
Published: December 2021

Oil and gas will remain essential to global economic development and prosperity for decades to come, and the oil and gas industry is an energy-intensive industry. Thus, enhancing energy efficiency for producing oil and gas in oil and gas companies is an important issue. The intelligent energy consumption prediction method with the ability to analyze energy consumption patterns and to identify targets for energy saving proved itself as an effective approach for energy efficiency in many industrial domains. Moreover, prediction of energy consumption enables managers to scientifically plan out the energy usage of energy production and to shift energy usage to off-peak periods. However, it still remains a challenging issue to some degree with the unpredictability and uncertainty caused by various energy consumption behaviors, and this phenomenon is becoming more obvious in the oil and gas company. To this end, in our work, we primarily discussed the forecasting of the energy consumption in the oil and gas company. Firstly, four different forecasting models, support vector machine, linear regression, extreme learning machine, and artificial neural network, were trained on the training dataset and then evaluated by the test dataset. Secondly, in order to enhance the energy consumption prediction accuracy, the combinations of all these four models were examined with the RMSE value by taking the average of two models’ outputs. The outcomes show that these four different models are able to predict energy consumption with good accuracy, but the hybrid model—artificial neural network and extreme learning machine—would present higher accuracy. In addition, the hybrid model is installed in the energy management system of the oil and gas industry to manage oil field energy consumption and improve the efficiency.
MicroRNA Hsa-Let-7b Regulates the Osteogenic Differentiation of Human Periodontal Ligament Stem Cells by Targeting CTHRC1
Authors: Fu Lin , Li Na , Ye Yu , Ye Xiaying , Xiao Tong , Wu Xiao , Ma Yanxia , Yu Jinhua
Published: December 2021

Let-7 miRNA family has been proved as a key regulator of mesenchymal stem cells’ (MSCs’) biological features. However, whether let-7b could affect the differentiation or proliferation of periodontal ligament stem cells (PDLSCs) is still unknown. Here, we found that the expression of hsa-let-7b was visibly downregulated after mineralization induction of PDLSCs. After transfected with hsa-let-7b mimics or inhibitor reagent, the proliferation ability of PDLSCs was detected by cell counting kit-8 (CCK-8), flow cytometry, and 5-ethynyl-2-deoxyuridine (EdU) assay. On the other hand, the osteogenic differentiation capacity was detected by alkaline phosphatase (ALP) staining and activity, alizarin red staining, Western blot, and quantitative real-time reverse-transcription polymerase chain reaction (qRT-PCR). We verified that hsa-let-7b did not significantly impact the proliferation ability of PDLSCs, but it could curb the osteogenic differentiation of PDLSCs. Besides, we predicted CTHRC1 acts as the downstream gene of hsa-let-7b to affect this process. Moreover, the combination of CTHRC1 and hsa-let-7b was verified by dual luciferase reporter assay. Our results demonstrated that the osteogenic differentiation of PDLSCs was enhanced after inhibiting hsa-let-7b, while was weakened after cotransfection with Si-CTHRC1. Collectively, hsa-let-7b can repress the osteogenic differentiation of PDLSCs by regulating CTHRC1.
[Retracted] Generalized Zero‐Adjusted Models to Predict Medical Expenditures
Authors: Xu Xin , Ye Tao , Chu Dongxiao
Published: December 2021

In healthcare research, medical expenditure data for the elderly are typically semicontinuous and right‐skewed, which involve a point mass at zero and may exhibit heteroscedasticity. The problem of a substantial proportion of zero values prevents traditional regression techniques based on the Gaussian, gamma, or inverse Gaussian distribution, which may lead to understanding the standard errors of the parameters and overestimating their significance. A common way to counter the problem is using zero‐adjusted models. However, due to the right‐skewness in the nonzeros’ response, conventional zero‐adjusted models such as zero‐adjusted gamma, zero‐adjusted Inverse Gaussian, and classic Tobit may not perform well. Here, we firstly generalize those three types of the conventional zero‐adjusted model to solve the problem of right‐skewness in health care. The generalized zero‐adjusted models are very flexible and include the zero‐adjusted Weibull, zero‐adjusted gamma, zero‐adjusted inverse Gaussian, and classic Tobit models as their special cases. Using the Chinese Longitudinal Healthy Longevity Survey, we find that, according to the AIC, SBC, and deviance criteria, the zero‐adjusted generalized gamma model is the best one of these generalized models to predict the odds of zero cost accurately. In order to depict the predictors affecting the amount expenditure, we further discuss the situations where the mean, dispersion of a nonzero amount expenditure and model the probability of a zero amount of ZAGG in terms of predictor variables using suitable link functions, respectively. Our analysis shows that age, health, chronic diseases, household income, and residence are the main factors influencing the medical expenditure for the elderly, but the insurance is not significant. To the best of our knowledge, little study focused on these situations, and this is the first time.
Influence of Silica Exposure for Lung Silicosis Rat
Authors: Jiao Jie , Li Li , Yao Wu , Qin Weidong , Hao Changfu , Lu Lingeng
Published: December 2021

Objective. To investigate the influence of silica exposure on the expression of connective tissue growth factor (CTGF), transforming growth factor beta-1 (TGF-β1), and platelet-derived growth factor (PDGF) in lung silicosis rat. Methods. Wistar rats were divided into an experimental group and a control group. In the experimental group, rats were exposed to silica by intratracheal instillation. In the control group, rats were exposed to physiological saline by intratracheal instillation. After 45 days, we compared the level of fibrosis and CTGF, TGF-β1, and PDGF in the lungs by immunohistochemistry or reverse transcription-polymerase chain reaction between the two groups. Results. The results showed that the expression levels of CTGF, TGF-β1, and PDGF mRNA were significantly higher in the experimental group than those in the control group (

P
<
0.05

). The positive staining of CTGF, TGF-β1, and PDGF mRNA was found in the cytoplasm, especially in the silicotic nodules of the hyalinisation section and cell endochylema of the alveolar macrophages, type II pneumonocytes, and lung tracheal epithelium. There were significantly positive correlations between CTGF, TGF-β1, and PDGF expressions (

P
<
0.05

). A protein–protein interaction analysis showed interactions between TGF-β1, CTGF, and PDGF. Conclusions. TGF-β/CTGF signaling pathway plays an important role in silicosis. Silicon dioxide exposure can induce the expression of CTGF, TGF-β1, and PDGF.
Sequestration of Hazardous Dyes from Aqueous Solution Using Raw and Modified Agricultural Waste
Authors: Jegede Mobolaji M. , Durowoju Olatunde S. , Edokpayi Joshua N.
Published: December 2021

The continuous degradation of surface water quality by dye materials is of concern globally. Agricultural waste Litchi chinensis (LC) peel in its raw (RL) and modified (CL) forms was used as potential sorbents for sequestration of Congo red (CR) dye from an aqueous solution. The sorbents were characterized before and after sorption with Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), Brunauer, Emmett, and Teller (BET) surface area analysis, and X-ray diffraction (XRD). Determination of the point of zero charge (PZC) suggested CR dye sorption from an aqueous solution would be best in acidic pH. Batch experimental drivers such as the effects of time, dosage, initial concentration, pH, and temperature were optimized and used. Results from the study showed that modification with citric acid (CA) reduced the equilibration time from 90 to 15 min. Change in water chemistry did not significantly affect the removal efficiency of the sorbent but rather slightly improved it for both sorbent types. The smaller particle size of <125  μm recorded higher removal efficiency than the larger one (>125  μm). The effect of temperature affects the sorption differently. For the RL system, it decreases with an increase in the temperature, while for the CL system it increases with an increase in temperature. The Langmuir isotherm best described the equilibrium data obtained based on the linearized coefficients with maximum sorption capacities ([Formula: see text]) of 55.56 mg/g (RL) and 58.48 mg/g (CL). The pseudo-second-order model also best described the kinetic data. The thermodynamics study showed that the reaction is both feasible and spontaneous. Both sorbents recorded high removal efficiency for other dyes such as rhodamine B, methylene blue, methyl orange, malachite green, and erythrosin B. The five cycled regeneration/sorption experiments with 0.1 M NaOH as the desorbing agent showed that the regenerated sorbents efficiently removed CR dye from an aqueous solution close to their virgin samples for the first three cycles. This research, therefore, establishes LC peel as a potential eco-friendly, readily available, and effective sorbent for sequestration of hazardous dyes from wastewater.
A Chinese Patient with Spastic Paraplegia Type 4 with a De Novo Mutation in the SPAST Gene
Authors: Xu Li , Peng Zijuan , Zhou Chunhui , Wang Jiqing , Luo Hunjin , Lu Qin , Bao Zhengjun
Published: December 2021

Background. Spastic paraplegia type 4 (SPG4) is the most common type of hereditary spastic paraplegia (HSP) caused by mutations in the SPAST gene. Case Presentation. We report the case of a 27-year-old pregnant Chinese woman with HSP in whom we identified a missense mutation in the SPAST gene (c.1496G>A, p.Arg499His) and a nonsense mutation in the NEFH gene (c.289G>T, p.Glu97

∗

) via whole-exome sequencing; this finding corroborated that of Sanger sequencing. The patient exhibited the pure SPG4 phenotype with onset during childhood. The SPAST mutation was absent in the parents and paternal relatives. However, the NEFH mutation was identified in five people with no clinical phenotype. Based on theoretical conjecture and the family gene segregation information, we concluded that the SPAST mutation, but not the NEFH mutation, accounted for the proband’s phenotype. Eventually, the woman gave birth to a healthy baby girl with the NEFH mutation. Conclusion. In this report, we identified a missense mutation in the SPAST gene (p.Arg499His) in a 27-year-old pregnant Chinese woman with HSP. We believe that this study expands the knowledge about the clinical parameters and mutation spectrum of SPG4.
Clinical and Genetic Findings of the First Report of PAPA Syndrome in Brazil
Authors: Fernandes Sérgio Júlio , Valdomir Nadaf Maria Isabel , Monteiro Nauro Hudson , Nadaf Izabel Nazira , Lélis Cleiton Ribeiro , Takano Bianca Yumi , Gabriella de Camargo Monteiro Bárbarah , Gabriella de Camargo Monteiro Nyvea , Takano Olga Akiko , Mendonça Leonardo Oliveira
Published: December 2021

Background. PAPA syndrome (MIM #604416) is a rare monogenic autoinflammatory disease genetically transmitted in an autosomal dominant trait that results from missense mutations in the proline-serine-threonine phosphatase-interactive protein 1 (PSTPIP1) gene located on chromosome 15 and is characterized by sterile pyogenic arthritis, pyoderma gangrenosum, and cystic acne. We describe the clinical and molecular findings of two related Brazilian patients with PAPA syndrome. Case Presentation. A 7-year-and-3-month-old boy with nonconsanguineous parents had had recurrent pyoarthritis since the age of 5 years and 8 months. During his last and long hospitalization, the lack of improvement with antibiotics, evidence of increased inflammatory activity, repeated arthrotomies, draining purulent fluid that had negative cultures, and the history of trauma, all on in a clinical background of pyoarthritis, led to the suspicion of an autoinflammatory syndrome. This was confirmed by the good clinical response to corticotherapy. Genetic sequencing confirmed the diagnosis of PAPA syndrome, with the pathogenic mutation c.688 G > A (p. Ala230Thr) in the PSTPIP1 gene present in the patient and in the mother. Conclusions. This case illustrates that in children with recurrent/recalcitrant sterile recurrent pyogenic arthritis/osteomyelitis, the possibility of an underlying immunological condition should be considered. In both, recurrent infections or recurrent inflammation, many genes involved in the inborn errors of immunity can be associated, and a correct and precocious diagnosis is necessary to avoid mobility and mortality. To the best of our knowledge, this is the first report of PAPA syndrome in Brazil.
Reinforcement Learning for Interference Coordination Stackelberg Games in Heterogeneous Cellular Networks
Authors: Sun Chen , Wu Shiyi , Zhang Bo
Published: December 2021

In future heterogeneous cellular networks with small cells, such as D2D and relay, interference coordination between macro cells and small cells should be addressed through effective resource allocation and power control. The two‐step Stackelberg game is a widely used and feasible model for resource allocation and power control problem formulation. Both in the follower games for small cells and in the leader games for the macro cell, the cost parameters are a critical variable for the performance of Stackelberg game. Previous studies have failed to adequately address the optimization of cost parameters. This paper presents a reinforcement learning approach for effectively training cost parameters for better system performance. Furthermore, a two‐stage pretraining plus ε‐greedy algorithm is proposed to accelerate the convergence of reinforcement learning. The simulation results can demonstrate that compared with the three beachmarking algorithms, the proposed algorithm can enhance average throughput of all users and cellular users by up to 7% and 9.7%, respectively.
Comparison of the Meta-Active Machine Learning Model Applied to Biological Data-Driven Experiments with Other Models
Authors: Wang Hao
Published: December 2021

Currently, many methods that could estimate the effects of conditions on a given biological target require either strong modelling assumptions or separate screens. Traditionally, many conditions and targets, without doing all possible experiments, could be achieved by driven experimentation or several mathematical methods, especially conversational machine learning methods. However, these methods still could not avoid and replace manual labels completely. This paper presented a meta-active machine learning method to resolve this problem. This project has used nine traditional machine learning methods to compare their accuracy and running time. In addition, this paper analyzes the meta-active machine learning method (MAML) compared with a classical screening method and progressive experiments. The obtained results show that applying this method yields the best experimental results on the current dataset.
Ash Evaluation of Indonesian Coal Blending for Pulverized Coal-Fired Boilers
Authors: Hariana  , Prismantoko Adi , Ahmadi Ganda Arif , Darmawan Arif
Published: December 2021

Coal calorific value is one of the main considerations for using coal as a power plant fuel. In addition, the requirements for indications of slagging and fouling are also important to maintain combustion efficiency. However, coal power plants often experience problems in boiler operations due to the use of certain types of coal, even though they have a relatively high calorific value. This research investigates the effect of coal blending on ash fouling and slagging in an experimental investigation using a drop tube furnace with or without additives. Five different types of coal from different locations have been used in this study. Pulverized low-rank coal samples are burned in a drop tube furnace at 1,175°C with probe temperatures of 550°C and 600°C, corresponding to the combustion chamber of 600 MW power plants, including superheater and reheater areas. The ash particles’ characteristics and material composition were also analyzed using scanning electron microscopy with energy-dispersive X-ray (SEM-EDX) and X-ray diffraction (XRD), respectively. All coal mixture combinations demonstrated potential as a fuel for power plants that use pulverized coal-fired boilers. Because of its capacity to reduce slagging and fouling potentials, combining coal blending with the use of chemical additives yielded the greatest results.
Construction of a 5G Wireless Semantic Web-Assisted English Digital Learning Resource Query System
Authors: Liu Lili
Published: December 2021

Based on the 5G wireless semantic network, this paper realizes the construction of the English digital learning resources query system, providing the query and management functions for English digital learning resources, and realizes the integration of functions and resources on the digital learning system and mobile learning system. The platform is put into practical application, and data analysis is conducted to conclude how this system is used and whether it is conducive to improving students’ interest in learning English and their English proficiency. We propose a quality algorithm for 5G wireless networks, which not only captures the characteristics of 5G wireless networks such as local broadcast and node movement but also combines quality predicates as guards with broadcast reception actions, which are used to portray that a node can continue to execute subsequent processes only when the node reception actions satisfy certain conditions, which works together with the node default value mechanism to reduce the impact caused by unreliable links. The query content is interpreted and supplemented at the semantic level by using synonym expansion, and the knowledge base is used to filter the synonym expansion and further expand the synonym expansion query based on knowledge structure, to tap the implicit knowledge points related to the query, and to fuse the two extensions to realize the knowledge-based query expansion. We use 5G wireless semantic web-related technologies to build an English digital learning resource query system with complete functions and good experience across terminals. Through the questionnaire survey and data analysis of the users of this system, it is found that the system is well used and effectively enhances students’ interest in learning English and improves learning efficiency. By applying the experimental comparison method, it is known that this system has improved students’ English proficiency to a certain extent.
Estimation of the Exposure–Response Relation between Benzene and Acute Myeloid Leukemia by Combining Epidemiologic, Human Biomarker, and Animal Data
Authors: Scholten Bernice , Portengen Lützen , Pronk Anjoeka , Stierum Rob , Downward George S. , Vlaanderen Jelle , Vermeulen Roel
Published: December 2021

Background:

Chemical risk assessment can benefit from integrating data across multiple evidence bases, especially in exposure–response curve (ERC) modeling when data across the exposure range are sparse.

Methods:

We estimated the ERC for benzene and acute myeloid leukemia (AML), by fitting linear and spline-based Bayesian meta-regression models that included summary risk estimates from non-AML and nonhuman studies as prior information. Our complete dataset included six human AML studies, three human leukemia studies, 10 human biomarker studies, and four experimental animal studies.

Results:

A linear meta-regression model with intercept best predicted AML risks after cross-validation, both for the full dataset and AML studies only. Risk estimates in the low exposure range [<40 parts per million (ppm)-years] from this model were comparable, but more precise when the ERC was derived using all available data than when using AML data only. Allowing for between-study heterogeneity, RRs and 95% prediction intervals (95% PI) at 5 ppm-years were 1.58 (95% PI, 1.01–3.22) and 1.44 (95% PI, 0.85–3.42), respectively.

Conclusions:

Integrating the available epidemiologic, biomarker, and animal data resulted in more precise risk estimates for benzene exposure and AML, although the large between-study heterogeneity hampers interpretation of these results. The harmonization steps required to fit the Bayesian meta-regression model involve a range of assumptions that need to be critically evaluated, as they seem crucial for successful implementation.

Impact:

By describing a framework for data integration and explicitly describing the necessary data harmonization steps, we hope to enable risk assessors to better understand the advantages and assumptions underlying a data integration approach.

See related commentary by Keil, p. 695