bluuebunny/crossref_metadata_2025 huggingface dataset:
Uncertainty-aware Prediction Validator in Deep Learning Models for Cyber-physical System Data
Authors: Catak Ferhat Ozgur , Yue Tao , Ali Shaukat
Published: March 2022

The use of Deep learning in Cyber-Physical Systems (CPSs) is gaining popularity due to its ability to bring intelligence to CPS behaviors. However, both CPSs and deep learning have inherent uncertainty. Such uncertainty, if not handled adequately, can lead to unsafe CPS behavior. The first step toward addressing such uncertainty in deep learning is to quantify uncertainty. Hence, we propose a novel method called
NIRVANA
(uNcertaInty pRediction ValidAtor iN Ai) for prediction validation based on uncertainty metrics. To this end, we first employ prediction-time Dropout-based Neural Networks to quantify uncertainty in deep learning models applied to CPS data. Second, such quantified uncertainty is taken as the input to predict wrong labels using a support vector machine, with the aim of building a highly discriminating prediction validator model with uncertainty values. In addition, we investigated the relationship between uncertainty quantification and prediction performance and conducted experiments to obtain optimal dropout ratios. We conducted all the experiments with four real-world CPS datasets. Results show that uncertainty quantification is negatively correlated to prediction performance of a deep learning model of CPS data. Also, our dropout ratio adjustment approach is effective in reducing uncertainty of correct predictions while increasing uncertainty of wrong predictions.
Synthesis, Antioxidant, and Antidiabetic Activities of Ketone Derivatives of Succinimide
Authors: Waheed Bushra , Mukarram Shah Syed Muhammad , Hussain Fida , Khan Mohammad Ijaz , Zeb Anwar , Jan Muhammad Saeed
Published: March 2022

The prevalence of diabetes mellitus is persistently increasing globally creating a serious public health affliction. Diabetes mellitus is categorized into two major types designated as type I and Type II. Type I diabetes mellitus is characterized by complete lack of secretion of insulin, while Type II diabetes mellitus is the resistance of peripheral tissues to the action of insulin and inadequate compensatory secretion of insulin. Chronic hyperglycemia associated with diabetes causes failure of cardiovascular system, nervous system, kidneys, and eyes. At present, different types of drugs are used for the management of diabetes, but each of them is associated with more or less serious side effects. Therefore, we need to develop new therapeutic agents that have better efficacy and safety profile. In this study, three ketone derivatives of succinimides were synthesized based on Michael addition and characterized using NMR. All the synthesized compounds were checked for their in vitro α-amylase and α-glucosidase inhibitory activities. Further the synthesized compounds were also explored for their antioxidant activities, i.e, DPPH and ABTS assays. Based on the in vitro results, the synthesized compounds were further evaluated for in vivo antidiabetic activity. The synthesized compounds were (2-oxocyclohexyl)-1-phenylpyrrolidine-2,5-dione (BW1), benzyl-3-(2-oxocyclohexyl) pyrrolidine-2,5-dione (BW2), and (4-bromophenyl)-3-(2-oxocyclohexyl) pyrrolidine-2,5-dione (BW3). BW1 showed the highest inhibitory activity for DPPH causing 83.03 ± 0.48 at 500 μg/ml with IC50 value of 10.84 μg/ml and highest inhibitory activity for ABTS causing 78.35 ± 0.23 at 500 μg/ml with IC50 value of 9.40 μg/ml against ascorbic acid used as standard. BW1 also exhibited the highest activity against α-amylase and α-glucosidase inhibition causing 81.60 ± 0.00 at concentrations of 500 μg/ml with IC50 value of 13.90 μg/ml and 89.08 ± 1.04 at concentrations of 500 μg/ml with IC50 value of 10.49 μg/ml, respectively, against the standard drug acarbose.
Effect Evaluation of Electronic Health PDCA Nursing in Treatment of Childhood Asthma with Artificial Intelligence
Authors: Li Wensong , Liu Zhidong , Song Tao , Zhang Chunlong , Xue Jianzhen
Published: March 2022

Asthma in children has a long duration and is prone to recurring attacks. Children will feel chest tightness, shortness of breath, cough, and difficulty breathing when they are onset, which has a serious impact on their health. Clinical nursing is of great significance in the treatment of childhood asthma. At present, the electronic health PDCA nursing model is widely used in clinical nursing as a common and effective nursing method. Therefore, it is very important to evaluate the efficacy of the PDCA nursing model in the treatment of childhood asthma. With the development of artificial intelligence, artificial intelligence can be used to evaluate the effect of the PDCA nursing model in the treatment of childhood asthma. The BP network can effectively perform data training and discrimination, but its training efficiency is low, and it is easily affected by initial weights and thresholds. Aiming at this defect, this work uses the genetic simulated annealing (GSA) algorithm to improve it. In view of the problems that the genetic algorithm falls into local minimum and simulated annealing algorithm has a slow convergence speed, the improved genetic simulated annealing algorithm is used to optimize the BP neural network, and an improved genetic simulated annealing BP network (IGSA-BP) is proposed. The algorithm not only reduces the problem that the BP network has an influence on initial weight and threshold on the algorithm but also improves the population diversity and avoids falling into local optimum by improving the crossover and mutation probability formula and improving Metropolis criterion. The proposed method has more efficient performance.
Manufacturing and Separation Characteristics of Hemodialysis Membranes to Improve Toxin Removal Rate
Authors: Lee Gyeong Tae , Hong Young Ki
Published: March 2022

With the recently growing interest in health care, hemodialysis is being performed not only to treat patients with renal disease but also to improve blood circulation. At present, filters used for hemodialysis are manufactured only in certain countries, and all other countries must rely on imports. In this study, polyethersulfone (PES), which has excellent blood compatibility, was used as the main material to develop hemodialysis membranes for hemodialysis filters, and these hemodialysis membranes were prepared by adding a hydrophilic polymer, polyvinylpyrrolidone (PVP), and varying the type of nonsolvent during the manufacturing process to improve the toxin removal rate and biocompatibility. The addition of PVP was confirmed through attenuated total reflection Fourier transform infrared (ATR-FTIR), and the structure of the membranes depending on the nonsolvent was analyzed through scanning electron microscopy (SEM) and atomic force microscopy (AFM) images. The contact angle results indicated that the hydrophilicity of the membrane surface was improved as the concentration of PVP increased. The results of the toxin filtration efficiency experiment using urea, creatinine, and bovine serum albumin (BSA) confirmed removal rates of 58.8% and 56.87%, respectively, and a protein loss of less than 8%. Also, cell viability was over 90% at the PVP concentration of 2% or higher. A preliminary study was conducted on the improvement of toxin filtration efficiency and the development potential of these hemodialysis membranes with excellent biocompatibility.
Anesthetic Approach in Ambulatory Vitrectomy: Peribulbar Block vs. Balanced General Anesthesia
Authors: Gouveia Bárbara , Ferreira Leonardo , Maia Paula
Published: March 2022

Background. Vitrectomy is one of the most common outpatient ophthalmic surgeries. The anesthetic technique used in outpatient surgery should contribute to a faster functional recovery, better pain control, and fewer complications. The aim of this study was to compare peribulbar block and balanced general anesthesia, in patients undergoing outpatient vitrectomy. Methods. A prospective cohort study was carried out, including adult patients undergoing ambulatory vitrectomy, between January and February 2018. Peribulbar block or balanced general anesthesia was the independent variable analyzed. Clinical and perioperative variables were evaluated, namely, postoperative pain, nausea, and vomiting in the postoperative period, intraoperative hypotension, patient satisfaction with the anesthetic technique, time to oral diet introduction and to hospital discharge, operating room occupancy time, and pharmacological costs. SPSS® 27 was used for statistical analyses. Results. Twenty-one patients were evaluated, 11 of whom underwent peribulbar block and 10 underwent balanced general anesthesia. Patients undergoing peribulbar block did not experience postoperative pain when compared to patients undergoing balanced general anesthesia (

p
=
0.001

). Intraoperative hypotension occurred in 18.2% of patients undergoing peribulbar block and in 70% of those undergoing balanced general anesthesia (

p
=
0.03

). Time to oral diet introduction (<1 hour vs. > 2 hours;

p
<
0.05

), operating room occupancy time (70 vs. 90 minutes;

p
=
0.027

), time to hospital discharge (17 vs. 22.5 hours;

p
=
0.004

), and pharmacological costs (4.65 vs. 12.09 euros;

p
<
0.05

) were lower in patients undergoing peribulbar block versus balanced general. Conclusions. Peribulbar block seems to meet the criteria of an ideal anesthetic technique in outpatient vitrectomy surgery.
Computed Tomography Images under the Nomogram Mathematical Prediction Model in the Treatment of Cerebral Infarction Complicated with Nonvalvular Atrial Fibrillation and the Impacts of Virus Infection
Authors: Zhu Yi , Cheng Hai , Min Rui , Wu Tong
Published: March 2022

The aim of this work was to explore the effect of the nomogram mathematical model on the treatment of cerebral infarction complicated with nonvalvular atrial fibrillation (NVAF) and viral infection. The data were scanned by a circular trajectory fan beam isometric scanning mode system (scanning system), and the speckle noise of computed tomography (CT) images was smoothed by Lee filtering. 52 patients with postoperative recurrent viral infection (RVI group) and 248 patients without postoperative recurrent viral infection (NRVI group) were selected for retrospective analysis. The mathematical model curve was then analyzed through calibration plots and decision curves to predict the accuracy of the mathematical model. The results showed that the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy based on the training set were 0.7868, 0.7634, 0.6982, and 0.7146, respectively. The AUC, sensitivity, specificity, and accuracy based on the validation set were 0.7623, 0.7734, 0.6882, and 0.6948, respectively. There was no significant difference in the AUC between the two groups (P > 0.05), indicating that the nomogram mathematical prediction model had high repeatability. In conclusion, CT images based on the nomogram mathematical prediction model had good predictive ability in the treatment of cerebral infarction complicated with NVAF.
A Multioffspring Genetic Algorithm Based on Sorting Grouping Selection and Combination Pairing Crossover
Authors: Jin Xin , Wang Fulin
Published: March 2022

A multi-offspring genetic algorithm based on sorting grouping selection and combination pairing crossover was proposed in this paper. First, individuals in the population were sorted according to their objective function values, and the remaining individuals were divided into several groups after eliminating the worst. Then, the selection operation, which has the advantage of a simplified calculation that can be easily performed, was implemented. Second, a combination pairing crossover operator was designed. Individuals from different groups were selected for new combinations. In a combination, if a crossover condition was met, individuals pairing and transposons crossover operation were made. Otherwise, offspring copies of the individuals in the combination were used, which increase the opportunity of generating better offspring by producing multi-offspring. Finally, a new population was formed by adopting basic bit mutation operator, elitism policy and the strategy of multi-offspring population competition. Moreover, the catastrophe mechanism has been introduced into improved algorithm to avoid premature convergence. The test results on the functions of CEC 2017 test suites shown that the algorithm proposed in this paper has better search performance, stability and faster convergence to the global optimal solution. These results thus verified the effectiveness and feasibility of the algorithm proposed in this paper. Applying the improved algorithm to the location optimization problem of agricultural product logistics facilities, it shown that the improved algorithm is an effective method to solve the location optimization.
Efficacy of Date Palm Pollen in the Male Sexual Dysfunction after Coronary Artery Bypass Graft: A Randomized, Double-Blind, Clinical Trial
Authors: Hooshang Hamed , Farahani Ali Vasheghani , Rezaeizadeh Hossein , Forouzannia Seyed Khalil , Alaeddini Farshid , Ashraf Haleh , Karimi Mehrdad
Published: March 2022

Background. Bypass graft surgery of the coronary artery has a significant effect on the creation and development of sexual dysfunction among male patients. The previous studies have demonstrated that date palm pollen (DPP) increases the count and quality of sperm. Additionally, it has been shown that DPP has a protective effect against myocardial infarction and cardiac remodeling. Therefore, this is the first study investigating the impact of DPP (Phoenix dactylifera L.) on managing male sexual dysfunction after coronary artery bypass graft. Methods. This randomized, double-blind, placebo-controlled clinical trial was conducted on 60 patients (DPP group n = 30, control group n = 30) of Iranian men after coronary artery bypass graft. Two parallel groups were randomly generated from the study participants. The intervention group was prescribed 3 grams of the powder of DPP twice a day (9 AM and 9 PM) for two months, while the control group received the same prescription of the placebo powder. Results. The DPP consumption significantly increased the International Index of Erectile Function (IIEF) (from 23.21 to 46.57) and the Hurlbert Index of Sexual Desire (HISD) (from 59.39 to 64.45) scores over time in the intervention group. However, there were no significant changes in the control group. Conclusion. Daily intake of 6 g DPP for two months exhibited beneficial effects on the symptoms of male sexual dysfunction in patients who have undergone coronary artery bypass graft (CABG).
Mortality Predictive Value of APACHE II and SOFA Scores in COVID-19 Patients in the Intensive Care Unit
Authors: Beigmohammadi Mohammad Taghi , Amoozadeh Laya , Rezaei Motlagh Forough , Rahimi Mojgan , Maghsoudloo Maziar , Jafarnejad Behzad , Eslami Babak , Salehi Mohammad Reza , Zendehdel Kazem
Published: March 2022

Background. COVID-19 pandemic has become a global dilemma since December 2019. Are the standard scores, such as acute physiology and chronic health evaluation (APACHE II) and sequential organ failure assessment (SOFA) score, accurate for predicting the mortality rate of COVID-19 or the need for new scores? We aimed to evaluate the mortality predictive value of APACHE II and SOFA scores in critically ill COVID-19 patients. Methods. In a cohort study, we enrolled 204 confirmed COVID-19 patients admitted to the intensive care units at the Imam Khomeini hospital complex. APACHE II on the first day and daily SOFA scoring were performed. The primary outcome was the mortality rate in the nonsurvived and survived groups, and the secondary outcome was organ dysfunction. Two groups of survived and nonsurvived patients were compared by the chi-square test for categorical variables and an independent sample t-test for continuous variables. We used logistic regression models to estimate the mortality risk of high APACHE II and SOFA scores. Result. Among 204 severe COVID-19 patients, 114 patients (55.9%) expired and 169 patients (82.8%) had at least one comorbidity that 103 (60.9%) of them did not survive (

P
=
0.002

). Invasive mechanical ventilation and its duration were significantly different between survived and nonsurvived groups (

P
≤
0.001

and

P
=
0.002

, respectively). Mean APACHE II and mean SOFA scores were significantly higher in the nonsurvived than in the survived group (14.4 ± 5.7 vs. 9.5 ± 5.1,

P
≤
0.001

, 7.3 ± 3.1 vs. 3.1 ± 1.1,

P
≤
0.001

, respectively). The area under the curve was 89.5% for SOFA and 73% for the APACHE II score. Respiratory diseases and malignancy were risk factors for the mortality rate (

P
=
0.004

and

P
=
0.007

, respectively) against diabetes and hypertension. Conclusion. The daily SOFA was a better mortality predictor than the APACHE II in critically ill COVID-19 patients. But they could not predict death with high accuracy. We need new scoring with consideration of the prognostic factors and daily evaluation of changes in clinical conditions.
A Network Meta-Analysis of the Differences in Effectiveness and Safety between Nivolumab and Targeted Drug Therapy in Metastatic Renal Cell Carcinoma
Authors: Qu Hongchen , Mu Zhongyi , Wang Kai , Hu Bin
Published: March 2022

Objective. Nivolumab plus other drugs have provided significant benefits in patients with metastatic renal cell carcinoma (mRCC), but most of the available comparisons were conducted with sunitinib, and differences in efficacy with targeted drugs were marginally reported. Thus, this study used a network meta-analysis to compare the difference in efficacy between nivolumab combination therapy and other targeted agents. Methods. In this systematic review and network meta-analysis, we searched PubMed, Embase, and Cochrane Library databases for randomized controlled trials (RCTs) with the time set from database establishment to December 10, 2021, using programmed death factor 1 (PD-1) inhibitors, nivolumab, and sunitinib in the treatment of mRCC. Progression-free survival (PFS), overall survival (OS), response rate (RR), and adverse events (AEs) were collated and analyzed using the gemtc package in the R language. Results. A total of ten studies satisfied the inclusion criteria, including 6568 RCC cases, 10 drugs, and 11 treatment protocols. The Ate_Axi protocol obtained similar PFS to the Niv_Cab protocol, which outperformed that of all other protocols. The Niv_Cab regimen showed better PFS benefits than the Niv_Ipi regimen (HR < 1,

P
<
0.05

), and Niv_Ipi had superior PFS compared to the Ate, Eve, Paz, Sor, and Sun scheme. The regimens Cab, Niv_Cab, and Niv_Ipi were associated with the best PFS benefits, while Eve is the least favorable drug in terms of PFS. Niv_Cab showed better OS than Ate_Bev, Eve, Paz, Sor, and Sun. The patients given Ate_Bev, Eve, Paz, Sor, and Sun had inferior OS to those given Niv_Ipi. The Pem_Axi, Niv_Cab, and Niv_Ipi regimens had the best OS, and that of Eve is considered least promising. The Niv_Cab protocol showed significantly better RRs than the Eve, Paz, Sor, and Sun protocols, and the Ate_Bev, Eve, Paz, Sor, and Sun protocols presented superior RRs compared to the Niv_Ipi protocol. The Ate, Eve, and Niv_Ipi regimens had the lowest incidence of AEs, and the Sor regimen had the highest incidence of AEs. Conclusion. Among the targeted treatment options for mRCC, both Niv_Cab and Niv_Ipi yield better efficacy and safety in the treatment of mRCC, with Niv_Cab providing more survival benefit but with a less favorable safety profile.
Asymptotic Convergence Analysis and Error Estimate for Black-Scholes Model of Option Pricing
Authors: He Juan , Tu Wei , Zhang Aiqing
Published: March 2022

In this work, we discuss the numerical method for the solution of the Black-Scholes model. First of all, the asymptotic convergence for the solution of Black-Scholes model is proved. Second, we develop a linear, unconditionally stable, and second-order time-accurate numerical scheme for this model. By using the finite difference method and Legendre-Galerkin spectral method, we construct a time and space discrete scheme. Finally, we prove that the scheme has second-order accuracy and spectral accuracy in time and space, respectively. Several numerical experiments further verify the convergence rate and effectiveness of the developed scheme.
Study on Evaluation Theory of Bridge Damage State and Methodology on Early Warning of Danger
Authors: Jiang Guofu , Liang Qianxue , Wang Hua , Ju Yucai , Wang Haihua , Wang Xirui , Wang Longlin , Wang Wensheng
Published: March 2022

When evaluating and prewarning the damage state of bridges, the observation equation and state equation of bridge systems are not constructed in the existing methods, which would cause the evaluation results to be inconsistent with the actual damage state of bridges. Therefore, the existing methods have the problems of low evaluation accuracy, high false alarm rate, and poor real-time performance. In order to solve the above problems, this paper proposes a novel evaluation and judgment theory of bridge damage state and methodology on early warning of danger. The wavelet packet analysis method is used to construct the observation equation and state equation of bridge systems, which could provide a relevant basis for evaluating the damage state of bridges. Then, the fuzzy comprehensive evaluation method is used to construct the fuzzy evaluation model of the bridge damage state to evaluate and judge the damage state of bridges. According to the evaluation results, combined with mathematical-statistical analysis methods and principal component analysis methods, the methodology on early warning of danger for bridge structures can be realized. The experimental results showed that the proposed method has high evaluation and judgment accuracy, low false alarm rate, and good real-time performance and reliability.
Retrospective Study Comparing Clinical Outcomes of Fixed Dental Prostheses in Matched Groups of Bruxer and Nonbruxer Patients
Authors: Hawthan Mohammed , Chrcanovic Bruno R. , Larsson Christel
Published: March 2022

Background. Tooth-supported fixed dental prosthesis (FDP) is one of the most reliable treatment options to replace missing teeth. The longevity of the treatment could, however, be affected by several general and local factors, especially bruxism. Objective. To investigate the influence of bruxism on the long-term survival of tooth-supported FDPs in bruxers compared to a matched group of nonbruxers, taking several clinical variables into account. Materials and Methods. The present retrospective cohort study was based on records of patients treated with 3–7-unit tooth-supported FDPs with a minimum follow-up time of 6 months after prosthesis delivery. The criteria for the diagnosis of “possible” and “probable” sleep or awake bruxism were used. A matched group of nonbruxers was selected on the basis of similarities in four factors, patients’ gender and age, number of prosthetic units of the FDPs, and follow-up time. The paired-samples t-test or Wilcoxon signed rank test were used to compared mean values between the two groups. Contingency tables of categorical data were analyzed by McNemar’s test. Results. The cohort group consisted of 62 noncantilevered FDPs in each group, followed up for a mean of 110.1 and 106.5 months (bruxers and nonbruxers, respectively). Tooth-supported FDPs in bruxers presented significantly higher failure rate than in nonbruxers (32.3% vs. 25.8%, respectively;

p
=
0.001

). Loss of retention and tooth loss were the main reasons for failures in both groups. For nonsmokers, the FDP failure rate was higher in nonbruxers. Technical and biological complications were significantly more prevalent in bruxers compared to nonbruxers. Conclusions. Bruxism is suggested to increase technical and biological complications and FDP failure.
A Novel Discrete‐Time Leslie–Gower Model with the Impact of Allee Effect in Predator Population
Authors: Vinoth S. , Sivasamy R. , Sathiyanathan K. , Unyong B. , Vadivel R. , Gunasekaran Nallappan
Published: March 2022

The discrete‐time system has more complex and chaotic dynamical behaviors as compared to the continuous‐time system. This paper extends a discrete Leslie–Gower predator‐prey system with the Allee effect in the predator’s population, whose dynamics are analyzed and explored. We have determined the equilibrium points and studied their local stability properties. We find that the system undergoes flip bifurcation and Neimark–Sacker bifurcation around the interior equilibrium point by choosing the Allee parameter as a bifurcation parameter. We discuss the stability and direction of both bifurcations with the help of the normal form theory and center manifold theorem. The flip bifurcation and Neimark–Sacker bifurcation are the most common routes to the chaotic orbit in the discrete system. Moreover, we utilize state feedback, pole placement, and hybrid control methods to control the chaos in the system. The work is complete with the numerical simulations to confirm the analytical findings.
College Cross-Country Skiing Teaching and Sports Training Based on VR
Authors: Chen Wenying
Published: March 2022

As a kind of simulation equipment that can correctly simulate skiing actions, ski simulators are widely used in ski teaching and training in colleges. With the rapid development of VR, it has been widely used in the development of ski simulator systems. This article mainly talks about the research of college cross-country skiing teaching and sports training based on VR and intends to provide ideas and directions for combining VR with college cross-country skiing teaching and sports training. This article puts forward the research methods of cross-country skiing teaching and sports training in colleges based on VR, including the literature retrieval method, expert interview method, survey method, mathematical statistics method, logical analysis summary method, ski simulator algorithm, etc. At the same time, this paper also conducts experiments on cross-country skiing teaching and sports training in colleges and universities. The experimental results in this paper show that 96.67% of students believe that the college cross-country skiing teaching and sports training system based on VR can stimulate the enthusiasm of ski training.
Regional Double-Layer, High-Precision Indoor Positioning System Based on iBeacon Network
Authors: Zhang Xiaona , Zhang Shufang , Wang Chao , Sun Shujing
Published: March 2022

With the development of modern society, the demand for indoor positioning technology is higher and higher. The existing indoor positioning technology is difficult to really solve the problem of accuracy and achieve high-performance indoor positioning system design. Based on iBeacon equipment, this paper proposes a method to optimize received signal strength indication indoor positioning algorithm by using the Gaussian filtering method so as to reduce the adverse impact of multipath fading in indoor environment. In order to further improve the accuracy of indoor positioning algorithm, the stack automatic encoder in the deep neural network algorithm is introduced. Through the deep learning method, the high-dimensional information of the fingerprint database collected by the system can be extracted and the adverse impact of data noise on the database is also reduced. Through the simulation test of the system, it can be seen that the error of received signal strength indication indoor positioning algorithm based on extended Gaussian filter is small. Compared with the traditional iBeacon algorithm, the improved algorithm can achieve better data classification. The maximum error of the whole system is 1.02 M. Comprehensive analysis shows that the proposed indoor positioning system has a certain practical value and can be applied to the indoor positioning needs in a certain range of environment.
Research on Dynamic Characteristics of Stock Market Based on Big Data Analysis
Authors: Yang Ping , Hou Xiaohong
Published: March 2022

The stock market is a real and continuously evolving extremely complex dynamic system. This paper analyzes the change of stock market efficiency from the perspective of dynamic evolution, and the recursive graph method is used to obtain the dynamic characteristics of stock price time series. For the sharp rise and fall of stock prices, this paper uses the heuristic segmentation algorithm of nonlinear time series mutation detection to study the detection of market dynamics characteristics before the stock market crash. Based on the above research results, this paper studies the dynamic evolution of financial markets and the construction of a complex network of dynamic characteristics between financial markets. The simulation results show that there are typical characteristics of small world network in stock market complex network, the stock market complex network shows stronger synchronization ability, and the transmission range of information between the stock markets in the complex network is significantly expanded.
Information Monitoring of Animal Husbandry Industry Based on the Internet of Things and Wireless Communication System
Authors: Shen Yuhong
Published: March 2022

This paper was aimed at discussing the information monitoring of animal husbandry based on the Internet of Things and wireless communication system. The breeding and health of animals in the breeding industry has always been a topic that people talk about. The advent of the wireless communication system has made monitoring and positioning technologies more and more simple. The wireless communication network technology is applied to the environmental monitoring of animal breeding farms, and a real-time reporting system is designed to pay attention to animal health in real time. This article focuses on the connection between the two. First, this article briefly describes the state of the wireless communication network and the aquaculture industry, furthermore explains the research methods, such as the livestock breeding environment monitoring system model, which needs to have the characteristics of humanization, fast and simple, easy to maintain, high reliability, compatibility, scalability, and intelligence, and designs related monitoring systems and hardware systems to integrate carbon dioxide, ammonia, and other gas sensors with temperature and humidity sensors to sense the environment. Next, this article shows the wireless communication network monitoring and positioning algorithm, namely, the TOA-based wireless communication positioning algorithm and the LTE prediction algorithm. The predicted time is used as the link weight, and the weight within the wide link cluster is defined according to the time threshold, making the link maintain stability for a short time to enhance the network topology. Then, this article conducts experiments based on ZigBee wireless communication network sensor combined with improved genetic algorithm in the temperature and humidity test of farms, designs the environmental monitoring system, improves the algorithm, and cooperates with experiments and analysis to verify the feasibility and apply it to the temperature and humidity test of the livestock farm. The results are good, and the temperature and humidity errors are reduced by 88.28% and 84.21%, respectively. It has a certain degree of guidance. Finally, it is discussed and summarized. It can be seen that the system and algorithm designed in this paper have a good prospect in the development of animal husbandry. However, this algorithm takes a long time and has a broader research space.
Novel Multirole-Oriented Deep Learning Text Classification Model
Authors: Luo Ting
Published: March 2022

In order to improve the analysis of multiple roles in novels, this article applies the deep learning text classification model to the analysis of novel roles. Moreover, in this article, the scale space formed by multiple text images of the same size is called an octave, and the text image size of adjacent groups is halved to construct a Gaussian pyramid. In text classification, this article uses the argument and amplitude information to form a direction gradient histogram and takes the argument corresponding to the largest peak as a main direction of the key point. Finally, this article constructs an intelligent analysis model. The research results show that the deep learning text classification model for multiple roles in novels proposed in this article has good effects on role analysis and text classification. For film and television scripts, the classification analysis of analysis texts and the contrast creation have very good application help.
Data-Driven ICA-Bi-LSTM-Combined Lithium Battery SOH Estimation
Authors: Sun Hanlei , Sun Jianrui , Zhao Kun , Wang Licheng , Wang Kai
Published: March 2022

Lithium battery state of health (SOH) is a key parameter to characterize the actual battery life. SOH cannot be directly measured. In order to further improve the accuracy of SOH estimation of lithium batteries, a model combining incremental capacity analysis (ICA) and bidirectional long- and short-term memory (Bi-LSTM) neural networks based on health characteristic parameters is proposed to predict the SOH of lithium-ion batteries. First, the health characteristic parameters are initially selected from the lithium battery charging curve, and the health characteristics are extracted by the Pearson correlation coefficient, including the charging time of constant current, charging time of constant voltage, voltage change rate from 300 s to 1000 s, 200s of voltage per cycle at a time. Second, ICA was used to deeply mine the deep associations related to SOH and the peaks of IC curves and their corresponding voltages were extracted as additional inputs to the model. Then, Bi-LSTM is used to form a combined SOH estimation model through adaptive weighting factors. Finally, the verification is based on the 5th battery parameters of the NASA lithium battery data set. The experimental results show that the proposed combined model reduces the mean square error by 55.17%, 49.28%, and 41.47%, respectively, compared with single models such as BP neural network (BPNN), LSTM, and gated recurrent neural network (GRU).
Fatigability and the Role of Neuromuscular Impairments in Chronic Kidney Disease
Authors: Gollie Jared M. , Patel Samir S. , Harris-Love Michael O. , Cohen Scott D. , Blackman Marc R.
Published: March 2022

Background: The combination of neuromuscular impairments plus psychosocial aspects of chronic kidney disease (CKD) may predispose these patients to greater risk for experiencing increased levels of fatigability. There has been extensive clinical and scientific interest in the problem of fatigue in CKD and end-stage kidney disease (ESKD) patients, whereas less attention has been directed to understanding fatigability. Accordingly, the primary purposes of this review are to (1) discuss fatigue and fatigability and their potential interactions in patients with CKD and ESKD, (2) provide evidence for increased fatigability in CKD and ESKD patients, (3) examine how commonly experienced neuromuscular impairments in CKD and ESKD patients may contribute to the severity of performance fatigability, and (4) highlight preliminary evidence on the effects of exercise as a potential clinical treatment for targeting fatigability in this population. Summary: Fatigue is broadly defined as a multidimensional construct encompassing a subjective lack of physical and/or mental energy that is perceived by the individual to interfere with usual or desired activities. In contrast, fatigability is conceptualized within the context of physical activity and is quantified as the interactions between reductions in objective measures of performance (i.e., performance fatigability) and perceptual adjustments regulating activity performance (i.e., perceived fatigability). We propose herein a conceptual model to extend current understandings of fatigability by considering the interactions among fatigue, perceived fatigability, and performance fatigability. Neuromuscular impairments reported in patients with CKD and ESKD, including reductions in force capacity, skeletal muscle atrophy, mitochondrial dysfunction, abnormal skeletal muscle excitability, and neurological complications, may each contribute to the greater performance fatigability observed in these patients. Key Messages: Considering the interactions among fatigue, perceived fatigability, and performance fatigability provides a novel conceptual framework to advance the understanding of fatigability in CKD and ESKD patients. Measures of fatigability may provide valuable clinical insights into the overall health status of CKD and ESKD patients. Existing data suggest that CKD and ESKD patients are at greater risk of experiencing increased fatigability, partly due to neuromuscular impairments associated with reduced kidney function. Further investigations are warranted to determine the potential clinical role fatigability measures can play in monitoring the health of CKD and ESKD patients, and in identifying potential treatments targeting fatigability in this patient population.
The Amount and Concentration of Drain Amylase Together Predict Postoperative Pancreatic Fistula after Gastric Cancer Surgery More Accurately than the Concentration Alone
Authors: Miura Susumu , Wakahara Tomoyuki , Yamauchi Saya , Yasuhara Yuki , Mukubo Hideyo , Kanemitsu Kiyonori , Iwasaki Takeshi , Sasako Mitsuru , Kakeji Yoshihiro
Published: March 2022

Introduction: The drain amylase concentration (dAmy-C) is a useful marker for predicting pancreatic fistula after gastric cancer surgery. However, dAmy-C might be reduced in cases of high drainage volume. Therefore, we hypothesized that we could accurately assess the amount of amylase leaked from the pancreas by multiplying dAmy-C by the daily drainage volume. In this study, we investigated the clinical utility of the amount of drain amylase (A-dAmy: concentration × volume) for predicting pancreatic fistula. We investigated the clinical utility of the combination of dAmy-C and A-dAmy for predicting pancreatic fistula. Methods: We investigated patients who underwent gastrectomy for gastric cancer at Yodogawa Christian Hospital between 2012 and 2020. The optimal cutoff levels of dAmy-C and A-dAmy on postoperative day 1 for predicting Clavien-Dindo (CD) grade II or higher pancreatic fistula was calculated using receiver operating characteristic (ROC) curves. We calculate the positive predictive value and negative predictive value for predicting pancreatic fistula using these cutoff levels. Results: A total of 448 patients were eligible for analysis. Twenty-two patients experienced CD grade II or higher pancreatic fistula. ROC curves identified 1,615 IU/L as the optimal cutoff level of dAmy-C, predicting pancreatic fistula. When the simple cutoff level of dAmy-C was 1,600 IU/L, the positive predictive value for was 22.8%, and the negative predictive value was 99.7%. ROC curves identified 177.52 IU as the optimal cutoff level of A-dAmy predicting pancreatic fistula. When the simple cutoff level of A-dAmy was 177 IU, the positive predictive value was 21.2%, and the negative predictive value was 99.7%. Using these two cutoff levels together, the positive predictive value was 34.4%, and the negative predictive value was 99.7%. Conclusion: A-dAmy could predict and exclude pancreatic fistula after gastrectomy as with dAmy-C. The combination of dAmy-C and A-dAmy predict pancreatic fistula more accurately than dAmy-C alone.
Effects of Pulsatility on Arterial Endothelial and Smooth Muscle Cells
Authors: Meki Moustafa , El-Baz Ayman , Sethu Palaniappan , Giridharan Guruprasad
Published: March 2022

Continuous flow ventricular assist device (CFVAD) support in advanced heart failure patients causes diminished pulsatility, which has been associated with adverse events including gastrointestinal bleeding, end organ failure, and arteriovenous malformation. Recently, pulsatility augmentation by pump speed modulation has been proposed as a means to minimize adverse events. Pulsatility primarily affects endothelial and smooth muscle cells in the vasculature. To study the effects of pulsatility and pulse modulation using CFVADs, we have developed a microfluidic co-culture model with human aortic endothelial (ECs) and smooth muscle cells (SMCs) that can replicate physiologic pressures, flows, shear stresses, and cyclical stretch. The effects of pulsatility and pulse frequency on ECs and SMCs were evaluated during (1) normal pulsatile flow (120/80 mmHg, 60 bpm), (2) diminished pulsatility (98/92 mmHg, 60 bpm), and (3) low cyclical frequency (115/80 mmHg, 30 bpm). Shear stresses were estimated using computational fluid dynamics (CFD) simulations. While average shear stresses (4.2 dynes/cm2) and flows (10.1 mL/min) were similar, the peak shear stresses for normal pulsatile flow (16.9 dynes/cm2) and low cyclic frequency (19.5 dynes/cm2) were higher compared to diminished pulsatility (6.45 dynes/cm2). ECs and SMCs demonstrated significantly lower cell size with diminished pulsatility compared to normal pulsatile flow. Low cyclical frequency resulted in normalization of EC cell size but not SMCs. SMCs size was higher with low frequency condition compared to diminished pulsatility but did not normalize to normal pulsatility condition. These results may suggest that pressure amplitude augmentation may have a greater effect in normalizing ECs, while both pressure amplitude and frequency may be required to normalize SMCs morphology. The co-culture model may be an ideal platform to study flow modulation strategies.
Review of song patterns and sound production in armoured ground crickets (Orthoptera: Tettigoniidae: Hetrodini) with karyological data and taxonomic notes
Authors: HELLER KLAUS-GERHARD , CHOBANOV DRAGAN , WARCHAŁOWSKA-ŚLIWA ELŻBIETA , HEMP CLAUDIA
Published: March 2022

In the mate finding system of bush-crickets, acoustical signals play a central role. Here we review and describe the bioacoustics of Hetrodini, a morphologically uniform group of Tettigonioidea with a distribution centered in Africa. The male calling songs are produced by tegmino-tegminal stridulation. In all species, these fore wings are completely covered by the pronotum (invisible in intact specimens) and lack the glossy mirror cells which are well-known from many other singing Ensifera. Concerning spectral composition, the broad frequency peak and the parts with the most energy lie in the high audio or low ultrasonic range. In amplitude modulation, the songs are relatively simply structured and contain only one type of syllables each. These syllables consist of heavily dampened impulses (non-resonant song) and are arranged in long series of echemes (chirps) or trills. As far as it is known, syntopic species differ in syllable and/or echeme repetition rates. In contrast to the uniform morphology, the karyotypes are surprisingly diverse with chromosome numbers ranging from 2n = 29 to 17 and one of two sex determination systems: X0 and neo-XY. In our opinion, taxonomically the group is at the moment at best considered as a tribe incertae sedis (without subfamily classification) within Tettigoniidae (not Tettigoniinae sensu OSF).
Diagnosing Hawaii’s Recent Drought
Authors: Eischeid J. K. , Hoerling M. P. , Quan X.-W. , Diaz H. F.
Published: March 2022

Hawaii’s recent drought is among the most severe on record. Wet-season (November–April) rainfall deficits during 2010–19 rank second lowest among consecutive 10-yr periods since 1900. Various lines of empirical and model evidence indicate a principal natural atmospheric cause for the low rainfall, mostly unrelated to either internal oceanic variability or external forcing. Empirical analysis reveals that traditional factors have favored wetness rather than drought in recent decades, including a cold phase of the Pacific decadal oscillation in sea surface temperatures (SSTs) and a weakened Aleutian low in atmospheric circulation. But correlations of Hawaiian rainfall with patterns of Pacific sea level pressure and SSTs that explained a majority of its variability during the twentieth century collapsed in the twenty-first century. Atmospheric model simulations indicate a forced decadal signal (2010–19 vs 1981–2000) of Aleutian low weakening, consistent with recent observed North Pacific circulation. However, model ensemble means do not generate reduced Hawaiian rainfall, indicating that neither oceanic boundary forcing nor a weakened Aleutian low caused recent low Hawaiian rainfall. Additional atmospheric model experiments explored the role of anthropogenic forcing. These reveal a strong sensitivity of Hawaiian rainfall to details of long-term SST change patterns. Under an assumption that anthropogenic forcing drives zonally uniform SST warming, Hawaiian rainfall declines, with a range of 3%–9% among three models. Under an assumption that anthropogenic forcing also increases the equatorial Pacific zonal SST gradient, Hawaiian rainfall increases 2%–6%. Large spread among ensemble members indicates that no forced signals are detectable.
A dimension-reduction based Chebyshev polynomial method for uncertainty analysis in composite corrugated sandwich structures
Authors: Li Feng , Li Hongfeng , Zhao Heng , Zhou Yichen
Published: March 2022

A prediction method for the ultimate load of composite corrugated sandwich structures (CCSS) was established based on the dimension-reduction method and Chebyshev polynomial. First, an ultimate load response function of the CCSS was reduced in dimension on basis of the univariate method. The original response function was converted to the sum of univariate functions of all random variables. Chebyshev polynomial was used to fit all univariate functions, and the univariate Chebyshev approximate model (UCAM) of the response function was obtained. Second, the fitting accuracy of the UCAM was analytically compared with the Kriging model, radial basis function, and response surface methodology. Finally, the effect of the order on the fitting accuracy of UCAM was studied. The UCAM has higher fitting accuracy and calculation efficiency compared with the other three approximate models. When the order of UCAM is lower than ninth-order, the larger the order, the higher the fitting accuracy. And the order and the fitting accuracy are no longer positively correlated when the order exceeds ninth-order. The order is recommended to choose an odd-order when using UCAM to solve the uncertainty problem.
Natural Family Planning, An Option in Reproductive Healthcare: A Qualitative Study on Clinicians’ Perceptions
Authors: Joan Ibeziako Ozoemena
Published: March 2022

Natural family planning (NFP) empowers women to control their reproductive health and approach fertility as a normal biological process. Although substantive literature supports their comparative effectiveness with contraceptive methods, there is a paucity of this knowledge amongst clinicians and users. This study aimed to understand clinicians’ perceptions regarding offering NFP to patients as part of reproductive health care. It explored clinicians’ knowledge of NFP, described their perceptions of their effectiveness, and identified enabling and deterring factors to their use. Basic Interpretive qualitative research design was appropriate in obtaining an in-depth description of this phenomenon. It was conducted in 2018 in two hospitals and clinics in Ekurhuleni health district, located East of Gauteng Province, South Africa. Fifteen doctors and nurses from diverse cultural and educational backgrounds were purposefully selected and interviewed. Transcribed data were analyzed, coded, and recurrent themes identified. Training that empowers clinicians on NFP methods and their effectiveness will improve their willingness to advocate for it and promote patient autonomy by providing comprehensive counseling on family planning methods. Further, a pro-NFP policy would drive training in undergraduate and postgraduate programs and increase public awareness, including early education of male and female children.