bluuebunny/crossref_metadata_2025 huggingface dataset:
Functional Microbes and Their Incorporation into Foods and Food Supplements: Probiotics and Postbiotics
Authors: Puntillo Melisa , Segli Franco , Champagne Claude P. , Raymond Yves , Vinderola Gabriel
Published: March 2022

Life expectancy has dramatically increased over the past 200 years, but modern life factors such as environmental exposure, antibiotic overuse, C-section deliveries, limited breast-feeding, and diets poor in fibers and microbes could be associated with the rise of noncommunicable diseases such as overweight, obesity, diabetes, food allergies, and colorectal cancer as well as other conditions such as mental disorders. Microbial interventions that range from transplanting a whole undefined microbial community from a healthy gut to an ill one, e.g., so-called fecal microbiota transplantation or vaginal seeding, to the administration of selected well-characterized microbes, either live (probiotics) or not (postbiotics), with efficacy demonstrated in clinical trials, may be effective tools to treat or prevent acute and chronic diseases that humans still face, enhancing the quality of life.
Combined Electrochemical, Ellipsometric and Microgravimetric Study of Ion Permeable Polydopamine Films
Authors: Almeida Luís C. , Correia Rui D. , Correia Jorge P. , Viana Ana S.
Published: March 2022

The facile deposition of polydopamine on virtually any material and its recognized adhesive properties justify its extensive application in the biomedical field. However, these films are heterogeneous, poorly conductive and impermeable to many small molecules and ions, limiting their use in electrochemical applications. Hereby, we have potentiodynamically grown polydopamine films on gold using an anodic potential limit of 1.1 V, higher than the typically used values (0.5−0.8 V), aiming at preparing thick and permeable films. The mass increment during the electropolymerization of dopamine undergoes an abrupt change upon the 20th potential cycle, forming a more porous coating, compared to the polymer grown up to 0.8 V. By modelling in situ ellipsometric data, the abrupt phenomenon could be related to a temporary and local loss of polymer adherence to the surface, with the creation of a very porous layer, that is fulfilled in the subsequent cycles with new polymer fibers. Consequently, drastic topographic changes are depicted in polymers grown with 20 and 100 cycles, by atomic force microscopy. Films prepared with 100 cycles are thicker, more electroactive and more permeable to ionic species, than thinner films, unraveling their potential as adhesive matrices in electrochemical transduction devices.
Review—Surface Coatings for Cathodes in Lithium Ion Batteries: From Crystal Structures to Electrochemical Performance
Authors: Kaur Gurbinder , Gates Byron D.
Published: March 2022

Lithium ion batteries (LIBs) have dominated the energy industry due to their unmatchable properties that include a high energy density, a compact design, and an ability to meet a number of required performance characteristics in comparison to other rechargeable systems. Both government agencies and industries are performing intensive research on Li-ion batteries for building an energy-sustainable economy. LIBs are single entities that consist of both organic and inorganic materials with features covering multiple length scales. Two vital parameters for LIBs are their stable and safe operation. Critical insights should be made for understanding the structure to property relationships and the behavior of components under the working condition of LIBs. Since, the cathode serves as a central component of LIBs, the overall cell performance is significantly affected by the chemical and physical properties of the cathode. Cathodes tend to react with the electrolytes and, hence, to undergo surface modifications accompanied by degradation. These side-reactions result in an erosion of battery performance, thereby causing a reduced battery life and power capacity. Recently, techniques for preparing surface coatings on cathode materials have been widely implemented as a measure to improve their stability, to enhance their electrochemical performance, and to prevent detrimental surface reactions between the electrode materials and electrolyte. This review will cover different types of surface coatings for cathode materials, as well as a comparison of the changes in electrochemical performance between those materials with and without an applied coating. In addition, a brief outlook is included for different cathode materials and their coatings.
Nanowire Sensors Using an Electrical Resonance Approach for Vapor Detection
Authors: Prashanthi K. , Thundat T.
Published: March 2022

Recent advances in our understanding of 1D nanomaterials are paving the way for developing novel platforms for sensors and devices based on multi-physics, multi-modal approaches. Here, we report a new way of detecting volatile organic compounds (VOC) using electrical resonance of a single platinum nanowire. The adsorption of molecular dipoles on a nanowire causes a measurable change in the dissipation and frequency of the electrical resonance. The dissipation at the resonance shows enhanced variations depending on the dipole moments of the adsorbates. Experimental results show the limit of detection (LOD) for sensing acetone, methanol, and ethanol by a nanowire sensor in the range of a few ppm. The LOD, however, can be improved by optimizing the electrical parameters of the nanowire. Furthermore, monitoring the dissipation variations at resonance as a function of temperature provides information on thermally induced polarization or depolarization of adsorbed chemical species. The temperature response of the nanowire at resonance could potentially be used to discriminate different vapor molecules based on differential calorimetry.
Fully Vacuum-Free Fabrication of Bi-Directional Polymer Light-Emitting Diodes Based on a Hybrid Lamination Top Electrode
Authors: Kim Yejin , Park Sejung , Lee Inwoo , Lee Yu Seong , Yun Changhun
Published: March 2022

This study investigates a hybrid lamination electrode based on a silver nanowire and a conductive polymer for the top electrode of bi-directional polymer light-emitting diodes (PLEDs). Through a vacuum-free hot-press lamination step, the proposed hybrid electrode employed a complete and concrete electrical contact with the underlying emissive polymer layer. In addition, by inserting a hole injecting poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS) layer to increase the level of work function, the bi-directional PLED device with a laminated top electrode showed a more competitive device performance such as an operating voltage, a current efficiency, and a total external quantum efficiency compared to the counterpart device with a multilayered electrode of MoO3/Ag/MoO3 by the vacuum thermal evaporation method. An analysis carried out on the angular characteristics of bi-directional PLEDs including the variation of color coordinates and change in luminance values according to emission angles confirmed that the hybrid lamination electrode provided a more uniform angular distribution regardless of the direction of emission without any optical micro-cavity effect. Detailed optical and electrical analyses were also performed to evaluate the compatibility of the hybrid lamination electrode for the low-cost fabrication of efficient PLEDs.
Design, Process, and Characterization of Complementary Metal–Oxide–Semiconductor Circuits and Six-Transistor Static Random-Access Memory in 4H-SiC
Authors: Hung Chia-Lung , Tsui Bing-Yue , Tsai Te-Kai , Lin Li-Jung , Wen Yu-Xin
Published: March 2022

In this study, the performance of complementary metal–oxide–semiconductor (MOS) circuits fabricated on SiC substrates was investigated by designing several digital and analog circuits, and a unique process flow was developed to integrate n-type MOS (NMOS) and p-type MOS (PMOS) transistors with low and high threshold voltages (Vth) into a single chip. A detailed process flow with local oxidation of SiC isolation and a dual gate oxide with a compromised gate dielectric are presented. The performance of NMOS field-effect transistors (FETs) and PMOSFETs with low and high Vth were characterized in detail. Lateral MOS capacitors were also fabricated in the same chip to explore the characteristics of the gate dielectric. Several common logic gate components were fabricated and tested at elevated temperatures to demonstrate the normal function of these elements in a digital circuit. Static random-access memory (SRAM) cells were designed and optimized through simulation. Characterizations of all the circuit blocks are presented to demonstrate the capability of these circuits in harsh environments.
Synthesis, Structural, Microscopic, and Electrical Properties Studies of Neodymium Chromite Perovskite Nanoparticles
Authors: Shanker Jada , Ananthaiah J. , Kumar N. Pavan , Venkataramana Kasarapu , Raju P. , Anand pandarinath M. , Meher Abhinav E. , U P Ujwal
Published: March 2022

NdCrO3 perovskite compound synthesized via sol-gel auto-combustion process. Impedance spectroscopic data have been studied in the wide frequency range (0.1 Hz −10 MHz), at various temperatures (RT-500 °C). Structural analysis has been done using Raman spectroscopy, which indicates single-phase orthorhombic structure. EDX, XPS spectrums have shown Nd, Cr, O elements in the NdCrO3 compound, suggesting that mentioned sample is pure. The SEM and TEM analysis confirmed that the distribution of grains and particles is not uniform throughout the surface and material respectively. TEM image indicating the polycrystalline nature and particle size is in the order of 30 nm–50 nm. This material showed the giant dielectric behaviour (

ε

′

>

10

4

). Impedance studies of NdCrO3 perovskite exhibited a negative temperature coefficient of resistance type semiconductor behaviour. The dc conductivity and relaxation plots were followed by Arrhenius law. Frequency reliant ac conductivity plots followed Jonscher’s power law. These results suggest that NdCrO3 is suitable for giant capacitors applications.
Efficacy and Safety of Kleeb Bua Daeng Formula in Mild Cognitive Impairment Patients: A Phase I Randomized, Double-Blind, Placebo-Controlled Trial
Authors: Musigavong Natdanai , Boonyarat Chantana , Chulikhit Yaowared , Monthakantirat Orawan , Limudomporn Makorn , Pitiporn Supaporn , Kwankhao Pakakrong , Daodee Supawadee
Published: March 2022

Individuals with mild cognitive impairment (MCI) were at increased risk of conversion to dementia. The Kleeb Bua Daeng (KBD) formula could be the alternative treatment option for MCI through multitarget activities. Lacking of clinical trial information brought about the study in our research. Forty patients with MCI were randomly assigned to receive the KBD capsule or placebo at a dose of 1,000 mg twice a day for three months. Their cognitive functions were monitored by the Montreal Cognitive Assessment (MoCA) and blood chemistry assessment every one month. We found that the KBD-treated group had no significant differences in the MoCA test compared to placebo. Moreover, there was no alteration in biochemical parameters of the liver and renal function was observed which could confirm the safety of this KBD formula.
5G Network Slicing: Methods to Support Blockchain and Reinforcement Learning
Authors: Hu Juan , Wu Jianwei
Published: March 2022

With the advent of the 5G era, due to the limited network resources and methods before, it cannot be guaranteed that all services can be carried out. In the 5G era, network services are not limited to mobile phones and computers but support the normal operation of equipment in all walks of life. There are more and more scenarios and more and more complex scenarios, and more convenient and fast methods are needed to assist network services. In order to better perform network offloading of the business, make the business more refined, and assist the better development of 5G network technology, this article proposes 5G network slicing: methods to support blockchain and reinforcement learning, aiming to improve the efficiency of network services. The research results of the article show the following: (1) In the model testing stage, the research results on the variation of the delay with the number of slices show that the delay increases with the increase of the number of slices, but the blockchain + reinforcement learning method has the lowest delay. The minimum delay can be maintained. When the number of slices is 3, the delay is 155 ms. (2) The comparison of the latency of different types of slices shows that the latency of 5G network slicing is lower than that of 4G, 3G, and 2G network slicing, and the minimum latency of 5G network slicing using blockchain and reinforcement learning is only 15 ms. (3) In the detection of system reliability, reliability decreases as the number of users increases because reliability is related to time delay. The greater the transmission delay, the lower the reliability. The reliability of supporting blockchain + reinforcement learning method is the highest, with a reliability of 0.95. (4) Through the resource utilization experiment of different slices, it can be known that the method of blockchain + reinforcement learning has the highest resource utilization. The resource utilization rate of the four slices under the blockchain + reinforcement learning method is all above 0.8 and the highest is 1. (5) Through the simulation test of the experiment, the results show that the average receiving throughput of video stream 1 is higher than that of video stream 2, IOT devices and mobile devices, and the average cumulative receiving throughput under the blockchain + reinforcement learning method. The highest is 1450 kbps. The average QOE of video stream 1 is higher than that of video stream 2, IOT devices and mobile devices, and the average QOE is the highest under the blockchain + reinforcement learning method, reaching 0.83.
Interstitial Granulomatous Drug Reaction to Ustekinumab
Authors: Walker A. , Westerdahl J. S. , Zussman J. , Mathis J.
Published: March 2022

Interstitial granulomatous drug reaction (IGDR) is a distinct inflammatory process that often presents as annular, violaceous plaques distributed on the extremities, proximal trunk, and intertriginous areas. The list of drugs implicated for inciting IGDR is growing, but most prominently includes ACE inhibitors, antihistamines, beta-blockers, antidepressants, and anticonvulsants. Ustekinumab is a human monoclonal antibody that targets inflammatory cytokines IL-12 and IL-23 and has been have shown to be effective in treating IGDR. However, we present a case that suggests ustekinumab can also act as an inciting agent for IGDR.
A Study on Information Classification and Storage in Cloud Computing Data Centers Based on Group Collaborative Intelligent Clustering
Authors: Ren Jie , Liu Lijuan
Published: March 2022

Internet of things (IoT) and cloud computing are combined to form a cloud computing data center, and cloud computing provides virtualization, storage, computing, and other support services for IoT applications. Data is the foundation and core of cloud IoT platform applications, and massive multisource heterogeneous IoT data aggregation and storage have basic requirements such as real-time, security, and scalability. This paper focuses on the aggregation and storage methods of massive heterogeneous cloud IoT data, solving the multisource data aggregation problem caused by inconsistent protocols and the heterogeneous data storage problem caused by inconsistent data types. A heterogeneous network protocol adaptation and data aggregation method is proposed for the multisource data aggregation problem caused by protocol inconsistency. A protocol adaptation layer is set up in the IoT virtual gateway to achieve compatibility with multiple types of data aggregation protocols, ensuring adaptive access to different types of IoT nodes, and on this basis, data is transmitted to the cloud IoT platform through a unified interface, shielding the variability of IoT sensing devices. Given the problems of device forgery and malicious tampering in the data aggregation process, we propose a fast authentication and data storage method for IoT devices based on “API key” and implant the device authentication API key into the protocol adaptation layer of the virtual gateway to realize the source authentication of IoT nodes and ensure the authenticity of data.
An Improved Teaching-Learning-Based Optimization Algorithm with Reinforcement Learning Strategy for Solving Optimization Problems
Authors: Wu Di , Wang Shuang , Liu Qingxin , Abualigah Laith , Jia Heming
Published: March 2022

This paper presents an improved teaching-learning-based optimization (TLBO) algorithm for solving optimization problems, called RLTLBO. First, a new learning mode considering the effect of the teacher is presented. Second, the Q-Learning method in reinforcement learning (RL) is introduced to build a switching mechanism between two different learning modes in the learner phase. Finally, ROBL is adopted after both the teacher and learner phases to improve the local optima avoidance ability of RLTLBO. These two strategies effectively enhance the convergence speed and accuracy of the proposed algorithm. RLTLBO is analyzed on 23 standard benchmark functions and eight CEC2017 test functions to verify the optimization performance. The results reveal that proposed algorithm provides effective and efficient performance in solving benchmark test functions. Moreover, RLTLBO is also applied to solve eight industrial engineering design problems. Compared with the basic TLBO and seven state-of-the-art algorithms, the results illustrate that RLTLBO has superior performance and promising prospects for dealing with real-world optimization problems. The source codes of the RLTLBO are publicly available at https://github.com/WangShuang92/RLTLBO.
Recognition of Human Body Feature Changes in Sports Health Based on Deep Learning
Authors: Jiao Chendao
Published: March 2022

With the rapid development of social economy and the extensive and in-depth development of national fitness activities, national physical fitness monitoring and research work has achieved rapid development. In recent years, the application of deep learning technology has also achieved research breakthroughs in the field of computer vision. How deep learning technology can effectively capture motion information in sample data and use it to realize the recognition and classification of human actions is currently a research hot spot. Today’s popularization of various shooting devices such as mobile phones and portable action cameras has contributed to the vigorous growth of image data. Therefore, through computer vision technology, image data is widely used in practical application scenarios of human feature recognition. This paper proposes a deep learning network based on the recognition of human body feature changes in sports, improves the recognition method, and compares the recognition accuracy with the original method. The experimental results of this paper show that the result of this paper is 1.68% higher than the original recognition method, the accuracy rate of the improved motion history image is increased by 14.8%, and the overall recognition rate is higher. It can be seen from the above experimental results that this method has achieved good results in human body action recognition.
Delayed Signs and Symptoms of Extended Release Guanfacine Overdose in Two Adolescent Patients: Implications of Monitoring on the Psychiatry Unit
Authors: Mishra Sanskriti , Shekunov Julia , Derscheid Della J. , Canterbury Elizabeth A. , Leung Jonathan G.
Published: March 2022

Guanfacine is a selective alpha-2a adrenoreceptor agonist that with overdose can cause symptoms ranging from mild sedation to coma, respiratory depression, hyporeflexia, hypotonia, bradycardia, and hypotension. Despite a well-defined and predictable toxidrome, variations can be seen based on multiple factors including age, quantity ingested, organ functions, coingestions, time since ingestion, and specific dosage form. Here, we describe two cases of delayed presentation of extended release guanfacine toxicity and highlight the variations encountered in the toxidrome presentation. These cases bring to attention the importance of maintaining a high suspicion for such atypical presentations, keeping in mind the limitations of managing these complications on an inpatient psychiatric unit.
SPINK5 is a Tumor-Suppressor Gene Involved in the Progression of Nonsmall Cell Lung Carcinoma through Negatively Regulating PSIP1
Authors: Zhang Jiaojiao , Rong Jingfeng , Ge Wen , Wang Jing , Wang Wenjin , Chi Hao
Published: March 2022

This study aimed to elucidate how SPINK5 affects the malignant phenotypes of NSCLC and the molecular mechanism. NSCLC and adjacent normal tissues were collected to detect the differential level of SPINK5. The influence of SPINK5 on pathological indicators of NSCLC was analyzed. Cellular functions of NSCLC cells overexpressing SPINK5 were assessed by CCK-8, EdU, and transwell assay. By confirming the downstream target of SPINK5, its molecular mechanism on regulating NSCLC was finally explored through rescue experiments. SPINK5 was lowly expressed in NSCLC tissues, and it predicted tumor staging and lymphatic metastasis. In vitro overexpression of SPINK5 declined proliferative and migratory rates in NSCLC cells. PSIP1 was verified as the target gene binding SPINK5, and they displayed a negative correlation in NSCLC tissues. Overexpression of PSIP1 was able to reverse the inhibited proliferative and migratory potentials in NSCLC cells overexpressing SPINK5. SPINK5 level has a close relation to tumor staging and lymphatic metastasis in NSCLC. It serves as a tumor-suppressor gene that inhibits proliferation and migration of NSCLC through negatively regulating PSIP1.
Combining Ability Analysis of Relevant Characters of Maize Inbred Lines Suitable for Machine Harvest
Authors: Jiang Long , Rong Meiqi , Wang Mingxin , Chen Dianyuan , Yu Haiyan
Published: March 2022

In this study, 9 maize inbred lines and 36 combinations were used as materials to analyze the combining ability of plant height, ear height, kernel depth, grain water content, tassel branches, stem diameter, and 100 kernels weight so as to screen excellent inbred lines and maize combinations with suitable mechanical harvest characters, which would provide a theoretical basis for breeding new maize varieties suitable for mechanical harvest. The results showed that JK2023, JK2368, and JK2018 were inbred lines whose comprehensive characters met the machine harvest standard and performed well. Besides, the combinations that meet the machine harvest standard and perform well were JK2023 × JK2197, JK2023 × JK2368, JK2023 × JK2005, JK2197 × JK2005, JK2197 × JK2368, and JK2368 × JK2005.
Early OCT Angiography Changes of Macular Neovascularization in Patients with Exudative AMD Treated with Brolucizumab in a Real-World Setting
Authors: Rübsam Anne , Rau Saskia , Pilger Daniel , Zeitz Oliver , Joussen Antonia M.
Published: March 2022

Background. To report on the short-term outcome of intravitreal brolucizumab in patients with neovascular age-related macular degeneration (nAMD). Methods. This is a prospective, interventional, monocentric study on 10 eyes of 10 patients with a treatment-naïve neovascular AMD. Patients were treated according to the HAWK and HARRIER trials. After loading with 3 monthly injections, eyes received an injection 12 weeks after the upload (q12w) or were adjusted to an 8 week interval (q8w), if disease activity was present 8 weeks after the upload. Main outcome measures were the change in central retinal thickness (CRT) assessed by spectral domain optical coherence tomography (SD-OCT), the change in macular neovascularization (MNV) size on optical coherence tomography angiography (OCTA), and the change in best corrected visual acuity (BCVA) 8 and 12 weeks after the upload. We further assessed clinical parameters that predict the treatment response at baseline based on the need of q8w or q12w injections after the upload. Results. CRT decreased significantly from 461.7 ± 82.9 μm to 343.6 ± 74.3 μm (

p
=
0.004

) 12 weeks after the upload. The MNV size decreased significantly from 0.85 ± 1.1 to 0.75 ± 1.2 mm2 (

p
=
0.022

). BCVA improved from 0.67 ± 0.4 to 0.55 ± 0.4logMAR but without statistical significance. MNV size in eyes on q12w was considerably smaller compared to that in eyes on q8w (0.54 ± 0.7 mm2 vs. 1.98 ± 2.4 mm2). The percentage of eyes without any persistent fluid was 70% (7/10 eyes). Conclusions. Brolucizumab appears to be a valuable tool for the management of patients with nAMD. Furthermore, MNV size at baseline might serve as an early predictor of treatment response.
The Synthesis of Hydroxyapatite by Hydrothermal Process with Calcium Lactate Pentahydrate: The Effect of Reagent Concentrations, pH, Temperature, and Pressure
Authors: Szterner Piotr , Biernat Monika
Published: March 2022

Hydroxyapatite and other calcium phosphates in the form of whiskers are lately widely considered as fillers for biocomposites due to their special biological and reinforcing properties. Depending on the method of synthesis, apatite whiskers of various sizes and phase composition can be obtained. In our work, hydroxyapatite (HAp) whiskers were successfully prepared in reaction between calcium lactate pentahydrate and orthophosphoric acid. The advantage of the proposed technique is the simple but precise control of the HAp crystal morphology and high product purity which is necessary for biomedical applications. The effect of reagent concentrations, pH, reaction temperature, and pressure on HAp whiskers’ morphology and composition was investigated. In the result, we obtained hydroxyapatite of different morphology such as whiskers, hexagonal rods, and nanorods. The products were characterized by SEM, XRD, and FTIR. In this work, the synthesis of HAp whiskers by direct decomposition of calcium lactate pentahydrate chelates under hydrothermal conditions was showed for the first time.
The Classification of the Exact Single Travelling Wave Solutions to the Constant Coefficient KP-mKP Equation Employing Complete Discrimination System for Polynomial Method
Authors: Sarkar Tanay , Raut Santanu , Mali Prakash Chandra
Published: March 2022

The purpose of this article is to explore different types of solutions for the Kadomtsev-Petviashvili-modified Kadomtsev-Petviashvili (KP-mKP) equation which is termed as KP-Gardner equation, extensively used to model strong nonlinear internal waves in (

1
+
2

)-dimensions on the stratified ocean shelf. This evolution equation is also used to describe weakly nonlinear shallow-water wave and dispersive interracial waves traveling in a mildly rotating channel with slowly varying topography. Introducing Liu’s approach regarding the complete discrimination system for polynomial and the trial equation technique, a set of new solutions to the KP-mKP equation containing Jacobi elliptic function have been derived. It is found that these analytical solutions numerically exhibit different nonlinear structures such as solitary waves, shock waves, and periodic wave profiles. The reliability and effectiveness are confirmed from the numerical graphs of the solutions. Finally, the existence and validity of the various topological structures of the solutions are confirmed from the phase portrait of the dynamical system. Based on this investigation, it is confirmed that the method is not only suited for obtaining the classification of the solutions but also for qualitative analysis, which means that it can also be extended to other fields of application.
Quantifying Carbon Emissions Generated by Monorail Transits: A Life Cycle Assessment Approach
Authors: Li Teng , Zhu Eryu
Published: March 2022

The use of rail transits results in the generation of a large amount of carbon emissions. Throughout the life cycle of a rail transit system, huge amounts of carbon are emitted, which contributes to the threat posed by carbon emission on the city ecosystem. Despite the many methods previously proposed to quantify carbon emissions from rail transit systems, a method that can be applied to measure carbon emissions of monorail systems is yet to be developed. We have used the life cycle assessment (LCA) method to propose a method that can be used to quantify carbon emissions from monorail transits. The life cycle of a monorail transit system was divided into four stages (production, construction, use, and end-of-life). A monorail transit line segment in Chongqing, China, was selected for a case study. The results show that the “use” stage of the monorail transit line system significantly increases (93.2%) carbon emissions, while the “end-of-life” stage does not contribute significantly to the total carbon emitted. The processes of generation of steal, concrete, and cement are the three leading processes that contribute to the emission of carbon dioxide. The percentages of carbon emitted during these processes are 32%, 29.6%, and 13.3%, respectively. Prestressed concrete activity accounts for the largest proportion (91.1%) of the total carbon emissions. The results presented herein can potentially help in realizing sustainable development and developing green transportation.
General Use of Chinese Herbal Products among Female Patients with Mastitis in Taiwan
Authors: Chou Shu-Huey , Huang Chun-Che , Lin Ching-Heng , Wu Kun-Chang , Chiang Pei-Jung
Published: March 2022

Objectives. Little information is available regarding the use of Chinese herbal medicine to treat mastitis. This study evaluated the prescription patterns of Chinese herbal medicine products in women with mastitis in Taiwan. Design. This is a population-based cross-sectional study. Setting. 8,531 women aged 20–49 years, who received a diagnosis of mastitis between 2004 and 2013, were identified from the Longitudinal Health Insurance Database in Taiwan. We collected data on demographic characteristics, including age, monthly insurance premium, and urbanization level. The ten most Chinese herbal medicines prescribed for mastitis were assessed, including frequency, percentage, average daily dose, and average duration of prescription. Main outcome measures. We analysed the ten most single Chinese herbs and Chinese herbal formulae prescribed for mastitis. Results. Overall, 437 (5.1%) women received Chinese herbal medicine to treat mastitis. Mai Men Dong (Ophiopogon japonicus (Thunb.) Ker Gawl.; 22.3%), Pu Gong Yin (Taraxacum mongolicum Hand.-Mazz.; 7.8%), and Wang Bu Liu Xing (Vaccaria hispanica (Mill.) Rauschert; 3.5%) were three of the most commonly prescribed single Chinese herbs for mastitis. Xian-Fang-Huo-Ming-Yin (18.2%), Jia-Wei-Xiao-Yao-San (9.1%), and Chai-Hu-Shu-Gan-San (8.4%) were three of the most commonly prescribed Chinese herbal formulae. Conclusion. Xian-Fang-Huo-Ming-Yin can clear heat, detoxify body, alleviate swelling, activate blood, and relieve pain. It was the most frequently prescribed Chinese herbal formula in patients with mastitis.
Effects of Angelica Fritillaria Kushen Pill on Renal Function and Immune Function after Laparoscopic Radical Nephrectomy for Patients with Renal Carcinoma
Authors: Wang Xiaohua , Liu Jian , Zhou Ping , Han Zengtai , Meng Zhen , Yang Hongyan
Published: March 2022

Objective. To investigate the effect of Danggui Beimu Kushen Pills on renal cell carcinoma patients undergoing laparoscopic radical resection and their effects on renal function and immune function. Methods. 106 patients with renal cell carcinoma who underwent retroperitoneal laparoscopic radical surgery in our hospital from March 2015 to February 2017 were selected, and they were divided into control group and treatment group. The control group was treated with interferon and the treatment group was treated with Danggui Beimu Kushen pills on the basis of the control group. The clinical efficacy, incidence of adverse reactions, survival rate, and the relationship with clinical stages were detected in the two groups. The renal function index levels, immune function index levels, and quality of life levels were measured in the two groups after treatment. Results. Compared with the control group, the total clinical effective rate was increased, the abnormal renal function, abnormal liver function, and platelet decline were decreased, and the survival rate was significantly elevated in the treatment group. The patients with clinical stage I∼II’ survival rate was increased, relative to patients with clinical stage III. After treatment, the levels of β2-MG, SCr, BUN, and CD8+ in the two groups were decreased, while the levels of CD3+, CD4+, and CD4+/CD8+ were increased. Moreover, the scores of physical function, social function, emotional function, role function, cognitive function, and total score of the two groups were improved. Compared with the control group, the treatment group changes were more obvious. Conclusion. The Danggui Beimu Kushen Pill has significant clinical effects on the treatment of renal cancer, which can improve the clinical symptoms, enhance the immune function, restore the health renal function, improve the quality of life, prolong the survival time of patients, reduce the incidence of adverse reactions, and provide high safety.
Research on College Students’ Physique Testing Platform Based on Big Data Analysis
Authors: Chu Ting
Published: March 2022

With the progress of the times, people’s living standards have significantly improved, gradually put physical health in the first place, college students as the country’s future talent reserve, its physical health development is particularly important. But for a long time, the physique level of college students has failed to reach the standard, and universities are exploring ways to improve the physique level of college students. In view of the existing deficiencies in the monitoring platform of student’s physique, we fully utilize the advanced technology of computer and Internet development and follow the basic principles of economical practicality, scalability, user-friendliness and real-time information exchange to establish monitoring and service platform for college students’ physique. With the aid of the thinking mode of big data and related technology, build the physical health of college students in China big data analytics platform framework, physical health of large numbers of college students in China are put forward According to the analysis platform construction principle, data source, data handling, data platform and application platform, etc., in order to guide the physical health of college students practice in our country, to promote the reform of physical health education for students in colleges and universities. By using big data analysis technology, 65,535 physical health records of all students in a university from 2017 to 2019 were recorded as data sources, and algorithm based on distance was applied to cluster analysis of two groups of data classified by male and female gender, and a series of data were processed, converted, and modeled.
A Novel Reformed Reduced Kernel Extreme Learning Machine with RELIEF-F for Classification
Authors: Liu Zongying , Hao Jiangling , Yang Dongrui , Tahir Ghalib Ahmed , Pan Mingyang
Published: March 2022

With the exponential growth of the Internet population, scientists and researchers face the large-scale data for processing. However, the traditional algorithms, due to their complex computation, are not suitable for the large-scale data, although they play a vital role in dealing with large-scale data for classification and regression. One of these variants, which is called Reduced Kernel Extreme Learning Machine (Reduced-KELM), is widely used in the classification task and attracts attention from researchers due to its superior performance. However, it still has limitations, such as instability of prediction because of the random selection and the redundant training samples and features because of large-scaled input data. This study proposes a novel model called Reformed Reduced Kernel Extreme Learning Machine with RELIEF-F (R-RKELM) for human activity recognition. RELIEF-F is applied to discard the attributes of samples with the negative values in the weights. A new sample selection approach, which is used to further reduce training samples and to replace the random selection part of Reduced-KELM, solves the unstable classification problem in the conventional Reduced-KELM and computation complexity problem. According to experimental results and statistical analysis, our proposed model obtains the best classification performances for human activity data sets than those of the baseline model, with an accuracy of 92.87 % for HAPT, 92.81 % for HARUS, and 86.92 % for Smartphone, respectively.
Class-Incremental Learning on Video-Based Action Recognition by Distillation of Various Knowledge
Authors: Maraghi Vali Ollah , Faez Karim
Published: March 2022

Recognition of activities in the video is an important field in computer vision. Many successful works have been done on activity recognition and they achieved acceptable results in recent years. However, their training is completely static, meaning that all classes are taught to the system in one training step. The system is only able to recognize the equivalent classes. The main disadvantage of this type of training is that if new classes need to be taught to the system, the system must be retrained from scratch and all classes retaught to the system. This specification has many challenges, such as storing and retaining data and respending training costs. We propose an approach for training the action recognition system in video data which can teach new classes to the system without the need for previous data. We will provide an incremental learning algorithm for class recognition tasks in video data. Two different approaches are combined to prevent catastrophic forgetting in the proposed algorithm. In the proposed incremental learning algorithm, two approaches are introduced and used to maintain network information in combination. These two approaches are network sharing and network knowledge distillation. We introduce a neural network architecture for action recognition to understand and represent the video data. We propose the distillation of network knowledge at the classification and feature level, which can be divided into spatial and temporal parts at the feature level. We also suggest initializing new classifiers using previous classifiers. The proposed algorithm is evaluated on the USCF101, HMDB51, and Kinetics-400 datasets. We will consider various factors such as the amount of distillation knowledge, the number of new classes and the incremental learnings stages, and their impact on the final recognition system. Finally, we will show that the proposed algorithm can teach new classes to the recognition system without forgetting the previous classes and does not need the previous data or exemplar data.
Research on Forecast of Macroeconomic Indicators Based on Multiobjective Optimization
Authors: Fan Hongyu
Published: March 2022

In recent years, with China’s economic development entering a new normal, the total scale and complexity of economic development have increased unprecedentedly, and the requirements of government management and regulation of the economy are getting higher and higher. Traditional management concepts, methods, and tools are difficult to meet the needs of the new situation. Therefore, using computer science and technology to fully consider the correlation between various industries and explore new laws of economic operation under the new normal can provide new technical support for promoting the precision of government governance. In previous studies, Most of them take statistics and econometrics as the theoretical basis of macroeconomic decision-making research. This study is based on the analysis of the relationship between the macroeconomic indicators, the establishment of forecasting models to predict the trend of the macroeconomic indicators, and according to the relationship between various economic indicators to build a multiobjective optimization problem, through the multiobjective optimization algorithm to obtain optimal data for the government decision-making basis. In the research process, we focus on solving the problem of prediction overfitting caused by small samples of economic index data and high feature dimension of samples and how to balance the convergence and diversity of solution set in high-dimensional multiobjective optimization problems. In view of the above problems, we propose two economic index forecasting models to solve a variety of fitting problems. On the premise of optimizing space decomposition, an adaptive generation strategy based on inflection point and center point is proposed, and an adaptive solution set selection strategy based on included angle, inflection point, and strong dominance relationship is proposed to balance the convergence and diversity of the multiobjective optimization algorithm.
Automatic Control Model of Power Information System Access Based on Artificial Intelligence Technology
Authors: Jiang De Yong , Zhang Hong , Kumar Harish , Naveed Quadri Noorulhasan , Takhi Chandan , Jagota Vishal , Jain Rituraj
Published: March 2022

Looking at the issues of low efficiency, poor control performance, and difficult access control of the traditional role-based access control model, an artificial intelligence technique-based power information system access control model has been designed. The detector is designed by artificial intelligence technology, combining artificial neural network, and artificial immune algorithm, which provide the basis for checking the access request module. It has been proved that the design model can effectively support the access and modification of legitimate users and prevent illegal users from accessing, and the control accuracy is high. The use of artificial intelligence (AI) in the power sector is now reaching emerging markets, where it may have a critical impact, as clean, cheap, and reliable energy is essential to development. Artificial intelligence can be proven very efficient for resolving the control and decision-making issues in high complex systems.
Comprehensive Landscape of HOXA2, HOXA9, and HOXA10 as Potential Biomarkers for Predicting Progression and Prognosis in Prostate Cancer
Authors: Song Yan-ping , Xian Peng , Luo Hong , Dai Jun-yong , Bai Yu , Li Yuan , Tang Xian-li
Published: March 2022

Prostate cancer (PCa) is recognized as a common malignancy in male patients. The homeobox A cluster (HOXA) family members have been confirmed to be implicated in the development of several types of tumors. However, the expression pattern and prognostic values of HOXA genes in PCa have not been investigated. In this study, we analyzed TCGA datasets and identified six HOXA family members which showed a dysregulated expression in PCa specimens compared with nontumor specimens. We also explored the potential mechanisms involved in the dysregulation of HOXA family members in PCa, and the results of Pearson’s correlation revealed that most HOXA members were negatively related to the methylation degree. Moreover, we explored the prognostic values of HOXA family members and identified six survival-related HOXA members. Importantly, HOXA2, HOXA9, and HOXA10 were identified as critical PCa-related genes which were abnormally expressed in PCa and associated with clinical outcomes of PCa patients. Then, we explored the association between the above three genes and immune cell infiltration. We observed that the levels of HOXA2, HOXA9, and HOXA10 were associated with the levels of immune infiltration of several kinds of immune cells. Overall, our findings identified the potential values of the HOXA family for outcome prediction in PCa, which might facilitate personalized counselling and treatment in PCa.
Ming-Mu-Di-Huang-Pill Activates SQSTM1 via AMPK-Mediated Autophagic KEAP1 Degradation and Protects RPE Cells from Oxidative Damage
Authors: Chen Xi , Zhu Yujie , Shi Xiaoqing , Zuo Jing , Hu Tianming , Wu Hao , Xia Ying , Shi Wei , Wei Wei
Published: March 2022

Oxidative stress and diminished autophagy in the retinal pigment epithelium (RPE) play crucial roles in the pathogenesis of age-related macular degeneration (AMD). Enhancing autophagy has recently been identified as an important strategy to protect RPE cells from oxidative damage. Ming-Mu-Di-Huang-Pill (MMDH pill) is a traditional herbal medicine used to treat AMD, and its molecular mechanism is not well understood. The aim of the present study was to investigate whether the MMDH pill relieved acute oxidative damage by activating autophagy in an in vitro and in vivo model of sodium iodate (NaIO3). The results showed that NaIO3 induced cell death and inhibited proliferation. The MMDH pill increased cell viability, restored the activities of antioxidant enzymes, and reduced reactive oxygen species (ROS) fluorescence intensity. The MMDH pill mediated Kelch-like ECH-associated protein 1 (Keap1) degradation and decreased oxidative damage, which was blocked in autophagy inhibitor (chloroquine) or sequestosome-1 (SQSTM1) siRNA-treated RPE cells. Furthermore, we indicated that the MMDH pill could promote adenosine monophosphate-activated protein kinase (AMPK) phosphorylation and autophagy adaptor-SQSTM1 expression, which could stimulate autophagic degradation of Keap1. In addition, the MMDH pill increased nuclear factor (erythroid-derived 2)-like 2 (Nrf2) nuclear translocation in a SQSTM1-dependent manner and induced the expression of the downstream antioxidant factors heme oxygenase-1 (HO-1) and nicotinamide adenine dinucleotide phosphate quinone dehydrogenase 1 (NQO1). In conclusion, MMDH pill plays a protective role in relieving NaIO3-induced oxidative stress by activating the AMPK/SQSTM1/Keap1 pathway. The MMDH pill may be useful to treat AMD by maintaining redox homeostasis and autophagy.
A Corpus-Driven Study on Three Elements of Third Personal Pronoun Endophora in English Abstracts of Chinese and Foreign Theses
Authors: Luo Yuxiao
Published: March 2022

The corpus is applied to compare and analyze three elements of the third personal pronoun endophora in English abstracts of Chinese and foreign theses. It is discovered that there is no significant difference in the total frequency of third personal pronoun endophora used by Chinese and foreign masters, but there is a significant difference in three elements of third personal pronoun endophora. Native Chinese-speaking masters tend to choose “it” as the anaphor, while native English-speaking masters are inclined to select “them” as the anaphor; antecedents used by native Chinese-speaking masters are mostly consistent with keywords of theses, while antecedents used by native English-speaking masters are rarely consistent with keywords of theses; distances between antecedents and anaphors set by native Chinese-speaking masters are much longer than those set by native English-speaking masters. These findings are beneficial for Chinese masters in terms of better understanding the writing conventions of English abstracts of foreign theses and further improving the language quality of English abstracts in their theses.