bluuebunny/crossref_metadata_2025 huggingface dataset:
[Retracted] Clinical Efficacy of Laparoscopic‐Assisted Proximal Gastrectomy with Postoperative Double‐Channel Digestive Tract Reconstruction: A Case‐Control Analysis
Authors: Yang Qian , Mo Weisheng , Che Xiao , Chen Hongzhen , Cui Chunhui
Published: August 2022

Objective. To investigate the clinical effect of laparoscopic‐assisted proximal gastrectomy with postoperative double‐channel digestive tract reconstruction. Methods. A total of 40 patients with proximal gastric cancer who underwent gastrectomy in Zhujiang Hospital, Southern Medical University, were selected to collect relevant clinical data. They were divided into two groups according to their treatment methods: TG‐RY group (total gastrectomy with Roux‐en‐Y reconstruction group) and PG‐DT group (proximal gastrectomy with double tract reconstruction group). The general data, perioperative indicators, nutritional indicators, and postoperative complications of the two groups were analyzed and compared. Results. There was no statistical significance in the comparison of general data between the two groups, but the proportion of III stage patients of TNM stage in the PG‐DT group was larger than that in the TG‐RY group. Meanwhile, the intraoperative blood loss, postoperative hospital stay, and first exhaust time in PG‐DT group were lower than those in TG‐RY group (P < 0.05). After surgery, the nutritional indexes of the PG‐DT group decreased, and the decrease degree was less than that of the TG‐RY group, while the infection indicators of the PG‐DT group increased less than that of the TG‐RY group. Statistical analysis of postoperative complications showed that the total incidence of PG‐DT group was lower than that of TG‐RY group. Conclusion. Proximal gastric cancer resection and postoperative DTR anastomosis can effectively speed up the recovery of patients and reduce the incidence of postoperative complications, with good efficacy. This experiment provides evidence for the advantages of various postoperative anastomosis methods and also provides a reliable basis for clinicians’ diagnosis and treatment, thus effectively improving patients’ postoperative quality of life.
Preclinical Evaluation of the Tumorigenic and Immunomodulatory Properties of Human Bone Marrow Mesenchymal Stromal Cell Populations with Clonal Trisomy 5
Authors: Marodin Maria Susana Joya , Godoy Juliana A. , Alves-Paiva Raquel M. , Alvarez Kelen , Mitsugi Thiago Giove , Krepischi Ana Cristina Victorino , Hamerschlak Nelson , Bortolini Maria Augusta Tezelli , Castro Rodrigo , Kondo Andrea T. , Kutner Jose Mauro , Okamoto Oswaldo Keith
Published: August 2022

Cytogenetic aberrations may emerge in human mesenchymal stromal cells (MSC) during ex vivo expansion for cell therapy. We have detected clonal trisomy 5 in two distinct autologous MSC products expanded from bone marrow which, based on the current quality control criteria, could not be released for clinical use. Although a safety concern, it is still unclear to what extent recurrent aneuploidies detected in MSC products may affect the threshold for neoplastic transformation or the medicinal properties of these cells. We have carried out an exploratory preclinical study to evaluate these MSC products with clonal trisomy 5, regarding their oncogenic and immunomodulatory potential. Cell population growth in vitro was reduced in MSC cultures with clonal trisomy 5 compared with the population growth of their euploid MSC counterparts, based on a lower cumulative population doubling level, reduced cell proliferation index, and increased senescence-associated beta-galactosidase activity. Subcutaneous injection of clinically relevant amount of MSC population, either with or without clonal trisomy 5, did not generate tumors in immunodeficient mice within a follow-up period of six months. Most importantly, MSC population with clonal trisomy 5 kept immunomodulatory properties upon interferon gamma (IFNγ) licensing, displaying overexpression of IDO, CXCL9, CXCL10, and CXCL11, in a similar fashion than that of IFNγ-licensed euploid MSC. Our findings suggest that bone marrow MSC products with clonal trisomy 5 may retain their therapeutic potential, based on poor tumor initiating capability and preserved immunomodulatory potency. This preclinical evidence may further support the definition of release criteria of autologous MSC products for cell therapy under critical clinical scenarios. This trial is registered with Clinical Study registration number: RBR-29x2pr.
Hypoxia-Driven M2-Polarized Macrophages Facilitate Cancer Aggressiveness and Temozolomide Resistance in Glioblastoma
Authors: Zhang Ge , Tao Xiang , Ji Baowei , Gong Jie
Published: August 2022

Hypoxia-induced M2 phenotypes of tumor associated macrophages (TAMs) promote the development and chemoresistance of multiple types of cancers, including glioblastoma (GBM). However, the detailed molecular mechanisms have not been fully understood. In this study, we firstly reported that hypoxic pressure promoted M2 macrophage generation, which further promoted cancer progression and temozolomide (TMZ) resistance in GBM through secreting vascular endothelial growth factor (VEGF). Specifically, the clinical data suggested that M2 macrophages were significantly enriched in GBM tissues compared with the adjacent normal tissues, and the following in vitro experiments validated that hypoxic pressure promoted M2-polarized macrophages through upregulating hypoxia-inducible factor-1α (HIF-1α). In addition, hypoxic M2 macrophages VEGF-dependently promoted cell proliferation, epithelial-mesenchymal transition (EMT), glioblastoma stem cell (GSC) properties, and TMZ resistance in GBM cells through activating the PI3K/Akt/Nrf2 pathway. Also, M2 macrophages secreted VEGF to accelerate angiogenesis in human umbilical vein endothelial cells (HUVECs) through interacting with its receptor VEGFR. In general, we concluded that hypoxic M2 macrophages contributed to cancer progression, stemness, drug resistance, and angiogenesis in GBM through secreting VEGF, and our data supported the notion that targeting hypoxia-associated M2 macrophages might be an effective treatment strategy for GBM in clinical practices.
WSN Protocols and Security Challenges for Environmental Monitoring Applications: A Survey
Authors: Adu-Manu Kofi Sarpong , Engmann Felicia , Sarfo-Kantanka Godwin , Baiden Godwill Enchill , Dulemordzi Bernice Akusika
Published: August 2022

In recent years, communication technology has improved exponentially, partly owing to the locations and nature of the deployment of sensor nodes. Wireless sensor networks (WSNs) comprise these sensor nodes and can provide real-time physical and environmental measurements. The sensor nodes have limited power, which reduces their lifespan, especially when placed in human-inaccessible locations. This paper reviews energy-efficient protocols for environmental monitoring applications and energy harvesting-wireless sensor networks. The dynamic deployment and communication challenges associated with environmental monitoring applications (EMAs) make this paper take into account the WSN protocol stack, focusing on the physical layer, network layer (routing), and medium access control (MAC). The paper will delve deeper into the security challenges of deploying sensor nodes for environmental monitoring applications (EMAs). The paper further describes scientific approaches that churn out innovative and engineering applications that must be followed to improve environmental monitoring applications.
Decreased Hospital Length of Stay for ICH and PE after Adoption of an Artificial Intelligence-Augmented Radiological Worklist Triage System
Authors: Petry Michael , Lansky Charlotte , Chodakiewitz Yosef , Maya Marcel , Pressman Barry
Published: August 2022

The purpose of the study was to determine whether there was a difference in the length of stay (LOS) for inpatients diagnosed with intracranial hemorrhage (ICH) or pulmonary embolism (PE) prior to and following implementation of an (AI) triage software. A retrospective review was performed for patients that underwent CT imaging procedures related to ICH and PE from April 2016 to October 2019. All patient encounters that included noncontrast head computed tomography (CT) or CT chest angiogram (CTCA) procedures, identified by the DICOM study descriptions, from April 2016 to April 2019 were included for ICH and PE, respectively. All patients that were diagnosed with ICH or PE were identified using ICD9 and ICD10 codes. Three separate control groups were defined as follows: (i) all remaining patients that underwent the designated imaging studies, (ii) patients diagnosed with hip fractures, and (iii) all hospital wide encounters, during the study period. Pre-AI and post-AI time periods were defined around the deployment dates of the ICH and PE modules, respectively. The reduction in LOS was 1.30 days (95% C.I. 0.1–2.5), resulting in an observed percentage decrease of 11.9% (

p

value = 0.032), for ICH and 2.07 days (95% C.I. 0.1–4.0), resulting in an observed percentage decrease of 26.3% (

p

value = 0.034), for PE when comparing the pre-AI and post-AI time periods. Reductions in LOS were observed in the ICH pre-AI and post-AI time period group for patients that were not diagnosed with ICH, but that underwent related imaging, 0.46 days (95% C.I. 0.1–0.8) resulting in an observed percentage decrease of 5% (

p

value = 0.018), and inpatients that were diagnosed with hip fractures, 0.60 days (95% C.I. 0.1–1.2) resulting in an observed percentage decrease of 8.3% (

p

value = 0.004). No other significant decrease in length of stay was observed in any of the other patient groups. The introduction of computer-aided triage and prioritization software into the radiological workflow was associated with a significant decrease in length of stay for patients diagnosed with ICH and PE.
Spam Identification in Cloud Computing Based on Text Filtering System
Authors: Mu Rong
Published: August 2022

With the rapid increase of spam on the Internet and the diversification of its forms, how to quickly and effectively identify a large number of spam on the Internet has become an urgent topic. Cloud computing has obvious advantages in storage and processing, so it can effectively calculate a large amount of mail data. Due to the uncertainty and life cycle of spam, feedback re-judgment is added to the anti-spam system, and a text filtering system based on active learning with four stages of training, filtering, feedback, and re-filtering is implemented. Compared with the original system, the filtering system with feedback can improve the filtering of keywords. In order to effectively reduce the misjudgment rate of ordinary mail and improve the accuracy of spam judgment, it is suggested to improve the use of weighted decision-making of email header information to implement effective auxiliary classification. For emails lacking content, the filtering method of title weighting is feasible and effective, which can improve the identification of spam with relatively little text content. Because the filtering method on the cloud is far more advanced than the traditional algorithm, the development of the Internet can effectively solve the infinite increase of spam. Therefore, this paper makes an in-depth study on spam identification in cloud computing based on text filtering system by summarizing and analyzing the current anti-spam technologies.
Evaluation Method of Enterprise Management Effectiveness Based on Improved Analytic Hierarchy Process
Authors: Cheng Lingfeng
Published: August 2022

To describe the effectiveness of enterprise management through quantitative methods, this paper established an evaluation index system through five levels: profitability, solvency, operation ability, development ability, marketization ability. The data of enterprise performance evaluation indicators were dimensionless processed to remove the influence of dimensionality of evaluation indicators and finally synthesized into a relative quantitative value. The study used hierarchical analysis on determining indicator weights. Through the construction of management possible set and management front surface, the general form of management effectiveness was put forward. By using this method, the influence of the difference of objective basic conditions between the evaluation units can be completely eliminated. There were several enterprises selected as samples to conduct an empirical study, and the results showed that the evaluation method of enterprise management effectiveness can completely eliminate the impact of differences in objective basic conditions between enterprises on the evaluation of management effect. This study shows that the evaluation method of management effectiveness can fairly describe the pros and cons of the degree of enterprise management.
Quantifying Information Flows among Developed and Emerging Equity Markets
Authors: Boateng Ebenezer , Owusu Junior Peterson , Adam Anokye M. , Abeka Mac Jr. , Qabhobho Thobekile , Asafo-Adjei Emmanuel
Published: August 2022

We rely on daily changes in implied volatility indices for the US stock market (VIX), developed markets excluding the US (VXEFA), stock markets in Brazil (VXEWZ), Russia (RVI), India (NIFVIX), China (VXFXI), and the overall emerging market volatility index (VXEEM) to examine the degree of information flows among the markets in the coronavirus pandemic. The study also employs the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) to decompose the data into intrinsic mode functions (IMFs). Subsequently, we cluster the IMFs based on their level of frequencies into short-, medium-, and long-term horizons. The analysis draws on the concept of Rényi transfer entropy (RTE) to enable an assessment of linear as well as non-linear and tail-dependence in the markets. The study reports significant information flows from BRIC volatility indices to the overall emerging market volatility index in the short-and medium-terms and vice versa. We also document a mixture of bi-directional and uni-directional flow of high risk information and low risk information emanating from emerging equity markets and from the developed markets. We find that the transmission of high risk information is largely dominated by the developed markets (VIX and VXEFA). In the midst of high degree of contagion, our findings reveal that investors can find minimal benefits by shielding against adverse shocks from the developed markets with a combination of stocks from India and other equities in the emerging markets in the short-term, within 1–15 days. For as low as 1–5 days, the empirical evidence indicates that a portfolio consisting of stocks from Russia and Brazil also offer immunity to shocks from the VXEFA. Our study makes an important empirical contribution to the study of market integration and contagion among emerging markets and developed markets in crisis periods.
Thermal Analysis of Ni-Cu Alloy Nanocomposites Processed by Sand Mold Casting
Authors: Kumaraswamy J. , Shetty Vidyasagar , Sanman S. , Naik Premkumar , Shedthi Shabari , Gnanavel C. , Mogose Ibsa Neme
Published: August 2022

Ni-Cu based alloy metal matrix nanocomposites are in great demand for advanced technological applications due to their high temperature, strength, and better thermal properties. The aim is to investigate the thermal conductivity and coefficient of thermal expansion of the nickel based alloy nanocomposites reinforced with titanium dioxide (TiO2) which varies from 3 to 12 weight % nanoparticulates (45 to 60 nm). The thermal conductivity was measured using a comparative cut bar method (ASTM E1225), and thermal expansion was analyzed using a push-rod dilatometer method (ASTM E228). From experimentation, it was observed that thermal conductivity of the nanocomposites activity increases with inclusion of the nanoparticles up to 9 weight % after descent due to the temperature effects in nanocomposites, and thermal expansion of the nanocomposites decreases with addition of the nanoparticles up to 9 weight % and further rises marginally due to ductility of composites. Due to the incorporation of hard ceramic particles into the matrix, the composites’ thermal conductivity increases to 57.42 W/m℃, and their thermal expansion decreases to 12 × 10−6. Nickel alloys are widely used in marine, automotive, valve, pump, and aircraft applications.
Dynamical Behavior of the SEIS Infectious Disease Model with White Noise Disturbance
Authors: Song Yuheng , Han Qixing
Published: August 2022

Mathematical model plays an important role in understanding the disease dynamics and designing strategies to control the spread of infectious diseases. In this paper, we consider a deterministic SEIS model with a saturation incidence rate and its stochastic version. To begin with, we propose the deterministic SEIS epidemic model with a saturation incidence rate and obtain a basic reproduction number R0. Our investigation shows that the deterministic model has two kinds of equilibria points, that is, disease‐free equilibrium E0 and endemic equilibrium E∗. The conditions of asymptotic behaviors are determined by the two threshold parameters R0 and . When R0 < 1, the disease‐free equilibrium E0 is locally asymptotically stable, and it is unstable when R0 > 1. E∗ is locally asymptotically stable when . In addition, we show that the stochastic system exists a unique positive global solution. Conditions and are used to show extinction of the disease in the exponent. Finally, SEIS with a stochastic version has stationary distribution and the ergodicity holds when by constructing appropriate Lyapunov function. Our theoretical finding is supported by numerical simulations. The aim of our analysis is to assist the policy‐maker in prevention and control of disease for maximum effectiveness.
Evaluation of College English Teaching Quality Based on Improved BT-SVM Algorithm
Authors: Lou Minsheng
Published: August 2022

With the development of teaching evaluation program, colleges and universities have reformed according to the actual situation of the school. With the development of evaluation activities, many universities are eager to establish their own teaching quality evaluation system, so as to pre-evaluate the teaching quality of schools. SVM is one of the most widely used machine learning algorithms that enables efficient statistical learning with a very limited number of samples. Considering the excellent learning performance of SVM, it is very suitable for the teaching quality evaluation system. In this paper, we optimize the existing multiple classification algorithm for binary trees and propose a new method. Learning the popular teaching quality evaluation system in colleges and universities, the binary tree support vector machine classification algorithm, and design comparison experiment, the experimental results show that the evaluation model proposed in this paper has strong generalization ability and higher classification accuracy and better classification efficiency.
[Retracted] Innovation of French Interpretation Teaching Mode in the New Liberal Arts Environment
Authors: Zhang Junxiu
Published: August 2022

The status of French as a language has improved to some extent in recent years as a result of the exchange and blending of cultures from various nations. Each language, including French, must undergo a protracted process in order to become more widely spoken. It is essential to develop top‐notch French interpreters in order to lower the barriers preventing cross‐border communication. The teaching of French interpretation has recently received more attention in many colleges, but the issue of a single teaching method has long persisted. In recent years, a new approach to teaching the liberal arts has emerged. Its main goal is to implement comprehensive interdisciplinary teaching by fusing contemporary information technology with traditional liberal arts instruction. This paper conducted a cutting‐edge study on the teaching method of French interpretation against the backdrop of the new liberal arts in order to alter the teaching strategy and increase teaching effectiveness. In this paper, an intelligent interpretation teaching system was constructed using information technology. Through text classification algorithms, it incorporated and optimized teaching resources. According to the experimental findings, the teaching process was optimized, and the teaching efficiency increased by 7.94% when French interpretation was taught against a backdrop of new liberal arts.
A Novel Framework of Modelling, Control, and Simulation for Autonomous Quadrotor UAVs Utilizing Arduino Mega
Authors: Tran Hoang T. , Tran Dong L. T. , Nguyen Vinh Q. , Do Hai T. , Nguyen Minh T.
Published: August 2022

In recent decades, there has been a constant increase in the use of unmanned aerial vehicles (UAVs). There has also been a huge growth in the number of control algorithms to support the many applications embodied by the vehicles, including challenges and open issues to develop. This paper focuses on three major classes of control methods applied to quadrotors in order to create an open-source model based on the Arduino Mega that allows for the derivation and design of quadrotor control strategies. We consider the perspective classes, including linear, nonlinear, and intelligent methods representing in details with applications in developing an open-source controller for the quadrotor using the Arduino Mega and the BNO055 9 DOF sensor. We propose Proportional Integral Derivative (PID), backstepping integrator, and model predictive control (MPC) to track a generated Lissajous curve for surveillance. Simulations in the Matlab–Simulink environment with 3D visualization of a developed quadrotor model using CAD software, with robustness and performance discussion, are provided. Our experimental work is developed with an extensive illustration of the hardware and algorithm design and by demonstrating the effectiveness of the proposed architectures. The results show promise in practical and in intelligent applications.
[Retracted] Cellular Imaging Analysis Algorithm‐Based Assessment and Prediction of Disease in Patients with Acute Lung Injury
Authors: Gao Liang , Xiao Chengwang , Cheng Taoyi , Wang Zhaohan , Xia Wenhan
Published: August 2022

This paper uses cellular imaging analysis algorithms to assess and predict the condition of patients with acute lung injury. Given the unique optical properties of UCNPs, this paper designs a ratiometric upconversion fluorescent nanoprobe for the determination of nitric oxide (NO) content in living cells and tissues. To address the image degradation phenomenon of optical sections, this paper uses a blind deconvolution method to abate the degradation effect caused by the scattered focus surface, thus completing the image recovery. After that, grayscale and binarization are performed using the weighted average method and the Otsu method. In this paper, we propose a migration learning‐based Resnet‐50 network for the triple classification of unlabeled leukocytes based on the characteristics of cell images acquired by a miniaturized label‐free microfluidic cell imaging detection device. The migration learning can rapidly optimize the network parameters, the short connection structure of Resnet‐50 is more suitable for feature extraction of unlabeled leukocytes than the InceptionV3 model without a short connection structure, and the accuracy of the Resnet‐50 network can reach 94% in the test set. In this paper, we propose two tracking algorithms based on the dynamic Gaussian mixture model and mathematical morphology‐based algorithms suitable for cells of different shapes for cell tracking in microscopic images, neuronal cell labeling in fluorescent images, and cell segmentation in mice. These methods have the advantages of low cost, speed, reproducibility, and objectivity, and we hope that their elicitation will be useful for relevant cell biology research.
Signature and Molecular Mechanism of Mitochondrial Energy Metabolism Pathway-Related Genes in Lung Adenocarcinoma
Authors: Liu Jiayuan , Zhang Feng , Zhong Jinlong , Zheng Zhi
Published: August 2022

Objective. The mitochondrial energy metabolic pathway (MEMP) is the primary energy metabolism of tumor cells, and its disruption may promote cancer emergence, spreading, and immune escape. However, there is a lack of studies to determine the relationship between relevant functional mechanisms and lung adenocarcinoma (LUAD) prognosis. Methods. Gene set enrichment analysis (GSEA) was employed to determine MEMP pathway-related genes. Then, a prognostic model was created using the MEMP key genes that were found by LASSO-Cox regression analysis. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases provided the training and validation sets. Furthermore, the infiltration of immune cells was examined by ssGSEA. Finally, a screening of candidate therapeutic compounds for LUAD patients was performed using DrugBank, Protein Data Bank (PDB), and AutoDock Vina databases. Results. First, 266 MEMP pathway-related genes that exhibited aberrant activity in tumors were identified. Then, 19 MEMP key genes were used to build a prognostic model, which can successfully predict the survival rates of LUAD patients after 1, 3, and 5 years, respectively. The Kaplan-Meier curve showed that patients in the high-risk group had considerably lower survival outcomes than those in the low-risk group. Furthermore, it was discovered that the high-risk group had the majority of activated T cells, while the low-risk group tended to have more other activated immune cells. The majority of immunological checkpoints expressed themselves more strongly in the high-risk group as well. Finally, 11 prospective medication small molecules were obtained from the projected potential therapeutic drugs, with DB0980 being regarded as the most promising of them for the treatment of LUAD. Conclusion. This current study developed reliable prognostic signature, called MEMP score, which provides new guidance for prognostic assessment, immunotherapy, and drug development in LUAD. Thereby, DB0980 appears to be the most likely approach for the treatment of LUAD.
Network Pharmacology and Molecular Docking‐Based Mechanism Study to Reveal Antihypertensive Effect of Gedan Jiangya Decoction
Authors: Liu Hanxing , Mohammed Shadi A. D. , Lu Fang , Chen Pingping , Wang Yu , Liu Shumin
Published: August 2022

Primary hypertension is understood as a disease with diverse etiology, a complicated pathological mechanism, and progressive changes. Gedan Jiangya Decoction (GJD), with the patent publication number CN114246896A, was designed to treat primary hypertension. It contains six botanical drugs; however, the underlying mechanism is uncertain. We utilized network pharmacology to predict the active components, targets, and signaling pathways of GJD in the treatment of primary hypertension. We also investigated the potential molecular mechanism using molecular docking and animal experiments. The Traditional Chinese Medicine System Pharmacology Database and Analysis Platform (TCMSP), the Protein Database (UniProt), and a literature review were used to identify the active components and related targets of GJD’s pharmacological effects. The GeneCards, Online Mendelian Inheritance in Man (OMIM), Therapeutic Target Database (TTD), and DrugBank databases were utilized to identify hypertension‐related targets. Based on a Venn diagram of designed intersection targets, 214 intersection targets were obtained and 35 key targets for the treatment of hypertension were determined using the STRING data platform and Cytoscape software. The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of key targets revealed that the relevant molecular action pathways of GJD in the treatment of hypertension include the Toll‐like receptor, MAPK, PI3K‐Akt, and renin‐angiotensin signaling pathways. A GJD active ingredient‐key target‐pathway connection diagram was created using Cytoscape software, and 11 essential active components were selected. Molecular docking was then used to verify the binding activity of key targets and key active ingredients in GJD to treat primary hypertension. The results of this study indicate that AGTR1, AKT1 with puerarin, EDNRA with tanshinone IIA, MAPK14 with daidzein, MAPK8 with ursolic acid, and CHRM2 with cryptotanshinone had high binding activity to the targets with active components, whereas AGTR1 was selected as target genes verified by our experiment. HPLC was utilized to identify the five active ingredients. Experiments in high‐salt rats demonstrated that GJD might decrease the expression of AGTR1 in the kidney and thoracic aorta while increasing the expression of eNOS by preventing the activation of the renin‐angiotensin pathway, thereby reducing lowering systolic and diastolic blood pressure.
Aurantiamide Acetate Ameliorates Lung Inflammation in Lipopolysaccharide‐Induced Acute Lung Injury in Mice
Authors: Fang Zhengyu , Fang Jie , Gao Chunxiao , Wu Yueguo , Yu Wenying
Published: August 2022

Purpose. Aurantiamide acetate (AA) is a dipeptide derivative with complex pharmacological activities and remarkable effects on preventing and treating various diseases. In the current study, we aimed to investigate whether AA can exert protective effects in a mouse model of ALI induced by LPS. Materials and Methods. In this model, mice were given intranasal LPS for 3 days prior to receiving AA (2.5, 5, and 10 mg/kg) via oral gavage. An assessment of histopathological changes was performed by hematoxylin and eosin (HE). Proinflammatory cytokines were detected in bronchoalveolar lavage fluids (BALFs) by enzyme‐linked immunosorbent assays (ELISAs). The effects of AA on protein expression of NF‐κB and PI3K/AKT signaling pathways were determined by Western blot. In addition, lung wet/dry (W/D) weight ratio, myeloperoxidase (MPO) activity, cell counts, and protein content were also measured. Results. According to results, AA pretreatment significantly reduced lung pathological changes, W/D ratio, MPO activity, and protein content. Additionally, AA resulted in a significant reduction in the number of total cells, neutrophils, and proinflammatory cytokines in the BALF after LPS stimulation. The subsequent study revealed that pretreatment with AA dose dependently suppressed LPS‐induced activation of NF‐κB as well as PI3K/AKT phosphorylation. Conclusion. The results indicated that the AA had a protective effect on LPS‐induced ALI in mice and could be a potential drug for ALI.
Establishment of FK506‐Enriched PLGA Nanomaterial Neural Conduit Produced by Electrospinning for the Repair of Long‐Distance Peripheral Nerve Injury
Authors: Xu Ting-Min , Chu Hong-Yu , Li Ming , Talifu Zuliyaer , Ke Han , Pan Yun-Zhu , Xu Xin , Wang Yan-hua , Guo Wei , Wang Chuan-Lin , Gao Feng , Li Jian-Jun
Published: August 2022

Peripheral nerve injury (PNI) is a serious complication of trauma. Autologous nerve transplantation is the gold standard for the treatment of long‐distance peripheral nerve defects, but is often limited by insufficient donor sites, postoperative pain, and paresthesia at the donor site. Peripheral nerve tissue engineering has led to the development of neural conduits to replace autologous nerve grafts. This study aimed to evaluate a new type of electrospun nanomaterial neural conduit, enriched with tacrolimus (FK506), which is an FDA‐approved immunosuppressant, for the repair of long‐distance peripheral nerve injuries. Poly (lactic‐co‐glycolic acid) (PLGA) nanofibrous films, with FK506, were prepared by electrostatic spinning and rolled into hollow cylindrical nerve vessels with an inner diameter of 1 mm and length of 15 mm. Material characterization, mechanical testing, degradation, drug release, cytotoxicity, cell proliferation, and migration assays were performed in vitro. Long‐distance sciatic nerve injuries in rats were repaired in vivo using electrospun nerve conduit bridging, and nerve regeneration and muscle and motor function recovery were evaluated by gait analysis, electrophysiology, and neuromuscular histology. Compared to PLGA, the PLGA/FK506 nanomaterial neural conduit showed little change in morphology, mechanical properties, and chemical structure. In vitro, PLGA/FK506 showed lower cytotoxicity and better biocompatibility and effectively promoted the proliferation, adhesion, and migration of Schwann cells. In vivo, PLGA/FK506 had a better effect on sciatic nerve index, compound muscle action potential intensity and delay time, and nerve regeneration quality 12 weeks post‐transplantation, effectively promoting long‐distance defect sciatic nerve regeneration and functional recovery in rats. FK506‐enriched PLGA nanomaterial neural conduits offer an effective method for repairing long‐distance peripheral nerve injury and have potential clinical applications.
Machine Learning-Devised Immune-Related lncRNA Signature Panel Predicts the Prognosis and Immune Landscape in Breast Cancer Novel IRLP Signature in BRCA
Authors: Zhu Jun-Yu , Lyu An-Qi , Wang Zhang-Ting , Chan Wai-Yee , Qin Tao , Miu Kai-Kei , Yao He-Rui
Published: August 2022

Long noncoding RNAs (lncRNAs) actively participate in breast cancer (BRCA) tumorigenesis via epigenetic mechanisms. Our study identified immune-related lncRNA (irlncRNA) pairs and compiled them into a set of noncoding gene signatures able to stratify subtypes of BRCA associated with variable degrees of survival and immune cell infiltration. A 40 immune-related lncRNA pair (IRLP) signature including 43 irlncRNAs was built, with high sensitivity and specificity for the prediction of survival in different molecular subtypes of BRCA. Results demonstrated that the low-risk group showed a significantly longer survival rate, and this novel IRLP signature was highly associated with survival status, T stage, metastatic disease, and overall stage in BRCA. Immune infiltrating analyses found that the low-risk group has a lower expression level of macrophage M2 and a higher expression level of immunosuppressed biomarkers than the high-risk group. DEirlncRNAs were further proven to be significantly related to the MAPK signaling, Jak-STAT signaling, and ErbB signaling pathways in BRCA. In conclusion, the 40 IRLP signature showed a promising clinical prediction value in the prognosis of different molecular subtypes and immunotherapy response in BRCA, and the underlying mechanism for these IRLPs warrants further investigations.
Evaluation Model of Highway Reconstruction and Expansion Scheme Based on Multiple Attribute Decision Making
Authors: Pan Xinhao , Xu Man , Jia Jie , Xia Yifeng , Chen Qian
Published: August 2022

The renovation and expansion of highway is a technical, comprehensive, and complex work, and the determination of its optimal scheme requires the consideration of multiple factors. In the process of highway construction, road engineers attempt to select an optimal scheme with the aim of saving cost, reducing construction difficulties, and protecting environment. It is difficult to assess because of the large number of attribute indices and the diversity of data distribution. In order to scientifically evaluate the comprehensive benefits of highway reconstruction and extension (HRE) schemes, an evaluation model of HRE scheme based on multiple attribute decision making (MADM) was established. This paper constructed the evaluation index system of HRE based on the four aspects of technology, economy, environmental impact, and landscape. This paper has made two major improvements. First, a method was proposed to determine the weight of evaluation index by coupling fuzzy analytic hierarchy process (FAHP) with difference driven principle (DDP). Then, technique for order preference by similarity to an ideal solution (TOPSIS) method was optimized by grey relational analysis (GRA) method. Finally, the MADA evaluation model is utilized to analyze the ranking of optimal scheme selection problem by relative closeness as a decision index. The results showed that the subjective intention of decision makers was considered and also fully the objective information of data itself was fully mined. The optimal scheme was scheme 3 through the analysis of five HRE schemes. This model highlighted the differences among the schemes and also avoided the problem of excessive differences. The results were consistent with the actual situation, verifying the feasibility and practicability of the model.
Video Analysis in Sports by Lightweight Object Detection Network under the Background of Sports Industry Development
Authors: Zheng Yifei , Zhang Hongling
Published: August 2022

This study uses the video image information in sports video image analysis to realize scientific sports training. In recent years, game video image analysis has referenced athletes’ sports training. The sports video analysis is a widely used and effective method. First, the you only look once (YOLO) method is explored in lightweight object detection. Second, a sports motion analysis system based on the YOLO-OSA (you only look once-one-shot aggregation) target detection network is built based on the dense convolutional network (DenseNet) target detection network established by the one-shot aggregation (OSA) connection. Finally, object detection evaluation principles are used to analyze network performance and object detection in sports video. The results show that the more obvious the target feature, the larger the size, and the more motion information contained in the sports category feature, the more obvious the effect of the detected target. The higher the resolution of the sports video image, the higher the model detection accuracy of the YOLO-OSA target detection network, and the richer the visual video information. In sports video analysis, video images of the appropriate resolution are fed into the system. The YOLO-OSA network achieved 21.70% precision and 54.90% recall. In general, the YOLO-OSA network has certain pertinence for sports video image analysis, and it improves the detection speed of video analysis. The research and analysis of video in sports under the lightweight target detection network have certain reference significance.
Potential Use of Anti-Cancer Drugs for Treatment of Preeclampsia by Targeting the miRNA-IGF1R-PI3K-AKT Axis
Authors: Li Jieyan , Hou Lei , Zhao Rong , Zou Liying
Published: August 2022

Aim. Preeclampsia (PE) belongs to hypertensive disorders of pregnancy (HDP), which can cause maternal death worldwide. This study aimed to identify the miRNA-mRNA-associated ceRNA network and to find new treatment schedules for PE. Methods. 4 microarray datasets were downloaded from the Gene Expression Omnibus database. We obtained 1737 differentially expressed mRNAs (865 upregulated and 872 downregulated) and 148 differentially expressed miRNAs (76 upregulated and 72 downregulated) from the placenta tissues of PE, respectively. Functional enrichment analyses of DEmRNAs were performed. The regulatory relationship between DEmiRNAs and DEmRNA was predicted via related databases. An miRNA-mRNA regulatory network was constructed. Results. hsa-let-7c and IGF1R were identified as potential regulators for PE, and function enrichment analysis showed that the PI3K-Akt signaling pathway was closely related. Therefore, ceRNAs might regulate the PI3K-Akt signaling pathway via the upregulation of IGF1R by binding to hsa-let-7c, affecting invasion of trophoblast, angiogenesis, and proinflammation in PE. Further study demonstrated that anticancer drugs including the PI3K inhibitor, AKT inhibitor, and IGF-1 inhibitor might be a potential solution for PE treatment. Conclusions. The hsa-let-7c/IGF1R axis might affect the PI3K-Akt signaling pathway which is involved in the pathogenesis of PE, and inhibitors targeting this pathway might be used for PE treatment.
Inspecting Decorative Ceramic Defects by Fusing Convolutional Neural Network and Image Recognition
Authors: Jin Kaiyan , Wang Chunbin
Published: August 2022

The intelligent inspection of ceramic decorative defects is one of the hot research at present. This work aims to improve the defect inspection automation of finished decorative ceramic workpieces. First, it introduces the multi-target detection algorithm and compares the performance of different network models on the public data set. Second, the initial images are collected on the spot. The initial pictures are easy to produce noise in actual deployment, affecting the image quality. Therefore, image preprocessing is performed for the initial images, and a median filtering method is used to calculate the denoising. Finally, the original You Only Look Once version 3 network model is realized. Based on this, the decorative ceramic-oriented Automated Surface Defect Inspection model is proposed. Then, decorative ceramic defect images are inputted for model training. The experimental conclusions are deeply studied and analyzed. The results show that the proposed decorative ceramic-oriented Automated Surface Defect Inspection model based on Deep Learning technology has good feature extraction and inspection ability. The detection accuracy is 94.90% on the test set, and the detection speed reaches 25 frames per second. Compared with the traditional manual inspection method, the proposed model greatly improves the inspection effect and can meet the on-site inspection requirements of surface defects of decorative ceramics under complex backgrounds. It is of great significance to improve the quality inspection efficiency and economic benefits of China’s decorative ceramics industry.
Water-Saving Benefit Model Analysis of Plain Reservoirs in Arid Areas Based on Nonlinear Data Prediction under Floating Ball Cover
Authors: Wang Haitao , Yan Xinjun , Shi Kebin , Xu Siyuan
Published: August 2022

In order to reduce the ineffective evaporation of plain reservoirs in arid areas, strengthen the effective utilization of water resources, and explore effective water-saving benefit models. Research methods: Field tests were carried out with antievaporation floating balls with different coverage rates, and the water-saving rate and economic benefits under floating ball coverage were analyzed. By analyzing the frequency of different wind speeds, daily evaporation under different coverage rates, monthly evaporation inhibition rates under different coverage rates, and the cost of materials used were analyzed. The results showed that (1) during the test period, the total evaporation from the water surface of different cover groups was 149.5 mm, 122.2 mm, 100.1 mm, 81.1 mm, and 63.1 mm, respectively, and the evaporation inhibition rates of different cover groups were 18.4%, 30.8%, 43.4%, and 58.6%, respectively. (2) Comprehensive consideration of the preliminary input and output ratio of the latter determine when the float coverage rate of 50% is the optimal coverage rate, the annual water savings of 5421.86

m

3

, the annual increase in production value of 87,700 yuan, and the float in the reservoir site operation for 5 years to reach the recovery period and start to profit. (3) Based on the analysis of the economic indicators of laying floating balls in a large area of the reservoir and the calculation of the sales income and total investment, the results show that the total investment is a sensitive factor, and the project has a strong risk resistance ability. Therefore, the floating ball covering method to inhibit the ineffective evaporation of water surfaces is practical and feasible in terms of reservoir water-saving and economic benefits.
A Variable Radius Side Window Direct SLAM Method Based on Semantic Information
Authors: Chen Yan , Ni Jianjun , Mutabazi Emmanuel , Cao Weidong , Yang Simon X.
Published: August 2022

Simultaneous Localization and Mapping (SLAM) is a challenging and key issue in the mobile robotic fields. In terms of the visual SLAM problem, the direct methods are more suitable for more expansive scenes with many repetitive features or less texture in contrast with the feature-based methods. However, the robustness of the direct methods is weaker than that of the feature-based methods. To deal with this problem, an improved direct sparse odometry with loop closure (LDSO) is proposed, where the performance of the SLAM system under the influence of different imaging disturbances of the camera is focused on. In the proposed method, a method based on the side window strategy is proposed for preprocessing the input images with a multilayer stacked pixel blender. Then, a variable radius side window strategy based on semantic information is proposed to reduce the weight of selected points on semistatic objects, which can reduce the computation and improve the accuracy of the SLAM system based on the direct method. Various experiments are conducted on the KITTI dataset and TUM RGB-D dataset to test the performance of the proposed method under different camera imaging disturbances. The quantitative and qualitative evaluations show that the proposed method has better robustness than the state-of-the-art direct methods in the literature. Finally, a real-world experiment is conducted, and the results prove the effectiveness of the proposed method.
Application of Multimedia Tilt Photogrammetry Technology Based on Unmanned Aerial Vehicle in Geological Survey
Authors: Li Wenyu
Published: August 2022

In order to better investigate the geological research, a tilt photogrammetry technology based on the unmanned aerial vehicle is proposed. This paper makes use of UAV tilt photogrammetry technology to make geological macroscopic analysis and establishes 3d color digital ground model, forming a set of technical methods for geological survey assisted by UAV. The experimental results show that the coordinate calculation is significantly improved, and the root mean square error of plane coordinates reaches 0.2 m, which can meet the requirements of later cartography and spatial measurement. The feasibility and efficiency of carrying out a geological survey based on the unmanned aerial vehicle are verified by the practical application in landslide hazard geological survey. It is proved that DEM and DOM data obtained based on oblique photogrammetry data can form various thematic maps by superimposing them with vector GIS data, which will provide a basic data model for subsequent engineering investigation, site management, and image display.