bluuebunny/crossref_metadata_2025 huggingface dataset:
Transcriptome-wide analyses of adipose tissue in outbred rats reveal genetic regulatory mechanisms relevant for human obesity
Authors: Crouse Wesley L. , Das Swapan K. , Le Thu , Keele Gregory , Holl Katie , Seshie Osborne , Craddock Ann L. , Sharma Neeraj K. , Comeau Mary E. , Langefeld Carl D. , Hawkins Gregory A. , Mott Richard , Valdar William , Solberg Woods Leah C.
Published: April 2022

Transcriptomic analysis in metabolically active tissues allows a systems genetics approach to identify causal genes and networks involved in metabolic disease. Outbred heterogeneous stock (HS) rats are used for genetic mapping of complex traits, but to-date, a systems genetics analysis of metabolic tissues has not been done. We investigated whether adiposity-associated genes and gene coexpression networks in outbred heterogeneous stock (HS) rats overlap those found in humans. We analyzed RNAseq data from adipose tissue of 415 male HS rats, correlated these transcripts with body weight (BW) and compared transcriptome signatures to two human cohorts: the “African American Genetics of Metabolism and Expression” and “Metabolic Syndrome in Men.” We used weighted gene coexpression network analysis to identify adiposity-associated gene networks and mediation analysis to identify genes under genetic control whose expression drives adiposity. We identified 554 orthologous “consensus genes” whose expression correlates with BW in the rat and with body mass index (BMI) in both human cohorts. Consensus genes fell within eight coexpressed networks and were enriched for genes involved in immune system function, cell growth, extracellular matrix organization, and lipid metabolic processes. We identified 19 consensus genes for which genetic variation may influence BW via their expression, including those involved in lipolysis (e.g., Hcar1), inflammation (e.g., Rgs1), adipogenesis (e.g., Tmem120b), or no previously known role in obesity (e.g., St14 and Ms4a6a). Strong concordance between HS rat and human BW/BMI associated transcripts demonstrates translational utility of the rat model, while identification of novel genes expands our knowledge of the genetics underlying obesity.
Mitochondrial quality control in health and in Parkinson’s disease
Authors: Eldeeb Mohamed A. , Thomas Rhalena A. , Ragheb Mohamed A. , Fallahi Armaan , Fon Edward A.
Published: April 2022

As a central hub for cellular metabolism and intracellular signaling, the mitochondrion is a pivotal organelle, dysfunction of which has been linked to several human diseases including neurodegenerative disorders and in particular Parkinson’s disease. An inherent challenge that mitochondria face is the continuous exposure to diverse stresses that increase their likelihood of dysregulation. In response, eukaryotic cells have evolved sophisticated quality control mechanisms to monitor, identify, repair, and/or eliminate abnormal or misfolded proteins within the mitochondrion and/or the dysfunctional mitochondrion itself. Chaperones identify unstable or otherwise abnormal conformations in mitochondrial proteins and can promote their refolding to recover their correct conformation and stability. However, if repair is not possible, the abnormal protein is selectively degraded to prevent potentially damaging interactions with other proteins or its oligomerization into toxic multimeric complexes. The autophagic-lysosomal system and the ubiquitin-proteasome system mediate the selective and targeted degradation of such abnormal or misfolded protein species. Mitophagy (a specific kind of autophagy) mediates the selective elimination of dysfunctional mitochondria, to prevent the deleterious effects of the dysfunctional organelles within the cell. Despite our increasing understanding of the molecular responses toward dysfunctional mitochondria, many key aspects remain relatively poorly understood. Here, we review the emerging mechanisms of mitochondrial quality control including quality control strategies coupled to mitochondrial import mechanisms. In addition, we review the molecular mechanisms regulating mitophagy, with an emphasis on the regulation of PINK1/Parkin-mediated mitophagy in cellular physiology and in the context of Parkinson’s disease cell biology.
Dynamic Interdependence of Systematic Risks in Emerging Markets Economies: A Recursive‐Based Frequency‐Domain Approach
Authors: Asafo-Adjei Emmanuel , Adam Anokye M. , Adu-Asare Idun Anthony , Ametepi Peace Y.
Published: April 2022

We examine the interdependence of systematic risk in twenty emerging market economies. The interdependence structures are performed for subregional and regional categorizations of emerging markets, which have demonstrated financial openness over the years. Hence, the Kalman filter‐based wavelet approach is adopted to execute the purpose of this study. The outcome from the contemporaneous correlations demonstrates that the degree of comovements among the equity betas varies. Moreover, from the wavelet multiple cross‐correlations, Qatar, Brazil, Indonesia, and Czech Republic led for most timescales. Conversely, the equity betas of United Arab Emirates (Africa and Middle East), Argentina (Americas), China (Asia), and Russia (Europe) exhibit low degrees of integration with other systematic risk returns from each subregion. The low correlations, especially in the short term, of these countries within their respective regions signify less risk transmission and should be included in a portfolio of assets in determining investment risks. Generally, we find significant integration among systematic risks in emerging markets in the long term. We institute that the nature of interdependence in systematic risk has been heterogeneous across time. Accordingly, the equity betas increase with scale for most subregions and the emerging markets as a whole, implying that market interconnections heighten as the investment horizon is prolonged, revealing saturated markets with shocks. It is recommended that prudent liquidity policies are implemented to augment resilience to systematic risks susceptibilities in the long term. The findings present pertinent implications for portfolio diversification, policy decisions, investing risk, and risk management schemes.
High-Sensitivity Multiband Detection Based on the Local Enhancement Effect of an Electric Field at Terahertz Frequency
Authors: Xiong Zhonggang , Shang Liping , Deng Hu , Xiong Liang , Chen Linyu , Guo Jin , Li Guilin
Published: April 2022

The terahertz detection sensitivity interaction with other substances has received extensive attention and remains challenging due to the loss of terahertz waves. Herein, a terahertz, multiband sensor with high sensitivity based on the local enhancement effect of an electric field at terahertz frequency is proposed. The designed terahertz sensor is based on a common metamaterial sandwich absorber of electromagnetic energy that only employs an asymmetric metallic strip, which produces three resonance peaks with an absorption coefficient of greater than 95% in the 0.2-1.5 THz range and a maximum

Q

-factor of 46 at 1.397. Based on the principle of impedance matching, the high absorption of electromagnetic wave energy is reasonably analyzed. Furthermore, the influence of the top metal structure on the absorptivity and resonance frequency is analyzed by simulation optimization, and the optimum structural parameters are obtained. In addition, the influence of the refractive index (RI) change of the sample and dielectric layer on the resonance characteristics of the sensor is analyzed. When the thickness of the surface sample of the terahertz sensor metamaterial-based absorber is changed so that the RI changes in 1-2, the RI sensitivity increases up to 208 GHz/RIU, which can be used as an RI sensor. Furthermore, the influence of the sensor sensitivity and reflection coefficient on the thickness parameters of the sample covered by the sensor surface is analyzed, and the optimal sample thickness is 6 μm. The influence of the incident angle of the THz wave on the detection performance in the TM polarization mode is analyzed, and it is determined that the change in the incident angle in the range of 0-40 degrees has minimal influence on the resonance peak and absorption rate of multiband detection. Therefore, we suggest that our proposed sensor has considerable potential in biomedicine and trace detection applications.
Magnetic Matching-Aided Indoor Localization System Based on a Waist-Mounted Self-Contained Sensor Array
Authors: Li Hu , Liu Yu , Zhang Liqiang , Wang Han
Published: April 2022

This paper presents a magnetic matching-aided indoor localization system based on a waist-mounted self-contained sensor array. Our purpose is to localize and track the elderly in nursing homes through the proposed wearable device to ensure their safety. The device consists of a low-cost 9-axis self-contained sensor array, a microcontroller, and a WiFi transmission module. This system uses the step length and heading-based pedestrian dead reckoning (PDR) framework as the backbone to estimate the user’s position using the averaged inertial data from the sensor array. A magnetic fingerprint matching (MFM) algorithm is introduced to constrain the drift of the PDR system. Meanwhile, we construct a single-step-based hybrid magnetic fingerprint model to improve the low discernibility of the magnetic field. Finally, we propose an augmented particle filter to fuse the PDR and the MFM algorithms to enhance the system performance further. Experimental results show that 95% of the positioning error after fusion is about 1.47 m, which is 99.3% higher than that of PDR, and the average positioning error after fusion is 0.55 m, which is 61.3% higher than that of PDR. Experimental results have successfully validated the effectiveness and high performance of the proposed magnetic matching-aided wearable indoor localization system.
An Exact Algorithm Based on the Kuhn–Tucker Conditions for Solving Linear Generalized Semi‐Infinite Programming Problems
Authors: Barragán Abraham , Camacho-Vallejo José-Fernando
Published: April 2022

Optimization problems containing a finite number of variables and an infinite number of constraints are called semi‐infinite programming problems. Under certain conditions, a class of these problems can be represented as bi‐level programming problems. Bi‐level problems are a particular class of optimization problems, in which there is another optimization problem embedded in one of the constraints. We reformulate a semi‐infinite problem into a bi‐level problem and then into a single‐level nonlinear one by using the Kuhn–Tucker optimality conditions. The resulting reformulation allows us to employ a branch and bound scheme to optimally solve the problem. Computational experimentation over well‐known instances shows the effectiveness of the developed method concluding that it is able to effectively solve linear semi‐infinite programming problems. Additionally, some linear bi‐level problems from literature are used to validate the robustness of the proposed algorithm.
Semantic Understandings for Aerial Images via Multigrained Feature Grouping
Authors: Lin Dan , Chen Zhikui
Published: April 2022

Aerial images play a key role in remote sensing as they can provide high-quality surface object information for continuous communication services. With advances in UAV-aided data collection technologies, the volume of aerial images has been greatly promoted. To this end, semantic understandings for these images can significantly improve the quality of service for smart devices. Recently, the multilabel aerial image classification (MAIC) task has been widely researched in academics and applied in industries. However, existing MAIC methods suffer from suboptimal performance as objects are located in different sizes and scales. To address these issues, we propose a novel multigrained semantic grouping model for aerial image learning, named MSGM. First, image features presented by the backbone are sent to spatial pyramid convolutional layers which extract the instances in a parallel manner. Then, three grouping mechanisms are designed to integrate the instances from the pyramid framework. In addition, MSGM builds a concept graph to represent the label relationship. MSGM resorts to the graph convolutional network to learn the concept graph directly. We extensively evaluate MSGM on two benchmark aerial image datasets, the commonly used UCM dataset, and the high-resolution DFC15 dataset. Quantitative and qualitative results support the effectiveness of the proposed MSGM.
Deciphering a Novel Necroptosis-Related miRNA Signature for Predicting the Prognosis of Clear Cell Renal Carcinoma
Authors: Bao Jia-hao , Li Jiang-bo , Lin Han-sen , Zhang Wen-jin , Guo Bing-yan , Li Jun-jie , Fu Liang-min , Sun Yang-peng
Published: April 2022

Clear cell renal cell carcinoma (ccRCC) is the most common histological and devastating subtype of renal cell carcinoma. Necroptosis is a form of programmed cell death that causes prominent inflammatory responses. miRNAs play a significant role in cancer progression through necroptosis. However, the prognostic value of necroptosis-related miRNAs remains ambiguous. In this study, 39 necroptosis-related miRNAs (NRMs) were extracted and 17 differentially expressed NRMs between normal and tumor samples were identified using data form The Cancer Genome Atlas (TCGA). After applying univariate Cox proportional hazard regression analysis and LASSO Cox regression model, six necroptosis-related miRNA signatures were identified in the training cohort and their expression levels were verified by qRT-PCR. Using the expression levels of these miRNAs, all patients were divided into the high- and low-risk groups. Patients in the high-risk group showed poor overall survival (

P
<
0.0001

). Time-dependent ROC curves confirmed the good performance of our signature. The results were verified in the testing cohort and the entire TCGA cohort. Univariate and multivariate Cox regression models demonstrated that the risk score was an independent prognostic factor. Additionally, a predictive nomogram with good performance was constructed to enhance the implementation of the constructed signature in a clinical setting. We then employed miRBD, miRTarBase, and TargetScan to predict the target genes of six necroptosis-related miRNAs. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses indicated that 392 potential target genes were enriched in cell proliferation-related biological processes. Six miRNAs and 59 differentially expressed target genes were used to construct an miRNA–mRNA interaction network, and 11 hub genes were selected for survival and tumor infiltration analysis. Drug sensitivity analysis revealed potential drugs that may contribute to cancer management. Hence, necroptosis-related genes play an important role in cancer biology. We developed, for the first time, a necroptosis-related miRNA signature to predict ccRCC prognosis.
Contribution for the Summation Formulas for the Generalized Hypergeometric Series 6F5(−1)
Authors: Jayarama Prathima , Lim Dongkyu , Rathie Arjun Kumar
Published: April 2022

In this paper, our aim is to provide as many as one hundred and ninety‐two summation formulas for the generalized hypergeometric series 6F5(−1) in terms of gamma functions. For this, we have established eight theorems containing general results. This is achieved by means of applying generalized Watson’s and Dixon’s summation formulas obtained earlier by Lavoie et al. into a known transformation formula available in the literature. Results obtained earlier by Zhao follows special cases of our main findings.
Antioxidative Stress and Antiapoptosis Effect of Chitosan Nanoparticles to Protect Cardiac Cell Damage on Streptozotocin-Induced Diabetic Rat
Authors: Wardani Giftania , Nugraha Jusak , Mustafa Mohd. Rais , Kurnijasanti Rochmah , Sudjarwo Sri Agus
Published: April 2022

The antioxidant can inhibit oxidative stress and apoptosis, which has a role in an important mechanism on diabetic-induced cardiac cell damage. The research goal was to prove the antioxidative stress and antiapoptosis effect of chitosan nanoparticles as a cardioprotector in streptozotocin-induced diabetic rats. Scanning electron microscope (SEM) and dynamic light scattering (DLS) characterize the chitosan nanoparticles. This research is a laboratory experiment which consists of the control group (rats were given distilled water), the streptozotocin group (rats were injected streptozotocin at dose of 55 mg/kg BW i.p), and the chitosan nanoparticle group (rats were given streptozotocin at dose 55 mg/kg BW i.p, and then given chitosan nanoparticles at dose 75 mg/kg BW, 150 mg/kg BW, and 300 mg/kg BW peroral). Creatine kinase-myoglobin (CK-MB) and lactate dehydrogenase (LDH) were measured from the blood sample. Malondialdehyde (MDA), superoxide dismutase (SOD), and glutathione peroxidase (GPx) from cardiac tissue were examined by ELISA; nuclear factor erythroid 2-related factor 2 (Nrf2) was evaluated by western blotting; B-cell lymphoma 2 (Bcl-2) and Caspase-3 expression were investigated by immunohistochemical staining and also were evaluated histological preparation by hematoxylin & eosin (H&E) staining. The chitosan nanoparticles have a rough surface and an irregular shape. Its size is

247.3
±
38.1
 
μ
m

. Streptozotocin injection significantly increased the levels of CK-MB, LDH, MDA, and expression of caspase-3. In contrast, the levels of SOD, GPx, Nrf2, and expression of Bcl-2 decreased as compared with the control group (

p
<
0.05

). This is accompanied by the loss of normal cardiac cell structure and necrosis. The administration of chitosan nanoparticles significantly reduced levels of CK-MB, LDH, MDA, and expression of Caspase-3. However, the levels of SOD, GPx, Nrf2, and expression of Bcl-2 increased as compared with the streptozotocin group (

p
<
0.05

). And also, chitosan nanoparticles inhibited cell necrosis in diabetic rats. This study suggests that the administration of chitosan nanoparticles can protect cardiac cell damage in diabetic rats through antioxidative stress by decreasing ROS and increasing Nrf2 expression, level of SOD, and GPx and through antiapoptosis by increasing expression of Bcl-2 and decreasing expression of Caspase-3.
Internal Validation of the Predictive Performance of Models Based on Three ED and ICU Scoring Systems to Predict Inhospital Mortality for Intensive Care Patients Referred from the Emergency Department
Authors: Rahmatinejad Zahra , Hoseini Benyamin , Rahmatinejad Fatemeh , Abu-Hanna Ameen , Bergquist Robert , Pourmand Ali , Miri MirMohammad , Eslami Saeid
Published: April 2022

Background.A variety of scoring systems have been introduced for use in both the emergency department (ED) such as WPS, REMS, and MEWS and the intensive care unit (ICU) such as APACHE II, SAPS II, and SOFA for risk stratification and mortality prediction. However, the performance of these models in the ICU remains unclear and we aimed to evaluate and compare their performance in the ICU. Methods. This multicenter retrospective cohort study was conducted on severely ill patients admitted to the ICU directly from the ED in seven tertiary hospitals in Iran from August 2018 to August 2020. We evaluated all models in terms of discrimination (AUROC), the balance between positive predictive value and sensitivity (AUPRC), calibration (Hosmer‐Lemeshow test and calibration plots), and overall performance using the Brier score (BS). The endpoint was considered inhospital mortality. Results. Among the 3,455 patients included in the study, 54.4% of individuals were male (N = 1,879) and 26.5% deceased (N = 916). The BS for the WPS, REMS, MEWS, APACHE II, SAPS II, and SOFA were 0.178, 0.165, 0.183, 0.157, 0.170, and 0.182, respectively. The AUROC of these models were 0.728 (0.71‐0.75), 0.761 (0.74‐0.78), 0.682 (0.66‐0.70), 0.810 (0.79‐0.83), 0.767 (0.75‐0.79), and 0.785 (0.77‐0.80), respectively. The AUPRC was 0.517 (0.50‐0.53) for WPS, 0.547 (0.53‐0.56) for REMS, 0.445 (0.42‐0.46) for MEWS, 0.630 (0.61‐0.65) for APACHE II, 0.559 (0.54‐0.58) for SAPS II, and 0.564 (0.54‐0.57) for SOFA. All models except the MEWS and SOFA had good calibration. The most accurate model belonged to APACHE II with lowest BS. Conclusion. The APACHE II outperformed all the ED and ICU models and was found to be the most appropriate model in predicting inhospital mortality of patients in the ICU in terms of discrimination, calibration, and accuracy of predicted probability. Except for MEWS, the rest of the models had fair discrimination and partially good calibration. Interestingly, although the REMS is less complicated than the SAPS II, both models exhibited similar performance. Clinicians can utilize the REMS as part of a larger clinical assessment to manage patients more effectively.
Dynamics of Multimodal Families of m‐Modal Maps
Authors: González-Salas S. , Cassal-Quiroga B. B. , Tuxpan J. , Campos E.
Published: April 2022

In this work, we introduce families of multimodal maps based on logistic map, i.e., families of m‐modal maps are defined on an interval I ⊂ ℝ, which is partitioned into non‐uniform subdomains, with m ∈ ℕ. Because the subdomains of the partition are not uniform, each subdomain contains a unimodal map, given by the logistic map, that can have different heights. Therefore, we give the necessary and sufficient conditions for these modal maps present a multimodal family of m‐modal maps, i.e., a bifurcation parameter can set a unimodal map, a bimodal map, up to a m‐modal map. Some numerical examples are given according to the developed theory. Some numerical examples are given in accordance with the developed theory.
Intelligent Spraying Water Based on the Internet of Orchard Things and Fuzzy PID Algorithms
Authors: Zhang Pingchuan , Wang Sijie , Bai Menglong , Bai Qiaoling , Chen Zhao , Chen Xu , Hu Yanjun , Zhang Jianming , Li Yulin , Hu Xueqian , Shi Yiran , Deng Jiajun
Published: April 2022

During the fruit ripening period, the orchard temperature difference between day and night has a substantial impact on the fruit quality, and it is not easy to be controlled like that of in greenhouse, this paper designed the smart orchard Internet of Things (IoT), through the fuzzy PID (Proportion-Integration-Differentiation) algorithm to control the water spraying to adjust the temperature difference

Δ
T

between day and night in the orchard, intelligently influenced the orchard energy conversion process, and promoted the fruit sugar accumulation. Experiments show that the maximum

Δ
T

can reach 20°C, the intelligent energy regulation based on the IoT has a good effect, and a scheme to intervene the microclimate in farmland (quite different from the greenhouse environment) is provided.
Modeling Intercity CO2 Trading Scenarios in China: Complexity of Urban Networks Integrating Different Spatial Scales
Authors: Li Chongming , Li Na , Zhang Zuo , Zhang Lu , Li Zhi , Liu Yanzhong
Published: April 2022

Today, cities account for the majority of global energy consumption and CO2 emissions. The interaction between cities is critical for regional low‐carbon development. At this time, China has turned to the full opening of the carbon trading market as an important policy tool for achieving its ambitious emission reduction goals. This paper attempts to explore the spatial relationships among cities from the perspective of carbon trading. A “multiscenarios across different spatial scales” analysis framework applied to the allocation and trading of CO2 emission quotas among cities in China is proposed. Based on this framework, the carbon trading networks of 182 cities in China are specifically simulated under four different scenarios, with a comparative analysis of the networks’ complexity made from different perspectives. The results of the study are as follows: firstly, significant spatial network correlations exist between the cities’ carbon trading under each scenario. Secondly, on a national scale, there are more inner connections in carbon trading networks, with stronger correlations and robustness, while the degree of connection of intercity carbon trading is higher overall on a regional scale. Thirdly, on a national scale, no obvious core nodes exist in the network, while core nodes do exist in the overall network and in each region under the regional scale. Fourthly, cities in the central region have the highest core position overall. Finally, based on the research results, practical guidance in using the framework for achieving carbon reduction, promoting economic growth, and balancing regional development, as well as the important inspiration for policy formulation, is further discussed.
Reversal of NADPH Oxidase-Dependent Early Oxidative and Inflammatory Responses in Chronic Obstructive Pulmonary Disease by Puerarin
Authors: Zhang Pan , Zhang Yixuan , Wang Lu , Wang Xinjing , Xu Shiqing , Zhai Zhenguo , Wang Chen , Cai Hua
Published: April 2022

In the present study, we investigated effects of Puerarin on the early oxidative and inflammatory responses in the lung triggered by acute cigarette smoking (ACS). C57BL/6 mice were exposed to ACS for 1 hr in the presence or absence of Puerarin and harvested at 2, 6, and 24 hours. ACS induced significant increases in superoxide production in mouse lungs at 2 and 6 hours; and superoxide production was also elevated in a time and concentration dependent manner in cigarette smoke extract (CSE) stimulated human small airway epithelial cells (HSAECs), which was dose-dependently abrogated by Puerarin. ACS exposure upregulated NOX1, NOX2, and NOX4 protein expression in mouse lungs. Likewise, NOX1 and NOX4 were upregulated in CSE-stimulated HSAECs. These responses were significantly or completely attenuated by Puerarin. ACS induced significant infiltrations of neutrophils and macrophages in mouse lung parenchyma and BAL fluid, which were completely or significantly abrogated by Puerarin, so was the activation of the NF-кB pathway and the upregulation in inflammatory mediators including TNF-α, KC (murine homolog of IL-8), COX-2, IL-6 and MCP-1. Nuclear translocation of p65, IL-8 secretion, and upregulation of COX-2 in CSE stimulated HSAECs were also markedly attenuated by Puerarin. Moreover, ACS or CSE stimulated upregulation in reactive oxygen species (ROS) production and expression of inflammatory mediators were alleviated by ROS scavenger TEMPO in vivo and vitro, with no synergy combining with Puerarin, indicating that the effects of Puerarin are redox-sensitive following activation of NOX. In summary, our data for the first time demonstrate that Puerarin robustly attenuates NOX isoform-dependent ROS production and inflammatory activation in ACS exposed mice and CSE treated HSAECs, indicating that Puerarin might be used as a robust therapeutic agent for early or early stage COPD.
Application of Multisource Big Data Mining Technology in Sports Economic Management Analysis
Authors: Li Qinglan
Published: April 2022

The sports economy also occupies a main part of the national economy, which requires professionals to be able to evaluate the development of the sports economy. The sports industry will generate cumbersome data, which are important for the future development trend of the sports economy. This research will collect a large amount of data from the sports industry, data mining technology, and neural network method that will be used to fully mine and predict the relationship between sports economic data, and it will provide corresponding management references for sports industry companies. Some important statistical parameters will be used to evaluate the feasibility of data mining techniques and neural network methods in sports economic management. The research results show that the error of data mining technology in the classification of sports economy is within 2.54%, and the prediction error of the neural network method is also within 3.2%. This shows that the data mining technology proposed in this study is feasible for classification and prediction application in sports economic management. Once the forecast data of the sports economy are output through the output layer, the sports economy managers can rely on these data to manage and adjust the relevant factors of the sports economy.
Functional Analysis of Bronchopulmonary Dysplasia-Related Neuropeptides in Preterm Infants and miRNA-Based Diagnostic Model Construction
Authors: Zhang Yue , Kong Xiangyong , Zhang Jie , Wang Xu
Published: April 2022

Background. Bronchopulmonary dysplasia (BPD) has a high mortality rate. This study was aimed at identifying and analysing the risk factors associated with BPD using bioinformatic and mechanical analyses and establishing a predictive model to assess the risk of BPD in preterm infants. Methods. We identified differentially expressed RNAs via the intersection of miRNAs between datasets. Online analysis tools were used to predict genes targeted by differentially expressed miRNAs (DEmiRNAs) and to generate and visualise competing endogenous RNA (ceRNA) coexpression networks. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were subsequently performed on the DEmiRNAs. In addition, an intersection analysis was performed on mRNA and neuropeptide-related genes in the ceRNA network. DEmiRNAs associated with BPD and those involved in ceRNA networks were used to establish a diagnostic prediction model. The GSE108604 dataset was used as a validation set to verify the model. Results. A total of 26 DEmiRNAs were identified from the tracheal aspirates (TAs) of patients with BPD and healthy controls. In addition, a total of 1076 DEmRNAs were obtained from the GSE8586 dataset. Functional enrichment analysis of DEmRNAs revealed an abnormal reduction in mitochondrial-related activity and cellular responses to oxidative stress in patients with BPD. The neuropeptide-related genes OPRL1 and NPPA were found to be upregulated in BPD samples. Eventually, hsa-miR-1258, hsa-miR-298, hsa-miR-483-3p, and hsa-miR-769-5p were screened out and used to establish the prediction model. Calibration curves and detrended correspondence analysis (DCA) revealed that the model had good clinical applicability. Conclusions. The prediction model provided a simple method for individualised assessment, early diagnosis, and prevention of BPD risk in preterm infants.
Study on the Migration Law of Overlying Strata on the Working Surface of Large Mining Height in Y.C.W Coal Mine
Authors: Liu Hongtao , Huo Tianhong , Liu Yang , Han Zhou , Han Zijun , Liang Wanliang
Published: April 2022

The migration law of overlying strata on working face is of great significance for safe mining of working face. In this paper, theoretical calculation, numerical simulation, and similar simulation are used to study the distribution characteristics, migration, and fracture law of key strata in the overlying strata of 130204 working face of Y.C.W coal mine and the relationship between the development height of water flowing fractured zone and the spatial position of weak aquifer. The theoretical calculation results show that there are “one main two sub” key strata in the overlying strata of 130204 working face, which play an important role in controlling rock movement. Numerical simulation and similar simulation results show that the first weighting step distance of the direct roof of 130204 working face is about 30-40 m. The initial weighting interval of the basic roof of the working face is about 70-80 m, and the periodic weighting interval is about 23.5-25 m. After the first weighting and multiple periodic weighting of the basic roof of the working face, the first subcritical layer is located in the caving zone, the second subcritical layer is located in the fracture zone, and the main key layer is finally located in the bending subsidence zone. The final height of the caving zone of the overlying strata is about 24 m, and the height of the water flowing fractured zone is about 130 m. Since the water-conducting fractured zone is connected and passes through the second subcritical layer with weak water-bearing property, it is possible for the water permeability accident of the working face. Therefore, in order to ensure the safety of the working face, the water should be detected and released in advance during the mining of the working face.
On Acyclic Structures with Greatest First Gourava Invariant
Authors: Imtiaz Mariam , Naseem Maria , Arshad Misbah , Kanwal Salma , Liaqat Maria
Published: April 2022

Let

ξ

be a simple connected graph. The first Gourava index of graph

ξ

is defined as

G

O

1

ξ

=

∑

μ
η
∈
E

ξ

d

μ

+
d

η

+
d

μ

d

η

, where

d

μ

indicates the degree of vertex

μ

. In this paper, we will find the upper bound of

G

O

1

ξ

for trees of given diameter, order, size, and pendent nodes, by using some graph transformations. We will find the extremal trees and also present an ordering of these trees having this index in decreasing order.
Onpz–Laplacian System Involving Critical Nonlinearities
Authors: Aberqi Ahmed , Bennouna Jaouad , Benslimane Omar , Ragusa Maria Alessandra
Published: April 2022

In this paper, we deal with the existence of at least two nonnegative nontrivial solutions to apz–Laplacian system involving critical nonlinearity in the context of Sobolev spaces with variable exponents on complete manifolds. We have established our main results by exploring both Nehari’s method and doing a refined analysis on the associated fiber map and some variational techniques.
An Intelligent Supervision for Supply Chain Finance and Logistics Based on Internet of Things
Authors: Bai Wei , Liu Yongbin , Wang Jingjie
Published: April 2022

Supply chain finance and logistics activities are developing rapidly. In the economic activities of the tripartite cooperation between financial institutions, logistics enterprises, and loan enterprises, the goods will enter the logistics and supervision links of pledged goods immediately after they are postponed. It is proposed to integrate computer network communication technologies such as the Internet of Things with supply chain finance and logistics supervision to strengthen the information interaction between suppliers, which is widely used in supply chain activities to help realize the Internet finance. An intelligent supply chain supervision can implement monitoring and early warning of the time of the pledged goods in the warehouse, in transit, and during processing. Therefore, this paper proposes an intelligent supply chain supervision model by integrating supply chain finance, logistics, and pledge finance models into an operation management platform to better promote the smooth progress of supply chain finance and logistics supervision activities, which can effectively reduce various external risks, improve operational efficiency, and provide reference for supply chain finance and logistics activities.
Green Building Design Based on 5G Network and Internet of Things System
Authors: Wang Meida , Yang Qingfeng
Published: April 2022

An information-based and intelligent comprehensive energy consumption management system should not only collect, manage, and analyze energy consumption data but also monitor the environmental data inside the building, to manage and display the real energy consumption and internal environmental quality more effectively and reliably. In order to solve this problem, the design and construction of the front-end hardware of the energy consumption management system are proposed, mainly including the design of data acquisition node and data centralization end. The design of data acquisition node includes the selection of DSP controller, wireless communication module, and data acquisition module and the design of main circuit and peripheral circuits. The design of data centralization end includes the selection of its high-performance processor and the transplantation of Linux operating system. This paper only introduces the design and research of lighting control algorithm and applies fuzzy control algorithm to intelligent lighting. The fuzzy control system is introduced, and a fuzzy controller based on intelligent lighting is created. The fuzzy control rule table and fuzzy control query table of the intelligent lighting system are obtained through the fuzzy control algorithm. According to the basic rules of light intensity control, when the indoor light intensity is greater than the set value of light intensity, the LED lamps are turned off, so when

e
<
0

, the LED lamp is off and the PWM output value is 0. Therefore, when designing the fuzzy controller of intelligent lighting system, the basic domain of illumination intensity error

E

is

0500

, excluding the case that the indoor illumination intensity is greater than the set value of illumination intensity.
Vibration Control of a Helicopter Rescue Simulator on a Flexible Base
Authors: Wang Shengye , Wang Haitao , Xiong Wei , Guan Guangfeng
Published: April 2022

The vibration compensation control of a hovering helicopter rescue simulator mounted on a crane beam is studied in this research. A Stewart platform is used as the motion generator of the helicopter simulation cabin and the vibration compensation device of the beam, simultaneously. This study describes how the dynamic model of the Stewart platform with consideration of the beam vibration is established. To determine the interference of the Stewart platform motion control in the special application of a large component flexible base requiring large-scale movement, a hybrid vibration controller composed of a feed-forward compensation module and a PD (proportional-derivative) feedback control module is designed. The experimental results show that this method can effectively compensate for the beam vibration and improve the accuracy of the motion reproduction of a helicopter simulation cabin.
Omadacycline Efficacy against Streptococcus Agalactiae Isolated in China: Correlation between Resistance and Virulence Gene and Biofilm Formation
Authors: Li Guiqiu , Wei Ying , Guo Yan , Gong Hui , Lian Jie , Xu Guangjian , Bai Bing , Yu Zhijian , Deng Qiwen
Published: April 2022

This study aimed to evaluate the activity, resistance, clonality of MIC distribution, and the correlation between virulence and resistance genes and biofilm formation of omadacycline (OMC) in clinics for Streptococcus agalactiae isolates from China. 162 isolates were collected retrospectively in China. The S. agalactiae were collected from the body’s cervical secretions, wound secretions, ear swabs, secretions, semen, venous blood, cerebrospinal fluid, pee, etc. The MIC of OMC against S. agalactiae was determined by broth microdilution. The inhibition zone diameters of OMC and other common antibiotics were measured using filter paper. D-test was performed to determine the phenotype of cross resistance between erythromycin and clindamycin. In Multilocus sequence typing (MLST), some commonly-detected resistance genes and virulence gene of these S. agalactiae isolates were investigated using polymerase chain reaction (PCR). Biofilms were detected by crystal violet staining. Our data demonstrated the correalation of the biofilm formation and OMA antimicrobial susceptibility of S.agalactiae clinical isolates with the carrier of virulence gene scpB. Conclusively, OMC exhibits the robust antimcirobial activity against clinical S. agalactiae isolates from China compared with DOX or MIN, and the carrier of the virulence gene scpB might correlate with the biofilm formation in OMC-resistant S. agalactiae.
An Improved Deep Belief Network IDS on IoT-Based Network for Traffic Systems
Authors: Malik Rayeesa , Singh Yashwant , Sheikh Zakir Ahmad , Anand Pooja , Singh Pradeep Kumar , Workneh Tewabe Chekole
Published: April 2022

Internet of things (IoT) services are turning out to be more domineering with the rising security considerations fading with time. All this owes to the propagating heterogeneity and budding technologies teamed up with resource-constrained IoT systems, sculpting smart systems to be more susceptible to cyber-attacks. The security challenges such as privacy, scalability, authenticity, trust, and centralization thwart the quick adaptation of the smart services; hence, effective solutions are needed to be in place. Traditional approaches of intrusion detection mechanisms have become irrelevant now, as the bad actors often use obfuscation techniques to evade detections. Moreover, these techniques collapse, while detecting zero-day attacks. Hence, there is a need to use an intelligent mechanism based on machine learning (ML) and deep learning (DL), to detect attacks. In this study, the authors have proposed an intrusion detection engine with a deep belief network (DBN) being the core. The implementation of DBN_Classifier is performed using TensorFlow 2.0 and evaluated using a sample of the TON_IOT_Weather dataset. The findings indicate that the proposed engine outperforms the other state-of-the-art techniques with an average accuracy of 86.3%.
An Intelligent Control-Based Vacuum Circuit Breaker with Permanent Magnet and Dynamic Characteristic Analysis
Authors: Peng Jin , Wang Xianbing
Published: April 2022

In the transmission and distribution of energy, circuit breaker plays a very important role. In order to fulfill the current market/user demands, they must be capable of promptly identifying the problem and isolating the problematic areas. According to the extinguishing medium used, circuit breakers are divided into the following categories: air blast, SF6, vacuum, and oil. Among others, permanent magnet (PM) based vacuum circuit breaker is also gaining popularity with each passing day and has become a crucial control and protection equipment in the modern power systems. This study proposes the pulse width modulation (PWM) intelligent control strategy for PM vacuum circuit breaker closing/opening capacitance, group charging, and movement process. For the practical implementation of this idea, dual CPUs are utilized for PM vacuum circuit breaker intelligent control components, by taking STM32F103RBT6 as the core and combining peripheral hardware circuit. PWM pulse output drives IGBT to fulfill the closing/opening capacitance group intelligent charging. On the other hand, PM circuit breaker closing/opening motion displacement signals and coil current feedback achieve closed-loop for PWM intelligent control. The experimental results show that the proposed intelligent control component and PWM intelligent control strategy effectively improve the PM circuit breaker intelligent charging and motion dynamic characteristics.
Pharmacological Properties of Bergapten: Mechanistic and Therapeutic Aspects
Authors: Quetglas-Llabrés Maria Magdalena , Quispe Cristina , Herrera-Bravo Jesús , Catarino Marcelo D. , Pereira Olívia R. , Cardoso Susana M. , Dua Kamal , Chellappan Dinesh Kumar , Pabreja Kavita , Satija Saurabh , Mehta Meenu , Sureda Antoni , Martorell Miquel , Satmbekova Dinara , Yeskaliyeva Balakyz , Sharifi-Rad Javad , Rasool Naeem , Butnariu Monica , Bagiu Iulia Cristina , Bagiu Radu Vasile , Calina Daniela , Cho William C.
Published: April 2022

Bergapten (BP) or 5-methoxypsoralen (5-MOP) is a furocoumarin compound mainly found in bergamot essential oil but also in other citrus essential oils and grapefruit juice. This compound presents antibacterial, anti-inflammatory, hypolipemic, and anticancer effects and is successfully used as a photosensitizing agent. The present review focuses on the research evidence related to the therapeutic properties of bergapten collected in recent years. Many preclinical and in vitro studies have been evidenced the therapeutic action of BP; however, few clinical trials have been carried out to evaluate its efficacy. These clinical trials with BP are mainly focused on patients suffering from skin disorders such as psoriasis or vitiligo. In these trials, the administration of BP (oral or topical) combined with UV irradiation induces relevant lesion clearance rates. In addition, beneficial effects of bergamot extract were also observed in patients with altered serum lipid profiles and in people with nonalcoholic fatty liver. On the contrary, there are no clinical trials that investigate the possible effects on cancer. Although the bioavailability of BP is lower than that of its 8-methoxypsoralen (8-MOP) isomer, it has fewer side effects allowing higher concentrations to be administered. In conclusion, although the use of BP has therapeutic applications on skin disorders as a sensitizing agent and as components of bergamot extract as hypolipemic therapy, more trials are necessary to define the doses and treatment guidelines and its usefulness against other pathologies such as cancer or bacterial infections.
Achievements and Visibility of Scientific Publications of All Peruvian Medical Schools: A 5‐Year Scientometric Analyses
Authors: Mayta-Tovalino Frank , Pacheco-Mendoza Josmel , Bardales-Garcia Jesus , Alvitez Juan , Temoche Abigail , Mendoza Roman , Munive-Degregori Arnaldo
Published: April 2022

Objective. To evaluate the bibliometric profile of the national academic production of public and private medical schools in Scopus after the publication of a new university law (2015–2020). Methods. A descriptive bibliometric study was conducted. The secondary data corresponding to the 42 Peruvian medical schools that had scientific publications in Scopus from 2015 to 2020 were evaluated, and the Affiliation ID of each Peruvian institution was considered. Data were analysed using SciVal. Results. The total production of the Peruvian medical schools was 5406 manuscripts (100%), of which 3018 (56%) were included in the ‘clinical medicine’ category. The total production of publications in Peru from 2015 to 2020 was 21597 manuscripts, of which medical publications accounted for 7950, with only 5406 manuscripts belonging to the Faculties of Medicine of Peru. The Peruvian Journal of Experimental Medicine and Public Health had published the highest number of manuscripts (500 articles), with an approximate publication citation of two. Conclusion. There was a constant increase in the scientific production of Peruvian medical schools from 2015 to 2020. Additionally, it was found that medical publications contribute the most to the total scientific production of Peru.
Tap versus Bottled Water in Kampala, Uganda: Analyses of Consumers’ Perception alongside Bacteriological and Physicochemical Quality
Authors: Onyutha Charles , Akobo Josephine Taata , Mubialiwo Ambrose
Published: April 2022

In Uganda, tap water is always ensured to be potable. However, people are not sure whether tap water is generally safe for drinking without being boiled. Conversely, bottled water consumption is on the increase in Uganda. The main problem lies in the cost of energy for boiling tap water or purchasing bottled water. This study analyzed results of laboratory tests and consumers’ perception for comparison of tap and bottled water in Nakawa division, Kampala. Tap water was sampled at four representative locations. At least 16 different brands of bottled water were considered. The top four most consumer‐preferred bottled water brands were selected for further analysis. In our study, 28.8%, 6.06%, and 13.64% of the 142 respondents indicated that bottled water had taste, color, and smell, respectively. However, 27.5%, 25.4%, and 34.5% of the respondents agreed that tap water had taste, color, and smell, respectively. Both tap and bottled water met the World Health Organization (WHO) guidelines for pH, total dissolved solids, chloride, copper, sodium, sulfate, and nitrate. However, a tap water sample was found to contain Coliform bacteria. In this line, affected communities need to thoroughly boil the raw tap water to kill the pathogens. All tap water samples yielded iron concentrations above the WHO recommended limit. Student's t‐tests showed that tap and bottled water samples were significantly (p<0.05) different with respect to total dissolved solids, pH, chloride, calcium, magnesium, iron, sodium, sulfate, and nitrate. We emphasize the need for routine maintenance of the water distribution system to check for leakages which can be potential source of contaminations.