Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of periodontal health in patients taking atorvastatin

Introduction: Periodontal disease as a chronic inflammatory condition is more prevalent in adults. Considering the anti-inflammatory effect of statins and the need to find out the effects of these drugs on the prevention and treatment of periodontal diseases, this study was conducted to investigate the role of atorvastatin in periodontal health. Material & Methods: In this cross sectional study the effect of atorvastatin on plaque index, probing pocket depth (PPD), gingival index (GI) and bleeding on probing (BOP) index were examined. Patients with plaque index between 1 and 2 were included in the study, and those who had taken atorvastatin for at least 3 months were selected as the case group and those who had not taken atorvastatin were considered as the control group. Results: A total of 138 patients (50 patients for the atorvastatin group and 88 patients for the control group) were included. The mean probing pocket depth in the atorvastatin group was 2.03±0.35 mm and that in the control group was 2.8±0.31 mm (p=0.335). The mean bleeding index in the atorvastatin group was 0.20±0.14 and compared to the control group was 0.20±0.17 (p<0.001). The GI index in the atorvastatin group was 1.29±0.33, compared to the control group was 1.20±0.40 (p=0.218). Conclusion: The results of this study indicate the positive effect of the use of atorvastatin on reducing the bleeding on probing index in patients taking this drug. The probing pocket depth index and gingival index were not significantly different between the atorvastatin group and the group not taking this drug.
MAMMALIAN SPECIES RICHNESS IN AN ISOLATED FRAGMENT OF CERRADO

The Brazilian Savanna (Cerrado) is one of the most threatened biomes worldwide and is considered a “hotspot,” area with great endemism and less than 30% remaining natural vegetation, by Myers et al. (2000). According to Kronka (2005), among the 7,500 cerrado fragments in the state of São Paulo, 71% has less than 20 ha. Rodrigues & Bononi (2008) suggest that the remaining fragments with significant area should be permanently protected. Fragmentation plays an important role on species richness, especially on those one who require more resources or territory. If we focus on mammals, we notice the richness of species decreases in smaller fragments (Cáceres et al., 2010). In addition, habitat isolation disrupts species distribution patterns, with consequent effects on metapopulation dynamics and the genetic structure of the populations (Ewers & Didhan, 2005). Besides those, hunting and habitat changing are the biggest threatens to medium and large sized mammals (Costa et al. 2005; Trolle et al., 2007). As we can see, human influence causes a high pressure on natural areas.
INFLUENCE ON SPECTRAL AND IMAGE PREPROCESSING ON COFFEE BEAN VARIETY IDENTIFICATION USING HYPERSPECTRAL IMAGING

Hyperspectral imaging was used to identify and visualize coffee bean varieties. Spectral preprocessing of pixel-wise spectra by moving average smoothing with different smoothing points (7,11,15,19,23) and spatial preprocessing of the grey-scale image at each wavelength by median filter with different window size (3×3, 5×5, 7×7, 9×9, 11×11) were conducted. Average spectrum of each sample and the pixel-wise spectra were extracted. Optimal wavelengths were selected by principle component analysis (PCA). Support vector machine (SVM) models with full spectra and optimal wavelengths all obtained classification accuracy of prediction over 85%, respectively. The prediction of a hyperspectral image by applying the SVM models using the optimal wavelengths obtained poor performance with most pixels misclassified. Use of pixel-wise spectra preprocessed by moving average smoothing to build classification models would improve the performance of image prediction and overcome the influence of sample shape. The results indicated that the performances of the prediction images were affected by random noises, model performances and sample shape. The image preprocessing methods and visualization need to be greatly improved in future studies.
Mechanisms of Action of Andro

Andrographis paniculata isaherbaceous component isolated from Andrographis pa and thus prevent inflammatory diseases. A called atheromas or atheromatous plaque. emphasizing intimal cellular proliferation repeated formation and organization of preventing atherosclerosis from becoming by blocking the cytochrome c release from that result inthe suppression of endothelia peniculatawould be attributed to its antiIt was also shown that it has vaso guanylylcyclase to release nitric oxide dephosporylation of NF-kB subunit p65 S smooth muscle cells thus preventing end demonstrated that Andrographis paniculat by reducing de novo protein synthesis and focusing on the available literature whi paniculata as anti-atherosclerotic agent.
FLC control for tuning exploration phase in bio-inspired metaheuristic

Growing popularity of the Bat Algorithm has encouraged researchers to focus their work on its further improvements. Most work has been done within the area of hybridization of Bat Algorithm with other metaheuristics or local search methods. Unfortunately, most of these modifications not only improves the quality of obtained solutions, but also increases the number of control parameters that are needed to be set in order to obtain solutions of expected quality. This makes such solutions quite impractical. What more, there is no clear indication what these parameters do in term of a search process. In this paper authors are trying to incorporate Mamdani type Fuzzy Logic Controller (FLC) to tackle some of these mentioned shortcomings by using the FLC to control the exploration phase of a bio-inspired metaheuristic. FLC also allows us to incorporate expert knowledge about the problem at hand and define expected behaviors of system – here process of searching in multidimensional search space by modeling the process of bats hunting for their prey.
Physicochemical, Antioxidant and Sensorial Properties of Pasteurized Guava Nectar Incorporated with Pomegranate Peel and Guava Leaf Extracts

The aim of the present study was to evaluate the effect of pomegranate peel extract (PPE) and guava leaf extract (GLE) addition (0 “control”, 0.1, 0.2 and 0.3%) on physicochemical, antioxidant, microbiological and sensorial properties of pasteurized guava nectar during storage at room temperature (25±5°C) for 6 months. PPE and GLE exhibited high total phenolic contents with 129.04 and 92.21 mg/g, respectively and antioxidant activities with 91.15 and 87.34%, respectively. The results showed that adding PPE and GLE increased total soluble solids, titratable acidity and browning index of nectar samples. However, pH and color (L*, a* and b*) values were decreased. Furthermore, addition of PPE GLE significantly increased (compared to control) ascorbic acid (by 5.09 to 41.05%), total phenolic content (by 62.24 to 164.93%) and antioxidant activity (by 20.98 to 47.68%). All nectar samples were microbiologically safe (total bacterial, yeast and mold counts were less than 10 CFU/mL) and stable during storage. Sensory evaluation results revealed that the addition of PPE and GLE had no significant impact on all sensory properties. From the obtained results, it is concluded that the incorporation of guava nectar with PPE and GLE proved to be effective in the production of a safe nectar with better nutritional and sensorial qualities.
Deadline-Aware Multicast Transfers in Software-Defined Optical Wide-Area Networks

The increasing amount of data replication across datacenters introduces a need for efficient bulk data transfer protocols which provide certain guarantees, most notably timely transfer completion. We present <italic>DaRTree</italic> which leverages emerging optical reconfiguration technologies, to jointly optimize topology and multicast transfers in software-defined optical Wide-Area Networks (WANs), and thereby maximize throughput and acceptance ratio of transfer requests subject to transfer deadlines. <italic>DaRTree</italic> is based on a novel integer linear program relaxation and deterministic rounding scheme. To this end, <italic>DaRTree</italic> uses Steiner trees for forwarding and adaptive routing based on the current network load. <italic>DaRTree</italic> provides transfer completion guarantees without the need for rescheduling or preemption. Our evaluations show that <italic>DaRTree</italic> increases the network throughput and the number of accepted requests by up to <inline-formula> <tex-math notation="LaTeX">$1.7\times $ </tex-math></inline-formula>, especially for larger WANs. Moreover, <italic>DaRTree</italic> even outperforms state-of-the-art solutions when the traffic demands are only unicast transfers or when the WAN topology cannot be reconfigured. While <italic>DaRTree</italic> determines the rate and route to serve a request at the time of (online) admission control, we show that the acceptance ratio and throughput can be improved by up to <inline-formula> <tex-math notation="LaTeX">$1.3\times $ </tex-math></inline-formula> even further when <italic>DaRTree</italic> updates the rate and route of admitted transfers also at runtime.
Input image shifts for 3D deep learning-based segmentation of organs at risk on chest CT

In this work, we applied up to eight 3-dimensional positional shifts to a chest CT for organs segmentation by a 3D neural network and compared the added beneﬁt of combining those segmentations ( SI ) to the model results on the baseline image ( REF ) and to the combinations of as many results of the model on the same input image with diﬀerent neurons activation using only dropout ( DO ). With only one 7-voxel shift per dimension for any shift combination, signiﬁcant improvements in Dice and Hausdorﬀ distances were seen in SI over DO and REF for the lungs, spinal cord and heart segmentation when at least three to ﬁve images were combined, and all spatial dimensions represented in the shift combinations.
Abiotic stress in plants: Late Embryogenesis Abundant proteins

In order to improve our understanding on LEA proteins and their molecular functions in drought tolerance, the present work analyzes in the first place, the composition of LEA subproteomes from Arabidopsis seeds and maize embryos; second, three maize embryo LEA proteins from groups 1, 2, and 3 are analyzed in order to detect functional differences among them and finally, transgenic maize plants over-expressing group 5 “rab28” lea gene are characterized. The following results are presented: - Chapter 1. Proteomic approach to analyze the composition of LEA subproteomes from Arabidopsis seeds by mass spectrometry. The main objective was the development and isolation method to obtain enriched LEA populations from Arabidopsis seeds. LEA subproteomes were obtained using an extraction procedure that combines heat stability and acid solubility of LEA proteins. To identify the protein content, we followed two approaches: first, a classical 1D (SDSPAGE) gel-based procedure associated with MS analysis using an electrospray ionization source coupled on-line to liquid chromatography (LC-ESI-MSMS) and second, a gel-free protocol associated with an off-line HPLC and analysis via matrix assisted laser desorption/ionization (LC-MALDI-MSMS). - Chapter 2. Proteomic analysis of LEA proteins accumulated in maize mature seeds. Identification of LEA protein content by mass spectrometry and selection of three LEA proteins, Emb564, Rab17 and Mlg3, as representatives of groups 1, 2 and 3 for further study. Comparative functional analysis covering different aspects of maize Emb564, Rab17 and Mlg3 proteins, posttranslational modifications, subcellular localization and their properties in in-vitro and in- vivo assays. - Chapter 3. Characterization of transgenic maize plants expressing maize group 5 rab28 LEA gene under the ubiquitin promoter. Evaluation of Rab28 transcripts and protein levels, phenotype and stress tolerance traits of transgenic plants under drought stress. Investigation of the subcellular localization of transgenic and wild-type Rab28 protein using immunocytochemical approaches.
The Benefit of Using Web Quest in Teaching English as a Second language

: Background :The course suggested below is designed for a private language institute in Greece and it will, approximately, take 5 teaching hours to be completed. The institute is well equipped, has a modern computer lab with internet access and both the teachers and students are competent users of the internet and computer literate. Also the headmasters of the institute are open minded and willing to give students a variety of tools to assist them in their learning. The principal aim of the institute, is to produce competent, autonomous learners, that actively participate in their own development. Learners, therefore, are encouraged to experiment with ideas, try out different solutions to problems ,and be active learners and users of language. Moreover, the politics of the school also support that students should be actively involved with new technologies and the WWW, so as to develop their critical thinking skills, and thus assist them in succeeding in their exams and also, help learners improve their understanding of the complexities of modern life, enable them to grapple with new ethical and practical issues and thus become responsible and successful members in the society. Materials and Methods : The age of the learners in the class, ranges from 16-18 years old ,their language level is advanced and they are preparing for the CPE language examination. The CPE examination involves learners in writing opinion and critical essays , either on universal themes like smoking or pollution or on events that had universal effect or impact. Moreover their reading skills (skimming, scanning ) will be tested, as well as their ability to identify the author’s opinion in reading texts that appear neutral. Additionally, in the speaking section of the exam, students will be asked to express opinions, to think critically and examine an issue from various perspectives, challenge and
Near Optimal Adjacency Labeling Schemes for Power-Law Graphs

An adjacency labeling scheme labels the n nodes of a graph with bit strings in a way that allows, given the labels of two nodes, to determine adjacency based only on those bit strings. Though many graph families have been meticulously studied for this problem, a non-trivial labeling scheme for the important family of power-law graphs has yet to be obtained. This family is particularly useful for social and web networks as their underlying graphs are typically modelled as power-law graphs. Using simple strategies and a careful selection of a parameter, we show upper bounds for such labeling schemes of ~O(sqrt^{alpha}(n)) for power law graphs with coefficient alpha;, as well as nearly matching lower bounds. We also show two relaxations that allow for a label of logarithmic size, and extend the upper-bound technique to produce an improved distance labeling scheme for power-law graphs.
Some Relativistic and Gravitational Properties of the Wolfram Model

The Wolfram Model, which is a slight generalization of the model first introduced by Stephen Wolfram in A New Kind of Science (NKS), is a discrete spacetime formalism in which space is represented by a hypergraph whose dynamics are determined by abstract replacement operations on set systems, and in which the conformal structure of spacetime is represented by a causal graph. The purpose of this article is to present rigorous mathematical derivations of many key properties of such models in the continuum limit, as first discussed in NKS, including the fact that large classes of them obey discrete forms of both special and general relativity. First, we prove that causal invariance (namely, the requirement that all causal graphs be isomorphic, irrespective of the choice of hypergraph updating order) is equivalent to a discrete version of general covariance, with changes to the updating order corresponding to discrete gauge transformations. This fact then allows one to deduce a discrete analog of Lorentz covariance, and the resultant physical consequences of discrete Lorentz transformations. We also introduce discrete notions of Riemann and Ricci curvature for hypergraphs, and prove that the correction factor for the volume of a discrete spacetime cone in a causal graph corresponding to curved spacetime of fixed dimensionality is proportional to a timelike projection of the discrete spacetime Ricci tensor, subsequently using this fact (along with the assumption that the updating rules preserve the dimensionality of the causal graph in limiting cases) to prove that the most general set of constraints on the discrete spacetime Ricci tensor corresponds to a discrete form of the Einstein field equations.
Recurrent neural networks in the context of SQL attacks

In the paper we present a new approach based on application of neural networks to detect SQLattacks. SQL attacks are those attacks that take advantage of using SQL statements to beperformed. The problem of detection of this class of attacks is transformed to time seriesprediction problem. SQL queries are used as a source of events in a protected environment. Todifferentiate between normal SQL queries and those sent by an attacker, we divide SQL statementsinto tokens and pass them to our detection system, which predicts the next token, taking intoaccount previously seen tokens. In the learning phase tokens are passed to recurrent neuralnetwork (RNN) trained by backpropagation through time (BPTT) algorithm. Teaching data areshifted by one token forward in time with relation to input. The purpose of the testing phase is topredict the next token in the sequence. All experiments were conducted on Jordan and Elmannetworks using data gathered from PHP Nuke portal. The experimental results show that theJordan network outperforms the Elman network predicting correctly queries of the length up toten.
Environment and Complexity of Organizations Œ Emergence: Complexity and Organization

December 31, 2001 · Emergence Leonid Rybakov Rybakov L. Environment and Complexity of Organizations. Emergence: Complexity and Organization. 2001 Dec 31 [last modified: 2016 Nov 21]. Edition 1. doi: 10.emerg/10.17357. afead99adb24518903ba336f63aa25de. Interaction among and unification of people are the very agents that create an organization. An organization can only exist if it exchanges individuals, information, or material resources with the environment permanently surrounding it. Many organizational scientists have recognized that the environment plays a significant but not absolute role in the origin and evolution of organizations (see, e.g., Lawrence & Lorsch, 1967; Meyer & Scott, 1983; Pfeffer & Salanick, 1978). Although every organization continually feels the influence of the environment, it can preserve integrity (invariability of behavior) through four natural operators:
Semantic-Head-Driven Generation

We present an algorithm for generating strings from logical form encodings that improves upon previous algorithms in that it places fewer restrictions on the class of grammars to which it is applicable. In particular, unlike a previous bottom-up generator, it allows use of semantically nonmonotonic grammars, yet unlike top-down methods, it also permits left-recursion. The enabling design feature of the algorithm is its implicit traversal of the analysis tree for the string being generated in a semantic-head-driven fashion.
Genetic Algorithms, Problem Difficulty, and the Modality of Fitness Landscapes

We generally assume that the modality (i.e., number of local optima) of a tness landscape is related to the diiculty of nding the best point on that landscape by evolutionary computation (e.g., hillclimbers and genetic algorithms (GAs)). This thesis rst examines the limits of modality by constructing a unimodal function and a maximally multimodal function. At such extremes our intuition breaks down. A tness landscape consisting entirely of a single hill leading to the global optimum proves to be harder for hillclimbers than for GA crossover. A provably maximally multimodal function, in which half the points in the search space are local optima, can be easier than the unimodal, single hill problem for both hillclimbers and GAs. Exploring the more realistic intermediate range between the extremes of modality, local optima are constructed with varying degrees of \attraction" to evolutionary algorithms. To construct such optima, it is necessary rst to deene attraction for an algorithm. Most work on optima and their basins of attraction has focused on hills and hillclimbers, while some research has explored attraction for the GA's crossover operator. This thesis extends some of the latter results by deening and implementing maximal partial deception in problems with k arbitrarily placed global optima. This allows the creation of functions, such as the minimum distance function f mdG , with k isolated global optima and multiple local optima attractive to both crossover and hillclimbers. This function appears to be a powerful new tool for generalizing deception and relating hillclimbers (and Hamming space) to GAs and crossover. Experiments using variations on f mdG demonstrate four quasi-separable dimensions of GA problem diiculty: multimodality, solution isolation and signal, and misleadingness (deception). Finally, this thesis addresses the appropriateness of Sewall Wright's tness landscape to the study of evolutionary computation, demonstrating that the metaphor can help us understand and predict the performance of our algorithms, including both hillclimbers and recombinative GAs. iii For Gabriele, who cared as much about this thesis as I did. iv Acknowledgments First I must thank my thesis advisor, David E. Goldberg. In addition to his expertise, oversight , and encouragement, he also contributed the original, inspired ideas of exponentially long hillclimbing paths, bipolar deception, and massive multimodality. I also thank my coworkers and coauthors on much of the long path problem and multimodal deception eeorts: David E. Goldberg and Kalyanmoy Deb. I am grateful for the reviews, comments, and suggestions of …
Behavioral Finance Biases in Investment Decision Making

Traditional finance suggests that investments made by rational behaviors investors examine risk and return before decision making to gain maximum profit later behavioral finance challenge traditional finance and introduce psychological factors affect decision making. The aim of this research paper is to explore how behavioral biases affect investment decision making under uncertainty. Dependent variable investment decision making is a composite activity, it never be made in a vacuity by depending on personal resources. Based on this study investment choices alternatives influence by human rational and irrational behavior, therefore, examine the impact of behavioral finance in the decision-making process. Behavioral finance phenomenon variables; heuristic, prospects, personality characteristics, feeling, moods and ecological factors explore under this research. Overconfidence, Representativeness, Anchoring, Regret Aversion, Hindsight, Herding Effect and Home Bias included in investors psychology behaviors. Survey questionnaire tool used to collect sample to conduct quantitative research. To test the hypothesis Regression analysis run by the SPS software. Findings revealed that there was an effect of behavioral biases on investment decisions. Empirical results concluded investment decision making influenced by heuristic behaviors more than prospects and personality characteristics. The originality of this study, it is very beneficial for investors and financial institutions to make decision by observation of psychological factors.