bluuebunny/crossref_metadata_2025 huggingface dataset:
How nitrogen and phosphorus supply to nutrient‐limited autotroph communities affects herbivore growth: testing stoichiometric and co‐limitation theory across trophic levels
Authors: Redoglio Andrea , Radtke Kassandra , Sperfeld Erik
Published: June 2022

Primary producer communities are often growth‐limited by essential nutrients such as nitrogen (N) and phosphorus (P). The magnitude of limitation and whether N, P or both elements are limiting autotroph growth depends on the supply and ratios of these essential nutrients. Previous studies identified single, serial or co‐limitation as predominant limitation outcomes in autotroph communities by factorial nutrient additions. Little is known about potential consequences of such scenarios for herbivores and whether their growth is primarily affected by changes in autotroph quantity or nutritional quality. We grew a community of phytoplankton species differing in various food quality aspects in experimental microcosms at varying N and P concentrations resulting in three different N:P ratios. At carrying capacity, N, P, both nutrients or none were added to reveal which nutrients were limiting. The nutrient‐supplied communities were fed to the generalist herbivorous rotifer Brachionus calyciflorus to investigate how changing phytoplankton biomass and community composition affect herbivore abundance. We found phytoplankton being growth‐limited either by N alone (single limitation) or serially, i.e. primarily by N and secondarily by P, altering available food quantity for rotifers. Rotifer growth showed a different response pattern compared to phytoplankton, suggesting that apart from food quantity food quality aspects played a substantial role in the transfer from primary to secondary production. The combined addition of N and P to phytoplankton had generally a positive effect on herbivore growth, whereas adding non‐limiting nutrients had a rather detrimental effect probably due to stoichiometrically imbalanced food in terms of nutrient excess. Our experiment shows that adding various nutrients to primary producer communities will not always lead to increased autotroph and herbivore growth, and that differences between autotroph and herbivore responses under co‐limiting conditions can be partly well explained by concepts of ecological stoichiometry theory.
Long term analysis of social structure: evidence of age‐based consistent associations in male Alpine ibex
Authors: Brambilla Alice , von Hardenberg Achaz , Canedoli Claudia , Brivio Francesca , Sueur Cédric , Stanley Christina R.
Published: June 2022

Despite its recognized importance for understanding the evolution of animal sociality as well as for conservation, long term analysis of social networks of animal populations is still relatively uncommon. We investigated social network dynamics in males of a gregarious mountain ungulate (Alpine ibex,Capra ibex) over ten years focusing on groups, sub‐groups and individuals, exploring the dynamics of sociality over different scales. Despite the social structure changing between seasons, the Alpine ibex population was highly cohesive: fission–fusion dynamics lead almost every male in the population to associate with each other male at least once. Nevertheless, we found that male Alpine ibex showed preferential associations that were maintained across seasons and years. Age seemed to be the most important factor driving preferential associations while other characteristics, such as social status, appeared less crucial. We also found that centrality measures were influenced by age and were also related to individual physical condition. The multi‐scale and long‐term frame of our study helped us show that ecological constrains, such as resource availability, may play a role in shaping associations in a gregarious species, but they cannot solely explain sociality and preferential association that are likely also to be driven by life‐history linked physiological and social needs. Our results highlight the importance of long‐term studies based on individually recognizable subjects to help us build on our understanding of the evolution of animal sociality.
Remittances and domestic violence
Authors: Silverio‐Murillo Adan , Balmori de la Miyar Jose Roberto
Published: June 2022

This paper estimates the effects of money transfers sent by relatives or acquaintances, better known as remittances, on intimate partner violence (IPV) against married women living in Mexico. Using three waves of a national state‐based representative survey specialized in violence against women, and state‐fixed effects regression models, the results show that receiving remittances increases the likelihood of IPV by 6%. We document several mechanisms for this detrimental effect of receiving remittances on IPV. Among these mechanisms, we find that receiving remittances is positively correlated to men's alcohol consumption, a factor associated with IPV, and that receiving remittances is negatively correlated to the probability of men being employed, suggesting that men exert violence against women to compensate for the lack of income with remittances.
Exotic wave patterns in Riemann problem of the high‐order Jaulent–Miodek equation: Whitham modulation theory
Authors: Liu Yaqing , Wang Deng‐Shan
Published: June 2022

The Riemann problem of the high‐order Jaulent–Miodek (JM) equation with initial data of step discontinuity is explored by Whitham modulation theory, which is a modified version of the well‐known finite‐gap integration method. Based on the reparameterization of the solution with the use of algebraic resolvent of the polynomial defining the solution, the periodic wave solutions of the high‐order JM equation are described by the elliptic function along with the Whitham modulation equations. Complete classification of possible wave structures of the high‐order JM equation is given for all possible jump conditions at the discontinuity initial value. The analytic results proposed in this work are confirmed by direct numerical simulations.
Creation of a Life Prediction Model for Combined High-Cycle Fatigue and Creep
Authors: Bouchenot Thomas , Patel Kirtan , Gordon Ali P. , Shinde Sachin
Published: June 2022

While industrial gas turbine blades are commonly designed to resist creep and high-cycle fatigue (HCF) failure, the combination of these two loading conditions is seldom considered. The effect of creep damage elicited prior or concurrent to HCF loading is not well established and can significantly reduce the HCF lifetime of these critical components. A comprehensive life prediction model capable of capturing these superimposed effects is needed to ensure current reliability standards are maintained when designing aggressively loaded, next-generation industrial gas turbine blades. The consequence of combined HCF and creep loading to the lifetime a Ni-base superalloy is characterized and modeled in this study. Composition and calibration of the model are carried out using data from HCF tests conducted on virgin and pre-crept specimens at 750 °C and 850 °C. The experimental data encompass a wide range of stress ratios and pre-creep strains to mimic to the expansive set of potential turbine blade loading conditions. The proposed microstructurally informed model is based on existing principles and relies on test data and information gathered from a comprehensive failure analysis of the tested samples.
The ADP-Heptose Biosynthesis Enzyme GmhB is a Conserved Gram-Negative Bacteremia Fitness Factor
Authors: Holmes Caitlyn L. , Smith Sara N. , Gurczynski Stephen J. , Severin Geoffrey B. , Unverdorben Lavinia V. , Vornhagen Jay , Mobley Harry L. T. , Bachman Michael A.
Published: June 2022

Klebsiella pneumoniae
is a leading cause of Gram-negative bacteremia, which is a major source of morbidity and mortality worldwide. Gram-negative bacteremia requires three major steps: primary site infection, dissemination to the blood, and bloodstream survival.
Phylodynamics of HIV in the Mexico City Metropolitan Region
Authors: Avila-Rios Santiago , García-Morales Claudia , Reyes-Terán Gustavo , González-Rodríguez Andrea , Matías-Florentino Margarita , Mehta Sanjay R. , Chaillon Antoine
Published: June 2022

Phylogeographic investigation of the Mexico City HIV epidemic illustrates the complexity of HIV transmission in the region. An active transmission area involving a few municipalities in the north of the city, with transmission links throughout the region, is identified and could be a location where targeted interventions could have a more pronounced effect on the entire regional epidemic, compared with those dispersed in other manners.
The Native Orthobunyavirus Ribonucleoprotein Possesses a Helical Architecture
Authors: Hopkins Francis R. , Álvarez-Rodríguez Beatriz , Heath George R. , Panayi Kyriakoulla , Hover Samantha , Edwards Thomas A. , Barr John N. , Fontana Juan
Published: June 2022

Bunyaviruses are emerging RNA viruses that cause significant disease and economic burden and for which vaccines or therapies approved for humans are not available. The bunyavirus genome is wrapped up by the nucleoprotein (NP) and interacts with the viral polymerase, forming a ribonucleoprotein (RNP).
Leveraging Existing 16SrRNA Microbial Data to Define a Composite Biomarker for Autism Spectrum Disorder
Authors: Xu YuShuang , Wang YiHua , Xu JinShuang , Song Yu , Liu BingQiang , Xiong ZhiFan
Published: June 2022

This study provides an updated analysis to characterize the gut microbiota in ASD using 16SrRNA gene high-throughput sequencing data from 10 publicly available studies. Our analysis suggests an association between the fecal microbiota and ASD.
Decreased Passive Immunity to Respiratory Viruses through Human Milk during the COVID-19 Pandemic
Authors: Grobben Marloes , Juncker Hannah G. , van der Straten Karlijn , Lavell A. H. Ayesha , Schinkel Michiel , Buis David T. P. , Wilbrink Maarten F. , Tejjani Khadija , Claireaux Mathieu A. F. , Aartse Aafke , de Groot Christianne J. M. , Pajkrt Dasja , Bomers Marije K. , Sikkens Jonne J. , van Gils Marit J. , van Goudoever Johannes B. , van Keulen Britt J.
Published: June 2022

Passive immunity derived from antibodies in human milk is important for protecting young infants against invading viruses. During the COVID-19 pandemic, circulation of common respiratory viruses was virtually absent due to preventative measures.
Absolute Quantification of Viable but Nonculturable Vibrio cholerae Using Droplet Digital PCR with Oil-Enveloped Bacterial Cells
Authors: Zhao Shuo , Lu Xin , Zhang JingYun , Kan Biao
Published: June 2022

The viable but nonculturable (VBNC) state of bacteria represents an important life state for their survival in adverse environments. The VBNC cells of the pathogenic bacteria in the environment and food will be a potential threat to public health because these pathogens cannot be found by the detection of culture.
Cyclic t-z model for the long-term thermomechanical analysis of energy piles
Authors: Pei Huafu , Song Huaibo , Zhou Chao , Yang Qing , Xiao Da
Published: June 2022

Many elastoplastic and nonlinear models have simulated the long-term behavior of energy piles under cyclic thermomechanical loads. Although they considered the strain–stress hysteretic relationship at the pile–soil interface, the interface strength was assumed independent of the number of thermomechanical cycles. This simplification may cause errors in predicting the long-term responses of energy piles. Therefore, we proposed a cyclic t-z model for the long-term thermomechanical analysis of an energy pile. Here, the interface strength of the model changes with the cycle number of thermomechanical loads. In addition, the accumulation of irreversible deformation at the pile–soil interface can be modeled. Moreover, the cyclic performance of interface shear tests and the long-term behavior of an in situ energy pile were simulated. Comparisons between the measured and simulated results indicated several vital aspects of the energy pile–soil interaction, including strength degradation, strain ratcheting phenomenon of the interface, and long-term pile responses under cyclic thermomechanical loading. Furthermore, numerical simulations were used to evaluate the effects of model parameters on the long-term behavior of energy piles under thermomechanical loads.
Ab Initio Study of Electronic Properties on WS2 Monolayer and Transition Metal Doped WS2
Authors: Poornimadevi C. , Gayathri Devi S. , Preferencial Kala C. , Thiruvadigal D. John
Published: June 2022

Two-dimensional materials have attracted the attention of many researchers. Especially transition metal dichalcogenides (TMDs) like MoS2, WS2, etc., grants a wide scale of the band gap. TMDCs, MoS2 and WS2 monolayers have similar electronic and structural properties. WS2 has a great surface to volume ratio, a wide band gap range, high thermal and oxidative stability. It also has the peak carrier mobility and least effective mass than other TMDCs. So, it has been used in many applications like solar cells, LED, rechargeable batteries and sensors. In this work, we have analysed the stability and the electronic properties of monolayer and doped WS2 with Cobalt (Co), Iron (Fe) and Nickel (Ni) using density functional theory (DFT). The stability of the system has been studied by the formation energy. The electronic properties are analysed by band structure, the density of states, charge transfer, chemical potential, and total energy of the systems. These results show that the formation energy of the doped system is increasing with a negative magnitude which proves that the doped structures are more stable. We have observed reasonable changes in the band structure and density of states for transition metal doped WS2 while comparing with WS2 monolayer. We concluded that the doped WS2 shows better results than monolayer WS2 in the stability and improved electronic properties. These results may provide a prospective insight for making gas sensing devices.
Double-doping Effect on Structural and Magnetic Properties of Perovskite Lanthanum Manganite
Authors: Hanna Farid F. , Ibrahim Peter N. G.
Published: June 2022

Polycrystalline samples La(2+4x)/3Sr(1–4x)/3Mn1−xCuxO3 (x = 0, 0.1, 0.15 and 0.25) with double doping in the A site and B site were successfully prepared by the conventional solid-state reaction method with heat treatment up to 1300 °C. All the obtained samples consist of single perovskite phase with a rhombohedral symmetry and

R

3
¯

C

space group. The (a) lattice parameter and the volume of the unit cell were found to increase with the increase of Cu doping level (x). The morphology of the prepared samples was studied by scanning electron microscope imaging, and the stoichiometry of the compositions was confirmed. The hysteresis loops at room temperature for x = 0, 0.1 and 0.15 samples are characteristic for soft ferromagnetic materials, with a decrease of the ferromagnetic interaction and a decrease of the magnetic moment with the increase of Cu doping level. No ferromagnetic behavior was detected at room temperature for the x = 0.25 sample. The question of the valency of Cu ions was discussed during the present study. Our results are best interpreted by assuming the coexistence of Cu2+ and Cu3+ ions.
Menthol in electronic cigarettes causes biophysical inhibition of pulmonary surfactant
Authors: Xu Lu , Yang Yi , Simien Jennifer Michelle , Kang Christopher , Li Guangle , Xu Xiaojie , Haglund Ellinor , Sun Rui , Zuo Yi Y.
Published: June 2022

With an increasing prevalence of electronic cigarette (e-cigarette) use, especially among youth, there is an urgent need to better understand the biological risks and pathophysiology of health conditions related to e-cigarettes. A majority of e-cigarette aerosols are in the submicron size and would deposit in the alveolar region of the lung, where they must first interact with the endogenous pulmonary surfactant. To date, little is known whether e-cigarette aerosols have an adverse impact on the pulmonary surfactant. We have systematically studied the effect of individual e-cigarette ingredients on an animal-derived clinical surfactant preparation, bovine lipid extract surfactant, using a combination of biophysical and analytical techniques, including in vitro biophysical simulations using constrained drop surfactometry, molecular imaging with atomic force microscopy, chemical assays using carbon nuclear magnetic resonance and circular dichroism, and in silico molecular dynamics simulations. All data collectively suggest that flavorings used in e-cigarettes, especially menthol, play a predominant role in inhibiting the biophysical function of the surfactant. The mechanism of biophysical inhibition appears to involve menthol interactions with both phospholipids and hydrophobic proteins of the natural surfactant. These results provide novel insights into the understanding of the health impact of e-cigarettes and may contribute to better regulation of e-cigarette products.
Porcellio scaber Algorithm with t-Distributed Elite Mutation for Global Optimization
Authors: Zhang Chao , Yang Yi
Published: June 2022

As the convergence accuracy of the Porcellio scaber algorithm (PSA) is low, this study proposes an improved algorithm based on the t-distribution elite mutation mechanism. First, the improved algorithm applies a t-distribution mutation to each dimension of the optimal solution of each generation. Using the dominant information of the optimal solution and t-distribution characteristics, the result of the mutation is then employed as the updated location of the selected porcellio; thus, the algorithm enhances the ability to jump out of local extreme values and improves the convergence speed. Second, the updated iterative rule of PSA may lead to the loss of information of the elite porcellio in the last generation. To solve this problem, the judgment mechanisms of the current and previous optimal solutions are included in the algorithm process. Finally, dynamic self-adaptive improvement is applied to the weight allocation parameters of PSA. Simulation results on 24 benchmark functions show that the improved algorithm has significant advantages in convergence accuracy, convergence speed, and stability when compared with basic PSA, PSO, GSA, and FPA. This indicates that the improved algorithm has certain advantages in terms of optimization. An optimal solution with good practicability is obtained by solving three practical engineering problems: three-bar truss, welded beam, and tension/compression-spring design.
Stacked Input-Output High Step-Up Buck-Boost DC-DC Converter with Coupled Inductor and Voltage Multiplier
Authors: Miguel Klein Faistel Tiago , Toebe Ademir , Andrade António Manuel Santos Spencer , Guisso Ronaldo Antonio , Mendes da Silva Mauricio
Published: June 2022

This paper presents three high voltage gain DC-DC converters based on stacked input and output connection of nonisolated buck-boost converters with coupled inductor and voltage multiplier cells. Besides that, an empirical approach for the coupled inductor winding is proposed to show how to reduce the leakage inductance. In this way, the proposed converter achieves high voltage gain, low voltage, and current stress across the components without using an auxiliary clamp circuit, and they present a low component count. Besides that, this paper presents the evaluation of MPPT, modeling, and control of the converters. To validate the theoretical evaluations, three prototypes were built and evaluated experimentally, considering input power of 200 W, input voltage of 37.4 V, output voltage of 400 V, and switching frequency of 50 kHz. Finally, it should be noted that the maximum efficiency achieved is 97.53% at nominal input power.
Benefits and Barriers of Holistic Nursing Training by High-Fidelity Simulation in Obstetrics
Authors: Zhang Wenxi , Lozynska Inna , Li Wei , Cai Nana , Yang Hongmin
Published: June 2022

Background. With the technology of high-fidelity simulates developed, the clinical education route has changed. The nursing school pays attention on the use of high-fidelity simulations in nursing education. However, in China, only a few schools can afford the expensive teaching tools, including SimMom 3G and virtual reality (VR) devices, which also focus on “holistic nursing simulation.” Objective. To explore the evaluation and development of a holistic nursing simulation session for nursing students based on an integrated nursing approach in obstetrics. Methods. This study was based in a rich Chinese nursing school under the medical university that value nursing education. This study is founded on 147 third-year nursing students in obstetrics classes. After the simulation teaching, the teaching effect of the questionnaire was investigated, and the total number of questionnaires was 124 students. Results. Students agreed that the holistic nursing simulation cultivated humanistic care literacy, clinical practice ability, and clinical thinking ability; enhanced teamwork ability; and reinforced professional knowledge. Conclusion. This simulation teaching method helps to cultivate students’ enthusiasm and initiative and fosters their self-learning ability.
Evaluation of Oxidative Status in Elderly Patients with Multiple Cerebral Infarctions and Multiple Chronic Total Coronary Occlusions
Authors: Li Xia , Guo Dianxuan , Hu Youdong , Chen Ying
Published: June 2022

Background. Oxidative stress plays a key role in atherosclerosis. Acting via high level of reactive oxygen species, an increase of oxidative stress is involved in the pathogenesis and progression of atherosclerostic stenosis or occlusion of arteries. Oxidative stress leads to an accumulation of oxidized low-density lipoprotein, which plays important roles in steno-occlusion of cerebral and coronary arteries. However, the exact reasons for multiple cerebral and coronary artery steno-occlusion in elderly patients remain unclear. The aim was to evaluate the effects of imbalance of oxidative/antioxidative status on concomitant multiple brain infarcts and multiple chronic total coronary occlusions in elderly patients. Methods. We measured the circulating levels of malondialdehyde (MDA), reactive oxygen species (ROS), thiobarbituric acid reactive substance (TBARS), advanced oxidation protein products (AOPP), superoxide dismutase 1 (SOD 1), superoxide dismutase 2 (SOD 2), superoxide dismutase 3 (SOD 3), and paraoxonase 1 (PON 1) in patients with concomitant multiple cerebral infarcts and multiple chronic total coronary occlusions. Results. Circulating levels of oxidative stress markers (MDA, ROS, TBARS, and AOPP) were increased (

P
<
0.001

) and antioxidative stress markers (SOD 1, SOD 2, SOD 3, and PON 1) were decreased (

P
<
0.001

) in elderly patients with concomitant multiple brain infarcts and multiple chronic total coronary occlusions. Conclusions. The findings suggested that the imbalance of oxidative/antioxidative status may be associated with multiple cerebral infarcts and multiple chronic total coronary occlusions and may contribute to the development of concomitant multiple brain infarcts and multiple chronic total coronary occlusions in elderly patients.
Coverage Properties of a Neural Network Estimator of Finite Population Total in High‐Dimensional Space
Authors: Were Festus A. , Orwa George O. , Otieno Romanus O. , Makumi Nicholas , Aldallal Ramy
Published: June 2022

The problem in nonparametric estimation of finite population total particularly when dealing with high‐dimensional datasets is addressed in this paper. The coverage properties of a robust finite population total estimator based on a feedforward backpropagation neural network developed with the help of a superpopulation model are computed, and a comparison with existing model‐based estimators that can handle high‐dimensional datasets is conducted to evaluate the estimator’s performance using simulated datasets. The results presented in this paper show good performance in terms of bias, MSE, and mean absolute error for the feedforward backpropagation neural network estimator as compared to other identified existing estimators of finite population total in high‐dimensional datasets. In this regard, the paper recommends the use of the proposed estimator in estimating population parameters such as population total in the presence of high‐dimensional datasets.
A Novel Angiogenesis-Related Gene Signature to Predict Biochemical Recurrence of Patients with Prostate Cancer following Radical Therapy
Authors: Fan Bohan , Wang Yicun , Zheng Xin , Zhang Xin , Zhang Zijian , Hu Xiaopeng
Published: June 2022

Background. Prostate cancer (PCa) is one of the most common malignancies in males; we aim to establish a novel angiogenesis-related gene signature for biochemical recurrence (BCR) prediction in PCa patients following radical therapy. Methods. Gene expression profiles and corresponding clinicopathological data were acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We quantified the levels of various cancer hallmarks and identified angiogenesis as the primary risk factor for BCR. Then machine learning methods combined with Cox regression analysis were used to screen prognostic genes and construct an angiogenesis-related gene signature, which was further verified in external cohorts. Furthermore, estimation of immune cell abundance and prediction of drug responses were also conducted to detect potential mechanisms. Results. Angiogenesis was regarded as the leading risk factor for BCR in PCa patients (HR = 1.58, 95% CI: 1.38–1.81), and a novel prognostic signature based on three genes (NRP1, JAG2, and VCAN) was developed in the training cohort and successfully validated in another three independent cohorts. In all datasets, this signature was identified as a prognostic factor with promising and robust predictive values. Moreover, it also predicted higher infiltration of regulatory T cells and M2-polarized macrophages and increased drug sensitivity of angiogenesis inhibitors in high-risk patients. Conclusions. The angiogenesis-related three-gene signature may serve as an independent prognostic factor for BCR, which would contribute to risk stratification and personalized management of PCa patients after radical therapy in clinical practice.
Enhanced-Dose Statins for ST-Segment Elevation Myocardial Infarction Patients after Emergency Percutaneous Coronary Intervention
Authors: Chen Wenzhong , Fan Zhiwen , Huang Canhui , Han Zhiyuan , Liu Junying
Published: June 2022

Background. Acute ST-segment elevation myocardial infarction (STEMI) is a serious multiple acute cardiovascular disease. This study investigated the effect of statins on the efficacy and prognosis of STEMI patients after emergency PCI. Methods. From October 2019 to January 2021, 98 patients with STEMI in our hospital were selected and divided into study group and control group. The study group took atorvastatin 40 mg 2 hours before surgery, 40 mg/day after surgery, and 20 mg/day 1 week later. The control group received 20 mg of atorvastatin every night after admission. The cardiac output, left ventricular ejection fraction, blood flow classification, vagus nerve function, heart rate deceleration force and chemoreflex sensitivity were compared between the two groups, and recorded the incidence of adverse reactions before and after treatment and 3 months after treatment. The number of major adverse cardiac events (MACEs) was also recorded. Results. Before treatment, there were no differences in CO, CI, and LVEF between the study and control groups. After treatment, CO, CI, and LVEF in the study group were significantly higher than those in the control group. Before treatment, there was no significant difference in TIMI blood flow classification among the groups, and after treatment, the study group was better than the control group. DC and ChRS were significantly higher in the study group than in the control group. There was no difference in the incidence of adverse reactions between the study group and the control group. However, the incidence of MACE in the study group was lower than that in the control group. Conclusion. Enhanced-dose atorvastatin for STEMI patients improved PCI treatment effect, cardiac function, and vagus nerve function and reduced the incidence of adverse cardiac events. Thus, statins are safe and worth considering.
Phytochemical Screening and In Vitro Antifungal Activity of Selected Medicinal Plants against Candida albicans and Aspergillus niger in West Shewa Zone, Ethiopia
Authors: Gizaw Askale , Marami Lencho Megersa , Teshome Ibsa , Sarba Edilu Jorga , Admasu Petros , Babele Dagmawit Atalel , Dilba Getachew Mulatu , Bune Wakuma Mitiku , Bayu Morka Dandecha , Tadesse Miressa , Abdisa Kebede
Published: June 2022

Antimicrobial resistance to commercially available medications has become a global issue, yet there is still the possibility of developing new drugs from medicinal plants. As a result, the aims of the present study were to screen secondary metabolites and to evaluate in vitro antifungal activities of Brucea antidysenterica, Aloe vera, and Justicia schimperiana. After the plants were identified, their leaves were collected, washed, dried under the shade, pulverized, and extracted with methanol (99.8%) using the maceration technique. The presence of secondary metabolites in plant extracts was screened using various laboratory protocols. The antifungal activities of the plant extract against reference fungal strains of Candida albicans and Aspergillus niger at concentrations of 200, 100, and 50 mg/mL were assessed using the agar-well diffusion method. Ketoconazole (15 μg) was used as a positive control, while 5% dimethyl sulfoxide and/or 5% Tween 80 were used as negative controls. All tests were conducted in triplicate. Alkaloids, flavonoids, and phenols were secondary metabolites found in all plant extracts. The extract of leaves of B. antidysenterica and J. schimperiana formed a mean zone of inhibition of 15.5 ± 0.5 mm and 15.3 ± 0.58 mm, respectively, against Candida albicans at a concentration of 200 mg/mL, whereas extracts of A. vera leaves formed a 12.3 ± 0.58 mm inhibition zone only against Aspergillus niger at 200 mg/mL. In conclusion, the current study found that B. antidysenterica, A. vera, and J. schimperiana had antifungal activity. In addition, all these plants had a variety of secondary metabolites that possibly have antifungal activities. Studies on in vivo investigations and isolation of specific antifungal compounds from these medicinal plants are suggested.
Application of Expert Adjustable Fuzzy Control Algorithm in Temperature Control System of Injection Machines
Authors: Hu Yanan , Wu Kun
Published: June 2022

The stability and accuracy of temperature control of the injection molding machine is one of the keys to determine the quality and appearance of plastic parts. Due to the temperature control system of water-cooled injection molding machine has the characteristics of coupling, nonlinearity, and hysteresis, the traditional proportion-integral-derivative (PID) method to control the barrel temperature of injection molding machine will yield temperature overshoot and oscillation, affecting the product and appearance quality. In order to improve the effect of barrel temperature control, in this paper, an expert adjustable fuzzy control strategy (EAFCA) is designed to optimize the barrel temperature control system through the combination of expert control, fuzzy control, and PID control. The expert control rules are designed according to the barrel temperature deviation e and its change rate ec. The expert rules are used to adjust the mapping range of the fuzzy universe in real time for the input and output variables of the fuzzy controller and finally to realize the accurate adjustment of the PID controller parameters. In terms of control systems, the distributed control system (DCS) monitoring system of injection molding machine is designed with Siemens CPU315-2PN/DP and industrial computer as the hardware core and Step7 and windows control center (WinCC) as the software platform to complete the tool plastic production monitoring system. The DCS improves the operability, data management convenience, and plastic production efficiency of the injection molding machine monitoring system. The Simulink simulation and field test show that the EAFCA method can increase the adjustment speed by approximately 34 s and reduce the overshoot by nearly 3.1%, which significantly improves the stability and accuracy of the barrel temperature and improves the quality of plastic parts.
Classification for Memory Activities: Experiments and EEG Analysis Based on Networks Constructed via Phase-Locking Value
Authors: Xi Jing , Huang Xiao-Lin , Dang Xing-Yan , Ge Bin-Bin , Chen Ying , Ge Yun
Published: June 2022

Electroencephalogram (EEG) plays a crucial role in the study of working memory, which involves the complex coordination of brain regions. In this research, we designed and conducted series of experiments of memory with various memory loads or target forms and collected behavioral data as well as 32-lead EEG simultaneously. Combined with behavioral data analysis, we segmented EEG into slices; then, we calculated phase-locking value (PLV) of Gamma rhythms between every two leads, conducted binarization, constructed brain function network, and extracted three network characteristics of node degree, local clustering coefficient, and betweenness centrality. Finally, we inputted these network characteristics of all leads into support vector machines (SVM) for classification and obtained decent performances; i.e., all classification accuracies are greater than 0.78 on an independent test set. Particularly, PLV application was restricted to the narrow-band signals, and rare successful application to EEG Gamma rhythm, defined as wide as 30-100 Hz, had been reported. In order to address this limitation, we adopted simulation on band-pass filtered noise with the same frequency band as Gamma to help determine the PLV binarizing threshold. It turns out that network characteristics based on binarized PLV have the ability to distinguish the presence or absence of memory, as well as the intensity of the mental workload at the moment of memory. This work sheds a light upon phase-locking investigation between relatively wide-band signals, as well as memory research via EEG.
Implementation of Efficient Teaching Scheme of Human Anatomy and Physiology Based on Multimedia Information Processing Technologies
Authors: Ma Yue , Zhi Zhuangzhi
Published: June 2022

An application scheme based on the teaching of human anatomy and physiology, namely, PBL, is proposed. In particular, 95 medical students were randomly divided into two groups: classes 2 and 3 were the experimental classes (48 students), and then, the teaching practice was carried out according to the machine learning route; year 1 and class 4 were the control classes (47 students), and the traditional teaching method was used. The teaching effectiveness was evaluated by performance analysis, the mean score of the overall evaluation of the experimental class was (93.23 ± 2.01), the mean score of the control group was (91.51 ± 2.89), and the difference was statistically significant (

p
<
0.01

). The survey showed that more than 93% of the students in the experimental class thought that the deep learning model helped stimulate their interest in learning, enhance their sense of teamwork, and improve their overall ability.
Influence Model of Analyzing the Effect of Mental Health Level Based on Big Data Mining System
Authors: Wang Xiaolong
Published: June 2022

In order to explore the effect of big data mining system on analyzing mental health level, this paper proposes to influence model of analyzing the effect of mental health level based on big data mining system. Through continuous testing and analysis, the main symptom affecting students’ mental health is obsessive-compulsive disorder. Therefore, taking obsessive-compulsive disorder as the classification target to view the model, in this application, the factor of compulsion in students’ psychology occupies a relatively high proportion. Anxiety, interpersonal relationship, and paranoia have a great impact on goal attribute obsessive-compulsive disorder. The results showed that if the degree of anxiety = medium, there was a tendency of obsessive-compulsive disorder regardless of the degree of interpersonal relationship. If anxiety level = none, when paranoia level = [mild, moderate], obsessive-compulsive symptoms level = mild, and when paranoia level = none, it is related to interpersonal relationship and hostility. If the degree of paranoia = “severe” or “extremely severe”, the degree of obsessive-compulsive symptoms = none. If the degree of anxiety = light, there is a tendency of obsessive-compulsive disorder regardless of the degree of interpersonal relationship. If the degree of anxiety = severe, the degree of obsessive-compulsive symptoms = moderate. If the degree of depression = medium, the degree of anxiety = medium. If the degree of depression = none, when the degree of terror = medium, the degree of anxiety = light, and when the degree of terror = [none, light, heavy], there is almost no anxiety. If the degree of depression = mild and the degree of obsessive-compulsive symptoms = none, there is no anxiety tendency. If the degree of depression = severe, the degree of anxiety = severe. If the degree of depression = medium, the degree of interpersonal relationship = medium. If the degree of depression = none, when the degree of terror = light and there is psychosis, the degree of interpersonal relationship = light. If the degree of depression = mild and there is obsessive-compulsive disorder, there are problems in interpersonal relationship. The data analysis of mental health problems has been greatly improved, verifying the reliability of the application of data mining systems in mental health evaluation systems.
Risk Factors for Contralateral Occult Papillary Thyroid Carcinoma in Patients with Clinical Unilateral Papillary Thyroid Carcinoma: A Case-Control Study
Authors: Yihao Liu , Shuo Li , Pu Xi , Zipeng Wang , Hanlin Sun , Qungang Chang , Yongfei Wang , Detao Yin
Published: June 2022

Introduction. Papillary thyroid cancer (PTC) is one of the most prevalent endocrine malignancies that has increased in recent decades around the world. Although the indicator for navigating the surgical extent in PTC patients is still in debate, a key issue is how to predict that there are undetected preoperative tumors in the contralateral thyroid lobe. This study aims to find risk factors for contralateral occult papillary thyroid cancer (COPTC) to facilitate more accurate surgical decisions made for patients with PTC. Materials and Methods. In our study, we included 229 patients who underwent total thyroidectomy plus central and ipsilateral lateral lymph nodes dissection from January 1, 2019, to September 1, 2021. Univariate and multivariate logistic regression analyses were conducted to assess the association between COPTC and clinical-pathological characteristics, as well as the relation between the diameter of the occult lesions and predictors. The forest plot was plotted to visualize the prediction factors from the output of the multivariate regression analysis. A ROC curve was used to evaluate the combining potency of all the risk factors. Results. Of the 229 patients included in our study, 46 with COPTC were assigned to the case group, representing 20.1% in this study. Multifocality in one lobe (OR = 2.21,

P
=
0.03

), intact capsule (OR = 2.54,

P
=
0.01

), central lymph node metastasis (OR = 3.00,

P
=
0.02

), and Hashimoto’s thyroiditis (OR = 2.08, P = 0.04) are more prone to present contralateral occult papillary thyroid carcinoma. The ROC curve of the aggregate potency of the risk factors presents AUC = 0.701 (

P
<
0.001

), and the best cutoff value was 2.02, with a sensitivity of 78.3% and specificity of 55.2%. Furthermore, there was no statistical correlation between the diameter of the occult tumor and the four obtained variables. Conclusion. Patients with multifocality in one lobe, intact capsule, central lymph node metastasis, and HT may harbor contralateral papillary thyroid carcinoma. It is essential to be prudent to make a surgical or follow-up decision on these patients. In addition, more clinical rather than postoperative pathological indicators need to be revealed in the future.
Effect of Kvass on Improving Functional Dyspepsia in Rats
Authors: Shao Zhanmei , Zhong Jidong , Fang Yuming , Ma Yongqiang
Published: June 2022

Functional dyspepsia (FD) is a common digestive system disease, and probiotics in the treatment of FD have a good curative effect. Patients with gastrointestinal diseases often show a poor response to traditional drug treatments and suffer from adverse reactions. Kvass can be used as a functional drink without side effects to improve the symptoms of FD patients. The results showed that compared with those of the model group, the body weight and food intake of the treatment group were significantly increased (

P
<
0.05

), and the gastric residual rate of the treatment group was significantly decreased (

P
<
0.05

); the amount of pepsin in the treatment group was significantly higher than that in the model group (

P
<
0.05

); a high dose of Kvass could increase the contents of ghrelin, motilin (MTL), and gastrin (GAS) in the plasma and decrease the contents of vasoactive intestinal peptide (VIP) in the plasma; the contents of ghrelin, MTL, and GAS in the gastric antrum were also increased in the high-dose group. Kvass beverage can significantly improve the gastrointestinal function of rats, which may be because it can improve the contents of ghrelin, MTL, GAS, and VIP in both the serum and gastric antrum by regulating the expression of short-chain fatty acids in the colon.
Target Detection and Network Optimization: Deep Learning in Face Expression Feature Recognition
Authors: Gan Baiqiang , Zhang Chi
Published: June 2022

Facial expression recognition technology has been more and more in demand in security, entertainment, education, medical, and other domains as artificial intelligence has advanced, and face expression recognition technology based on deep learning has become one of the research hotspots. However, there are still some issues with the existing deep learning convolutional neural network; the feature extraction technique has to be improved, and the design of the detailed network structure needs to be optimized. It is critical to do more research on the deep learning convolutional neural network model in order to increase the accuracy of face facial expression detection. In this paper, a deep learning convolutional neural network structure combining VGG16 convolutional neural network and long and short-term memory networks is designed to address the shortcomings of existing deep learning methods in face expression recognition, which are prone to overfitting and gradient disappearance, resulting in low test accuracy. This structure easily and effectively collects facial expression information and then classifies the retrieved features using a support vector machine to detect face expressions. Finally, the fer2013 dataset is used to train face expression recognition, and the results demonstrate that the built deep convolutional neural network model can effectively increase face expression identification accuracy.
Factors Associated with Arkansans’ First Use of Telehealth during the COVID-19 Pandemic
Authors: Andersen Jennifer A. , Felix Holly C. , Su Dejun , Selig James P. , Ratcliff Shawn , McElfish Pearl A.
Published: June 2022

Objective. To examine the factors associated with the first use of telehealth during the COVID-19 pandemic using Andersen’s Model of Healthcare Utilization. Andersen’s Model of Healthcare Utilization allowed the categorization of the independent variables into the following: (1) predisposing factors, including sociodemographic variables and health beliefs; (2) enabling factors, including socioeconomic status and access to care; and (3) need for care, including preexisting or newly diagnosed conditions and reasons to seek out care or to utilize a new mode of care. Methods. Potential respondents (

n
=
4,077

) were identified for recruitment from a volunteer registry in Arkansas. Recruitment emails provided a study description, the opportunity to verify meeting the study’s inclusion criteria and to consent for participation, and a link to follow to complete the survey online. The online survey responses were collected between July and August of 2020 (

n
=
1,137

). Results. Telehealth utilization included two categories: (1) utilizers reported the first use of telehealth services during the pandemic, and (2) nonutilizers reported they had never used telehealth. Lower odds of reporting telehealth utilization during the pandemic were associated with race (Black;

OR
=
0.57

, CI [0.33, 0.96]) and education (high School or less;

OR
=
0.45

, CI [0.25, 0.83]). Higher odds of reporting telehealth utilization included having more than one provider (

OR
=
2.33

, CI [1.30, 4.18]), more physical (

OR
=
1.12

, CI [1.00, 1.25]) and mental (OR 1.53, CI [1.24, 1.88]) health conditions, and changes in healthcare delivery during the pandemic (

OR
=
3.49

, CI [2.78, 4.38]). Conclusions. The results illustrate that disparities exist in Arkansans’ utilization of telehealth services during the pandemic. Future research should explore the disparities in telehealth utilization and how telehealth may be used to address disparities in care for Black Arkansans and those with low socioeconomic status.
A Low-Carbon Planning Model for Regional Power Systems with Generation-Load-Storage Coordination considering New Energy Resources’ Consumption
Authors: Chen Huiyuan , Zhang Hua , Dai Qiqi , Wang Wei , Wang Min
Published: June 2022

With the increase in the proportion of new energy resources being generated in the power system, it is necessary to plan the capacity configuration of the power supply side through the coordination of power generation, grid, load, and energy storage, to create a relatively controllable power generation output and ensure the safe and stable operation of the power system is a key problem that needs to be solved at present. Therefore, combined with national and regional policies and resource constraints in China, this paper firstly determines the requirements and boundary conditions of various power supply planning in the regional power system and proposes a “generation-grid-load-energy storage” coordination mode. Secondly, establish a regional power system coordination planning model considering the proportion of new energy consumption and low-carbon cost. Finally, in three scenarios with a high, medium, and low proportion of new energy resources, the new installed capacity configuration of regional power supply is optimized to verify the effectiveness of the proposed model and provides reference for regional power supply planning.
Determination of the Influence of Strut Connector on Stent Deployment
Authors: Hashim V. , Resmi S. L. , Dileep P. N.
Published: June 2022

Coronary artery stents are tubular structures employed together with angioplasty. Stented angioplasty is a clinical procedure widely applied in the treatment of atherosclerosis to reopen the blocked artery. It is a simple and fast curing minimally invasive clinical procedure. However, it is essential to understand the expansion characteristics of a stent before implantation since the stent geometry, inflating pressure, etc., influence the performance of stents. Finite element analysis and in vitro experiments are simultaneously employed before clinical testing to predict the characteristics during deployment. In this paper, the expansion and deployment characteristics of Meril Osum

2.75
×
24

coronary stent and Envision

3.5
×
28

stent were investigated to study the influence of strut connector on the expansion behaviour of the stent by experimental and computational methods. The current study analyzes the real-time deployment characteristics such as rate of expansion, stress on stent, recoil, dog boning, and foreshortening. The stent expansion characteristics obtained from experiments and simulations were found matching and observed that strut connector has a significant effect on stent expansion. Further, the curved connector of small radius of curvature shows better performance with high patency rate.