bluuebunny/crossref_metadata_2025 huggingface dataset:
On the Transient Atomic/Heat Diffusion in Cylinders and Spheres with Phase Change: A Method to Derive Closed-Form Solutions
Authors: Ferreira I. L. , Garcia A. , Moreira A. L. S.
Published: February 2021

Analytical solutions for the transient single-phase and two-phase inward solid-state diffusion and solidification applied to the radial cylindrical and spherical geometries are proposed. Both solutions are developed from the differential equation that treats these phenomena in Cartesian coordinates, which are modified by geometric correlations and suitable changes of variables to achieve closed-form solutions. The modified differential equations are solved by using two well-known closed-form solutions based on the error function, and then equations are obtained to analyze the diffusion interface position as a function of time and position in cylinders and spheres. These exact correlations are inserted into the closed-form solutions for the slab and are used to update the roots for each radial position of the moving boundary interface. The predictions provided by the proposed analytical solutions are validated against the results of a numerical approach. Finally, a comparative study of diffusion in slabs, cylinders, and spheres is also presented for single-phase and two-phase solid-state diffusion and solidification, which shows the importance of the effects imposed by the radial cylindrical and spherical curvatures with respect to the Cartesian coordinate system in the process kinetics. The analytical model is proved to be general, as far as, a semi-infinite solution for diffusion problems with phase change exists in the form of the error function, which enables exact closed-form analytical solutions to be derived, by updating the root at each radial position the moving boundary interface.
Evaluation of Thymic Output and Regulatory T Cells in Kidney Transplant Recipients with Chronic Antibody‐Mediated Rejection
Authors: Shahi Abbas , Salehi Saeedeh , Afzali Shima , Gol Mohammad Pour Afrakoti Ladan , Esmaeili Marzie , Bagherpour Farzaneh , Aghsaeifard Ziba , Dehghani Sanaz , Pourmand Gholamreza , Amirzargar Ali Akbar
Published: February 2021

Background. Regulatory T cells (Tregs) and recent thymic emigrants (RTEs) have an essential role in the regulation of allogeneic immune responses. However, their mechanisms of action in chronic antibody‐mediated rejection (cAMR) are still unclear. In this study, we aimed to compare Treg and RTE levels between stable graft function (SGF) patients and cAMR subjects after kidney transplantation. Method. Mononuclear cells (MNs) were separated from peripheral blood, and flow cytometry analysis was performed for detection of CD4+ and CD25high as Treg markers and CD4+, CD31+, and CD45RA+ as RTE immunophenotyping markers. Result. The level of peripheral Treg cells was significantly lower in cAMR subjects in comparison to stable graft function patients. Moreover, SGF patients who had received cyclosporine A had a higher level of Treg in comparison to the tacrolimus recipients. Nevertheless, the RTE level between SGF and cAMR patients did not show any significant differences. Conclusion. It seems that Treg cells are significantly associated with transplant outcomes in cAMR patients, and prescribed immunosuppressive drugs can influence the frequency of this crucial subset of T cells. Although these drugs are beneficial and inevitable for allograft maintenance, more investigations are needed to elucidate their complete effects on different immune cell subsets which some of them like Tregs are in favor of transplant tolerance. Besides, the thymic output is seemingly not a beneficial biomarker for predicting cAMR; however, more in vivo and in vitro studies are needed for revealing the precise role of Tregs and RTEs in the transplantation context.
Durability and Reliability Estimation of Flax Fiber Reinforced Composites Using Tweedie Exponential Dispersion Degradation Process
Authors: Yan Weian , Riahi Hassen , Benzarti Karim , Chlela Robert , Curtil Laurence , Bigaud David
Published: February 2021

Flax fiber reinforced composites are demonstrating promising outcomes which make them potential candidates to replace synthetic composites in various industrial applications. However, there is limited information regarding their long-term performance, and it is usually acknowledged that natural fibers are less resistant than their synthetic counterparts. In this context, it is crucial to study their durability before considering their use for structural rehabilitation and strengthening in construction. This research aims to study and predict the performance of flax fiber reinforced polymer (FFRP) composites with a biobased epoxy matrix. The test program consists in exposing FFRP laminates and FFRP strengthened concrete slabs to different accelerated ageing conditions over a total period of two years. In the present study, not a single stress variable but various combinations and coupling of two environmental stress variables, temperature (T) and relative humidity (RH), are considered, thereby distinguishing this study from most of the works reported in the literature. Then, a series of mechanical destructive tests are performed periodically on aged samples to evaluate property evolutions over ageing time. The collected experimental data are analyzed to develop a performance evolution model and to evaluate the service lifetime performance of this new biobased FFRP composite. For that, the potential of the Tweedie exponential dispersion (TED) process model, which takes some famous stochastic processes (Wiener process, Gamma process, and inverse Gaussian process) as special cases, is investigated. The TED process modeling, particularly interesting in the cases of complicated degradation mechanisms, is written here for destructive tests and, finally, a reliability analysis based on the TED process model determined is carried out in order to update the FRP design equations provided by international codes in the specific case of FFRP.
Study on the Mechanical Effect and Constitutive Model of Montmorillonite under the Action of Acid Rain: A Case Study on Montmorillonite‐Quartz Remolded Soil
Authors: Li Li , Liu Jian , Xu Xingqian
Published: February 2021

Clay minerals are the common insoluble cementing substances in soil. To study the mechanical effect of montmorillonite under the action of acid rain, the variation law and mechanism of the cohesive force and internal friction angle were discussed by immersing montmorillonite‐quartz remolded soil in HNO3 solution with pH = 3. It was found that, under acidic conditions, the cohesive force increased after the first drop and subsequently decreased again, while the internal friction angle remained basically unchanged. Considering the vertical pressure of soil landslide, the change in the shear strength of cohesive soil under acid rain is consistent with the change in the cohesive force. The X‐ray diffraction (XRD) results showed that the acid could erode the cement‐montmorillonite, and no new substance was generated, which caused a decrease in cohesion. In addition, based on the microcementation nature of montmorillonite and the change mechanism of cohesion under acid rain, the cohesive force model of saturated montmorillonite‐quartz remolded soil under acid rain was established. The change trend of calculated cohesion values was consistent with the one of measured values, and the error was small.
Improving the Accuracy for Analyzing Heart Diseases Prediction Based on the Ensemble Method
Authors: Gao Xiao-Yan , Amin Ali Abdelmegeid , Shaban Hassan Hassan , Anwar Eman M.
Published: February 2021

Heart disease is the deadliest disease and one of leading causes of death worldwide. Machine learning is playing an essential role in the medical side. In this paper, ensemble learning methods are used to enhance the performance of predicting heart disease. Two features of extraction methods: linear discriminant analysis (LDA) and principal component analysis (PCA), are used to select essential features from the dataset. The comparison between machine learning algorithms and ensemble learning methods is applied to selected features. The different methods are used to evaluate models: accuracy, recall, precision, F‐measure, and ROC.The results show the bagging ensemble learning method with decision tree has achieved the best performance.
Development and Application of an Intelligent Evaluation and Control Platform for Tunnel Smooth Blasting
Authors: Zou Baoping , Luo Zhanyou , Wang Jianxiu , Hu Lisheng
Published: February 2021

Many tunnels around the world are still being constructed by drilling and blasting because these methods have an unmatched degree of flexibility relative to machine excavations using tunnel boring machines. At present, a large gap exists between evaluation theory and the control application of tunnel smooth blasting (TSB) quality. In this study, a handheld mobile platform that is based on the Android system and is written in the Java language is proposed to evaluate and control the performance of TSB. The function of this handheld mobile platform mainly includes data input, data modification, data deletion, weight setting for smooth blasting evaluation, smooth blasting quality assessment, and smooth blasting quality control. Using the proposed mobile platform, end users can evaluate and control TSB quality after each blast. The proposed handheld mobile platform is also applied to the real case history of line 6 in Guangzhou, China.
Stability of Milling Process with Variable Spindle Speed Using Runge–Kutta-Based Complete Method
Authors: Lv Shujie , Zhao Yang
Published: February 2021

The variable-spindle-speed (VSS) technique is effective in preventing regenerative chatter in milling processes. However, spindle-speed-modulation parameters should be deliberately selected to augment the material removal rate. Stability-prediction algorithms of stability predicting play an important role in this respect, as they allow the prediction of stability for all ranges of a given spindle speed. The increase in calculation time in variable-spindle-speed milling, which is caused by the modulation frequency, hinders its practical use in the workshop. In this paper, a Runge–Kutta-based complete discretization method (RKCDM) is presented to predict the stability of milling with variable spindle speeds, which is described by a set of delay differential equations (DDEs) with time-periodic coefficients and time-varying delay. The convergence and calculation efficiency are compared with those of the semidiscretization method (SDM) under different testing configurations and milling conditions. Results show that RKCDM is more accurate and saves at least 50% of the calculation time of SDM. The effects of modulation parameters on the stability of VSS milling are explored through stability lobe diagrams produced from RKCDM.
Comparison of Blood and Tissue Eosinophil Count and Blood IgE in Patients with Chronic Sinusitis and Nasal Polyps
Authors: Asghari Masoud , Izadpanahi Shadi , Esfahani Mina Heidari
Published: February 2021

Background. The inflammatory mucosa of the sinus cavities is called sinusitis and is divided into various types based on its appearance and sign. Chronic rhinosinusitis is an inflammatory-infectious disease that involves the frontal, sphenoid, ethmoid, and maxillary sinuses. Chronic sinusitis is a multifactorial disease and the range of causes varies from environmental factors to genetic factors. The purpose of this study was to compare blood and tissue eosinophils and serum IgE levels in patients with chronic sinusitis with nasal polyp in Vali-e-Asr hospital in 1397. Methods. In this descriptive-analytical study, the population under study included those with chronic sinusitis referred to Birjand Valiasr Hospital in 1397.3 cc of blood samples were taken 1 day before surgery to evaluate eosinophil counts and serum IgE levels. Also, samples taken from patients during surgery were counted, and then, 100 cells were counted, and eosinophil counts and percentages were calculated. The data were entered into the SPSS software after data collection. Results. This study was performed on 70 patients with chronic rhinosinusitis which included 43 men (61.4%) and 27 women (38.6%) with mean age of

39.11
±
13
 
13.72

years. There was no significant difference between sex of patients and mean serum IgE level (

P
<
0.05

). The mean percentage of eosinophils in blood samples and tissues of patients with chronic sinusitis was significantly increased with the increase in CT scan (

P
<
0.05

). Conclusions. Tissue or blood eosinophilia was not observed in patients with chronic rhinosinusitis. Also, the mean eosinophil percentage of blood and tissue increased significantly in patients with increased scanning computed tomography (

P
<
0.05

).
Finding Radial Network Configuration of Distribution System Based on Modified Symbiotic Organisms Search
Authors: Thanh Nguyen Thuan , Ngo Thanh-Quyen , Duong Thanh Long , Nguyen Thang Trung
Published: February 2021

Network reconfiguration (NR) is one of the most effective methods to reduce line power loss in the distribution system, which causes higher losses than the other parts of the power system. This paper proposes a modified symbiotic organisms search (MSOS) algorithm to solve the NR problem. For the purpose of enhancing the effectiveness of MSOS, the mutualism and parasitism strategies of the original symbiotic organisms search (SOS) have been modified to create better new solutions. In the mutualism strategy, the so‐far best solution is updated immediately as soon as new solutions are created. In the parasitism strategy, the update is only implemented for the first half of control variables, whereas another half still remains unchanged. The comparison results between MSOS and SOS on twenty‐five benchmark functions and different scales of test distribution systems with 14, 33, 69, and 119 nodes show that the improvement level of MSOS over SOS is significant with higher success rates and better quality of gained solutions. Similarly, MSOS also reaches better results than other methods in the literature. Consequently, MSOS can be a favorable method for determining the most appropriate configurations for the distribution systems.
Acupuncture at Back-Shu and Front-Mu Acupoints Prevents Gastric Ulcer by Regulating the TLR4/MyD88/NF-κB Signaling Pathway
Authors: Li Li , Zang Hao , Jiang Yang , Zhang Yue , Mu Shuangshuang , Cao Jiazhen , Qu Ying , Wang Zhaohui , Qi Wei
Published: February 2021

Purpose. To assess the preventive effects of acupuncture at back-shu and front-mu acupoints on rats with restraint water-immersion stress (RWIS)-induced gastric ulcer. Methods. Thirty-six rats were randomly divided into four groups for 10 days of treatment as follows: the normal group received no treatment; the model group received RWIS-induced gastric ulcer; the omeprazole group was administered omeprazole orally every 2 days; and the electroacupuncture group received electroacupuncture at the RN12 and BL21 acupoints every 2 days. After 10 days of treatment, except for the normal group, all rats were induced with gastric ulcer by RWIS for 3 h. The ulcer index (UI), ulcer inhibition rate, and histopathological score were calculated. We determined the levels of tumor necrosis factor (TNF)-α and interleukin (IL)-6 in serum, and the activities of myeloperoxidase (MPO), malondialdehyde (MDA), superoxide dismutase (SOD), nitric oxide (NO), and glutathione peroxidase (GSH-Px) in serum and gastric tissues. Protein expression of MyD88, nuclear factor (NF)-κB (p65), and toll-like receptor (TLR) 4 was quantified in gastric tissues. Results. The electroacupuncture and omeprazole groups were equivalent in terms of UI, ulcer inhibition rate, and histopathological score. The serum levels of TNF-α and IL-6 were significantly lower in the electroacupuncture group compared with the omeprazole group (

P

 < 0.05). Compared with the model group, there were significant changes in the levels of NO, MPO, GSH-Px, and MDA in all other groups, while the expression of TLR4, MyD88, and NF-κB p65 in gastric tissue decreased significantly in the electroacupuncture group. The expression of TLR4 was substantially lower in the electroacupuncture group compared with the omeprazole group. Conclusion. Acupuncture at back-shu and front-mu acupoints played a role in preventing gastric ulcer by inhibiting extracellular signals, stimulating kinases in serum and gastric tissues, and activating the inhibition of the TLR4 signaling pathway.
Glowworm Swarm Optimization Algorithm- and K-Prototypes Algorithm-Based Metadata Tree Clustering
Authors: Li Yaping
Published: February 2021

The main objective of this paper is to present a new clustering algorithm for metadata trees based on K-prototypes algorithm, GSO (glowworm swarm optimization) algorithm, and maximal frequent path (MFP). Metadata tree clustering includes computing the feature vector of the metadata tree and the feature vector clustering. Therefore, traditional data clustering methods are not suitable directly for metadata trees. As the main method to calculate eigenvectors, the MFP method also faces the difficulties of high computational complexity and loss of key information. Generally, the K-prototypes algorithm is suitable for clustering of mixed-attribute data such as feature vectors, but the K-prototypes algorithm is sensitive to the initial clustering center. Compared with other swarm intelligence algorithms, the GSO algorithm has more efficient global search advantages, which are suitable for solving multimodal problems and also useful to optimize the K-prototypes algorithm. To address the clustering of metadata tree structures in terms of clustering accuracy and high data dimension, this paper combines the GSO algorithm, K-prototypes algorithm, and MFP together to study and design a new metadata structure clustering method. Firstly, MFP is used to describe metadata tree features, and the key parameter of categorical data is introduced into the feature vector of MFP to improve the accuracy of the feature vector to describe the metadata tree; secondly, GSO is combined with K-prototypes to design GSOKP for clustering the feature vector that contains numeric data and categorical data so as to improve the clustering accuracy; finally, tests are conducted with a set of metadata trees. The experimental results show that the designed metadata tree clustering method GSOKP-FP has certain advantages in respect to clustering accuracy and time complexity.
RNA Modification by m6A Methylation in Cardiovascular Disease
Authors: Chen Jun , Wei Xiang , Yi Xin , Jiang Ding-Sheng
Published: February 2021

Cardiovascular disease is currently the leading cause of death worldwide, and its underlying regulatory mechanisms remain largely unknown. N6‐Methyladenosine (m6A) RNA methylation is an epigenetic modification involved in the splicing, nuclear export, translational regulation, and degradation of RNA. After the initial identification of m6A RNA methylation in 1974, the rise of next‐generation sequencing technology to detect m6A throughout the transcriptome led to its renewed recognition in 2012. Since that time, m6A methylation has been extensively studied, and its functions, mechanisms, and effectors (e.g., METTL3, FTO, METTL14, WTAP, ALKBH5, and YTHDFs) in various diseases, including cardiovascular diseases, have rapidly been investigated. In this review, we first examine and summarize the molecular and cellular functions of m6A methylation and its readers, writers, and erasers in the cardiovascular system. Finally, we discuss future directions for m6A methylation research and the potential for therapeutic targeting of m6A modification in cardiovascular disease.
Sizing a Hybrid Renewable Energy System by a Coevolutionary Multiobjective Optimization Algorithm
Authors: Li Wenhua , Zhang Guo , Yang Xu , Tao Zhang , Xu Hu
Published: February 2021

Hybrid renewable energy system (HRES) arises regularly in real life. By optimizing the capacity and running status of the microgrid (MG), HRES can decrease the running cost and improve the efficiency. Such an optimization problem is generally a constrained mixed‐integer programming problem, which is usually solved by linear programming method. However, as more and more devices are added into MG, the mathematical model of HRES refers to nonlinear, in which the traditional method is incapable to solve. To address this issue, we first proposed the mathematical model of an HRES. Then, a coevolutionary multiobjective optimization algorithm, termed CMOEA‐c, is proposed to handle the nonlinear part and the constraints. By considering the constraints and the objective values simultaneously, CMOEA‐c can easily jump out of the local optimal solution and obtain satisfactory results. Experimental results show that, compared to other state‐of‐the‐art methods, the proposed algorithm is competitive in solving HRES problems.
Six Glycolysis‐Related Genes as Prognostic Risk Markers Can Predict the Prognosis of Patients with Head and Neck Squamous Cell Carcinoma
Authors: Chen LangXiong , He XiaoSong , Yi ShiJiang , Liu GuanCheng , Liu Yi , Ling YueFu
Published: February 2021

Objective. Head and neck squamous cell carcinoma (HNSCC) is one of the worst‐prognosis malignant tumors. This study used bioinformatic analysis of the transcriptome sequencing data of HNSCC and the patients’ survival and clinical data to construct a prediction signature of glycolysis‐related genes as the prognostic risk markers. Methods. Gene expression profile data about HNSCC tissues (n = 498) and normal tissues in the head and neck (n = 44) were got from The Cancer Genome Atlas (TCGA), as well as patients’ survival and clinical data. Then, we obtained core genes; their expression in head and neck squamous cell carcinoma tissues is significantly different from that in normal head and neck tissues. The predicted glycolysis‐related genes are screened through univariate Cox regression analysis, and then, the prognostic risk markers were constructed through further correction of multivariate Cox regression analysis. The Kaplan‐Meier curve and receiver operating characteristic curve are used to analyze the potential value of these risk markers in diagnosis and prognosis. We also evaluated that the glycolysis‐related prognostic risk markers composed of 6 oncogenes are correlated with clinical features, such as age, gender, grade, and clinical stage of the tumor, by univariate and multivariate Cox regression analyses. Results. Differentially expressed glycolytic genes in HNSCC tissues and normal head and neck tissues were screened from TCGA databases using the bioinformatic method. We confirmed a set of six glycolytic genes that were significantly associated with OS in the test series. According to our analysis, the prognostic risk markers composed of HPRT1, STC2, PLCB3, GPR87, PYGL, and SLC5A12 may be an independent risk factor for the prognosis of HNSCC. Conclusions. Through this analysis, we constructed new prognostic risk markers related to glycolysis as a prognostic risk marker for patients with HNSCC and provided new ideas and molecular targets for the research and individualized treatment of HNSCC.
Improved Whale Optimization Algorithm for Solving Constrained Optimization Problems
Authors: Ning Gui-Ying , Cao Dun-Qian
Published: February 2021

In view of the shortcomings of the whale optimization algorithm (WOA), such as slow convergence speed, low accuracy, and easy to fall into local optimum, an improved whale optimization algorithm (IWOA) is proposed. First, the standard WOA is improved from the three aspects of initial population, convergence factor, and mutation operation. At the same time, Gaussian mutation is introduced. Then the nonfixed penalty function method is used to transform the constrained problem into an unconstrained problem. Finally, 13 benchmark problems were used to test the feasibility and effectiveness of the proposed method. Numerical results show that the proposed IWOA has obvious advantages such as stronger global search ability, better stability, faster convergence speed, and higher convergence accuracy; it can be used to effectively solve complex constrained optimization problems.
Online Optimal Control of Robotic Systems with Single Critic NN‐Based Reinforcement Learning
Authors: Long Xiaoyi , He Zheng , Wang Zhongyuan
Published: February 2021

This paper suggests an online solution for the optimal tracking control of robotic systems based on a single critic neural network (NN)‐based reinforcement learning (RL) method. To this end, we rewrite the robotic system model as a state‐space form, which will facilitate the realization of optimal tracking control synthesis. To maintain the tracking response, a steady‐state control is designed, and then an adaptive optimal tracking control is used to ensure that the tracking error can achieve convergence in an optimal sense. To solve the obtained optimal control via the framework of adaptive dynamic programming (ADP), the command trajectory to be tracked and the modified tracking Hamilton‐Jacobi‐Bellman (HJB) are all formulated. An online RL algorithm is the developed to address the HJB equation using a critic NN with online learning algorithm. Simulation results are given to verify the effectiveness of the proposed method.
Effect of Lamination on Shale Reservoir Properties: Case Study of the Montney Formation, Canada
Authors: Woo Juhwan , Lee Hyun Suk , Ozyer Carl , Rhee Chul Woo
Published: February 2021

The presence of lamination on sedimentary rocks is a distinct characteristic, particularly in shales. They are distinct due to the contrast between successive layers with regard to grain size, composition, color, and sedimentary structures, such as graded beds. Typically, the degree of lamination is controlled by the sedimentation rate and flow regime. Herein, we developed a mudstone classification scheme in terms of lamination because lamination-based shale facies are related to differing features in mineral composition, porosity, and Young’s modulus. This study also attempts to verify whether wireline log patterns are relevant to shale lithofacies. The relationship between the porosity and lamination of the Montney Formation can be used to estimate reservoir properties. Our results show that an increased silt lamina in mudstone leads to an increase in the quartz and calcite contents and a decrease in the clay content, which increases the porosity, permeability, and Young’s modulus. However, reservoir quality is not solely dependent on lamination because of the complex interaction between components. The degree of lamination affected the neutron, density, and sonic log responses. Furthermore, the presence of lamination tends to decrease the neutron percentage, with similar trends in density and sonic log box plots in the study area. When the percentage of clay or cement material decreases, the neutron and density log responses diminish. Meanwhile, when the rock texture variation increases with an increase in the degree of lamination, the sonic log response decreases.
Effective Capacity Maximization in beyond 5G Vehicular Networks: A Hybrid Deep Transfer Learning Method
Authors: Huang Yi , Ma Xinqiang , Liu Youyuan , Yang Zhigang
Published: February 2021

How to improve delay‐sensitive traffic throughput is an open issue in vehicular communication networks, where a great number of vehicle to infrastructure (V2I) and vehicle to vehicle (V2V) links coexist. To address this issue, this paper proposes to employ a hybrid deep transfer learning scheme to allocate radio resources. Specifically, the traffic throughput maximization problem is first formulated by considering interchannel interference and statistical delay guarantee. The effective capacity theory is then applied to develop a power allocation scheme on each channel reused by a V2I and a V2V link. Thereafter, a deep transfer learning scheme is proposed to obtain the optimal channel assignment for each V2I and V2V link. Simulation results validate that the proposed scheme provides a close performance guarantee compared to a globally optimal scheme. Besides, the proposed scheme can guarantee lower delay violation probability than the schemes aiming to maximize the channel capacity.
The Added Value of SOX10 Immunohistochemistry to Other Breast Markers in Identifying Cytokeratin 5-Positive Triple Negative Breast Cancers as of Mammary Origin
Authors: Sejben Anita , Vörös András , Golan Arbel , Zombori Tamás , Cserni Gábor
Published: February 2021

Aims: Triple-negative breast cancer (TNBC) represents a specific group that lacks the expression of estrogen receptors, progesterone receptors, and human epidermal growth factor receptor-2 and might also lack the expression other breast markers like GATA3, mammaglobin (MG), GCDFP15 (growth cystic disease fluid protein 15), and NYBR1; when this occurs, proving the breast origin of a metastasis is a challenging task. In the present study, we assessed the added value of SOX10 immunohistochemistry to known GATA3, MG, GCDFP15, and NY-BR-1 statuses in a series of CK5-positive primary TNBCs. Methods: Tissue microarrays were made from the formalin-fixed and paraffin-embedded blocks of 120 TNBCs, and 3-4-mm-thick sections were immunostained for SOX10. The cut-off for a positive reaction was at least 10% of tumor cells staining. Results: In our cohort, SOX10 positivity was seen in 82/119 cases, 61, 74, 76, and 82 all of which were GATA3, MG, GCDFP15, and NY-BR-1 negative, respectively. Of the SOX10 negative cases, 12 stained with at least another breast marker. Nevertheless, 25/119 (21%) cases remained negative with all markers assessed. Discussion: SOX10 proved to be the most commonly positive breast marker in our CK5 expressing TNBCs, but the other markers also had some additive value to SOX10.
The Risk of Necrotizing Enterocolitis following the Administration of Hyperosmolar Enteral Medications to Extremely Preterm Infants
Authors: Latheef Faiza , Wahlgren Hanna , Lilja Helene Engstrand , Diderholm Barbro , Paulsson Mattias
Published: February 2021

Introduction: Necrotizing enterocolitis (NEC) is a disease predominantly affecting preterm infants. The administration of hyperosmolar solutions could lead to the development of NEC. The objective of this study was to measure the osmolality of enteral medications used in clinical practice and to assess the risk of NEC following exposure to hyperosmolar medications. Methods: A retrospective cohort study in extremely preterm infants (gestational age <28 weeks) born between 2010 and 2016 at a tertiary neonatal intensive care unit in Sweden. 465 infants were identified via the Swedish Neonatal Quality register. Data relating to enteral administrations received during a two-week period were collected from the medical records. The osmolalities of medications were measured using an osmometer. Logistic regression was used to calculate the odds ratio of developing NEC. Results: A total of 253 patients met the inclusion criteria. The osmolalities of 5 commonly used medications significantly exceeded the recommended limit of 450 mOsm/kg set by the American Academy of Paediatrics (AAP). Most patients (94%) received at least one hyperosmolar medication. No significant risk of developing NEC could be found. Conclusion: The medications used in clinical practice can significantly exceed the limit set by the AAP. This study does not indicate an increased risk of developing NEC in extremely preterm infants following exposure to hyperosmolar medications. Further studies in larger cohorts are needed to determine the specific cut-off level of osmolality in relation to the pathogenesis of NEC.
Safety and Clinical Evaluation of Dual Inhibition with Pertuzumab and Trastuzumab Biosimilar SB3 in HER2-Positive Breast Cancer Patients
Authors: Suppan Christoph , Steiner Daniel , Klocker Eva Valentina , Posch Florian , Henzinger Elisabeth , Müller Hannah Deborah , Stöger Herbert , Dandachi Nadia , Balic Marija
Published: February 2021

Background: The addition of trastuzumab to standard chemotherapy has improved survival in patients with HER2-positive breast cancer in neoadjuvant, adjuvant, and metastatic settings. In higher tumor stages, the addition of pertuzumab is now a standard of care and associated with a favorable toxicity profile. We evaluated the safety and efficacy of the trastuzumab biosimilar SB3 in combination with pertuzumab in HER2-positive breast cancer patients. Methods: Seventy-eight patients with HER2-positive breast cancer treated at the Division of Oncology at the Medical University of Graz were included. Summary measures are reported as medians (25th to 75th percentile) for continuous variables and as absolute frequencies (%) for count data. Results: Thirty-five patients received a median of 4 (3–7) cycles of trastuzumab biosimilar SB3 plus pertuzumab. All patients had a normal baseline left ventricular ejection fraction (LVEF; >50%) prior to the initiation of SB3 plus pertuzumab treatment with a median LVEF of 60% (60–65). Twenty-one patients had a median absolute LVEF decline of 1% (–5 to 0). Two patients (5.7%) had a LVEF reduction ≤50%, but none ≥10%. There were no unexpected adverse events. Twenty-two of 35 patients (63%) were treated with trastuzumab biosimilar SB3 and pertuzumab in the neoadjuvant setting and 11 patients (50%) achieved a pathological complete response. The safety and the efficacy in this setting was comparable to the trastuzumab plus pertuzumab combination in neoadjuvantly treated matched samples. Conclusion: In this series of HER2-positive breast cancer patients, the combination of SB3 plus pertuzumab was consistent with the known safety and efficacy profile of trastuzumab and pertuzumab combination.
A Brief Survey Paper on Multi-Legged Robots
Authors: Behmanesh Mohammad , Amiri Tehranizadeh Ehsan , Iwan Solihin Mahmud
Published: February 2021

This paper presents a brief survey on multi-legged robots and their applications in agriculture such as for harvesting. Multi-legged robots have the benefit of more flexibility and adapt to different rough terrain in a better way. They also have very important applications in fulfilling the dangerous tasks such as mine detecting.
Sampled-Data Backstepping Control of a Quadrotor Unmanned Aerial Vehicle
Authors: Jabbar Abdul , Mumtaz Malik Fahad
Published: February 2021

Sampled-data backstepping control of a quadrotor UAV is presented in this paper. The discrete time controllers have been designed on the basis of a continuous time system model and an approximate discrete time equivalent system model (Euler Approximate model) obtained using the Euler method. The performance of the controllers obtained using the two sampled-data approaches has been compared in the presence of wing gusts and modeling uncertainties. Simulations have revealed that the backstepping controller designed on the basis of an approximate discrete time model has better performance in the presence of wind gusts and modeling uncertainties. In addition, the closed loop system has a larger region of attraction.
Wall-E Surveyor Robot using Wireless Networks
Authors: Chandak Aatish , Aravind Arjun , Kamath Nithin
Published: February 2021

The methods for autonomous navigation of a robot in a real world environment is an area of interest for current researchers. Although there have been a variety of models developed, there are problems with regards to the integration of sensors for navigation in an outdoor environment like moving obstacles, sensor and component accuracy. This paper details an attempt to develop an autonomous robot prototype using only ultrasonic sensors for sensing the environment and GPS/ GSM and a digital compass for position and localization. An algorithm for the navigation based on reactive behaviour is presented. Once the robot has navigated to its final location based on remote access by the owner, it surveys the geographical region and uploads the real time images to the owner using an API that is developed for the Raspberry PI’s kernel.
Nonlinear Hybrid Controller for a Quadrotor Based on Sliding Mode and Backstepping
Authors: Zhang Chuan Lian , Chong Kil To
Published: February 2021

In this paper, one nonlinear hybrid controller, based on backstepping and sliding mode, was developed and applied to a quadrotor for waypoint navigation application. After dynamics modeling, the whole quadrotor dynamics system could be divided into two subsystems: rotational system and translational system. Backstepping control law was derived for attitude control whereas sliding mode control law was developed for position control. By using Lyapunov theory and satisfying sliding stable rules, the convergence of system could be guaranteed. A nonlinear equation was proposed to solve the under-actuated problem. To validate the effectiveness of proposed nonlinear hybrid controller, waypoint navigation simulation was performed on the nonlinear hybrid controller. Results showed that the nonlinear hybrid controller finished waypoint navigation successfully.
A Nonlinear Model to Study Selectively Deformable Wing of an Aircraft
Authors: Ganesh A Deiva
Published: February 2021

Aeroelasticity of an aircraft includes the study of dynamics of prime movers, structural dynamics, and aerodynamics. Research efforts are on in every area to improve the overall performance of an aircraft. In this paper preliminary studies conducted on the dynamics of selectively deformable wing using an under actuated nonlinear model is reported. First, the literature related to the design and analysis of selectively deformable structure (SDS) wing is reviewed. Second, a single degree of freedom (DOF) model to represent a fixed wing and a two DOF under-actuated model to represent SDS are discussed and their mathematical models are derived. Third, the effect of deformable wing portion on the wing dynamics is studied by varying the excitation frequency and stiffness of the model. Fourth, an experimental setup consisting of two rigid links connected by spring and subjected to sinusoidal displacement is investigated. Final section summarizes the research and provides directions for future work.
A New 6 DOF Robotic Arm with Linkage Motion Mechanism and Actuators Placed in Base
Authors: Shahhosseini Mohsen , Rastegari Rambod , Abbasi Roozbeh
Published: February 2021

We examined mechanism design and kinematic simulation of a new six degrees of freedom (DOF) robotic arm with rotational joints and a linkage motion mechanism. In the design, a parallel linkage mechanism, accompanied by an additional set of bevel gears, was used to create the desired motion for all six links along with transfer of all actuators to the robot’s base to reduce the mass of most of the arms. These changes resulted in reduction of the torque required for joints 1, 2, and 3. Using this parallel mechanism ensures dependence to motion links and creates a special case for the control of the robot and more rigidity against unwanted movement. Initially, we examined mechanism design methods for a parallel linkage mechanism and considered methods for application in an operational robot. In the next step, we determined the kinematic relationships that were established between the robot’s actuators and joints spaces due to the use of this mechanism. Then, we developed an example of the robot’s function in a performance simulation. The simulation results indicated that the mechanism and controller performance were acceptable.
Self-Tuning Geometric Control for a Quadrotor UAV Based on Lyapunov Stability Analysis
Authors: Goodarzi Farhad
Published: February 2021

A Lyapunov-based self gain tuning geometric nonlinear controller for a quadrotor UAV has been developed on SE(3) in this paper. By designing an adaptive law with Lyapunov stability analysis for the controller gains, the proposed control system can asymptotically follow an attitude and position command while tuning the PID gains online, and it is extended to guarantee boundedness of tracking errors in the presence of unstructured disturbances. This introduce an unprecedented algorithm to autonomously tune the controller gains without need of extra effort or introducing boundary conditions. Proposed controller considers all the coupling effects between rotational and translational dynamics, and it is developed in a coordinate-free fashion to avoid complexities and ambiguities associated with other attitude representations such as Euler angles or quaternions. The desirable features of the proposed controller are illustrated by numerical simulations and juxtaposed with a well-known offline gain tuning method. The proposed algorithm is ultimately validated with an experimental example.
Development of Teach Pendent based Robotic Arm for Drawing using Mechatronics Approach
Authors: Madhusudanan Harikrishnan
Published: February 2021

The main scope of this project is to use mechatronics approach to design and develop a complete humanoid robotic arm which can be used to draw different figures. A mechatronic approach is basically a synergistic combination of mechanical, electrical and control systems such that each and every stage of the product life cycle of the final product gets optimised. So, this approach which is used in this project would ensure that the robotic arm which would be the final product would have its design metrics optimised at each and every stage of its development cycle. The motive of developing this arm is to ensure that the final arm which is produced could be easily attached to the complete humanoid robot and would enable it to draw any kind of complex figures using highly accurate teach pendent mechanism.
Anchor Movement Strategy for Conjecture Geometry Based Localization Scheme in Wireless Sensor Network
Authors: Kapase Niraj Bhupal , Salgar Santosh P , Patil Mahesh K , Zirmite Prashant P
Published: February 2021

Abstract—Localization of sensor node with least error is one of the major concern in wireless sensor network as some of the application require sensor node to know their location with high degree of precision. For mobile anchor based localization many of the path planning schemes already developed which includes scan, double scan, Circles & S- Curves. These path planning schemes have some limitations like localization error, Number of sensor nodes covered in the network, Trajectory length of mobile anchor node.  This paper represents anchor movement strategy which is based on Scan path, with modifications are made in such a way that it satisfies the requirements of localization scheme.  This movement strategy ensures that trajectory of mobile anchor node will minimize localization error and also will cover majority of sensor node in the environment. The localization error yielded by Modified Scan algorithm is in the range of 0.2 to 0.4m which is quite lower than the other existing mentioned path planning strategies producing localization error in the range 0.6 to 1.8m

Keywords—Localization; Mobile anchor node; Wireless sensor network; Modified Scan algorithm
Design and Control of Underwater Robots with Rotating Thrusters
Authors: Jebelli Ali , Yagoub M. C.E. , Dhillon B. S.
Published: February 2021

Among other robots, underwater robot design involves critical control issues due to complex non-linear force and turns controlling. In this paper, a robust approach was proposed to efficiently control the behavior of an underwater robot through five degrees of freedom. Also, by designing a new type of a pair of thruster with the ability to 360 degree rotation along with a mass shifter, it gives this possibility to the robot that easily and with a minimal energy, change its depth quickly, preserving its balance best possible at the same time.
A parameter less stochastic optimization technique for tuning of speed PI controller of DTC induction motor drive
Authors: Goel Naveen , Chacko Saji , Patel R. N.
Published: February 2021

The Direct Torque Controlled (DTC) induction motor (IM) drives over the years have been the work force of industries. The popularity of this motor drive is due to the low cost and low maintenance of induction motor coupled with the fast dynamic response and simple control structure of direct torque control method. The robust performance of the DTC induction motor drive depends on the proper tuning of its speed controller. The proposed paper make use of the stochastic optimization technique namely the popular Harmony Search Algorithm and is compared with the parameter free Jaya Algorithm for tuning the gains of the speed proportional integral controller. Simulation studies in MATLAB/Simulink shows the success of the Jaya Optimization for improving the performance of DTC drive with respect to speed and torque peak over shoot and steady state error under different drive operating conditions.
Design of POD controller using linear quadratic regulator tecniques for SMIB power system stability enhancement installed with UPFC
Authors: Dubey Brijesh Kumar , Singh N. K.
Published: February 2021

In the field of the power system stability, this paper presents the current research status and developments. This paper presents a systematic approach for designing Power Oscillation Damping Controller (POD) based Linear Quadratic Regulator Techniques for SMIB power system stability installed with UPFC to damp out low frequency oscillations in a power system. The impacts of control strategy on power system single machine infinite bus installed with UPFC, without UPFC and with UPFC and POD controller at different operating conditions are discussed. The accuracy of the developed models is verified through comparing the study results with those obtained from detailed MATLAB programming.
Fuzzy neuro-genetic approach for feature selection and image classification in augmented reality systems
Authors: Thilahar C. Rajendra , R. Sivaramakrishnan
Published: February 2021

In this paper, a new approach for implementing an Augmented Reality system by applying fuzzy genetic neural networks is proposed. It consists of two components namely feature selection and classification modules. For feature detection, extraction and selection, the proposed model uses a fuzzy logic based incremental feature selection algorithm which has been proposed in this work in order to recognize the important features from 3D images. Moreover, this paper explains the implementation and results of the proposed algorithms for an Augmented Reality system using image recognition, feature extraction, feature selection and classification by  considering the global and local features of the images. For this purpose, we propose a three layer fuzzy neural network that has been implemented based on weight adjustments using fuzzy rules in the convolutional neural networks with genetic algorithm for effective optimization of rules. The classification algorithm is also based on fuzzy neuro-genetic approach which consists of two phases namely Training phase and testing phase. During the training phase, rules are formed based on objects and these rules are applied during the testing phase for recognizing the objects which can be used in robotics for effective object recognition. From the experiments conducted in this work, it is proved that the proposed model is more accurate in 3D
 object recognition.
Queer as a Zombie: metaforizações da homofobia na ficção televisiva
Authors: Silva Anderson Lopes da
Published: February 2021

Mais do que simplesmente apresentar uma tenebrosa e angustiante imagem, a figura dos mortos-vivos traz a possibilidade de múltiplas leituras metafóricas acerca do que esses seres podem falar sobre nossa sociedade e os seus mais diversos dilemas. Assim, a proposta deste artigo é discutir como a série britânica In the flesh metaforiza a homofobia a partir das questões de gênero e sexualidade nas relações afetivas de personagens zumbis e gays da trama. A metodologia baseiase no estudo da metaforização discursiva e, de maneira intrínseca a ela, utiliza-se do conceito de isotopia discursiva como o direcionador preponderante de análise. Finalmente, as considerações finais apontam que a trama da obra desvela exemplos de metaforização discursiva a partir da homofobia familiar, homofobia clínica, homofobia religiosa, homofobia institucionalmente persecutória e homofobia interiorizada.
O diálogo social solidário na ressignificação das periferias
Authors: Gonçalves Julio Cesar
Published: February 2021

Resenha do livro Jornalismo das Periferias o diálogo social solidário nas bordas urbanas