bluuebunny/crossref_metadata_2025 huggingface dataset:
EFFECT OF CONTROLLED-RELEASE SELENIUM GRANULES APPLIED WITH FERTILISER ON BLOOD LEVELS OF GRAZING SHEEP
Authors: Watkinson J.H.
Published: July 2020

Two sheep grazing trials, at Awarua, Southland. and at Wairakei, central North Island, on selenium (&)-deficient and Se-retentive soils under a rainfall of about 1000 mm were used to test the duration of effectiveness of a mixture of standard and controlled-release Selcote Se granules applied at 0.5 kg/ha each. Selenium concentrations in blood of ewes and lambs were maintained above deficiency levels for 2 years in both trials. Peak values were observed or inferred from both rapid-release and slow-release granules. The pattern of pasture Se was consistent with blood Se values where sampling was sufficiently intensive to allow for the low rate of granule application. Keywords: Pasture, ewes, lambs, yellow-brown pumice soils, lowland yellow-brown earths, Selcote.
The Past and the Future Are Now
Authors: Scott Sascha T. , Lonetree Amy
Published: July 2020

On 20 June 1918, Crescencio Martinez (Ta’e), a painter and pottery designer from San Ildefonso Pueblo, died of influenza [...]
Microplastics in Freshwater: What Is the News from the World?
Authors: Cera Alessandra , Cesarini Giulia , Scalici Massimiliano
Published: July 2020

Plastic has become a “hot topic” for aquatic ecosystems’ conservation together with other issues such as climate change and biodiversity loss. Indeed, plastics may detrimentally affect habitats and biota. Small plastics, called microplastics, are more easily taken up by freshwater organisms, causing negative effects on growth, reproduction, predatory performance, etc. Since available information on microplastics in freshwater are fragmentary, the aim of this review is twofold: (i) to show, analyse, and discuss data on the microplastics concentration in freshwater and (ii) to provide the main polymers contaminating freshwater for management planning. A bibliographic search collected 158 studies since 2012, providing the scientific community with one of the largest data sets on microplastics in freshwater. Contamination is reported in all continents except Antarctica, but a lack of information is still present. Lentic waters are generally more contaminated than lotic waters, and waters are less contaminated than sediments, suggested to be sinks. The main contaminating polymers are polypropylene and polyethylene for sediment and water, while polyethylene and polyethylene terephthalate are mainly found in biota. Future research is encouraged (1) to achieve a standardised protocol for monitoring, (2) to identify sources and transport routes (including primary or secondary origin), and (3) to investigate trophic transfer, especially from benthic invertebrates.
Portfolio Optimization for Binary Options Based on Relative Entropy
Authors: Mercurio Peter Joseph , Wu Yuehua , Xie Hong
Published: July 2020

The portfolio optimization problem generally refers to creating an investment portfolio or asset allocation that achieves an optimal balance of expected risk and return. These portfolio returns are traditionally assumed to be continuous random variables. In An Entropy-Based Approach to Portfolio Optimization, we introduced a novel non-parametric optimization method based on Shannon entropy, called return-entropy portfolio optimization (REPO), which offers a simple and fast optimization algorithm for assets with continuous returns. Here, in this paper, we would like to extend the REPO approach to the optimization problem for assets with discrete distributed returns, such as those from a Bernoulli distribution like binary options. Under a discrete probability distribution, portfolios of binary options can be viewed as repeated short-term investments with an optimal buy/sell strategy or general betting strategy. Upon the outcome of each contract, the portfolio incurs a profit (success) or loss (failure). This is similar to a series of gambling wagers. Portfolio selection under this setting can be formulated as a new optimization problem called discrete entropic portfolio optimization (DEPO). DEPO creates optimal portfolios for discrete return assets based on expected growth rate and relative entropy. We show how a portfolio of binary options provides an ideal general setting for this kind of portfolio selection. As an example we apply DEPO to a portfolio of short-term foreign exchange currency pair binary options from the NADEX exchange platform and show how it outperforms leading Kelly criterion strategies. We also provide an additional example of a gambling application using a portfolio of sports bets over the course of an NFL season and present the advantages of DEPO over competing Kelly criterion strategies.
Calibration Optimization Methodology for Lithium-Ion Battery Pack Model for Electric Vehicles in Mining Applications
Authors: Astaneh Majid , Andric Jelena , Löfdahl Lennart , Maggiolo Dario , Stopp Peter , Moghaddam Mazyar , Chapuis Michel , Ström Henrik
Published: July 2020

Large-scale introduction of electric vehicles (EVs) to the market sets outstanding requirements for battery performance to extend vehicle driving range, prolong battery service life, and reduce battery costs. There is a growing need to accurately and robustly model the performance of both individual cells and their aggregated behavior when integrated into battery packs. This paper presents a novel methodology for Lithium-ion (Li-ion) battery pack simulations under actual operating conditions of an electric mining vehicle. The validated electrochemical-thermal models of Li-ion battery cells are scaled up into battery modules to emulate cell-to-cell variations within the battery pack while considering the random variability of battery cells, as well as electrical topology and thermal management of the pack. The performance of the battery pack model is evaluated using transient experimental data for the pack operating conditions within the mining environment. The simulation results show that the relative root mean square error for the voltage prediction is 0.7–1.7% and for the battery pack temperature 2–12%. The proposed methodology is general and it can be applied to other battery chemistries and electric vehicle types to perform multi-objective optimization to predict the performance of large battery packs.
Epidemiology of Cancers in Men Who Have Sex with Men (MSM): A Protocol for Umbrella Review of Systematic Reviews
Authors: Honaryar Manoj Kumar , Tarasenko Yelena , Almonte Maribel , Smelov Vitaly
Published: July 2020

While earlier studies on men having sex with men (MSM) tended to examine infection-related cancers, an increasing number of studies have been focusing on effects of sexual orientation on other cancers and social and cultural causes for cancer disparities. As a type of tertiary research, this umbrella review (UR) aims to synthesize findings from existing review studies on the effects of sexual orientation on cancer. Relevant peer-reviewed systematic reviews (SRs) will be identified without date or language restrictions using MEDLINE, Cochrane Database of Systematic Reviews, and the International Prospective Register for Systematic Reviews, among others. The research team members will prepare the data extraction forms. Two reviewers will independently assess extracted SRs using the Assessment of Methodological Quality of Systematic Reviews. A third reviewer will weigh in to resolve discrepancies. The reviewers will be blinded to publisher, journal, and authors, making their judgements on the title, year, and abstract. The Preferred Reporting Items for Systematic Reviews and Meta-analysis checklist will guide data synthesis. By collating evidence from multiple reviews into one accessible and usable document, our first UR on global epidemiology of malignancies among MSM would serve as an evidence-based decision-making tool for the public health community.
Lipid Peroxidation and Chlorophyll Fluorescence of Photosystem II Performance during Drought and Heat Stress is Associated with the Antioxidant Capacities of C3 Sunflower and C4 Maize Varieties
Authors: Killi Dilek , Raschi Antonio , Bussotti Filippo
Published: July 2020

Agricultural production is predicted to be adversely affected by an increase in drought and heatwaves. Drought and heat damage cellular membranes, such as the thylakoid membranes where photosystem II occurs (PSII). We investigated the chlorophyll fluorescence (ChlF) of PSII, photosynthetic pigments, membrane damage, and the activity of protective antioxidants in drought-tolerant and -sensitive varieties of C3 sunflower and C4 maize grown at 20/25 and 30/35 °C. Drought-tolerant varieties retained PSII electron transport at lower levels of water availability at both temperatures. Drought and heat stress, in combination and isolation, had a more pronounced effect on the ChlF of the C3 species. For phenotyping, the maximum fluorescence was the most effective ChlF measure in characterizing varietal variation in the response of both species to drought and heat. The drought-tolerant sunflower and maize showed lower lipid peroxidation under drought and heat stress. The greater retention of PSII function in the drought-tolerant sunflower and maize at higher temperatures was associated with an increase in the activities of antioxidants (glutathione reductase, superoxide dismutase, catalase, peroxidase, and ascorbate peroxidase), whereas antioxidant activity declined in the drought-sensitive varieties. Antioxidant activity should play a key role in the development of drought- and heat-tolerant crops for future food security.
Plastid Transformation: How Does it Work? Can it Be Applied to Crops? What Can it Offer?
Authors: Yu Yihe , Yu Po-Cheng , Chang Wan-Jung , Yu Keke , Lin Choun-Sea
Published: July 2020

In recent years, plant genetic engineering has advanced agriculture in terms of crop improvement, stress and disease resistance, and pharmaceutical biosynthesis. Cells from land plants and algae contain three organelles that harbor DNA: the nucleus, plastid, and mitochondria. Although the most common approach for many plant species is the introduction of foreign DNA into the nucleus (nuclear transformation) via Agrobacterium- or biolistics-mediated delivery of transgenes, plastid transformation offers an alternative means for plant transformation. Since there are many copies of the chloroplast genome in each cell, higher levels of protein accumulation can often be achieved from transgenes inserted in the chloroplast genome compared to the nuclear genome. Chloroplasts are therefore becoming attractive hosts for the introduction of new agronomic traits, as well as for the biosynthesis of high-value pharmaceuticals, biomaterials and industrial enzymes. This review provides a comprehensive historical and biological perspective on plastid transformation, with a focus on current and emerging approaches such as the use of single-walled carbon nanotubes (SWNTs) as DNA delivery vehicles, overexpressing morphogenic regulators to enhance regeneration ability, applying genome editing techniques to accelerate double-stranded break formation, and reconsidering protoplasts as a viable material for plastid genome engineering, even in transformation-recalcitrant species.
Cyclic AMP: A Polyhedral Signalling Molecule in Plants
Authors: Blanco Emanuela , Fortunato Stefania , Viggiano Luigi , de Pinto Maria Concetta
Published: July 2020

The cyclic nucleotide cAMP (3′,5′-cyclic adenosine monophosphate) is nowadays recognised as an important signalling molecule in plants, involved in many molecular processes, including sensing and response to biotic and abiotic environmental stresses. The validation of a functional cAMP-dependent signalling system in higher plants has spurred a great scientific interest on the polyhedral role of cAMP, as it actively participates in plant adaptation to external stimuli, in addition to the regulation of physiological processes. The complex architecture of cAMP-dependent pathways is far from being fully understood, because the actors of these pathways and their downstream target proteins remain largely unidentified. Recently, a genetic strategy was effectively used to lower cAMP cytosolic levels and hence shed light on the consequences of cAMP deficiency in plant cells. This review aims to provide an integrated overview of the current state of knowledge on cAMP’s role in plant growth and response to environmental stress. Current knowledge of the molecular components and the mechanisms of cAMP signalling events is summarised.
Surface-Bound and Volatile Mo Oxides Produced During Oxidation of Single MoS2 Crystals in Air and High Relative Humidity
Authors: Szoszkiewicz Robert , Rogala Maciej , Dąbrowski Paweł
Published: July 2020

We report on the MoO3 oxides and their derivatives on microscopic 2H MoS2 flakes oxidized in air and high relative humidity at a moderate temperature range below 410 °C. We combine XPS and AFM measurements such as topography, friction, creation of nanoscale ripples and scratches on the MoS2 flakes deposited on Si substrates. We detect MoO3 oxides mostly by measuring selected nanomechanical properties of the MoO3 layer, such as its compressive mechanical stress at the plastic yield. We discuss basal surface coverage of the single MoS2 flakes by the MoO3 oxides. We discuss conditions for appearance of all possible MoO3 oxide derivatives, such as molybdenum(VI) hydroxyoxides and MoO3 hydrates. Our findings agree with an expected mechanistic switch in thermal oxidation in water vapors vs. air.
Cerium Oxide Nanoparticles: Recent Advances in Tissue Engineering
Authors: Hosseini Motaharesadat , Mozafari Masoud
Published: July 2020

Submicron biomaterials have recently been found with a wide range of applications for biomedical purposes, mostly due to a considerable decrement in size and an increment in surface area. There have been several attempts to use innovative nanoscale biomaterials for tissue repair and tissue regeneration. One of the most significant metal oxide nanoparticles (NPs), with numerous potential uses in future medicine, is engineered cerium oxide (CeO2) nanoparticles (CeONPs), also known as nanoceria. Although many advancements have been reported so far, nanotoxicological studies suggest that the nanomaterial’s characteristics lie behind its potential toxicity. Particularly, physicochemical properties can explain the positive and negative interactions between CeONPs and biosystems at molecular levels. This review represents recent advances of CeONPs in biomedical engineering, with a special focus on tissue engineering and regenerative medicine. In addition, a summary report of the toxicity evidence on CeONPs with a view toward their biomedical applications and physicochemical properties is presented. Considering the critical role of nanoengineering in the manipulation and optimization of CeONPs, it is expected that this class of nanoengineered biomaterials plays a promising role in the future of tissue engineering and regenerative medicine.
High-Fat Diet Enhances Working Memory in the Y-Maze Test in Male C57BL/6J Mice with Less Anxiety in the Elevated Plus Maze Test
Authors: Yoshizaki Kaichi , Asai Masato , Hara Taichi
Published: July 2020

Obesity is characterized by massive adipose tissue accumulation and is associated with psychiatric disorders and cognitive impairment in human and animal models. However, it is unclear whether high-fat diet (HFD)-induced obesity presents a risk of psychiatric disorders and cognitive impairment. To examine this question, we conducted systematic behavioral analyses in C57BL/6J mice (male, 8-week-old) fed an HFD for 7 weeks. C57BL/6J mice fed an HFD showed significantly increased body weight, hyperlocomotion in the open-field test (OFT) and Y-maze test (YMZT), and impaired sucrose preference in the sucrose consumption test, compared to mice fed a normal diet. Neither body weight nor body weight gain was associated with any of the behavioral traits we examined. Working memory, as assessed by the YMZT, and anxiety-like behavior, as assessed by the elevated plus maze test (EPMT), were significantly correlated with mice fed an HFD, although these behavioral traits did not affect the entire group. These results suggest that HFD-induced obesity does not induce neuropsychiatric symptoms in C57BL/6J mice. Rather, HFD improved working memory in C57BL/6J mice with less anxiety, indicating that an HFD might be beneficial under limited conditions. Correlation analysis of individual traits is a useful tool to determine those conditions.
Minimum Dietary Diversity for Women of Reproductive Age (MDD-W) Data Collection: Validity of the List-Based and Open Recall Methods as Compared to Weighed Food Record
Authors: Hanley-Cook Giles T. , Tung Ji Yen A. , Sattamini Isabela F. , Marinda Pamela A. , Thong Kong , Zerfu Dilnesaw , Kolsteren Patrick W. , Tuazon Maria Antonia G. , Lachat Carl K.
Published: July 2020

Minimum dietary diversity for women of reproductive age (MDD-W) was validated as a population-level proxy of micronutrient adequacy, with indicator data collection proposed as either list-based or open recall. No study has assessed the validity of these two non-quantitative proxy methods against weighed food records (WFR). We assessed the measurement agreement of list-based and open recall methods as compared to WFR (i.e., reference method of individual quantitative dietary assessment) for achieving MDD-W and an ordinal food group diversity score. Applying a non-inferiority design, data were collected from non-pregnant women of reproductive age in Cambodia (n = 430), Ethiopia (n = 431), and Zambia (n = 476). For the pooled sample (n = 1337), proportions achieving MDD-W from both proxy methods were compared to WFR proportion by McNemar’s chi-square tests, Cohen’s kappa, and receiver operating characteristic (ROC) analysis. Ordinal food group diversity (0–10) was compared by Wilcoxon matched-pairs signed-rank tests, intraclass correlation coefficients (ICC), and weighted kappa. MDD-W food groups that were most frequently misreported (i.e., type I and II errors) by the proxy methods were determined. Our findings indicate statistically significant differences in proportions achieving MDD-W, ordinal food group diversity scores, and ROC curves between both proxy methods and WFR (p < 0.001). List-based and open recall methods overreported women achieving MDD-W by 16 and 10 percentage points, respectively, as compared to WFR (proportion achieving MDD-W: 30%). ICC values between list-based or open recall and WFR were 0.50 and 0.55, respectively. Simple and weighted kappa values both indicated moderate agreement between list-based or open recall against WFR. Food groups most likely to be misreported using proxy methods were beans and peas, dark green leafy vegetables, vitamin A-rich fruit and vegetables, and other fruits. Our study provides statistical evidence for overreporting of both list-based and open recall methods for assessing prevalence of MDD-W or ordinal food group diversity score in women of reproductive age in low- and middle-income countries. Operationalizing MDD-W through qualitative recall methods should consider potential trade-offs between accuracy and simplicity.
Omega-3 Long-Chain Polyunsaturated Fatty Acids Intake by Ethnicity, Income, and Education Level in the United States: NHANES 2003–2014
Authors: Cave Caleb , Hein Nicholas , Smith Lynette M. , Anderson-Berry Ann , Richter Chesney K. , Bisselou Karl Stessy , Appiah Adams Kusi , Kris-Etherton Penny , Skulas-Ray Ann C. , Thompson Maranda , Nordgren Tara M. , Hanson Corrine , Thoene Melissa
Published: July 2020

Although there are many recognized health benefits for the consumption of omega-3 (n-3) long-chain polyunsaturated fatty acids (LCPUFA), intake in the United States remains below recommended amounts. This analysis was designed to provide an updated assessment of fish and n-3 LCPUFA intake (eicosapentaenoic (EPA), docosahexaenoic acid (DHA), and EPA+DHA) in the United States adult population, based on education, income, and race/ethnicity, using data from the 2003-2014 National Health and Nutrition Examination Survey (NHANES) (n = 44,585). Over this survey period, participants with less education and lower income had significantly lower n-3 LCPUFA intakes and fish intakes (p < 0.001 for all between group comparisons). N-3 LCPUFA intake differed significantly according to ethnicity (p < 0.001), with the highest intake of n-3 LCPUFA and fish in individuals in the “Other” category (including Asian Americans). Supplement use increased EPA + DHA intake, but only 7.4% of individuals consistently took supplements. Overall, n-3 LCPUFA intake in this study population was low, but our findings indicate that individuals with lower educational attainment and income are at even higher risk of lower n-3 LCPUFA and fish intake.
Christian Ethical Analysis of the L.A. Riots in 1992: The Media and Institutional Racism
Authors: Song Yong Sup
Published: July 2020

This essay utilizes Reinhold Niebuhr’s theology of the universality of sin to analyze institutional racism, using the 1992 Los Angeles riots as a case study. Contrary to the conventional interpretation of the riots as a conflict between African Americans and Korean Americans, the pervasive institutional racism of the mainstream media of that era spread the riots into multiracial conflicts, which explains Niebuhr’s thinking regarding the universality of sin. Furthermore, the sensationalism of the media that fueled the massive violence deprived African Americans of the moral dynamic for social transformation and victimized Korean Americans as scapegoats. As a result, the institutional processes promoted the status quo that benefited the white privileged class at the expense of the racial minorities. Implications found in this essay may be applicable to current issues, such as anti-Asian racism that has surfaced during the COVID-19 pandemic in the United States.
Ionospheric Responses to the June 2015 Geomagnetic Storm from Ground and LEO GNSS Observations
Authors: Gao Chao , Jin Shuanggen , Yuan Liangliang
Published: July 2020

Geomagnetic storms are extreme space weather events, which have considerable impacts on the ionosphere and power transmission systems. In this paper, the ionospheric responses to the geomagnetic storm on 22 June 2015, are analyzed from ground-based and satellite-based Global Navigation Satellite System (GNSS) observations as well as observational data of digital ionosondes, and the main physical mechanisms of the ionospheric disturbances observed during the geomagnetic storm are discussed. Salient positive and negative storms are observed from vertical total electron content (VTEC) based on ground-based GNSS observations at different stages of the storm. Combining topside observations of Low-Earth-Orbit (LEO) satellites (GRACE and MetOp satellites) with different orbital altitudes and corresponding ground-based observations, the ionospheric responses above and below the orbits are studied during the storm. To obtain VTEC from the slant TEC between Global Positioning System (GPS) and LEO satellites, we employ a multi-layer mapping function, which can effectively reduce the overall error caused by the single-layer geometric assumption where the horizontal gradient of the ionosphere is not considered. The results show that the topside observations of the GRACE satellite with a lower orbit can intuitively detect the impact caused by the fluctuation of the F2 peak height (hmF2). At the same time, the latitude range corresponding to the peak value of the up-looking VTEC on the event day becomes wider, which is the precursor of the Equatorial Ionization Anomaly (EIA). However, no obvious response is observed in the up-looking VTEC from MetOp satellites with higher orbits, which indicates that the VTEC responses to the geomagnetic storm mainly take place below the orbit of MetOp satellites.
A Modified Bayesian Framework for Multi-Sensor Target Tracking with Out-of-Sequence-Measurements
Authors: Shi Yifang , Qayyum Sundas , Memon Sufyan Ali , Khan Uzair , Imtiaz Junaid , Ullah Ihsan , Dancey Darren , Nawaz Raheel
Published: July 2020

Target detection and tracking is important in military as well as in civilian applications. In order to detect and track high-speed incoming threats, modern surveillance systems are equipped with multiple sensors to overcome the limitations of single-sensor based tracking systems. This research proposes the use of information from RADAR and Infrared sensors (IR) for tracking and estimating target state dynamics. A new technique is developed for information fusion of the two sensors in a way that enhances performance of the data association algorithm. The measurement acquisition and processing time of these sensors is not the same; consequently the fusion center measurements arrive out of sequence. To ensure the practicality of system, proposed algorithm compensates the Out of Sequence Measurements (OOSMs) in cluttered environment. This is achieved by a novel algorithm which incorporates a retrodiction based approach to compensate the effects of OOSMs in a modified Bayesian technique. The proposed modification includes a new gating strategy to fuse and select measurements from two sensors which originate from the same target. The state estimation performance is evaluated in terms of Root Mean Squared Error (RMSE) for both position and velocity, whereas, track retention statistics are evaluated to gauge the performance of the proposed tracking algorithm. The results clearly show that the proposed technique improves track retention and and false track discrimination (FTD).
A Raster-Based Methodology to Detect Cross-Scale Changes in Water Body Representations Caused by Map Generalization
Authors: Shen Yilang , Ai Tinghua
Published: July 2020

In traditional change detection methods, remote sensing images are the primary raster data for change detection, and the changes produced from cartography generalization in multi-scale maps are not considered. The aim of this research was to use a new kind of raster data, named map tile data, to detect the change information of a multi-scale water system. From the perspective of spatial cognition, a hierarchical system is proposed to detect water area changes in multi-scale tile maps. The detection level of multi-scale water changes is divided into three layers: the body layer, the piece layer, and the slice layer. We also classify the water area changes and establish a set of indicators and rules used for the change detection of water areas in multi-scale raster maps. In addition, we determine the key technology in the process of water extraction from tile maps. For evaluation purposes, the proposed method is applied in several test areas using a map of Tiandi. After evaluating the accuracy of change detection, our experimental results confirm the efficiency and high accuracy of the proposed methodology.
Research on Environmental, Economic, and Social Sustainability in Dairy Farming: A Systematic Mapping of Current Literature
Authors: Arvidsson Segerkvist Katarina , Hansson Helena , Sonesson Ulf , Gunnarsson Stefan
Published: July 2020

Dairy cows are able to convert fibrous materials, such as grass, roughage, and by-products from the food industry, into milk and meat, which justifies their role in food production. However, modern dairy farming is associated with major sustainability challenges, including greenhouse gas emissions. In order to develop sustainable future production, it is important to implement existing knowledge and fill knowledge gaps. The aim of this study was to systematically map the scientific literature on environmental, economic, and social sustainability at farm level in dairy farming. Literature published between January 2000 and March 2020 and with the geographical focus on Europe, North America, and Australia–New Zealand was included. In total, the literature search resulted in 169 hits, but after removing duplicates and papers outside the study scope only 35 papers remained. Of these, only 11 dealt with the three dimensions of sustainability, and several of these only mentioned one or two of the dimensions or set them in relation to that/those actually studied. Overall, the selected literature did not clearly explain how aspects of sustainability are interlinked, so possible negative or positive interactions between different aspects of sustainability dimensions remain unidentified.
Value Creation through Corporate Sustainability in the Port Sector: A Structured Literature Analysis
Authors: Stein Michael , Acciaro Michele
Published: July 2020

Corporate Sustainability (CS) in the port sector has emerged as an important driver behind strategy definition for port authorities globally. It has been argued that CS practices have the potential of delivering value for port users and, as such, grant port operators and port managing entities competitive advantages. There is, however, limited evidence behind this claim. The difficulty with collecting such evidence is that we lack measures of port value creation, and CS metrics have rarely been developed and applied in ports. This paper provides a framework for collecting empirical evidence aimed at assessing in what way CS can benefit port competitiveness. The framework is built on a systematic literature analysis of the past years. The literature analysis exceeds previous comparable contributions by its analytical detail and provides valuable new insights on sustainability in the maritime domain. The research indicates that the accurate measurement of CS initiatives in the port sector is urgent and meaningful. When appropriately measured, the value that CS can deliver to port users becomes apparent. This is, however, often created indirectly via branding, risk mitigation, etc. The paper contributes to academic knowledge as it is the first to develop a rigorous CS measurement framework usable for ports in terms of value.
CARACTERIZACIÓN MORFOLÓGICA Y FENOLÓGICA DE ESPECIES SILVESTRES DE FRIJOL (Phaseolus)
Authors: Meza-Vázquez Karen Elizabeth , Lépiz-Ildefonso Rogelio , López-Alcocer José de J. , Morales-Rivera Moisés Martín
Published: July 2020

Con el objetivo de generar información útil para el incremento y conservación de accesiones de frijol silvestre, se realizó la caracterización morfológica y fenológica de 12 especies silvestres de Phaseolus. Las especies de procedencia tropical y subtropical se sembraron en invernadero y las oriundas de sitios templados en campo bajo estructura de malla sombra. En la caracterización se utilizaron los descriptores varietales de frijol común (Phaseolus vulgaris L.) del Servicio Nacional de Inspección y Certificación de Semillas de México; y para las etapas de desarrollo se usó la escala establecida por el Centro Internacional de Agricultura Tropical de Colombia. Se utilizó una parcela de un surco de 4 m de longitud por especie y se registraron 39 variables de tipo cualitativo y cuantitativo. El valor de las variables cuantitativas es el promedio de 10 registros. Se observó gran variabilidad morfológica y fenológica entre las especies. La longitud de hoja primaria varió de 1.4 a 5.4 cm y del foliolo central de 3.1 a 8.5 cm; la longitud de vaina de 1.2 a 6.3 cm, el número de vainas por planta de 21 a 314, y la longitud de semilla de 3.0 a 7.9 mm; el tamaño del polen varió de 41.7 a 55.4 μm. Seis de las doce especies mostraron cotiledones epigeos, seis tuvieron hipocotilo de color rosado, ocho formaron flores de color lila y ocho fueron de raíz tuberosa indicativa de ciclo plurianual. En las primeras etapas de desarrollo fenológico, las especies silvestres presentaron un comportamiento similar; en cambio en la fase reproductiva mostraron diferencias notables. Las especies de frijol se agruparon en dos conjuntos principales relacionados con el tamaño de la planta y ciclo biológico; la mayor similitud se presentó entre P. vulgaris y P. acutifolius, P. microcarpus y P. macvaughii, y P. nodosus y P. scrobiculatifolius. La información obtenida puede apoyar acciones para incrementos de semilla, conservación, uso eficiente y mejoramiento genético.
Estudios de caso de la inteligencia emocional en los estudiantes de grado de educación
Authors: Peña Acuña Beatriz , García Hernández María Luisa
Published: July 2020

Se trata de una investigación sobre inteligencia emocional llevada a cabo en dos casos de estudio con alumnas universitarias españolas de los Grados de Educación mediante un proyecto con carácter innovador en el que se les introdujo a contenidos de inteligencia emocional, se trabajaba la inteligencia emocional en el aula de forma trasversal identificando las emociones, se les animó a apuntar un diario de notas sobre el clima emocional del aula, a identificar en obras audiovisuales las emociones vividas en el lenguaje corporal junto a los tipos de inteligencia hallados en los personajes, así como la relación de la inteligencia emocional con la inteligencia social con respecto a la expresión y la empatía. Queríamos hacer esta investigación para comprobar la eficacia de las actividades docentes y el interés de las alumnas sobre esta cuestión con el fin de vertebrar con posterioridad un proyecto de innovación sobre inteligencia emocional que fuera financiado. La herramienta de investigación usada ha consistido en un test para que autoevaluaran la inteligencia emocional antes y después de aplicársele la metodología docente para que se conocieran, y en una entrevista semiestructurada que recogía datos cuantitativos y datos cualitativos y de la que extraemos datos.
Multimodel Image Segmentation and Classification by MAP based graph cut and Improved VGG16
Authors:   grade, in independence school, friscos texas, united states., desan Jathin
Published: July 2020

Diagnosing brain diseases possess various inbuilt complexities to the nature of the diagnostic process. Brain tumor, Stroke, and Hemorrhage are the commonly prevailing disease and comprise more complexity in diagnosing where there arises the confusion in case of high grade or low-grade tumor and acute or sub-acute stroke. In general most of the prevailing algorithms is suited for the predicted of the image only employing the MRI or CT image. The paper mainly focused on the employment of a suitable proposed algorithm to adopt both the CT and MRI images for precise segmentation and classification. The segmentation algorithm is a map (map a posterior) based graph cut method The segmentation results are compared with the existing methods like (FCM) Fuzzy C Means and KFCM Kernel Fuzzy C Means and it is proved that our proposed system outperformed to the performance metrics. An improved VGG 16architecture is proposed for efficient classification. The overall classification results proved to be more efficient when compared with the existing R-CNN and NS-CNN methods. The paper focused on overcoming the difficulty and make a clear understanding of segmenting and classification irrespective of the nature of the diagnostic process.
IntelliFin: Advanced Stock Prediction using Hybrid ML and LSTM Model with Financial Indicators powered by Sentiment Determination using NLP
Authors:   Department of Electrical Computer Science and Engineering from SRM Institute of Science and Technology, Chennai., Singh Shashank , Ahmad Maaz ,   Department of Electrical Computer Science and Engineering from SRM Institute of Science and Technology, Chennai., Bhattacharya Aditya ,   Department of Electrical Computer Science and Engineering from SRM Institute of Science and Technology, Chennai., Prabhu D. ,   Assistant Professor in Computer Science and Engineering at SRM Institute of Science and Technology, Chennai.
Published: July 2020

Stock Trading has been one of the most important parts of the financial world for decades. People investing in the share market analyze the financial history of a corporation, the news related to it and study huge amounts of data so as to predict its stock price trend. The right investment i.e. buying and selling a company stock at the right time leads to monetary benefits and can make one a millionaire overnight. The stock market is an extremely fluctuating platform wherein data is produced in humongous quantities and is influenced by numerous disparate factors such as socio-political issues, financial activities like splits and dividends, news as well as rumors. This work proposes a novel system “IntelliFin” to predict the share market trend. The system uses the various stock market technical indicators along with the company's historical market data trends to predict the share prices. The system employs the sentiment determination of a company's financial and socio-political news for a more accurate prediction. This system is implemented using two models. The first is a hybrid LSTM model optimized by an ADAM optimizer. The other is a hybrid ML model which integrates a Support Vector Regressor, K-Nearest Neighbor classifier, an RF classifier and a Linear Regressor using a Majority Voting algorithm. Both models employ a sentiment analyzer to account for the news impacting the stock prices which is powered by NLP. The models are trained continuously using Reinforcement Learning implemented by the Q-Learning Algorithm to increase the consistency and accuracy. The project aims to support the inexperienced investors, who don't have enough experience in investing in the stock market and help them maximize their profit and minimize or eliminate the losses. The developed system will also serve as a tool for professional investors to help and aid their decision making.
Displacements Schemes for Obtaining the Frequency Dependence on the Cottonseeds Moisture
Authors:   Department of Electronics and Automatics of Tashkent State Technical University, Tashkent, Uzbekistan., Zakirovich Nasirov Tulkun , Raxmatovich Ismatullayev Patxulla ,   Department of Electronics and Automatics of Tashkent State Technical University, Tashkent, Uzbekistan., Shaymardonovich Jabborov Hamdam ,   Department of Electronics and Automatics of Tashkent State Technical University, Tashkent, Uzbekistan, qizi Eraliyeva Yulduzxon Mumtoz ,   Department of Electronics and Automatics Of Tashkent State Technical University, Tashkent, Uzbekistan.
Published: July 2020

The mathematic model of the high frequency moisture meter for cottonseeds has been constructed, in which the studying material as a complex dielectric installing in an electric field is represented. The displacement scheme which includes capacity between electrodes and also capacities and resistors corresponding to different polarization types has been presented. 4 variants of displacement schemes which describe approximately the dependence of angle tangency of dielectric losses on the electromagnet field frequency using in the measuring device have been considered. It has been shown that the simplest two element R-C scheme connected parallel corresponds to the closest real description of measuring object in frequencies range from 105 up to 108 Hertz.
Image Fusion Based on Wavelet Transformation
Authors:   Department of Computer Science and Engineering, KLS Gogte Institute of Technology, Belagavi., Naik Raghawendra Bhimarao , Kunchur Pavan N. ,   Assistant Professor, Department of Computer Science and Engineering, Gogte Institute of Technology, Belagavi.
Published: July 2020

The article based totally on the MATLAB software program simulation was carried out on the image fusion; to design and develop a MATLAB based image processing application for fusing two images of the similar scene received through other modalities. The application is required to use Discrete Wavelet Transform (DWT) and Pulse Coupled Neural Network (PCNN) techniques. The comparison is to be performed on the results obtained on the above mentioned techniques.
Solution of One Dimensional Conformable fractional Heat Equation
Authors:   Basic Science and Humanities Department, Deogiri Institute of Engineering and Management Studies, Aurangabad, India., Jadhav C. P. , Navlekar A. A. ,   Department of Mathematics, Pratishthan Mahavidyalaya , Paithan, India, Ghadle K. P. ,   Department of Mathematics, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, India.
Published: July 2020

The aim of this paper is to present the solution of one dimensional conformable fractional heat equation by applying conformable fractional derivative which is considered as more convenient definition of fractional derivative.
Host Utilization Algorithm to Reduce Energy Consumption in Cloud Computing
Authors:   Easwari Engineering College, Chennai, India., Kanagasubaraja S. , M Hema ,   Easwari Engineering College, Chennai, India., M Vineeth ,   Easwari Engineering College, Chennai, India., K Shreyas Rao ,   Easwari Engineering College, Chennai, India., S Siva Anandh ,   Easwari Engineering College, Chennai, India.
Published: July 2020

The utilization of distributed computing server farm is developing quickly to fulfill the large increment required for systems administration, High-Performance Computing(HPC) as well as stockpiling assets for executing business and logical applications. The process of Virtual Machine (VM) solidification is inclusive of VMs getting relocated in order to make use of less physical servers. As a result, it enables the shut down or lowpower mode of more number of servers which enhances the vitality utilization effectiveness, working expense and CO2 discharge. An urgent advance in VM union is have over-burden discovery, which endeavors to foresee whether a physical server is going to be oversubscribed with VMs. On the contrary to usual studies which performed utilization of CPU being the standalone indicator for host overload, a multiple correlation host overload detection algorithm was proposed in the recent study by considering a lot of factors in this regard. A higher load balance model was introduced in this text for the general public cloud, supported by the concept of cloud partitioning, in addition to a switch mechanism used to strategize differently under different scenarios. The IP address is generally shared by a true server and carbo balance. In this regard, the load balancer considers the interface developed with IP address which accepts request packets and the packets are directed to the selected servers. With an aim to improve the efficiency in public cloud environment, the algorithm employed the sport theory in the load balancing strategy.
Castellated Steel Beams A Torsional Analysis
Authors:   Research Scholar, Late G. N. Sapkal COE, Nashik, SPPU, Maharashtra, India, Mehetre A. J. , Talikoti R. S. ,   Associate Professor, R. H. Sapat COE, management studies & research, Nashik, SPPU, Maharashtra, India.
Published: July 2020

Practice of castellated beams (CBs) or perforated beams for several structures speedily gaining petition. This is because of the increased depth in the segment, high strength to weight ratio, light in weight, easy to erect, economical, and stronger. The principal advantages of the castellated beam are an attractive provision, an increase in vertical bending stiffness, & ease of service provision. The CBs is prepared from its virgin sections i.e. I beam by cutting it in a zigzag or any suitable cutting pattern and again rejoined it by welding therefore depth of the resulting section increases. The load-carrying capacity of the parent I section is increased with the same quantity of material and weight, due to an increase in depth of beams. Web post-buckling and lateral-torsional buckling failure occur when these beams are subjected to loading, this is the effect of an increase in depth of the castellated beams. There are five basic failure modes associated with castellated steel beams that need to be taken care of 1) Development of flexure mechanism. 2) Lateral-torsional buckling 3) Vierendeel mechanism 4) rupture of the welded joint in a web post 5) shear buckling of a web post. Therefore, in this research paper, an effort has been made to estimate the torsional moment capacity castellated beam for hexagonal or honeycomb opening with 300 , 450 , 600 & sinusoidal opening with different fillet radii.
Automatic Gun Targeting System using Face Detection, IR and Ultra Sonic Sensor
Authors:   School of Electronics Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India., Prasad Aditya , Gupta Jayant ,   , School of Electronics Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India., Sharma Yogesh ,   School of Electronics Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India., Priyadarsini M. Jasmine Pemeena ,   Higher Academic Grade, School of Electronics Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India
Published: July 2020

In this paper, our objective is to devise a new defence mechanism using automation, which will seek to provide a viable solution to tighten the security around the border areas and simultaneously reduce the burden on soldiers. With the help of automation, we can increase the efficiency of safeguarding our borders in remote areas to a great extent, and this will also result in a better quality of surveillance due to this technological intervention. The main focus for us will be in the creation of an active and real-time device for the armed forces, which will help safeguard the relatively remote border areas where human mobility is restricted. The devised mechanism will consist of three modules: face detection of a human intruder, wireless communication, and hardware detection of an intruder. The automation system in this defence mechanism majorly consists of face detection of a human intruder, which is supported and complemented by Ultrasonic and IR Sensors. This system is implemented using Arduino microcontroller, which will be complemented with NodeMCU to provide necessary wireless communication for sending intruder detection and location information to the cloud, which will trigger the gun to shoot down the enemy. The use of wireless communication over GSM is preferred solely because the control stations receive Wi-Fi signals directly from the satellite, which is very reliable and fast. The main application of our research work is to ensure safeguarding border region around remote areas where patrolling is difficult for army personnel and will be implemented by the armed forces.
An Exploration of Current Data Agglomeration Technique in Wireless Sensor Network
Authors:   School of Electronics Engineering, Vellore Institute of Technology, Vellore, India, Rhesa M. J. , Revathi S. ,   Ph.D in Optical Engineering, School of Electronics Engineering, Vellore Institute of Technology, Vellore, India.
Published: July 2020

Wireless sensor network plays prominently in various applications of the emerging advanced wireless technology such as smart homes, Commercial, defence sector and modern agriculture for effective communication. There are many issues and challenges involved during the communication process. Energy conservation is the major challenging matter and fascinates issue among the researchers. The reason for that, Wireless sensor network has ‘n’ number of sensor nodes to identify and recognize the data and send that data to the base station or sink through either directly or intermediate node. These nodes with poor energy create intricacy on the data rate or flow and substantially affect the lifespan of a wireless sensor network. To decrease energy utilization the sensor node has to neglect unnecessary received data from the neighbouring nodes prior to send the optimum data to the sink or another device. When a specific target is held in a particular sector, it can be identified by many sensors. To rectify such process this paper present Data agglomeration technique is one of the persuasive techniques in the neglecting unnecessary data and of improves energy efficiency and also it increases the lifetime of WSNs. The efficacious data aggregation paradigm can also decrease traffic in the network. This paper discussed various data agglomeration technique for efficient energy in WSN