Abstract: The use of alternative energy sources to meet energy demand reduces environmental damage. To diversify an energy matrix and to minimize global warming, a solar energy is gaining space, being an important source of renewable energy, and its potential depends on the climatic conditions of the region. Brazil presents a great solar potential for a generation of electric energy, so the knowledge of solar radiation and its characteristics are fundamental for the study of energy use. Due to the above reasons, this article aims to verify the climatic variability corresponding to the variations in solar radiation anomalies, in the face of climate change scenarios. The data used in this research are part of the Intercomparison of Interconnected Models, Phase 5 (CMIP5), which contributed to the preparation of the fifth IPCC-AR5 report. The solar radiation data were extracted from The Australian Community Climate and Earth System Simulator (ACCESS) model using the RCP 4.5 and RCP 8.5 scenarios that represent an intermediate structure and a pessimistic framework, the latter being the most worrisome in all cases. In order to allow the use of solar radiation as a source of energy in a given location and/or region, it is important, first, to determine its availability, thus justifying the importance of the study. The results pointed out, for the 75-year period (2026-2100), based on a pessimistic scenario, indicate a drop in solar radiation of the approximately 12% in the eastern region of Rio Grande do Sul. Factors that influence the pessimistic prospects of this scenario should be better observed by the responsible authorities, since they can affect the possibility to produce electricity from solar radiation.
Abstract: The total chromatic number χ"(G) of a graph G is the
minimum number of colors needed to color the elements (vertices
and edges) of G such that no incident or adjacent pair of elements
receive the same color Let G be a graph with maximum degree Δ(G).
Considering a total coloring of G and focusing on a vertex with
maximum degree. A vertex with maximum degree needs a color and
all Δ(G) edges incident to this vertex need more Δ(G) + 1 distinct
colors. To color all vertices and all edges of G, it requires at least
Δ(G) + 1 colors. That is, χ"(G) is at least Δ(G) + 1. However,
no one can find a graph G with the total chromatic number which
is greater than Δ(G) + 2. The Total Coloring Conjecture states that
for every graph G, χ"(G) is at most Δ(G) + 2. In this paper, we prove that the Total Coloring Conjectur for a
Δ-claw-free 3-degenerated graph. That is, we prove that the total
chromatic number of every Δ-claw-free 3-degenerated graph is at
most Δ(G) + 2.
Abstract: Deficiency and insufficiency of Vitamin D is a pandemic of the 21st century. Obesity patients have a lower level of vitamin D, but the literature data are contradictory. The purpose of this study is to investigate deficiency and insufficiency vitamin D in postmenopausal women with obesity. We examined 1007 women aged 50-89 years. Mean age was 65.74±8.61 years; mean height was 1.61±0.07 m; mean weight was 70.65±13.50 kg; mean body mass index was 27.27±4.86 kg/m2, and mean 25(OH) D levels in serum was 26.00±12.00 nmol/l. The women were divided into the following six groups depending on body mass index: I group – 338 women with normal body weight, II group – 16 women with insufficient body weight, III group – 382 women with excessive body weight, IV group – 199 women with obesity of class I, V group – 60 women with obesity of class II, and VI group – 12 women with obesity of class III. Level of 25(OH)D in serum was measured by means of an electrochemiluminescent method - Elecsys 2010 analyzer (Roche Diagnostics, Germany) and cobas test-systems. 34.4% of the examined women have deficiency of vitamin D and 31.4% insufficiency. Women with obesity of class I (23.60±10.24 ng/ml) and obese of class II (22.38±10.34 ng/ml) had significantly lower levels of 25 (OH) D compared to women with normal body weight (28.24±12.99 ng/ml), p=0.00003. In women with obesity, BMI significantly influences vitamin D level, and this influence does not depend on the season.
Abstract: In this paper, we study the performance of the strong
stability method of the univariate classical risk model. We interest to
the stability bounds established using two approaches. The first based
on the strong stability method developed for a general Markov chains.
The second approach based on the regenerative processes theory . By
adopting an algorithmic procedure, we study the performance of the
stability method in the case of exponential distribution claim amounts.
After presenting numerically and graphically the stability bounds, an
interpretation and comparison of the results have been done.
Abstract: Computing with Words (CWW) and Possibilistic Relational Universal Fuzzy (PRUF) are the two concepts which widely represent and measure the vaguely defined natural phenomenon. In this paper, we study the positional alteration of the phrases by which the impact of a natural language proposition gets affected and/or modified. We observe the gradations due to sensitivity/feeling of a statement towards the positional alterations. We derive the classification and modification of the meaning of words due to the positional alteration. We present the results with reference to set theoretic interpretations.
Abstract: A probabilistic formulation to assess the slopes safety under the hazard of strong storms is presented and illustrated through a slope in Mexico. The formulation is based on the classical safety factor (SF) used in practice to appraise the slope stability, but it is introduced the treatment of uncertainties, and the slope failure probability is calculated as the probability that SF
Abstract: 22 physicochemical variables have been determined in water samples collected weekly from January to December in 2013 from three sampling stations located within a major drinking water reservoir. Classical Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) analysis was used to investigate the environmental factors associated with the physico-chemical variability of the water samples at each of the sampling stations. Matrix augmentation MCR-ALS (MA-MCR-ALS) was also applied, and the two sets of results were compared for interpretative clarity. Links between these factors, reservoir inflows and catchment land-uses were investigated and interpreted in relation to chemical composition of the water and their resolved geographical distribution profiles. The results suggested that the major factors affecting reservoir water quality were those associated with agricultural runoff, with evidence of influence on algal photosynthesis within the water column. Water quality variability within the reservoir was also found to be strongly linked to physical parameters such as water temperature and the occurrence of thermal stratification. The two methods applied (MCR-ALS and MA-MCR-ALS) led to similar conclusions; however, MA-MCR-ALS appeared to provide results more amenable to interpretation of temporal and geological variation than those obtained through classical MCR-ALS.
Abstract: Tropaeolum majus L. is a native plant to South and Central America, used since ancient times by our ancestors to combat different diseases. Glucotropaeolonin is one of its main components, which when hydrolyzed, forms benzyl isothiocyanate (BIT) that promotes cellular apoptosis (programmed cell death in cancer cells). Therefore, the present research aims to evaluate the effect of the pressure and temperature of BIT extraction by supercritical CO2 from Tropaeolum majus L. The extraction was carried out in a supercritical fluid extractor equipment Speed SFE BASIC Brand: Poly science, the leaves of Tropaeolum majus L. were ground for one hour and lyophilized until obtaining a humidity of 6%. The extraction with supercritical CO2 was carried out with pressures of 200 bar and 300 bar, temperatures of 50°C, 60°C and 70°C, obtained by the conjugation of these six treatments. BIT was identified by thin layer chromatography using 98% BIT as the standard, and as the mobile phase hexane: dichloromethane (4:2). Subsequently, BIT quantification was performed by high performance liquid chromatography (HPLC). The highest yield of oleoresin by supercritical CO2 extraction was obtained pressure 300 bar and temperature at 60°C; and the higher content of BIT at pressure 200 bar and 70°C for 30 minutes to obtain 113.615 ± 0.03 mg BIT/100 g dry matter was obtained.
Abstract: In construction industry, reinforced concrete (RC) slabs
represent fundamental elements of buildings and bridges. Different
methods are available for analysing the structural behaviour of
slabs. In the early ages of last century, the yield-line method has
been proposed to attempt to solve such problem. Simple geometry
problems could easily be solved by using traditional hand analyses
which include plasticity theories. Nowadays, advanced finite element
(FE) analyses have mainly found their way into applications of
many engineering fields due to the wide range of geometries to
which they can be applied. In such cases, the application of an
elastic or a plastic constitutive model would completely change the
approach of the analysis itself. Elastic methods are popular due to
their easy applicability to automated computations. However, elastic
analyses are limited since they do not consider any aspect of the
material behaviour beyond its yield limit, which turns to be an
essential aspect of RC structural performance. Furthermore, their
applicability to non-linear analysis for modeling plastic behaviour
gives very reliable results. Per contra, this type of analysis is
computationally quite expensive, i.e. not well suited for solving
daily engineering problems. In the past years, many researchers have
worked on filling this gap between easy-to-implement elastic methods
and computationally complex plastic analyses. This paper aims at
proposing a numerical procedure, through which a pseudo-lower
bound solution, not violating the yield criterion, is achieved. The
advantages of moment distribution are taken into account, hence the
increase in strength provided by plastic behaviour is considered. The
lower bound solution is improved by detecting over-yielded moments,
which are used to artificially rule the moment distribution among
the rest of the non-yielded elements. The proposed technique obeys
Nielsen’s yield criterion. The outcome of this analysis provides a
simple, yet accurate, and non-time-consuming tool of predicting the
lower-bound solution of the collapse load of RC slabs. By using
this method, structural engineers can find the fracture patterns and
ultimate load bearing capacity. The collapse triggering mechanism is
found by detecting yield-lines. An application to the simple case of
a square clamped slab is shown, and a good match was found with
the exact values of collapse load.
Abstract: The expanding informal sector in developing countries and in Ghana in particular from the 1980s has now been aggravated by the growing population and downsizing in both the public and private sectors, with displaced workers finding alternative livelihoods in the informal sector. Youth and graduate unemployment also swell the numbers and further promote the continuity of the sector. Formal workers and institutions facilitate the growth and complicate demarcations between informality within the formal and informal sectors. In spite of its growth and increasing importance, the informal economy does not feature in policy debates and has often been neglected by the Ghana government. The phenomenon has evolved with modernity into myriad unimaginable forms. Indeed, actors within the sector often clash with the interventions provided by policy makers - because neither the operatives nor the activities they perform can be clearly defined. This study uses in-depth interviews to explore the behavioural nature of the informal workers in Ghana to understand how the operatives describe and perceive the sector, and to identify the factors that influence their drive to stay within the sector. This paper concludes that the operatives clearly distinguish between the formal and informal sectors and identify the characteristics and conditions that constitute the informal sector. Other workers are trapped between formality and informality. The findings also enumerate the push and pull factors contributing to the growth of the sector.
Abstract: Crop yield prediction is a paramount issue in
agriculture. The main idea of this paper is to find out efficient
way to predict the yield of corn based meteorological records.
The prediction models used in this paper can be classified into
model-driven approaches and data-driven approaches, according to
the different modeling methodologies. The model-driven approaches are based on crop mechanistic
modeling. They describe crop growth in interaction with their
environment as dynamical systems. But the calibration process of
the dynamic system comes up with much difficulty, because it
turns out to be a multidimensional non-convex optimization problem.
An original contribution of this paper is to propose a statistical
methodology, Multi-Scenarios Parameters Estimation (MSPE), for the
parametrization of potentially complex mechanistic models from a
new type of datasets (climatic data, final yield in many situations).
It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction
is free of the complex biophysical process. But it has some strict
requirements about the dataset.
A second contribution of the paper is the comparison of these
model-driven methods with classical data-driven methods. For this
purpose, we consider two classes of regression methods, methods
derived from linear regression (Ridge and Lasso Regression, Principal
Components Regression or Partial Least Squares Regression) and
machine learning methods (Random Forest, k-Nearest Neighbor,
Artificial Neural Network and SVM regression).
The dataset consists of 720 records of corn yield at county scale
provided by the United States Department of Agriculture (USDA) and
the associated climatic data. A 5-folds cross-validation process and
two accuracy metrics: root mean square error of prediction(RMSEP),
mean absolute error of prediction(MAEP) were used to evaluate the
crop prediction capacity.
The results show that among the data-driven approaches, Random
Forest is the most robust and generally achieves the best prediction
error (MAEP 4.27%). It also outperforms our model-driven approach
(MAEP 6.11%). However, the method to calibrate the mechanistic
model from dataset easy to access offers several side-perspectives.
The mechanistic model can potentially help to underline the stresses
suffered by the crop or to identify the biological parameters of interest
for breeding purposes. For this reason, an interesting perspective is
to combine these two types of approaches.
Abstract: The global concern about climate change has been increasing, since the emission of gases from human activities contributes to the greenhouse effect in the atmosphere, indicating significant impacts to the planet in the coming years. The study of precipitation regime is fundamental for the development of research in several areas. Among them are hydrology, agriculture, and electric sector. Using the climatic projections of the models belonging to the CMIP5, the main objective of the paper was to present an analysis of the impacts of climate change without rainfall in the Uruguay River basin. After an analysis of the results, it can be observed that for the future climate, there is a tendency, in relation to the present climate, for larger numbers of dry events, mainly in the winter months, changing the pluviometric regime for wet summers and drier winters. Given this projected framework, it is important to note the importance of adequate management of the existing water sources in the river basin, since the value of rainfall is reduced for the next years, it may compromise the dynamics of the ecosystems in the region. Facing climate change is fundamental issue for regions and cities all around the world. Society must improve its resilience to phenomenon impacts, and spreading the knowledge among decision makers and citizens is also essential. So, these research results can be subsidies for the decision-making in planning and management of mitigation measures and/or adaptation in south Brazil.
Abstract: In impedance spectroscopy (IS) the response of a photo-active device is analysed as a function of ac bias. It is widely applied in a broad class of material systems and devices. It gives access to fundamental mechanisms of operation of solar cells. We have implemented a method of IS where we modulate the light instead of the bias. This scheme allows us to analyze not only carrier dynamics but also impedance of device locally. Here, using this scheme, we have measured the frequency-dependent photocurrent response of the thin-film planar and nano-textured Si solar cells using this method. Photocurrent response is measured in range of 50 Hz to 50 kHz. Bode and Nyquist plots are used to determine characteristic lifetime of both the cells. Interestingly, the carrier lifetime of both planar and nano-textured solar cells depend on back and front contact positions. This is due to either heterogeneity of device or contacts are not optimized. The estimated average lifetime is found to be shorter for the nano-textured cell, which could be due to the influence of the textured interface on the carrier relaxation dynamics.
Abstract: Forced vibration problem of a delaminated beam made of fiber metal laminates is studied in this paper. Firstly, a delamination is considered to divide the beam into four sections. The classic beam theory is assumed to dominate each section. The layers on two sides of the delamination are constrained to have the same deflection. This hypothesis approves the conditions of compatibility as well. Consequently, dynamic response of the beam is obtained by the means of differential transform method (DTM). In order to verify the correctness of the results, a model is constructed using commercial software ABAQUS 6.14. A linear spring with constant stiffness takes the effect of contact between delaminated layers into account. The attained semi-analytical outcomes are in great agreement with finite element analysis.
Abstract: Delays in the construction industry are a global phenomenon. Many construction projects experience extensive delays exceeding the initially estimated completion time. The main purpose of this study is to identify construction projects typical behaviors in order to develop a prognosis and management tool. Being able to know a construction projects schedule tendency will enable evidence-based decision-making to allow resolutions to be made before delays occur. This study presents an innovative approach that uses Cluster Analysis Method to support predictions during Earned Value Analyses. A clustering analysis was used to predict future scheduling, Earned Value Management (EVM), and Earned Schedule (ES) principal Indexes behaviors in construction projects. The analysis was made using a database with 90 different construction projects. It was validated with additional data extracted from literature and with another 15 contrasting projects. For all projects, planned and executed schedules were collected and the EVM and ES principal indexes were calculated. A complete linkage classification method was used. In this way, the cluster analysis made considers that the distance (or similarity) between two clusters must be measured by its most disparate elements, i.e. that the distance is given by the maximum span among its components. Finally, through the use of EVM and ES Indexes and Tukey and Fisher Pairwise Comparisons, the statistical dissimilarity was verified and four clusters were obtained. It can be said that construction projects show an average delay of 35% of its planned completion time. Furthermore, four typical behaviors were found and for each of the obtained clusters, the interim milestones and the necessary rhythms of construction were identified. In general, detected typical behaviors are: (1) Projects that perform a 5% of work advance in the first two tenths and maintain a constant rhythm until completion (greater than 10% for each remaining tenth), being able to finish on the initially estimated time. (2) Projects that start with an adequate construction rate but suffer minor delays culminating with a total delay of almost 27% of the planned time. (3) Projects which start with a performance below the planned rate and end up with an average delay of 64%, and (4) projects that begin with a poor performance, suffer great delays and end up with an average delay of a 120% of the planned completion time. The obtained clusters compose a tool to identify the behavior of new construction projects by comparing their current work performance to the validated database, thus allowing the correction of initial estimations towards more accurate completion schedules.
Abstract: Studying DNA (deoxyribonucleic acid) sequence is useful in biological processes and it is applied in the fields such as diagnostic and forensic research. DNA is the hereditary information in human and almost all other organisms. It is passed to their generations. Earlier stage detection of defective DNA sequence may lead to many developments in the field of Bioinformatics. Nowadays various tedious techniques are used to identify defective DNA. The proposed work is to analyze and identify the cancer-causing DNA motif in a given sequence. Initially the human DNA sequence is separated as k-mers using k-mer separation rule. The separated k-mers are clustered using Self Organizing Map (SOM). Using Levenshtein distance measure, cancer associated DNA motif is identified from the k-mer clusters. Experimental results of this work indicate the presence or absence of cancer causing DNA motif. If the cancer associated DNA motif is found in DNA, it is declared as the cancer disease causing DNA sequence. Otherwise the input human DNA is declared as normal sequence. Finally, elapsed time is calculated for finding the presence of cancer causing DNA motif using clustering formation. It is compared with normal process of finding cancer causing DNA motif. Locating cancer associated motif is easier in cluster formation process than the other one. The proposed work will be an initiative aid for finding genetic disease related research.
Abstract: The purpose of the present research is to equate two
test forms as part of a study to evaluate the educational effectiveness
of the ARTé: Mecenas art history learning game. The researcher
applied Item Response Theory (IRT) procedures to calculate item,
test, and mean-sigma equating parameters. With the sample size
n=134, test parameters indicated “good” model fit but low Test
Information Functions and more acute than expected equating
parameters. Therefore, the researcher applied equipercentile equating
and linear equating to raw scores and compared the equated form
parameters and effect sizes from each method. Item scaling in IRT
enables the researcher to select a subset of well-discriminating items.
The mean-sigma step produces a mean-slope adjustment from the
anchor items, which was used to scale the score on the new form
(Form R) to the reference form (Form Q) scale. In equipercentile
equating, scores are adjusted to align the proportion of scores in each
quintile segment. Linear equating produces a mean-slope adjustment,
which was applied to all core items on the new form. The study
followed a quasi-experimental design with purposeful sampling of
students enrolled in a college level art history course (n=134) and
counterbalancing design to distribute both forms on the pre- and posttests.
The Experimental Group (n=82) was asked to play ARTé:
Mecenas online and complete Level 4 of the game within a two-week
period; 37 participants completed Level 4. Over the same period, the
Control Group (n=52) did not play the game. The researcher
examined between group differences from post-test scores on test
Form Q and Form R by full-factorial Two-Way ANOVA. The raw
score analysis indicated a 1.29% direct effect of form, which was
statistically non-significant but may be practically significant. The
researcher repeated the between group differences analysis with all
three equating methods. For the IRT mean-sigma adjusted scores,
form had a direct effect of 8.39%. Mean-sigma equating with a small
sample may have resulted in inaccurate equating parameters.
Equipercentile equating aligned test means and standard deviations,
but resultant skewness and kurtosis worsened compared to raw score
parameters. Form had a 3.18% direct effect. Linear equating
produced the lowest Form effect, approaching 0%. Using linearly
equated scores, the researcher conducted an ANCOVA to examine
the effect size in terms of prior knowledge. The between group effect
size for the Control Group versus Experimental Group participants
who completed the game was 14.39% with a 4.77% effect size
attributed to pre-test score. Playing and completing the game
increased art history knowledge, and individuals with low prior
knowledge tended to gain more from pre- to post test. Ultimately,
researchers should approach test equating based on their theoretical
stance on Classical Test Theory and IRT and the respective assumptions. Regardless of the approach or method, test equating
requires a representative sample of sufficient size. With small sample
sizes, the application of a range of equating approaches can expose
item and test features for review, inform interpretation, and identify
paths for improving instruments for future study.
Abstract: Jesus and Socrates shared a remarkable gift; a channel of inner spiritual communication, to afford them truthful guidance in their respective religious discourse. Jesus is part of the Trinity; he is the Son, the Son of God. In mortal life he is the son of a carpenter. He called on all peoples to repent of their sins but fell foul of the authorities and was crucified. Socrates was an ancient Greek philosopher and the son of an artisan. His mission is to drive the Athenians to investigate truth, but he too incurs the displeasure of fellow citizens, to the extent of execution. The accusations made against them centre around, in Jesus’ case, proclaiming himself the Son of God, with the means to pardon, and in Socrates’, that a daimonion, an inner voice, speaks to him in his heart. Jesus talks with God directly through prayer, as the pneuma of God, i.e. to pneuma to hagion, or Holy Spirit, is with him. Socrates seems to enter what we would now think of as a trance-like condition, wherein he communicates with his inner daimonion, who directs him to take courage on the righteous path.
Abstract: With recent trends in Big Data and advancements
in Information and Communication Technologies, the healthcare
industry is at the stage of its transition from clinician oriented to
technology oriented. Many people around the world die of cancer
because the diagnosis of disease was not done at an early stage.
Nowadays, the computational methods in the form of Machine
Learning (ML) are used to develop automated decision support
systems that can diagnose cancer with high confidence in a timely
manner. This paper aims to carry out the comparative evaluation
of a selected set of ML classifiers on two existing datasets: breast
cancer and cervical cancer. The ML classifiers compared in this study
are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest
Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and
Artificial Neural Networks (ANN). The evaluation is carried out based
on standard evaluation metrics Precision (P), Recall (R), F1-score and
Accuracy. The experimental results based on the evaluation metrics
show that ANN showed the highest-level accuracy (99.4%) when
tested with breast cancer dataset. On the other hand, when these
ML classifiers are tested with the cervical cancer dataset, Ensemble
(Bagged Tree) technique gave better accuracy (93.1%) in comparison
to other classifiers.
Abstract: Emotion dysregulation has been linked to psychopathology in general and, in particular, to substance abuse and other addiction-related disorders, such as eating disorders, impulsive disorder, and gambling. It has been proposed that a lessening of the difficulties in emotion regulation can have a significant positive impact on the treatment of these disorders. The present study explores the association between the progress in the Change & Grow® therapeutic model (5 stages of treatment), and the decrease in the difficulties related to emotion regulation. The Change & Grow® model has five stages of treatment according to the model’s five principles (Truth, Acceptance, Gratitude, Love and Responsibility) and incorporates different therapeutic approaches such as positive psychology, cognitive and behavioral therapy and third generation therapies. The main objective is to understand the impact of the presented therapeutic model on difficulties in emotion regulation in patients with addiction-related disorders. The exploratory study has a cross-sectional design. Participants were 44 (15 women and 29 men) Portuguese patients in the residential Villa Ramadas International Treatment Centre. The instrument used was the Portuguese version of the Difficulties in Emotion Regulation Scale (DERS), which measures six dimensions of emotion regulation (Strategies, Non-acceptance, Awareness, Impulse, Goals, and Clarity). The mean rank scores for both the DERS total score and the Impulse subscale showed statistically significant differences according to Stage of Treatment/Principles. Furthermore, Stage of Treatment/Principles held a negative correlation with the scores of the Non-acceptance and Impulse subscales, as well as the DERS total score. The results indicate that the Change & Grow® model seems to have an impact in lessening the patient’s difficulties in emotion regulation. The Impulse dimension suffered the greater impact, which supports the well-known relevance of impulse control, or related difficulties, in addiction-related disorders.