bluuebunny/crossref_metadata_2025 huggingface dataset:
Exposure to Air Pollution Exacerbates Inflammation in Rats with Preexisting COPD
Authors: Wang Jing , Li Ya , Zhao Peng , Tian Yange , Liu Xuefang , He Huihui , Jia Rui , Oliver Brian G. , Li Jiansheng
Published: May 2020

Particulate matter with an aerodynamic diameter equal or less than 2.5 micrometers (PM2.5) is associated with the development of chronic obstructive pulmonary disease (COPD). The mechanisms by which PM2.5 accelerates disease progression in COPD are poorly understood. In this study, we aimed to investigate the effect of PM2.5 on lung injury in rats with hallmark features of COPD. Cardinal features of human COPD were induced in a rat model by repeated cigarette smoke inhalation and bacterial infection for 8 weeks. Then, from week 9 to week 16, some of these rats with COPD were subjected to real-time concentrated atmospheric PM2.5. Lung function, pathology, inflammatory cytokines, oxidative stress, and mucus and collagen production were measured. As expected, the COPD rats had developed emphysema, inflammation, and deterioration in lung function. PM2.5 exposure resulted in greater lung function decline and histopathological changes, as reflected by increased Mucin (MUC) 5ac, MUC5b, Collagen I, Collagen III, and the profibrotic cytokine α-smooth muscle-actin (SMA), transforming growth factor- (TGF-) β1 in lung tissues. PM2.5 also aggravated inflammation, increasing neutrophils and eosinophils in bronchoalveolar lavage fluid (BALF) and cytokines including Interleukin- (IL-) 1β, granulocyte-macrophage colony-stimulating factor (GM-CSF), and IL-4. The likely mechanism is through oxidative stress as antioxidants levels were decreased, whereas oxidants were increased, indicating a detrimental shift in the oxidant-antioxidant balance. Altogether, these results suggest that PM2.5 exposure could promote the development of COPD by impairing lung function and exacerbating pulmonary injury, and the potential mechanisms are related to inflammatory response and oxidative stress.
An Improved Nonhomogeneous Discrete Grey Model and Its Application
Authors: Jiang Jianming , Zhang Yu , Liu Changqing , Xie Wanli
Published: May 2020

In recent years, the nonhomogeneous grey model has received much attention owing to its flexibility and applicability of forecasting small samples. To improve further the prediction accuracy of the nonhomogeneous grey model, this paper is to introduce a new whitening equation with variable coefficient into the original nonhomogeneous grey model, which is abbreviated as ONGM1,1,k,c. First of all, the detailed computational steps of the time response function of the novel model and the restored values of the raw data sequence are deduced through grey modelling techniques. Secondly, two empirical examples from the previous literature are conducted to prove the validity of the novel model. Finally, the novel model is applied to forecast natural gas demand of China, and the results show that the novel model has a better prediction performance compared with other commonly used grey models, including GM1,1, DGM1,1, NGM1,1,k,c, and NGBM1,1.
Percutaneous Nephrolithotomy: Challenges for a Novice Urologist
Authors: Chaurasia Ashish
Published: May 2020

PCNL is the treatment of choice for large renal stones. It is a procedure of expertise. It may look simpler when done by an experienced urologist; however, for a beginner, learning each and every step is very important. He should be well-versed about the difficulties faced at every step and know how to tackle them. This article focuses mainly on the intricacies faced by a trainee during the procedure and how to troubleshoot them. Failure at any stage can lead to bleeding complications or incomplete removal of stones.
A Revised Surgical Strategy for the Distal Tibiofibular Interosseous Osteochondroma
Authors: Yang Huarui , Shou Kangquan , Wei Shijun , Fang Zhi , Hu Qiwen , Wan Qiong , Yang Yi , Bao Tongzhu
Published: May 2020

Osteochondroma is one of the most common benign bone tumor; however, the surgical treatment still remains a challenge for those that occur at the distal tibiofibular interosseous location. Previously, the transfibular approach has been successfully described, but the potential damage of the syndesmosis would give rise to the instability of the ankle joint and thus may result in the unfavorable long‐term outcome. Here, a revised strategy which can protect the syndesmotic complex is introduced. From 2010 to 2017, eleven patients with the distal tibiofibular interosseous osteochondroma who underwent the revised surgery were collected. The distal fibular osteotomy and posterior tibial osteotomy were performed to keep the inferior syndesmosis intact for better stability of the ankle joint. Both the anterior tibiofibular ligaments (AITFL) and posterior tibiofibular ligaments (PITFL) have been preserved successfully, and thus, the stability of the ankle joint has been maintained due to our strategy. The VAS and AOFAS scores were utilized to assess the clinical outcome and function. Postoperatively, all the patients were pain‐free and were able to wear the appropriate shoes at the last follow‐up. Preoperative and postoperative AOFAS scores were 93.63 ± 6.91 and 47.27 ± 5.27 (P < 0.05), respectively. Moreover, the average VAS score was 1.73 ± 0.27 (compared with preoperative as 7.45 ± 2.15, P < 0.05), demonstrating obvious improvement after the operation. To our best knowledge, this is the first time to perform the resection of the distal tibial interosseous osteochondroma involving the fibula without interrupting the inferior syndesmotic complex especially the AITFL and PITFL. We believe that this strategy may pave a new way for optimized clinical outcome for these patients with distal tibiofibular interosseous osteochondroma. This clinical trial study is registered with number ChiCTR1900024690.
Fuzzy Multicriteria Decision-Making for Ranking Intercrop in Rubber Plantations under Social, Economic, and Environmental Criteria
Authors: Muangman Jitsupa , Krootsong Kittipong , Polrong Phattamon , Yukunthorn Weera , Udomsap Weerawat
Published: May 2020

Rubber price instability causes great economic problems for rubber plantation in Thailand. Intercropping is an alternative way for rubber farmers in problem-solving. In this paper, we established decision-making system for plant selection in rubber fields under social, economic, and environment criteria with the use of fuzzy multicriteria decision-making (FMCDM) to rank plant options. Firstly, we modified the traditional FMCDM by defuzzification with norm centroid and developed the fuzzifier maps the norm centroid to triangular fuzzy number (TFN). According to fuzzification, the final rating evaluation of plant options are determined by total utility values. Finally, ranking of the plant options is obtained. Our modifications provided an alternative decision-making process with softer computational capability compared with the traditional method. In addition to soft computing, data visualization and analysis of the possibility in each factors could be investigated. This decision-making system was implemented in Phang-Nga Province, Thailand. Its outputs assisted the rubber farmer in selecting suitable plants for cultivation. Pros and cons of each plant options and area-based approaches were easily seen by data visualizations. This decision-making system provided beneficial information which support precision developments for rubber farmer and government agencies.
SSVEP Enhancement Using Moving Average Filter Controlled by Phase Features
Authors: Trigui Omar , Daoud Sawsan , Ghorbel Mohamed , Mhiri Chokri
Published: May 2020

Brain-computer interface (BCI) systems translate the human neurophysiological activities into commands through EEG analysis. Improving the BCI performances leads to faster and easier use and less fatigue. In this study, we proposed a new prepossessing approach to increase the robustness of a steady-state visual evoked potential (SSVEP) based BCI. Inspiring from the known properties of the SSVEP frequency components, the goal was to enhance the signal quality by making it more convenient to be interpreted by the decision-making step. We first investigated the potential to detect the deteriorating periods based on the physiological properties of the SSVEP. The proposed system localizes the intervals which can obscure the SSVEP frequencies by a new algorithm founded on the processing and the analysis of the instantaneous phase. The piecewise linear regression allows a sampler comprehension of the phase signal. Then, these intervals are filtered by the moving average filter to enhance the SSVEP quality. Finally, the decision making is made by the canonical correlation analysis (CCA) algorithm. The results of experiments, using real EEG signals from five subjects, show that the proposed approach significantly increases the performances in terms of accuracy and information transfer rate by about 7.3% and 3.85 bits/min, respectively, in case of 2 s segment length. On the other hand, the spatial filtering methods of the literature weaken the system performances.
Cross-Subject Seizure Detection in EEGs Using Deep Transfer Learning
Authors: Zhang Baocan , Wang Wennan , Xiao Yutian , Xiao Shixiao , Chen Shuaichen , Chen Sirui , Xu Gaowei , Che Wenliang
Published: May 2020

Electroencephalography (EEG) plays an import role in monitoring the brain activities of patients with epilepsy and has been extensively used to diagnose epilepsy. Clinically reading tens or even hundreds of hours of EEG recordings is very time consuming. Therefore, automatic detection of seizure is of great importance. But the huge diversity of EEG signals belonging to different patients makes the task of seizure detection much challenging, for both human experts and automation methods. We propose three deep transfer convolutional neural networks (CNN) for automatic cross-subject seizure detection, based on VGG16, VGG19, and ResNet50, respectively. The original dataset is the CHB-MIT scalp EEG dataset. We use short time Fourier transform to generate time-frequency spectrum images as the input dataset, while positive samples are augmented due to the infrequent nature of seizure. The model parameters pretrained on ImageNet are transferred to our models. And the fine-tuned top layers, with an output layer of two neurons for binary classification (seizure or nonseizure), are trained from scratch. Then, the input dataset are randomly shuffled and divided into three partitions for training, validating, and testing the deep transfer CNNs, respectively. The average accuracies achieved by the deep transfer CNNs based on VGG16, VGG19, and ResNet50 are 97.75%, 98.26%, and 96.17% correspondingly. On those results of experiments, our method could prove to be an effective method for cross-subject seizure detection.
Thermal Aging of Menzolit BMC 3100
Authors: Kostial Pavol , Kostialova Jancikova Zora , Krejcar Ondrej , Kuca Kamil , Fadeyi Oluwaseun , Orogun Adebola , Frischer Robert
Published: May 2020

This paper deals with the influence of thermal aging on physical properties of a composite material, Menzolit BMC 3100. First, we present a number of analysis, FTIR (infrared spectroscopy), DSC (differential scanning calorimetry), TMA (thermomechanical analysis), TGA (thermogravimetric analysis), and HDT (heat deflection temperature), to understand the material performance under heat, and then, we carry out a test of toughness and strength using Charpy impact strength and Brinell hardness. Finally, we present optical surface analysis of the material under investigation by carrying out aging analysis at increments from room temperature up to 300°C. It was observed that above 200°C, the material begins to degrade at the surface, especially its organic component, polyester resin. This type of degradation has a negative impact on a variety of its physical properties. Exposure to temperatures above 200°C reduces the material’s hardness, toughness, and shape stability, likewise, material degradation was found to increase with higher thermal loads almost linearly for all the observed properties.
Hazard of Cervical, Oropharyngeal, and Anal Cancers in HIV-Infected and HIV-Uninfected Medicaid Beneficiaries
Authors: Michaud Joanne M. , Zhang Tingting , Shireman Theresa I. , Lee Yoojin , Wilson Ira B.
Published: May 2020

Background:

Human immunodeficiency virus–infected (HIV+) individuals are disproportionately at risk for human papillomavirus (HPV)-associated cancers, but the magnitude of risk estimates varies widely. We conducted a retrospective study using a large U.S.-based cohort to describe the relationship between HIV infection and incident cervical, oropharyngeal, and anal cancers.

Methods:

Using 2001–2012 U.S. Medicaid data from 14 states, we matched one HIV+ to three HIV-uninfected (HIV−) enrollees on sex, race, state, age, and year, and followed persons for up to 10 years. We developed Cox proportional hazards models comparing HIV+ to HIV− for time to cancer diagnosis adjusted for demographic and comorbidity attributes.

Results:

Our cohorts included 443,592 women for the cervical cancer analysis, and 907,348 and 906,616 persons for the oropharyngeal and anal cancer analyses. The cervical cancer cohort had a mean age of 39 years and was 55% Black. The oropharyngeal and anal cancer cohorts were 50% male, had a mean age of 41 years, and were 51% Black. We estimated the following HRs: cervical cancer, 3.27 [95% confidence interval (CI), 2.82–3.80]; oropharyngeal cancer, 1.90 (95% CI, 1.62–2.23; both sexes), 1.69 (95% CI, 1.39–2.04; males), and 2.55 (95% CI, 1.86–3.50; females); and anal cancer, 18.42 (95% CI, 14.65–23.16; both sexes), 20.73 (95% CI, 15.60–27.56; males), and 12.88 (95% CI, 8.69–19.07; females).

Conclusions:

HIV+ persons were at an elevated risk for HPV-associated cancers, especially anal cancer.

Impact:

Medicaid claims data corroborate previous estimates based on registries and clinical cohorts.
A gestão do conhecimento holística
Authors: Corrêa Fábio , Ziviani Fabrício , Carvalho Rodrigo Baroni de , Ribeiro Jurema Suely de Araújo Nery , Ferreira Eric De Paula
Published: May 2020

O paradigma holístico é apontado, de forma recorrente, como uma abordagem a ser utilizada para o desenvolvimento de modelos de Gestão do Conhecimento, visando contemplar o conhecimento em sua integralidade no âmbito organizacional. Diante desta necessidade, esta pesquisa tem por objetivo analisar a aderência do modelo de Tuamsuk, Phabu e Vongprasert (2013) a Gestão do Conhecimento holística. Por meio de procedimentos metodológicos mistos, valendo-se de abordagens qualitativas-quantitativas e do método de Análise de Conteúdo, o referido modelo é examinado. Por resultado, o modelo de Tuamsuk, Phabu e Vongprasert (2013) adere parcialmente as dimensões da Gestão do Conhecimento holística. Isto permite inferir que há necessidade de desenvolvimento de novos modelos que considerem todas as vertentes expressas nesta pesquisa, pois estas são críticas para o sucesso de um gerenciamento do conhecimento holístico. Esta pesquisa contribui por evidenciar um método para análise de modelos desta natureza, permitindo que outros pesquisadores o façam de forma a revelar uma visão mais contundente de como a Gestão do Conhecimento se posiciona frente ao paradigma holístico. Assim, a análise de outros modelos, seguindo os procedimentos metodológicos aqui utilizados, é uma sugestão para pesquisas futuras.
A Classificação Decimal Universal (CDU) na web semântica
Authors: Tomoyose Kazumi , Arakaki Ana Carolina Simionato
Published: May 2020

Sendo o processo de classificação uma das principais atividades englobadas pela Ciência da Informação no que tange à organização da informação, o presente trabalho aborda os conceitos da disciplina de Classificação aplicados na Web Semântica, com foco nos princípios Linked Data, como forma de proporcionar ordem e padronização aos termos a serem usados na ligação de dados, por meio da iniciativa UDC Summary Linked Data. A partir de uma pesquisa exploratória, teórica e aplicada busca-se analisar a presença da iniciativa nas ferramentas de busca dos catálogos dos centros de informação, bem como os benefícios que a mesma proporciona às instituições. Para isso, foram investigados 26 Online Public Access Catalogs (OPACs) a fim de identificar a adoção do UDC Summary Linked Data. Foi possível averiguar que nenhum dos catálogos investigados faz aderência ao UDC Summary Linked Data, além da escassez de produções na literatura que discorram sobre a iniciativa. Levanta-se como possível propulsor à visibilidade do sumário em Linked Data a sua inserção no diagrama Linked Open Data Cloud. Entretanto, a restrição no número de notações que incorporam o UDC Summary Linked Data limita sua adoção, diminuindo a flexibilidade de uso por parte dos centros de informação. Considera-se que a partir da aplicação da iniciativa promove-se uma representação temática mais semântica da informação, beneficiando a descoberta e a visibilidade de diferentes fontes de informação.
The Binding of Isaac in J.R.R. Tolkien and Stephen King
Authors: Selvén Sebastian
Published: May 2020

This article investigates biblical reception in the works of two popular modern fantasy authors. It stages an intertextual dialogue between Genesis 22:1-19, “the binding of Isaac”, and two episodes, in Stephen King’s The Gunslinger and J.R.R. Tolkien’s The Return of the King. After presenting the dynamics of what happens to the biblical text in these two authors and the perspectives that come out, a hermeneutical reversal is then suggested, in which the modern stories are used to probe the biblical text. One can return to the Bible with questions culled from its later reception, in this case King and Tolkien. This article argues that the themes touched upon by the two authors are important and hermeneutically relevant ones, sometimes novel and sometimes contributions to exegetical debates that have been going on for centuries.
The Fall and Rise of Eutychus: The Church of Paul and the Spatial Habitus of Luke
Authors: Smith Eric C.
Published: May 2020

The story of Eutychus in Acts 20 seems to narrate a scene of a Pauline community, meeting for a communal meal and instruction in an insula building in Alexandria Troas. Some scholars have argued, however, that this tale was borrowed by Luke and appropriated to tell the story of Paul. When read through combined theoretical lenses from Michel de Certeau and Pierre Bourdieu, the story of Eutychus provides a window not into one of Paul’s communities, but into Luke’s own spatial practice, and the habitus of community that he knew from his own late-first-century context. Luke therefore repurposed the framework of the story, but also filled the story with his own experience and expectations of space and practice in his creative reconstruction of a Pauline vignette. The tale of Eutychus provides evidence of late-first-century or early-second-century urban Christianity in Asia Minor, not of a community from the life of Paul.
The Experience of Persons with Parkinson’s Disease: a Hermeneutic-Phenomenological Exploration
Authors: Machalaba John W. , Sass Louis
Published: May 2020

This study seeks to understand the subjective experience or lived world typical of patients with Parkinson’s disease (PD). It uses qualitative methodology, grounded in a hermeneutic-phenomenological perspective, to consider lived experience in a small sample of 7 individuals (4 published accounts, 3 subjects interviewed in depth). The analysis identified four themes that appear to be characteristic of the experience of PD: A) Denial, B) Emotion and symptom expression, C) Volitional and spontaneous action, and D) Alteration of temporal perspective. Concepts from existential-phenomenological philosophy (including the notions of “bad faith,” reflective versus pre-reflective experience, being-in-itself versus being-for-itself, and temporality) were used to reflect upon these themes to achieve a synthetic account of the subjective experience of PD. The findings of the study are compared to other findings in the phenomenological literature, and suggestions for further research are posed.
From the King’s Two Bodies to the People’s Two Bodies: Spinoza on the Body Politic
Authors: Terpstra Marin
Published: May 2020

In this article, using Spinoza’s treatment of the image of the political body, I aim to show what happens to the concept of a healthy commonwealth linked to a monarchist model of political order when transformed into a new context: the emergence of a democratic political order. The traditional representation of the body politic becomes problematic when people, understood as individual natural bodies, are taken as the starting point in political theory. Spinoza’s understanding of the composite body, and the assumption that each body is composed, raises the question of the stability or instability of this composition. This has implications for the way one looks at the political order’s conditions of possibility, I argue, and at the same time reveals the imaginary nature of the political body.
Vitamin D Promotes Vascular Endothelial Cell Function via the Regulation of miR-199a-5p
Authors: He Lianman , Wang Yong , Liu Min , Li Ling
Published: May 2020

Essential hypertension (EH) is a main risk factor for cardiovascular disease. Vitamin D (VD) levels are inversely related to hypertension. MicroRNAs (miRNA or miR) are involved in various diseases, including EH. Till now, the role of miR-199a-5p in EH remains unclear. Cell counting
kit-8, flow cytometry and Transwell assay were carried out in the current study to study the effects of VD on the biological behavior of Human umbilical vein endothelial cells (HUVECs). The expression of miR-199a-5p was subsequently determined using reverse transcription-quantitative (RT-q)
PCR. TargetScan prediction and double luciferase reporter gene detection were applied to confirm the binding sites between Sirtuin 1 (SIRT1) and miR-199a-5p. The results showed that VD promoted the proliferation and migration of HUVECs and reduced cell apoptosis. VD was observed to significantly
reduced miR-199a-5p level in HUVECs. Transfection of the miR-199a-5p mimic was indicated to reverse the influence of VD on the proliferation, migration and apoptosis of HUVECs. SIRT1 was also confirmed to be a target gene of miR-199a-5p. Western blot analysis and RT-qPCR were performed to
measure the impact of VD on the SIRT1/AMP-activated protein kinase (AMPK)- /NFB pathway. The results demonstrated that VD increased SIRT1 expression and p-AMPK- and decreased the expression of p-p65, and the transfection of miR-199a-5p mimic reversed these effects. In conclusion, the results
of the current study indicated that VD may relieve EH through promoting vascular endothelial cell function via regulating miR-199a-5p.
Marginal Integrity, Internal Adaptation and Compressive Strength of 3D Printed, Computer Aided Design and Computer Aided Manufacture and Conventional Interim Fixed Partial Dentures
Authors: Al Deeb Laila , Al Ahdal Khold , Alotaibi Ghaith , Alshehri Abdullah , Alotaibi Bader , Alabdulwahab Faris , Al Deeb Modhi , AlFawaz Yasser F. , Vohra Fahim , Abduljabbar Tariq
Published: May 2020

The aim was to investigate the marginal fit, internal adaptation and compressive strength of SLA provisionals (SLA) in comparison to CAD-CAM and conventional (CONV) interim fixed partial dentures (FPDs). Thirty interim FPDs were fabricated using CAD-CAM technology (CAD-CAM blocks Ceramill
TEMP, PMMA), conventional molding technique (CONV) (TrimPlus, PMMA) and Stereolithography (SLA) method (Form 2, Formlabs, PMMA) (n = 10). Internal adaptation (occlusal, coronal, middle and cervical) and marginal integrity (inner and outer edge) was assessed using micro-computerized tomography
(Micro-CT). The failure and compressive strength was assessed by application of a static load at a crosshead speed of 1 mm/min until fracture. Data was analysed using ANOVA and multiple comparisons test. The maximum and minimum marginal mis-fit was for CONV (283.3± 98.6 nm) and CAD-CAM
(68.2± 18.1 m) groups. CAD-CAM (68.2± 18.1 m) and SLA (84.7± 27.5 m) provisionals showed comparable marginal mis-fit (p > 0.05). The mean failure load was significantly higher (p < 0.05) in CAD-CAM (687.86± 46.72 N), compared to SLA (534.8± 46.1 N)
and CONV (492.7± 61.8 N) samples. Compressive strength for CAD-CAM (2.44± 0.27 MPa) samples was significantly higher (p < 0.05) than SLA (1.80± 0.15 MPa) and CONV (1.65± 0.20 MPa) groups. Marginal fit and internal adaptation of SLA printed FPDs was comparable
to CAD-CAM interims. Compressive strength of the SLA interims FPDs can withstand intra-oral loads.
3D Printing of Stem Cell Responsive Ionically-Crosslinked Polyethylene Glycol Diacrylate/ Alginate Composite Hydrogels Loaded with Basic Fibroblast Growth Factor for Dental Pulp Tissue Engineering: A Preclinical Evaluation in Animal Model
Authors: Feng Song , Liu Jingming , Ramalingam Murugan
Published: May 2020

The main aim of this study was to develop a 3D printed stem cell-responsive polyethylene glycol diacrylate (PEGDA) and sodium alginate (SA) composite hydrogel system (PEGDA/SA) loaded with basic fibroblast growth factor (bFGF) suitable for dental pulp tissue engineering. The PEGDA/SA
loaded with bFGF (PEGDA/SA-bFGF) at different concentration ratios were 3D printed via stereolithography (SLA) under optimal processing conditions, followed by ionic crosslinking. The morphological and porous structure of the 3D printed PEGDA/SA-bFGF constructs and release profile of the bFGF
were analyzed. The cellular compatibility of the hydrogel constructs was evaluated using human dental pulp stem cells (hDPSCs)in vitro. Subsequently, biocompatibility and tissue regenerative potential of the hydrogel constructs were evaluated in immunodeficient mice model. The in
vitro cell culture results of PEGDA/SA-bFGF constructs exhibited high cell compatibility and supported cell proliferation, irrespective of their concentration ratios. Thein vivo animal experiment results showed that the hDPSCs-laden PEGDA/SA (PEGDA/SA-hDPSCs) group failed to form
a good pulp structure even at various concentration ratios. When the mass ratio of PEGDA/SA was 25:1, hDPSCs-laden PEGDA/SA-bFGF (PEGDA/SA-bFGF-hDPSCs) group also failed to form dental pulp-like tissue but a partial loose connective tissue formation was observed. However, when the mass ratio
of PEGDA/SA reduces to 20:1 ~ 15:1, the PEGDA/SA-bFGF-hDPSCs group tends to form a well-organized pulp structure post 4 weeks implantation, thus highlighting the potential of this particular hydrogel scaffolding system for dental pulp tissue regenerative applications.
Effect of Long-Chain Non-Coding RNA GAS5 on Osteogenic/Adipogenic Differentiation of Bone Marrow Mesenchymal Stem Cells Under Oxidative Stress Through Targeting MiR-365
Authors: Wu Wenming , Liang Dongming
Published: May 2020

Oxidative stress affects BMSCs. LncRNA GAS5 regulates cell proliferation and apoptosis. However, the effect of LncRNA GAS5 on osteogenesis/adipogenic differentiation of BMSCs under oxidative stress has not been reported. Rat BMSCs were cultured and randomly divided into 4 groups, normal
control group; oxidative stress group; GAS5 siRNA group; GAS5 siRNA+ miR-365 inhibitor group followed by analysis of LncRNA GAS5 expression by Real time PCR, cell proliferation by MTT assay, Caspase3 activity, GAS5 and miR-365 targeting relationship by luciferase reporter assay, ALP activity,
expression of Runx2, OP and PPAR 2 by Real time PCR, as well as ROS content and SOD activity. In oxidative stress group, GAS5 expression was significantly increased along with inhibited cell proliferation, increased Caspase3 activity, decreased ALP activity and the expression of Runx2 and
OP, increased PPAR 2 expression and ROS content, and decreased SOD activity compared to control group (P < 0 05). miR-365 was the target miRNA of GAS5. GAS5 siRNA down-regulated GAS5 expression, significantly promoted cell proliferation, inhibited Caspase3 activity, increased ALP activity
and Runx2 and OP expression, decreased PPAR 2 expression and ROS content, and increased SOD activity. (P < 0 05). However, GAS5 siRNA+ miR-365 inhibitor group reversed the effect of GAS5 siRNA. Oxidative stress promotes LncRNA GAS5 expression in BMSCs. LncRNA GAS5 regulates oxidative stress
by targeting miR-365. Knockdown of GAS5 can promote BMSCs proliferation and osteogenic differentiation and inhibit adipogenic differentiation under oxidative stress.
Distal Low Homeobox 3 Promotes Bone Marrow Mesenchymal Stem Cells Osteogenic Differentiation and Bone Synthesis and Ameliorates Osteoporosis by Activating Typical Wnt Signaling
Authors: Xu Yongyi , Chen Lei
Published: May 2020

The distal low homeobox 3 (DLX3) regulates the bone marrow mesenchymal stem cells (BMSC) osteogenic differentiation. However, whether DLX3 affects osteoporosis (OP) remains unclear. An OVX-induced OP rat model was constructed and DLX3 plasmid was injected followed by analysis of bone
mineral density and ALP activity. Rat BMSCs were isolated and divided into control group, OP group and DLX3 group (transfected with DLX3 plasmid) followed by analysis of chondrocytes survival rate by MTT assay, Caspase 3 activity, type I collagen and Osterix expression by Real time PCR and
-catenin level by Western blot. DLX3 expression was significantly down-regulated in OP rats with deceased bone density and ALP activity compared to sham group (P < 0 05). When DLX3 was transfected into OP rats, DLX3 expression was significantly up-regulated with increased bone density and
ALP activity compared with OP group (P < 0 05). BMSCs survival was significantly decreased in OP group and Caspase 3 activity was significantly increased with downregulated type I collagen, Osterix and -catenin (P < 0 05). However, transfection of DLX3 plasmid into OP group BMSCs cells
can significantly reverse the above changes, compared to OP group (P < 0 05). DLX3 expression is reduced in osteoporosis. Up-regulation of DLX3 can promote osteogenic differentiation of BMSCs by regulating typical Wnt signaling, promote differentiation into osteoblasts, increase bone density
increase, and then ameliorate osteoporosis.
Cloud Based Smart Parking System
Authors: Sathya V. , Bheemanadham  , Sai Surya , Tharad Arpit , Kumar Ayush , Kumar Suraj , Verma Utkarsh
Published: May 2020

Lately, the idea of brilliant urban communities has increased awesome notoriety. Parking becomes one of the tedious tasks in our day to day life. Many efforts have been done in this field to solve parking based problems like traffic congestion, limited parking space, high parking charges,
and the most basic problem is to find nearby parking space. In this paper, we proposed an algorithm that increases the efficiency of the current cloud-based smart parking system and develops a network architecture based on Internet-Of-Things technology. Our proposed system helps users automatically
find a free parking space at the least cost based on new performance metrics to calculate the user parking cost by considering the distance from the user to parking area and the total number of free places in each car park. A mobile application is provided that navigate the user to the free
parking space based on the efficiency based on distance and cost. This cost will be utilized to offer an answer of finding an accessible parking spot upon a demand by the client and an answer of proposing another car park if the present park is full.
Stock Market Prediction Using Machine Learning
Authors: Shiva Nandhini J. , Bari Chitrak , Pradip Gareja
Published: May 2020

The basic tool aimed at increasing the rate of investor’s interest in stock markets is by developing a vibrant application for analyzing and predicting stock market prices. In this report we explain, the development and implementation of a stock market price prediction application
using machine learning algorithm. In this report, we try to analyze existing and new methods of stock market prediction. We take three different approaches for solving the problem: Fundamental analysis, Technical Analysis and The application of Machine Learning. We found evidence in support
of the weak form of the Efficient Market Hypothesis. We can use Fundamental Analysis and Machine Learning to guide an investor’s decisions. We demonstrate a common flaw in Technical Analysis methodology to show that it produces limited useful information. Based on our findings, algorithmic
trading programs are developed and simulated using Quant. During the past few decades, various machine learning techniques have been applied to study the highly theoretical and speculative nature of stock market by capturing and using repetitive patterns. Different companies use different
types of analysis tools for forecasting and the main aim is the accuracy, with which they predict which set of stocks would yield the maximum amount of profit.
Data Mining and 3D Imaging Applications in Agricultural Field Analysis
Authors: Sathish K. , Arun Kumar S. , Deb Aniruddha , Ramakrishna Santhosh
Published: May 2020

Historically scientific and technological advances have impacted the agriculture industry with early farmers improving their harvest by inventing the first hoes. Today farmers improved crop production by using varied IOT and Data Mining Solutions. Earlier a wide range of 3D vision technologies
were used each with their specific advantages and drawbacks; examples include: stereo vision, laser triangulation, photometric stereo and RGB-D cameras. The following paperwork utilizes Data Mining and spectral analysis to produce a novel predictive analytics model to perform floor optimization
and increase harvest profit throughput to enable effective distribution of optimal farming strategies to a wider agrarian diaspora.
Real Time Automation of Agriculture for Detecting Plant Diseases
Authors: Priya Shiva , Alekha M. , Saikiran U. , Sivakrishnateja T. , Kasikumar Reddy B.
Published: May 2020

In agricultural land, there are lot of plants affected by number of diseases. Just like we can get sick, plants can get sick too and sometimes, the same type of things that make us sick can affect our green companions. A sick plant can even look under the weather. Its leaves may wilt
or have holes in it. Early data on leaf well-being and sickness discovery can encourage the control of illnesses through legitimate administration techniques. If not treated, these plants may succumb to the disease and perish. Pathogens are any organism that makes plants ill, whether it be
another animal such as an insect, or smaller organisms such as bacteria and viruses. Normally we have to check each and every plant to identify the plant disease. And we treat disease by various methods like MILK SPRAY, ELDER LEAF SPRAY, HORSERADISHSPRAY, BAKING SODA… etc. This proposed
system solves these problems so that we can automatically detect plant diseases and can apply self-treatment. This paper presents a method for early detection of leaf diseases in plants based on some important features extracted from its leaf images. Here we use BEAGLE BONE BLACK DEVICE which
stores healthy leaf images and compare it with current images which is called IMAGE PROCESSING. So after image processing, if the disease leaves are found, then it enables auto medicining. Medicine supply is enabled through Sprinkler or Drip irrigation method, climatic conditions. To avoid
spreading the diseases, Temperature sensors and moisture sensors are used. These sensors control spreading diseases.
Automatic Street Light System
Authors: Subashini P. , Sivaramchaitanya A. , Sivasai P. , Sai Teja J. V. V. L. , Hemanshureddy A.
Published: May 2020

This project provides the simplest answer for power wastage. Conjointly the manual operation of the lighting system is totally replaced. In this project the LDR sensor is used to point a day/night time and also the microcontroller is used which is able to detect brightness of sunlight
and the GSM module that acts on back side. The microcontroller Arduino board is employed as brain which is to manage the road lightweight system, The programming language used for developing the microcontroller is C language. The most important aim of the project is to avoid wasting the ability,
by exploitation effectively we are able to save a lot of power, as we all know that there’s large scale shortage of power these days in everyplace especially in villages. So, to beat that shortage we are able replace the manual street lights system with the intelligent systems. therefore
in future we are able to style more advanced technologies to avoid wasting power.
The New Age of Democracy—Voting System
Authors: Sreeram Atmakuri , Kiran Kumar L. , Natarajan Jayakrishna , Ashwini C.
Published: May 2020

Elections are one of the biggest events to take place in any democratic country. In India, which has a population of 1.2 Billion, elections are especially important as it selects the leader of about one-sevenths of the World’s Population. The usual method of voting is through
the use of Electronic Voting Machines (EVM). In this modern era, where technology is being used in every sphere of life, considering the fact that Voting is one of the fundamental rights of every citizen of a democratic country, technology should be used to stop any unfair means being used
in the elections. The objective of this project is to develop a system which will be suitable for elections in countries like India. In this project we use Arduino and Finger Print Scanner which will identify its voters and prevent digital malpractices. We also propose a mobile application
which will enable the voters to cast their vote from anyplace they want. The proposed system is more digital, technology-based and secure.
Design Optimisation for Modified Series-Parallel Resonant Converter
Authors: Tanavade Satish S. , Suresh Manic K.
Published: May 2020

Optimum design with systematic design procedure for a resonant converter is presented in this paper. For the converter design with high efficiency constraint of minimum power losses loss and cost are considered. For reducing the size of the converter, an integrated structure of high
frequency transformer-inductor is proposed. A step-by-step systematic procedure for designing the converter is presented that results in high input line power factor and reduction of the stresses on the components of resonant tank circuit of the converter is given. Simulation and experimental
results on a prototype of modified series-parallel resonant converter (MSPRC) are presented to validate the optimum design procedure.
Heuristic Algorithm Assisted Controller Design for Nonlinear Type Liquid Level Process
Authors: Suresh Manic K. , Tanavade Satish S.
Published: May 2020

In process control industries, controlling the liquid inside the non-linear tanks such as a conical tank, hopper tank and spherical tank is a highly challenging task due to the change in the cross section area of the tank. The aim of this project is to design a suitable controller to
control the level of the hopper type tank by using conventional controllers like Ziegler-Nichols tuning method (ZN) and computational controllers using metaheuristic algorithms such as Bacteria Foraging Optimization (BFO) algorithm, Particle Swarm Optimization (PSO) algorithm and Firefly Algorithm
(FA). This controller can be used for the industries that deal with this nonlinear type of process. The mathematical model for the conical tank was done to identify the transfer function of the system. The conventional and computational controllers were designed and implemented using MATLAB/Simulink
to choose the best controller for the conical/hopper type tank liquid level process based on the time domain specifications such as rise time, settling time and peak overshoot percentage. Moreover, the performance of the system was analyzed based on the error indices such as Integral Square
Error (ISE), Integral Absolute Error (IAE), Integral Time Square Error (ITSE) and Integral Time Absolute Error (ITAE). Also, servo and regulatory operations were tested for the chosen best controller.
Design of Combinational Circuits Using Reversible Decoder in Tanner Tools
Authors: Kannan R. , Vidhya K.
Published: May 2020

Reversible logic is the emerging field for research in present era. The aim of this paper is to realize different types of combinational circuits like full-adder, full-subtractor, multiplexer and comparator using reversible decoder circuit with minimum quantum cost. Reversible decoder
is designed using Fredkin gates with minimum Quantum cost. There are many reversible logic gates like Fredkin Gate, Feynman Gate, Double Feynman Gate, Peres Gate, Seynman Gate and many more. Reversible logic is defined as the logic in which the number output lines are equal to the number of
input lines i.e., the n-input and k-output Boolean function F(X1,X2,X3, ...,Xn) (referred to as (n,k) function) is said to be reversible if and only if (i) n is equal to k and (ii) each input pattern is mapped uniquely to output pattern.
The gate must run forward and backward that is the inputs can also be retrieved from outputs. When the device obeys these two conditions then the second law of thermo-dynamics guarantees that it dissipates no heat. Fan-out and Feed-back are not allowed in Logical Reversibility. Reversible
Logic owns its applications in various fields which include Quantum Computing, Optical Computing, Nano-technology, Computer Graphics, low power VLSI etc. Reversible logic is gaining its own importance in recent years largely due to its property of low power consumption. The comparative study
in terms of garbage outputs, Quantum Cost, numbers of gates are also presented. The Circuit has been implemented and simulated using Tannaer tools v15.0 software.
A Study of Hand Gesture Segmentation Techniques for Sign Languages
Authors: Gobhinath S. , Vignesh T. , Pavankumar R. , Kishore R. , Koushik K. S.
Published: May 2020

This paper presents about an overview on several methods of segmentation techniques for hand gesture recognition. Hand gesture recognition has evolved tremendously in the recent years because of its ability to interact with machine. Mankind tries to incorporate human gestures into modern
technologies like touching movement on screen, virtual reality gaming and sign language prediction. This research aims towards employed on hand gesture recognition for sign language interpretation as a human computer interaction application. Sign Language which uses transmits the sign patterns
to convey meaning by hand shapes, orientation and movements to fluently express their thoughts with other person and is normally used by the physically challenged people who cannot speak or hear. Automatic Sign Language which requires robust and accurate techniques for identifying hand signs
or a sequence of produced gesture to help interpret their correct meaning. Hand segmentation algorithm where segmentation using different hand detection schemes with required morphological processing. There are many methods which can be used to acquire the respective results depending on its
advantage.
The Impact of Effective Relationship Between Production and Sales
Authors: Anbarasi M. , Praveen Kumar S.
Published: May 2020

Production and sales are key component for the success of any organizations. In past there are many research conducted to study the relationship between sales and production (D. H. Parante et al., 2002). Many of these studies have emphasized on quality and customer satisfaction which
is the important aspect for increased sales and profitability. The focus of this paper is to highlight how production and sales is interrelated and the use of value chain in connecting these two activities.
Power Factor Correction Using Sensorless Brushless DC Motor with Bridgeless Converter Topology
Authors: Arunkumar U. , Radhakrishnan G. , Boobalan S. , Kishore J.
Published: May 2020

In this paper the regulation of brushless drives is attained by developing a new technique called hysteretic comparator with desirable standard of power at supply mains. By this methodology the composite difference of output due to noises or undulation are avoided and the phase delay
is recompensed. Fuzzy logic improves the robustness with enhancement in the consistent performance of the system. The proposed regulator operates in intermittent conduction mode which helps the accomplishment of power factor nearer unity at supply ends. Moreover absence of DBR framework offer
minimized switching losses. The proposed system is developed using MATLAB 2013 and with an experiment model. Thus the harmonics are minimized and the compatible limits of various international standards like IEC 61000-3-2 and IEEE-519 standards are attained.
Design and Experimental Analysis of Composite Material with Piezoelectric Layer
Authors: Fredrick Gnanaraj F. , Vijaya Kumar K. R.
Published: May 2020

The main objective of this work is to analyze the active vibration control using smart sensors and actuators in a laminated E-Glass/epoxy cyanate composite beam. The cantilevered composite beam has piezoelectric ceramic patches as smart sensors and actuators. Hand layup technique for
vibration suppression is done on the fabricated E-Glass/Epoxy-cyanate composite laminated beam. Experimental modal testing is performed to achieve vibration suppression on the flexible composite beam bonded with seven circular type piezoelectric actuator elements and seven circular type sensor
elements. The complete vibration suppression utilizes a data acquisition system, a real-time control system, and a functional generator, in addition to the composite beam with PZT sensor and actuator. The data acquisition hardware consists of model NI 9233 (4 channel +5 V 24 Bit IEPE Analog
input I2VA 1-to earth ground).
Comparison and Performance Evaluation of Prime Number Generation Using Sieves Algorithm
Authors: Umadevi V. , Sivakami K.
Published: May 2020

People are used prime numbers in secret codes to secure the message and data. Prime numbers are essential in computer security problem to perform certain operations over the Internet. It can be used for encryption. The larger the prime number used, the intricate it is to decipher the
code. So finding the “massive” prime number is a current problem. One of the most widely used applications of prime number in computing is the RSA encryption system. A prime sieve is a fast type of algorithm for finding prime numbers. Sieve of Eratosthenes, Sieve of Sundaram and
Sieve of Atkins are the algorithms that can be used to generate prime numbers. This research paper is to study and testing to find out, which algorithm is better used for large prime numbers in terms of time complexity. The prime sieve algorithm is coded in java language and the results are
summarized.
Secured Routing Using Neighbour Coverage with Minimum Overhead in Ad Hoc Networks
Authors: Bindhu M. , Jackson Beulah , Asha S.
Published: May 2020

A wireless ad hoc network is a dispersed type of wireless network. The network is called as ad hoc as it does not rely on any pre existing infrastructure. Routing decisions are ready by node itself, so the determination of which node to forward data is prepared dynamically based on
network connectivity. The overhead of a route discovery cannot be neglected. In this, Neighbour coverage protocol proposes for reducing routing overhead and to utilize the neighbour coverage knowledge and the probabilistic mechanism, which can radically decrease the number of retransmissions
to reduce the routing overhead, and can also improve the routing performance. Due to high mobility of nodes in ad hoc networks, there exist regular link breakages, which lead to frequent path failures and route discoveries. ALERT dynamically partitions the network field into zones and arbitrarily
chooses nodes in zones as intermediate relay nodes, which form a non-traceable unsigned route. In addition, it conceals the data initiator/receiver among many initiators/receivers to build up source and destination anonymity protection. Thus, ALERT offers anonymity security to sources, destinations,
and routes for effective counter intersection and timing attacks and overheads are reduced.