bluuebunny/crossref_metadata_2025 huggingface dataset:
First Multimessenger Observations of a Neutron Star Merger
Authors: Margutti Raffaella , Chornock Ryan
Published: June 2021

We describe the first observations of the same celestial object with gravitational waves and light. ▪  GW170817 was the first detection of a neutron star merger with gravitational waves. ▪  The detection of a spatially coincident weak burst of gamma-rays (GRB 170817A) 1.7 s after the merger constituted the first electromagnetic detection of a gravitational wave source and established a connection between at least some cosmic short gamma-ray bursts (SGRBs) and binary neutron star mergers. ▪  A fast-evolving optical and near-infrared transient (AT 2017gfo) associated with the event can be interpreted as resulting from the ejection of ∼0.05 M⊙of material enriched in r-process elements, finally establishing binary neutron star mergers as at least one source of r-process nucleosynthesis. ▪  Radio and X-ray observations revealed a long-rising source that peaked ∼160,d after the merger. Combined with the apparent superluminal motion of the associated very long baseline interferometry source, these observations show that the merger produced a relativistic structured jet whose core was oriented ≈20 deg from the line of sight and with properties similar to SGRBs. The jet structure likely results from interaction between the jet and the merger ejecta. ▪  The electromagnetic and gravitational wave information can be combined to produce constraints on the expansion rate of the Universe and the equation of state of dense nuclear matter. These multimessenger endeavors will be a major emphasis of future work.
Advancements in and Integration of Water, Sanitation, and Solid Waste for Low- and Middle-Income Countries
Authors: Narayan Abishek Sankara , Marks Sara J. , Meierhofer Regula , Strande Linda , Tilley Elizabeth , Zurbrügg Christian , Lüthi Christoph
Published: June 2021

The water, sanitation, and solid waste sectors are closely related and have many interactions between their respective service chains in low- and middle-income countries. Currently, these interactions mostly lead to cross-contamination, and opportunities for co-benefits are seldom realized. This review presents the key advancements within each of these three development sectors in the past two decades. We identify numerous similarities such as decentralization, resource recovery, community involved planning, and digitalization. Despite the potential for synergies and the opportunities to maximize positive interactions, there have been few attempts to break the existing sectoral silos in order to integrate these three service chains. We argue that, with the right enabling environment, an integrated approachto holistically planning and implementing water supply, sanitation, and solid waste management can create positive interactions resulting in co-benefits among complementary development goals.
Review—Multifunctional Copper Nanoparticles: Synthesis and Applications
Authors: Bhagat Madhulika , Anand Rythem , Sharma Pooja , Rajput Prerna , Sharma Neha , Singh Khushwace
Published: June 2021

Copper nanomaterials due to their unique properties are rapidly finding place as an important component of next-generation material in various sectors such as electronics, machinery, construction, engineering, pharmaceutical, agriculture, energy, environment etc In fact in past decades, researchers have devoted several studies to Cu nanomaterials, and have achieved many innovative results from synthesis to applications, highlighting its immeasurable potential for extensive practical and theoretical applications holding great promises. This review emphasises on the recent progress made in synthesis of copper nanoparticles by various techniques such as physical, chemical and biological methods. The application section describes their utility in several sectors including agriculture, environment, construction, electronics etc Moreover, the emphasis was also laid to understand the uptake mechanism of the copper nanoparticles by plants, the toxicity caused at higher concentrations and the associated implications of exposure to both human and environmental health, including the challenges and difficulties to be addressed in the future.
A Portfolio Selection Model Based on the Interval Number
Authors: Hu Jiangshan , Sui Yunyun , Ma Fang
Published: June 2021

Traditional portfolio theory uses probability theory to analyze the uncertainty of financial market. The assets’ return in a portfolio is regarded as a random variable which follows a certain probability distribution. However, it is difficult to estimate the assets return in the real financial market, so the interval distribution of asset return can be estimated according to the relevant suggestions of experts and decision makers, that is, the interval number is used to describe the distribution of asset return. Therefore, this paper establishes a portfolio selection model based on the interval number. In this model, the semiabsolute deviation risk function is used to measure the portfolio’s risk, and the solution of the model is obtained by using the order relation of the interval number. At the same time, a satisfactory solution of the model is obtained by using the concept of acceptability of the interval number. Finally, an example is given to illustrate the practicability of the model.
Determinants of Preeclampsia among Women Attending Delivery Services in Public Hospitals of Central Tigray, Northern Ethiopia: A Case-Control Study
Authors: Haile Teklehaimanot Gereziher , Assefa Nega , Alemayehu Tadesse , Mariye Teklewoini , Geberemeskel Gebreamlak Gebremedhn , Bahrey Degena , Mebrahtom Guesh , Demisse Biniyam , Gebrekidan Hailemikael , Getachew Tamirat
Published: June 2021

Background. Preeclampsia occurs in up to 5% of all pregnancies, in 10% of first pregnancies, and 20–25% of women with a history of chronic hypertension. Objective. This study aims to assess the determinants of preeclampsia among women attending delivery services in public hospitals of central Tigray, Ethiopia. Methods. Hospital-based unmatched case-control study design was conducted. Women diagnosed with preeclampsia were cases, and women who had no preeclampsia were controls admitted to the same hospitals. A systematic sampling technique was used to select study participants for both cases and controls. The data were entered in EPI data 3.1 statistical software and, then, exported to SPSS Version 22 for cleaning and analysis. Results. Family history of hypertension (AOR: 2.60; 95% CI: 1.15, 5.92), family history of preeclampsia (AOR: 5.24; 95% CI: 1.85, 14.80), history of diabetes mellitus (AOR: 4.31; 95% CI: 1.66, 11.21), anemia (AOR: 3.23; 95% CI: 1.18, 8.86), history of preeclampsia on prior pregnancy (AOR: 5.55; 95% CI: 1.80, 17.10), primigravida (AOR: 5.41; 95% CI: 2.85, 10.29), drinking alcohol during pregnancy (AOR: 4.06; 95% CI: 2.20, 7.52), and vegetable intake during pregnancy (AOR: 0.39; 95% CI: 0.21, 0.74) were significantly associated with preeclampsia. Conclusion. This study concludes that a family history of hypertension and preeclampsia; a history of diabetes mellitus and anemia; and a history of preeclampsia on prior pregnancy, primigravida, and drinking alcohol were found to be risk factors for preeclampsia. However, vegetable intake was found to be a protective factor for the development of preeclampsia.
Influence of Urena lobata Fibre Treatment on Mechanical Performance Development in Hybrid Urena lobata: Fibre/Gypsum Plaster Composites
Authors: Kengoh Jerum Biepinwoh , Peter Etape Ekane , Victorine Namondo Beckley , Foba-Tendo Josepha , Nafu Yakum Renata , Fabien Betene Ebanda
Published: June 2021

Autogenous shrinkage is related to the chemistry and changes in the internal structure of the cement concrete paste on drying. This problem of drying shrinkage in early stages that occur without any moisture transfer to the surrounding environment has triggered the incorporation of fibres in the cement concrete matrix to fill the micropores and control cracking (autogenous shrinkage). This study aimed at investigating the potential use of Urena lobata (UL) fibre as microreinforcement in enhancing mechanical properties of hybrid UL‐fibre/gypsum cement composites used for plasters. The fibre was harvested from the coastal region of Cameroon and treated with 0.06 M NaOH over different periods. Dispersion of treated fibre bundles in the composite (at Wt. % UL‐fibre dosages of 0, 1.5, 2.5, and 3.5) was facilitated by blending with the cement paste which also helped to improve interfacial bonding between the fibre and the cement matrix. The moisture/water absorption and flexural properties within the hardened cement matrix were quantitatively assessed, and it was observed that the incorporation of treated fibre accelerated the hydration process. The test results showed an increment in compressive strength and reduction in autogenous shrinkage for the hybrid UL fibre/gypsum cement composites, while lower percentage additions (less than 2.5%) of untreated fibre appeared to have adverse effects on specimens. It was observed that properly dispersed (blended) treated UL fibres filled the fine pores in the cement matrix by providing an additional nucleation site that resulted in a denser microstructure, which in turn enhanced the strengths and limited the autogenous shrinkage.
A Novel Approach on the Intuitionistic Fuzzy Rough Frank Aggregation Operator‐Based EDAS Method for Multicriteria Group Decision‐Making
Authors: Yahya Muhammad , Naeem Muhammad , Abdullah Saleem , Qiyas Muhammad , Aamir Muhammad
Published: June 2021

The basic ideas of rough sets and intuitionistic fuzzy sets (IFSs) are precise statistical instruments that can handle vague knowledge easily. The EDAS (evaluation based on distance from average solution) approach plays an important role in decision‐making issues, particularly when multicriteria group decision‐making (MCGDM) issues have more competing criteria. The purpose of this paper is to introduce the intuitionistic fuzzy rough Frank EDAS (IFRF‐EDAS) methodology based on IF rough averaging and geometric aggregation operators. We proposed various aggregation operators such as IF rough Frank weighted averaging (IFRFWA), IF rough Frank ordered weighted averaging (IFRFOWA), IF rough Frank hybrid averaging (IFRFHA), IF rough Frank weighted geometric (IFRFWG), IF rough Frank ordered weighted geometric (IFRFOWG), and IF rough Frank hybrid geometric (IFRFHG) on the basis of Frank t‐norm and Frank t‐conorm. Information is given for the basic favorable features of the analyzed operator. For the suggested operators, a new score and precision functions are described. Then, using the suggested method, the IFRF‐EDAS method for MCGDM and its stepwise methodology are shown. After this, a numerical example is given for the established model, and a comparative analysis is generally articulated for the investigated models with some previous techniques, showing that the investigated models are much more efficient and useful than the previous techniques.
Image‐Based Detection of Plant Diseases: From Classical Machine Learning to Deep Learning Journey
Authors: Khan Rehan Ullah , Khan Khalil , Albattah Waleed , Qamar Ali Mustafa
Published: June 2021

Plant disease automation in agriculture science is the primary concern for every country, as the food demand is increasing at a fast rate due to an increase in population. Moreover, the increased use of technology today has increased the efficacy and accuracy of detecting diseases in plants and animals. The detection process marks the beginning of a series of activities to fight the diseases and reduce their spread. Some diseases are also transmitted between animals and human beings, making it hard to fight them. For many years, scientists have researched how to deal with the common diseases that affect humans and plants. However, there are still many parts of the detection and discovery process that have not been completed. The technology used in medical procedures has not been adequate to detect all diseases on time, and that is why some diseases turn out to become pandemics because they are hard to detect on time. Our focus is to clarify the details about the diseases and how to detect them promptly with artificial intelligence. We discuss the use of machine learning and deep learning to detect diseases in plants automatically. Our study also focuses on how machine learning methods have been moved from conventional machine learning to deep learning in the last five years. Furthermore, different data sets related to plant diseases are discussed in detail. The challenges and problems associated with the existing systems are also presented.
Regional Ecological Security Evolution and Green Economy: An Empirical Study
Authors: Yu Chengxue , Chen Meilan
Published: June 2021

How to maintain and improve ecological security in the process of green economy development is of great significance in terms of both theory and practice. Hence, in this paper, based on the framework of DPESAR (driving force-pressure-exposure-sensitivity-adaptation-response), we establish a structural model using SPASS and Eviews6 software to identify the contributing factors for green economy development. We use panel data of Liaoning Province, China, from 1995 to 2017 to analyze the relationships among these factors and their indicators. Furthermore, we simulate and identify the ideal evolution status of the ecological security and green economy development up to the year of 2022. Our results show that first, those adjusted indicators of ecological security can greatly promote green economy development. Second, specific regulation indicators and scope can be obtained by identifying the evolutionary state of ecological security. Third, the interactions among the government, firms, and the public should be considered to further develop regional ecological security and green economy.
An Adaptive Control Combination Forecasting Method for Time Series Data
Authors: Jiang Hongyan , Fang Dianjun , Zhang Xinyan
Published: June 2021

According to the individual forecasting methods, an adaptive control combination forecasting (ACCF) method with adaptive weighting coefficients was proposed for short-term prediction of the time series data. The US population dataset, the American electric power dataset, and the vibration signal dataset in a hydraulic test rig were separately tested by using ACCF method, and then, the accuracy analysis of ACCF method was carried out in the study. The results showed that, in contrast to individual methods or combination methods, the proposed ACCF method was adaptive to adopt one or some of prediction methods and showed satisfactory forecasting results due to flexible adaptability and a high accuracy. It was also concluded that the higher the noise ratio of the tested datasets, the lower the prediction accuracy of the ACCF method; the ACCF method demonstrated a better prediction trend with good volatility and following quality under noisy data, as compared with other methods.
Safety and Efficacy of High Power Shorter Duration Ablation Guided by Ablation Index or Lesion Size Index in Atrial Fibrillation Ablation: A Systematic Review and Meta-Analysis
Authors: Liu Xing , Gui Chun , Wen Weiming , He Yan , Dai Weiran , Zhong Guoqiang
Published: June 2021

Background. High power shorter duration (HPSD) ablation may lead to safe and rapid lesion formation. However, the optimal radio frequency power to achieve the desired ablation index (AI) or lesion size index (LSI) is insubstantial. This analysis aimed to appraise the clinical safety and efficacy of HPSD guided by AI or LSI (HPSD-AI or LSI) in patients with atrial fibrillation (AF). Methods. The Medline, PubMed, Embase, Web of Science, and the Cochrane Library databases from inception to November 2020 were searched for studies comparing HPSD-AI or LSI and low power longer duration (LPLD) ablation. Results. Seven trials with 1013 patients were included in the analysis. The analyses verified that HPSD-AI or LSI revealed benefits of first-pass pulmonary vein isolation (PVI) (RR: 1.28; 95% CI: 1.05–1.56, P = 0.01) and acute pulmonary vein reconnection (PVR) (RR: 0.65; 95% CI: 0.48–0.88, P = 0.005) compared with LPLD. HPSD-AI or LSI showed higher freedom from atrial tachyarrhythmia (AT) (RR = 1.32, 95% CI: 1.14–1.53, P = 0.0002) in the subgroup analysis of studies with PVI ± (with or without additional ablation beyond PVI). HPSD-AI or LSI could short procedural time (WMD: −22.81; 95% CI, −35.03 to −10.60, P = 0.0003), ablation time (WMD: −10.80; 95% CI: −13.14 to −8.46, P < .00001), and fluoroscopy time (WMD: −7.71; 95% CI: −13.71 to −1.71, P = 0.01). Major complications and esophageal lesion in HPSD-AI or LSI group were no more than LDLP group (RR: 0.58; 95% CI: 0.20–1.69, P = 0.32) and (RR: 0.84; 95% CI: 0.43–1.61, P = 0.59). Conclusions. HPSD-AI or LSI was efficient for treating AF with shorting procedural, ablation, and fluoroscopy time, higher first-pass PVI, and reducing acute PVR and may increase freedom from AT for patients with additional ablation beyond PVI compared with LPLD. Moreover, complications and esophageal lesion were low and no different between two groups.
Cardiogenic Shock and Guillain–Barré Syndrome as the First Manifestations of Pheochromocytoma
Authors: Heidarpour Maryam , Sereshti Nafiseh , Shafie Davood , Iraj Bijan , Rezvanian Hassan
Published: June 2021

Febrile congestive heart failure is a rare first manifestation of pheochromocytoma. Herein, the case of a 31-year-old female with febrile congestive heart failure and subsequent cardiogenic shock is presented. After intensive care unit (ICU) admission and further evaluating the right adrenal mass observed in abdominal ultrasonography, the diagnosis of pheochromocytoma was confirmed. Then, she was scheduled for the right adrenalectomy. Before surgery, she complained of acute-onset progressive muscle weakness in the lower limbs, followed by the upper limbs. After further investigation, she was diagnosed with Guillain–Barré syndrome and treated with intravenous immunoglobulin (IVIG). She recovered well after the right adrenalectomy, and during the subsequent 18 months, the follow-up did not reveal any complications, and left ventricular function recovered to normal.
Anti-inflammatory Effects of Empagliflozin and Gemigliptin on LPS-Stimulated Macrophage via the IKK/NF-κB, MKK7/JNK, and JAK2/STAT1 Signalling Pathways
Authors: Lee Nami , Heo Yu Jung , Choi Sung-E , Jeon Ja Young , Han Seung Jin , Kim Dae Jung , Kang Yup , Lee Kwan Woo , Kim Hae Jin
Published: June 2021

Background. Sodium-glucose cotransporter 2 (SGLT2) and dipeptidyl peptidase-4 (DPP-4) inhibitors are glucose-lowering drugs whose anti-inflammatory properties have recently become useful in tackling metabolic syndromes in chronic inflammatory diseases, including diabetes and obesity. We investigated whether empagliflozin (SGLT2 inhibitor) and gemigliptin (DPP-4 inhibitor) improve inflammatory responses in macrophages, identified signalling pathways responsible for these effects, and studied whether the effects can be augmented with dual empagliflozin and gemigliptin therapy. Methods. RAW 264.7 macrophages were first stimulated with lipopolysaccharide (LPS), then cotreated with empagliflozin, gemigliptin, or empagliflozin plus gemigliptin. We conducted quantitative RT-PCR (qRT-PCR) to determine the most effective anti-inflammatory doses without cytotoxicity. We performed ELISA and qRT-PCR for inflammatory cytokines and chemokines and flow cytometry for CD80, the M1 macrophage surface marker, to evaluate the anti-inflammatory effects of empagliflozin and gemigliptin. NF-κB, MAPK, and JAK2/STAT signalling pathways were examined via Western blotting to elucidate the molecular mechanisms of anti-inflammation. Results. LPS-stimulated CD80+ M1 macrophages were suppressed by coincubation with empagliflozin, gemigliptin, and empagliflozin plus gemigliptin, respectively. Empagliflozin and gemigliptin (individually and combined) inhibited prostaglandin E2 (PGE2) release and COX-2, iNOS gene expression in LPS-stimulated RAW 264.7 macrophages. These three treatments also attenuated the secretion and mRNA expression of proinflammatory cytokines, such as TNF-α, IL-1β, IL-6, and IFN-γ, and proinflammatory chemokines, such as CCL3, CCL4, CCL5, and CXCL10. All of them blocked NF-κB, JNK, and STAT1/3 phosphorylation through IKKα/β, MKK4/7, and JAK2 signalling. Conclusions. Our study demonstrated the anti-inflammatory effects of empagliflozin and gemigliptin via IKK/NF-κB, MKK7/JNK, and JAK2/STAT1 pathway downregulation in macrophages. In all cases, combined empagliflozin and gemigliptin treatment showed greater anti-inflammatory properties.
Analysis of Serum MicroRNA‐122 Expression at Different Stages of Chronic Hepatitis B Virus Infection
Authors: Liu Wenjun , He Xinxiang , Huang Fei
Published: June 2021

Objective. To investigate the expression of microRNA‐122 (miR‐122) in the progression of chronic hepatitis B virus‐ (HBV‐) infected liver diseases, thus determining the role of serum miR‐122 as a marker of HBV‐caused liver injury. Methods. Sera were collected from patients with different stages of HBV infection (n = 63) and healthy volunteers (n = 11). And the serum miR‐122 levels were detected using RT‐qPCR. Moreover, an analysis was applied for identifying the specific correlation of the miR‐122 level with HBV DNA, HBeAg, and ALT levels. After liver biopsy, Ishak scoring was utilized for evaluation of the fibrosis stage and the histological activity index (HAI). Results. We confirmed, in the serum, increased miR‐122 expression in HBV‐infected patients and its highest expression in chronic HBV carriers, based on such comparison between the healthy controls and patients. The correlation analysis results were taken as confirmation of the positive relationship of miR‐122 with HBV DNA (r = 0.354, P = 0.005) and ALT (r = 0.331, P = 0.009). But no correlation of this molecule with HBeAg levels was found (P = 0.187). In comparison with the HBeAg‐negative patients, serum miR‐122 expression showed an increase in the HBeAg‐positive patients (P = 0.001). miR‐122 expression, in addition, was of a significant correlation with HAI, but not with the liver fibrosis score. Conclusion. The peak of the serum miR‐122 expression normally occurs in the early stage of the progression from the HBV carrier phase to chronic hepatitis to cirrhosis. This molecule can be considered as a marker for evaluation of HBV‐caused liver injury.
The Sub-Riemannian Limit of Curvatures for Curves and Surfaces and a Gauss–Bonnet Theorem in the Rototranslation Group
Authors: Liu Haiming , Miao Jiajing , Li Wanzhen , Guan Jianyun
Published: June 2021

The rototranslation group

ℛ
T

is the group comprising rotations and translations of the Euclidean plane which is a 3-dimensional Lie group. In this paper, we use the Riemannian approximation scheme to compute sub-Riemannian limits of the Gaussian curvature for a Euclidean

C

2

-smooth surface in the rototranslation group away from characteristic points and signed geodesic curvature for Euclidean

C

2

-smooth curves on surfaces. Based on these results, we obtain a Gauss–Bonnet theorem in the rototranslation group.
Aging and CNS Myeloid Cell Depletion Attenuate Breast Cancer Brain Metastasis
Authors: Wu Alex Man Lai , Gossa Selamawit , Samala Ramakrishna , Chung Monika A. , Gril Brunilde , Yang Howard H. , Thorsheim Helen R. , Tran Andy D. , Wei Debbie , Taner Esra , Isanogle Kristine , Yang Yuan , Dolan Emma L. , Robinson Christina , Difilippantonio Simone , Lee Maxwell P. , Khan Imran , Smith Quentin R. , McGavern Dorian B. , Wakefield Lalage M. , Steeg Patricia S.
Published: June 2021

Purpose:

Breast cancer diagnosed in young patients is often aggressive. Because primary breast tumors from young and older patients have similar mutational patterns, we hypothesized that the young host microenvironment promotes more aggressive metastatic disease.

Experimental Design:

Triple-negative or luminal B breast cancer cell lines were injected into young and older mice side-by-side to quantify lung, liver, and brain metastases. Young and older mouse brains, metastatic and naïve, were analyzed by flow cytometry. Immune populations were depleted using antibodies or a colony-stimulating factor-1 receptor (CSF-1R) inhibitor, and brain metastasis assays were conducted. Effects on myeloid populations, astrogliosis, and the neuroinflammatory response were determined.

Results:

Brain metastases were 2- to 4-fold higher in young as compared with older mouse hosts in four models of triple-negative or luminal B breast cancer; no age effect was observed on liver or lung metastases. Aged brains, naïve or metastatic, contained fewer resident CNS myeloid cells. Use of a CSF-1R inhibitor to deplete myeloid cells, including both microglia and infiltrating macrophages, preferentially reduced brain metastasis burden in young mice. Downstream effects of CSF-1R inhibition in young mice resembled that of an aged brain in terms of myeloid numbers, induction of astrogliosis, and Semaphorin 3A secretion within the neuroinflammatory response.

Conclusions:

Host microenvironmental factors contribute to the aggressiveness of triple-negative and luminal B breast cancer brain metastasis. CSF-1R inhibitors may hold promise for young brain metastasis patients.
Repertoire Remodeling through CD4+ T-cell Depletion
Authors: Yao Winnie , Satpathy Ansuman T.
Published: June 2021

Understanding the cellular regulation of tumor-specific CD8+ T-cell responses is critical to designing improved clinical strategies for cancer immunotherapy. In this issue, Aoki and colleagues deepen our knowledge of this topic by demonstrating that transient depletion of CD4+ T cells in patients with gastrointestinal cancer induces remodeling of the T-cell repertoire, including clonal replacement and expansion of CD8+ T-cell clones shared between the blood and tumor.

See article by Aoki et al., p. 624
Leptomeningeal Carcinomatosis of Metastatic Primary Prostate Cancer
Authors: Stenberg Daniel , Shalavadi Megha , Syeda Humera , Reddy Krishna , Saunders Phillip
Published: June 2021

Leptomeningeal carcinomatosis (LC) is an uncommon complication of cancer in which the disease metastasizes to the meninges; it is estimated that this occurs in 5% of cancer patients and is most often terminal. LC has a median survival time of approximately 15.7 weeks [Leal et al., Curr Cancer Ther Rev. 2011;7(4):319–27]. Furthermore, metastasis from the prostate is exceptionally rare with only a few cases described in medical literature. Until recently, leptomeningeal disruption was very rare and cerebral involvement was irrelevant [Bubendorf et al., Hum Pathol. 2000;31(5):578–83; Schaller et al., Br J Cancer. 2000;77(12):2386–9]. With improved imaging, diagnostic modalities, and treatment with therapies that do not cross the blood-brain barrier, the incidence of LC has been on the rise [Batool and Kasi, StatPearls, https://www.ncbi.nlm.nih.gov/books/NBK499862/]. Diagnosis previously relied on biopsy, supported by lumbar puncture findings. We submit a case demonstrating progressive and consistent evidence of LC found on imaging, justifying its acceptance as a diagnostic modality.
Design of utility functions for game-based channel allocation in cognitive radio wireless sensor network
Authors: Rai Prativa , Kanti Ghose Mrinal , Kumar Deva Sarma Hiren
Published: June 2021

Cognitive radio enabled wireless sensor network is capable of reducing the spectrum scarcity problem of the wireless networks. Looking at the scarcity of available bandwidth, and the high growth in the number of communication devices in recent times, cognitive radio technology has proven to be a promising technology for the days to come. The application of Game Theory in cognitive radio networks has been visible in recent research works. However, only limited literature is available in which possibilities of applying the game-theory based approaches for the challenging task of channel assignment in cognitive radio wireless sensor are available in the literature. It is understood that the crux of the solution to the problem of scheming games for allocation of the channel is centered on the selection of the utility function in order to increase the efficiency of the channel allocation algorithm. Accordingly, the study regarding the influence of several utility functions on the performance of the corresponding channel allocation algorithm is important.  Such a study enables designers to arrive at the optimal utility function to be used in game-theory based channel allocation algorithms, and the same is explored to the best extent, in this paper. The detailed procedure of allocating channels to all the contending nodes through game-based channel allocation has been discussed in this paper. Moreover, the performance of six different utility functions proposed which can be used for channel allocation using game theory has been evaluated for respective performances through MATLAB-based simulations.
Connection status report generator
Authors: Gupta Pratyush , Banerjee Somnath , Prasad Mishra Debani , Reddy Salkuti Surender
Published: June 2021

This paper presents “Connection Status Report Generator” which is an auto executable application and it generates a detailed textual and pictorial representation of the network connectivity status of a particular computer and sends the generated reports to the concerned party. The features developed in this paper aim to constantly monitor the network connectivity status as well as ease the troubleshooting process of finding the major cause of call-drops which is a popular problem in every industry. This paper is divided into three major sub-categories of real-time connection status tracker, report generator, and the image viewer interface. The proposed executable application is coded in Java and designed to run as a background application with minimal system prerequisites.
Autonomous path planning through application of rotated two-parameter overrelaxation 9-point Laplacian iteration technique
Authors: Ling W. K. , Ahmad Dahalan A'Qilah , Saudi Azali
Published: June 2021

Autonomous path navigation is one of the important studies in robotics since a robot’s ability to navigate through an environment brings about many advancements with it. This paper suggests the iteration technique called half-sweep two parameter overrelaxation 9-point laplacian (HSTOR-9P) to be applied on autonomous path navigation and aims to investigate its effectiveness in performing computation for path planning in an indoor static environment. This iteration technique is a harmonic function that solves the Laplace’s equation where the modelling of the environment is based on. The harmonic functions are an appropriate method to be used on autonomous path planning because it satisfies the min-max principle, therefore avoiding the occurrence of local minima which traps robot’s movements, and that it offers complete path planning algorithm. Its performance is tested against its predecessor iteration technique. Results shown that HSTOR-9P iteration technique enables path construction in a lower number of iterations, thus, performs better than its predecessors.
Dynamic composition components based on machine learning: architecture design and process
Authors: Zouani Younes , Abdali Abdelmounaim , Ait Zaouiat Charafeddine
Published: June 2021

The dynamic composition of components is an emerging concept that aims to allow a new application to be constructed based on a user’s request. Three main ingredients must be used to achieve the dynamic composition of components: goal, scenario, and context-awareness. These three ingredients must be completed by artificial intelligence (AI) techniques that help process discovery and storage. This paper presents framework architecture for the dynamic composition of components that can extract expressed goals, deduce implicit ones using AI. The goal will be combined with pertinent contextual data, to compose the relevant components that meet the real requirements of the user. The core element of our proposed architecture is the composer component that (i) negotiate user goal, (ii) load the associated scenarios and choose the most suitable one based on user goal and profile, (iii) get binding information of scenario’s actions, (iv) compose the loaded actions, and (v) store the new component as a tree of actions enabled by contextual or process constraint. In our e-learning proven of concept, we consider five components: composer component, reader component, formatter component, matcher component, and executor component. These five components stipulate that a course is the combination of existing/scrapped chapters that have been adapted to a user profile in terms of language, level of difficulty, and prerequisite. The founding result shows that AI is not only an element that enhances system performance in terms of timing response but a crucial ingredient that guides the dynamic composition of components.

 
Weather prediction using random forest machine learning model
Authors: Meenal R. , Michael Prawin Angel , Pamela D. , Rajasekaran E.
Published: June 2021

The complex numerical climate models pose a big challenge for scientists in weather predictions, especially for tropical system. This paper is focused on presenting the importance of weather prediction using machine learning (ML) technique. Recently many researchers recommended that the machine learning models can produce sensible weather predictions in spite of having no precise knowledge of atmospheric physics. In this work, global solar radiation (GSR) in MJ/m2/day and wind speed in m/s is predicted for Tamil Nadu, India using a random forest ML model. The random forest ML model is validated with measured wind and solar radiation data collected from IMD, Pune. The prediction results based on the random forest ML model are compared with statistical regression models and SVM ML model. Overall, random forest machine learning model has minimum error values of 0.750 MSE and R2 score of 0.97. Compared to regression models and SVM ML model, the prediction results of random forest ML model are more accurate. Thus, this study neglects the need for an expensive measuring instrument in all potential locations to acquire the solar radiation and wind speed data.
Robot movement controller based on dynamic facial pattern recognition
Authors: Nurmaini Siti , Zarkasi Ahmad , Stiawan Deris , Yudho Suprapto Bhakti , Desy Siswanti Sri , Ubaya Huda
Published: June 2021

In terms of movement, mobile robots are equipped with various navigation techniques. One of the navigation techniques used is facial pattern recognition. But Mobile robot hardware usually uses embedded platforms which have limited resources. In this study, a new navigation technique is proposed by combining a face detection system with a ram-based artificial neural network. This technique will divide the face detection area into five frame areas, namely top, bottom, right, left, and neutral. In this technique, the face detection area is divided into five frame areas, namely top, bottom, right, left, and neutral. The value of each detection area will be grouped into the ram discriminator. Then a training and testing process will be carried out to determine which detection value is closest to the true value, which value will be compared with the output value in the output pattern so that the winning discriminator is obtained which is used as the navigation value. In testing 63 face samples for the Upper and Lower frame areas, resulting in an accuracy rate of 95%, then for the Right and Left frame areas, the resulting accuracy rate is 93%. In the process of testing the ram-based neural network algorithm pattern, the efficiency of memory capacity in ram, the discriminator is 50%, assuming a 16-bit input pattern to 8 bits. While the execution time of the input vector until the winner of the class is under milliseconds (ms).
Breast tumor segmentation in mammography image via Chan-Vese technique
Authors: Kamil Mohammed Y. , Radhi Eman A.
Published: June 2021

The accurate segmentation of tumours is a crucial stage of diagnosis and treatment, reducing the damage that breast cancer causes, which is the most common type of cancer among women, especially after the age of forty. The task of segmenting breast tumours in mammograms is very difficult, as its difficulty lies in the lack of contrast between the tumour and the surrounding breast tissue, especially when dealing with small tumours that are not clear boundaries and hidden under the tissues. As algorithms often lose an automatic path toward the boundaries of the tumour at try to determine the site of this type of tumour. The study aims to create a clear contrast between the tumour and the healthy breast area. For this purpose, we used a Gaussian filter as a pre-processing as it works to intensify the low-frequency components while reducing the high-frequency components as the breast structure is enhanced and noise suppression. Then, CLAHE was used to improve the contrast of the image, which increases the contrast between the tumour and the surrounding tissue and sharpens the edges of the tumour. Next, the tumour was segmented by using the Chan-Vese method with appropriate parameters defined. The proposed method was applied to all abnormal mammogram images taken from a publicly available mini-MIAS database. The proposed model was tested in two ways, the first is statistical that got results (90.1, 94.8, 95.5, 92.1, 99.5) for Jaccard, Dice, PF-Score, precision, and sensitivity respectively. And the other is based on the segmented region's characteristics that results showed the algorithm could identify the tumour with high efficiency.
An android-based mobile educational game for disaster preparedness: an input to risk reduction management
Authors: Catedrilla Gene Marck Bañares , Lerios Jefferson Llobit , Sapin Sherwin Banaag , Lanuang Manuel C , Buama Chester Alexis C
Published: June 2021

The Philippines is one of the countries in the world who suffers in different disasters, particularly natural disasters. Every year, there are more than twenty incidents recorded in the country related to different disasters which involve numerous lives of its citizens. It is found that most Filipinos have lack of knowledge in terms of disaster preparation specially, teenagers. This paper intended to develop a mobile-based game that aims to spread awareness on what to do during disasters. Upon development, forty-five (45) respondents were chosen to test the reliability of the application which composed of elementary students, household owners, police officers, fire fighters and IT experts. Further, ISO 25010 was adapted and modified in assessing the project. The results showed that the application is strongly acceptable and gives appropriate output in terms of disaster preparation garnering a total mean of 3.83
State Violence and Weaving: implications of Aristophanes’ Lysistrata for Plato’s Statesman
Authors: Marren Marina
Published: June 2021

This paper uses Aristophanes' Lysistrata to draw out the central violent tension of the weaving paradigm in Plato's Statesman. In the Lysistrata, weaving is offered as a metaphor for a tyrannical refashioning of the polis. In strikingly similar terms, the Eleatic Stranger of the Statesman proposes weaving as a metaphor for the best form of government. What is laughed off in the play, the characters of Plato's dialogue seem to take seriously. Through a comparative reading, I argue that the interpretations of the Statesman that take weaving as a paradigm for the best government of state, not only miss the comedy in the Stranger's discussion of statesmanship, but also the tragic allusions to tyranny. Furthermore, by drawing out the dialogue’s resonance with comedy, I conclude that the weaving paradigm succeeds in giving us a means for identifying tyranny in the Statesman; even when tyranny appears dressed up in a political science ostensibly formulated with the best of intentions.
Plato and Equality for Women across Social Class
Authors: Zoller Coleen Patricia
Published: June 2021

This essay will marshal evidence for Plato’s extension of equal education and professional opportunity to all women, including artisan women who are not his ideal city’s philosopher-queens. I examine the explicit commentary in the Republic, Timaeus, and Laws about women in artisan professions, and I link it together with the three of the core principles advanced in the Republic, particularly (1) the principle of specialization (R. 369b-370c), (2) the principle of irrelevant reproductive differences (R. 454b-e, 456b), and (3) the principle of children’s potential (R. 415a-c, 423c-d) that arises from the myth of metals. Plato uses his Socrates and the Athenian to argue against gender discrimination because it violates these principles. Plato offering a theory of equal opportunity for women across all classes ought to be highlighted as one of the central achievements of the Republic.
A mulher sitiada de Clarice Lispector: o serafim coxo
Authors: Jeronimo Thiago Cavalcante
Published: June 2021

Este artigo propõe discutir o romance A cidade sitiada (1949), de Clarice Lispector, como marcado pelo recurso discursivo nomeado paródia. A autora, vivendo em Berna, sitiada em contexto europeu, situa o seu texto em um molde tradiconal de construção narrativa e, ao se valer de figuras do capítulo seis do livo do profeta Isaías, as reconfigura à constituição de sua protagonista, Lucrécia Neves, mulher sitiada dentro dos muros da cidade de São Geraldo. O foco das análises privilegia o capítulo quatro da narrativa de Lispector – “A estátua pública” –, tendo como respaldo teórico, além de interpretações da fortuna crítica acerca da obra da ficcionista, textos abalizados ligados às esferas literária e bíblica.
O Mendigo Cego - conto de Eliyahu Meidanek
Authors: Steinberg Gabriel
Published: June 2021

Este texto apresenta a tradução do conto Hakabtsan Hayiver (O Mendigo Cego), do escritor em língua hebraica Eliyahu Meidanek. Em sua curta trajetória, Meidanek demonstrou grande domínio do hebraico literário, e ao igual que outros escritores e intelectuais da época, contribuiu para a popularização da língua já que seus contos eram publicados nos jornais hebraicos que circulavam na época pela Europa Oriental.
Myofibroblast Deficiency of LSD1 Alleviates TAC-Induced Heart Failure
Authors: Huo Jin-Ling , Jiao Lemin , An Qi , Chen Xiuying , Qi Yuruo , Wei Bingfei , Zheng Yichao , Shi Xiaojing , Gao Erhe , Liu Hong-Min , Chen Dong , Wang Cong , Zhao Wen
Published: June 2021

Rationale:

Histone LSD1 (lysine-specific demethylase 1) is an important epigenetic antitumor drug target, whose inhibitors are currently in phase I/II clinical trials. However, the potential side effects of LSD1 inhibition in the progress of cardiac remodeling to heart failure remain to be investigated.

Objective:

To evaluate the roles of myofibroblast- or cardiomyocyte-specific LSD1 deficiency in pressure overload-induced cardiac remodeling.

Methods and Results:

Adult mouse cardiac fibroblasts, neonatal rat cardiac myocytes, and fibroblasts were isolated, respectively. The myofibroblast-specific and cardiomyocyte-specific LSD1 inducible knockout mice were then generated. We found that LSD1 was increased not only in human dilated cardiomyopathy hearts but also in wild-type mouse heart homogenates and isolated cardiac fibroblasts, following 20 weeks of transverse aortic constriction. The upregulation of LSD1 was also observed in Ang II-treated neonatal rat cardiac fibroblasts, which was reversed by LSD1 silence or its activity inhibition by ORY-1001. These findings suggested a potential involvement of LSD1 in cardiac remodeling. Importantly, myofibroblast-specific LSD1 inducible knockout in vivo significantly alleviated systolic dysfunction, cardiac hypertrophy, and fibrosis, following 6 and 20 weeks of transverse aortic constriction. Mechanistically, through RNA-sequencing and the following Western blot analysis, we found that loss of LSD1 in Ang II-induced myofibroblasts not only inhibited the intracellular upregulation of TGFβ1 (transforming growth factor β1), its downstream effectors Smad2/3 phosphorylation, as well as the phosphorylation of p38, ERK1/2 and JNK, but also reduced the supernatant TGFβ1 secretion, which then decreased myocyte hypertrophy in the indirect coculture model. On the other hand, cardiomyocyte-specific LSD1-inducible knockout in vivo triggered the reprogramming of fetal genes, mild cardiac hypertrophy, and dysfunction under both basal and stressed conditions.

Conclusions:

Our findings, for the first time, implicate that myofibroblast-specific LSD1 deletion attenuates transverse aortic constriction-induced cardiac remodeling and improves heart function, suggesting that LSD1 is a potential therapeutic target for late-stage heart failure.
Regulation of the Methylation and Expression Levels of the BMPR2 Gene by SIN3a as a Novel Therapeutic Mechanism in Pulmonary Arterial Hypertension
Authors: Bisserier Malik , Mathiyalagan Prabhu , Zhang Shihong , Elmastour Firas , Dorfmüller Peter , Humbert Marc , David Gregory , Tarzami Sima , Weber Thomas , Perros Frederic , Sassi Yassine , Sahoo Susmita , Hadri Lahouaria
Published: June 2021

Background:

Epigenetic mechanisms are critical in the pathogenesis of pulmonary arterial hypertension (PAH). Previous studies have suggested that hypermethylation of the BMPR2 (bone morphogenetic protein receptor type 2) promoter is associated with BMPR2 downregulation and progression of PAH. Here, we investigated for the first time the role of SIN3a (switch-independent 3a), a transcriptional regulator, in the epigenetic mechanisms underlying hypermethylation of BMPR2 in the pathogenesis of PAH.

Methods:

We used lung samples from PAH patients and non-PAH controls, preclinical mouse and rat PAH models, and human pulmonary arterial smooth muscle cells. Expression of SIN3a was modulated using a lentiviral vector or a siRNA in vitro and a specific adeno-associated virus serotype 1 or a lentivirus encoding for human SIN3a in vivo.

Results:

SIN3a is a known transcriptional regulator; however, its role in cardiovascular diseases, especially PAH, is unknown. It is interesting that we detected a dysregulation of SIN3 expression in patients and in rodent models, which is strongly associated with decreased BMPR2 expression. SIN3a is known to regulate epigenetic changes. Therefore, we tested its role in the regulation of BMPR2 and found that BMPR2 is regulated by SIN3a. It is interesting that SIN3a overexpression inhibited human pulmonary arterial smooth muscle cells proliferation and upregulated BMPR2 expression by preventing the methylation of the BMPR2 promoter region. RNA-sequencing analysis suggested that SIN3a downregulated the expression of DNA and histone methyltransferases such as DNMT1 (DNA methyltransferase 1) and EZH2 (enhancer of zeste 2 polycomb repressive complex 2) while promoting the expression of the DNA demethylase TET1 (ten-eleven translocation methylcytosine dioxygenase 1). Mechanistically, SIN3a promoted BMPR2 expression by decreasing CTCF (CCCTC-binding factor) binding to the BMPR2 promoter. Last, we identified intratracheal delivery of adeno-associated virus serotype human SIN3a to be a beneficial therapeutic approach in PAH by attenuating pulmonary vascular and right ventricle remodeling, decreasing right ventricle systolic pressure and mean pulmonary arterial pressure, and restoring BMPR2 expression in rodent models of PAH.

Conclusions:

All together, our study unveiled the protective and beneficial role of SIN3a in pulmonary hypertension. We also identified a novel and distinct molecular mechanism by which SIN3a regulates BMPR2 in human pulmonary arterial smooth muscle cells. Our study also identified lung-targeted SIN3a gene therapy using adeno-associated virus serotype 1 as a new promising therapeutic strategy for treating patients with PAH.