bluuebunny/crossref_metadata_2025 huggingface dataset:
LINC01087 Promotes the Proliferation, Migration, and Invasion of Thyroid Cancer Cells by Upregulating PPM1E
Authors: Yin Ying , Huang Jianhao , Shi Hongyan , Huang Yijie , Huang Ziyang , Song Muye , Yin Liping
Published: March 2022

This study is aimed at investigating the effect and mechanism of LINC01087 on the malignant evolution of thyroid cancer cells. The expression levels of LINC01087, miR-135a-5p, and PPM1E in thyroid carcinoma tissues were detected by QRT-PCR. Cell viability was detected using the CCK-8 method. Transwell assay was used to assess the ability of cells to invade. The targeting relationship between LINC01087 and miR-135a-5p was detected by dual luciferase reporting assay. In comparison with normal thyroid tissues and cells, the expression level of LINC01087 in thyroid cancer tissues and TPC-1 and K1 cells increased, and the expression level of miR-135a-5p in thyroid cancer tissues and TPC-1 and K1 cells decreased. LINC01087 knockdown and the high expression of miR-143-3p inhibited the proliferation, invasion, and EMT processes of TPC-1 and K1 in thyroid cancer cells. LINC01087 negatively targeted miR-135a-5p. Has-miR-135a-5p inhibited the malignant evolution and EMT of thyroid cancer by targeting PPM1E. The PPM1E overexpression can reverse the inhibitory effect of LINC01087 gene knockdown on the proliferation, migration, and invasion of thyroid cancer cells. LINC01087 can promote the proliferation and apoptosis of thyroid cancer cells, and its mechanism may be related to the miR-135a-5p/PPM1E axis.
Construction and Clinical Application Effect of General Surgery Patient-Oriented Nursing Information Platform Using Cloud Computing
Authors: Chen Yuanyuan , Wang Jingjing , Gao Weiwei , Yu Dongli , Shou Xiaoxia
Published: March 2022

The paper aims to build a nursing information platform (NIP) for general surgery (GS) patients and explore its clinical application effect based on cloud computing (CC) technology. Specifically, the present work first analyzes and expounds on the characteristics of GS patients, the CC concept, the three-tier service mode of CC, and the cloud data center (CDC). Secondly, based on the principle of the overall system design, the evaluation indexes of medical care end, patient end, family end, and management end are constructed using Visual Studio 2010. Thirdly, the expert evaluation and user evaluation methods are selected to analyze the clinical application effect of the proposed system. Finally, SPSS is used to analyze the effect of the proposed system. The results of the first and second rounds of the expert evaluation show that the authority coefficient of experts is greater than 0.7, which indicates that the degree of expert authority is good. The proposed CC-based GS patient-oriented NIP system is universal. The evaluation results of 20 users have shown 15 doctors and nurses, 14 patients, and 18 family members, who mostly still support applying the proposed CC-based GS patient-oriented NIP system and believe that the system brings convenience and improves work efficiency. In short, more incentives should be taken to build a NIP for GS patients.
Types, Risk Factors, Consequences, and Detection Methods of Train Driver Fatigue and Distraction
Authors: Fan Chaojie , Huang Shufang , Lin Shuxiang , Xu Diya , Peng Yong , Yi Shengen
Published: March 2022

Train drivers’ inattention, including fatigue and distraction, impairs their ability to drive and is the major risk factor for human-caused train accidents. Many experts have undertaken numerous studies on train driver exhaustion and distraction, but a systematic study is still missing. Through a systematic review, this work aims to outline the types, risk factors, consequences, and detection methods of train driver fatigue and distraction. The effects of central nervous fatigue and cognitive distraction in train drivers during driving are caused by rest and sleep schedules, workload, automation levels, and mobile phones. Furthermore, train drivers’ fatigue and distraction can cause loss of concentration and slow reaction, resulting in dangerous driving behaviour such as speeding and SPAD. Researchers have combined subjective reporting, physiological parameters, and physical factors to construct detection algorithms with good results to detect train driver fatigue and distraction. This review offers recommendations for researchers looking into train driver fatigue and distraction. And it can also make valuable recommendations for future studies about railway traffic safety.
Comparative Pharmacokinetic Study of Three Major Bioactive Components in the Normal and Different Courses of Liver-Stagnation and Spleen-Deficiency Syndrome Depressive Rats after Intragastric Administration of Zhi-Zi-Hou-Po Decoction
Authors: Luo Kaiwen , Wang Mengdie , Pan Xiangxiang , Xing Yadong
Published: March 2022

To reveal the pharmacokinetic process of narirutin, naringin, and honokiol in normal and different courses of liver-stagnation and spleen-deficiency syndrome depressive rats after intragastric administration of Zhi-Zi-Hou-Po decoction (ZZHPD), a rapid ultra-high performance liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS) method was proposed in this study. Chronic unpredictable mild stress (CUMS) rat was employed as the depression model. Acetonitrile solution containing 0.1% acetic acid and methyl alcohol-water (50 : 50,

v
/
v

) was chosen as the protein precipitant and redissolve solution severally; a Shim-pack GISS C18 column coupled with 0.1% aqueous acetic acid-acetonitrile in gradient elution was employed to separate the mixed constituents in plasma. The WinNonLin software (version 6.1) was chosen as the analytical tool for the pharmacokinetic parameters. The results indicated that compared with rats in the control group, the sucrose preference, scores in the open-field test, and the concentration of 5-HT in plasma of rats in CUMS and CUMS + ZZHPD treatment groups were lower, while the immobility time in the forced swimming test of rats in these two groups was longer, which implied that the depression model was successful. These behavioral and biochemical indexes of rats above in the CUMS + ZZHPD treatment group were improved after oral administration of ZZHPD, which indicated that the antidepressant effect of ZZHPD was definite. The UHPLC-MS/MS method was stabilized, sensitive, and exclusive, and the extraction recovery and matrix effect of three analytes were all above 89%. The Tmax, AUC, and Cmax of three ingredients in CUMS-induced depression rats were significantly larger than control rats, while these pharmacokinetic parameters in CUMS + ZZHPD treatment rats were decreased significantly compared with CUMS-induced depression rats, which may relate with the changes in physiological function of the gastrointestinal tract and liver in CUMS-induced liver-stagnation and spleen-deficiency syndrome depressive rats. This study provided important information for the clinical rational use of ZZHPD in antidepressant treatment.
Diagnostic Value and Prognostic Evaluation of Autophagy-Related Protein Expression Level in Sepsis Complicated with Acute Respiratory Distress Syndrome
Authors: Xu Jia-Li , Yu Xue-Lu , Yao Xiao-Qin , Xu Li-Hong , Jing Mei
Published: March 2022

Objective. To explore the diagnostic value and prognostic evaluation of the autophagy-related protein expression level among patients with sepsis comorbid with acute respiratory distress syndrome. Methods. A total of 182 sepsis patients were admitted to Naval Medical Center from March 2016 to April 2020 and divided into the acute respiratory distress syndrome and non-ARDS groups. Immunoblotting was employed to identify the expression of autophagy-associated protein from participants’ peripheral blood mononuclear cells. Multivariate linear regression analysis was used to examine the association between mortality and the protein expression in sepsis complicated with acute respiratory distress syndrome. Results. Among the 182 patients with sepsis included in this study, 82 patients had acute respiratory distress syndrome and 100 patients did not have acute respiratory distress syndrome. We observed that microtubule-related protein 1A/1B LC3II, Beclin-1, RAB7, and LAMP2 protein expression was significantly decreased in septic patients with ARDS, and p62 was significantly increased. Further receiver operating characteristic curve analysis showed that autophagy-related proteins had a high recognition ability in sepsis complicated with acute respiratory distress syndrome. LAMP2 protein was the best among them, and its specificity was up to 91.46%. In this study, 38 of the 82 patients with sepsis complicated with acute respiratory distress syndrome died, with a mortality rate of 46.34%. We found that the autophagy level was further inhibited in the patients with death, LC3II, Beclin-1, and RAB7. However, the lysosomal-associated membrane protein 2 levels in the survival patients were remarkably higher than that in the dead patients. In addition, the p62 level was lower in survival patients as well. Our results indicated age and SOFA score were the independent risk factors for mortality in septic patients with acute respiratory distress syndrome. Conclusion. The autophagy level is significantly inhibited in septic patients with acute respiratory distress syndrome, and autophagy-associated proteins LC3II, Beclin-1, RAB7, LAMP2, and p62 have good value for the diagnosis and prognosis evaluation of sepsis comorbid with acute respiratory distress syndrome.
Product Processing Quality Classification Model for Small-Sample and Imbalanced Data Environment
Authors: Liu Feixiang , Dai Yiru
Published: March 2022

With the rapid development of machine learning technology, how to use machine learning technology to empower the manufacturing industry has become a research hotspot. In order to solve the problem of product quality classification in a small sample data and imbalanced data environment, this paper proposes a data generation model called MSMOTE-GAN, which is based on Mahalanobis Synthetic Minority Oversampling Technology (MSMOTE) and Generative Adversarial Network (GAN). Among them, MSMOTE is proposed to solve the problem of the sample biased to the majority class expanded by methods such as GAN in a sample imbalanced environment. Based on the traditional SMOTE method, the sample distance measurement method is modified from Euclidean distance to Mahalanobis distance, taking into account the correlation between attributes and the influence of dimensions on the sample distance. In the data generation model, MSMOTE is used to balance the positive and negative samples in the data. GAN generates fake data with the same distribution as the original data based on a balanced data set and expands the sample size to solve the problems of overfitting and insufficient model expression ability that occur when the sample size is too small. The quality classification framework of water heater liner based on the data generation model and Random Forest is constructed, and the process of the quality classification of water heater liner under the environment of small sample data and imbalanced data is fully described. This paper compares the MSMOTE-GAN model, Bootstrap, and tableGAN on the water heater liner production line data set and the public data set. The experimental result shows that the expanded data set of the MSMOTE-GAN model can effectively improve the performance of the classification model.
Effect of Resveratrol Combined with Donepezil Hydrochloride on Inflammatory Factor Level and Cognitive Function Level of Patients with Alzheimer’s Disease
Authors: Fang Xincui , Zhang Jing , Zhao Jianping , Wang Litao
Published: March 2022

Objective. To explore the effect of resveratrol (RES) combined with donepezil hydrochloride on inflammatory factor level and cognitive function level of patients with Alzheimer’s disease (AD). Methods. A total of 90 AD patients treated in our hospital from June 2019 to June 2020 were selected as the study objects and divided into the control group (CG) and experimental group (EG) by the randomized and double-blind method, with 45 cases each. Patients in CG received donepezil hydrochloride treatment, and on this basis, those in EG received additional RES treatment, so as to compare the clinical indicators between the two groups. Results. Compared with CG after treatment, EG obtained significantly higher good rate, MMSE score, and FIM score (

P
<
0.05

) and obviously lower clinical indicators and ADAS-cog score (

P
<
0.001

), and between CG and EG, no obvious difference in total incidence rate of adverse reactions was observed after treatment (

P
>
0.05

). Conclusion. Combining RES with donepezil hydrochloride has significant clinical efficacy in treating AD, which can effectively improve patients’ inflammatory factor indicators, promote their cognitive function, and facilitate patient prognosis.
Application of Machine Learning Techniques to Detect the Children with Autism Spectrum Disorder
Authors: Liao Mengyi , Duan Hengyao , Wang Guangshuai
Published: March 2022

Early detection of autism spectrum disorder (ASD) is highly beneficial to the health sustainability of children. Existing detection methods depend on the assessment of experts, which are subjective and costly. In this study, we proposed a machine learning approach that fuses physiological data (electroencephalography, EEG) and behavioral data (eye fixation and facial expression) to detect children with ASD. Its implementation can improve detection efficiency and reduce costs. First, we used an innovative approach to extract features of eye fixation, facial expression, and EEG data. Then, a hybrid fusion approach based on a weighted naive Bayes algorithm was presented for multimodal data fusion with a classification accuracy of 87.50%. Results suggest that the machine learning classification approach in this study is effective for the early detection of ASD. Confusion matrices and graphs demonstrate that eye fixation, facial expression, and EEG have different discriminative powers for the detection of ASD and typically developing children, and EEG may be the most discriminative information. The physiological and behavioral data have important complementary characteristics. Thus, the machine learning approach proposed in this study, which combines the complementary information, can significantly improve classification accuracy.
Cytotoxic Activity and Antibiofilm Efficacy of Biosynthesized Silver Nanoparticles against Methicillin-Resistant Staphylococcus aureus Strains Colonizing Cell Phones
Authors: Merghni Abderrahmen , Lassoued Mohamed Ali , Noumi Emira , Hadj Lajimi Ramzi , Adnan Mohd , Mastouri Maha , Snoussi Mejdi
Published: March 2022

The interest for green synthesis of metallic nanoparticles (NPs) has acquired particular attention due to its low toxicity and economic feasibility compared with chemical or physical process. Here we carried out an extracellular synthesis approach of silver nanoparticles (AgNPs) using dried orange peel extract. Characterization studies revealed the synthesis of 25–30 nm AgNPs with distinct morphology as observed in transmission electron microscopes. Dynamic light scattering spectroscopy and Fourier transform infrared spectroscopy analyses further characterized nanoparticles confirming their stability and the presence of functional groups. The biological properties of biosynthesized AgNPs were subsequently investigated. Our results revealed anticancer activity of biogenic silver NPs against the B16 melanoma cell line with an IC50 value of 25 µg/ml. Additionally, the developed AgNPs displayed a considerable antagonistic activity against methicillin-resistant Staphylococcus aureus (MRSA) strains colonizing cell phones, with inhibition zones between 12 and 14 mm and minimum inhibitory concentration values between 1.56 and 12.5 µg/ml. Furthermore, the AgNPs exhibited potent antibiofilm activity against MRSA strains with the percent biofilm disruption reaching 80%. Our results highlighted the efficacy of biosynthesized AgNPs against bacterial biofilms and pointed to the exploration of orange peels as a natural and cost-effective strategy.
HB+-MHT: Lightweight and Efficient Data Integrity Verification Scheme for Cloud Virtual Machines
Authors: Yang Zhi , Li Xiaopeng , Jin Shuyuan , Sun Lei , Zhang Zhao , Yang Baoshan , Du Xuehui , Chao Fan
Published: March 2022

With the rapid development of cloud computing, cloud storage is widely used. In the cloud environment, users’ virtual machine system mirrors and data are stored in the cloud server. The escape of virtual machines and Trojan virus attacks make it challenging to ensure the integrity of virtual machine systems. Trusted computing is expensive to randomly verify data integrity and does not adapt to dynamic data changes. Provable data integrity is a potential solution to this problem. Merkle Hash Tree (MHT) model is widely adopted in provable data integrity. Although MHT requires only a small amount of evidence for verification, the verifier’s number of hash calculations and the server’s efficiency of evidence query are not optimal. Moreover, the verification frequency of each piece of data is not considered by MHT. Properly handling these factors can improve the actual verification performance. In this paper, a lightweight and efficient data integrity verification approach called HB+-MHT is proposed for the tenant virtual machine (TVM) in cloud computing. In HB+-MHT, the Huffman hash tree scheme is used for small file verification to ensure that the hot file has a shorter path, which reduces the required amount of evidence for verification. Meanwhile, the B+ hash tree scheme is used for big files verification, which can effectively reduce evidence query time and hash calculation times. The experimental results show that the scheme proposed in this paper can perform data integrity verification well, with reduced computing and storage overhead.
Stem Cells Promote the Regeneration of Knee Joint Degenerative Bone and Articular Cartilage
Authors: Zheng Min
Published: March 2022

Cartilage damage has a certain ability to spontaneously repair, but the repaired tissue often shows the phenomenon of cartilage terminal differentiation, which causes irreversible damage to its structure and function and seriously affects the quality of life and work of patients. It is of great significance to study the problems encountered in the process of cartilage damage repair. This article mainly studied stem cells to promote the regeneration of knee joint degenerative bone articular cartilage. First, the animal articular cartilage defect is modeled, 10 ml of animal venous blood is drawn, 0.5 ml of PRP is collected by centrifugation, mixed with cartilage fragments, and transplanted into the defect area into a gel. In the BMSCs group, 1 ml of BMSCs with a cell concentration of 107 cells/ml was injected intra-articularly. The histological chromosomes were observed after 6 weeks and 12 weeks, and the effect of cartilage tissue repair was analyzed and evaluated, and the related data were statistically analyzed. We evaluated the spontaneous repair ability of partial cartilage damage, full-thickness cartilage damage, and osteochondral damage. Furthermore, for partial cartilage damage repair, by using the cartilage damage in vitro model and biomaterials to simulate the in vivo microenvironment, the adhesion and cell morphology on the surface of partial- and full-thickness cartilage damage were evaluated, and the experiments were further used to evaluate the exogenous and internal induced migration effect of source on cultured cells in vitro. In the cell concentration study, the cartilage repair effect increased with the increase in concentration within a certain range, and the tissue repair ability remained stable when the concentration exceeded 107 cells/ml. Using ECM-oriented scaffolds to compound autologous BMSCs, tissue-engineered cartilage was successfully constructed, which had the histological and biochemical characteristics of normal cartilage tissue, and better repaired the damaged articular cartilage of large animals.
Intelligent Design Model of Urban Landscape Space Based on Optimized BP Neural Network
Authors: Wu Guoping , Miao Yihua , Wang Fang
Published: March 2022

Urban landscape space planning is an important application field of landscape ecology. With the continuous development of the field of architectural optimization, more and more optimization methods have sprung up, including various intelligent optimization algorithms. Such intelligent optimization algorithms usually rely on traditional building performance simulation methods to obtain building performance indicators for optimization in the optimization process. However, intelligent optimization algorithms generally require large-scale calculations. At the same time, the time required for building performance simulation is often limited by the complexity of the building model and the configuration of the computer, which leads to too long performance optimization time for designers in the project. With efficient and accurate feedback, building performance optimization methods based on intelligent optimization algorithms are mainly used in scientific research and are difficult to invest in actual projects. Because the traditional BP neural network has its own limitations and its insufficient sample size and weak generalization ability in complex prediction problems, this paper uses the learning algorithm of optimizing the BP neural network to propose an urban landscape space intelligent design model. This article introduces the artificial neural network, a new application technology with the assistance of a geographic information system, and establishes a BP neural network model for urban landscape ecological planning. Seven elements of distance and number of residential points are used as input variables, patch density, fractal dimension, the Shannon diversity index, and aggregation degree are selected as output changes, and 20 samples are carefully collected to train the network. The results show that the network convergence effect is ideal and the generalization ability is strong, which provides a new simulation analysis method for landscape ecological planning.
Diseases That Occur Prior to Spontaneous Intracerebral Hemorrhage: Identification of Predisposing and Risk Factors Using Lag Sequential Analysis
Authors: Ting Hsien-Wei , Chien Ting-Ying , Liao Chun-Chih
Published: March 2022

Spontaneous intracerebral hemorrhage (sICH) has many predisposing/risk factors. Lag sequential analysis (LSA) is a method of analyzing sequential patterns and their associations within categorical data in different system states. The results of this study will assist in preventing sICH and improving the patient outcome after sICH. The correlations between a first sICH and previous clinic visits were examined using LSA with data obtained from the Taiwan National Health Insurance Research Database (NHIRD). In this study, LSA was employed to examine the data in the Taiwan NHIRD in order to identify predisposing and risk factors related to sICH, and the results increased our knowledge of the temporal relationships between diseases. This study employed LSA to identify predisposing/risk factors prior to the first occurrence of sICH using a healthcare administrative database in Taiwan. The data were managed using the clinical classification software (CCS). All cases of traumatic ICH were excluded. Ten disease groups were identified using CCS. Hypertension and dizziness/vertigo were identified as two important predisposing/risk factors for sICH, and early treatment of hypertension resulted in a greater survival rate. Five disease groups were found to have occurred prior to other diseases and affected mostly the elderly, resulting in subsequent sICH. The results of this study also showed that nutritional status and tooth health were highly associated with the occurrence of sICH owing to a poor state of the digestive system. In conclusion, there are many diseases that influence the risk of a subsequent sICH. This study demonstrated that LSA is a very useful tool for future study of healthcare administrative databases.
Mechanical Properties of Polypropylene-Fiber-Reinforced High-Performance Concrete Based on the Response Surface Method
Authors: Song Min , Song Nixia , Zhang Yunlong , Wang Jing
Published: March 2022

Polypropylene fibers are added to concrete to improve the toughness of the material. Manufactured sand and fly ash with high content are used to reduce the impact on the environment and cost. The response surface method (RSM) was used to design the test and study the mechanical and bending properties of polypropylene-fiber-reinforced high-performance concrete (PPFHPC). Three process variables, including the content of polypropylene fiber (1%, 1.5%, and 2%), content of fly ash (45%, 60%, and 75%), and water-binder (W/B) ratio (0.27, 0.3, and 0.33), were considered as factors. The compressive strength, flexural strength, flexural-compressive ratio, splitting tensile strength, and first-crack strength and bending strength of thin plate were evaluated. The prediction model established by the RSM showed the correlation and predictability between the response and the factors, and the corresponding relationship equation between the factors and the response was obtained. Results of multiobjective optimization indicated that the optimal three factors (content of PPF, FA, and W/B) were 2%, 62%, and 0.27. The established model can be used to predict the basic mechanical properties and bending properties of materials. This test laid a theoretical foundation for the development of PPFHPC materials.
Evaluation of Functional Magnetic Resonance Imaging under Artificial Intelligence Algorithm on Plan‐Do‐Check‐Action Home Nursing for Patients with Diabetic Nephropathy
Authors: Du Qianqian , Liang Dianchao , Zhang Lixin , Chen Guoyan , Li Xueyan
Published: March 2022

This study aimed to evaluate the effect of functional magnetic resonance imaging (fMRI) under the fuzzy C‐means (FCM) clustering algorithm on plan‐do‐check‐action (PDCA) home nursing for patients with diabetic nephropathy (DN). As the characteristics of fMRI image data were combined, the FCM algorithm was improved and applied into the clustering processing of fMRI activation regions of patients. 64 patients with DN were chosen as the research objects and were divided into the research group with PDCA home nursing and the control group with routine home nursing. The patients were randomly divided into the research group (n = 32) and the control group (n = 32). The curative effect, nursing satisfaction, and quality of life of patients after nursing were compared. The results showed that the coverage of fMRI activation points was significantly higher as being detected by the FCM algorithm, and the running time was shortened by 33.6 min. After nursing, the total effective rates in the research group and the control group were 87.5% vs. 34.4% in 3 months, 93.8% vs. 68.8% in 6 months, and 96.9% vs. 75.0% in 12 months, respectively; those in the research group were significantly higher than those in the control group (P < 0.05). The nursing satisfaction score (91.3 ± 4.5 vs. 80.9 ± 5.2) and nursing service quality score (89.7 ± 6.6 vs. 80.3 ± 7.1) in the research group were also significantly higher than those in the control group (P < 0.05). Meanwhile, the scores of each item after nursing in the research group were significantly higher than those in the control group (P < 0.05). The improved FCM algorithm detected the activation regions in the fMRI images more effectively, which could provide help for diagnosis and reduce error and misdiagnosis. At the same time, the PDCA home nursing also offered great help to the recovery of patients with DN, which was more superior for the curative effect of hospitalization, the promotion of recovery, and the improvement of patients’ quality of life.
Basquetebol: componentes da ação pedagógica
Authors:   Universidade de São Paulo. Escola de Artes, Ciências e Humanidades, Rose Junior Dante de
Published: March 2022

O livro traz uma abordagem diferenciada sobre o impacto desses componentes no processo ensino-aprendizagem desta modalidade esportiva. Baseado na vasta experiência e vivência prática e acadêmica do autor no assunto, embasado pela opinião de diversos outros especialistas referenciados na obra, o livro aponta a importância dos cinco componentes da ação pedagógica para um melhor desenvolvimento de crianças e jovens na prática do basquetebol, tanto em nível de iniciação, quanto no aperfeiçoamento de suas capacidades e habilidades. Além de todo o embasamento teórico e prática trazido pelo autor, o apêndice traz a contribuição de profissionais envolvidos nesse processo e que compartilham sua experiência na aplicação desses componentes. Assim sendo, espera-se que este livro possa contribuir para uma melhor capacitação de profissionais para atuar em uma fase tão importante no desenvolvimento esportivo das crianças e jovens, mas também na sua trajetória de vida como cidadãos.
Ensino de literatura e avaliação formativa: a experiência de alunos das camadas populares
Authors: Dias Rafaela Kelsen , Magalhães Túlio Romualdo
Published: March 2022

Considerando os debates sobre o declínio do número de leitores na sociedade contemporânea e sobre o modelo ideal de avaliação para um ensino significativo de literatura, este artigo volta-se ao estudo de práticas avaliativas de literatura para jovens matriculados no Ensino Médio. De modo mais específico, desenvolve-se este trabalho em torno do seguinte problema: a avaliação formativa em literatura é capaz de promover uma formação humana integral para os discentes das camadas populares? Dessa forma, o objetivo geral é investigar, no âmbito do IFMG campus Ouro Preto, a existência e a efetividade da avaliação formativa de literatura para alunos das camadas populares. O estudo foi conduzido por meio de pesquisa exploratória, descritiva e documental, calcada em análises qualiquantitativas dos dados obtidos. Ao fim do estudo, espera-se complementar o debate sobre a real dimensão da leitura e incentivar uma política inclusiva do ensino de literatura.
Exports and Wage Premiums: Evidence from Mexican Employer-Employee Data
Authors: Frías Judith A. , Kaplan David S. , Verhoogen Eric , Alfaro-Serrano David
Published: March 2022

This paper draws on employer-employee and longitudinal plant data from Mexico to investigate the impact of exports on wage premiums, defined as wages above what workers would receive elsewhere in the labor market. We decompose plant-level average wages into a component reflecting skill composition and a component reflecting wage premiums. Using the late-1994 peso devaluation interacted with initial export propensity as a source of exogenous changes in exports, we find that exports have a significant positive effect on wage premiums and that the effect on wage premiums accounts for essentially all of the medium-term effect of exporting on plant-average wages.
Curriculum Reforms and Infant Health
Authors: Dursun Bahadir , Eren Ozkan , Nguyen My
Published: March 2022

This paper examines the effects of high school curriculum reforms on infant health by exploiting sharp and staggered changes across states in core course requirements for graduation. Our results suggest that curriculum reforms significantly reduced the incidence of low birthweight and prematurity for black mothers. For white mothers, the estimated effects are small and generally insignificant. We also explore the mechanisms for observed effects and provide evidence consistent with our explanations. Finally, we calculate a large social gain induced by favorable infant health outcomes. Several robustness checks and different placebo tests support our findings.
The Geography of Jobs and the Gender Wage Gap
Authors: Liu Sitian , Su Yichen
Published: March 2022

Prior studies show that women are more willing to accept lower wages for shorter commutes than men. We show that gender differences in commuting preferences lead to a gender wage gap only if there is a wage penalty for shortening commutes, determined by the geography of jobs. We demonstrate this by showing that the commuting and wage gaps are considerably smaller among workers living near city centers, especially for occupations with a high geographic concentration of high-wage jobs. We highlight the geography of jobs as a key force that amplifies the impact of commuting preferences on the gender wage gap.
Zeolitic Imidazolate Framework-8 (ZIF-8) and Its Derivative Nanomaterials for Antibiotics Adsorption in Contaminated Water
Authors: Qin Yuxuan , Li Wenyao , Akpinar Isil , Hang Chen , Huang Liping , Wang Liyang , Gu Wen , Wu Jianghong
Published: March 2022

Antibiotics have gradually received extensive attention as a new organic pollutant in the water environment, which is detrimental to aquatic organisms and humans. It was found in groundwater, surface water, especially contaminated water. Hence, it’s imperative to take effective
methods to remove residual antibiotics in contaminated water. Zeolitic imidazole frameworks (ZIFs) with adjustable porous structures and large specific surface areas are conducive to adsorbing antibiotic pollutants. This review summarized ZIF-8 and its derivative nanomaterials covering the
related researches on adsorbents for antibiotics in contaminated water. Besides, we emphasized how ZIF-8 derivative materials are more convenient for practical application in water treatment. In addition, the adsorption mechanism was further illustrated. This review aims to provide a theoretical
foundation basis for the application of ZIF-8 in water treatment.
ZnO and ZnO/Co3O4 Nanorods for Enhanced Photovoltaic and Photosensors Applications
Authors: Mugheri Abdul Qayoom , Otho Ajaz Ali , Kaleri Ghulam Murtaza , Ghanghro Sahib , Kandhro Aftab , Fouad Hassan , Akhtar M. Shaheer
Published: March 2022

In this present work, we plan for the first time an all-oxide solar cell and ambient light sensors constructed onto n-type semiconductor zinc oxide along with p-type material having extrinsic type of semiconductor Co3O4 nanowires. The perpendicular ZnO nanorods
are dense and are working like scattering layer used for the visible light, even though Co3O4 nano material acting as a visible-light absorber directly. Characterization by SEM, AFM, TEM, XRD, EDS, Optical transmittance, J–V curve. The p-n junction based on metal
oxides can operate both such as a photovoltaic (PV) device and a visible light photodetector. The photovoltaic parameters measured beneath simulated sunlight, demonstrating for the first time a PV effect in longitudinal nanowire junctions with decent fill factor (FF, 45%). Furthermore, the
heterojunction has also shown an excellent, stable, highly reproducible material, having very fast activity designed for the exposure of visible light. Functional, or effective as possible of the device is essential to strongly improve its functionalities of material. The proposed oxide nanowire
p-n junction provides advancement in the field of PV and optoelectronic devices by using inexpensive, stable, and earth-abundant metal oxides.
Fault Diagnosis of Synchronous Belt of Machine Tool Based on Improved Back Propagation Neural Network
Authors: Shi Yao-Chen , Li Ze-Qi , Zhao Tian-Xiang , Yu Xue-Lian , Yin Chun-Mei , Bai Yi-Shi
Published: March 2022

Aiming at the problem that the machine tool synchronous belt failure during the transmission process will affect the machine tool transmission, a machine tool synchronous belt fault diagnosis method based on genetic algorithm (GA) optimized back propagation (BP) neural network is proposed.
First, utilize wavelet decomposition to extract the energy characteristics of the synchronization belt fault; construct a BP neural network, and use genetic algorithms to optimize the BP neural network; finally, the energy characteristic of the vibration signal of the synchronous belt is used
as the input of the neural network, and the fault simulation test is carried out. The results show that the genetic algorithm GA-optimized BP neural network has higher accuracy than the traditional BP neural network for fault diagnosis of machine tool synchronous belt.
A Scaling Theory for the Diffusivity of Poleward Eddy Heat Transport Based on Rhines Scaling and the Global Entropy Budget
Authors: Chang Chiung-Yin , Held Isaac M.
Published: March 2022

Diffusive theories for the meridional atmospheric energy transport can summarize our understanding of this central aspect of the general circulation. They can also be utilized in simple models of Earth’s energy balance to help interpret the response of the system to perturbations. A theory for this diffusivity of eddy heat transport is described based on Rhines scaling and the global entropy budget, each of which provides a constraint between the kinetic energy dissipation and the diffusivity. An expression for the diffusivity is then obtained by eliminating the dissipation from this set of two constraints. The theory can be thought of as a generalization of the theories of Held–Larichev and Barry–Craig–Thuburn. The theory is compared to simulations of the Held–Suarez idealized dry atmospheric model. Limitations of the theory are emphasized. The form of the theory allows it to be readily generalized to a moist atmosphere.
Skillful Seasonal Prediction of North American Summertime Heat Extremes
Authors: Jia Liwei , Delworth Thomas L. , Kapnick Sarah , Yang Xiaosong , Johnson Nathaniel C. , Cooke William , Lu Feiyu , Harrison Matthew , Rosati Anthony , Zeng Fanrong , McHugh Colleen , Wittenberg Andrew T. , Zhang Liping , Murakami Hiroyuki , Tseng Kai-Chih
Published: March 2022

This study shows that the frequency of North American summertime (June–August) heat extremes is skillfully predicted several months in advance in the newly developed Geophysical Fluid Dynamics Laboratory (GFDL) Seamless System for Prediction and Earth System Research (SPEAR) seasonal forecast system. Using a statistical optimization method, the average predictability time, we identify three large-scale components of the frequency of North American summer heat extremes that are predictable with significant correlation skill. One component, which is related to a secular warming trend, shows a continent-wide increase in the frequency of summer heat extremes and is highly predictable at least 9 months in advance. This trend component is likely a response to external radiative forcing. The second component is largely driven by the sea surface temperatures in the North Pacific and North Atlantic and is significantly correlated with the central U.S. soil moisture. The second component shows largest loadings over the central United States and is significantly predictable 9 months in advance. The third component, which is related to the central Pacific El Niño, displays a dipole structure over North America and is predictable up to 4 months in advance. Potential implications for advancing seasonal predictions of North American summertime heat extremes are discussed.
Frontogenesis, Mixing, and Stratification in Estuarine Channels with Curvature
Authors: Bo Tong , Ralston David K.
Published: March 2022

Idealized numerical simulations were conducted to investigate the influence of channel curvature on estuarine stratification and mixing. Stratification is decreased and tidal energy dissipation is increased in sinuous estuaries compared to straight channel estuaries. We applied a vertical salinity variance budget to quantify the influence of straining and mixing on stratification. Secondary circulation due to the channel curvature is found to affect stratification in sinuous channels through both lateral straining and enhanced vertical mixing. Alternating negative and positive lateral straining occur in meanders upstream and downstream of the bend apex, respectively, corresponding to the normal and reversed secondary circulation with curvature. The vertical mixing is locally enhanced in curved channels with the maximum mixing located upstream of the bend apex. Bend-scale bottom salinity fronts are generated near the inner bank upstream of the bend apex as a result of interaction between the secondary flow and stratification. Shear mixing at bottom fronts, instead of overturning mixing by the secondary circulation, provides the dominant mechanism for destruction of stratification. Channel curvature can also lead to increased drag, and using a Simpson number with this increased drag coefficient can relate the decrease in stratification with curvature to the broader estuarine parameter space.
Maternal Outcomes After Trauma in Pregnancy: A National Database Study
Authors: Siddiqi Mahwash , Guiab Keren , Roberts Andrew , Evan Teresa , Nahar Tanzilan , Patel Vidhi , Capron Gweniviere , Brigode William , Starr Frederic , Bokhari Faran
Published: March 2022

Objectives

Trauma is an important non-obstetric cause of mortality in pregnant females.

Methods

The National Trauma Databank (NTDB) was queried between 2017 and 2018. Pregnant women >20 weeks gestation, who underwent trauma, were included. They were categorized into different age groups from 12-18, 18-35, and 36-50 years of age. The primary outcome measure was 30-day mortality.

Results

1,058 pregnant trauma patients were included. Mean age was 26.7 ± 6 years. Of those 94.5% had blunt and 3.8% had penetrating injuries. Median GCS and ISS were 15 (15, 15) and 2 (1, 5), respectively. Penetrating trauma patients required more operative intervention (57.5%) than blunt trauma patients (24.6%). Univariate analysis comparing age groups 12-18, 19-35, and >36 years revealed differences. ( P < .05) in ED systolic blood pressure (110.9 ± 19.7 vs 117.3 ± 20.3 vs 129.1 ± 29.3 mmHg, P = .01) and diabetes mellitus (.0 vs 2.7% vs 6.6% P = .03). There was no difference in HLOS ( P = .72), complications ( P = .279), and mortality ( P = .32). Multivariate logistic regression analysis revealed that compared to patients 12-18 years old, patients 19 to 35 ( P = .27) or those >36 ( P = 1.0) did not show a significant difference in mortality. Patients with high ISS had higher complication rates (OR 1.09; 95% CI 1.04-1.15) and prolonged HLOS (OR 1.00; 95% CI 1.07-1.15).

Conclusion

On average pregnant women (>20 weeks gestation) who presented to trauma centers had minor injuries and maternal age or mechanism of injury did not affect mortality. Despite a low ISS, a significant number of these patients required operative procedures.
Percutaneous Retrieval of Retained Gallstones
Authors: McCarley Saudia , Yu Bernice , Guay Robert , Ong Adrian , Sacks David , Butts Christopher A.
Published: March 2022

Laparoscopic cholecystectomy has become the gold standard for patients with gallbladder disease. However, spilled gallstones occur in up to 18% of laparoscopic cholecystectomies, which may result in retained gallstones. Though most do not cause issues, there may be abscess formation from 4 months to 10 years postoperatively. We present a 78-year-old patient who formed a subhepatic abscess 3 months postoperatively from his laparoscopic cholecystectomy secondary to a 1 cm retained gallstone. The abscess was percutaneously drained by interventional radiology (IR), and the stone was subsequently removed by IR using a percutaneous approach. Open and laparoscopic approaches have been previously described for abscess drainage and removal of gallstones. In this case, both the abscess and stone were drained and removed percutaneously by IR. Though this is an uncommon entity, percutaneous decompression can aid in preventing such patients from undergoing additional surgery.
A Portable Negative Pressure Isolation System as a Solution to Minimize Exposure of Health Care Providers to Infectious Pathogens
Authors: Economopoulos Konstantinos P. , Fearis Paul , Simmons W. Neal , Richardson Eric S. , Montgomery Sean P.
Published: March 2022

The COVID-19 pandemic has resulted in the exposure of many surgeons and healthcare providers (HCPs) to disease given high patient loads and limited availability of negative pressure rooms. For these reasons we pursued the development of a portable patient isolation system (COVIAGE™ by iSolace, Inc.) that can be used to contain patients with respiratory illness and minimize the exposure of HCPs. COVIAGE™ is comprised of a reusable aluminum frame, a disposable thermoplastic polyurethane tent and a HEPA filtration/ventilation system (HVAC) utilizing two inline filters. The efficacy of filtration was tested by comparing particulate concentration inside and outside of the device by an independent third party. Additionally, physician, nursing, and respiratory tasks were performed initially on simulated patients and then on intubated patients in the ICU. The system attained a verified filtration efficiency greater than 99.999% for an average 0.3-μm size particulates. Simulation testing revealed that most common physician, nursing, and respiratory tasks could be completed in the device, including endotracheal intubation. Emergency removal of the device can be accomplished in 8.8 ± 2.8 seconds. The reusable aluminum frame allows for simple attachment to the bed, and adaptability to different types and sizes of beds/stretchers. An emergency use authorization was granted by the FDA. The device created results in a portable negative pressure isolation system that can be placed over the patient’s bed to contain aerosols during high aerosol generating procedures, transportation of patients or for total patient care in environments where negative pressure rooms are not available.
Safety and Effectiveness of Endovascular Therapy for the Treatment of Peripheral Artery Disease in Patients with and without Diabetes Mellitus
Authors: Korosoglou Grigorios , Giusca Sorin , Langhoff Ralf , Lichtenberg Michael , Lawall Holger , Schellong Sebastian , Stausberg Jürgen , Hoffmann Ulrich , Enders Dominic , Malyar Nasser
Published: March 2022

This study investigated the distribution of risk factors, lesion characteristics and endovascular revascularization (EVR) strategies in patients with peripheral arterial disease (PAD) with vs without diabetes mellitus (DM). Data were collected within the RECcording COurses of vasculaR Diseases (RECCORD) registry. Demographic data, lesion localization (iliac vs femoropopliteal vs below-the-knee (BTK)) and lesion complexity score (LCS) based on number of affected segments, and lesion length (< 10 vs 10–20 vs > 20 cm), EVR strategies and peri-procedural complications were analysed in 786 patients with and 1337 without diabetes mellitus. Patients with diabetes mellitus were older (71.6 ± 9.6 vs 69.4 ± 10.5 years, P < .001) and had higher LCS and more often BTK lesions ( P < .05 for all). Lesions were treated less frequently with stents (48.7 vs 59.6%, P < .001) in patients with diabetes mellitus, whereas a non-significant trend was noticed for higher DCB treatment rates (48.3 vs 44.4%, P = .07). Post-interventional ankle-brachial index (ABI) increase was similar (from .77 ± .28 to .92 ± .25 with diabetes mellitus and from .74 ± .21 to .90 ± .20 without diabetes mellitus, P < .001 for both). Peri-/post-procedural complications were low in both groups (4.6%). Patients with diabetes mellitus, who undergo endovascular revascularization are older, have more comorbidities and higher target lesion complexity. However, treatment success rates are similar and complication rates are low.