Search results for: attenuation index.

Authors: Cristian Păuna

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In the first decades of the 21st century, in the electronic trading environment, algorithmic capital investments became the primary tool to make a profit by speculations in financial markets. A significant number of traders, private or institutional investors are participating in the capital markets every day using automated algorithms. The autonomous trading software is today a considerable part in the business intelligence system of any modern financial activity. The trading decisions and orders are made automatically by computers using different mathematical models. This paper will present one of these models called Price Prediction Line. A mathematical algorithm will be revealed to build a reliable trend line, which is the base for limit conditions and automated investment signals, the core for a computerized investment system. The paper will guide how to apply these tools to generate entry and exit investment signals, limit conditions to build a mathematical filter for the investment opportunities, and the methodology to integrate all of these in automated investment software. The paper will also present trading results obtained for the leading German financial market index with the presented methods to analyze and to compare different automated investment algorithms. It was found that a specific mathematical algorithm can be optimized and integrated into an automated trading system with good and sustained results for the leading German Market. Investment results will be compared in order to qualify the presented model. In conclusion, a 1:6.12 risk was obtained to reward ratio applying the trigonometric method to the DAX Deutscher Aktienindex on 24 months investment. These results are superior to those obtained with other similar models as this paper reveal. The general idea sustained by this paper is that the Price Prediction Line model presented is a reliable capital investment methodology that can be successfully applied to build an automated investment system with excellent results.

Keywords: Algorithmic trading, automated investment system, DAX Deutscher Aktienindex.

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Authors: P. V. Pramila, V. Mahesh

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Pulmonary Function Tests are important non-invasive diagnostic tests to assess respiratory impairments and provides quantifiable measures of lung function. Spirometry is the most frequently used measure of lung function and plays an essential role in the diagnosis and management of pulmonary diseases. However, the test requires considerable patient effort and cooperation, markedly related to the age of patients resulting in incomplete data sets. This paper presents, a nonlinear model built using Multivariate adaptive regression splines and Random forest regression model to predict the missing spirometric features. Random forest based feature selection is used to enhance both the generalization capability and the model interpretability. In the present study, flow-volume data are recorded for N= 198 subjects. The ranked order of feature importance index calculated by the random forests model shows that the spirometric features FVC, FEF25, PEF, FEF25-75, FEF50 and the demographic parameter height are the important descriptors. A comparison of performance assessment of both models prove that, the prediction ability of MARS with the `top two ranked features namely the FVC and FEF25 is higher, yielding a model fit of R2= 0.96 and R2= 0.99 for normal and abnormal subjects. The Root Mean Square Error analysis of the RF model and the MARS model also shows that the latter is capable of predicting the missing values of FEV1 with a notably lower error value of 0.0191 (normal subjects) and 0.0106 (abnormal subjects) with the aforementioned input features. It is concluded that combining feature selection with a prediction model provides a minimum subset of predominant features to train the model, as well as yielding better prediction performance. This analysis can assist clinicians with a intelligence support system in the medical diagnosis and improvement of clinical care.

Keywords: FEV1, Multivariate Adaptive Regression Splines Pulmonary Function Test, Random Forest.

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Authors: Tuba Tekin, Nurcan Baglam, Emine Dincer

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This study aimed to examine the effects of nutrition education received by university students on sustainable healthy eating behaviors and adherence to the Mediterranean diet. The 2nd, 3rd, and 4th-grade university students studying at the Faculty of Health Sciences, Nutrition and Dietetics, Midwifery, Nursing, Physical Therapy, and Rehabilitation departments of universities in Turkey were included in the study. Students' adherence to the Mediterranean diet was evaluated using the Mediterranean Diet Adherence Scale, and their sustainable and healthy eating behaviors were evaluated using the Sustainable and Healthy Eating Behaviors Scale. In addition, the body weight and height of the students were measured by the researchers, and the Body Mass Index (BMI) value was calculated. A total of 181 students, 85 of whom were studying in the Department of Nutrition and Dietetics and 96 of whom were educated in other departments, were included in the study; 75.7% of the students in the sample are female, while 24.3% are male. The average body weight of the students was 61.17 ± 10.87 kg, and the average BMI was 22.04 ± 3.40 kg/m2. While the mean score of the Mediterranean Diet Adherence Scale was 6.72 ± 1.84, in the evaluation of adherence to the Mediterranean diet, it was determined that 25.4% of the students had poor adherence and 66.9% needed improvement. When the adherence scores of students who received and did not receive nutrition education were compared, it was discovered that the students who received nutrition education had a higher score (p < 0.05). Students who received nutrition education had a higher total score on the Sustainable and Healthy Eating Behaviors scale (p < 0.05). A moderately positive correlation was found between the Sustainable and Healthy Eating Behaviors scale total score and the Mediterranean Diet Adherence scores (p < 0.05). As a result of the linear regression analysis, it was revealed that a 1-unit increase in the Mediterranean diet adherence score would result in a 1.3-point increase in the total score of the Sustainable and Healthy Eating Behaviors scale. Sustainable and healthy diets are important for improving and developing health and the prevention of diseases. The Mediterranean diet is defined as a sustainable diet model. The findings revealed the relationship between the Mediterranean diet and sustainable nutrition and showed that nutrition education increased knowledge and awareness about sustainable nutrition and increased adherence to the Mediterranean diet. For this reason, courses or seminars on sustainable nutrition can be organized during educational periods.

Keywords: Healthy eating, Mediterranean diet, nutrition education, sustainable nutrition.

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Authors: M. Alizadeh, M. Mahdavi, M.H. Jouri

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The rangelands, as one of the largest dynamic biomes in the world, have very capabilities. Regulation of greenhouse gases in the Earth's atmosphere, particularly carbon dioxide as the main these gases, is one of these cases. The attention to rangeland, as cheep and reachable resources to sequestrate the carbon dioxide, increases after the Industrial Revolution. Rangelands comprise the large parts of Iran as a steppic area. Rudshur (Saveh), as area index of steppic area, was selected under three sites include long-term exclosure, medium-term exclosure, and grazable area in order to the capable of carbon dioxide’s sequestration of dominated species. Canopy cover’s percentage of two dominated species (Artemisia sieberi Besser & Stipa barbata Desf) was determined via establishing of random 1 square meter plot. The sampling of above and below ground biomass style was obtained by complete random. After determination of ash percentage in the laboratory; conversion ratio of plant biomass to organic carbon was calculated by ignition method. Results of the paired t-test showed that the amount of carbon sequestration in above ground and underground biomass of Artemisia sieberi Besser & Stipa barbata Desf is different in three regions. It, of course, hasn’t any difference between under and surface ground’s biomass of Artemisia sieberi Besser in long-term exclosure. The independent t-test results indicate differences between underground biomass corresponding each other in the studied sites. Carbon sequestration in the Stipa barbata Desf was totally more than Artemisia sieberi Besser. Altogether, the average sequestration of the long-term exclosure was 5.842gr/m², the medium-term exclosure was 4.115gr/m², and grazable area was 5.975gr/m² so that there isn’t valuable statistical difference in term of total amount of carbon sequestration to three sites.

Keywords: Carbon sequestration, the Industrial Revolution, greenhouse gases, Artemisia sieberi Besser, Stipa barbata Desf, steppic rangelands

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Authors: Maad Kamal Al-Anni

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This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Keywords: Mobile ad hoc network, MANET, intrusion detection system, back propagation algorithm, neural networks, traffic table, multilayer perceptron, feed-forward back-propagation, network simulator 2.

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Authors: G. Disciglio, G. Gatta, F. Lops, A. Libutti, A. Tarantino, E. Tarantino

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The experimental trial was carried out in open field at Foggia district (Apulia Region, Southern Italy), during the spring-summer season 2014, in order to evaluate the effect of four biostimulant products (RadiconÒ, Viormon plusÒ, LysodinÒ and SiaptonÒ 10L), compared with a control (no biostimulant), on the infestation of processing tomato crop (cv Dres) by the chlorophyll-lacking root parasite Phelipanche ramosa. Biostimulants consist in different categories of products (microbial inoculants, humic and fulvic acids, hydrolyzed proteins and aminoacids, seaweed extracts) which play various roles in plant growing, including the improvement of crop resistance and quali-quantitative characteristics of yield. The experimental trial was arranged according to a complete randomized block design with five treatments, each of one replicated three times. The processing tomato seedlings were transplanted on 5 May 2014. Throughout the crop cycle, P. ramosa infestation was assessed according to the number of emerged shoots (branched plants) counted in each plot, at 66, 78 and 92 day after transplanting. The tomato fruits were harvested at full-stage of maturity on 8 August 2014. From each plot, the marketable yield was measured and the quali-quantitative yield parameters (mean weight, dry matter content, colour coordinate, colour index and soluble solids content of the fruits) were determined. The whole dataset was tested according to the basic assumptions for the analysis of variance (ANOVA) and the differences between the means were determined using Tukey’s tests at the 5% probability level. The results of the study showed that none of the applied biostimulants provided a whole control of Phelipanche, although some positive effects were obtained from their application. To this respect, the RadiconÒ appeared to be the most effective in reducing the infestation of this root-parasite in tomato crop. This treatment also gave the higher tomato yield.

Keywords: Biostimulants, control methods, Phelipanche ramosa, processing tomato crop.

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Authors: Emmanuel Dele Balogun

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This paper analyzes, using descriptive statistics and econometrics data which span the period 1981 to 2014 to gauge the effects of trade policy incentives on economic growth in Nigeria. It argues that the provided incentives penalize economic growth during pre-trade liberalization eras, but stimulated a rapid increase in total factor productivity during the post-liberalization period of 2000 to 2014. The trend analysis shows that Nigeria maintained high tariff walls in economic regulation eras which became low in post liberalization era. The protections were in favor of infant industries, which were mainly appendages of multinationals but against imports of competing food and finished consumer products. The trade openness index confirms the undue exposure of Nigeria’s economy to the vagaries of international market shocks; while banking sector recapitalization and new listing of telecommunications companies deepened the financial markets in post-liberalization era. The structure of economic incentives was biased in favor of construction, trade and services, but against the real sector despite protectionist policies. Total Factor Productivity (TFP) estimates show that the Nigerian economy suffered stagnation in pre-liberalization eras, but experienced rapid growth rates in post-liberalization eras. The regression results relating trade policy incentives to TFP growth rate yielded a significant but negative intercept suggesting that a non-interventionist policy could be detrimental to economic progress, while protective tariff which limits imports of competing products could spur productivity gains in domestic import substitutes beyond factor growth with market liberalization. The main constraint to the effectiveness of trade policy incentives is the failure of benefiting industries to leverage on the domestic factor endowments of the nation. This paper concludes that there is the need to review the current economic transformation strategies urgently with a view to provide policymakers with a better understanding of the most viable options that could make for rapid success.

Keywords: Trade Policies, macroeconomic incentives, total factor productivity and economic growth.

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Authors: Michely Vargas Delpupo, José Geraldo Romanello Bueno

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The right to basic sanitation, was elevated to the category of fundamental right by the Constitution of 1988 to protect the ecologically balanced environment, ensuring social rights to health and adequate housing and put the dignity of the human person as the foundation of the Brazilian Democratic State. Before their essentiality to humans, this article seeks to understand why universal access to basic sanitation is a goal so difficult to achieve in Brazil. Therefore, this research uses the deductive and analytical method. Given the nature of the research literature, research techniques were centered in specialized books on the subject, journals, theses and dissertations, laws, relevant law case and raising social indicators relating to the theme. The relevance of the topic stems, among other things, the fact that sanitation services are essential for a dignified life, i.e., everyone is entitled to the maintenance of the necessary existence conditions are satisfied. However, the effectiveness of this right is undermined in society, since Brazil has huge deficit in sanitation services, denying thus a worthy life to most of the population. Thus, it can be seen that the provision of water and sewage services in Brazil is still characterized by a large imbalance, since the municipalities with lower population index have greater disability in the sanitation service. The truth is that the precariousness of water and sewage services in Brazil is still very concentrated in the North and Northeast regions, limiting the effective implementation of the Law 11.445/2007 in the country. Therefore, there is urgent need for a positive service by the State in the provision of sanitation services in order to prevent and control disease, improve quality of life and productivity of individuals, besides preventing contamination of water resources. More than just social and economic necessity, there is a government duty to implement such services. In this sense, given the current scenario, to achieve universal access to basic sanitation imposes many hurdles. These are mainly in the field of properly formulated and implemented public policies, i.e., it requires an excellent institutional organization, management services, strategic planning, social control, in order to provide answers to complex challenges.

Keywords: Fundamental rights, sanitation, universal access.

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Authors: Mustafa M. Donma, Orkide Donma

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Obesity is defined as a severe chronic disease characterized by a low-grade inflammatory state. Therefore, inflammatory markers gained utmost importance during the evaluation of obesity and metabolic syndrome (MetS), a disease characterized by central obesity, elevated blood pressure, increased fasting blood glucose and elevated triglycerides or reduced high density lipoprotein cholesterol (HDL-C) values. Some inflammatory markers based upon complete blood cell count (CBC) are available. In this study, it was questioned which inflammatory marker was the best to evaluate the differences between various obesity groups. 514 pediatric individuals were recruited. 132 children with MetS, 155 morbid obese (MO), 90 obese (OB), 38 overweight (OW) and 99 children with normal BMI (N-BMI) were included into the scope of this study. Obesity groups were constituted using age- and sex-dependent body mass index (BMI) percentiles tabulated by World Health Organization. MetS components were determined to be able to specify children with MetS. CBC were determined using automated hematology analyzer. HDL-C analysis was performed. Using CBC parameters and HDL-C values, ratio markers of inflammation, which cover neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (dNLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), monocyte-to-HDL-C ratio (MHR) were calculated. Statistical analyses were performed. The statistical significance degree was considered as p < 0.05. There was no statistically significant difference among the groups in terms of platelet count, neutrophil count, lymphocyte count, monocyte count, and NLR. PLR differed significantly between OW and N-BMI as well as MetS. Monocyte-to HDL-C value exhibited statistical significance between MetS and N-BMI, OB, and MO groups. HDL-C value differed between MetS and N-BMI, OW, OB, MO groups. MHR was the ratio, which exhibits the best performance among the other CBC-based inflammatory markers. On the other hand, when MHR was compared to HDL-C only, it was suggested that HDL-C has given much more valuable information. Therefore, this parameter still keeps its value from the diagnostic point of view. Our results suggest that MHR can be an inflammatory marker during the evaluation of pediatric MetS, but the predictive value of this parameter was not superior to HDL-C during the evaluation of obesity.

Keywords: Children, complete blood cell count, high density lipoprotein cholesterol, metabolic syndrome, obesity.

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Authors: Samart Homthong, Wutthipong Moungnoi

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Critical success factors (CSFs) and the criteria to measure project success have received much attention over the decades and are among the most widely researched topics in the context of project management. However, although there have been extensive studies on the subject by different researchers, to date, there has been little agreement on the CSFs. The aim of this study is to identify the CSFs that influence the performance of construction projects, and determine their relative importance for different objectives across five stages in the project life cycle. A considerable literature review was conducted that resulted in the identification of 179 individual factors. These factors were then grouped into nine major categories. A questionnaire survey was used to collect data from three groups of respondents: client representatives, consultants, and contractors. Out of 164 questionnaires distributed, 93 were returned, yielding a response rate of 56.7%. Using the mean score, relative importance index, and weighted average method, the top 10 critical factors for each category were identified. The agreement of survey respondents on those categorised factors were analysed using Spearman’s rank correlation. A one-way analysis of variance was then performed to determine whether the mean scores among the various groups of respondents were statistically significant. The findings indicate the most CSFs in each category in procurement phase are: proper procurement programming of materials (time), stability in the price of materials (cost), and determining quality in the construction (quality). They are then followed by safety equipment acquisition and maintenance (health and safety), budgeting allowed in a contractual arrangement for implementing environmental management activities (environment), completeness of drawing documents (productivity), accurate measurement and pricing of bill of quantities (risk management), adequate communication among the project team (human resource), and adequate cost control measures (client satisfaction). An understanding of CSFs would help all interested parties in the construction industry to improve project performance. Furthermore, the results of this study would help construction professionals and practitioners take proactive measures for effective project management.

Keywords: Critical success factors, procurement phase, project life cycle, project performance.

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Authors: Krassimir Todorov

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The purpose of the paper is to redefine the levels of structure of corporate, business and functional strategies that were established over the past several decades, to a conceptual model, consisting of corporate, business and operations strategies, that are reinforced by functional strategies. We will propose a conceptual framework of different perspectives in the role of strategic operations as a separate strategic place and reposition the remaining functional strategies as supporting tools, existing at all three levels. The proposed model is called ‘the strategic engine’, since the mutual relationships of its ingredients are identical with main elements and working principle of the internal combustion engine. Based on theoretical essence, related to every strategic level, we will prove that the strategic engine model is useful for managers seeking to safeguard the competitive advantage of their companies. Each strategy level is researched through its basic elements. At the corporate level we examine the scope of firm’s product, the vertical and geographical coverage. At the business level, the point of interest is limited to the SWOT analysis’ basic elements. While at operations level, the key research issue relates to the scope of the following performance indicators: cost, quality, speed, flexibility and dependability. In this relationship, the paper provides a different view for the role of operations strategy within the overall strategy concept. We will prove that the theoretical essence of operations goes far beyond the scope of traditionally accepted business functions. Exploring the applications of Resource-based theory and Market-based theory within the strategic levels framework, we will prove that there is a logical consequence of the theoretical impact in corporate, business and operations strategy – at every strategic level, the validity of one theory is substituted to the level of the other. Practical application of the conceptual model is tested in automotive industry. Actually, the proposed theoretical concept is inspired by a leading global automotive group – Inchcape PLC, listed on the London Stock Exchange, and constituent of the FTSE 250 Index.

Keywords: Business strategy, corporate strategy, functional strategies, operations strategy.

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Authors: Ilaha Rzayeva, Emin Alasgarov, Orkhan Karim-Zada

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This study attempts to consider the linkage between management and computer sciences in order to develop the software named “IntelSymb” as a demo application to prove data analysis of non-energy^* fields’ diversification, which will positively influence on energy dependency mitigation of countries. Afterward, we analyzed 18 years of economic fields of development (5 sectors) of 13 countries by identifying which patterns mostly prevailed and which can be dominant in the near future. To make our analysis solid and plausible, as a future work, we suggest developing a gateway or interface, which will be connected to all available on-line data bases (WB, UN, OECD, U.S. EIA) for countries’ analysis by fields. Sample data consists of energy (TPES and energy import indicators) and non-energy industries’ (Main Science and Technology Indicator, Internet user index, and Sales and Production indicators) statistics from 13 OECD countries over 18 years (1995-2012). Our results show that the diversification of non-energy industries can have a positive effect on energy sector dependency (energy consumption and import dependence on crude oil) deceleration. These results can provide empirical and practical support for energy and non-energy industries diversification’ policies, such as the promoting of Information and Communication Technologies (ICTs), services and innovative technologies efficiency and management, in other OECD and non-OECD member states with similar energy utilization patterns and policies. Industries, including the ICT sector, generate around 4 percent of total GHG, but this is much higher — around 14 percent — if indirect energy use is included. The ICT sector itself (excluding the broadcasting sector) contributes approximately 2 percent of global GHG emissions, at just under 1 gigatonne of carbon dioxide equivalent (GtCO2eq). Ergo, this can be a good example and lesson for countries which are dependent and independent on energy, and mainly emerging oil-based economies, as well as to motivate non-energy industries diversification in order to be ready to energy crisis and to be able to face any economic crisis as well.

Keywords: Energy policy, energy diversification, “IntelSymb” software, renewable energy.

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Authors: M. A. Putera, N. Yasufuku, A. Alowaisy, R. Ishikura, J. G. Hussary, A. Rifa’i

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Indonesia’s government has planned a project for a high-speed railway connecting the capital cities, Jakarta and Surabaya, about 700 km. Based on that location, it has been planning construction above the lowland soil region. The lowland soil region comprises cohesive soil with high water content and high compressibility index, which in fact, led to a settlement problem. Among the variety of railway track structures, the adoption of the ballastless track was used effectively to reduce the settlement; it provided a lightweight structure and minimized workspace. Contradictorily, deploying this thin layer structure above the lowland area was compensated with several problems, such as lack of bearing capacity and deflection behavior during traffic loading. It is necessary to combine with ground improvement to assure a settlement behavior on the clayey soil. Reflecting on the assurance of strength increment and working period, those were convinced by adopting methods such as cement-treated soil as the substructure of railway track. Particularly, evaluating mechanical properties in the field has been well known by using the plate load test and cone penetration test. However, observing an increment of mechanical properties has uncertainty, especially for evaluating cement-treated soil on the substructure. The current quality control of cement-treated soils was established by laboratory tests. Moreover, using small strain devices measurement in the laboratory can predict more reliable results that are identical to field measurement tests. Aims of this research are to show an intercorrelation of confining pressure with the initial condition of the Young’s modulus (E0), Poisson ratio (υ0) and Shear modulus (G0) within small strain ranges. Furthermore, discrepancies between those parameters were also investigated. Experimental result confirmed the intercorrelation between cement content and confining pressure with a power function. In addition, higher cement ratios have discrepancies, conversely with low mixing ratios.

Keywords: Cement content, confining pressure, high-speed railway, small strain ranges.

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Authors: Cheima Ben Soltane, Ittansa Yonas Kelbesa

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Speaker Identification (SI) is the task of establishing identity of an individual based on his/her voice characteristics. The SI task is typically achieved by two-stage signal processing: training and testing. The training process calculates speaker specific feature parameters from the speech and generates speaker models accordingly. In the testing phase, speech samples from unknown speakers are compared with the models and classified. Even though performance of speaker identification systems has improved due to recent advances in speech processing techniques, there is still need of improvement. In this paper, a Closed-Set Tex-Independent Speaker Identification System (CISI) based on a Multiple Classifier System (MCS) is proposed, using Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction and suitable combination of vector quantization (VQ) and Gaussian Mixture Model (GMM) together with Expectation Maximization algorithm (EM) for speaker modeling. The use of Voice Activity Detector (VAD) with a hybrid approach based on Short Time Energy (STE) and Statistical Modeling of Background Noise in the pre-processing step of the feature extraction yields a better and more robust automatic speaker identification system. Also investigation of Linde-Buzo-Gray (LBG) clustering algorithm for initialization of GMM, for estimating the underlying parameters, in the EM step improved the convergence rate and systems performance. It also uses relative index as confidence measures in case of contradiction in identification process by GMM and VQ as well. Simulation results carried out on voxforge.org speech database using MATLAB highlight the efficacy of the proposed method compared to earlier work.

Keywords: Feature Extraction, Speaker Modeling, Feature Matching, Mel Frequency Cepstrum Coefficient (MFCC), Gaussian mixture model (GMM), Vector Quantization (VQ), Linde-Buzo-Gray (LBG), Expectation Maximization (EM), pre-processing, Voice Activity Detection (VAD), Short Time Energy (STE), Background Noise Statistical Modeling, Closed-Set Tex-Independent Speaker Identification System (CISI).

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Authors: W. V. W. H. Wickramaarachchi, S. Walpalage, S. M. Egodage

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Thermoplastic elastomer (TPE) is a multifunctional polymeric material which possesses a combination of excellent properties of parent materials. Basically, TPE has a rubber phase and a thermoplastic phase which gives processability as thermoplastics. When the rubber phase is partially or fully crosslinked in the thermoplastic matrix, TPE is called as thermoplastic elastomer vulcanizate (TPV). If the rubber phase is non-crosslinked, it is called as thermoplastic elastomer olefin (TPO). Nowadays TPEs are introduced into the commercial market with different products. However, the application of TPE as a roofing material is limited. Out of the commercially available roofing products from different materials, only single ply roofing membranes and plastic roofing sheets are produced from rubbers and plastics. Natural rubber (NR) and high density polyethylene (HDPE) are used in various industrial applications individually with some drawbacks. Therefore, this study was focused to develop both TPO and TPV blends from NR and HDPE at different compositions and then to identify the best blend composition to use as a roofing material. A series of blends by varying NR loading from 10 wt% to 50 wt%, at 10 wt% intervals, were prepared using a twin screw extruder. Dicumyl peroxide was used as a crosslinker for TPV. The standard properties for a roofing material like tensile properties tear strength, hardness, impact strength, water absorption, swell/gel analysis and thermal characteristics of the blends were investigated. Change of tensile strength after exposing to UV radiation was also studied. Tensile strength, hardness, tear strength, melting temperature and gel content of TPVs show higher values compared to TPOs at every loading studied, while water absorption and swelling index show lower values, suggesting TPVs are more suitable than TPOs for roofing applications. Most of the optimum properties were shown at 10/90 (NR/HDPE) composition. However, high impact strength and gel content were shown at 20/80 (NR/HDPE) composition. Impact strength, as being an energy absorbing property, is the most important for a roofing material in order to resist impact loads. Therefore, 20/80 (NR/HDPE) is identified as the best blend composition. UV resistance and other properties required for a roofing material could be achieved by incorporating suitable additives to TPVs.

Keywords: Thermoplastic elastomer, natural rubber, high density polyethylene, roofing material.

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Authors: Oqba Basal, András Szabó

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Legume crops are able to fix atmospheric nitrogen by the symbiotic relation with specific bacteria, which allows the use of the mineral nitrogen-fertilizer to be reduced, or even excluded, resulting in more profit for the farmers and less pollution for the environment. Soybean (Glycine max (L.) Merrill) is one of the most important legumes with its high content of both protein and oil. However, it is recommended to combine the two nitrogen sources under stress conditions in order to overcome its negative effects. Drought stress is one of the most important abiotic stresses that increasingly limits soybean yields. A precise rate of mineral nitrogen under drought conditions is not confirmed, as it depends on many factors; soybean yield-potential and soil-nitrogen content to name a few. An experiment was conducted during 2017 growing season in Debrecen, Hungary to investigate the effects of nitrogen source on the physiology and the yield of the soybean cultivar 'Boglár'. Three N-fertilizer rates including no N-fertilizer (0 N), 35 kg ha^-1 of N-fertilizer (35 N) and 105 kg ha^-1 of N-fertilizer (105 N) were applied under three different irrigation regimes; severe drought stress (SD), moderate drought stress (MD) and control with no drought stress (ND). Half of the seeds in each treatment were pre-inoculated with Bradyrhizobium japonicum inoculant. The overall results showed significant differences associated with fertilization and irrigation, but not with inoculation. Increasing N rate was mostly accompanied with increased chlorophyll content and leaf area index, whereas it positively affected the plant height only when the drought was waived off. Plant height was the lowest under severe drought, regardless of inoculation and N-fertilizer application and rate. Inoculation increased the yield when there was no drought, and a low rate of N-fertilizer increased the yield furthermore; however, the high rate of N-fertilizer decreased the yield to a level even less than the inoculated control. On the other hand, the yield of non-inoculated plants increased as the N-fertilizer rate increased. Under drought conditions, adding N-fertilizer increased the yield of the non-inoculated plants compared to their inoculated counterparts; moreover, the high rate of N-fertilizer resulted in the best yield. Regardless of inoculation, the mean yield of the three fertilization rates was better when the water amount increased. It was concluded that applying N-fertilizer to provide the nitrogen needed by soybean plants, with the absence of N₂-fixation process, is very important. Moreover, adding relatively high rate of N-fertilizer is very important under severe drought stress to alleviate the drought negative effects. Further research to recommend the best N-fertilizer rate to inoculated soybean under drought stress conditions should be executed.

Keywords: Drought stress, inoculation, N-fertilizer, soybean physiology, yield.

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Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

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Speaker recognition is performed in high Additive White Gaussian Noise (AWGN) environments using principals of Computational Auditory Scene Analysis (CASA). CASA methods often classify sounds from images in the time-frequency (T-F) plane using spectrograms or cochleargrams as the image. In this paper atomic decomposition implemented by matching pursuit performs a transform from time series speech signals to the T-F plane. The atomic decomposition creates a sparsely populated T-F vector in “weight space” where each populated T-F position contains an amplitude weight. The weight space vector along with the atomic dictionary represents a denoised, compressed version of the original signal. The arraignment or of the atomic indices in the T-F vector are used for classification. Unsupervised feature learning implemented by a sparse autoencoder learns a single dictionary of basis features from a collection of envelope samples from all speakers. The approach is demonstrated using pairs of speakers from the TIMIT data set. Pairs of speakers are selected randomly from a single district. Each speak has 10 sentences. Two are used for training and 8 for testing. Atomic index probabilities are created for each training sentence and also for each test sentence. Classification is performed by finding the lowest Euclidean distance between then probabilities from the training sentences and the test sentences. Training is done at a 30dB Signal-to-Noise Ratio (SNR). Testing is performed at SNR’s of 0 dB, 5 dB, 10 dB and 30dB. The algorithm has a baseline classification accuracy of ~93% averaged over 10 pairs of speakers from the TIMIT data set. The baseline accuracy is attributable to short sequences of training and test data as well as the overall simplicity of the classification algorithm. The accuracy is not affected by AWGN and produces ~93% accuracy at 0dB SNR.

Keywords: Time-frequency plane, atomic decomposition, envelope sampling, Gabor atoms, matching pursuit, sparse dictionary learning, sparse autoencoder.

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Authors: A. Atli, K. Candelier, J. Alteyrac

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Environmental and sustainability concerns push the industries to manufacture alternative materials having less environmental impact. The Wood Plastic Composites (WPCs) produced by blending the biopolymers and natural fillers permit not only to tailor the desired properties of materials but also are the solution to meet the environmental and sustainability requirements. This work presents the elaboration and characterization of the fully green WPCs prepared by blending a biopolymer, BIOPLAST® GS 2189 and spruce sawdust used as filler with different amounts. Since both components are bio-based, the resulting material is entirely environmentally friendly. The mechanical, thermal, structural properties of these WPCs were characterized by different analytical methods like tensile, flexural and impact tests, Thermogravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC) and X-ray Diffraction (XRD). Their water absorption properties and resistance to the termite and fungal attacks were determined in relation with different wood filler content. The tensile and flexural moduli of WPCs increased with increasing amount of wood fillers into the biopolymer, but WPCs became more brittle compared to the neat polymer. Incorporation of spruce sawdust modified the thermal properties of polymer: The degradation, cold crystallization, and melting temperatures shifted to higher temperatures when spruce sawdust was added into polymer. The termite, fungal and water absorption resistance of WPCs decreased with increasing wood amount in WPCs, but remained in durability class 1 (durable) concerning fungal resistance and quoted 1 (attempted attack) in visual rating regarding to the termites resistance except that the WPC with the highest wood content (30 wt%) rated 2 (slight attack) indicating a long term durability. All the results showed the possibility to elaborate the easy injectable composite materials with adjustable properties by incorporation of BIOPLAST® GS 2189 and spruce sawdust. Therefore, lightweight WPCs allow both to recycle wood industry byproducts and to produce a full ecologic material.

Keywords: Biodegradability, durability, mechanical properties, melt flow index, spectrophotometry, structural properties, thermal properties, wood-plastic composites.

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Authors: Brennan Lodge

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Amidst a complex regulatory landscape, Retrieval Augmented Generation (RAG) emerges as a transformative tool for Governance Risk and Compliance (GRC) officers. This paper details the application of RAG in synthesizing Large Language Models (LLMs) with external knowledge bases, offering GRC professionals an advanced means to adapt to rapid changes in compliance requirements. While the development for standalone LLMs is exciting, such models do have their downsides. LLMs cannot easily expand or revise their memory, and they cannot straightforwardly provide insight into their predictions, and may produce “hallucinations.” Leveraging a pre-trained seq2seq transformer and a dense vector index of domain-specific data, this approach integrates real-time data retrieval into the generative process, enabling gap analysis and the dynamic generation of compliance and risk management content. We delve into the mechanics of RAG, focusing on its dual structure that pairs parametric knowledge contained within the transformer model with non-parametric data extracted from an updatable corpus. This hybrid model enhances decision-making through context-rich insights, drawing from the most current and relevant information, thereby enabling GRC officers to maintain a proactive compliance stance. Our methodology aligns with the latest advances in neural network fine-tuning, providing a granular, token-level application of retrieved information to inform and generate compliance narratives. By employing RAG, we exhibit a scalable solution that can adapt to novel regulatory challenges and cybersecurity threats, offering GRC officers a robust, predictive tool that augments their expertise. The granular application of RAG’s dual structure not only improves compliance and risk management protocols but also informs the development of compliance narratives with pinpoint accuracy. It underscores AI’s emerging role in strategic risk mitigation and proactive policy formation, positioning GRC officers to anticipate and navigate the complexities of regulatory evolution confidently.

Keywords: Retrieval Augmented Generation, Governance Risk and Compliance, Cybersecurity, AI-driven Compliance, Risk Management, Generative AI.

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Authors: Wan-Ting Liao, Angela K. Tzeng

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Empathy has been an important issue in psychology, education, as well as cognitive neuroscience. Empathy has two major components: cognitive and emotional. Cognitive component refers to the ability to understand others’ perspectives, thoughts, and actions, whereas emotional component refers to understand how others feel. Empathy can be induced, attitude can then be changed, and with enough attitude change, helping behavior can occur. This finding leads us to two questions: is attitude change really necessary for prosocial behavior? And, what roles cognitive and affective empathy play? For the second question, participants with different psychopathic personality (PP) traits are critical because high PP people were found to suffer only affective empathy deficit. Their cognitive empathy shows no significant difference from the control group. 132 college students voluntarily participated in the current three-stage study. Stage 1 was to collect basic information including Interpersonal Reactivity Index (IRI), Psychopathic Personality Inventory-Revised (PPI-R), Attitude Scale, Visual Analogue Scale (VAS), and demographic data. Stage two was for empathy induction with three controversial scenarios, namely domestic violence, depression with a suicide attempt, and an ex-offender. Participants read all three stories and then rewrite the stories by one of two perspectives (empathetic vs. objective). They would then complete the VAS and Attitude Scale one more time for their post-attitude and emotional status. Three IVs were introduced for data analysis: PP (High vs. Low), Responsibility (whether or not the character is responsible for what happened), and Perspective-taking (Empathic vs. Objective). Stage 3 was for the action. Participants were instructed to freely use the 17 tokens they received as donations. They were debriefed and interviewed at the end of the experiment. The major findings were people with higher empathy tend to take more action in helping. Attitude change is not necessary for prosocial behavior. The controversy of the scenarios and how familiar participants are towards target groups play very important roles. Finally, people with high PP tend to show more public prosocial behavior due to their affective empathy deficit. Pre-existing value and belief as well as recent dramatic social events seem to have a big impact and possibly reduce the effect of the independent variables (IV) in our paradigm.

Keywords: Affective empathy, attitude, cognitive empathy, prosocial behavior, psychopathic traits.

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Authors: Abdullah Alnutayfat, Alexander Sutin, Dong Liu

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Wind turbine has become one of the most popular energy production methods. However, failure of blades and maintenance costs evolve into significant issues in the wind power industry, so it is essential to detect the initial blade defects to avoid the collapse of the blades and structure. This paper aims to apply modulation of high-frequency blade vibrations by low-frequency blade rotation, which is close to the known Vibro-Acoustic Modulation (VAM) method. The high-frequency wideband blade vibration is produced by the interaction of the surface blades with the environment air turbulence, and the low-frequency modulation is produced by alternating bending stress due to gravity. The low-frequency load of rotational wind turbine blades ranges between 0.2-0.4 Hz and can reach up to 2 Hz for strong wind. The main difference between this study and previous ones on VAM methods is the use of a wideband vibration signal from the blade's natural vibrations. Different features of the VAM are considered using a simple model of breathing crack. This model considers the simple mechanical oscillator, where the parameters of the oscillator are varied due to low-frequency blade rotation. During the blade's operation, the internal stress caused by the weight of the blade modifies the crack's elasticity and damping. The laboratory experiment using steel samples demonstrates the possibility of VAM using a probe wideband noise signal. A cycle load with a small amplitude was used as a pump wave to damage the tested sample, and a small transducer generated a wideband probe wave. The received signal demodulation was conducted using the Detecting of Envelope Modulation on Noise (DEMON) approach. In addition, the experimental results were compared with the modulation index (MI) technique regarding the harmonic pump wave. The wideband and traditional VAM methods demonstrated similar sensitivity for earlier detection of invisible cracks. Importantly, employing a wideband probe signal with the DEMON approach speeds up and simplifies testing since it eliminates the need to conduct tests repeatedly for various harmonic probe frequencies and to adjust the probe frequency.

Keywords: Damage detection, turbine blades, Vibro-Acoustic Structural Health Monitoring, SHM, Detecting of Envelope Modulation on Noise.

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Authors: Mustafa M. Donma, Orkide Donma

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Zinc (Zn) is a vital element required for growth and development particularly in children. It exhibits some protective effects against cardiovascular diseases (CVDs). Zn may be a potential biomarker of cardiovascular health. High sensitive cardiac troponin T (hs-cTnT) and cardiac myosin binding protein C (cMyBP-C) are new generation markers used for prediagnosis, diagnosis and prognosis of CVDs. The aim of this study is to determine Zn as well as new generation cardiac markers’ profiles in children with normal body mass index (N-BMI), obese (OB), morbid obese (MO) children and children with metabolic syndrome (MetS) findings. The association among them will also be investigated. Four study groups were constituted. The study protocol was approved by the institutional Ethics Committee of Tekirdag Namik Kemal University. Parents of the participants filled informed consent forms to participate in the study. Group 1 is composed of 44 children with N-BMI. Group 2 and Group 3 comprised 43 OB and 45 MO children, respectively. 45 MO children with MetS findings were included in Group 4. World Health Organization age- and sex-adjusted BMI percentile tables were used to constitute groups. These values were 15-85, 95-99 and above 99 for N-BMI, OB and MO, respectively. Criteria for MetS findings were determined. Routine biochemical analyses including Zn were performed. hs-cTnT and cMyBP-C concentrations were measured by enzyme-linked immunosorbent assay. Data were analyzed by using SPSS software. p < 0.05 was accepted as significant. Four groups were matched for age and gender. Decreased Zn concentrations were measured in Groups 2, 3 and 4 compared to Group 1. Groups did not differ from one another in terms of hs-cTnT. There were statistically significant differences between cMyBP-C levels of MetS group and N-BMI as well as OB groups. There was an increasing trend going from N-BMI group to MetS group. There were statistically significant negative correlations between Zn and hs-cTnT as well as cMyBP-C concentrations in MetS group. In conclusion, inverse correlations detected between Zn and new generation cardiac markers (hs-TnT and cMyBP-C) have pointed out that decreased levels of Zn accompany increased levels of hs-cTnT as well as cMyBP-C in children with MetS. This finding emphasizes that both Zn and these new generation cardiac markers may be evaluated as biomarkers of cardiovascular health during severe childhood obesity precipitated with MetS findings and also suggested as the messengers of the future risk in the adulthood periods of children with MetS.

Keywords: Cardiac myosin binding protein-C, cardiovascular diseases, children, high sensitive cardiac troponin T, obesity.

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Authors: U. K. Hulihalli, Shantveerayya

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Buckwheat (Fagopyrum esculentum Moench) is an annual crop belongs to family Poligonaceae. The cultivated buckwheat species are notable for their exceptional nutritive values. It is an important source of carbohydrates, fibre, macro, and microelements such as K, Ca, Mg, Na and Mn, Zn, Se, and Cu. It also contains rutin, flavonoids, riboflavin, pyridoxine and many amino acids which have beneficial effects on human health, including lowering both blood lipid and sugar levels. Rutin, quercetin and some other polyphenols are potent carcinogens against colon and other cancers. Buckwheat has significant nutritive value and plenty of uses. Cultivation of buckwheat in Sothern part of India is very meager. Hence, a study was planned with an objective to know the performance of buckwheat genotypes to different planting geometries and fertility levels. The field experiment was conducted at Main Agriculture Research Station, University of Agriculture Sciences, Dharwad, India, during 2017 Kharif. The experiment was laid-out in split-plot design with three replications having three planting geometries as main plots, two genotypes as sub plots and three fertility levels as sub-sub plot treatments. The soil of the experimental site was vertisol. The standard procedures are followed to record the observations. The planting geometry of 30*10 cm was recorded significantly higher seed yield (893 kg/ha⁻¹), stover yield (1507 kg ha⁻¹), clusters plant⁻¹ (7.4), seeds clusters⁻¹ (7.9) and 1000 seed weight (26.1 g) as compared to 40*10 cm and 20*10 cm planting geometries. Between the genotypes, significantly higher seed yield (943 kg ha⁻¹) and harvest index (45.1) was observed with genotype IC-79147 as compared to PRB-1 genotype (687 kg ha⁻¹ and 34.2, respectively). However, the genotype PRB-1 recorded significantly higher stover yield (1344 kg ha⁻¹) as compared to genotype IC-79147 (1173 kg ha⁻¹). The genotype IC-79147 was recorded significantly higher clusters plant⁻¹ (7.1), seeds clusters⁻¹ (7.9) and 1000 seed weight (24.5 g) as compared PRB-1 (5.4, 5.8 and 22.3 g, respectively). Among the fertility levels tried, the fertility level of 60:30 NP kg ha⁻¹ recorded significantly higher seed yield (845 kg ha^-1) and stover yield (1359 kg ha⁻¹) as compared to 40:20 NP kg ha^-1 (808 and 1259 kg ha⁻¹ respectively) and 20:10 NP kg ha^-1 (793 and 1144 kg ha⁻¹ respectively). Within the treatment combinations, IC 79147 genotype having 30*10 cm planting geometry with 60:30 NP kg ha⁻¹ recorded significantly higher seed yield (1070 kg ha⁻¹), clusters plant⁻¹ (10.3), seeds clusters⁻¹ (9.9) and 1000 seed weight (27.3 g) compared to other treatment combinations.

Keywords: Buckwheat, fertility levels, genotypes, geometry, polyphenols, rutin.

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Authors: A. Taqaddas

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Purpose: Planning and dosimetry of different VMAT algorithms (SmartArc, Ergo++, Autobeam) is compared with IMRT for Head and Neck Cancer patients. Modelling was performed to rule out the causes of discrepancies between planned and delivered dose. Methods: Five HNC patients previously treated with IMRT were re-planned with SmartArc (SA), Ergo++ and Autobeam. Plans were compared with each other and against IMRT and evaluated using DVHs for PTVs and OARs, delivery time, monitor units (MU) and dosimetric accuracy. Modelling of control point (CP) spacing, Leaf-end Separation and MLC/Aperture shape was performed to rule out causes of discrepancies between planned and delivered doses. Additionally estimated arc delivery times, overall plan generation times and effect of CP spacing and number of arcs on plan generation times were recorded. Results: Single arc SmartArc plans (SA4d) were generally better than IMRT and double arc plans (SA2Arcs) in terms of homogeneity and target coverage. Double arc plans seemed to have a positive role in achieving improved Conformity Index (CI) and better sparing of some Organs at Risk (OARs) compared to Step and Shoot IMRT (ss-IMRT) and SA4d. Overall Ergo++ plans achieved best CI for both PTVs. Dosimetric validation of all VMAT plans without modelling was found to be lower than ss-IMRT. Total MUs required for delivery were on average 19%, 30%, 10.6% and 6.5% lower than ss-IMRT for SA4d, SA2d (Single arc with 2⁰ Gantry Spacing), SA2Arcs and Autobeam plans respectively. Autobeam was most efficient in terms of actual treatment delivery times whereas Ergo++ plans took longest to deliver. Conclusion: Overall SA single arc plans on average achieved best target coverage and homogeneity for both PTVs. SA2Arc plans showed improved CI and some OARs sparing. Very good dosimetric results were achieved with modelling. Ergo++ plans achieved best CI. Autobeam resulted in fastest treatment delivery times.

Keywords: Dosimetry, Intensity Modulated Radiotherapy, Optimization Algorithms, Volumetric Modulated Arc Therapy.

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Authors: Cherry Dhiman, Ayushi Paliwal, Mohd. Shahid Khan, M. N. Reddy, Vinay Gupta, Monika Tomar

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The laser based high resolution spectroscopic experimental techniques such as Laser Induced Breakdown Spectroscopy (LIBS), Rotating Disk Electrode Optical Emission spectroscopy (RDE-OES) and Surface Plasmon Resonance (SPR) have been used for the study of composition and degradation analysis of used engine oils. Engine oils are mainly composed of aliphatic and aromatics compounds and its soot contains hazardous components in the form of fine, coarse and ultrafine particles consisting of wear metal elements. Such coarse particulates matter (PM) and toxic elements are extremely dangerous for human health that can cause respiratory and genetic disorder in humans. The combustible soot from thermal power plants, industry, aircrafts, ships and vehicles can lead to the environmental and climate destabilization. It contributes towards global pollution for land, water, air and global warming for environment. The detection of such toxicants in the form of elemental analysis is a very serious issue for the waste material management of various organic, inorganic hydrocarbons and radioactive waste elements. In view of such important points, the current study on used engine oils was performed. The fundamental characterization of engine oils was conducted by measuring water content and kinematic viscosity test that proves the crude analysis of the degradation of used engine oils samples. The microscopic quantitative and qualitative analysis was presented by RDE-OES technique which confirms the presence of elemental impurities of Pb, Al, Cu, Si, Fe, Cr, Na and Ba lines for used waste engine oil samples in few ppm. The presence of such elemental impurities was confirmed by LIBS spectral analysis at various transition levels of atomic line. The recorded transition line of Pb confirms the maximum degradation which was found in used engine oil sample no. 3 and 4. Apart from the basic tests, the calculations for dielectric constants and refractive index of the engine oils were performed via SPR analysis.

Keywords: Laser induced breakdown spectroscopy, rotating disk electrode optical emission spectroscopy, surface plasmon resonance, ICCD spectrometer, Nd:YAG laser, engine oil.

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Authors: Ayelet Gur

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Background: In recent years we are witnessing a welcome trend in which more children/persons with disabilities are living at home with their families and within their communities. This trend is related to various policy innovations as the UN Convention on the Rights of People with Disabilities that reflect a shift from the medical-institutional model to a human rights approach. We also witness the emergence of family centered approaches that perceive the family and not just the individual with the disability as a worthy target of policy planning, implementation and evaluation efforts. The current investigation aims to explore economic, psychological and social factors among households of families of children or adults with intellectual disabilities in Israel and to present policy recommendation. Methods: A national sample of 301 households was recruited through the education and employment settings of persons with intellectual disability. The main caregiver of the person with the disability (a parent) was interviewed. Measurements included the income and expense surveys; assets and debts questionnaire; the questionnaire on resources and stress; the social involvement questionnaire and Personal Wellbeing Index. Results: Findings indicate significant gaps in financial circumstances between households of families of children with intellectual disabilities and households of the general Israeli society. Households of families of children with intellectual disabilities report lower income and higher expenditures and loans than the general society. They experience difficulties in saving and coping with unexpected expenses. Caregivers (the parents) experience high stress, low social participation, low financial support from family, friend and non-governmental organizations and decreased well-being. They are highly dependent on social security allowances which constituted 40% of the household's income. Conclusions: Households' dependency on social security allowances may seem contradictory to the encouragement of persons with intellectual disabilities to favor independent living in light of the human rights approach to disability. New policy should aim at reducing caregivers' stress and enhance their social participation and support, with special emphasis on families of lower socio-economic status. Finally, there is a need to continue monitoring the economic and psycho-social needs of households of families of children with intellectual disabilities and other developmental disabilities.

Keywords: Disability policy, family policy, intellectual and developmental disabilities, Israel, households study, parents of children with disabilities.

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Authors: S. Jamshidi, E. Feizi Ashtiani, M. Ardestani

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Waste Load Allocation (WLA) strategies usually intend to find economic policies for water resource management. Water quality trading (WQT) is an approach that uses discharge permit market to reduce total environmental protection costs. This primarily requires assigning discharge limits known as total maximum daily loads (TMDLs). These are determined by monitoring organizations with respect to the receiving water quality and remediation capabilities. The purpose of this study is to compare two approaches of TMDL assignment for WQT policy in small catchment area of Haraz River, in north of Iran. At first, TMDLs are assigned uniformly for the whole point sources to keep the concentrations of BOD and dissolved oxygen (DO) at the standard level at checkpoint (terminus point). This was simply simulated and controlled by Qual2kw software. In the second scenario, TMDLs are assigned using multi objective particle swarm optimization (MOPSO) method in which the environmental violation at river basin and total treatment costs are minimized simultaneously. In both scenarios, the equity index and the WLA based on trading discharge permits (TDP) are calculated. The comparative results showed that using economically optimized TMDLs (2nd scenario) has slightly more cost savings rather than uniform TMDL approach (1st scenario). The former annually costs about 1 M$ while the latter is 1.15 M$. WQT can decrease these annual costs to 0.9 and 1.1 M$, respectively. In other word, these approaches may save 35 and 45% economically in comparison with command and control policy. It means that using multi objective decision support systems (DSS) may find more economical WLA, however its outcome is not necessarily significant in comparison with uniform TMDLs. This may be due to the similar impact factors of dischargers in small catchments. Conversely, using uniform TMDLs for WQT brings more equity that makes stakeholders not feel that much envious of difference between TMDL and WQT allocation. In addition, for this case, determination of TMDLs uniformly would be much easier for monitoring. Consequently, uniform TMDL for TDP market is recommended as a sustainable approach. However, economical TMDLs can be used for larger watersheds.

Keywords: Waste load allocation (WLA), Water quality trading (WQT), Total maximum daily loads (TMDLs), Haraz River, Multi objective particle swarm optimization (MOPSO), Equity.

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Authors: Orkide Donma, Mustafa M. Donma

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Obesity is associated with increased fat mass as well as fat percentage. Minerals are the elements, which are of vital importance. In this study, the relationships between body as well as bone mineral profile and the percentage as well as mass values of fat, fat-free portion, protein, skeletal muscle were evaluated in adult men with normal body mass index (N-BMI), and those classified according to different stages of obesity. A total of 103 adult men classified into five groups participated in this study. Ages were within 19-79 years range. Groups were N-BMI (Group 1), overweight (OW) (Group 2), first level of obesity (FLO) (Group 3), second level of obesity (SLO) (Group 4) and third level of obesity (TLO) (Group 5). Anthropometric measurements were performed. BMI values were calculated. Obesity degree, total body fat mass, fat percentage, basal metabolic rate (BMR), visceral adiposity, body mineral mass, body mineral percentage, bone mineral mass, bone mineral percentage, fat-free mass, fat-free percentage, protein mass, protein percentage, skeletal muscle mass and skeletal muscle percentage were determined by TANITA body composition monitor using bioelectrical impedance analysis technology. Statistical package (SPSS) for Windows Version 16.0 was used for statistical evaluations. The values below 0.05 were accepted as statistically significant. All the groups were matched based upon age (p > 0.05). BMI values were calculated as 22.6 ± 1.7 kg/m², 27.1 ± 1.4 kg/m², 32.0 ± 1.2 kg/m², 37.2 ± 1.8 kg/m², and 47.1 ± 6.1 kg/m² for groups 1, 2, 3, 4, and 5, respectively. Visceral adiposity and BMR values were also within an increasing trend. Percentage values of mineral, protein, fat-free portion and skeletal muscle masses were decreasing going from normal to TLO. Upon evaluation of the percentages of protein, fat-free portion and skeletal muscle, statistically significant differences were noted between NW and OW as well as OW and FLO (p < 0.05). However, such differences were not observed for body and bone mineral percentages. Correlation existed between visceral adiposity and BMI was stronger than that detected between visceral adiposity and obesity degree. Correlation between visceral adiposity and BMR was significant at the 0.05 level. Visceral adiposity was not correlated with body mineral mass but correlated with bone mineral mass whereas significant negative correlations were observed with percentages of these parameters (p < 0.001). BMR was not correlated with body mineral percentage whereas a negative correlation was found between BMR and bone mineral percentage (p < 0.01). It is interesting to note that mineral percentages of both body as well as bone are highly affected by the visceral adiposity. Bone mineral percentage was also associated with BMR. From these findings, it is plausible to state that minerals are highly associated with the critical stages of obesity as prominent parameters.

Keywords: Bone, men, minerals, obesity.

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Authors: Nahla Al-Bayyari, Rae’d Hailat

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Vitamin D deficiency and overweight are common in women suffering from polycystic ovary syndrome (PCOS). Weight gain in PCOS is an important factor for the development of menstrual dysfunction and signs of hyperandrogenism and alopecia. Features of PCOS such as oligomenorrhea can be predicted by anthropometric measurements as body mass index (BMI). Therefore, the aim of this trial was to study the effect of 50,000 IU/week of vitamin D₃ supplementation on the body composition and on the anthropometric measurements of overweight women with PCOS and to examine the impact of this effect on ovaries ultrasonography and menstrual cycle regularity. The study design was a prospective randomized, double-blinded placebo-controlled clinical trial conducted on 60 overweight Jordanian women aged (18-49) years with PCOS and vitamin D deficiency. The study participants were divided into two groups; vitamin D group (n = 30) who were assigned to receive 50,000 IU/week of vitamin D₃ and placebo group (n = 30) who were assigned to receive placebo tablets orally for 90 days. The anthropometric measurements and body composition were measured at baseline and after treatment for the PCOS and vitamin D deficient women. Also, assessment of the participants’ picture of ovaries by ultrasound and menstrual cycle regulatory were performed before and after treatment. Results showed that there were no significant (p > 0.05) differences between the placebo and vitamin D group basal 25(OH)D levels, body composition and anthropometric parameters. After treatment, vitamin D group serum levels of 25(OH)D increased (12.5 ± 0.61 to 50.2 ± 2.04 ng/mL, (p < 0.001), and decreased (50.2 ± 2.04 to 48.2 ± 2.03 ng/mL, p < 0.001) after 14 days of vitamin D₃ treatment cessation. There were no significant changes in the placebo group. In the vitamin D group, there were significant (p < 0.001) decreases in body weight, BMI, waist, and hip circumferences and fat mass. In addition, there were significant increases (p < 0.05) in fat free mass and total body water. These improvements in both anthropometric and body composition as well as in 25(OH)D concentrations, resulted in significant improvements in the picture of PCOS women ovaries ultrasonography and in menstrual cycle regularity, where nearly most of them (93%) had regular cycles after vitamin D₃ supplementation. In the placebo group, there were only significant decreases (p < 0.05) in waist and hip circumferences. It can be concluded that vitamin D supplementation improving serum 25(OH)D levels and PCOS prognosis by reducing body weight of overweight PCOS women and regulating their menstrual cycle.

Keywords: Anthropometric, overweight, polycystic ovary syndrome, vitamin D3.

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Authors: G. Candel, D. Naccache

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t-SNE is an embedding method that the data science community has widely used. It helps two main tasks: to display results by coloring items according to the item class or feature value; and for forensic, giving a first overview of the dataset distribution. Two interesting characteristics of t-SNE are the structure preservation property and the answer to the crowding problem, where all neighbors in high dimensional space cannot be represented correctly in low dimensional space. t-SNE preserves the local neighborhood, and similar items are nicely spaced by adjusting to the local density. These two characteristics produce a meaningful representation, where the cluster area is proportional to its size in number, and relationships between clusters are materialized by closeness on the embedding. This algorithm is non-parametric. The transformation from a high to low dimensional space is described but not learned. Two initializations of the algorithm would lead to two different embedding. In a forensic approach, analysts would like to compare two or more datasets using their embedding. A naive approach would be to embed all datasets together. However, this process is costly as the complexity of t-SNE is quadratic, and would be infeasible for too many datasets. Another approach would be to learn a parametric model over an embedding built with a subset of data. While this approach is highly scalable, points could be mapped at the same exact position, making them indistinguishable. This type of model would be unable to adapt to new outliers nor concept drift. This paper presents a methodology to reuse an embedding to create a new one, where cluster positions are preserved. The optimization process minimizes two costs, one relative to the embedding shape and the second relative to the support embedding’ match. The embedding with the support process can be repeated more than once, with the newly obtained embedding. The successive embedding can be used to study the impact of one variable over the dataset distribution or monitor changes over time. This method has the same complexity as t-SNE per embedding, and memory requirements are only doubled. For a dataset of n elements sorted and split into k subsets, the total embedding complexity would be reduced from O(n2) to O(n2/k), and the memory requirement from n2 to 2(n/k)2 which enables computation on recent laptops. The method showed promising results on a real-world dataset, allowing to observe the birth, evolution and death of clusters. The proposed approach facilitates identifying significant trends and changes, which empowers the monitoring high dimensional datasets’ dynamics.

Keywords: Concept drift, data visualization, dimension reduction, embedding, monitoring, reusability, t-SNE, unsupervised learning.

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